Programming Hypothesis on Life Phenomena and the Key Processes Simulation

Jun Ma1, a, Shuyan Li2,b and Yide Ma 3,c 1,3 The School of Information Science and Engineering Lanzhou University, Lanzhou, China

2 Lanzhou University Chemistry and Chemical Engineering Lanzhou University,Lanzhou, China

amajun@lzu.edu.cn, blishuyan@lzu.edu.cn, cydma@lzu.edu.cn

Keywords: Programming hypothesis on life phenomena, Program simulation, Gene expression, Cell division and differentiation, Life evolution, P-code, reflection technology

Abstract. The formula that life process follows is a major scientific mystery during centuries. Some

people put programming thoughts into this field like Gates brought the idea that “Human DNA is like

a computer program but far, far more advanced than any software we’ve ever created”[1]. Here we

proposed a more specific hypothesis on this topic as that DNA is a set of p-code[2] and the enzymes

which control chemical reactions and transport processes in cell metabolism are the basic

instructions. Based on this hypothesis, some program models were developed successfully in this

work to simulate the key processes of life phenomena: gene expression, cell division and

differentiation, and life evolution. The results of these simulations show that there is a high level of

similarity between life phenomena and computer programs; the process of cell differentiation and

evolution of life can be explained in a programming way. These models also suggest that reflection

technology[3, 4] is essential to life process. Besides, C-value paradox, N-value paradox[5] and

pseudogene as well as some other biological problems could be also explained by these programming

models. These conclusions imply that life phenomena are consistent with the concept of “process” in

computer fields.

Introduction

The coding principle of life information challenges scientists for centuries and variety studies were

developed to approaching this goal. Recently, it is noticed that there are similarities between DNA

sequences and computer program code and consequently the programming explanation became

popular in this field. D'Onofrio viewed a cell “as a complete computational machine in terms that are

akin to a multi-core computer cluster, where there is a centralized memory and instruction set, yet

computational tasks are distributed among distinct processing elements”[6]. Flynn considered DNA

as an example of shared memory in a distributed heterogeneous multiprocessor system with multiple

input streams and multiple output streams[7]. In this way, each cell has over 2,000 different enzyme

computers that read the shared memory data in DNA, processing that data according to the individual

programs, many operating independently[8]. In the last 10 years, at least 20 different natural

information codes were discovered in life, each operating according to arbitrary conventions. Such as

proteins address codes[9], acetylation codes[10], RNA codes[11], metabolic codes[12], cytoskeleton

codes[13], histone codes[14], and alternative splicing codes[15]. All these codes suggested that the

complexities of biology are growing by orders of magnitude[16], and the signaling information in

cells is organized through networks of information rather than simple discrete pathways which are

similar to computer program as well. Whole-cell simulation[17] and the game of life evolving

program[18] are performed based on the ideas above.

These theories inspired our group to proposed the hypothesis that a DNA chain is an intermediate

code sequence, which stores the operation codes and operands in a p-code way. Life is macroscopic

showing that is presented by the p-code sequence in running status, as a computer process. The basic

instructions of this program are various enzymes, which control chemical reactions and transport

processes in cell metabolism.

Advanced Materials Research Vol. 647 (2013) pp 258-263© (2013) Trans Tech Publications, Switzerlanddoi:10.4028/www.scientific.net/AMR.647.258

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Comparison of life phenomena with computer programs

By comparing several programming languages with the process of cell metabolism, it is discovered

that Java processes the most similarities since it provides a p-code(Byecode) technology which is

more similar to DNA coding methodology than other languages. The comparison details of Jave with

cell metabolism were shown in Fig. 1a. Therefore, Java was utilized here in this paper to simulate the

the life phenomena.

If enzymes were considered as the basic instruction set for implementing cell metabolism by

controlling various chemical reactions or transport forms, then the running mode of life program

would be very similar to Java program, while RNA would be similar to the intermediate codes of

JVM (Java virtual machine) instructions, which need to be transformed to proteins. In these proteins,

the enzymes are similar to CPU instructions and they will be used to control chemical reactions of

metabolism, while the non-enzyme proteins are similar to the data in computer system, as shown in

Fig.1a. In addition, it is easier to understand the central dogma from the programming view, as shown

in Fig.1b and Fig.1c.

Simulation of key life processes

Figure 1.Comparison of cell life procedure and Java program execution procedure. a, Illustration of the

similarities of Java bytecode codes in computer program and DNA codes in cell program. b, Illustration of the

Central Dogma of molecular biology. c, Illustration of Central Dogma by programming model. The Center of

program is the bytecode sequence which is composed by the JVM instructions, A indicates that JVM loads

bytecode sequence and makes it into running state. B indicates that JVM instructions are translated into machine

instructions and then they were executed; C indicates that the bytecode instructions are wrote into the stored

bytecode sequence reversely, similar to the process as RNA reverse transcription to DNA; D indicates that the

bytecode sequence replicates itself which is controlled by machine instructions, similar to DNA replication

process which is controlled by DNA polymerases.

Based on the analysis above, the simulation of gene expression was put forward as follows: Firstly, appropriate gene class was selected from the chromosome and in this case javassist.CtClass (an abstract representation of a Java class in non-running state) object was utilized. Secondly, the objects were loaded into JVM through custom classloader, which made it into running state. Here java.lang.Class (an abstract representation of a Java class in running state) object was used. This procedure simulated the transcription from DNA to RNA. In whole process, the code sequence was not changed, but transformed from stored state into running state. Thirdly, the class object produced an instance object. This procedure simulated the translation from RNA to protein. Finally, the corresponding chemical reactions or transport forms were executed by the instance object. The principle of the specific gene function expression of a cell showed in Fig.2.

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Figure 2.Abstracted gene expression process. a, a gene was simulated using a Java class, which contains three

subparts: cell function expression, regulation of cell division and other auxiliary code. b, A chromosome is a

combination of a group of genes. c, Shows a gene expression process.

In addition, combining with Reflection technology[19] and Bytecode engineering technology[20],

another two programming models were constructed in this paper for the other two key life processes:

Cell division and differentiation l and life evolution [21].

In a life cycle of cell division, the first step is related to DNA replication and separation. The

second stage related to the products of gene expression which involves transcription and translation of

DNA segments, and tries to decode and express the new gene. From the perspective of programming,

the growth of life is a process that organism loading and decoding DNA codes and also is the process

of cell division and differentiation which controlled by the DNA codes and the internal and external

environment of the cell. Since one type of cell is determined by a group of genes, k types of cells will

be determined by m genes. Let xi represents the code part of cell function expression and yi represents

the code part of regulation of cell division, then the vector X (xk1, xk2, xk3 ...) and Y (yk1, yk2, yk3 ...) will

determine the expression of cell function and regulation function. The principle of cell division and

differentiation showed in Fig.3.

Figure 3.Abstracted process of cell division. a, Division process of a cell. Decoded x will generate productions

for implementing specific function, and decoded y will generate productions for regulating gene expression.

These productions are used to activate the subsequent genes according to the reflection of current environment

condition. Then, the cell will generate a new type of cell. If the activation conditions are not met, the cell will

make regeneration division. b, Schematic diagram of process that how a set of gene groups determine various

type of cells from a global view, in which, F(X) and G(Y) respectively represent the decoding operation for X

and Y.

260 Biomaterial and Bioengineering

When program starts, it generates an embryonic stem cell object first, then continuously decodes

DNA coding sequences and generates various cells that have different functions. These cells will do

their own works, and then die randomly. If all the cells are dead, the organism will be over. The cell

function expression and regulation of cell differentiation are implemented through the reflection to

environment conditions. This model performed properly to simulate the processes of cell division and

differentiation, function expression and death degradation. It indicated that reflection mechanism is

crucial in life process.

Relative to cell division, Life evolution process is more abstract and complex. From a long time

span, life evolution can be seemed as an evolving process of life-program p-code sequence (DNA

molecular chains). An Evolutionary Programming Model[22] is utilized here to simulate the process.

In order to get a concise model, the gene function expressions in cell level were ignored and the genes

here in this process are only used to simulate macro behavior.

Assume a single-sex breeding dog, having a virtual genome as Fig.4a, is abstracted to simulating

this process. As shown in Fig.4b, firstly, several dog objects are generated by the same genome, and

then some of these dogs generate gene mutations randomly or through reflection. The dogs, which are

adapted to the environment, will generate offspring, and the others will die. Hence, the instance object

of the offspring has new abilities as shown in Fig.4c, which is as same as breeding phenomena in

biological world. This showed our program model can simulate the life evolution process in some

degree.

Figure 4.Abstracted process of evolutionary program. a, Genome of abstracted dog in parent generation. b,

Schematic diagram of the evolutionary program. c, Genome of offspring, in which the code sequence of gene0

has been changed, and a new gene (genex) which can properly adapt the environment has been appended.

Results and discussions

The models performed properly to simulate the processes of gene expression, cell division and

differentiation, function expression, death degradation and life evolution. The result showed that these

program models were able to simulate the life phenomena perfectly in a macro-scale way Thus it

concluded that if DNA coding sequences were regarded as a set of programming p-codes, the life

phenomena would be fully consistent with the concept of computer processes. This implies that life

phenomena are macroscopic presentations of static program-coding sequence in running status and the

codes were stored in DNA chain by a special p-code way. Besides, the simulating model for cell

division and differentiation suggested that reflection mechanism is crucial in life process.

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When life program is running, a cell can be seemed as a microprocessor. Its signal channel[23] is

similar to the integrated circuit of computer chip, but the instruction set is more complex than

computer instruction set. Different from computer instructions that merely consume energy, the

instructions of a cell do not only consume energy, but also release or store energy. For life program

and computer program, although the complexity of their instruction sets is different, the essence of

them are the same from a procedural point of view: both are ordered instruction sequence, and both

can continuously run when there is enough amount of energy supply, and then perform the outcomes

as macro life phenomena by the organism or processing results by the computer. Based on this

modeling idea, it is discovered that many other pathways of metabolism, such as carbohydrate

metabolism, lipid metabolism, amino acids, nucleic acid metabolism and the citric acid cycle, are all

consistent with the work principle of sub-program.

Through program modeling and simulation, we are more convinced that the life phenomenon is a

process (which is the instructions continuously executing). The code of life program is stored in the

DNA in a p-code way. Chromosome is the compressed structure for the storage of these codes. And

we believe that the difference between chemical structures of deoxyribonucleotide and ribonucleotide

is just the difference of this p-code in stored status and running status.

In this p-code programming theory about DNA sequence, some exploratory explanation can be

provided for certain biological phenomena:

Exons and introns. Exons may be the codes that can be expressed as protein, while introns may be

the code that can indicate the position mark, regulation mark and temporary carrier.

Pseudogene. Maybe pseudogene is the outdated genes, which are not used at current growing

environment of organisms, but still have biological activities and positioning functions. They cannot

be removed because that cell differentiation process needs them to locate the follow-up gene.

Otherwise, it will cause inaccurate positioning, and then influencing the life process.

C-value paradox and N-value paradox. Since it is well known in the computer world that there are

no necessary connections between the complexity and code size of a computer program, the C-value

paradox and N-value paradox problem could be easily solved by considering a DNA coding sequence

as a program code.

Conclusions and methods summary

Inspired by the previous outstanding works, this paper puts forward a hypothesis: a DNA chain is a set

of intermediate programming codes which stores instructions and data, similar to Java bytecode

program in storing state; an mRNA chain is the programming codes in running state, similar to Java

bytecode program in running state. Life phenomena are the macroscopic performances of life program

when it starts running, which bases on cooperation of two related instruction, as RNA instruction set

and protease instruction set. These two sets are similar to JVM bytecode instructions and CPU

machine code instructions. In addition, based on this hypothesis, some computer program models were

developed in this work to simulate some key procedures of life phenomena: gene expression,

cell–division cycle and life evolution. These simulations show us that there is a high level of similarity

between life phenomena and computer process.

First, a gene is abstracted as a java class. Consequently, a chromosome can be composed of a series

of java classes. Then gene expression process and cell division and differentiation process can be

simulated. In this process we created many cell objects. Each object will activate or restrain the

corresponding genes according to various conditions and decode the activated genes. Decoding

process consists of two sub-processes. The first one is to locate and obtain the activated gene class in

chromosome, and uses a custom classloader to load it into JVM. This process is similar to the

transcription from DNA to RNA and RNA modification process. The second one is that JVM

translates the bytecode instructions in gene class into computer instructions, and executes these

instructions under appointed conditions. This process is similar to the translation from RNA to protein

and protein function expression. Cell division and differentiation is a continuous process of obtaining

and decoding genes.

262 Biomaterial and Bioengineering

Second, Evolutionary Programming Model is utilized here to simulate life evolution process. After

loaded and run the program which is designed by using EPM, the program's code sequence may be

changed. If the design is very exquisite, the program can perceive the environment and make

adaptive changes each time it runs, and then the program will have the ability to evolve. In our

program model only macro behaviors of organism were simulated while the gene function

expressions in cell level were ignored here in order to get a concise model.

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