ANTIBIOTIC RESISTANCE OF COLIFORM BACTERIA IN

THE RIETSPRUIT RIVER

GRACE NKECHINYERE IJOMA

207053456

Dissertation submitted in fulfilment of the requirements for the degree of

Magister Technologiae: Biotechnology

Department of Biosciences

Faculty of Applied and Computer Sciences

Vaal University of Technology

Vanderbijlpark

Supervisor: Mrs. CS van Wyk

Co-Supervisor: Dr. HA Esterhuysen

September 2010

ii

DECLARATION

I declare that this dissertation is my own work. It is submitted for the degree of Magister

Technologiae Biotechnology, in the Department of Biosciences at the Vaal University of

Technology, Vanderbijlpark. It has not been submitted before for any degree and is not being

concurrently submitted in candidature for any degree.

Ijoma Grace Nkechinyere

September 2010

iii

DEDICATION

To the memory of my father

Isaac Chijioke Ijomah

1943 - 2003

iv

ACKNOWLEDGEMENTS

I am greatly indebted to my supervisor, Mrs C. S. Van Wyk, the Principal Lecturer in

Biotechnology in the Department of Biosciences, Vaal University of Technology for her

encouragement and guidance during the course of this research.

My sincere thanks also go to:

Mr. George Dewing, the Plant Manager, Emfuleni, Waste Water Works, Sebokeng for your kind

assistance during sample collection;

Mrs. Laurette D. Marais, Biotechnology Research Laboratory, Vaal University of Technology

for your assistance during sample collection and laboratory analyses;

Victor, my first son and my partner Wale Adeyanju for their unflinching support during the

course of this research; and

To Sami, my son and Samira Ollanma, my daughter and little princess who was born during the

course of this research, I acknowledge the many weekends you had to spend alone without me.

Thank you.

v

TABLE OF CONTENTS

Declaration ii

Dedication iii

Acknowledgements iv

Table of contents v

List of tables viii

Abstract ix

Chapter 1 Introduction 1

Chapter 2 Literature Review 4

2.1 Introduction to Literature Review 4

2.2 Characteristics that qualify antibiotics as chemotherapeutic agents 4

2.3 Bacterial susceptibility to antibiotics 5

2.4 Antibiotics and their mode of action 5

2.4.1 Inhibition of cell wall synthesis 8

2.4.2 Damage to the cytoplasmic membrane 8

2.4.3 Inhibition of protein synthesis 9

2.4.4 Inhibition of nucleic acid synthesis 10

2.4.5 Inhibition of specific enzyme systems in metabolic pathways 10

2.5 Uses of antibiotics 11

2.5.1 Chemotherapeutic uses 11

2.5.2 Clinical uses as research tool 12

2.5.3 Veterinary uses 12

2.5.4 Food preservative uses 13

2.6 Adverse reactions to antibiotic use 14

2.7 Bacterial resistance to antibiotics 14

vi

2.7.1 Introduction to Bacterial resistance to antibiotics 14

2.7.2 Causes of antibiotic resistance 15

2.8 Genetic basis for antibiotic resistance 17

2.8.1 Organisms which are innately resistant to certain antibiotics 17

2.8.2 Organisms that acquire antibiotic resistance 17

2.8.3 Acquisition of antibiotic resistance through spontaneous mutation 19

2.8.4 Acquisition of antibiotic resistance through DNA transfer 20

2.9 Unprecedented trends that led to an increase in antibiotic resistance 22

2.10 Epidemiology of antibiotic resistance 24

2.11 Factors that encourage the spread of antibiotic resistance 27

2.12 Microbiology of water 29

2.12.1 Introduction to Microbiology of water 29

2.12.2 Indicators of water pollution and presence of water-borne infection 30

2.12.3 Water-borne diseases and the source of antibiotic resistant bacteria in

water 31

2.12.4 Brief overview of some clinically significant isolates identified using the

API 20E tests in this study 33

2.13 Purpose and aims of Study 43

Chapter 3 Materials and methods 44

3.1 Introduction to Materials and Methods 44

3.2 Study area 44

3.3 Sampling 45

3.4 Processing of water samples 45

3.4.1 Chemical Oxygen Demand (COD) 45

3.4.2 Biological Oxygen Demand (BOD) 46

vii

3.4.3 Tests for the presence of coliform bacteria 48

3.4.4 Preliminary identification of isolated bacteria 48

3.5 Antibiotic susceptibility test 48

3.6 Identification of organisms using the API 20E System 50

Chapter 4 Results 55

4.1 Introduction to Results 55

4.2 On-site analysis of water samples 55

4.3 Multiple antibiotic resistances 56

4.4 Antibiotic resistance patterns 64

4.5 API 20E tests 67

Chapter 5 Discussion 72

5.1 Introduction to Discussion 72

5.2 Discussion 73

5.4 Conclusion 78

Bibliography 76

Appendices 90

viii

List of tables

Table 2.1 Classes of Antibiotics based on chemical structure

Table 2.2 Properties of selected Antibiotics

Table 3.1 COD measuring range and corresponding sample volume for BOD5 testing.

Table 3.2 Antibiotics used in this study

Table 3.3 API 20E tests with their corresponding numerical value

Table 3.4 Chemical / Physical Principles – Basis for the API 20E System

Table 4.1a On-site examination of water samples

Table 4.1b COD and BOD values of water samples

Table 4.2 Number of Resistant Isolates at each Sample Point for each Date Collected

Table 4.3a Total Number of Resistant Isolates at each Sample Point

Table 4.3b Number of Isolates Resistant to Each Antibiotic

Table 4.4 Ranking of Antibiotics according to the number of resistant isolates

Table 4.5 Sample Site Multiple Antibiotic Resistance (MAR) Index

Table 4.6 Antibiotics to which all isolates at specific months were resistant per sample point

Table 4.7a Most Prevalent Antibiotic Resistance Patterns and notations

Table 4.7b The Most Prevalent Patterns (with notations) at Each Sample Point

Table 4.8a The Percentages of Individual Isolates in the Total number of Coliforms tested using the

API 20E and its occurrence in sample sites

Table 4.8b Isolates identified with the most prevalent patterns at each sample point

ix

ABSTRACT

Water samples were collected from the Rietspruit River during the course of three seasons and

investigated for the presence of antibiotic and multiple antibiotic resistant coliforms. Three

different sampling points were identified; the upstream, final effluent and downstream sampling

points. Both the upstream and downstream routes pass through urban, rural and industrial areas

as well as a variety of informal settlements; whilst the final effluent sampling point is located

within the premises of the Sebokeng Waste Water Works, where treatment is carried out on

water from the upstream before it is released downstream. Samples were taken in the months of

February, June and September. Coliforms were isolated from all sample points and their

multiple-antibiotic resistance (MAR) profiles were determined against seven different

antibiotics. Isolates showed a 100% resistance to Ampicillin with the least resistance shown

towards Streptomycin (4.8%). The highest MAR index (0.8) was shown in September at the

final Effluent site. The area MAR index for different months varied from 0.01 – 0.03 with the

final Effluent showing the lowest index. A total of 6 different patterns were identified as the

most prevalent; with the highest frequency occurring in multiple resistances to 5 different

antibiotics (Cephalothin, Cotrimoxazole, Colistin sulphate, Ampicillin, and Tetracycline). The

most prevalent resistance patterns at each sample point revealed no specific or common trend in

all 3 sample points over the 3 months period of sample collection; although isolates from the

same sample point tended to show resistance and susceptibilities to the same antibiotics but

varied in some cases with other sample points. Isolates were identified using the API 20E tests.

The API 20E tests revealed a variety of faecal and non-faecal coliforms present in the water

samples. There was not a particular growth pattern observed in all the seasons. A total of 17

different coliforms were identified using the API 20E test kits. Higher numbers of Klebsiella spp.

and Serratia spp, (both at 20.6%) were isolated. Isolates tended to share common resistance

patterns with other coliforms found at a particular sampling point or in some cases during a

particular season, in other cases increasing the number of antibiotics to which they were initially

resistant, making the transfer of antibiotic resistance a possibility. The absence of significant

differences in the presence of coliforms and patterns of multiple antibiotic resistances between

the upstream and downstream is indicative that treatment in the final effluent did not impact the

water quality and this may be attributed to the constant introduction of faecal matter into the

water body mostly from the informal settlements along its route.

1

CHAPTER 1

INTRODUCTION

Antibiotics have been a formidable force in the physician‟s arsenal in the battle against

bacterial pathogens, the discovery of antibiotics arguably being the greatest single

achievement in medicine in the 20th century in terms of human and animal lives saved

(Shoemaker, Vlamakis, Hayes & Salyers 2001: 561). In 1929, British bacteriologist

Alexander Fleming (1881–1955) discovered the bacteria-killing property of penicillin; this

triggered an era of discoveries of antimicrobials with chemotherapeutic properties. Fleming

noticed that a mould that had accidentally fallen into a bacterial culture of Staphylococcus

aureus in his laboratory had killed the bacteria. Having identified the mould as the fungus

Penicillium notatum, Fleming made a juice with it that he named penicillin. After giving it to

laboratory mice, he discovered that it killed bacteria in the mice without harming healthy

body cells. Although Fleming had made an incredible discovery, he was unable to produce

penicillin in a form useful to doctors (Pelczar, Chan & Krieg 1986: 513).

In the early 1940s, spurred partially by the need for antimicrobial agents in World War II,

penicillin was isolated, purified and injected into experimental animals, where it was found

not only to cure infections, but also to possess low toxicity towards animals (Harrison & Svec

1998; Purdom 2007: 1). The subsequent discoveries, development and clinical use of other

antibiotics that followed this major event, resulted in the effective treatment of infection

caused by major bacterial pathogens to the extent that many experts considered bacterial

infectious diseases to be under complete therapeutic control (Harrison & Svec 1998: 151).

Antibiotics are a special kind of chemotherapeutic agent obtained from living organisms.

Serrano (2005: 3) defines “antibiotics” as drugs of natural or synthetic origin that have the

capacity to kill or to inhibit the growth of micro-organisms. The word „antibiotic‟ refers to a

metabolic product of one microorganism that in very small amounts are detrimental or

inhibitory to other microorganisms (Pelczar et al. 1986: 513). This effect or antagonism as it

had been described has been known for many years. Vuillemin in 1889 was the first to define

the term „antibiosis‟ as the condition in which “one creature destroys the life of another in

order to sustain his own, the first being entirely active and the second entirely passive; one is

in unrestricted opposition to the life of the other” (Waksman 1947: 565). However, Waksman

in 1945 proposed the present day use of the term antibiotics as applying to those chemical

2

substances of microbial origin which in small amounts exert antimicrobial activity (Pelczar et

al. 1986: 514).

With the development and widespread application of antibiotics and vaccines, and through

improvements in urban sanitation and water quality, death from infectious diseases has

reduced dramatically. Progress was so great that, three decades ago, some experts predicted

the end of infectious diseases (WHO 2002: 1; Serrano 2005: 1). This optimism was

premature; the effectiveness of these so-called miracle drugs has waned in recent years. There

is a global resurgence of infectious diseases, with both newly identified infectious agents and

a re-emergence of older infectious diseases associated with the rapid spread of antimicrobial

resistance. Some of the very bacteria that these antibiotics are meant to control have been

mutating into new forms that don‟t respond to treatment. Many medical experts blame this

phenomenon on both the misuse and overuse of antibiotics in recent years in both human

medicine and in agriculture; other medical experts believe the increased prevalence of

antibiotic resistance is an outcome of evolution (Sircus 2008: 1). Whichever way we look at it

one fact prevails: the gains realized by the discovery of antibiotics are now being seriously

jeopardized by this phenomenon (WHO 2002: 1).

The emergence and spread of microbes that are resistant to cheap and effective first-choice,

or "first-line" drugs create severe consequences as infections caused by resistant microbes fail

to respond to treatment, resulting in prolonged illness and greater risk of death. Treatment

failures also lead to longer periods of infectivity, which increases the numbers of infected

people moving in the community and thus exposes the general population to the risk of

contracting a resistant strain of infection. When infections become resistant to first-line

antimicrobials, treatment has to be switched to second- or third-line drugs, which are nearly

always much more expensive and sometimes more toxic as well (WHO 2002: 1).

According to WHO Factsheet No. 194 released in 2002; the high cost of such replacement

drugs is prohibitive, with the result that some diseases can no longer be treated in areas where

resistance to first-line drugs is widespread in many countries. Most alarming of all are

diseases where resistance is developing for virtually all currently available drugs, thus raising

the spectre of a post-antibiotic era. Even if the pharmaceutical industry were to step up efforts

to develop new replacement drugs immediately, current trends suggest that some diseases

will have no effective therapies within the next ten years.

3

The Rietspruit River is a major source of water supply for the entire population of Southern

Gauteng; as a result periodic research into any form of contamination is of utmost

importance. The present study will be devoted to the collection of water samples from 3

major sampling points in Rietspruit River during 3 different seasons in 2009 (February, June

and September). The physico–chemical properties of this water, especially the presence and

identification (using both biochemical properties and DNA analysis) of antibiotic resistant

coliforms, that may be present in the water samples, will be investigated.

4

CHAPTER 2

LITERATURE REVIEW

2.1 Introduction to Literature Review

Certain organisms, in a bid for survival, produce metabolites that inhibit or destroy other

organisms present in their vicinity. The production of these metabolites does not take place in

the primary pathways in which these organisms synthesize and utilize essential chemical

compounds necessary for their survival (Mann 1978: 3 - 15). However in an environment

depleted of essential nutrients, organisms enter the stationary phase of growth (a state where

there is no net increase or decrease in cell numbers). It is at this stage that secondary

metabolites are produced and these include antibiotics (Rose 1979: 8). The production of

antibiotics by microorganisms in their natural environment confers an advantage to the

organism producing it in the perpetual war for survival (Rose 1979: 8).Antibiotics are

chemical compounds produced as secondary metabolites of microbial metabolism. Although

many antibiotics used today are produced by microorganisms, some are manufactured partly

or entirely by chemical synthesis. The term „antimicrobic‟ is often used to include agents

produced entirely by microorganisms, as well as commercial antibiotics that have been

chemically altered to improve potency or to increase the range of species they affect (Atlas

1997: 1181; Elliot, Hastings & Desselberger 1997: 332; Jacob 1999: 1).

2.2 Characteristics that qualify antibiotics as chemotherapeutic agents.

For antibiotics to be useful as chemotherapeutic agents, they must have the following

qualities:

1. They should have the ability to destroy or inhibit many different species of pathogenic

microorganisms; this means they should be broad-spectrum.

2. They should prevent the ready development of resistant forms of the microorganisms.

3. They should not produce undesirable side effects in the host, such as sensitivity or

allergic reaction, nerve damage, or irritation of the kidneys and gastrointestinal tract.

4. They should not eliminate the normal microbial flora of the host, because doing so

may upset the „balance of nature‟ and permit the normally non-pathogenic microbes,

5

or particularly pathogenic forms normally restrained by the usual flora, to establish a

new infection (Pelczar et al. 1986: 515).

2.3 Bacterial Susceptibility to Antibiotics.

Species and strains of species of microorganisms have varying degrees of susceptibility to

different antibiotics. Furthermore, the susceptibility of an organism to a given antibiotic may

change, especially during treatment. It is therefore important for the clinician to know the

identity of the organism and the specific antibiotic which may give the most satisfactory

results in treatment (Lancini, Parenti & Gallo 1995: 278; Lennette, Balows, Hausler, Truant

& Shadomy 1985: 451).

The susceptibility of a microorganism to antibiotics and other chemotherapeutic agents can

be determined by either the tube dilution or the paper-disk-plate technique. By the tube

dilution method, one can determine the “minimal inhibitory concentration” (MIC). The MIC

is the minimal concentration of antibiotic required to completely inhibit the growth of a given

bacterial strain (Lennette et al. 1985: 450 - 455; Pelczar et al. 1993: 897).

2.4 Antibiotics and their mode of action.

Antibiotics can be classified in several ways. For example, some are „bactericidal‟ and others

are „bacteriostatic‟. When an antibiotic is classified as bacteriostatic, it means it inhibits the

growth of bacteria without killing them. As a result bacteriostatic drugs rely on the normal

host defences to eliminate or kill the pathogen after growth has been inhibited. For example

de-sulpha drugs, which are frequently prescribed in the treatment of urinary tract infections,

simply inhibit the growth of the bacteria in the bladder until they are cleared by the normal

process of urination. On the other hand drugs that kill bacteria outright are bactericidal. These

drugs are particularly useful in situations where the host defences cannot be relied upon to

remove or destroy pathogens (Pelczar et al. 1986: 490; Nester, Roberts, Pearsall, Anderson &

Nester 1995: 450; Rafay & Nsanze 2003: 261).

The most common method classifies them according to their chemical structure, as antibiotics

sharing the same or similar chemical structure and these will generally show similar patterns

of antibacterial activity, effectiveness, toxicity and allergic potential. The usefulness of

antibiotics in medicine stems from the fact that their toxicity is often due to their ability to

6

interfere with essential biochemical structure or processes that are unique to prokaryotes; an

example is the synthesis of peptidoglycan. By interfering with a target that is unique to

prokaryotes, the antibiotics cause relatively little harm to the human host, in a phenomenon

called selective toxicity. That is, the drugs are toxic to the bacteria but not to the human host

(Nester et al. 1995: 448).

A third way of classifying is on the basis of their mode of action, which is the manner in

which they manifest their damage upon microbial cells. The major points of attack of

antibiotics on microorganisms include:

Inhibition of cell-wall synthesis;

Damage to the cytoplasmic membrane;

Inhibition of protein synthesis;

Inhibition of nucleic acid synthesis; and

Inhibition of specific enzyme systems in metabolic pathways.

Table 2.1 Classes of Antibiotics based on chemical structure

Class (chemical structure) Mechanism of action Examples

β-lactam antibiotics

Penicillins

Aminopenicillin

Cephalosporins

Carbapenems

Inhibit bacterial cell wall synthesis Penicillins

Penicillin G

Amoxicillin

Flucloxacillin

Aminopenicillin

Amoxicillin

Ampicillin

Cephalosporins

Cephalothin

Cefoxitin

Cefotaxime

Ceftriaxone

Carbapenem

7

Imipenem

Macrolides Inhibit bacterial protein synthesis Erythromycin

Azithromycin

Clarithromycin

Tetracyclines Inhibit bacterial protein synthesis Tetracycline

Minocycline

Doxycycline

Lymecycline

Quinolones

Fluoroquinolones

Inhibit bacterial DNA synthesis

Inhibit bacterial DNA synthesis

Nalidixic acid

Norfloxacin

Ciprofloxacin

Enoxacin

Ofloxacin

Sulphonamides Blocks bacterial cell metabolism by

inhibiting enzymes

Co-trimoxazole

Trimethoprim

Aminoglycosides Inhibit bacterial protein synthesis Gentamicin

Amikacin

Streptomycin

Kanamycin

Neomycin

Imidazoles Inhibit bacterial DNA synthesis Metronidazole

Peptides and polypeptides Inhibit bacterial cell wall synthesis Peptides

Bacitracin

Polypeptides

Colistin sulphate

Colistimethate

sodium

Lincosamides Inhibit bacterial protein synthesis Clindamycin

Lincomycin

Polyenes Damage to the cytoplasmic membrane Nystatin

Amphotericin

Candicidin

Ngan 2005 (Online). Available at: < www.dermnetnz.org/treatments/antibiotics.html>. Accessed: 15 October

2009.

8

2.4.1 Inhibition of cell-wall synthesis.

The substance that gives rigidity to the cell-wall is the peptidoglycan. The structure of this

compound is essentially that of a series of strands (polymers with repeating units of N-

acetylglucosamine and N-acetylmuramic acid) that are cross-linked with small peptides

(peptide-bridge), with a frequency and in a manner that imparts considerable rigidity to the

cell wall. It is a protective covering for the bacterial cell (Ferris & Beveridge 1985: 175).

Penicillin, the first antibiotic discovered, interferes with the formation of the peptide bridge

by binding to proteins, called penicillin-binding proteins (PBP) that are involved in cell wall

biosynthesis. The resulting lack of cross-linking weakens the structural integrity of the cell

wall, ultimately leading to cell lysis (Donowitz & Mandell 1988: 318). Since peptidoglycan is

only synthesized in actively growing cells, penicillin is only effective against multiplying

bacteria. Other antibiotics such as Bacitracin and Vancomycin also interfere with

peptidoglycan synthesis, but their action is not restricted to the cell wall and, therefore, their

therapeutic index is low (Donowitz & Mandell 1988: 318).

2.4.2 Damage to the cytoplasmic membrane.

Several polypeptide antibiotics produced by Bacillus spp. have the ability to damage cell

membrane structure. They adversely affect the normal permeability characteristics of the cell

membrane; they include Polymyxins, Gramicidins and Tyrocidines (Franklin & Snow 1989:

121).

The Polymyxins are particularly effective against Gram-negative organisms while the

Tyrocidines and Gramicidines are more effective against Gram-positive organisms (Franklin

& Snow 1989: 119). These agents are bactericidal; they cause a leakage from the cytoplasmic

content of the cell. Unfortunately, these drugs also bind to eukaryotic cells, though to a lesser

extent. As a result they have limited application in chemotherapy (Elsbach 1990: 26).

Another category referred to as Polyene antibiotics are, for example, Nystatin, produced by

Streptomyces noursei and Amphotericin, produced by Streptomyces nodusus. Polyene

antibiotics act upon cells which have sterols in their cytoplasmic membrane. They act upon

fungi (including yeasts) and animal cells but do not affect bacteria. Their antimicrobial action

is attributed to their ability to increase cell permeability (Franklin & Snow 1989: 119).

9

2.4.3 Inhibition of protein synthesis.

Several groups of antibiotics including streptomycin, chloramphenicol and tetracycline exert

their effect on bacteria by interfering with steps of protein synthesis. Streptomycin is

produced by Streptomyces griseus; it is particularly useful because it inhibits many organisms

resistant to sulphonamides and penicillin. Streptomycin and other aminoglycoside antibiotics

inhibit protein synthesis by combining irreversibly with the 30S subunit of the 70S mRNA;

this interferes with the formation of initiation complexes, the first step in genetic code

translation, thus affecting the fidelity of translation into protein (Garrod, Lambert & O‟

Grady 1981: 120; Mims, Playfair, Roitt, Wakelin & William 1993: 22; Atlas 1997: 1183).

Aminoglycosides are used almost exclusively in the treatment of infections caused by Gram-

negative bacteria, but they are relatively ineffective against anaerobic bacteria, facultative

anaerobes and Gram-positive bacteria (Elliot et al. 1997: 332).

According to Elliot et al. (1997: 332), chloramphenicol binds the 50S subunit and interferes

with the linkage of amino acids in the peptide chain formation, or combines with the bacterial

ribosome to prevent the assembly of amino acids into a protein chain. Chloramphenicol is

active against many species of Gram-negative bacteria. Chloramphenicol is used for treating

typhoid fever and various infections caused by Salmonella.

Tetracyclines bind to the 30S subunit, preventing binding of the aminoacyl transfer RNA to

the acceptor site in the ribosome, thereby inhibiting amino acid chain elongation. At least two

processes appear to be required for these antibiotics to gain access to the ribosomes of Gram-

negative bacteria, namely (i) passive diffusion through the hydrophilic channels formed by

the porin proteins of the outer membrane and (ii) active transport by an energy-depending

system that pumps all tetracyclines through the inner cytoplasmic membrane (Mandell &

Petri 1996: 1062). Tetracyclines have a broad spectrum of activity against many Gram-

positive and some Gram-negative bacteria (Elliot et al. 1997: 332). Tetracyclines are also

useful against various bacterial infections, including Mycoplasma pneumoniae, causative

agent of brucellosis, tularemia and cholera.

Only a few antibiotics having this mode of action are selective enough in their toxicity to be

administered safely to patients, which is not surprising since protein synthesis is a feature of

all cells, not just those of pathogenic microorganisms. Fortunately, 80S eukaryotic ribosomes

10

are different enough in their structure to allow for the possibility of some selectivity in their

action. Even so, bacterial-type (70S) ribosomes are present in the mitochondria. This may

partially account for the side effects often observed in patients undergoing treatment with

antimicrobial agents that interfere with prokaryotic protein synthesis (Franklin & Snow 1989:

123).

2.4.4 Inhibition of nucleic acid synthesis.

Several enzymes involved in DNA replication and transcription in prokaryotes are

sufficiently different from eukaryotes to act as selective targets. Rifampin, for example binds

strongly to bacterial RNA polymerase and thereby inhibit mRNA synthesis (Hooper &

Wolfson 1991: 392). Rifampin, a semi-synthetic derivative of rifamycin B inhibits DNA-

dependent RNA polymerase of mycobacteria and other microorganisms by forming a stable

drug-enzyme complex, leading to the suppression of the initiation of chain formation in RNA

synthesis (Mandell & Petri 1996: 1060). Rifampin is used in combination with other

antibiotics in the treatment of tuberculosis (Elliot et al. 1997: 332). Rifampin inhibits the

growth of most Gram-positive and Gram-negative microbes such as Escherichia coli,

Pseudomonas, indole-positive and indole-negative Proteus and Klebsiella. Rifampin is very

active against Staphylococcus aureus and coagulase-negative staphylococci (Mandell & Petri

1996: 1070).

The family of synthetic antibacterial drugs called quinolones (nalidixic acid) are also

inhibitors of nucleic acid synthesis, but they act against the enzyme DNA gyrase, thereby

stopping DNA synthesis. DNA gyrase mediates the breaking and reunion of DNA strands and

is required for replication of DNA as well as transcription of DNA to mRNA (Hooper &

Wolfson 1991: 392). Quinolones are effective against a broad range of Gram-positive and

Gram-negative bacteria including the mycobacteria (Mims et al. 1993: 27).

2.4.5 Inhibition of specific enzyme systems in metabolic pathways.

Some antimicrobial drugs interfere with metabolic pathways common in prokaryotes but not

humans. One such pathway is the synthesis of folic acid, which is an important precursor of

an essential coenzyme. Folic acid, consisting in part of para-aminobenzoic acid (PABA) has

an essential role as co-substrate in the biosynthesis of amino acids, purine and pyrimidines.

11

Many types of bacteria are able to synthesize folic acid through a multi-step pathway, but

they cannot take it up from their external environment. Humans, on the other hand, lack this

pathway, so folic acid must be provided in their diet (Franklin & Snow 1989: 122; Atlas

1997: 1184).

Drugs such as sulphonamides and trimethoprim that inhibit essential enzymes in the pathway

of folic acid synthesis are selectively toxic to bacteria because humans do not have the target

enzymes (Franklin & Snow 1989: 123). The one-carbon transfer required for the synthesis of

thymidine and purines does not occur in the presence of trimethoprim, an antimicrobial agent

(Nester et al. 1995: 452)

Many Gram-positive cocci, including Staphylococcus aureus, streptococci and the viridians

streptococci, and to a variable extent the enterococci, are susceptible to trimethoprim. The

enterobacteria, including E.coli and Salmonella species, are also sensitive to the action of

trimethoprim. The wide-spectrum activity of trimethoprim favors the application of this drug

in the treatment of gastroenteritis as well as respiratory and urinary tract infections caused by

susceptible organisms. Sulphonamides and trimethoprim are often used in combination to

combat bacterial infection (Mann & Grabbe 1996: 74; Atlas 1997: 1184 -1185).

2.5 Uses of Antibiotics.

Antibiotics have found diverse uses in various aspects of human and veterinary medicine and

in food preservation as well as it being used as research tools.

2.5.1 Chemotherapeutic uses

Antibiotics are chemotherapeutic agents used in the treatment of infectious diseases of

microbial origin. This is achieved by the systemic administration of the chosen antibiotic

(Lancini et al. 1995: 278).

Some antibiotics have been found to possess antitumor activity. The anthramycin group

(anthramycin, sibromycin, tomaymycin, neothramycin) is an example of potent antitumor

agents. However, research is still ongoing to eliminate their adverse side effects, and to find

new antibiotics with these qualities (Zenzaburo, Hisatoyo, Masayoshi & Takao 1983: 9).

12

2.5.2 Clinical uses as research tool

Antibiotics can be used in the identification of infectious bacterial agents. In cases where the

agent cannot be isolated and identified or the DNA cannot be matched it is possible that

antibiotic therapy will cause the release of the microbial antigen to initiate a specific antibody

response. The serologic measure of a change or response in the serum antibody level to a

bacterial infection would indicate its presence. The sero-conversion or the increase in

antibody titre, resulting from the administration of a vaccine would indicate the host‟s

immune responsiveness to a particular antibiotic therapy. The specificity and sensitivity of

the serologic response depends on the test used, such as: growth inhibition, neutralization,

agglutination (ELISA), complement fixation, immuno-blotting (Clark 2000: 1).

2.5.3 Veterinary uses

Following the discovery of the growth promoting and disease fighting capabilities of

antibiotics, fish farmers, poultry and livestock producers began using such drugs in animal

feeds. Antibiotics routinely used for treatment of human infections are also used for animals,

for therapy, prophylactic reasons or growth promotion. For the last-named purpose, sub-

therapeutic doses of antibiotics usually have been used (Khachatourians 1998: 1). The

addition of sub-therapeutic amounts of certain antimicrobial agents to animal feeds, not only

prevents infectious diseases caused by bacteria or protozoa, but also decrease the amount of

feed required while increasing the rate of weight gain (Du Pont & Steele 1987: 448). The

addition of tetracycline or penicillin to commercial swine or poultry feed at the rate of 5 to

20grams per ton of feed was found to have increased the growth rate of young animals by at

least 10% and sometimes more. This may be as result of the added drugs destroying

pathogenic bacteria and intestinal parasites that could have caused mild forms of disease that

affect the growth and development of young animals (Pelczar et al. 1993: 913;

Khachatourians 1998: 1). Antibiotics in animal feeds could also improve the performance of

animals under conditions of stress such as poor ventilation or overcrowding during transit.

Chronic respiratory disease in poultry, scouring and diarrhoeal diseases in pigs commonly

occur under these conditions (Cooke 1974: 82). The use of sub-therapeutic levels of

antimicrobial agents is one of the tools that have facilitated the confinement housing,

allowing larger numbers of animals to be maintained in a production facility of a given size.

13

This practice of adding sub-therapeutic amounts of antibiotics to the feed of livestock and

poultry probably contributes to lower cost of animal care and ultimately lowers cost to the

consumer of meat milk and eggs (Du Pont & Steele 1987: 459).

2.5.4 Food preservative uses.

Processing of fresh dressed poultry has always presented serious spoilage problems. This is

because the skin of live birds as well as feet, feathers and faeces contain a variety of

microorganisms. Contamination of poultry usually occurs during washing, plucking and

evisceration. Much has been done in recent years to improve poultry processing operations

and although improved sanitation has done much to better protect the consumer, dressed and

cut-up poultry still deteriorates rapidly. Even at refrigerator temperatures, microbial spoilage

still occurs when food is stored for long periods (Durbin 1956: 1307; Frazier & Westhoff

1996: 494). Freshly laid eggs, which are usually sterile inside become contaminated on the

outside by faecal matter from the hen, cage, nest and wash water if the eggs are washed

during handling. If these fresh eggs exhibit cracks in the shell this becomes a route of

infection which leads to spoilage during storage and if these organisms are pathogenic it

becomes a route of transmission to consumers (Frazier & Westhoff 1996: 494).

According to Jay (1992: 553), internal temperature of food is not reduced to within the

refrigerator range and the spoilage that is likely to occur is caused by internal sources,

including Clostridium perfringens and the genera of the Enterobacteriaceae family. Bacterial

spoilage of refrigerated-stored meats may also be reflective of external conditions and

sources of contamination including handling.

Preservation methods that have been developed to reduce the risk of food-borne outbreaks of

infectious diseases include physical procedures such as irradiation, freezing, vacuum

packaging or chilling (Frazier & Westhoff 1996: 495). Food can also be preserved using

chemicals such as benzoic acid, the parabens, sorbic acid, nitrites or nitrates, sulphites or

sulphur dioxide, or by increasing carbon dioxide concentrations. Nisin, a bacteriocin

produced by some strains of Lactococcus lactis, as well as antibiotics such as tetracycline,

natamycin and subtilins, are often applied to preserve food (Jay 1992: 553).

14

2.6 Adverse reactions to antibiotic use.

Some people develop hypersensitivities or allergies to certain antimicrobials. An allergic

reaction to penicillin and other related drugs may result in a fever or rash and can sometimes

lead to life-threatening anaphylactic shock. For this reason, it is important that people who

are allergic to antimicrobials alert their physician so they can prescribe alternative drugs

(Mandell, Douglas, Bennet & Dolin 1995: 122 - 145).

Several antibiotics are toxic at high concentration and occasionally cause adverse reactions.

For example, streptomycin can damage kidneys and impair a sense of balance, but its most

toxic effect is irreversible deafness. Patients taking this drug must be closely monitored

because it has a low therapeutic index. Some antibiotics have such severe potential side

effects that they are reserved only for life-threatening conditions. For example, in rare cases

chloramphenicol causes the potentially lethal condition called aplastic anaemia in which the

body is unable to make white and red blood cells. For this reason chloramphenicol is used

only when no other alternatives are available such as in treating penicillin-allergic patients

who have bacterial meningitis (Mandell & Petri 1996: 1069).

In some cases antibiotics suppress the normal flora of the body where the target pathogen is

located. These normal flora play an important role in excluding pathogens, their absence

could potentially lead to opportunistic infections (Pelczar et al. 1986: 894). Patients who take

broad-spectrum antibiotics are at risk of developing the life-threatening disease antibiotic

associated colitis (pseudomembranous colitis) caused by the growth of toxin-producing

Clostridium difficile in the intestine. This organism is not usually able to establish itself in the

intestine due to competition with other bacteria. However, when the growth of the normal

flora is inhibited or floras are killed, C. difficile can flourish and cause disease (Nester et al.

1995: 453; Mandell et al. 1995: 147).

2.7 Bacterial resistance to antibiotics

2.7.1 Introduction to Bacterial resistance to antibiotics.

The extraordinary ability of certain bacteria to develop resistance to antibiotics which are

otherwise useful in speeding recovery from some illnesses has been a hot topic on the minds

of doctors, hospital staff, reporters, and the general public for several years. It is also heralded

15

as a textbook example of evolution in action. Scientists are dismayed to discover that some

bacteria have become resistant to antibiotics through various alterations, or mutations, in their

DNA. Unfortunately the development of resistance is a normal process and occurs as a way

to protect bacteria from extinction (Purdom 2007: 1; Serrano 2005: 41). In the laboratory this

is observed when strains of bacteria are able to multiply in the presence of antibiotic

concentration higher than the concentration in humans receiving therapeutic doses (WHO

2002: 1).

Some studies have suggested that antibiotic resistance, once acquired are very slowly lost.

For example the persistence of streptomycin or sulphonamide resistance in E. coli despite the

decrease in antibiotic use and the persistence of vancomycin-resistant enterococci have led to

the ban of avoparicin in Norway (Enne, Livemore, Stephen & Hall 2001: 1325; Heuer,

Pedersen, Andersen & Madsen 2002: 137).

As early as the late 1940s resistant strains of bacteria began to appear. Currently, it is

estimated that more than 70% of the bacteria that cause hospital-acquired infections are

resistant to at least one of the antibiotics used to treat them (Purdom 2007: 1; Nester et al.

1995: 725).

The application of antibiotics in the treatment of viral infections, prescription of erroneous

dosage, or failure of patients to complete the prescribed course are factors that probably

played a major role in rendering many important antibiotics ineffective (Hardman & Limbird

1996: 1120).

2.7.2 Causes of antibiotic resistance

Microbes (the collective term for bacteria, fungi, parasites, and viruses) can cause infectious

diseases, and antimicrobial agents such as penicillin, streptomycin, and more than 150 others,

have been developed to combat the spread and severity of many of these diseases. Resistance

to antimicrobials is a natural biological phenomenon that can be amplified or accelerated by a

variety of factors, including human practices. The use of an antimicrobial for any infection,

real or feared, in any dose and over any time period, forces microbes to either adapt or die in

a phenomenon known as "selective pressure". The microbes which adapt and survive carry

genes for resistance, which can be passed on (Purdom 2007: 1).

16

Bacteria are particularly efficient at enhancing the effects of resistance, not only because of

their ability to multiply very rapidly but also because they can transfer their resistance genes,

which are passed on when the bacteria replicate. In the medical setting such resistant

microbes will not be killed by an antimicrobial agent during a standard course of treatment.

Resistant bacteria can also pass on their resistance genes to other related bacteria through

"conjugation", whereby plasmids carrying the genes jump from one organism to another.

Resistance to a single drug can thus spread rapidly through a bacterial population. When anti-

microbials are used incorrectly - for too short a time, at too low a dose, at inadequate

potency; or for the wrong disease - the likelihood that bacteria and other microbes will adapt

and replicate rather than be killed is greatly enhanced (Pelczar et al. 1993: 898; Purdom

2007: 1).

The accumulated scientific evidence is that certain uses of antibiotics in food-producing

animals can lead to antibiotic resistance in intestinal bacteria, and this resistance can then be

transmitted to the general population, causing treatment-resistant illness. These uses of

antibiotics can also create antibiotic resistance in non-pathogenic bacteria, the resistance

genes of which can be transferred to disease-causing bacteria, resulting in antibiotic-resistant

infections for humans (Khachatourians 1998: 1; Jacob 1999: 1; Ghosh & LaPara 2007: 191 -

203).

The report from the invitational European Union conference on The Microbial Threat (EU

1998) recognized that the major route of transmission of resistant microorganisms from

animals to humans is through the food chain. This trend is confirmed by other authors

(Nawaz, Erickson, Khan, Khan, Pothulari, Rafii, Sutherland, Wagner & Cerniglia 2001: 5).

According to WHO (2002: 1) the total consumption of antimicrobials is the critical factor in

selecting resistance. Paradoxically, underuse through lack of access, inadequate dosing, poor

adherence, and substandard anti-microbials may play as important a role as overuse. For

these reasons, improving use is a priority if the emergence and spread of resistance are to be

controlled (WHO 2002: 1).

17

2.8 Genetic basis for antibiotic resistance

2.8.1 Organisms which are innately resistant to certain antibiotics.

Organisms that naturally lack a target for a specific antibiotic are innately resistant to that

antibiotic. For example, members of the genus Mycoplasma lack a cell wall, as a result they

are resistant to penicillin and other drugs that target peptidoglycan. Additionally, many

Gram-negative organisms are inherently resistant to penicillin because the selective

permeability of their outer membrane excludes the drug from the cell wall. Innate resistance

is consistent and predictable because it reflects the natural composition of an organism

(Donowitz & Mandell 1988: 491).

2.8.2 Organisms that acquire antibiotic resistance.

Unlike innate resistance, acquired antibiotic resistance is ever changing. As antibiotics are

increasingly used and misused, the bacterial strains that are resistant to their effects have a

selective advantage over their sensitive counterparts when the antimicrobial is in the

environment. For example, when penicillin was first introduced, less than 3% of

Staphylococcus aureus strains were resistant to its effects. Heavy use of the drug, measured

in hundreds of tons per year, progressively eliminated sensitive strains, so that now 85% or

more are now resistant (Nester et al. 1995: 459; Neu 1992: 1064). This development is

understandably of great concern to health professionals because of the impact on cost,

complications and outcomes of treatment (Neu 1992: 1064; WHO 2002: 1).Bacteria have

evolved diverse and remarkable ways to avoid the effects of antimicrobials. In several cases,

resistance is due to a minor structural alteration in the target so that it is no longer bound by

the drug yet still functions. For example, streptomycin normally binds to a part of the

prokaryotic 30S ribosomal subunit that is critical for protein synthesis. A slight alteration in

the structure of the ribosome results in a distortion, so that streptomycin is no longer able to

bind but the ribosome can still functionally translate mRNA. Similarly, changes in the

penicillin-binding proteins (PBPs) do not alter their function but prevent the binding of

penicillin (Jacoby & Archer 1991: 608; Purdom 2007: 1).

Some bacteria have evolved the ability to over-produce the target as a way of avoiding the

effects of an antimicrobial drug. The increased quantity of target molecules overwhelms the

18

drug. For example, sulfa drugs normally interfere with the folic acid synthesis by acting as a

decoy substrate for the enzyme, thus competitively inhibiting the enzyme. When an organism

produces excess, enough uninhibited enzyme will be available to complete the synthesis of

folic acid (Nester et al. 1995: 452; Jacoby & Archer 1991: 608).

An entirely different mechanism of drug resistance involves the destruction or inactivation of

the antibiotic. Some organisms produce specific enzymes that can cleave or chemically

modify the essential portion of an antibiotic to destroy its activity. For example, the enzyme

„penicillinase‟ is one of a group of enzymes generally called „β-lactamases‟ that destroy the

activity of penicillin and some other similar drugs operate by cleaving an essential portion,

the β-lactam ring. Similarly, resistance to chloramphenicol is caused by the organisms‟

acquisition of a plasmid that encodes an enzyme (chloramphenicol acetyltransferase [CAT])

which inactivates the drug by adding an acetyl group. The modified form of chloramphenicol

is not toxic to bacteria (Wright 1994: 380; Jacoby & Archer 1991: 610; Neu 1992: 1064).

Sulphonamide-resistant bacteria produce modified enzymes which have a higher affinity for

the substrate para-amino benzoic acid (PABA), a precursor in folic acid metabolism, than for

sulphonamide. Consequently, even in the presence of sulphonamide, the enzyme works well

enough to allow the bacterium to function (Black 1996: 790).

Some sulphonamide-resistant bacteria may alter a metabolic pathway in order to bypass the

reaction inhibited by the antimicrobial agent. These organisms have acquired the ability to

use ready-made folic acid from their environment and no longer need to make it from PABA

(Black 1996: 790; Schwarz & Chaslus-Dancla 2001: 210).

Alteration in membrane permeability or its other functions may also confer antibiotic

resistance. In some cases, mutational alteration of a membrane protein responsible for

maintaining selective permeability prevents the drug from entering the cell. In the case of

tetracycline resistance, however, the drug is actively pumped back out of the cell (Jacoby &

Archer 1991: 612). This pump action prevents the accumulation of toxic levels of

tetracycline so that bacterial protein synthesis is not inhibited. The efflux pump mechanism

function is associated with the inner membrane and it occurs in both Gram-positive and

Gram-negative bacteria (Atlas 1997: 1185).

19

2.8.3 Acquisition of antibiotic resistance through spontaneous mutation.

In the presence of antibiotics, the process of natural selection will occur, favouring the

survival and reproduction of the mutant bacteria. The mutant bacteria are better able to

survive in the presence of the antibiotic and will continue to cause illness in the patient

(Purdom 2007: 1). Mutation may either arise spontaneously, or could be induced by external

stress factors in the environment, including chemical agents such as antibiotics, heat or

irradiation (Todar 1996b: 1; Elliot et al. 1997: 332; Nester et al. 1995: 156).

Acquisition of antimicrobial resistance may be due to spontaneous mutations that naturally

occur during cell growth. For example, streptomycin-resistance is acquired through point

mutation, that, like all spontaneous mutations occur only very rarely. However, given the

high numbers of bacteria associated with an active infection and the selective advantage that

resistant mutants have when antibiotics are used, the rare mutation is significant indeed

(Wright 1990: 23; 1994: 370).

Mutations causing a change in only a single nucleotide with no detectable alteration in the

end product, namely the transcribed protein, are referred to as point mutations. Point

mutations probably are of less consequence to the problem antibiotic resistance compared to

the major genetic changes that cause significant alterations in the bacterial cells. Such

alterations often are detrimental and the mutant organisms may not survive (Todar 1996b: 1;

Elliot et al. 1997: 332).

Antimicrobials to which spontaneous mutations frequently occur are sometimes given in

combination with a second antimicrobial drug. For example, streptomycin alone is never used

to treat tuberculosis but is instead used in combination with other drugs such as rifampin. The

chance that an organism will simultaneously develop resistance to both drugs is extremely

low, so an organism that develops resistance to one drug will still be killed by the other drug

(Mandell et al. 1995: 145).

Although the mutant bacteria can survive well in the hospital environment, the change has

come at a cost. The altered protein is less efficient in performing its normal function, making

the bacteria less fit in an environment without antibiotics. Typically, the non-mutant bacteria

are better able to compete for resources and reproduce faster than the mutant form (Purdom

20

2007: 1). A famous example to help clarify this was during the anthrax scare shortly after the

September 11 2001 attacks in the U.S., when Ciprofloxacin (Cipro) was given to potential

victims. Cipro belongs to a family of antibiotics known as quinolones, which bind to a

bacterial protein called gyrase, decreasing the ability of the bacteria to reproduce. This allows

the body‟s natural immune defences to overtake the infectious bacteria as they are

reproducing at a slower rate. Quinolone-resistant bacteria have mutations in the genes

encoding the gyrase protein. The mutant bacteria survive because the Cipro cannot bind to

the altered gyrase (Purdom 2007: 1). This comes at a cost as quinolone-resistant bacteria

reproduce more slowly (Heddle & Anthony 2002: 1814; Barnard & Anthony 2001; 1997).

Resistance to this family of antibiotics is becoming a major problem with Campylobacter

jejuni bacteria which cause food poisoning. In the US alone, studies show that C. jejuni

increased its resistance to quinolones 10-fold in just five years (Molbak, Gerner-Smidt &

Wegener 2002: 1).

2.8.4 Acquisition of antibiotic resistance through DNA transfer.

Bacteria can also become antibiotic-resistant by gaining mutated DNA from other bacteria.

This mechanism of exchanging DNA is necessary for bacteria to survive in extreme or

rapidly changing environments like a hospital (Purdom 2007: 1). Genetic traits for antibiotic

resistance are encoded by genes occurring either on the bacterial genome, or on extra-

chromosomal genetic elements called plasmids (Khachatourians 1998: 1).

Alterations in the bacterial genome may result in the mutant cell having new properties of

significant advantage under particular environmental conditions which may allow them to

out-compete other daughter cells (Todar 1996b: 1; Elliot et al. 1997: 332).

In bacteria, extra-chromosomal genetic material occurs in plasmid and transposons. Plasmids

carry those genes that encode properties or functions that are not essential for growth and

multiplication, but rather give the organism an advantage for survival in environments where

they are exposed to particular stress factors, such as antibiotics (Harrison & Svec 1998: 160).

Transposons, often known as jumping genes, are mobile genetic elements that move from one

site to another, inevitably causing the amino acid sequence in these sites to change. At the

end of the transposon there are specific base sequences known as insertion sequences which

21

allow the transposon DNA to be inserted into existing DNA strands. Transposons allow

genetic information to be transferred rapidly between plasmids and chromosomal DNA, and

also facilitate the dissemination of genetic information among bacteria in the environment

(Elliot et al. 1997: 332; Harrison & Svec 1998: 160; Nester et al. 1995: 157).

Plasmids are relatively large, independent, self-replicating genetic units that carry several

genes that control the activities of the plasmid itself as well as those of the parent cell, such as

plasmid replication, production of sex pili, conjugation, DNA transfer, antibiotic resistance

and toxin production (Mims et al. 1993: 27).

The resistance genes that code for enzymes that inactivate the antimicrobials are often found

on the conjugative plasmids called resistance plasmids or „R-plasmids‟. A single R-plasmid

frequently encodes on several different genes resistance to several different antimicrobial

drugs, thus enabling an organism to simultaneously gain resistance to several completely

different drugs in a phenomenon known as „multiple drug resistance‟ (Wright 1994: 372; Neu

1992: 1064; Jacoby & Archer 1991: 610). According to Harrison & Svec (1998: 161) the

frequent exchange of these R-plasmids is a major factor in the rapid distribution of resistance

genes among bacteria in the environment.

Unfortunately, the mobility of these genes makes the possibility of widespread resistance a

grim reality (Neu 1992: 1064). For example, extensive use of antibiotics selects for normal

flora such as Staphylococcus epidermidis that carry „R-plasmids‟. Normally this would not be

threatening, except for the fact that S. epidermidis is capable of transferring its plasmids to

the common pathogen S. aureus. As a result of the ease with which antibiotic resistance can

be transferred through conjugation; many isolates of S. aureus are now resistant to all

antibiotics except vancomycin (Mandell et al. 1995: 1069).

Vancomycin is a drug usually reserved for life-threatening conditions. Even more serious is

the fact that some strains of Enterococcus, a common opportunistic pathogen that is part of

normal flora, are resistant to all known antimicrobial agents including vancomycin. These

„vancomycin-resistant enterococci‟ (VRE) are particularly a problem in intensive-care

settings in which patients are prone to opportunistic infections. Infections caused by these

strains are untreatable with conventional drug therapy (Neu 1992: 1064; Mandell et al. 1995:

1070).

22

Table 2.2 Properties of selected Antibiotics

Target Drugs Action Original source Representative

Mechanism of

Resistance

Cell wall synthesis Penicillins Binds to protein

essential for cell

wall synthesis

Penicillium Enzymatic

inactivation of β-

lactamase

Cephalosporins Same as penicillin Cephalosporium Enzymatic

inactivation of β-

lactamase

Imipenem Same as penicillin Streptomyces Prevention of entry

into cell

Aztreonam Same as penicillin Chromobacterium Enzymatic

inactivation of β-

lactamase

Vancomycin Inhibits assembly

of peptidoglycan

Streptomyces Altered target

Cell membrane

function

Polymyxin Binds to membrane

protein and alters

permeability

Bacillus (Resistance is rare)

Protein synthesis Streptomycin Binds to 30S

ribosomal subunit

Streptomyces Enzymatic

inactivation

Chloramphenicol Binds to 50S

ribosomal subunit

Streptomyces Enzymatic

inactivation

Erythromycin Binds to 50S

ribosomal subunit

Streptomyces Enzymatic

inactivation

Tetracyclines Binds to 30S

ribosomal subunit

Streptomyces Prevention of entry

into cell

Lincomycin Binds to 50S

ribosomal subunit

Streptomyces Altered target

Nucleic acid

synthesis

Rifampin Binds to RNA

polymerase

Streptomyces Altered target

Fluoroquinolones Interferes with

DNA gyrase

Chemically

synthesized

Altered target

Folic acid

synthesis

Sulphonamides Competitively

inhibits enzymes

Chemically

synthesized

Altered target

Trimethoprim Competitively

inhibits enzymes

Chemically

synthesized

Altered target

Nester, Roberts, Pearsall, Anderson & Nester 2003, Microbiology: A Human Perspective. (2nd

ed.). Boston:

McGraw Hill: 157 -160.

2.9 Unprecedented trends that led to an increase in antibiotic resistance.

In the past, medicine and science were able to stay ahead of this natural phenomenon through

the discovery of potent new classes of antimicrobials, a process that flourished from 1930-

23

1970 and has since slowed to a virtual standstill, partly because of misplaced confidence that

infectious diseases had been conquered, at least in the industrialized world. In just the past

few decades, the development of resistant microbes has been greatly accelerated by several

concurrent trends (WHO 2002: 3). These have worked to increase the number of infections

and thus expand both the need for antimicrobials and the opportunities for their misuse. Such

trends include:

urbanization with its associated overcrowding and poor sanitation, which greatly

facilitate the spread of such diseases as typhoid, tuberculosis, respiratory infections,

and pneumonia;

pollution, environmental degradation, and changing weather patterns, which can

affect the incidence and distribution of infectious diseases, especially those, such as

malaria, that are spread by insects and other vectors;

demographic changes, which have resulted in a growing proportion of elderly people

needing hospital-based interventions and thus at risk of exposure to highly resistant

pathogens found in hospital settings;

the AIDS epidemic, which has greatly enlarged the population of immuno-

compromised patients at risk of numerous infections, many of which were previously

rare;

the resurgence of old foes, such as malaria and tuberculosis, which are now

responsible for many millions of infections each year; and

the enormous growth of global trade and travel which have increased the speed and

facility with which both infectious diseases and resistant microorganisms can spread

between continents (WHO 2002: 3).

As the number of infections and the corresponding use of antimicrobials have increased, so

has the prevalence of resistance. In addition, the enhanced food requirements of an expanding

world population have led to the widespread routine use of antimicrobials as growth

promoters or preventive agents in food-producing animals and poultry flocks. Such practices

have likewise contributed to the rise in resistant microbes, which can be transmitted from

animals to man (Khachatourians 1998: 1; WHO 2002: 3).

24

2.10 Epidemiology of antibiotic resistance

Emerging antimicrobial resistance, due to use of antimicrobials, is a public health concern in

human and animal medicine worldwide. According to the Centres for Disease Control and

Prevention (CDC) (HHS, 1999a: 1), resistant strains of three micro-organisms causing human

illness – Salmonella sp., Campylobacter sp. and Escherichia coli – are linked to the use of

antibiotics in animals. Young children, the elderly and immuno-compromised are the

population at risk. These bacteria infect humans through ingested contaminated foods,

especially foods of animal origin. Animals serve as reservoirs for many food-borne

pathogens, including Salmonella and Campylobacter. Antibiotic-resistant organisms may be

present in or on animals as a result of drug use and these resistant food-borne pathogens can

contaminate a carcass during slaughter or processing. When these resistant bacteria cause

illness in a person requiring medical treatment, medical therapy may be compromised if the

pathogenic bacteria are resistant to the drug(s) available for treatment. In England, in studies

of 5 400 strains of Campylobacter jejuni and 376 of Campylobacter coli reported by Frost &

Thwaites (1998: 4) and by Threlfall, Ward, Frost & Willshaw (2000: 4- 5), 11% were

resistant to ciprofloxacin at concentrations exceeding 8 mg/litre, with resistance being most

pronounced in C. coIi. It must be assumed that a proportion of ciprofloxacin-resistant isolates

originated in food producing animals.

In the United States of America, it has been demonstrated that a considerable increase

occurred in incidence of Campylobacter-resistant isolates in poultry, associated with the

licensing in the United States of America of fluoroquinolone antibiotics for use in chickens.

In the Netherlands, a direct association between the licensing of fluoroquinolones for water

medication for poultry and resistance development in animal isolates was demonstrated,

while at the same time resistance in human isolates increased. A similar situation has been

reported for Spain (Wegener, Aarestrup, Gerner-Smidt & Bager 1999). Campylobacter, the

most common bacterial cause of food-borne illness, infects an estimated 2.4 million people

annually in the United States of America. Fluoroquinolones (e.g. ciprofloxacin) are

commonly used in adults to reduce the severity and duration of the symptoms.

The continued use of fluoroquinolones in chickens threatens the efficacy of fluoroquinolones

for treatment of Campylobacter infections in humans, and so mitigating action is needed to

25

preserve the efficacy of fluoroquinolones (Rossiter, Joyce, Ray, Benson, Mackinson, Gregg,

Sullivan, Vought, Leano, Besser, Marano, Angulo: 1 & The EIP Food Networking Group

2000: 1). Each year, Salmonella bacteria infect an estimated 1.4 million persons in the United

States of America; these infections result in several hundred deaths annually. One of the most

common strains isolated from humans is multidrug-resistant (MR) Salmonella enterica

serotype typhimurium definitive type 104 (DT 104). This strain was first isolated from

humans in 1984 in the United Kingdom, where it emerged as a major cause of human illness

in the late 1980s, before its emergence in the United States of America and elsewhere in the

mid-1990s (Serrano 2005: 12).

Most of the infections are caused by Salmonella typhimurium DT 104, which is usually

resistant to ampicillin, chloramphenicol, streptomycin, sulphonamides and tetracycline, and

has acquired resistance against trimethoprim and fluoroquinolones, most probably because

affected groups of animals could only be treated with these antibiotics (Van den Bogaard &

Stobberingh 2000: 332). This strain was first isolated in the UK from exotic birds, and, with

the exception of a human outbreak in Scotland in the mid-1980s, it was not isolated from

human beings until 1989. During the next five years, the strain became an epidemic in bovine

animals, and common in poultry (particularly turkeys), pigs and sheep. It is often discussed

whether resistant Salmonella develops primarily as a result of antibiotic use in agriculture or

in human medicine. Although both uses always play a part, it is more probable that antibiotic

resistance in Salmonella-causing infection mainly reflects resistance developed in the animal

reservoirs. This is supported by the facts that humans are not often carriers of Salmonella

compared with food animals, that antibiotics are usually given to animals for long periods

and often in sub-therapeutic doses and, finally, that resistance to antibiotics used for food

animals (tetracycline, apramycin), but not for treatment of Salmonella in humans, has been

observed in Salmonella (Wegener et al. 1999: 56).

Human infection has been associated with the consumption of chicken, beef, pork sausages

and meat paste, and to a lesser extent with direct contact with farm animals. In the 1990s, the

infection was recognized in cattle and humans in the United States of America, and during

recent years this MR strain has been responsible for infections in European countries, Israel

and Canada (Threlfall et al. 2000: 4). It is important to note that all DT 104 isolates contained

26

the same cassette gene, which codifies for resistance irrespective of source (food animal or

human), or country of origin.

Since 1992, the DT 104 strain has acquired resistance against trimethoprim and ciprofloxacin,

and, as a consequence, since 1997, 15% of the isolates have been resistant to trimethoprim,

and 13% have shown decreased sensitivity to ciprofloxacine. The appearance of resistance to

trimethoprim has been attributed to the use of this drug to combat infections caused by DT

104. The emergence of isolates of MR DT 104 with reduced sensitivity to ciprofloxacin has

followed the licensing in the United Kingdom of a related fluoroquinolone drug,

enrofloxacin, for veterinary use. This drug has been used for prophylactic and therapeutic

purposes in poultry and cattle in the UK and as a consequence resistance against nalidixic

acid has rapidly emerged in food-producing animals in the United Kingdom, particularly

turkeys, chickens and cattle (Serrano 2005: 12).

In an outbreak of DT 104 in Denmark, attributed to the consumption of pork, lack of

response to fluoroquinolone has been described (Threlfall et al. 2000: 4). The Danish

researchers were unable to discover how the DT 104 strain entered the food chain. The pigs

suspected of carrying this resistant strain had not been fed any fluoroquinolones, but the

compounds may previously have been used at the farms. Wild animals or equipment may

have spread the bacteria environmentally, and concomitantly with globalization of trade such

outbreaks could become more common (Swint 1999: 1). More recently, in the light of these

findings, a series of proposals to ban the use of quinolones in food animals have been

proposed (Sundlof 2000: 1; Tollefson 2000: 1; Environmental Defense 2000: 1).

In countries that have banned certain sub-therapeutic uses of antibiotics, decreases in

resistance to those antibiotics have been reported, restoring the effectiveness of those

antibiotics for treating disease. For example, in Denmark, after a 1995 ban on the use of

avoparcin as a growth promoter, glycopeptide-resistant enterococci in Danish broiler flocks

declined from 82 to 12%. No reduction has been seen in swine, due probably to the facts that

swine production is continuous (in contrast to cyclical broiler production, which allows

complete cleaning between flocks) and that swine producers changed from avoparcin to

tylosine, which also selects for glycopeptides-resistant antibiotic, whereas Danish broiler

producers stopped using any kind of antimicrobial growth promoters. Nevertheless, in

27

Norway, vancomycin-resistant enterococci (VRE) were still isolated from broilers after three

years from its banning, and resistant genes were appearing in Lactococcus lactis and

Streptococcus bovis (Borgen, Serum, Wasteson & Kruse 2001: 91).

In Sweden, all antibiotics have been banned as growth promoters since 1986, including

avoparcin. There, avoparcin-resistant enterococci and VRE have not been isolated from pig

faecal samples. In other northern European countries, where avoparcin has been used as a

growth promoter, enterococci resistant to this antibiotic and also to vancomycin are common

in healthy people. In contrast, in United States of America, where agricultural uses of

avoparcin and vancomycin are banned, this kind of resistance is not observed (HHS

1999a&b). Another aspect of the resistance problem that has also to be considered is that

recently some similarities between bacterial resistance patterns to antibiotics and tobiocides

(antiseptics, disinfectants, preservatives) have been reported. Gram-negative bacteria that

have developed resistance to cationic biocides (chlorhexidine salts and quaternary ammonium

compounds) may also be resistant to some antibiotics (Russell 2000: 230). There is clear

evidence that, with an increase in the consumption of antimicrobial agents by humans or

animals, there is a resultant increase in antimicrobial resistance (Donabedian, Thal,

Hershberger, Perri, Chow, Bartlett, Jones, Joyce, Rossiter, Gay, Johnson, Mackinson, Debess,

Madden, Angulo & Zervos 2003: 1112).

2.11 Factors that encourage the spread of antibiotic resistance

The emergence and spread of antimicrobial resistance are complex problems driven by

numerous interconnected factors; many of which are linked to the misuse of antimicrobials

and are thus amenable to change. In turn, antimicrobial use is influenced by interplay of the

knowledge, expectations, and interactions of prescribers and patients, economic incentives,

characteristics of a country's health system, and the regulatory environment (WHO 2002: 3).

Patient-related factors are major drivers of inappropriate antimicrobial use. For example,

many patients believe that new and expensive medications are more efficacious than older

agents. In addition to causing unnecessary health care expenditure, this perception

encourages the selection of resistance to these newer agents as well as to older agents in their

class (WHO 2002: 3). Self-medication with antimicrobials is another major factor

contributing to resistance. Self-medicated antimicrobials may be unnecessary, are often

28

inadequately dosed, or may not contain adequate amounts of active drug, especially if they

are counterfeit drugs. In many developing countries, antimicrobials are purchased in single

doses and taken only until the patient feels better, which may occur before the pathogen has

been eliminated. Inappropriate demand can also be stimulated by marketing practices. Direct-

to-consumer advertising allows pharmaceutical manufacturers to market medicines directly to

the public via television, radio, print media, and the Internet. In particular, advertising on the

Internet is gaining market penetration, yet it is difficult to control with legislation due to poor

enforceability (WHO 2002: 4; Harrison & Svec 1998: 159 - 160).

Prescribers' perceptions regarding patient expectations and demands substantially influence

prescribing practice. Physicians can be pressured by patient expectations to prescribe

antimicrobials even in the absence of appropriate indications. In some cultural settings,

antimicrobials given by injection are considered more efficacious than oral formulations.

Such perceptions tend to be associated with the over-prescribing of broad-spectrum injectable

agents when a narrow-spectrum oral agent would be more appropriate. Prescribing “just to be

on the safe side" increases when there is diagnostic uncertainty, lack of prescriber knowledge

regarding optimal diagnostic approaches, lack of opportunity for patient follow-up, or fear of

possible litigation. In many countries, antimicrobials can easily be obtained in pharmacies

and markets without a prescription (WHO 2002: 3).

Patient compliance with recommended treatment is another major problem. Patients forget to

take medication, interrupt their treatment when they begin to feel better, or may be unable to

afford a full course, thereby creating an ideal environment for microbes to adapt rather than

be killed. In some countries, low quality antibiotics (poorly formulated or manufactured,

counterfeited or expired) are still sold and used for self-medication or prophylaxis (WHO

2002: 3).

Hospitals are a critical component of the antimicrobial resistance problem worldwide. The

combination of highly susceptible patients, intensive and prolonged antimicrobial use, and

cross-infection have resulted in nosocomial infections with highly resistant bacterial-

pathogens. Resistant hospital-acquired infections are expensive to control and extremely dif-

ficult to eradicate. Failure to implement simple infection control practices, such as hand

washing and changing gloves before and after contact with patients, is a common cause of

infection spread in hospitals throughout the world. Hospitals are also the eventual site of

29

treatment for many patients with severe infections due to resistant pathogens acquired in the

community. In the wake of the AIDS epidemic, the prevalence of such infections can be

expected to increase (Purdom 2007: 1; Pelczar et al. 1993: 912; Mandell et al. 1995: 151).

Veterinary prescription of antimicrobials also contributes to the problem of resistance. In

North America and Europe, an estimated 50% in tonnage of all antimicrobial production is

used in food-producing animals and poultry. The largest quantities are used as regular

supplements for prophylaxis or growth promotion, thus exposing a large number of animals,

irrespective of their health status, to frequently sub-therapeutic concentrations of

antimicrobials. Such widespread use of antimicrobials for disease control and growth

promotion in animals has been paralleled by an increase in resistance in those bacteria (such

as Salmonella and Campylobacter) that can spread from animals, often through food, to cause

infections in humans (Khachatourians 1998: 1).

2.12 Microbiology of Water.

2.12.1 Introduction to Microbiology of Water

The drinking water of most communities and municipalities is obtained from surface sources;

rivers, streams and lakes. Such natural water supplies, particularly streams and rivers, are

likely to be polluted with domestic and industrial wastes i.e., the used water of a community

(waste water). Municipal water-purification systems have been very effective in protecting

the inhabitants against polluted water. At the same time, as population centres grow, pollution

problems become more serious. A greater quantity of water is required, and the used water

must be disposed of, generally by returning it to a natural body of water in the vicinity, which

in turn may be the water supply source of another community or municipality (Pelczar et al.

1986: 593).

Water bodies are potential carriers of pathogenic microorganisms; as a result they can

endanger health and life. The pathogens that are frequently transmitted through water are

those which cause infections of the intestinal tract; namely typhoid and paratyphoid bacteria,

dysentery (bacillary and amoebic) and cholera bacteria as well as enteric viruses. The

causative organisms of these diseases are present in the faeces or urine of an infected person,

30

and when discharged may gain entrance into a body of water that ultimately serves as a

source of drinking water (Pelczar et al. 1986: 594).

Sources of faecal contamination to surface waters include wastewater treatment plants, on-

site septic systems, domestic and wild animal manure, and storm runoff. In addition to the

possible health risk associated with the presence of elevated levels of faecal bacteria, they can

also cause cloudy water, unpleasant odours, and an increased oxygen demand (USEPA 1985:

1).

2.12.2 Indicators of water pollution and presence of water-borne infections.

Municipalities usually treat drinking water to remove impurities and eliminate contamination

especially pathogenic microorganisms. Therefore regular testing must be done to ensure the

water is safe. It is not feasible to test for pathogens in the water on a regular basis (due in part

to cost limitation and time) so the accepted method tests for coliform bacteria and faecal

streptococci, a sure sign of faecal contamination and an indication of the possible presence of

pathogenic bacteria, viruses, and protozoans that also live in human and animal digestive

systems (Nester et al. 1995: 749; USEPA 1985: 1).

Coliforms are defined as a group of Gram-negative, rod-shaped, non-spore-forming, aerobic

and facultatively anaerobic bacteria that ferment lactose, forming acid and gas within 46hrs at

35oC. These bacteria are commonly found in soil and in the gut and faeces of warm-blooded

animals. Their presence in water may indicate contamination with human and/or animal

faeces. For municipal water supplies, a maximum of 1 coliform organism per 100mls is

considered safe for potable water. Higher numbers are acceptable in water used for other

purposes, such as recreational waters (Nester et al. 1995: 749; Pelczar et al. 1993: 598 - 99).

The classical species of this group are Escherichia coli and Enterobacter aerogenes. These

microorganisms have a common relationship with other enteric organisms which include;

Salmonella, Shigella, Klebsiella, Proteus, Serratia and other genera. Escherichia coli is a

normal inhabitant of the intestinal tract of humans and animals. Enterobacter aerogenes is

most frequently found on grains and plants but may occur in human and animal faeces. These

species bear a very close resemblance to each other in their morphological and cultural

31

characteristics. Consequently, it is necessary to resort to biochemical tests for differentiation

(Pelczar et al. 1986: 596 - 97).

2.12.3 Water-borne diseases and the source of antibiotic-resistant bacteria in water.

Pollution of water occurs from a variety of sources. Contamination of water with pathogenic

organisms remains a major cause of epidemics of disease and the incidence of antibiotic

resistant bacteria due to overuse in aquatic environment has greatly increased concern by

medical experts. At the present time antibiotic-resistant bacteria can be found in all

environments and under all kinds of climate. Thus antibiotic resistance has been reported in

rivers and coastal areas, in domestic sewage, in surface water and sediments, in lakes, in

sewage polluted sea waters and in drinking water (Nester et al. 1995: 155; Mezriou & Baleus

1994: 2404).

Aquaculture is becoming a more concentrated industry of fewer but much larger farms.

Infective diseases are always a hazard, and may cause major stock losses and problems of

animal welfare. To control infectious diseases in aquaculture, the same strategies used in

other areas of animal production are employed. Whenever antibiotics are used, they should be

strictly controlled under the same code applying to other veterinary medicines. As there are

no antibiotics specifically designed for aquaculture, authorized products developed for other

areas of veterinary medicine are used (Serrano 2005: 23 - 24).

In the United States of America, the majority of fish farming enterprises where antibiotics

might be used have pond-like or tank structures, rather than open-water habitats, like oceans

or lakes. Generally, after harvest, large commercial ponds for fish are not drained, so high

levels of drugs may still remain, affecting newly growing fish, which are then exposed to the

antibiotic residues and actively-resistant bacteria (Committee on Drug Use in Food Animals

1999: 1 - 8).

It is estimated that nearly 150 pounds of antibiotics are applied per acre (≈170 kg/ha) of

salmon harvested in the United States of America, and since pens are placed in natural

seawaters, antibiotics and the resultant resistant bacteria are in contact with the environment.

Some countries, such as Norway, utilize natural structures like fjords for salmon farming and,

32

for this reason; there are concerns about the wastes that collect in the bottom of fjords

(FAO/NACA/WHO 1997: 3).

Aquaculture promotes the production of various sizes and types of aquatic organisms, and the

use of antibiotics and drugs in the fish industry is complicated because of the need to

administer the compounds usually directly into the water where the organisms live. Several

factors have to be considered: the safety of aquatic fish products, the integrity of the

environment, the safety of target animals, and the safety of the persons administering the

compounds (Serrano 2005: 25).

Antibiotics effective in human medicine, including oxytetracycline, sulfamerazine and

ormethoprim, are used for treatment of bacterial infections in salmon, catfish, trout and other

commercially-raised fish. The most frequent fish infections treated with antibiotics are skin

ulcers, diarrhoea and blood sepsis. The micro-organisms responsible for these infections

belong to bacterial families that also produce infections in humans. Therefore, transference of

antibiotic resistance is highly probable. Even when treatment is suspended before the fish is

sold for consumption, the resistance can still be transmitted. For this reason, the

environmental and health impact of the use of antibiotics in aquaculture is recognized; in

many countries the use of antibiotics in aquaculture is under veterinary medicine control

(Serrano 2005: 25).

In situations where the water-borne infection is due to antibiotic-resistant bacteria, the

infected patients may fail to respond to antibiotics. Sewage-polluted water is often a common

source of diseases. The antibiotics used in the treatment of human infectious diseases and

also in animal diseases treated in veterinary practices present residues in alimentary canals

which are subsequently excreted and then find their way into sewage. Indiscriminate use of

antibiotics may result in surviving populations of antibiotic-resistant bacteria being shed with

faeces and urine and this contaminates soil and aquatic environments (FDA 2000a & b).

33

2.12.4 Brief overview of some clinically significant isolates identified using the API 20E

tests in this study.

Pantoea agglomerans

Formerly called Enterobacter agglomerans, but now renamed Pantoea agglomerans; is a

Gram-negative bacterium that belongs to the family Enterobacteriaceae. This bacterium is

known to be an opportunistic pathogen in the immuno-compromised causing wound, blood

and urinary tract infections. It is commonly isolated from plant surfaces, seeds, fruits

(especially mandarin oranges), and animal or human faeces (Winn, Allen, Janda, Koneman,

Propcop, Schreckenberger &Woods 2006: 211 - 302).

It is difficult to differentiate easily from other members of this family such as Enterobacter,

Klebsiella and Serratia species. The amino acid utilization pattern of lysine, arginine and

orinithine will distinguish Pantoea spp. from the others. Pantoea is negative for utilization of

these three amino acids (Barnes, Wiederhold, Micek, Polish & Ritchie 2003: 539).

Enterobacter cloacae

Enterobacter cloacae are clinically significant Gram-negative, facultatively-anaerobic, rod-

shaped bacterium. Enterobacter cloacae are sometimes associated with urinary tract and

respiratory tract infections. Treatment with cefepime and gentamycin has been reported

(Barnes et al. 2003: 540).

Enterobacter species, particularly Enterobacter cloacae and Enterobacter aerogenes, are

important nosocomial pathogens responsible for various infections, including bacteremia,

lower respiratory tract infections, skin and soft-tissue infections, urinary tract infections

(UTIs), endocarditis, intra-abdominal infections, septic arthritis, osteomyelitis, and

ophthalmic infections. Enterobacter species can also cause various community-acquired

infections, including UTIs, skin and soft-tissue infections, and wound infections, among

others. (Barnes et al. 2003: 540 - 541).

Risk factors for nosocomial Enterobacter infections include hospitalization for longer than 2

weeks, invasive procedures within the timeline of 72 hours, treatment with antibiotics in the

past 30 days, and the presence of a central venous catheter. Specific risk factors for infection

with nosocomial multidrug-resistant strains of Enterobacter species include the recent use of

34

broad-spectrum cephalosporins or aminoglycosides and ICU care (Fraser, Arnette & Sinave

2008:1).

These "ICU bugs" cause significant morbidity and mortality, and infection management is

complicated by resistance to multiple antibiotics. Enterobacter species possess inducible β-

lactamases, which are undetectable in vitro but are responsible for resistance during

treatment. Physicians treating patients with Enterobacter infections are advised to avoid

certain antibiotics, particularly third-generation cephalosporins, because resistant mutants can

quickly appear. The crucial first step is appropriate identification of the bacteria.

Antibiograms must be interpreted with respect to the different resistance mechanisms and

their respective frequency, as is reported for Enterobacter species, even if routine in vitro

antibiotic susceptibility testing has not identified resistance (Fraser et al. 2008:1).

Enterobacter species rarely cause disease in healthy individuals. This opportunistic pathogen,

similar to other members of the Enterobacteriaceae family, possesses an endotoxin known to

play a major role in the pathophysiology of sepsis and its complications (Fraser et al.

2008:1).

Rahnella aquatilis

Rahnella aquatilis is the only species of the new genus Rahnella within the family

Enterobacteriaceae; a rare enteric gram-negative rod which is usually found in fresh water,

and has been isolated from the bronchial washing of a patient with acquired

immunodeficiency syndrome (Harrell, Cameron & O‟Hara 1989:1671). R. aquatilis has been

known to cause septicaemia in immuno-compromised individuals (Maraki, Samonis,

Marnelakis & Tselentis 1994:2706).

Klebsiella spp.

Klebsiella are found widely throughout nature and are often found as part of the normal flora

of the GI tract, throat and skin of man and animals. K. pneumoniae and K. oxytoca are

responsible for almost all the infections associated with humans. Klebsiella oxytoca is

characterized by its ability to produce indole. Clinically it resembles Klebsiella pneumoniae;

however, nosocomial strains tend to exhibit a greater propensity to develop antibiotic

resistance. The number of infections caused by K. pneumoniae, however, is far greater in

number than those caused by K. oxytoca; thus, K. pneumoniae is the most medically

35

important of the group. Pneumonia caused by K. pneumoniae is the most common infection

caused by this microorganism inside and outside of healthcare facilities. Both K. pneumoniae

and K. oxytoca are associated with neonatal bacteremia. Most cases have occurred among

premature infants. K. pneumoniae is also a common causative agent of Urinary Tract

Infections (UTI). These urinary tract infections are usually clinically indistinguishable from

those caused by other common urinary tract pathogens. Most of these infections are the result

of urinary catheterization and are nosocomial in nature (Umeh & Berkowitz 2006:1).

In the hospital and long-term care setting, Klebsiella spp. are occasionally isolated from

wounds and abscesses. Their pathogenic role, however, is often questionable as they are often

colonizers causing no symptoms as opposed to being actual pathogens. Members of the genus

Klebsiellae are found as normal flora in the intestine; some strains of Klebsiella are

considered “enterotoxigenic” and are capable of causing diarrhoea. This is especially true in

immuno-compromised and immuno-suppressed individuals (Umeh & Berkowitz 2006:1).

Extensive use of broad-spectrum antibiotics in hospitalized patients has led to both increased

carriage of Klebsiellae and, subsequently, the development of multidrug-resistant strains that

produce extended-spectrum β-lactamase (ESBL). These strains are highly virulent, show

capsular type K55, and have an extraordinary ability to spread. Most outbreaks are due to a

single clone or single gene; the bowel is the major site of colonization with infection of the

urinary tract, respiratory tract, and wounds. Bacteremia and significant increased mortality

have resulted from infection with these species (Umeh & Berkowitz 2006:1).

In 1981, Bagley, Seidler & Brenner, and Izard, Ferragut, Gavini, Kersters, DeLey & Leclerc

described two new environmental species, Klebsiella planticola and Klebsiella terrigena, .

Originally thought to occur solely in aquatic, botanic, and soil environments, these species

was also recently isolated from human clinical specimens. These investigations found a

surprisingly high frequency of K. planticola among clinical Klebsiella isolates (Bouza &

Cercanado 2002: 217; Umeh & Berkowitz 2006:1). These species were differentiated from K.

pneumoniae and K. oxytoca by using tests for temperature-dependent fermentation of

glucose, acid production from melezitose and L-sorbose, utilization of carbon sources, and

gas production from lactose at 44.5°C (fecal coliform test). Studies from France and

Germany suggest that up to 19% of Klebsiella spp. identified in clinical settings is actually K.

planticola. K. planticola is not routinely identified because clinical identification protocols do

not include the tests that are necessary for its identification. Test kits and automated methods

36

have not been able to correctly identify these environmental organisms because they are not

included in the identification databases of most diagnostic products nor are substrates

included on panels that would differentiate them(Westbrook, O‟Hara, Roman & Miller 2000:

1495 – 1497)

In 1998, Podschun, Acktun, Okpara, Linderkamp, Ullmann & Borneff-Lipp isolated K.

planticola from neonates; these were obtained from oropharyngeal and rectal swabs.

Klebsiella belong to the eight most common bacterial pathogens causing nosocomial

infections. Immuno-compromised patients, especially elderly people and infants, comprise

the population most at risk. In pediatrics, too, nosocomial Klebsiella infections are

remarkably troublesome, particularly in premature infants and intensive care units. Pediatric

patients are easily colonized by Klebsiella spp. Intestinal and oropharyngeal colonization acts

as the main reservoir for nosocomial outbreaks.

Kluyvera ascorbata

Kluyvera is a relatively newly described genus in the family Enterobacteriaceae that

infrequently causes infections in humans. The organism has been isolated from various

clinical specimens, but its significance has not been clearly established. In fact, it has been

regarded as saprophytic, opportunistic, or pathogenic. In the early 1980s, the organism was

regarded mostly as a benign saprophyte that colonized predominantly the respiratory,

gastrointestinal, or urinary tract. More recently, however, diverse infections occurring under

various host conditions have been reported. Most of these infections involved the

gastrointestinal or urinary tract and the soft tissues. Bacteremia and other serious infections

have also occurred (West, Vijayan & Shekar 1998; Dollberg, Gandacu & Klar 1990).

Kluyvera is a small, flagellated, motile Gram-negative bacillus that clearly belongs to the

family Enterobacteriaceae (Asai, Iizuka & Komagata 1962). The organism is distinguished

from other related genera by its ability to use citrate and malonate, decarboxylate lysine and

ornithine and to produce large quantities of α-ketoglutaric acid during the fermentation of

glucose. Kluyvera grows well in ordinary culture media, and its colonies resemble those of

Escherichia (Kluyver & Van Niel 1936). No specific virulence factor has been identified, but

like other Enterobacteriaceae, the organism has a lipopolysaccharide complex and surface

antigens that may confer virulence. The genus has 3 species: Kluyvera ascorbata, the type

species of the genus and the species most frequently isolated in clinical specimens; Kluyvera

37

cryocrescens, a strain found predominantly in the environment; and Kluyvera species group

3, a strain infrequently isolated from any source. Kluyvera is present in the environment as

free-living organisms in water, soil, sewage, hospital sinks, and food products of animal

origin. In humans, it is usually isolated from sputum, urine, and stool samples. Kluyvera is

part of the normal flora of the human digestive tract, but it is usually associated with low

bacterial counts. This might explain why its isolation in clinical infections is rare. It is

unknown whether Kluyvera infections are predominantly endogenous or environmentally

acquired or whether both routes are equally important. In 2001, Sarria, Vidal & Kimbrough

isolated K. ascorbata from 5 cases of infections involving multiple organs and systems.

Escherichia coli

Escherichia coli (abbreviated as E. coli) are a large and diverse group of bacteria found in the

gut of humans and ruminants. Although most strains of E. coli are harmless, others are

capable of causing diseases. Virulent strains of E. coli can cause gastroenteritis, urinary tract

infections, and neonatal meningitis. In rare cases, virulent strains are also responsible for

hæmolytic-uremic syndrome (HUS), peritonitis, mastitis, septicemia and Gram-negative

pneumonia (Todar 2008:2). Still other kinds of E. coli are used as markers for water

contamination (USEPA 1985:4).

Some kinds of E. coli cause disease by making a toxin called Shiga toxin. The bacteria that

make these toxins are called “Shiga toxin-producing” E. coli or STEC for short. This group

are also called verocytotoxic E. coli (VTEC) or enterohemorrhagic E. coli (EHEC); these all

refer generally to the same group of bacteria (Karch,Tarr, Bielaszewska 2005:415). The most

commonly identified STEC in North America is E. coli O157:H7 (often shortened to E. coli

O157 or even just “O157”). Usually news reports about outbreaks of “E. coli” infections

mostly refer to E. coli O157. This particular strain is linked to the 2006 United States E. coli

outbreak of fresh spinach. Severity of the illness varies considerably; it can be fatal,

particularly to young children, the elderly or the immuno-compromised, but is more often

mild. Earlier, poor hygienic methods of preparing meat in Scotland killed seven people in

1996 due to E. coli poisoning, and left hundreds more infected (Dundas, Todd, Stewart,

Murdoch, Chaudhuri & Hutchinson 2001: 929).

In addition to E. coli O157, many other kinds (called serogroups) of STEC cause disease.

These other kinds are sometimes called “non-O157 STEC.” E. coli serogroups O26, O111,

38

and O103 are the non-O157 serogroups that most often cause illness in people in the United

States. Around 5–10% of those who are diagnosed with STEC infection develop a potentially

life-threatening complication known as hemolytic uremic syndrome (HUS) which could lead

to kidney failure and death. Infection is usually as a result of ingestion of the organism

(WHO 2002:1).

Serratia spp.

Serratia species are opportunistic Gram-negative bacteria classified in the tribe Klebsielleae

and the large family Enterobacteriaceae. Serratia marcescens is the primary pathogenic

species of Serratia. Rare reports have described disease resulting from infection with Serratia

plymuthica, Serratia liquefaciens,

Serratia rubidaea,

and Serratia odorifera (Hejazi &

Falkiner 1997: 903).

Some strains of S. marcescens are capable of producing a pigment called prodigiosin, which

ranges in colour from dark red to pale pink, depending on the age of the colonies. S

marcescens has a predilection for growth on starchy foodstuffs, where the pigmented

colonies are easily mistaken for drops of blood (Bennett & Bentley 2000: 2). In the hospital,

Serratia species tend to colonize the respiratory and urinary tracts, rather than the

gastrointestinal tract in adults and is responsible for most catheter-associated bacteraemia

cases. Since 1950, S. marcescens has steadily increased as a cause of human infection, with

many strains resistant to multiple antibiotics (Hejazi & Falkiner 1997: 907).

Serratia infection is responsible for about 1.4% of nosocomial infections of the bloodstream,

lower respiratory tract, urinary tract, surgical wounds, skin and soft tissues in adult patients

in the United States. Outbreaks of S. marcescens meningitis, wound infections, and arthritis

have occurred in pediatric wards (Ania 2008:1; Auwaerter 2007:1). S. marcescens can cause

infection in several sites, including the urinary tract, respiratory tract, wounds, and the eye,

where it may cause conjunctivitis, keratitis, endophthalmitis and tear duct infections (Cohen,

Flynn & Miller 1997: 195). It is also a rare cause of endocarditis and osteomyelitis

(particularly in people who use intravenous drugs recreationally), pneumonia and meningitis.

Most S. marcescens strains are resistant to several antibiotics because of the presence of R-

factors all are considered intrinsically resistant to ampicillin, macrolides, and first-generation

cephalosporins such as cefalexin (Ania 2008:1; Auwaerter 2007:1).

39

Serratia ficaria was first described in 1979 by Grimont, Grimont & Starr. S. ficaria produces

non-pigmented, lactose-negative colonies which give off a potato-like odour. This odour is a

primary feature of S. ficaria and distinguishes it from S. plymuthica and S. marcescens. In

1994, Darbas, Jean-Pierre & Paillisson showed that S. ficaria caused septicaemia as observed

from blood cultures collected post operation for antrectomy.

Citrobacter freundii

Citrobacter species are members of the aerobic Enterobacteriaceae family, Gram-negative

bacilli commonly found in water, soil, food and the intestinal tracts of animals and humans

(Gupta, Yadav, Chaoudhary & Arora 2003: 765; Forbes, Sahm & Weissfeld 2002: 617).

Citrobacter species use citrate as a carbon source. Citrobacter species have the ability to

accumulate uranium by building phosphate complexes. Citrobacter freundii has also been

investigated for biodegradation of tannic acid used in tanneries.

Citrobacter species cause a wide spectrum of infections in the urinary tract, blood, superficial

wounds, skin, peritoneum and several other normally sterile sites; most frequently, their

hosts

are hospitalized and immuno-compromised patients (Gupta et al., 2003:765; Forbes et al.,

2002: 617; Kim, Woo, Ryu & Kim 2003: 202). Citrobacter freundii and Citrobacter

diversus are often the cause of these opportunistic infections. Citrobacter spp. cause neonatal

meningitis but are unique in their frequent association with brain abscess formation. They

also can cause infections of the urinary tract infections and nosocomial pneumonia (hospital

pneumonia) (Kim et al., 2003)

Salmonella spp.

Salmonella is a genus of rod-shaped, Gram-negative, non-spore forming, predominantly

motile Enterobacteria that are peritrichously flagellated. Salmonella are facultative anaerobes

and are closely related to the Escherichia genus and are found worldwide in warm and cold-

blooded animals, in humans, and in nonliving habitats. They cause illnesses in humans and

many animals, such as typhoid fever, paratyphoid fever, and the food-borne illness

salmonellosis (Ryan & Ray 2004: 362 - 8). Salmonella infections are zoonotic; they can be

transmitted by humans to animals and vice versa. Infection via food is also possible. A

distinction is made between enteritis Salmonella and typhoid/paratyphoid Salmonella,

whereby the latter because of a special virulence factor and a capsule protein (virulence

40

antigen) can cause serious illness, such as Salmonella enterica subsp. enterica serovar Typhi,

or Salmonella typhi). Salmonella typhi is adapted to humans and does not occur in animals

(Ryan & Ray 2004: 362 - 8).

According to the Centre for food security and public safety (2005:8); enteritis Salmonella

(e.g., Salmonella enterica subsp. enterica serovar Enteritidis) can cause diarrhoea, which

usually does not require antibiotic treatment. However, people at risk such as infants, small

children, the elderly, HIV patients and those with suppressed immunity can become seriously

ill. Children with sickle cell anemia who are infected with salmonella may develop

osteomyelitis.

Salmonellosis is one of the most common and widely distributed food borne diseases. It

constitutes a major public health burden and represents a significant cost in many countries.

Millions of human cases are reported worldwide every year and the disease results in

thousands of deaths. Since the beginning of the 1990s, strains of Salmonella which are

resistant to a range of antimicrobials, including first-choice agents for the treatment of

humans, have emerged and are threatening to become a serious public health problem. This

resistance results from the use of antimicrobials both in humans and animal husbandry.

Multi-drug resistance to "critically important antimicrobials" are compounding the problems

(WHO 2005:1).

Research done in 1979/80 and 1989/90 identified Salmonella isolates (Salmonella

typhimurium definitive type 104) that were exhibiting antibiotic and multidrug resistance to

ampicillin, chloramphenicol, streptomycin, sulfonamides and tetracycline (Lee, Puhr,

Maloney, Bean & Taupe 1994: 128 - 34; Angulo 1997: 414).

Aeromonas hydrophila

Aeromonas hydrophila is a heterotrophic, Gram-negative, rod shaped bacterium with polar

flagella, mainly found in areas with a warm climate. This bacterium can also be found in

fresh, salt, marine, estuarine, chlorinated, and un-chlorinated water. Aeromonas hydrophila

can survive in aerobic and anaerobic environments. This bacterium can digest materials such

as gelatin, and haemoglobin. This bacterium is the most well known of the six species of

Aeromonas. It is also very hard to kill, because it is a very resistant bacterium. Aeromonas

hydrophila is resistant to chlorine, refrigeration or cold temperatures (Hayes 2008:1). The

41

toxicity of this species comes from its structure. When it enters the body of its victim, it

travels through the bloodstream to the first available organ. It produces Aerolysin Cytotoxic

Enterotoxin (ACT), a toxin that can cause tissue damage (Chopra, Xu, Ribardo, Gonzalez,

Kuhl, Peterson & Houston 2000: 2808). It is known as a pathogenic bacterium. Aeromonas

hydrophila, Aeromonas caviae and Aeromonas sobria are all considered to be “opportunistic

pathogens,” meaning they only infect hosts with weakened immune responses. Though

Aeromonas hydrophila is considered a pathogenic bacterium, scientists have not been able to

prove that it is the actual cause of some of the diseases it is associated with. It is believed that

this bacterium aids in the infection of diseases, but does not cause the diseases themselves.

Aeromonas hydrophila also excretes extracellular proteins which are toxic to other cells.

These are aerolysin, glycerophospholipid:cholesterol acyltransferase (GCAT), and serine

protease. Another major chemical that contributes to pathogenicity is hemolysin (Chopra et

al., 2000: 2808 - 2818; Hayes 2008:1).

Aeromonas hydrophila can cause both intestinal and non-intestinal infections in humans, and

can often be fatal (Chopra & Clifford 1999: 1130). Some of the diseases that Aeromonas

hydrophila and other Aeromonas species can cause include: septicemia, meningitis,

pneumonia, and gastroenteritis (FDA 2008:1; Farmer, Arduino & Hickman-Brenner 2005:

3028; Kirov & Hayward 1993: 54 - 58). There are many factors influencing the toxicity of

Aeromonas hydrophila. For example, this species is able to resist complement-mediated lysis.

It has been suggested that Aeromonas hydrophila causes human diarrhea, but this has not yet

been verified. The research of Albert, Ansaruzzaman, Talukder, Chopra, Kuhn, Rahman,

Faruque, Islam, Sack & Mollby (2000: 3785 - 90) indicates mixed infections, which has been

illustrated in a previous study as well. This finding suggests that Aeromonas organisms are

not true pathogens, but work with others to produce infection. There are three major wound

infections caused by Aeromonas hydrophila: cellulitis, myonecrosis, and ecthyma

gangrenosum. Cellulitis is the most common, and occurs as the result of injury or sepsis.

Myonecrosis and ecthyma gangrenosum are less common, and tend to occur in immuno-

compromised individuals. However, Aeromonas hydrophila is a very prevalent species, and is

capable of affecting immuno-competent people as well. At one point, it was believed this

species did not pose a threat to healthy individuals, but the work of Chopra & Clifford

(1999:1137) illustrates that Aeromonas hydrophila is more harmful than was previously

believed. Aeromonas hydrophila is resistant to many common antibiotics such as penicillin

and ampicillin (FDA 2008:1).

42

As a consequence of its prevalence in aquatic environments, Aeromonas hydrophila can

cause serious pathology in fish. It can cause tail rot, fin rot, haemorrhagic septicaemia, scale

protrusion disease, and ulcer disease. Systemic infections usually attack the liver or kidneys.

Aeromonas hydrophila is also responsible for a disease called Red Leg, which occurs in

Xenopus species of frogs. This disease causes internal haemorrhaging, and is often fatal. It is

similar to haemorrhagic septicaemia, which is also known as Red-Sore Disease. However,

Aeromonas hydrophila is naturally found in fish gut. Infection from this bacterium is usually

the result of stress (Cipriano 2001:1). Work done by King (2000:1) showed the development

of resistance to oxytetracycline by Aeromonas spp. as a result of its use in aquaculture.

Raoultella ornithinolytica

Raoultella ornithinolytica (formerly Klebsiella ornithinolytica) is a Gram-negative aerobic

bacillus in the family Enterobacteriaceae. This species has been related to histamine-

producing bacteria causing subsequent fish poisoning (Kanki, Yoda, Tsukamoto & Shibata

2002: 3462). R. ornithinolytica has also been isolated from dentin of infected root canals

(Nakajo, Nakazawa, Iwaku & Hoshino 2004: 390). Human infections caused by bacteria of

the genus Raoultella are infrequent, and spontaneously occurring bacteraemia cases have not

been reported. However, Morais, Daporta, Bao, Campello & Andrés (2009: 869) presented a

case of enteric fever-like syndrome and bacteraemia caused by R. ornithinolytica. R.

ornithinolytica is an uncommon cause of enteric fever-like syndrome characterized by fever,

headache, and abdominal pain that may be clinically indistinguishable from enteric fever

caused by Salmonella enterica serovar Typhi or other salmonellae (Morais et al. 2009: 869).

R. ornithinolytica has been isolated from the gut of fish, ticks, and termites and from

estuarine water (Henriques, Fonseca, Alves, Saavedra, Correia 2006: 938; Kamanda Ngugi,

Khamis Tsanuo, Iddi Boga 2007: 87; Montasser 2005: 95), and it has been shown to produce

histamine, contributing to fish poisoning (Becker, Southwick, Reardon, Berg, MacCormack

2001: 1327; Kanki et al., 2002: 3463; Lopéz-Sabater, Rodriguez-Jerez, Hernandez-Herrero &

Mora-Ventura 1996: 416). Fish poisoning (scombroid syndrome) has been associated with

the consumption of scombroid fish, such as tuna, bonito, sardine, and mackerel. Klebsiella

pneumoniae and Klebsiella oxytoca are the best-known histamine-producing bacteria in fish.

However, many of the histamine-producing bacteria from fish first identified as K.

pneumoniae or K. oxytoca by commercialized systems were later correctly identified as

Raoultella planticola as a result of additional tests (Kanki et al. 2002: 416). Histamine

43

(scombroid toxin) poisoning occurs when persons ingest fish in which the bacteria have

converted histidine to histamine, a process that can usually be controlled by storage at low

temperatures. Scombroid syndrome has an incubation period of 1 min to 3 hours after eating

tuna or other fish and manifests with facial flushing, dizziness, vomiting, diarrhoea, other

gastrointestinal symptoms, dyspnea, headache, burning of the mouth, urticaria, and

generalized pruritus, but the symptoms usually resolve in a few hours (Becker et al. 2001:

1329; Swaminathan, Beebee & Besser 1999: 174 - 190).

R. ornithinolytica has been shown to be resistant in vitro to ampicillin and other commonly

used antibiotics (Hostacká & Klokocniková 2001: 117). This resistance can be associated

with the presence of β-lactamases (Walckenaer, Poirel, Leflon-Guibout, Nordmann & Niolas-

Chanoine 2004: 311).

2.13 Purpose and aims of study

The general aim of this study is to investigate the presence of antibiotic resistant coliforms in

the Rietspruit River, which is a major source of water to the inhabitants of the Sebokeng area

and a significant source of water to the Gauteng province in general.

The objectives are to:

1. Determine the number of types of antibiotic resistant coliforms at three different

sampling points at different times of the year 2009;

2. Ascertain if there are any number of types of multiple antibiotic resistances present in

coliforms at these sampling points;

This study may contribute to:

1. Providing data on antibiotic resistance as a tool to enable the authorities to take

precautions that will prevent the spread of antibiotic resistant bacteria; and

2. Enabling the public to realise the consequences of the spread of antibiotic resistance

among bacteria.

44

CHAPTER 3

MATERIALS AND METHODS

3.1 Introduction to Materials and Methods

The materials and methods used in this study to isolate Gram-negative bacteria, specifically

coliforms, showing multiple drug resistance are described in this chapter.

3.2 Study Area

The study area was a portion of the Rietspruit River located within the premises of the

Sebokeng Waste Water Care Works Emfuleni and the downstream which is located within an

informal settlement in the Sebokeng Area.

Sampling Point 1 (Upstream): The upstream of the Rietspruit River has two branches; the

Eastern branch flows from Johannesburg through Bushkoppies, Goudkoppies, Orange farm,

Ennerdale, Evaton and Sebokeng. The Western branch comes through Mogale (Krugersdorp)

and Carltonville. These areas have large concentrations of mine lands and as a result

contribute alkalinity to the river water from chemical run-off used in gold purification

processes. Along this route are informal settlements and this river serves as their source of

domestic water supply. This also impacts on the final constitution of the river as waste water

both industrial and domestic are dumped into this water body.

Sampling Point 2 (Final Effluent): These samples were taken from the final effluent after

treatment in the Water Works; this treatment includes collecting the river water in quantities

as large as 150 mega-litres into maturation ponds and settling tanks where sedimentation

takes place and the natural process of aerobiosis and anaerobiosis allows the majority of the

microorganisms to die off. The final stage of treatment is chlorination. A limitation to the

chlorination process is that it is costly and in some instances it is by-passed.

Sampling Point 3 (Down Stream): The water, after treatment, is discharged back into the

river. The river downstream of the treatment plant also flows through the Sebokeng area.

Along this route are informal settlements with a significant presence of livestock (cattle)

reared by members of the informal settlement.

45

These sampling points were chosen for the study because water from the Rietspruit River,

after purification, is used for human consumption, recreational purposes, agricultural and

industrial uses. Although, the Downstream receives water from the sewage treatment plant

after treatment; majority of the informal settlements along the Rietspruit River route still

dump both human and domestic waste into the water body without prior treatment and this is

a definite way of introducing faecal contamination. As a result it is of the utmost importance

to investigate the microbiological quality of water from this source. Undesirable water quality

can impact negatively on human health. Prevalence of drug-resistant coliforms in water

supplies requires re-evaluation of water quality standards as well as the introduction of a

more advanced purification process for sewage before discharge into the environment.

3.3 Sampling

Water samples were collected from all three sampling areas during three seasons in a year i.e.

winter, spring and summer (February, June and September) of 2009. Water samples were

collected in 1000ml sterile glass bottles on the same day within a 2-hour period and brought

back to the laboratory. Some onsite analyses (pH, temperature and turbidity) were carried out

at the sampling point. The elapsed time between collection and processing was less than two

hours. Water samples for later analyses were stored in a refrigerator at 4oC. Water samples

were collected from shallow areas by directly dipping the bottles into the surface of the water.

A volume of 100ml of water was taken after shaking the bottles and was filtered through

membrane filters. These membrane filters were placed on plates of m.FC agar, a dehydrated

medium manufactured by Merck used in the selective isolation of faecal coliforms. The

composition of m.FC is given in Appendix A.

3.4 Processing of the Water Samples.

3.4.1 Chemical Oxygen Demand (COD).

In environmental chemistry, the chemical oxygen demand (COD) test is commonly used to

indirectly measure the amount of organic compounds in water. Most applications of COD

determine the amount of organic pollutants found in surface water (e.g. lakes and rivers),

making COD a useful measure of water quality. It is expressed in milligrams per litre (mg/L),

which indicates the mass of oxygen consumed per litre of solution. Because COD measures

46

the oxygen demand of organic compounds in a sample of water, it is important that no

outside organic material be accidentally added to the sample to be measured. To control for

this, a so-called blank sample is required in the determination of COD (and BOD, for that

matter). A blank sample is created by adding all reagents (e.g. acid and oxidizing agent) to a

volume of distilled water. COD is measured for both the water and blank samples, and the

two are compared. The oxygen demand in the blank sample is subtracted from the COD for

the original sample to ensure a true measurement of organic matter. The COD level can be

determined more readily than BOD, but this measurement does not indicate how much of the

waste can be decomposed by biological oxidation. Simply put, the higher the COD: the

higher the water pollution.

A volume of 2ml of sample water was added to each test-tube containing commercial

reagents; (1) Nanocolor® CSB 40 with COD measuring range of 2 – 40mg/l, (2) Nanocolor®

CSB with COD measuring range of 15 – 160mg/l and (3) Nanocolor® CSB with COD

measuring range of 100 – 1500mg/l. The COD digester (Nanocolor® Vario 3) was

programmed for 2 hours at a temperature of 120oC. The test-tubes were left to cool after

which the COD of each of the samples at various ranges was taken in a COD meter

(Macherey-Nagel Nanocolor® 500D).

3.4.2 Biological Oxygen Demand (BOD).

BOD is the measure of the amount of oxygen taken up by aerobic microorganisms that

decompose organic waste matter in water. It is therefore used as a measure of the amount of

certain types of organic pollutant in water. BOD is calculated by keeping a sample of water

containing a known amount of oxygen for five days at 20°C. The oxygen content is measured

again after this time. A high BOD indicates the presence of a large number of

microorganisms, which suggests a high level of pollution. It is used in water quality

management and assessment, ecology and environmental science. BOD is not an accurate

quantitative test, although it could be considered as an indication of the quality of a water

source. BOD can be used as a gauge of the effectiveness of wastewater treatment plants. The

BOD5 test measures the rate of oxygen uptake by micro-organisms in a sample of water at a

temperature of 20°C and over an elapsed period of five days in the dark. In theory the

expected BOD5 value is approximately 80% of the COD value.

47

The method used in the present study was the Manometric method (this method is limited to

the measurement of the oxygen consumption due only to carbonaceous oxidation. Ammonia

oxidation is inhibited). The OxiTop® BOD measuring device was used; the principle is

based on measuring pressure differences via piezoresistive electronic pressure sensors.

Measurements are taken automatically for a 5-day period. The sample is kept in a sealed

container fitted with a pressure sensor. A substance-absorbing carbon dioxide (typically

LiOH or NaOH) is added in the container above the sample level. The sample is stored in

conditions identical to the dilution method. Oxygen is consumed and, as ammonia oxidation

is inhibited, carbon dioxide is released. The total amount of gas, thus the pressure, decreases

because carbon dioxide is absorbed. From the drop of pressure, the electronic device

computes and displays the consumed quantity of oxygen.

From the COD readings the exact quantity of sample water (see Table 3.1) required for the

BOD testing was calculated and poured into brown bottles (in all sample-analysed water the

quantity required for BOD was 432ml) that had already been rinsed with the test samples, a

magnetic stirrer was put into each of these bottles and a rubber quiver was inserted in the

necks of the bottles, 2 sodium hydroxide tablets were put into the rubber quivers with the aid

of a tweezers (care was taken to avoid the tablets coming in contact with the water samples).

The OxiTop® bottle tops were screwed directly onto the sample bottles. The OxiTop® bottle

tops were programmed individually to start taking BOD readings for the next 5 days, as soon

as the water samples reached the 20oC standard temperature (taking between 1 – 3 hours at

the latest). The values after 5 days can be plotted on a graph.

Table 3.1 COD measuring range and corresponding sample volume for BOD5

testing**.

** Specific manufacturer’s range for product used in water sample analyses.

Expected BOD5 value ≈ 80% of the COD value

Sample filling volume (ml) COD measuring range (mg/l) Factor

432 0 – 40 1

365 0 – 80 2

250 0 – 200 5

164 0 – 400 10

48

97 0 – 800 20

43.5 0 – 2000 50

22.7 0 – 4000 100

3.4.3 Tests for the Presence of Coliform Bacteria.

A volume of 100ml from each of the water samples was filtered through a sterile 0.45µm

pore size filter (cellulose nitrate filter, Sartorius A.G., W. 3400). The membranes were placed

on the selective medium m.FC which was incubated at 37oC for 24 hours. At the end of 24

hours there were 2 types of colonies; the dark blue and creamy coloured colonies. Each of

these respective colonies were picked and plated on MacConkey agar (see Appendix A for

composition) and incubated at 37oC for 24 hours for further work (Merck Biolab Catalogue

(Version 2) 1997: 62).

3.4.4 Preliminary Identification of isolated bacteria

Colonies were picked from the MacConkey agar plates and streaked onto nutrient agar plates.

These were incubated at 37oC for 24 hours and colonies were picked and Gram stained. Gram

staining was performed as described by Harley and Prescott (2002: 43 – 45). Gram stain

reactions proved that all the colonies picked were Gram-negative bacilli.

3.5 Antibiotic Susceptibility Test.

Antibiotic resistance was assayed using the Kirby-Bauer disk diffusion method (Harley &

Prescott 2002: 257 - 260). In this method, commercially prepared paper disks impregnated

with the selected antibiotics were placed on a seeded Mueller-Hinton agar plate using a

mechanical dispenser or sterile forceps. The plates were then incubated for 16 – 18 hours, and

the diameter of the zone of inhibition around the disk was measured to the nearest millimetre.

Antibiotic susceptibility patterns are called antibiograms. Antibiograms can be determined by

comparing the zone diameter obtained with known zone diameter size for susceptibility.

Antibiotics used for MAR indices were especially selected because they are typically

associated with animal feed and/or clinical treatments. The following antibiotic disks at the

respective final concentration used were; Ampicillin (AP) – 10µg, Cephalothin (KF) – 30µg,

Colistin sulphate (Co) – 10µg, Gentamycin (GM) – 10µg, Streptomycin (S) – 300µg,

Tetracyclin (T) – 30µg and Cotrimoxazole (TS) – 25µg (Table 3.1). These antibiotic disks

49

are commercially available in these concentrations. These antibiotics were chosen for two

reasons: (1) all have been used in the treatment of human illness; (2) all have been used in

previous surveys of antibiotic resistance in aquatic environments.

Figure 3.1 An example of one of the Antibiotic Susceptibility Test Plates [Note: the clear

zones of inhibitions around the Streptomycin (S - 300µg) and the Gentamycin (GM – 10µg) disks as opposed to

no zones around other antibiotic disks on the plates in the picture (one of the sample plates from 18 February

2009 water sample collected)].

From each plate, three well-separated colonies were picked, each of these colonies was

transferred into tubes containing 10mls of Tryptone Soy Broth (see Appendix A for

composition). These were incubated overnight at 35oC. Before seeding the Mueller-Hinton

plates (see Appendix A for composition), a few drops of inoculum from individual Tryptone

Soy Broth culture tubes were put inside tubes containing 5mls of saline to be used in the API

20E identification process. Individual sterile swabs were immersed in the Tryptone culture

50

tubes and used to streak the entire surface of plates of Mueller-Hinton. These cultures were

left to dry for 10 minutes with their lids in place. A multiple dispenser was used to place the

antibiotic disks on the seeded plates. These plates were incubated for 18hours at 35oC. After

this period of incubation individual zones of inhibition were measured and recorded.

Table 3.2: Antibiotics used in this study

Antibiotics used Disk

concentration(µg)

Class

AP Ampicillin 10 β – Lactams

KF Cephalothin 30 β – Lactams

Co Colistin sulphate 10 Peptide antibiotics

GM Gentamycin 10 Aminoglycosides

S Streptomycin 300 Aminoglycosides

T Tetracycline 30 Tetracyclines

TS Cotrimoxazole 25 Sulphonamides

3.6 Identification of organisms using the API 20E System

The organisms isolated from the Rietspruit River using the m.FC media were identified using

the API 20E system. The API 20E system is a rapid but standardized, miniaturized version of

conventional biochemical procedures used in the identification of Enterobacteriaceae and

other gram-negative bacteria. A total of 127 taxa can be identified with this system. It is a

ready-to-use microtube system that performs 21 standard biochemical tests on pure cultures

from appropriate primary isolation media. This system consists of a strip containing 20

chambers, each consisting of a microtube and a depression called a cupule. The tubes contain

dehydrated substrates. The substrates are rehydrated by adding a bacterial saline suspension.

The system includes tests that require anaerobic conditions; to achieve this condition, sterile

mineral oil is added to several of the microtubes. The strip was incubated for 18 to 24 hours

at 35o to 37

oC so that the bacterium can act on the substrates. The strip was read by noting the

colour changes after the various indicator systems had been affected by the metabolites or

added reagents. The identification of the unknown bacterium was achieved by determining a

seven-digit profile index number and consulting the API 20E Profile Recognition System or

the API 20E Profile Index Booklet. On the result sheet, the tests were separated into groups of

3 and a value of 1, 2 or 4 was indicated for each. By adding the value corresponding to

51

positive reactions within each group, a 7-digit profile number was obtained for the 20 tests of

the API 20E strip. The oxidase reaction constituted the 21st test and had a value of 4 if it was

positive.

Table 3.3 API 20E tests with their corresponding numerical value

ONPG ADH LDC ODC CIT H2S URE TDA IND VP GEL GLU MAN INO SOR RHA SAC MEL AMY ARA OXI

1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2 4

Sterile disposable pipettes were used to transfer drops of inoculum (from the overnight

growth in the Tryptone Soy Broth used to seed the Mueller-Hinton plates) into 5ml of 0.85%

saline solutions in sterile test tubes. These were shaken and then drops of the bacterial

suspension were used to fill the tubes labelled ONPG, TDA, IND, GLU, MAN, INO, SOR,

RHA, SAC, MEL, AMY and ARA microtubes. The tubes labelled ADH, LDC, ODC, H2S

and URE were slightly under-filled and then completely filled with sterile mineral oil. Both

the tubes and cupules were filled for the tubes |CIT|, |VP| and |GEL| tubes. These strips were

incubated in plastic trays containing about 5ml of water (to create humidity and prevent

dehydration) at 35oC for 24 hours. After the 24 hours incubation period the colour changes

for the reactions that did not require the addition of reagents were recorded and allocated the

corresponding numerical value (Table 3.3). To the TDA tubules 1 drop of TDA reagent was

added, a reddish brown colour indicates a positive reaction. To the |VP| tubules 1 drop each

of VP1 and VP2 reagents were added and results were read after 10 minutes, a pink to red

colour indicates a positive reaction. Finally to the IND tubules 1 drop of JAMES reagent was

added, a pink colour indicated positive reaction. All reaction results were noted and the

numerical values were added up to get the corresponding 7-digit profile number which was

used to identify the unknown coliforms.

Table 3.4 Chemical / Physical Principles – Basis for the API 20E System

TESTS ACTIVE

INGREDIENTS

QUANTITY REACTION/ENZYMES CHEMICAL/PHYSICAL

PRINCIPLE

ONPG

2-nitrophenyl-βD-

galactopyranoside

0.2mg

β-galactosidase (Ortho

nitrophenyl-βD

galactopyranosidase)

Hydrolysis of ONPG by beta-

galactosidase releases yellow

orthonitrophenol from the colourless

ONPG; ITPG

52

ITPG 8.0µg (isopropylthiogalactopyranoside) is used

as the inducer. Expected reaction:

colourless is negative; yellow is

positive.

ADH L-arginine 2.0mg Arginine dihydrolase Arginine dihydrolase transforms

arginine into ornithine, ammonia and

carbon dioxide. This causes a pH rise in

the acid-buffered system and a change

in the indicator from yellow to red.

Expected reaction: yellow is negative;

red/orange-red is positive.

LDC L-lysine 2.0mg Lysine decarboxylase Lysine decarboxylase transforms lysine

into a basic primary amine, cadaverine.

This amine causes a pH rise in the acid-

buffered system and a change in the

indicator from yellow to red. Expected

reaction: yellow is negative;

red/orange-red is positive.

ODC L-ornithine 2.0mg Ornithine decarboxylase Ornithine decarboxylase transforms

ornithine into a basic primary amine,

putrescine. This amine causes a pH rise

in the acid- buffered system and a

change in the indicator from yellow to

red. Expected reaction: yellow is

negative; red/orange-red is positive.

CIT Trisodium citrate 0.8mg Citrate utilization Citrate is the sole carbon source. Citrate

utilization results in a pH rise and a

change in the indicator from green to

blue. Expected reaction: yellow/light

green is negative; turquoise/dark blue

is positive.

H2S Sodium thiosulfate 80.0µg H2S production Hydrogen sulphide is produced from

thiosulfate. The hydrogen sulphide

reacts with iron salts to produce a black

precipitate. Expected reaction:

colourless/greyish is negative; black

deposit/thin line is positive.

URE Urea 0.8mg Urease Urease releases ammonia from urea;

ammonia causes the pH to rise and

53

changes the indicator from yellow to

red. Expected reaction: yellow/ yellow-

orange is negative; red/orange-red is

positive.

TDA L-tryptophane 0.4mg Tryptophane Deaminase Tryptophane deaminase forms

indolepyruvic acid which produces a

brownish-red colour in the presence of

ferric chloride. Expected reaction

(immediate on the addition of TDA

reagent): yellow is negative; reddish

brown is positive.

IND L-tryptophane 0.2mg Indole production Metabolism of tryptohane results in the

formation of indole. Kovacs‟ reagent

forms a coloured complex (pink to red)

with indole. Expected reaction

(immediate on the addition of JAMES

reagent): colourless/pale green/yellow

is negative; pink is positive.

VP Sodium pyruvate

Creatine

2.0mg

0.9mg

Acetoin production

(Voges Proskauer)

Acetoin, an intermediary of glucose

metabolite, is produced from sodium

pyruvate and indicated by the formation

of a coloured complex. Conventional

VP tests may take up to 4 days, but by

using sodium pyruvate, API has

shortened the required test time.

Creatine intensifies the colour when the

tests are positive. Expected reaction (on

addition of VP1 + VP2 between 2-10

minutes): colourless/pale pink is

negative; pink/red is positive.

GEL Gelatin (bovine

origin)

0.6mg Gelatinase Liquefaction of gelatin by proteolytic

enzymes releases a black pigment which

diffuses throughout the tube. Expected

reaction: non-diffusion is negative;

diffusion of black pigment is positive.

GLU D-glucose 2.0mg Fermentation / oxidation

of Glucose

Utilization of the carbohydrate results in

acid formation and a consequent pH

drop. The indicator changes from blue to

yellow. Expected reaction: blue/ blue-

MAN D-manitol 2.0mg Fermentation /oxidation

of Manitol

54

INO Inositol 2.0mg Fermentation /oxidation

of Inositol

green is negative; yellow/ yellowish

gray is positive.

SOR D-sorbitol 2.0mg Fermentation /oxidation

of Sorbitol

RHA L-rhamnose 2.0mg Fermentation / oxidation

of Rhamnose

SAC D-sucrose 2.0mg Fermentation / oxidation

of Saccharose

MEL D-melibiose 2.0mg Fermentation / oxidation

of Melibiose

AMY Amygdalin 2.0mg Fermentation /oxidation

of Amygdalin

ARA L-arabinose 2.0mg Fermentation / oxidation

of Arabinose

Harley & Prescott 2002. Laboratory Exercises in Microbiology. (5th

ed.) New York: McGraw Hill: 208 -211

55

CHAPTER 4

RESULTS

4.1 Introduction to Results

A total of 21 different colonies of coliforms isolates from each of the three different sample

points (see section 3.2) were tested against seven different antibiotics for antibiotic resistance

and MAR indices. Gram stains were performed on each colony to confirm them as Gram-

negative bacilli. Biochemical tests which included oxidase tests were done on each isolate

using the API 20E test-kit. The antibiotics used were those commonly added to animal feed

and used clinically. The original results as obtained during the months of February, June and

September 2009, their preliminary tests, resistances as well as the MAR of different bacteria,

are given in Appendix B.

In February, because this was peak summer there was high rainfall; as a result the water flow

surpassed the plant capacity (150 mega litres) therefore making treatment difficult. There was

leaking due to the overflow of the Maturation pond into the treated Final Effluent and this

ended up in the Downstream. The result being that a great deal of untreated water flowed

back into the river. It is pertinent to note that due to rising costs of chlorination, treatment of

water at the facility does not (at times) include this step.

4.2 On-site analysis of water samples

The on-site examination of water samples showed no inconsistencies as the temperature

increase and decrease were consistent with the changing seasons; summer temperatures

(February) were higher than winter (June), while spring temperatures (September) were lower

than summer but higher than winter (Table 4.1). The pH through all the seasonal changes

remained between 7.0 – 7.7(Table 4.1) [WHO standard: 6.5 - 8.5] (WHO 2006). The

Upstream water samples in February showed the highest turbidity (53.4) when compared

with all the months of sample collection.

56

Table 4.1a On-site examination of water samples

SAMPLE

POINTS

pH Temperature (oC) Turbidity (NTU)

Feb. June Sept. Feb. June Sept. Feb. June Sept.

Upstream 7.6 7.0 7.7 22.9 12.5 18.9 53.4 18.5 20.9

Final Effluent 7.3 7.2 7.4 24.3 15.8 19.6 4.4 7.3 10.4

Downstream 7.1 7.1 7.1 25.0 15.4 15.9 27.0 20.5 25.7

The COD and BOD for all the water samples were determined and the results are given in

Table 4.1b. The COD values at the Final Effluent (after treatment) sample point were

consistently higher than those of the other two sampling points through all the months of

sample collection. The Upstream showed its highest COD value of 17 in February; this also

applied to both Final Effluent and Downstream sites with values 29 and 19 respectively. The

BOD at the Downstream sample point was highest (1.7) through all the seasons (and

remained consistent) compared to the other two sample points. All BOD readings were within

the range of the WHO standard of between 0 – 6mg/l (WHO 2006).

Table 4.1b COD and BOD values of water samples

SAMPLE POINTS

COD (mg/l) BOD (mg/l)

Feb. June Sept. Feb. June Sept.

Upstream 17 8 14 1.4 1.4 1.3

Final Effluent 29 16 25 1.1 0.8 1.4

Downstream 19 12 18 1.7 1.7 1.7

4.3 Multiple antibiotic resistance

From the data in Appendix B, it should be noted that all tested isolates exhibited some form

of multiple antibiotic resistance. All tested isolates showed resistance to Ampicillin.

Remarkably, all organisms isolated from Upstream (through different seasonal changes)

showed multiple resistance to three antibiotics; Cephalothin, Ampicillin and Tetracycline.

Susceptibility to Streptomycin and Gentamycin in the Upstream isolates is also remarkable as

resistance to Streptomycin (in less than 15% of isolates) was only achieved in September at

one sample point (Final Effluent whilst with Gentamycin it was achieved in the month of

57

September in the Final Effluent and Downstream sites, percentages of isolates being 28.6%

and 14.3% respectively (Table 4.2).

The results in September showed that isolates from the Final Effluent site showed resistance

to all the test-antibiotics (Table 4.2). All isolates collected at the Final Effluent site in

February showed resistance to Cephalothin and Cotrimoxazole. In the months of February

and June, isolates from Downstream showed resistance to Cephalothin, Ampicillin and

Tetracycline and susceptibilities to Streptomycin and Gentamycin.

In February, all isolates from Downstream showed resistance to Cotrimoxazole while in June

and September, all isolates showed resistance to Colistin sulphate. There were variations to

the percentage of resistance of isolates to each antibiotic at each sample point for each month.

All isolates exhibited more than a single resistance to the different antibiotics. Most isolates

showed susceptibilities to Streptomycin and Gentamycin. Isolates from the same sample

point tended to show resistance and susceptibilities to the same antibiotics but varied in some

cases to other sample points.

In Table 4.3b, which showed a total of all isolates, these exhibited a 100% resistance to

Ampicillin, which was followed by Cephalotin sulphate with 94%. Only a small percentage

of isolates were resistant to Streptomycin. Organisms isolated from the Upstream showed

100% resistance to Cephalothin, Ampicillin and Tetracycline (Table 4.3a); this trend was not

repeated at the other two sampling points.

58

Table 4.2 Number of Resistant Isolates at each Sample Point for each Date Collected.

SAMPLE POINT

DATE COLLECTED

KF TS S Co GM AP T

N % N % N % N % N % N % N %

UPSTREAM

FEBRUARY

7/21

33.3

5/21

24.0

0/21

0

0/21

0

0/21

0

7/21

33.3

7/21

33.3

JUNE

7/21

33.3

7/21

33.3

0/21

0

6/21

28.6

0/21

0

7/21

33.3

7/21

33.3

SEPTEMBER

7/21

33.3

7/21

33.3

0/21

0

7/21

33.3

0/21

0

7/21

33.3

7/21

33.3

FINAL

EFFLUENT

FEBRUARY

7/21

33.3

7/21

33.3

0/21

0

3/21

14.3

0/21

0

7/21

33.3

3/21

14.3

JUNE

6/21

28.6

4/21

19.0

0/21

0

3/21

14.3

0/21

0

7/21

33.3

4/21

19.0

SEPTEMBER

6/21

28.6

4/21

19.0

3/21

14.3

6/21

28.6

6/21

28.6

7/21

33.3

6/21

28.6

DOWN STREAM

FEBRUARY

7/21

33.3

7/21

33.3

0/21

0

3/21

14.3

0/21

0

7/21

33.3

7/21

33.3

JUNE

7/21

33.3

5/21

23.8

0/21

0

7/21

33.3

0/21

0

7/21

33.3

7/21

33.3

SEPTEMBER

5/21

33.3

5/21

23.8

0/21

0

7/21

33.3

3/21

14.3

7/21

33.3

5/21

23.8

59

Table 4.3a Total Number of Resistant Isolates at each Sample Point

SAMPLE POINT

KF TS S Co GM AP T

N % N % N % N % N % N % N %

UPSTREAM

21/21

100.0

19/21

90.5

0/21

0

13/21

62.0

0/21

0

21/21

100.0

21/21

100.0

FINAL

EFFLUENT

19/21

90.5

15/21

71.4

3/21

14.3

12/21

57.1

6/21

28.6

21/21

100.0

13/21

62.0

DOWNSTREAM

19/21

90.5

17/21

81.0

0/21

0

16/21

76.2

3/21

14.3

21/21

100.0

19/21

90.5

60

Table 4.3b Number of Isolates Resistant to Each Antibiotic

ANTIBIOTIC

Total number of

isolates

Percentage (%)

n=63

Cephalothin (KF) 59 94.0

Cotrimoxazole (TS) 51 80.9

Streptomycin (S) 3 4.8

Colistin sulphate (Co) 41 65.1

Gentamycin (GM) 9 14.3

Ampicillin (AP) 63 100.0

Tetracycline (T) 53 84.1

Table 4.4 shows the ranking of antibiotics according to the number of resistant isolates. It is

remarkable to note that all isolates showed resistance to Ampicillin followed by Cephalothin,

isolates which showed the least resistance to Streptomycin. Resistance towards Gentamycin

was achieved only in the month of September in the Final Effluent site (see also figures 1 – 8

in Appendix C that depicts the percentage resistance in all the sites as bar charts).

Table 4.4 Ranking of Antibiotics according to the number of resistant isolates

Antibiotic Number of resistant isolates

AP 63

KF 59

T 53

TS 51

Co 41

GM 9

S 3

The highest cumulative frequency (see Appendix C) was expressed by Ampicillin at 0.999

while the lowest was for Streptomycin at 0.047; this trend was only shown in the month of

61

September. Cumulative frequency for Gentamycin at the Upstream through all the months of

sample collections remained at 0.000 and marginally increased in the month of September at

the Final Effluent site. At the Downstream the cumulative frequency for Gentamycin

increased marginally from 0.095 to 0.144, when isolates were found here as well. Since all

organisms tested were resistant to Ampicillin, the cumulative frequency increased

accordingly with the final figure being 0.999.

The MAR index for each of the various sample sites and the average MAR index for all

isolates in a sample site were calculated (Table 4.5).

For an individual isolate the MAR index = the number of antibiotics to which the isolate was

resistant ÷ the total number of antibiotics tested.

The MAR index for samples at a site = the number of antibiotics to which all isolates at the

site were resistant ÷ (number of antibiotics tested x number of isolates) (Kasper, Burgess,

Knight & Colwell 1990: 892 -893).

62

TABLE 4.5 Sample Site Multiple Antibiotic Resistance (MAR) Index

SAMPLE SITE

DATE COLLECTED

NUMBER OF ISOLATES

TESTED

NUMBER OF ANTIBIOTICS

RESISTED BY ALL

ISOLATES

AVERAGE MAR

SAMPLE SITE MAR INDEX

UPSTREAM

FEBRUARY

21

2

.530

.013

JUNE

21

4

.700

.030

SEPTEMBER

21

5

.714

.034

FINAL EFFLUENT

FEBRUARY

21

3

.550

.020

JUNE

21

1

.500

.007

SEPTEMBER

21

1

.800

.007

DOWNSTREAM

FEBRUARY

21

4

.632

.030

JUNE

21

4

.673

.030

SEPTEMBER

21

2

.652

.013

63

From Table 4.5; the highest average MAR index (0.800) was shown in September at the Final

Effluent site, but because of high variations in the degree of resistance exhibited by isolates,

only one antibiotic was consistently resisted and as a result the MAR index of the site was the

lowest. It follows that the higher the number of antibiotics to which all isolates are resistant

the higher the area MAR index. The area MAR index for all the different months varied

between 0.01 – 0.03, with the Final Effluent site showing the lowest MAR index. In

September, the upstream site showed the highest area MAR index and isolates from this

month showed the highest number of antibiotic resistance.

Isolates showed the same MAR index when they were resistant to an equal number of

antibiotics irrespective of the type of antibiotic, for example at Upstream in February where

organisms were resistant to 2 antibiotics with sample site MAR index of 0.013; the same

applied to Downstream in September with the same values. The area MAR index from area to

area did not vary remarkably but was relatively low at the Final Effluent site (see values in

the Final Effluent site for the months of June and September [0.007]).

Table 4.6 shows antibiotics to which all isolates exhibited resistance at specific sample points

and in specific months of sample collection. In the Upstream site all 21 isolates showed

resistance to Cephalothin, Ampicillin and Tetracycline through the different months. In June

and September all isolates showed resistance to Cotrimoxazole, but in September all

Upstream isolates showed resistance to Colistin sulphate as well. At the Final Effluent site in

February, all isolates exhibited resistance to Cephalothin, Cotrimoxazole and Ampicillin,

while in June and September all isolates showed resistance to only Ampicillin. All isolates

from Downstream during the months of February showed resistance to Cephalothin,

Ampicillin and Tetracycline, with February isolates showing resistance to Cotrimoxazole as

well. During the months of June and September all isolates showed a resistance to Colistin

sulphate as well. Comparing all three sampling areas, a trend of resistance towards

Ampicillin was observed, therefore making it the most prominent antibiotic in this regard.

The antibiotic to which isolates were least resistant was Streptomycin.

64

Table 4.6 Antibiotics to which all isolates at specific months were resistant per sample

point.

SAMPLE POINT DATE COLLECTED NUMBER OF

ISOLATES

TESTED

ANTIBIOTICS

UPSTREAM

FEBRUARY 21 KF, AP, T

JUNE 21 KF, TS, AP,T

SEPTEMBER 21 KF, TS, Co, AP, T

FINAL EFFLUENT

FEBRUARY 21 KF, TS, AP

JUNE 21 AP

SEPTEMBER 21 AP

DOWN STREAM

FEBRUARY 21 KF, TS, AP, T

JUNE 21 KF, Co, AP, T

SEPTEMBER 21 Co, AP

4.4 Antibiotic Resistance Patterns

The most prevalent resistance patterns that were identified during the course of this study are

given in Table 4.7a. A total of 6 different patterns were identified. Resistance patterns that

did not recur at least 3 times within the 3 months sample period were not represented on the

table. Two antibiotics, Cephalothin and Ampicillin featured in all the documented resistance

patterns. A complex variety of patterns were observed (Table 4.7b&c). The antibiotic

resistance pattern that occurred with the highest frequency was C {KF, TS, Co, AP, T}.

Although B {KF, TS, AP, T} occurred in all the sample points, it did not occur with as much

frequency as C. In the month of September, all isolates tested from the Upstream

demonstrated homogeneity in their resistance patterns and exhibited only the resistance

pattern C. The most prevalent resistance patterns at each sample point revealed no specific or

65

common trend in antibiotic resistance patterns in all the 3 sample points over the 3 months

period of sample collection.

It is important to note that some patterns occurred in only a particular sample point for only a

particular season; antibiotic resistance pattern A {KF, AP, T} occurred in 28.6% of isolated

coliforms in February (summer) at the Upstream, but was not repeated in the other two

sample points nor was it repeated in any other season of the study; the same can be stated for

antibiotic resistance pattern D {KF, TS, AP} at the Final Effluent, which occurred in 14.3%

of isolated coliforms, in the month of February. Antibiotic resistance pattern E {KF, Co, AP}

occurred in the Final Effluent in the month of June (winter) with the percentage of

occurrence amongst the isolated coliforms being 28.6%; also in June, at the Downstream,

antibiotic resistance pattern F{K, Co, AP, T} occurred amongst the isolated coliforms with

the percentage of occurrence being 28.6%. In the month of September (spring), antibiotic

resistance pattern G {KF, TS, Co, GM, AP, T} occurred in both the Final Effluent and Down

Stream sites on both occasions with the percentage of occurrence amongst the isolated

coliforms being 42.8%.

Table 4.7a Most Prevalent Antibiotic Resistance Patterns and notations

Notation Resistance Patterns

A KF AP T

B KF TS AP T

C KF TS Co AP T

D KF TS AP

E KF Co AP

F KF Co AP T

G KF TS Co GM AP T

66

Table 4.7b The Most Prevalent Patterns (with notations) at Each Sample Point

FEBRUARY JUNE SEPTEMBER

UPSTREAM

A KF, AP, T 28.6% C KF, TS, Co, AP, T 85.7% C KF, TS, Co, AP, T 100.0%

B KF, TS, AP,T 74.4% B KF, TS, AP, T 14.3%

FINAL

EFFLUENT

B KF, TS, AP,T 42.8% B KF, TS, AP, T 42.8% G KF, TS, Co, GM, AP, T 42.8%

C KF, TS, Co, AP, T 42.8% C KF, TS, Co, AP, T 14.3%

D KF, TS, AP 14.3% E KF, Co, AP 28.6%

DOWNSTREAM

C KF, TS, Co, AP, T 42.8% C KF, TS, Co, AP, T 71.5% G KF, TS, Co, GM, AP, T 42.8%

B KF, TS, AP, T 57.1% F KF, Co, AP, T 28.6% C KF, TS, Co, AP, T 28.6%

67

4.5 API 20E tests

The API 20E tests revealed a variety of faecal and non-faecal coliforms present in the water

body (Rietspruit River) under study. There was no particular growth pattern observed in all

the seasons. A total of 17 different coliforms were identified using the API 20E test kits.

Higher numbers of Klebsiella spp. and Serratia spp., (20.6% allocated to each) (see Table

4.8a) were isolated. Isolates tended to share common resistance patterns with other coliforms

found at a particular sampling point or in some cases during a particular season and in some

cases increasing the number of antibiotics to which they were initially resistant, This can be

seen in Table 4.7b; Pantoea spp. when first isolated at the Upstream site in February was

only resistant to 3 antibiotics (Cephalothin, Ampicillin and Tetracycline). At the

Downstream site in February and June when Pantoea was isolated there was an increase from

3 to 5 antibiotics to which it was resistant; it exhibited resistance pattern C {Cephalothin,

Cotrimoxazole, Colistin sulphate, Ampicillin and Tetracycline} with other coliforms like

Enterobacter cloacae, Rahnella aquatilis, Serratia and E. coli. When Pantoea spp. was

isolated again at the Final Effluent site in September with other coliforms like Klebsiella,

Salmonella and Aeromonas, there was an increase in the number of antibiotics to which it

was resistant. It was resistant to 6 out of the 7 test antibiotics (this still included the former 3

antibiotics). The same phenomenon was observed with E. coli; when first isolated in

February at the Upstream site, it exhibited a resistance to 3 antibiotics (Cephalothin,

Ampicillin and Tetracycline); but in June at the same site there was an increase first by the

addition of one more antibiotic (Cotrimoxazole) to the former 3 antibiotics to which it was

resistant making it a total of 4 (resistance pattern B). In that same month (June) E. coli was

isolated that showed a resistance to 5 antibiotics (Cephalothin, Ampicillin, Tetracycline,

Cotrimoxazole and Colistin sulphate), which is the resistance pattern C. The resistance

pattern C was also exhibited by other coliforms isolated in June at the Upstream like

Kluyvera, Serratia, Enterobacter cloacae and Klebsiella. Both resistance patterns B and C

were repeated for E. coli in February and June for the Final Effluent and Downstream sites.

Klebsiella also showed this increase in the number of antibiotics to which it became resistant

with changes in season and sample sites. Serratia marcescens was isolated in the Upstream

site in June and September. It consistently exhibited the same resistance pattern C

{Cephalothin, Cotrimoxazole, Colistin sulphate, Ampicillin and Tetracycline}, thereby

showing resistance to 5 out of the 7 antibiotics tested. This same pattern was repeated in the

68

month of June when it was isolated at the Final Effluent and Downstream sites. It is

important to note that coliforms isolated in September resisted the highest number of

antibiotics i.e. 6 out of the 7 antibiotics used in the study (in the Final Effluent and

Downstream sites) and it was only in this season that Salmonella was isolated.

Figure 4.8a shows the percentages of individual isolates and their occurrence at each sample

site with passing of the months and seasons, some coliforms showed a pattern in their

occurrence as can be seen with Escherichia coli and Salmonella; with the latter, it occurred in

all three sample sites in the months of February and June whilst Salmonella occurred in all

sample sites in the month of September. Klebsiella occurred in February, June and September

in both the Upstream and Final Effluent sites but was only isolated in February at the

Downstream sites.

69

Table 4.8a The Percentages of Individual Isolates in the Total number of Coliforms

tested using the API 20E and its occurrence in sample sites

ISOLATED COLIFORMS

(%)

UPSTREAM FINAL EFFLUENT DOWNSTREAM

FEB. JUNE SEPT. FEB. JUNE SEPT. FEB. JUNE SEPT.

. *Serratia spp. 20.6 √

√

√

√

√

√

*Klebsiella spp. 20.6 √

√

√

√

√

√

√

Escherichia coli. 15.9 √

√

√

√

√

√

Kluyvera spp 12.7 √

√

√

√

√

*Enterobacter spp. 9.5 √

√

√

√

√

Pantoea spp 6.3 √

√

√

√

Salmonella spp. 4.8 √

√

√

Rhaoultella ornithinolytica 3.1 √

Rahnella aquatilis 3.1 √

√

Aeromonas hydrophila 1.6 √

Citrobacter freundii 1.6 √

* variety of species grouped together

√ occurred

% percentages

70

TABLE 4.8b Isolates identified with the most prevalent patterns at each sample point

FEBRUARY JUNE SEPTEMBER

UP

ST

RE

AM

A KF, AP, T 28.6% Pantoea spp.

Escherichia coli

C KF, TS, Co, AP, T 85.7% Kluyvera spp

Serratia fonticola

Enterobacter cloacae

Escherichia coli

Serratia marcescens

Klebsiella oxytoca

C KF, TS, Co, AP, T 100.0% Klebsiella oxytoca

Serratia marcescens

Raoultella ornithinolytica

Serratia odorifera

Salmonella spp.

B KF, TS, AP,T 74.4% Klebsiella pneumonia

Kluyvera spp.

Rahnella aquatilis

Klebsiella oxytoca

B KF, TS, AP, T 14.3% Escherichia coli

FIN

AL

EF

FL

UE

NT

B KF, TS, AP,T 42.8% Escherichia coli

Enterobacter cloacae

B KF, TS, AP, T 42.8% Enterobacter cloacae

Citrobacter freundii

Escherichia coli

G KF, TS, Co, GM, AP, T 42.8% Pantoea spp.

Salmonella spp.

Klebsiella pneumoniae ssp. ozaenae

C KF, TS, Co, AP, T 42.8% Escherichia coli

Kluyvera spp

C KF, TS, Co, AP, T 14.3% Serratia marcescens

D KF, TS, AP 14.3% Klebsiella pneumoniae E KF, Co, AP 28.6% Klebsiella pneumoniae ssp.

ozoenae

Enterobacter cloacae

71

FEBRUARY JUNE SEPTEMBER D

OW

NS

TR

EA

M

C KF, TS, Co, AP, T 42.8% Enterobacter cloacae

Pantoea spp

Rahnella aquatilis

C KF, TS, Co, AP, T 71.5% Escherichia coli

Pantoea spp

Serratia ficaria

Serratia marcescens

G KF, TS, Co, GM, AP, T 42.8% Serratia odorifera

Kluyvera spp

B KF, TS, AP, T 57.1% Serratia ficaria

Enterobacter amnigenus1

Klebsiella oxytoca

Escherichia coli

F KF, Co, AP, T 28.6% Serratia fonticola

Enterbacter cloacae

C KF, TS, Co, AP, T 28.6% Serratia odorifera

Kluyvera spp

72

CHAPTER 5

DISCUSSION

5.1 Introduction to Discussion

The resistance to antibiotics by bacteria is a natural phenomenon (Gaur & English 2006:1;

Purdom 2007:1). Resistant strains of micro-organisms have been noted since the discovery of

antibiotics (Palumbi 2001:1786). All living organisms need to develop defence mechanisms

against threats that would otherwise lead to their elimination and subsequent extinction of

their species at large. In the case of bacteria, antibiotics developed by humans are such

defence mechanisms; but because it is a struggle that entails a survival of the fittest; it follows

that with the development of this defence, humans must in turn intensify their effort so that

the stronger organism may survive. For this reason there has to be routine re-evaluation of

our status in this struggle for survival.

The development of single and multiple antibiotic resistance is of great concern to scientists

all over the world as this implies that expedient efforts must be applied to the production of

new and alternative treatment therapy for the same disease.

Many bacterial species multiply rapidly enough to double their numbers every 20–30

minutes, and their ability to adapt to changes in the environment and survive unfavourable

conditions often result in the development of mutations that protect them. In addition, a factor

contributing to their adaptability is that individual cells do not rely on their own genetic

resources alone. Many, if not all, have access to a large pool of itinerant genes that move

from one bacterial cell to another and can spread through bacterial populations on a variety of

mobile genetic elements, of which plasmids and transposable elements are two examples.

Bacterial capacity to adapt to external changes using these mechanisms is known as

resistance development in the face of selection pressures and this allows the resistant

organisms to proliferate in the prevailing conditions (Serrano 2005:19).

73

5.2 Discussion

It cannot be over emphasized that the Rietspruit River is an important source of water supply

to the population of South-west Johannesburg. The Rietspruit drains into the Vaal River

upstream of Vaal Barrage. The residential areas in the catchment include various gold mining

towns, smallholdings and the towns of Sebokeng, Evaton and Orange Farm. An iron and steel

works is situated in the lower part of the River. But, one significant contributor to the

microbiological change of the water body is the rapidly-expanding informal settlement in the

urban development component in South Africa; this has adversely affected most water bodies

that may be situated within the areas where they are located. These informal settlements

along the river route are a direct source of faecal contamination and this is further aggravated

because in most cases there is a lack of sanitation systems. This poses an increased risk for

the outbreak of water-borne diseases (Pretorius 2000: 11). Similarly, increase of faecal

pollution in source water is also a problem in developing as well as developed countries

(Sinton, Donnison & Hastie 1993: 136; Bezuidenhout, Mthembu, Pucktree & Lin 2002: 285).

These factors coupled with the lack of any chemical treatment (chlorine) are detrimental to

the final quality of discharged water. According to Momba, Osode & Sibewu (2006: 687)

there are statistical correlation between the type of treatment carried out on final effluents and

the final quality of the receiving water body. They alluded to the fact that better treatment of

effluents yielded better overall water quality. This phenomenon has necessitated routinely re-

evaluating and investigating the water bodies in South Africa. For the purpose of this study

the Rietspruit River was chosen. This study involved the isolation of pollution indicator

micro-organisms, faecal coliforms, from the water supply, identification of possible point

source and non-point source of antibiotic resistant coliforms, evaluating the MAR profiles

among the coliforms isolated and identified from different sample points. A volume of 100ml

of sample water was filtered and mFC (and later MacConkey) was used as a selective growth

medium. Seven antibiotics were used to test the MAR of the isolated coliforms; these isolates

were identified using both the API 20E test (see Chapter 3).

Preliminary analyses done on-site in February on samples collected Upstream showed the

highest turbidity value (53.4) through all the seasons of sample collection which could be

attributed to high amounts of rainfall the day before the samples were collected. Also in

February all COD values from all sample sites were greater than in the other months of

sample collection. It is important to recall that as a result of the high amounts of rainfall water

74

led to an overflow from the maturation pond (where there is a high concentration of

microorganisms) into the Final Effluent this would have contributed to the spike in the COD

values. Studies done by Bezuidenhout et al. (2002:285) showed that there is a strong

correlation between increased levels of faecal and other indicator micro-organisms and

changing meteorological conditions. It is also significant to note that the COD at the Final

Effluent (after treatment) sample point was consistently higher than those of the other two

sampling points through all the seasons as a result of the constant aeration of this sample

point. This study could not show if this had a positive impact on the final quality of the water.

Coliforms were recovered in February, June and September 2009 from the three sample

points, all of which could be indicative of a large reservoir of bacterial population in general.

The antibiotic susceptibility testing of coliforms isolated from water samples obtained from

the Rietspruit River in this study showed that a large proportion was resistant to multiple

antibiotics. High resistance of isolates in this study to Ampicillin, Tetracycline, Cephalothin,

Cotrimoxazole and Colistin sulphate (see Table 4.2a) corroborates the findings of Obi,

Bessong, Momba, Potgieter Samie & Igumbor (2004: 518) who showed that at least 20% of

bacterial isolates from the water supply in rural Venda communities of South Africa

demonstrated antibiotic resistance to Cotrimoxazole, Tetracycline, Erythromycin and

Chloramphenicol. In this present study a seasonal variation in antibiotic resistance pattern

was observed that was unique to an individual site. This type of phenomenon was also

observed by Abu & Egenonu (2008) with isolates from various sample sites on the new

Calabar River in Nigeria. Abu & Egeonu (2008: 139- 140) stated that this phenomenon may

be attributed to the impact of industrial and human activities on the bacterial isolates within

these sites. There are reports demonstrating the role played by industrial and human activities

on the antibiotic resistance distribution of bacterial isolates in an environment (Davidson

1999: 86; Lin, Biyela & Pucktree 2004: 27). Goni Urizza, Capdepuy, Arpin, Raymond,

Caumette & Quentin (2000: 130) found a correlation between antibiotic resistant bacteria in

rivers and the input of urban effluents.

Coliforms isolated and identified from the sites in significant numbers included Serratia,

Klebsiella, E. coli, Kluyvera, Enterobacter, Pantoea, Salmonella, Aeromonas hydrophila,

Citrobacter freundii, Rhaoultella ornithinolytica; majority of these coliforms were also

identified as present in the water treatment plants located in at Alice, Dimbaza, East London

75

and Fort Beaufort in South Africa (Momba et al. 2006: 691) and consequently could be found

in receiving water bodies. All of these microorganisms are capable of causing various forms

of gastro-intestinal diseases and other forms of infections either as opportunistic infections

(Winn et al. 2006: 211 – 302; Barnes et al. 2003: 537 - 42) or directly (Umeh & Berkowitz

2006: 1; Dundas et al 2001: 923 - 31). The presence of Aeromonas hydrophila and E. coli

was of particular concern in previous studies done by Momba et al. (2006: 690) they

concurred with work done by Pearson & Idema (1998: 1 -17) that indicated that the high

levels of Aeromonas hydrophila in the final effluents is an indication of the inefficiencies of

the wastewater treatment plants for the removal of the presumptive pathogens, and a

consequence of inadequate disinfection practices and inadequate maintenance of the

infrastructure. Another organism identified in this study, although not in high numbers (but

its presence at all is significant) is Rahnella aquatilis, studies show it can be found in

bronchial washings of AIDS patients and causes septicaemia in immunocompromised

individuals (Harrell et al. 1989: 1671; Maraki et al. 1994: 2706); its presence in South

African water bodies may be linked to the increasing populations of individuals with HIV.

Experiments with rabbits that inhaled endotoxins produced by Rahnella, induced strong

immunological responses with elevation of cytokines levels (Skórska, Sitkowska, Burrell,

Szuster-Ciesielska & Dutkiewicz 1996:61 – 65).

Isolates with a common MAR index may represent a common source of contamination

(indicating that antibiotic resistance profiles are a useful tool in separating populations). This

study measured antibiotic resistance of faecal coliforms from 3 different sources on the

Rietspruit River, but it has been difficult to use the information obtained conclusively to

identify the primary source of faecal pollution; taking into consideration that some faecal

contaminant may escape treatment as observed during the heavy rainfall seasons and the fact

that there were direct introduction of faeces into the water at the downstream as a result of the

presence of members of the informal communities living so close to the river route. The

advantage of analysing the MAR population within an area is that sub-populations can be

separated by isolates‟ MAR indices as explained by Kasper et al. (1990: 892 - 893). The data

showed that the MAR indices of isolates in the Upstream and Downstream sites are greater

than that of the Final Effluent (after treatment) site. This is to be expected as treatment in any

form on the water reduces the microbial load of the water body, but of considerable concern

is that the Downstream showed a relatively higher MAR index value to the Upstream which

76

should not be so as the Final Effluent body of water is usually emptied into it. This in turn,

should help reduce the microbial load. The only explanation that can be given is that along

the Downstream site are a group of informal settlements and from observation, most of them

did not have proper sanitation systems. Most inhabitants here also reared cattle and these

herds used the water for drinking purpose and also defecated directly into the river.

Isolates tested form all sample sites showed highest resistance to ampicillin and cephalothin

which both belong to the same family and have structural similarities. Resistance to β-

lactams antibiotics has become a particular problem in recent decades as strains that produce

β-lactamases have become more common. The β-lactamase enzymes cause many, if not all,

of the penicillins and cephalosporins to be ineffective as therapy (Paterson & Bonomo 2005:

658). The great resistance to ampicillin could be as a result of its use in the treatment and

prevention of infection or as growth promoters in poultry, a practice still carried out in most

poultry farms in South Africa. Wiggins (1996: 3997) showed that bacterial isolates from

chicken and turkey were generally more resistant to antibiotics given to them in sub-

therapeutic doses. Studies have also shown that micro-organisms tend to resist the older and

much more widely used antibiotics (Abu & Egeonu 2008: 140).

Isolates obtained from the same site tended to show common resistance to particular

antibiotics. As noted some antibiotic resistance patterns occurred in only a particular sample

point for only a particular season and this could be attributed to a transfer of resistance-

factors amongst the micro-organisms, the absence of this resistance pattern in subsequent

months may be due to dying-off of the particular population and with the changing season the

predominance of fresh colonies and/or the absence of certain coliforms carrying the

resistance genes for a cluster of antibiotics could also play a role in the loss of a particular

resistance pattern; Figure 4.8a shows the occurrence of individual coliforms at the different

sites and different seasons. There is a direct correlation between bacterial growth and

seasonal changes (Byamukama, Knasiime, Mach & Farnleitner 2000: 866; Solo-Gabriele,

Wolfert, Desmarais & Palmer 2000: 234; Pernthaler Glöckner, Unterholzner, Alfreider

Psenner & Amann 1998: 4304; Lobitz, Beck, Huq, Wood, Fuch, Faruque & Colwell 2000:

1441 ; Bezuidenhout et al. 2002; 285). To further buttress this point, from Table 4.7b it could

be seen that identified coliforms of the same species showed a variety of antibiotic resistance

patterns sometimes with change in seasons and in other cases, just with a change in the site as

77

was seen with Pantoea, E. coli, Serratia and Klebsiella. A study published in the journal

Science in August 2007 found the rate of adaptive mutation in E. coli is “in the order of 10-5

per genome per generation which is 1000 times as high as the previous estimate,” (Foster

2004: 4847) a finding which may have significance for the study and management of

antibiotic resistance. Work done by Salyers, Gupta & Wang (2004: 415) showed that E. coli

may pass on genes responsible for antibiotic resistance to species of bacteria, such as

Staphylococcus aureus. They also stated that E. coli often carry multidrug resistant plasmids

and under stress readily transfer those plasmids to other species; therefore E. coli and other

species in the Enterbacteriacae family are important reservoirs of transferable antibiotic

resistance. However, a wide variation in antibiotic resistance patterns was found among the

different coliforms isolated in this study. These variations may be attributed to predisposition

of isolates to the prevailing selective pressure in the river or to pre-existing characteristics

such as genetic composition and molecular mechanisms including cell permeability in the

organisms (Guardabassi & Dalsgaard 2002: 1; Kummerer 2004: 314). It is therefore

imperative to note that susceptibility of bacteria to antibiotics could be altered by the impact

of environmental and human activities on such isolates. This possibly results in the

development and selection of antibiotic resistant strains. This is a health risk as infections by

such resistant strains are more difficult to treat (Abu & Egeonu 2008: 140).

The sample collected in September yielded isolates with the highest MAR, there were 3

different resistance patterns observed involving six antibiotics which is similar to MAR

observed by Mezriou & Baleux (1994: 2401). These antibiotic resistance pattern are; KF, TS,

Co, GM, AP & T in Salmonella spp., KF, TS, S, Co, AP & T in Kluyvera spp. and KF, S,

Co, GM, AP & T in Aeromonas hydrophila/caviae/sobria. These 3 antibiotic resistance

patterns were exhibited with isolates obtained from the water sample collected at Final

Effluent, although the former resistance pattern (KF, TS, Co, GM, AP & T) was repeated by

Kluyvera spp. at the Downstream site, also in September. It is probable that there was a

transfer of R-factor to this species, since previous isolates of the same species did not exhibit

this antibiotic resistance pattern. The presence of Salmonella species, which are naturally

multi-resistant organisms (Angulo 1997: 414) within this site, may explain that situation.

78

5.4 Conclusion

Evidence provided in this study has shown the presence of antibiotic-resistant and multiple

antibiotic-resistant coliforms in the Rietspruit River. All coliforms isolated showed a form of

this phenomenon. The contributing factors such as the proximity of both industrial and

human activities cannot be overlooked; as these are having a significant impact on the aquatic

ecosystem; wastes from domestic and industrial source will eventually end up in the water

body. The observation of coliforms in the same sample site exhibiting similar multiple

antibiotic resistance, even showing coliforms of the same species exhibiting increased

multiple antibiotic resistance dependent on the sample site and in some cases seasonal

changes, needs to be further investigated. One effect of great concern is the insignificant

difference in microbial activity when comparing the Upstream to the downstream (also taking

into consideration the limitation of cost to chlorine treatment) it implies that the final quality

of water reaching end users is questionable. Although studies done in the Eastern Cape

Province showed that even the treatment of water with chlorine was not adequate in

eliminating target pathogens as high levels were still detected in final effluents (Momba et al.

2006: 692); the total by-pass of chlorination treatment at the wastewater plant in Sebokeng

further compounds the problem contamination and would prove catastrophic on the long run

for end users of water from the Rietspruit River. The introduction of these AR and MAR

coliforms into the human system has far-reaching consequences and as a result, steps must be

taken to remove these organisms from the water by introducing better and structured

treatment measures.

79

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93

APPENDICES

94

APPENDIX A

95

APPENDIX A

Media and Reagents

A. Nutrient Agar (g/l)

Meat extracts 1.0

Peptone 5.0

Yeast extract 2.0

Sodium chloride 8.0

Agar 15.0

To prepare agar plates: dissolve 31g of agar in a litre of distilled water. Stir constantly

until solution boils. Autoclave at 121oC for 15 minutes. After sterilization leave to

cool to about 55oC and pour into petridishes and leave in laminar airflow to gel before

streaking.

B. mFc Agar (g/l)

A selective medium for the enrichment, cultivation and isolation of faecal coliforms.

Tryptose 10.0

Peptone 5.0

Yeast extract 3.0

Sodium chloride 5.0

Lactose 12.5

Bile salts no. 3 1.5

Aniline Blue 0.1

Agar 13.0

Suspend 50g in one litre of demineralised water. Bring to boil whilst constantly

stirring until agar dissolves completely. Mix well and pour plates immediately. Allow

agar surface to dry before use. This medium is best used with membrane filtration

technique. The mFc medium should not be autoclaved.

96

C. MacConkey Agar (g/l)

A selective medium suitable for the isolation of Salmonella, Shigella and coliform

bacteria from foods, urine, faeces, waste water etc.

Peptone 20.0

Lactose 10.0

Bile Salts No.3 1.5

Sodium Chloride 5.0

Neutral Red 0.03

Crystal Violet 0.001

Agar 13.5

Suspend 50g in one litre of demineralised water. Bring to boil whilst constantly

stirring until agar dissolves completely. Autoclave at 121oC for 15minutes. Cool to

about 45 – 50oC, mix well and pour plates.

D. Mueller Hinton Agar (g/l)

A medium suitable for testing for the sensitivity of clinically important pathogens

towards antibiotics or sulphonamides.

Meat Infusion 5.0

Casein Hydrolysate 17.5

Soluble Starch 1.5

Agar 14.0

Suspend 38g in one litre demineralised water and allow to stand for 15minutes. Boil

whilst constantly stirring until agar dissolves completely. Autoclave at 121oC for 15

minutes. Caution should be taken not to overheat

97

E. Trypton Soy Broth

A versatile liquid medium, suitable for general laboratory use. Due to its high

nutrient value it will produce a luxuriant growth of many fastidious organisms

without the addition of serum.

Tryptone 15.0

Soy Peptone 5.0

Sodium Chloride 5.0

di-Potassium Hydrogen

Phosphate 2.5

Dextrose 2.5

Suspend 30g in one litre demineralised water. Dispense into final containers and

autoclave at 121oC for 15 minutes.

F. Saline solution (85%)

Sodium Chloride 8.5g

Distilled water 1000ml

G. Acetone Alcohol

Acetone 30ml

95% ethanol 70ml

H. Crystal Violet

Crystal violet 2.0g

95% ethanol 20ml

98

I. Gram’s Iodine

Iodine 1.0g

Potassium iodide 2.0g

Distilled water 300ml

Mix the iodine crystals and potassium iodide in a mortar and grind until fine. Add

water and mix well. Store in tinted bottles.

J. Safranin

Safranin 0.25g

95% ethanol 10ml

Distilled water 100ml

Dissolve the safranin in the alcohol, add the water and filter.

99

APPENDIX B

100

APPENDIX B

Antibiotic Resistance Data

r = resistance; s = sensitive

Upstream Samples

DATE

COLLECTED

SAMPLES KF

30µg

TS

25µg

S

300µg

Co

10µg

GM

10µg

AP

10µg

T

30µg

MAR

INDEX

FEBRUARY US1 r s s s s r r 0.429

US2 r r s s s r r 0.571

US3 r r s s s r r 0.571

US4 r r s s s r r 0.571

US5 r s s s s r r 0.429

US6 r r s s s r r 0.571

US7 r r s s s r r 0.571

JUNE US1a r r s r s r r 0.714

US2a r r s r s r r 0.714

US3a r r s s s r r 0.571

US4a r r s r s r r 0.714

US5a r r s r s r r 0.714

US6a r r s r s r r 0.714

US7a r r s r s r r 0.714

SEPTEMBER US1b r r s r s r r 0.714

US2b r r s r s r r 0.714

US3b r r s r s r r 0.714

US4b r r s r s r r 0.714

US5b r r s r s r r 0.714

US6b r r s r s r r 0.714

US7b r r s r s r r 0.714

101

Final Effluent Samples

DATE

COLLECTED

SAMPLES KF

30µg

TS

25µg

S

300µg

Co

10µg

GM

10µg

AP

10µg

T

30µg

MAR

INDEX

FEBRUARY FE1 r r s r s r r 0.714

FE2 r r s r s r r 0.714

FE3 r r s r s r r 0.714

FE4 r r s s s r s 0.428

FE5 r r s s s r s 0.428

FE6 r r s s s r s 0.428

FE7 r r s s s r s 0.428

JUNE FE1a r r s s s r r 0.571

FE2a r r s s s r r 0.571

FE3a r r s s s r r 0.571

FE4a r r s r s r r 0.714

FE5a r s s r s r s 0.428

FE6a r s s r s r s 0.428

FE7a s s s s s r s 0.142

SEPTEMBER FE1b r r s r r r r 0.857

FE2b r r s r r r r 0.857

FE3b r s r r r r r 0.857

FE4b r s r s r r r 0.714

FE5b r r s r r r r 0.857

FE6b s s s r r r s 0.428

FE7b r r r r s r r 0.857

102

Down Stream Samples

DATE

COLLECTED

SAMPLES KF

30µg

TS

25µg

S

300µg

Co

10µg

GM

10µg

AP

10µg

T

30µg

MAR

INDEX

FEBRUARY DS1 r r s r s r r 0.714

DS2 r r s r s r r 0.714

DS3 r r s r s r r 0.714

DS4 r r s s s r r 0.571

DS5 r r s s s r r 0.571

DS6 r r s s s r r 0.571

DS7 r r s s s r r 0.571

JUNE DS1a r r s r s r r 0.714

DS2a r r s r s r r 0.714

DS3a r s s r s r r 0.571

DS4a r r s r s r r 0.714

DS5a r r s r s r r 0.714

DS6a r s s r s r r 0.571

DS7a r r s r s r r 0.714

SEPTEMBER DS1b s s s r s r s 0.286

DS2b r r s r r r r 0.857

DS3b r r s r s r r 0.714

DS4b r r s r r r s 0.714

DS5b r r s r r r r 0.857

DS6b s s s r s r r 0.428

DS7b r r s r s r r 0.714

103

APPENDIX C

104

APPENDIX C

CUMULATIVE FREQUENCY AND BAR CHARTS

Bacterial Resistance to Cephalothin (KF) for the months of February, June, September 2009

UPSTREAM

Month Frequency Relative frequency Cumulative frequency

February 7 0.111 0.111

June 7 0.111 0.222

September 7 0.111 0.333

FINAL EFFLUENT

February 7 0.111 0.444

June 6 0.095 0.539

September 6 0.095 0.634

DOWNSTREAM

February 7 0.111 0.745

June 7 0.111 0.856

September 5 0.079 0.935

Bacterial Resistance to Cotrimoxazole (TS) for the months of February, June, September 2009

UPSTREAM

Month Frequency Relative frequency Cumulative frequency

February 5 0.079 0.079

June 7 0.111 0.190

September 7 0.111 0.301

FINAL EFFLUENT

February 7 0.111 0.412

June 4 0.063 0.475

September 4 0.063 0.538

DOWNSTREAM

February 7 0.111 0.649

June 5 0.079 0.728

September 5 0.079 0.807

105

Bacterial Resistance to Streptomycin (S) for the months of February, June, September 2009

UPSTREAM

Month Frequency Relative frequency Cumulative frequency

February 0 0.000 0.000

June 0 0.000 0.000

September 0 0.000 0.000

FINAL EFFLUENT

February 0 0.000 0.000

June 0 0.000 0.000

September 3 0.047 0.047

DOWNSTREAM

February 0 0.000 0.047

June 0 0.000 0.047

September 0 0.000 0.047

Bacterial Resistance to Colistin sulphate (Co) for the months of February, June, September 2009

UPSTREAM

Month Frequency Relative frequency Cumulative frequency

February 0 0.000 0.000

June 6 0.095 0.095

September 7 0.111 0.206

FINAL EFFLUENT

February 3 0.047 0.253

June 3 0.047 0.300

September 6 0.095 0.395

DOWNSTREAM

February 3 0.047 0.442

June 7 0.111 0.553

September 7 0.111 0.664

106

Bacterial Resistance to Gentamycin (GM) for the months of February, June, September 2009

UPSTREAM

Month Frequency Relative frequency Cumulative frequency

February 0 0.000 0.000

June 0 0.000 0.000

September 0 0.000 0.000

FINAL EFFLUENT

February 0 0.000 0.000

June 0 0.000 0.000

September 6 0.095 0.095

DOWNSTREAM

February 0 0.000 0.095

June 0 0.000 0.095

September 3 0.047 0.144

Bacterial Resistance to Ampicillin (AP) for the months of February, June, September 2009

UPSTREAM

Month Frequency Relative frequency Cumulative frequency

February 7 0.111 0.111

June 7 0.111 0.222

September 7 0.111 0.333

FINAL EFFLUENT

February 7 0.111 0.444

June 7 0.111 0.555

September 7 0.111 0.666

DOWNSTREAM

February 7 0.111 0.777

June 7 0.111 0.888

September 7 0.111 0.999

107

Bacterial Resistance to Tetracycline (T) for the months of February, June, September 2009

UPSTREAM

Month Frequency Relative frequency Cumulative frequency

February 7 0.111 0.111

June 7 0.111 0.222

September 7 0.111 0.333

FINAL EFFLUENT

February 3 0.047 0.380

June 4 0.063 0.538

September 6 0.095 0.633

DOWNSTREAM

February 7 0.111 0.744

June 7 0.111 0.855

September 5 0.079 0.934

108

Fig. 1 Percentage resistance of Isolates to Cephalothin

US – Upstream

FE – Final Effluent

DS – Down Stream

26

27

28

29

30

31

32

33

34

US FE DS

FEBRUARY

JUNE

SEPTEMBER

109

Fig. 2 Percentage resistance of Isolates to Cotrimoxazole

US – Upstream

FE – Final Effluent

DS – Down Stream

0

5

10

15

20

25

30

35

US FE DS

FEBRUARY

JUNE

SEPTEMBER

110

Fig. 3 Percentage resistance of Isolates to Streptomycin

US – Upstream

FE – Final Effluent

DS – Down Stream

0

2

4

6

8

10

12

14

16

US FE DS

FEBRUARY

JUNE

SEPTEMBER

111

Fig. 4 Percentage resistance of Isolates to Colistin Sulphate

US – Upstream

FE – Final Effluent

DS – Down Stream

0

5

10

15

20

25

30

35

US FE DS

FEBRUARY

JUNE

SEPTEMBER

112

Fig. 5 Percentage resistance of Isolates to Gentamycin

US – Upstream

FE – Final Effluent

DS – Down Stream

0

5

10

15

20

25

30

US FE DS

FEBRUARY

JUNE

SEPTEMBER

113

Fig. 6 Percentage resistance of Isolates to Ampicillin

US – Upstream

FE – Final Effluent

DS – Down Stream

0

5

10

15

20

25

30

35

US FE DS

FEBRUARY

JUNE

SEPTEMBER

114

Fig. 7 Percentage resistance of Isolates to Tetracycline

US – Upstream

FE – Final Effluent

DS – Down Stream

0

5

10

15

20

25

30

35

US FE DS

FEBRUARY

JUNE

SEPTEMBER

115

Fig. 8 Total Percentage Resistance of All Isolates to All Antibiotics Used in Study

KF – Cephalothin

TS – Cotrimoxazole

S – Streptomycin

Co – Colistin sulphate

GM – Gentamycin

AP – Ampicillin

T – Tetracycline

0

10

20

30

40

50

60

70

80

90

100

KF TS S Co GM AP T

116

APPENDIX D

117

APPENDIX D

ISOLATES AND THEIR ANTIBIOTIC RESISTANCE PATTERNS

Upstream Samples

DATE

COLLECTED

SAMPLES

ANTIBIOTIC

RESISTANCE PATTERN

TAXON

FEBRUARY US1 KF, AP,T Pantoea spp.

US2 KF,TS,AP,T Klebsiella pneumoniae

US3 KF,TS,AP,T Klebsiella pneumoniae

US4 KF,TS,AP,T Kluyvera spp.

US5 KF,AP,T Escherichia coli

US6 KF,TS, AP,T Rahnella aquatilis

US7 KF, TS, AP,T Klebsiella oxytoca

JUNE US1a KF, TS, Co, AP,T Kluyvera spp

US2a KF, TS ,Co, AP,T Serratia fonticola

US3a KF,TS,AP,T Escherichia coli

US4a KF, TS, Co, AP,T Enterobacter cloacae

US5a KF, TS, Co, AP,T Escherichia coli

US6a KF, TS, Co, AP,T Serratia marcescens

US7a KF, TS, Co, AP,T Klebsiella oxytoca

SEPTEMBER US1b KF, TS, Co, AP,T Klebsiella oxytoca

US2b KF, TS, Co, AP,T Serratia marcescens

US3b KF, TS, Co, AP,T Serratia marcescens

US4b KF, TS, Co, AP,T Raoultella ornithinolytica

US5b KF, TS, Co, AP,T Serratia odorifera

US6b KF, TS, Co, AP,T Salmonella spp.

US7b KF, TS, Co, AP,T Raoultella ornithinolytica

118

Final Effluent Samples

DATE

COLLECTED

SAMPLES

ANTIBIOTIC

RESISTANCE PATTERN

TAXON

FEBRUARY FE1 KF, TS, Co, AP, T Kluyvera spp.

FE2 KF,TS, Co, AP,T Kluyvera spp.

FE3 KF, TS. Co. AP,T Escherichia coli

FE4 KF,TS,AP, T Escherichia coli

FE5 KF, TS, AP, T Escherichia coli

FE6 KF, TS, AP, T Enterobacter cloacae

FE7 KF, TS, AP Klebsiella pneumonia

JUNE FE1a KF, TS, AP, T Enterobacter cloacae

FE2a KF, TS,AP, T Citrobacter freundii

FE3a KF, TS,AP,T Escherichia coli

FE4a KF, TS, Co, AP,T Serratia marcescens

FE5a KF, Co, AP Klebsiella pneumoniae ssp. ozoenae

FE6a KF, Co, AP Enterobacter cloacae

FE7a AP Klebsiella oxytoca

SEPTEMBER FE1b KF, TS, Co, GM, AP,T Pantoea spp.

FE2b KF, TS, Co, GM, AP,T Salmonella spp.

FE3b KF, S, Co, GM, AP,T Aeromonas hydrophila/caviae/sobria 1

FE4b KF,S,GM,AP,T Klebsiella oxytoca

FE5b KF, TS, Co, GM,AP,T Klebsiella pneumoniae ssp. ozaenae

FE6b Co, GM, AP Klebsiella oxytoca

FE7b KF, TS, S, Co, AP,T Kluyvera spp.

119

Down Stream Samples

DATE

COLLECTED

SAMPLES

ANTIBIOTIC RESISTANCE

PATTERN

TAXON

FEBRUARY DS1 KF, TS, Co ,AP,T Enterobacter cloacae

DS2 KF, TS, Co, AP,T Pantoea spp.

DS3 KF, TS, Co, AP,T Rahnella aquatilis

DS4 KF,TS,AP,T Serratia ficaria

DS5 KF,TS,AP,T Enterobacter amnigenus1

DS6 KF,TS,AP,T Klebsiella oxytoca

DS7 KF,TS,AP,T Escherichia coli

JUNE DS1a KF, TS, Co, AP,T Escherichia coli

DS2a KF, TS, Co ,AP,T Pantoea spp.

DS3a KF, Co, AP,T Serratia fonticola

DS4a KF, TS, Co, AP,T Serratia ficaria

DS5a KF, TS, Co, AP, T Serratia marcescens

DS6a KF, Co, AP,T Enterbacter cloacae

DS7a KF, TS, Co, AP,T Escherichia coli

SEPTEMBER DS1b Co, AP Salmonella spp.

DS2b KF,TS, Co, GM,AP,T Serratia odorifera

DS3b KF, TS, Co, AP,T Serratia odorifera

DS4b KF, TS, Co, GM,AP,T Serratia odorifera

DS5b KF, TS, Co, GM,AP,T Kluyvera spp.

DS6b Co, AP,T Kluyvera spp

DS7b KF, TS, Co, AP,T Kluyvera spp.

120

APPENDIX E

121

APPENDIX E: API 20E IDENTIFICATION

FEBRUARY RESULTS: UPSTREAM

ON

PG

AD

H

LD

C

OD

C

|CIT

|

H2S

UR

E

TD

A

IND

|VP

|

GE

L

GL

U

MA

N

INO

SO

R

RH

A

SA

C

ME

L

AM

Y

AR

A

IDENTIFICATION

COMMENT

TAXON

1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2

US1

+ - - - + - - - + - - + + + + + + + + + LOW DISCRIMINATION –

77.2% (identification); possibility

of Raoultella planticola

Pantoea spp.

1 2 4 4 7 7 3

US2

+ - + + - + + - - - - + - + + + + + + + GOOD IDENTIFICATION –

97.2% (identification); possibility

of Raoultella planticola

Klebsiella pneumoniae

5 2 1 4 6 7 3

US3

+ - + - + - + - - - - + - + + + + + + + GOOD IDENTIFICATION –

97.2% (identification); possibility

of Raoultella planticola

Klebsiella pneumoniae

5 2 1 4 6 7 3

US4

+ - + + + - - - + - - + + - + + + + + + GOOD IDENTIFICATION –

93.9% (identification)

Kluyvera spp.

5 3 4 4 5 7 3

US5

+ - + + - - - - + - - + + - + + - + - + VERY GOOD IDENTIFICATION

– 99.5% (identification)

Escherichia coli

5 1 4 4 5 7 2

US6 + - - - + - - + - + - + + - + + + + - + DOUBTFUL PROFILE – 95.3%

(identification)

Rahnella aquatilis

1 2 2 5 5 7 2

US7

+ - + - - - + - + - - + + + + + + + + + VERY GOOD IDENTIFICATION

– 99.1% (identification)

Klebsiella oxytoca

5 0 5 4 7 7 3

122

FEBRUARY RESULTS: FINAL EFFLUENT (AFTER TREATMENT)

O

NP

G

AD

H

LD

C

OD

C

|CIT

|

H2S

UR

E

TD

A

IND

|VP

|

GE

L

GL

U

MA

N

INO

SO

R

RH

A

SA

C

ME

L

AM

Y

AR

A

IDENTIFICATION

COMMENT

TAXON

1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2

FE1

+ - + + + - - - + - - + + - + + + + + + GOOD IDENTIFICATION –

93.9% (identification)

Kluyvera spp.

5 3 4 4 5 7 3

FE2

+ - + + - - - - + - - + + - + + + + + + LOW DISCRIMINATION –

83.9% (identification)

Kluyvera spp.

5 1 4 4 5 7 3

FE3

+ - + + - - - - + - - + + - + + - + - + EXCELLENT IDENTIFICATION

– 99.9% (identification)

Escherichia coli

5 1 4 4 5 5 2

FE4

+ - + + - - - - + - - + + - + + + + - + VERY GOOD IDENTIFICATION

– 99.5% (identification)

Escherichia coli

5 1 4 4 5 7 2

FE5

+ - + + - - - - + - - + + - + + - + - + EXCELLENT IDENTIFICATION

– 99.9% (identification)

Escherichia coli

5 1 4 4 5 5 2

FE6 + + - + + - + - - + - + + - + + + + + + GOOD IDENTIFICATION –

96.6% (identification)

Enterobacter cloacae

3 3 1 5 5 7 3

FE7

+ - + - + - + - - - - + - + + + + + + + GOOD IDENTIFICATION –

97.2% (identification)

Klebsiella pneumonia

5 2 1 4 6 7 3

123

FEBRUARY RESULTS: DOWNSTREAM

O

NP

G

AD

H

LD

C

OD

C

|CIT

|

H2S

UR

E

TD

A

IND

|VP

|

GE

L

GL

U

MA

N

INO

SO

R

RH

A

SA

C

ME

L

AM

Y

AR

A

IDENTIFICATION

COMMENT

TAXON

1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2

DS1

+ + - + + - + - - + - + + - + + + + + + GOOD IDENTIFICATION –

96.6% (identification)

Enterobacter cloacae

3 3 1 5 5 7 3

DS2

+ - - - + - - - + + - + + - + + + + + + GOOD IDENTIFICATION –

98.7% (identification); possibility

of Erwinia spp.

Pantoea spp.

1 2 4 5 5 7 3

DS3

+ - - - + - - + - + - + + - + + + + - + DOUBTFUL PROFILE – 95.3%

(identification)

Rahnella aquatilis

1 2 2 5 5 7 2

DS4

+ - - - + - - - - + + + + - + + + + - + DOUBTFUL PROFILE – 91.7%

(identification)

Serratia ficaria

1 2 0 7 5 7 2

DS5

+ + - + + - - - - - - + + - - + + + + + VERY GOOD IDENTIFICATION

TO THE GENUS – 55.3%

(identification); possibility of E.

cloacae

Enterobacter amnigenus1

3 3 0 4 1 7 3

DS6

+ - + - + - + - + - - + + + + + + + + + LOW DISCRIMINATION –

94.8% (identification); possibility

Raoultella planticola

Klebsiella oxytoca

5 2 5 4 7 7 3

DS7 + - + + - - - - + - - + + - + + - + - + EXCELLENT IDENTIFICATION

– 99.9% (identification)

Escherichia coli

5 1 4 4 5 5 2

124

JUNE RESULTS: UPSTREAM

O

NP

G

AD

H

LD

C

OD

C

|CIT

|

H2S

UR

E

TD

A

IND

|VP

|

GE

L

GL

U

MA

N

INO

SO

R

RH

A

SA

C

ME

L

AM

Y

AR

A

IDENTIFICATION

COMMENT

TAXON

1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2

US1a

+ - + + + - - - + - - + + - + + + + + + GOOD IDENTIFICATION –

93.9% (identification)

Kluyvera spp

5 3 4 4 5 7 3

US2a

+ - + + + - - - - - - + + + + + + + + + LOW DISCRIMINATION –

55.1% (identification);

Serratia fonticola

5 3 0 4 7 7 3

US3a

+ - + - + - + - - - - + - + + + + + + + GOOD IDENTIFICATION –

98.1% (identification);

Escherichia coli

5 0 4 4 5 4 2

US4a

+ + + + + - - - - - - + + - + + + + + + GOOD IDENTIFICATION –

96.6% (identification)

Enterobacter cloacae

7 3 0 4 5 7 3

US5a

+ - + + - - - - + - - + + - - + - + - + GOOD IDENTIFICATION –

97.7% (identification)

Escherichia coli

5 1 4 4 1 5 2

US6a

+ - + + - - - - - + + + + - + - + - + - VERY GOOD IDENTIFICATION

TO THE GENUS – 84.9%

(identification)

Serratia marcescens

5 1 0 7 5 2 1

US7a

+ - + - - - + - + - - + + + + + + + + + VERY GOOD IDENTIFICATION

– 99.1% (identification)

Klebsiella oxytoca

5 0 5 4 7 7 3

125

JUNE RESULTS: FINAL EFFLUENT (AFTER TREATMENT)

O

NP

G

AD

H

LD

C

OD

C

|CIT

|

H2S

UR

E

TD

A

IND

|VP

|

GE

L

GL

U

MA

N

INO

SO

R

RH

A

SA

C

ME

L

AM

Y

AR

A

IDENTIFICATION

COMMENT

TAXON

1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2

FE1a

+ + - - + - - - - + - - - - + + + + + + GOOD IDENTIFICATION –

96.8% (identification)

Enterobacter cloacae

3 2 0 1 4 7 3

FE2a

+ + - - + + - - - - - + + + + + + + + + EXCELLENT IDENTIFICATION

– 99.9% (identification)

Citrobacter freundii

3 6 0 4 7 7 3

FE3a

+ - + + - - - - + - - + + - + + - + - + EXCELLENT IDENTIFICATION

– 99.9% (identification)

Escherichia coli

5 1 4 4 5 5 2

FE4a

+ - + + - - - - - + + + + - + - + - + - VERY GOOD IDENTIFICATION

TO THE GENUS – 84.9%

(identification)

Serratia marcescens

5 1 0 7 5 2 1

FE5a

- - - - - - - - - - - + + + + + + + + + LOW DISCRIMINATION –

33.9% (identification)

Klebsiella pneumoniae ssp.

Ozoenae

0 0 0 4 7 7 3

FE6a

+ + - + + - + - - + - + + - + + + + + + GOOD IDENTIFICATION –

96.6% (identification)

Enterobacter cloacae

3 3 1 5 5 7 3

FE7a

+ - + - - - + - + - - + + + + + + + + + VERY GOOD IDENTIFICATION

– 99.1% (identification)

Klebsiella oxytoca

5 0 5 4 7 7 3

126

JUNE RESULTS: DOWNSTREAM

O

NP

G

AD

H

LD

C

OD

C

|CIT

|

H2S

UR

E

TD

A

IND

|VP

|

GE

L

GL

U

MA

N

INO

SO

R

RH

A

SA

C

ME

L

AM

Y

AR

A

IDENTIFICATION

COMMENT

TAXON

1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2

DS1a

+ - + - - - - - - - + + + - + + - + - + DOUBTFUL PROFILE – 86.8%

(identification)

Escherichia coli

5 0 0 6 5 5 2

DS2a

+ - - - + - - - + + - + + - + + + + + + GOOD IDENTIFICATION –

98.7% (identification); possibility

of Erwinia spp.

Pantoea spp.

1 2 4 5 5 7 3

DS3a

+ - - + + - - - - - - + + + + + + + + + GOOD IDENTIFICATION –

95.3% (identification)

Serratia fonticola

1 3 0 4 7 7 3

DS4a

+ - - - + - - - - + + + + - + + + + - + DOUBTFUL PROFILE – 91.7%

(identification)

Serratia ficaria

1 2 0 7 5 7 2

DS5a

+ - + + + - + - - - - + + + + + + + + - DOUBTFUL PROFILE – 38.7%

(identification)

Serratia marcescens

5 3 1 4 7 7 1

DS6a

+ - + - + - + - + - - + + + + + + + + + GOOD IDENTIFICATION –

96.6% (identification)

Enterbacter cloacae

3 3 1 5 5 7 3

DS7a + - + + - - - - + - - + + - + + - + - + EXCELLENT IDENTIFICATION

– 99.9% (identification)

Escherichia coli

5 1 4 4 5 5 2

127

SEPTEMBER RESULTS: UPSTREAM

O

NP

G

AD

H

LD

C

OD

C

|CIT

|

H2S

UR

E

TD

A

IND

|VP

|

GE

L

GL

U

MA

N

INO

SO

R

RH

A

SA

C

ME

L

AM

Y

AR

A

IDENTIFICATION

COMMENT

TAXON

1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2

US1b

- + + - + - + - + - - + + + + + + + + + DOUBTFUL PROFILE – 97.3%

(identification); possibility of

Raoultella planticola

Klebsiella oxytoca

6 2 5 4 7 7 3

US2b

+ - + + + - + - - - - + + + + + + + + - DOUBTFUL PROFILE – 38.7%

(identification)

Serratia marcescens

5 3 1 4 7 7 1

US3b

+ - + + - - - - - + + + + - + - + - + - VERY GOOD IDENTIFICATION

TO THE GENUS – 84.9%

(identification)

Serratia marcescens

5 1 0 7 5 2 1

US4b

+ + + + + - + - + - - + + - + + + + + + DOUBTFUL PROFILE – 98.6%

(identification)

Raoultella ornithinolytica

7 3 5 4 5 7 3

US5b

- - + + + - - - + - + + + + + + + + + + EXCELLENT IDENTIFICATION

– 99.9% (identification).

Serratia odorifera

4 3 4 6 7 7 3

US6b

- + + + + - - - + - - + + - + + + + - + ACCEPTABLE

IDENTIFICATION – 94.2%

(identification)

Salmonella spp.

6 3 4 4 5 7 2

US7b

- - + + + - + - + - - + - + + + + + + + DOUBTFUL PROFILE – 99.8%

(identification)

Raoultella ornithinolytica

4 3 5 4 6 7 3

128

SEPTEMBER RESULTS: FINAL EFFLUENT (AFTER TREATMENT)

O

NP

G

AD

H

LD

C

OD

C

|CIT

|

H2S

UR

E

TD

A

IND

|VP

|

GE

L

GL

U

MA

N

INO

SO

R

RH

A

SA

C

ME

L

AM

Y

AR

A

IDENTIFICATION

COMMENT

TAXON

1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2

FE1b

+ - - - + - - - + - - + + + + + + + + + LOW DISCRIMINATION –

77.2% (identification); possibility

of Raoultella planticola

Pantoea spp.

1 2 4 4 7 7 3

FE2b

- + + + + - - - + - - + + - + + + + - + ACCEPTABLE

IDENTIFICATION – 94.2%

(identification)

Salmonella spp.

6 3 4 4 5 7 2

FE3b

+ + + - - - - - - - + + + - - - + - - - DOUBTFUL PROFILE – 56.1%

(identification)

Aeromonas

hydrophila/caviae/sobria 1

7 0 0 6 1 2 0

FE4b

- - + - - - + - + - - + + + + + + + + + GOOD IDENTIFICATION –

99.5% (identification)

Klebsiella oxytoca

4 0 5 4 7 7 3

FE5b

- - - - - - - - - - - + + + + + + + + + LOW DISCRIMINATION –

33.9% (identification)

Klebsiella pneumoniae ssp.

ozaenae

0 0 0 4 7 7 3

FE6b - - + - + - + - + - - + + + + + + + + + GOOD IDENTIFICATION –

97.3% (identification)

Klebsiella oxytoca

4 2 5 4 7 7 3

FE7b

- - + + + - - - + - - + + - + + + + - + DOUBTFUL PROFILE – 71.5%

(identification)

Kluyvera spp.

4 3 4 4 5 7 2

129

SEPTEMBER RESULTS: DOWNSTREAM

O

NP

G

AD

H

LD

C

OD

C

|CIT

|

H2S

UR

E

TD

A

IND

|VP

|

GE

L

GL

U

MA

N

INO

SO

R

RH

A

SA

C

ME

L

AM

Y

AR

A

IDENTIFICATION

COMMENT

TAXON

1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2 4 1 2

DS1b

- + + + + - - - + - - + + - + + + + - + ACCEPTABLE

IDENTIFICATION – 94.2%

(identification)

Salmonella spp

6 3 4 4 5 7 2

DS2b

- - + + + - - - + - + + + + + + + + + + EXCELLENT IDENTIFICATION

– 99.9% (identification)

Serratia odorifera

4 3 4 6 7 7 3

DS3b

- - + + + - - - + - + + + + + + + + + + EXCELLENT IDENTIFICATION

– 99.9% (identification).

Serratia odorifera

4 3 4 6 7 7 3

DS4b

- - + + + - - - + - + + + + + + + + + + EXCELLENT IDENTIFICATION

– 99.9% (identification).

Serratia odorifera

4 3 4 6 7 7 3

DS5b

+ - + + - - - - + - - + + - + + + + + + LOW DISCRIMINATION –

83.9% (identification)

Kluyvera spp.

5 1 4 4 5 7 3

DS6b

+ - + + + - - - + - - + + - + + + + + + GOOD IDENTIFICATION –

93.9% (identification)

Kluyvera spp.

5 3 4 4 5 7 3

DS7b - - + + + - - - + - - + + - + + + + - + DOUBTFUL PROFILE –71.5%

(identification)

Kluyvera spp.

4 3 4 4 5 7 2

130