Aflatoxin conducive and non-conducive growth conditions reveal new gene associations with aflatoxin...

Fungal Genetics and Biology 42 (2005) 506–518

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AXatoxin conducive and non-conducive growth conditions revealnew gene associations with aXatoxin production

Michael S. Price a, Shannon B. Conners b, Sabrina Tachdjian b, Robert M. Kelly b,Gary A. Payne a,¤

a Center for Integrated Fungal Research, North Carolina State University, Raleigh, NC 27695-7244, USAb Department of Chemical Engineering, North Carolina State University, Raleigh, NC 27695-7905, USA

Received 26 October 2004; accepted 8 March 2005

Abstract

Research on aXatoxin (AF) production has traditionally focused on deWning the AF biosynthetic pathway with the goal of identi-fying potential targets for intervention. To understand the eVect of nitrogen source, carbon source, temperature, and pH on the regu-lation of AF biosynthesis, a targeted cDNA microarray consisting of genes associated with AF production over time was employed.Expression proWles for genes involved in AF biosynthesis grouped into Wve clades. A putative regulon was identiWed consisting of 20genes that were induced in the conducive nitrogen and pH treatments and the non-conducive carbon and temperature treatments, aswell as four other putative regulons corresponding to each of the four variables studied. Seventeen genes exhibited consistent induc-tion/repression proWles across all the experiments. One of these genes was consistently downregulated with AF production. Overex-pression of this gene resulted in repression of AF biosynthesis. The cellular function of this gene is currently unresolved. 2005 Elsevier Inc. All rights reserved.

Keywords: AXatoxin; Gene expression; Regulation; Aspergillus Xavus; Aspergillus parasiticus

1. Introduction

AXatoxins (AF) are carcinogenic polyketides pro-duced during secondary metabolism by Wve species ofAspergilli: A. Xavus, A. parasiticus, A. nomius, A. pseu-dotamarii, and A. bombycis (Samson, 2001; Varga et al.,2003). Only two of these species, A. Xavus and A. parasit-icus, are of agronomic importance and cause annuallosses of approximately $270M (Richard and Payne,2003). These fungi cause pre-harvest rots on corn, pea-nuts, various tree nuts, and cotton. Furthermore, theyare a post-harvest problem in many areas of the world.The main concern with these fungi is not the disease theycause, but their ability to contaminate food with AF.

* Corresponding author. Fax: +1 919 513 0024.E-mail address: [email protected] (G.A. Payne).

1087-1845/$ - see front matter 2005 Elsevier Inc. All rights reserved.doi:10.1016/j.fgb.2005.03.009

The regulation of AF biosynthesis has been studiedsince 1965, when a possible role of kojic acid in AF pro-duction was investigated (Heathcot et al., 1965). Sincethat time, the biosynthetic pathway for AF has been elu-cidated and a speciWc transcriptional regulator has beencharacterized (Chang et al., 1993; Woloshuk et al., 1994).Regulation appears to involve several gene products andis linked to fungal development (Calvo et al., 2002). Inaddition, many nutritional and environmental factorsare known to inXuence AF production, including nitro-gen source (Kachholz and Demain, 1983), carbon source(Buchanan and Stahl, 1984; Davis and Diener, 1968),culture temperature (Diener and Davis, 1967; Hunterand Tuite, 1967; Mayne et al., 1967; Schindler et al.,1966; Schindler et al., 1967), and culture pH (Cotty,1988; Keller et al., 1997). Organic sources of nitrogenand simple sugars favor AF production, while inorganicnitrogen sources and complex carbohydrates retard

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M.S. Price et al. / Fungal Genetics and Biology 42 (2005) 506–518 507

biosynthesis. The growth-optimal temperature of 37 °Cinhibits AF biosynthesis completely, while 28 °C allowsproduction. Conversely, the growth-optimal, pH 4.5, isconducive for AF biosynthesis and production is inhib-ited at, pH 8.0. Although the generalities are known, thespeciWc regulatory circuits that enable these factors tocontrol AF production remain unknown.

cDNA microarray analysis has rapidly become aninvaluable tool for deWning regulatory networks in cells(Alizadeh et al., 1999, 2000; Welcsh et al., 2002). Micro-arrays also are used to identify genes involved in cellularprocesses, such as pathogen defense (Cohen et al., 2000;de Torres et al., 2003; Golem and Culver, 2003; Moran etal., 2002; Ramonell et al., 2002; Whitham et al., 2003),infection (Takano et al., 2003), and growth (DeRisi et al.,1997; Lashkari et al., 1997; Pennie, 2000). Perhaps thegreatest power of microarray technology lies in two-wayclustering of genes and treatments to identify genes withcommon transcriptional proWles. Hughes et al. (2000)demonstrated this power by clustering expression datafrom 300 diVerent array experiments using the yeast Sac-charomyces cerevisiae and identifying previouslyunknown ergosterol biosynthesis genes.

In this study, we utilized a targeted cDNA array ofclones previously demonstrated to be correlated with AFbiosynthesis (OBrian et al., 2003) to investigate the inXu-ence of nitrogen source, carbon source, culture tempera-ture, and culture pH on AF production and genetranscription. The diVerential expression data for eachexperiment were clustered to produce a small compen-dium of expression proWles, which identiWed genes withexpression proWles similar to the AF cluster genes. Fur-thermore, new gene associations were made to AF pro-duction via the identiWcation of consistently induced orrepressed genes with respect to AF biosynthesis. Thegenes identiWed in this manner have not been previouslyassociated with AF production.

2. Materials and methods

2.1. Fungal strains and culture conditions

Conidia (106/mL) of Aspergillus parasiticus (Speare)strain SU1 (ATCC 56775) were inoculated into 2 LXasks consisting of either 500 mL YES broth (2% yeastextract, 5% sucrose, pH 4.5) or YEL broth (2% yeastextract, 5% lactose, pH 4.5) plus 0.4% agar. The addi-tion of agar maintained conXuent growth in submergedculture. Seed cultures were grown in shake culture(200 rpm) for 16 h at 28 °C in all experiments except thetemperature study, where the seed cultures were grownat 37 °C. A 6.25 mL aliquot of the seed cultures wasused to inoculate daughter cultures (100 mL each) inthe nitrogen, temperature and pH studies using SLSbroth (85 g/L sucrose, 10 g/L asparagine, and 50 mL/L

20£ salts [70 g/L (NH4)2SO4, 15 g/L KH2PO4, 7 g/LMgSO4 · 7H2O, 1.5 g/L CaCl2 · 2H2O, 0.4 g/L ZnSO4 ·7H2O, 0.1 g/L MnCl2 · 4H2O, 0.04 g/L (NH4)6Mo7O24,0.04 g/L Na2B4O7, and 0.04 g/L FeSO4 · 7H2O]) as thebase medium. YEL seed cultures were used toinoculate daughter cultures (100 mL each) in the carbonstudy.

Conditions conducive for AF production examined inthis study were as follows: NH4 as the nitrogen source,sucrose as the carbon source, a culture pH of 4.5, and aculture temperature of 28 °C. Therefore, SLS mediumwas used as the conducive medium, with constituentsaltered individually for each non-conducive medium.For example, in the nitrogen source comparison, themedia were identical for pH (pH 4.5), carbon source(sucrose), and temperature (28 °C), with the only diVer-ence being in nitrogen source (ammonium or nitrate).For the nitrogen source cultures, nitrogen was includedin the daughter culture medium as either ammonium ornitrate at 8.24 g/L nitrogen (using (NH4)2SO4 or NaNO3,respectively). This is similar to the amount of nitrogenused in a previous study that examined the repression ofAF and averuWn biosynthesis by nitrate (Kachholz andDemain, 1983). For the carbon source cultures, eithersucrose or lactose was included at 46.5 g/L carbon. Forthe pH experiment, SLS medium was prepared andbuVered at either pH 4.5 (using 100 mM citric acid) orpH 8.0 (using 100 mM Tris base). The temperatureexperiment utilized SLS medium, with the cultures incu-bated at either 28 or 37 °C.

The pH of the nitrogen, carbon, and temperaturedaughter cultures was maintained at, pH 4.5, by buVer-ing with 100 mM citric acid. The nitrogen, carbon, andpH daughter cultures were incubated at 28 °C. Alldaughter cultures were incubated for 24 h andharvested for RNA preparation and AF quantiWcation.AF concentrations for each culture were determined byHPLC. Triplicate cultures were grown for eachtreatment.

2.2. RNA preparation

Tissue was isolated from cultures by vacuum Wltra-tion. Tissue from individual culture replicates was placedinto pre-weighed 50 mL conical tubes and stored at¡80 °C prior to lyophilization. Tissue samples werelyophilized for 24–48 h to remove water, weighed, andstored at ¡80 °C until use.

For RNA extraction, replicate tissue samples for agiven treatment were pooled and ground with liquidnitrogen in a mortar with a pestle. RNA was thenextracted from the pulverized tissue using Trizol reagent(Invitrogen Life Technologies, Carlsbad, CA) followingmanufacturer’s instructions. RNA preparations werethen visualized by gel electrophoresis and quantiWed byspectrophotometry.

508 M.S. Price et al. / Fungal Genetics and Biology 42 (2005) 506–518

2.3. Microarray construction and target labeling

The microarrays used in this study were constructedas described previously (OBrian et al., 2003), with thefollowing exceptions. The PCR products were resus-pended in 50% DMSO and printed in sextuplet ontoCorning UltraGAPS slides using a Genetix Qarray Miniarray printer (Genetix Limited, Hampshire, UK). A poolof clones from the cDNA library used for printing wasprinted as a positive control. In addition, the AF path-way genes aXJ and aXR, as well as genes laeA (from A.nidulans), pkaA, pacC, areA, creA, and brlA were printedas positive controls. The gene crip3 (from maize) wasprinted as a negative control. Therefore, a total of 763genes were represented on the slides. Printed slides weredried overnight before UV cross-linking as per manufac-turer’s instructions.

Total RNA from A. parasiticus SU1 was converted toWrst strand cDNA using Stratascript reverse transcrip-tase (Stratagene, La Jolla, CA) and random hexamerprimers (Invitrogen Life Technologies, Carlsbad, CA)with the incorporation of aminoallyl dUTP (Ambion,Austin, TX) as described elsewhere (Chhabra et al.,2003) for all experiments except the Wrst nitrogen sourceexperiment. This array was labeled with the diVerent Cy-dyes using the Genisphere Array 350 kit (Genisphere,HatWeld, PA) and following manufacturer’s instructions.Each cDNA sample for each treatment was labeled oncewith each dye to account for diVerences in dye labeling.

2.4. Microarray hybridization, data acquisition, and analysis

Cy-dye-labeled cDNAs were hybridized to the micro-arrays for 16–20 h at 42 °C for each growth variable set.The hybridized slides were scanned using a Perkin ElmerScanArray Express Lite scanner (Perkin Elmer Life andAnalytical Sciences, Boston, MA). Pixel intensity datawere extracted from the resulting image Wles using Scan-alyze, a freeware microarray analysis program (http://rana.lbl.gov/EisenSoftware.htm). The microarray dataproduced in this study were deposited in the GeneExpression Omnibus (GEO) at the National Center forBiotechnology Information (NCBI) under AccessionNos. GSM27953, GSM27954, GSM27956, GSM27958,GSM27959, GSM27961, GSM27963, GSM27964,GSM27967, GSM27969, GSM27971, GSM27973,GSM27975, GSM27977, GSM27978, and GSM27979.

After extraction, data were imported into a statisticalsoftware package (SAS v8, SAS Institute, Cary, NC) andinitial background subtraction was performed. Mixedmodel analysis of microarray data (WolWnger et al., 2001)was used to evaluate diVerential expression data usingapproaches presented elsewhere (Chhabra et al., 2003;Pysz et al., 2004). BrieXy, the mixed procedure in SAS wasused to implement a linear normalization ANOVA

model to estimate global variation in the form of Wxed[dye (D), treatment (T)] and random [array (A), block(A (B)), and spot (A (S£ B))] eVects and random errorusing the model log2 (yijklmn) D� + Ai + Dj + Tk + Ai (Bl)+ Ai (Sm £ Bl) + �ijklm. A gene-speciWc ANOVA model wasthen used to partition the remaining variation into gene-speciWc eVects using the model rijklm D�+ Ai + Dj + Tk+ Ai (Bl) + Ai (Sm £ Bl) + �ijklm. Least squares estimates ofgene-speciWc treatment eVects across pairs of treatmentswere obtained for each gene under each treatment condi-tion. DiVerences between treatment eVects for pairs ofconducive and non-conducive conditions can be consid-ered as log2-transformed fold changes (WolWnger et al.,2001). Hierarchical clustering of selected log2-trans-formed fold changes from two biological repetitions ofall conditions of interest was performed using Ward’sminimum variance method in JMP 5.0 (SAS InstituteCary, NC). Genes were selected for hierarchical cluster-ing if they possessed fold changes greater than 1.7 or lessthan ¡1.7 in at least one experiment. This resulted in theinclusion of 542 genes in the clustering. Genes were des-ignated as signiWcantly diVerent in the individual micro-array experiments if they possessed p-values less than �.The value of � (0.003) was chosen based on the signiW-

cance of the AF pathway genes included on the array.

2.5. Overexpression of CA747470, a gene involved in AF production

The Universal GenomeWalkerkit (BD BiosciencesClontech, Palo Alto, CA) was used to determine thegenomic sequence Xanking EST CA747470 (Fig. 5). Thisgenomic sequence data was analyzed by the FGenesHgene prediction software package1 using “Aspergillus” asthe organism. Primers were designed 100 bp upstreamand downstream from the predicted coding region, andwere used to clone the putative gene into pNOM102, anexpression vector containing the gpdA promoter and A.nidulans trpC terminator sequences. The resulting con-struct was designated p01H11OE.

p01H11OE was co-transformed into A. Xavus 3357-5(pyrG) with pBS-pyr4, a construct containing the N.crassa pyr4 gene using a PEG-based protocol previouslydescribed (Woloshuk et al., 1989). Seventeen transfor-mants restored to uracil prototrophy were picked ontoPDA (Potato Dextrose Agar; Becton–Dickinson,Sparks, MD). The transformants were screened for thepresence of the p01H11OE construct using PCR primersdesigned to amplify a region from the pNOM102 back-bone into the CA747470 insert. Four of the seventeentransformants were identiWed as PCR-positive for hav-ing the overexpression construct (transformants 1-3, 3-1,3-2, and 3-3).

1 http://www.softberry.com.

http://rana.lbl.gov/EisenSoftware.htm



http://www.softberry.com

http://www.softberry.com


The PCR-positive transformants were tested for AFproduction. Agar plugs (3 mm diameter) taken fromgrowing cultures of the transformant strains 1-3, 3-1, 3-2,and 3-3, as well as 3357-5 and WT strain 3357. Eightplugs each were inoculated into twin 50 mL potato dex-trose broth (PDB) cultures (one set per strain). Thesecultures were grown at 28 °C, 200 rpm for 48 h. CultureWltrates were tested for AF as described above.

Quantitative-PCR (qPCR) data was collected fortransformant strains 1-3, 3-2, and 3-3, as well as 3357-5.The primers 5�-AAACCCACAAGGCAACAT-3� and5�-CTGGTTCTTGACCCAAAGGT-3� were used toamplify an 88 bp region of the putative coding sequenceof CA747470. The program used for PCR was as fol-lows: 1 cycle of 95 °C £ 10 min; 40 cycles of 95 °C £ 15 s,53.8 °C £ 30 s, and 72 °C £ 1 min. Raw Ct values forCA747470 expression were by normalized subtraction of18S control values by strain, then standardized by sub-traction of the wild-type Ct value from the transformantCt values, yielding a log2 expression value. The foldchange is obtained by raising 2 to the power representedby the log2 expression value for a given strain.

Lastly, to test the eVect of overexpression ofCA747470 on growth, the four PCR-positive transfor-mants along with A. Xavus wild-type strains 3357-5 and3357 were picked onto minimal media plates (MM; Cza-pek-Dox medium, Becton–Dickinson, Sparks, MD)amended with each of the following: 0.5 M KCl, 1.0 MKCl, 0.5 mM CuSO4, or 5mM CuSO4. In addition MMwas prepared with Wnal pH as pH 3.0 or 8.0. The plateswere incubated at 28 °C for 5 days. Colony diameter wasmeasured as the mean of cross-wise measurements foreach of three replicate plates for each strain on eachmedium. Measurements were taken approximately thesame time every day for 5 days. The results of growth onday 5 are reported.

3. Results and discussion

3.1. AXatoxin production in growth cultures

We were able to assay for AF production in each cul-ture, and use this as a phenotypic screen for the micro-array experiments. We consistently observed largestatistically signiWcant diVerences in AF productionbetween conducive and non-conducive treatments foreach experiment (Fig. 1). In fact, no AF was made at37 °C or at pH 8.0. While some AF was observed in cul-tures grown under non-conducive carbon and nitrogenconditions, the level of AF repression by nitrate was sim-ilar to that reported previously (Kachholz and Demain,1983). The level of AF in the lactose-containing cultureswas over 8-fold higher then previously reported byBuchanan and Stahl (1984), however, they included 75%less lactose in their culture medium. These diVerences in

carbon source amounts may have had an impact on AFproduction beyond the impact of the speciWc carbonsource they used.

3.2. Agreement of microarray data with previously published results

The array data from this study were compared toresults from a previous study that examined the inXu-ence of fungal development on AF production (OBrianet al., 2003). OBrian and colleagues examined thechange in AF gene expression over time by comparingtranscripts from tissue grown for either 8 h (no toxin)or 24 h (toxin). These time-points correspond to pri-mary and secondary growth, respectively. Of the 42diVerentially expressed genes identiWed in the OBrianstudy, 37 genes were diVerentially expressed in themicroarrays presented here (Fig. 2). This group of 37genes was subjected to clustering as described underSection 2. As shown in Fig. 2A, many of these geneshad unique expression patterns. However, one group ofgenes was identiWed with nearly identical expressionproWles, and three of the genes in this group exhibiteddiVerences which met our signiWcance criteria in allfour culture variable comparisons (purple box,Fig. 2A). Preliminary analysis of the upstreamsequences of these genes revealed the presence of creA,areA, and pacC transcription factor binding sites. Thisgroup of genes is part of a larger cluster in this studyconsisting of 20 genes (Fig. 2B), most of which have notbeen previously described (NSH, no signiWcant homol-ogy). The high degree of similarity in transcription pro-Wles suggests these genes constitute a putative regulon.These genes may share transcription factor bindingsites leading to their coordinate regulation, or there

Fig. 1. AXatoxin production by A. parasiticus grown in conducive ornon-conducive culture treatments. Data presented are for two biologi-cal replicates for each culture condition. Three replicate cultures foreach biological replicate were grown for 24 h and harvested for aXa-toxin quantiWcation and RNA extraction. Values presented are themeans of the six replicate cultures. Error bars represent standard errorfor each treatment.


may be a cascade eVect among genes in this cluster,whereby certain genes aVect the expression of othergenes within the cluster to the same extent by whichthey are expressed. Alternatively, if the protein productsof these genes are part of the same metabolic pathway,changes in product Xux through that pathway may yieldlike eVects on the transcription of all these genes througha mechanism similar to feedback inhibition.

This regulon has the unique characteristic of beingupregulated in the conducive nitrogen source and pH,and suggest these genes are involved in cross-talk

between nitrogen and pH regulatory pathways. A linkbetween nitrogen repression and pH has been examined(Cotty, 1988). Cotty showed that fourfold less AF wasproduced in cultures containing ammonium which werebuVered at pH 5.5 than ammonium-containing cultureswhich were not buVered. While this cross-talk may bedue solely to the apparent tendency of ammonium con-taining cultures to produce lower pH, the fact that a setof genes are upregulated in response to both environ-mental cues suggests that some amount of pathwaycross-talk may in fact exist.

Fig. 2. Behavior of genes in this study previously shown to be diVerentially expressed over time with regard to AF production. (A) A subset of 42genes shown to be diVerentially expressed in a prior temporal expression experiment (OBrian et al., 2003) were identiWed and subjected to hierarchi-cal clustering as described under Section 2. DiVerences in gene expression from the earlier study are qualitative and represented as red (higher in con-ducive treatment) or blue (higher in non-conducive treatment). The highlighted clade (purple box) represents a possible regulon. (B) The geneshighlighted in (A) were identiWed in the original clustering (used for Fig. 5), and reside in a larger group of genes with a similar expression proWle,suggesting a putative regulon of 20 genes.


3.3. IdentiWcation of treatment-speciWc regulons

Suites of genes were identiWed which corresponded tospeciWc culture variables tested in this study (Fig. 3).Carbon regulation of AF production has been studiedsince 1968, when the eVect of 13 carbon sources on AFaccumulation by cultures of A. parasiticus was investi-gated (Davis and Diener, 1968). The authors suggestedthat for a carbon source to support both growth and AFproduction, it must be accessible to both the hexose-monophosphate and glycolytic pathways. We identiWeda regulon consisting of genes upregulated in response to

sucrose and associated with AF production (Fig. 3A).Not surprisingly, one of the genes (enoA) in this clusterhas homology to enolase, which is responsible for theconversion of glycerate-2-P to phosphoenol-pyruvate inthe glycolytic pathway. Another gene (pdcA), putativelya pyruvate decarboxylase, is involved in the related glu-coneogenesis pathway. The Wve unique (NSH) genes inthis cluster provide tempting targets for further study ofcarbon regulation.

Much work has been done investigating the role ofpH and regulation of AF biosynthesis (Ehrlich et al.,1999; Keller et al., 1997). The binding site for the global

Fig. 3. IdentiWcation of putative culture-condition responsive regulons. (A) A subset of genes that exhibited higher expression in response to sucrose.Included in this clade are a putative enolase as well as a putative pyruvate decoarboxylase. The genes shown exhibited between 2.3- and 3.9-foldinduction in response to growth on sucrose. (B) A group of 27 genes, including the global pH regulatory gene pacC, that exhibited higher expressionat, pH 8.0. (C) A set of 18 genes, including a putative coproporphyrinogen III oxidase, that exhibited higher expression in response to nitrate. (D) Aset of three genes of unknown function, as well as three putative superoxide dismutases, that exhibited increased expression due to growth at 37 °C.Genes with no putative function are designated NSH.


pH regulator PacC has been identiWed in the promoterof aXR (Ehrlich et al., 1999). Our study identiWed 27genes coordinately induced with increasing pH (Fig. 3B).Included in this group is the global regulatory genepacC. This gene is known to induce expression of alka-line-expressed genes while repressing expression ofacidic-expressed genes. Putative PacC binding sites wereobserved in the upstream sequences of 19 genes in thiscluster (data not shown), further strengthening the argu-ment these genes constitute a putative regulon. This genecluster also included pkaA, which has been shown toinhibit AF production via phosphorylation of AFLR(Shimizu et al., 2003). pnc1, a gene involved in nicotin-amide metabolism, was also induced by high pH. ThisWnding is intuitive because this pathway is involved inthe production of NAD+ and NADP+, both of whichaccept hydride ions in enzymatic reactions, resulting inthe release of protons. This may be one way in which thefungus balances intracellular pH in an alkaline environ-ment.

Nitrate repression has likewise received much atten-tion with respect to AF production (Chang et al., 1995;Feng and Leonard, 1998; Ehrlich and Cotty, 2002; Flah-erty and Payne, 1997; Kachholz and Demain, 1983; Liuand Chu, 1998; Niehaus and Jiang, 1989). As early as1983, Kachholz and Demain showed that nitrate, in apH buVered medium, was capable of suppressingaveruWn production up to 70% compared to ammonium.Niehaus and Jiang (1989) later showed that the additionof nitrate to a growing culture caused a concomitantincrease in activity of mannitol dehydrogenase and man-nitol-1-P dehydrogenase (2.9- and 7.7-fold, respectively).These enzymes are capable of making NADPH andNADH, respectively, but are most likely not majorsources of these cofactors in the cell. The authors arguethat nitrate repression occurs due to an altered redoxstate in the cell, as measured by NADPH/NADP+ ratio.

No genes have been identiWed to date that are respon-sible for regulating nitrate repression of AF biosynthesis.In this study, we identiWed a potential regulon of geneswhich are coordinately induced by nitrate (Fig. 3C). Onegene, cpx, has homologs which are involved in heme pro-duction. Heme is a structural component of nitratereductase, which is the Wrst enzyme in the nitrogenassimilation pathway (Marzluf, 1997). Upregulation ofthis gene is intuitive, as nitrate reductase is required fornitrate utilization. Three other genes, cox12, hmpA, andfhp, encode proteins involved in the electron transportchain, which is responsible for production of energy andreducing power in the cell. Reducing power is essentialfor nitrate utilization, therefore increased expression ofthese genes is expected. Again, similar to the putative pHregulon, 16/18 genes identiWed in this cluster possessputative binding sites for the global nitrogen regulatoryprotein AreA (data not shown). This evidence bolstersour conWdence in these genes being co-regulated.

Temperature regulation of AF production has beenstudied since the late 1960’s, when Schindler et al. (1966)Wrst described the conducive temperatures for AF. TheeVect of high temperature on aXR transcription has beenwell established (Feng and Leonard, 1998; Liu and Chu,1998), yet a degree of post-transcriptional regulationcannot be ruled out. In the present study, a small puta-tive regulon consisting of six genes was identiWed thatresponded to growth at 37 °C. Three of the genes encodeputative superoxide dismutase genes (MnSOD andsodM; Fig. 3D). This Wnding may reXect the stressencountered by the fungus during growth at higher tem-peratures, or its need to escape host defenses duringplant or animal infection. The other genes in this clusterare undeWned (NSH), yet investigations into their func-tion may yield interesting insights into temperature regu-lation of AF biosynthesis.

3.4. Expression proWles of AF pathway genes

Transcriptional proWles of the AF genes on thismicroarray clustered into Wve clades (Fig. 4). The struc-tural gene clade contained genes responsible for some ofthe enzymatic steps of the AF pathway, including aXC(formerly pksA; 2 copies), aXJ (formerly estA), aXM (for-merly ver1; 2 copies), aXP (formerly omtA), and aXO(formerly omtB). Also included in this clade was onegene encoding a putative 6-phosphogluconate dehydro-genase. These genes exhibited large increases in expres-sion when grown under the conducive conditions tested.

Another clade with similar but less striking diVerencesin gene expression is the aXS clade. aXS (formerly aXJ) isdivergently transcribed from the pathway speciWc regu-lator aXR (Meyers et al., 1998). This gene was found in aseparate cluster from the other AF pathway genes withone gene of unknown function (NSH), two putativeactin subunits, a ribosomal subunit, and a putativetransaldolase (Fig. 4). While the diVerences in aXS geneexpression between treatments were not as great as themain structural genes, the observed diVerences corre-lated with AF production.

A recently described pathway gene, aXH (formerlyadhA) shared a similar transcription proWle with fourgenes homologous to ribosomal proteins and one genehomologous to cystathionine �-synthase. aXH has beenrecently demonstrated to convert 5�-hydroxyaverantin(HAVN) to averuWn (AVF) via a 5�-oxoaverantin(OAVN) intermediate in the AF biosynthetic pathway(Chang et al., 2000; Sakuno et al., 2003). SpeciWcally,AXH was shown to convert HAVN to OAVN. The con-version of OAVN to AVF was shown to be the result ofthe action of OAVN cyclase, a protein not encoded byany AF pathway gene (Sakuno et al., 2003). Cystathio-nine �-synthase is an enzyme involved in cysteine synthe-sis and sulfur metabolism. This enzyme is responsible forproducing L-cysteine and acetate in the sulfur metabolic


pathway. Acetate is believed to be a precursor to AFproduction in A. Xavus (Brown et al., 1999).

The early pathway gene aXD (formerly nor1) had aunique expression proWle, and shared an expression pro-Wle with Wve other genes including one gene of unknownfunction (NSH), a gal10 homolog, a ribosomal proteinhomolog, and two genes with homology to A. fumagatusallergen rasp f13. The pathway speciWc transcriptionalregulator aXR exhibited an expression proWle unlikeother pathway genes, and was grouped in a clade withthree NSH genes, a ribosomal protein gene, and a genewith homology to snaD, which is involved in asexualsporulation in A. nidulans (Liu and Morris, 2000).

In addition to Wnding genes with similar expressionproWles to known AF biosynthetic genes, other genes

were identiWed which were consistently associated withAF production in all the experiments performed(Table 1). Three of the genes on our array were consis-tently repressed with respect to AF production. Two ofthese genes were uncharacterized (i.e., NSH), while onehad homology to a nitrogen-starvation induced cDNAfrom Colletotrichum gloeosporioides. Conversely, 14genes were induced with respect to AF production.These included the AF pathway genes aXC, aXM, andaXP, as well as genes involved in other cellular processesand three NSH genes.

Least squared mean estimates of treatment eVectsrepresenting transcript detection levels in each of thetreatments tested were plotted by clone for genes ofinterest identiWed in Table 1, as well as two other genes

Fig. 4. Hierarchical clustering of AF pathway genes. DiVerential expression data for genes meeting cutoV criteria (diVerence estimate >0.75 or<¡0.75) were grouped using Ward’s hierarchical clustering as described under Section 2. Representative AF pathway genes exhibited diVerentexpression proWles and were grouped into Wve clades.


with interesting putative functions (Fig. 5). Three of theAF biosynthetic genes are shown: CA747495 (aXC),CA747496 (aXM), and CA747926 (aXP). Two othergenes, CA747645 and CA747794 (encoding putativetransaldolase (tal1) and 6-phosphogluconate dehydroge-nase (pgd), respectively), were also identiWed in Table 1and are of interest due to their possible role in the oxida-tive stress response and nitrate utilization pathways.Oxidative stress has been hypothesized as necessary forAF production (Jayashree and Subramanyam, 2000).Further, pgd is thought to be a major source of NADPHin the cell, and NADPH availability is hypothesized tobe important for AF production (Niehaus and Jiang,1989). Disruption of these genes is underway in thehopes of determining their role in AF biosynthesis.

Many fungi that produce mycotoxins possess mech-anisms for mitigating self-toxicity. Cercospora kikuchiihas a cercosporin pump which is involved in self-defense against this mycotoxin (Callahan et al., 1999;Upchurch et al., 2001), and a gene for singlet oxygenresistance has been shown to confer cercosporin resis-tance in C. nicotianae (Ehrenshaft et al., 1997, 1999). Arecently identiWed MFS transporter located in the AFbiosynthetic cluster, aXT, was shown to play no role inAF secretion or resistance (Chang et al., 2004). WeidentiWed a gene in our microarray clone set withhomology to aXatoxin aldehyde reductase (AFAR;CA748087), which has been shown to be responsiblefor AF resistance in a rat model (Hayes et al., 1993).This gene exhibited high expression in all treatmentsexcept 37 °C (Fig. 5). The presence and expression ofthis putative AFAR gene in all treatments suggests arole in AF resistance by A. Xavus. Gene-deletion exper-

Table 1Genes diVerentially expressed in all experiments

a Gene did not meet criteria [p value < 0.003, log2R > 0.75 (induced)or log2R < ¡0.75 (repressed)] for one replicate of one experiment.

Accession Putative gene ID Expressionresponse

Maximumfold change

CA747470a NSH Repressed 2.7CA747489a Actin Induced 1.5CA747495 aXC Induced 4.2CA747496 aXM Induced 6.2CA747500a Putative hydrophobin Induced 4.8CA747505 rpL2 Induced 2.7CA747547 rpL44E Induced 3.5CA747569a Nitrogen starvation-

induced cDNARepressed 2.1

CA747579 NSH Induced 3.2CA747603a Hypothetical protein Induced 1.7CA747645a tal1 Induced 4.0CA747766a hem13 Induced 1.6CA747794 pgd Induced 6.8CA747795a gal10 Induced 2.2CA747926 aXP Induced 7.0

CA747993a rAsp f13 Induced 2.5CA748049a NSH Repressed 2.5

iments are underway to verify a role for CA748087 inAF resistance.

Two genes in Fig. 5 were shown in Table 1 to be con-sistently downregulated with respect to AF: CA747470and CA747569. One of these genes showed no signiWcanthomology to any known genes, proteins, or proteindomains (CA747470), whereas the other gene exhibitedhomology to a nitrogen starvation induced cDNA fromColletotrichum gloeosporioides (CA747569). Induction ofCA747569 in nitrate medium were also observed here,however, there appears to be a greater transcriptionalresponse between conducive and non-conducive temper-ature and carbon source treatments. In the case ofCA747470, transcription of this gene was much higherthan the others in Fig. 5 in each treatment, suggestingthat perturbations in expression of this gene may wellyield a visible phenotype.

3.5. IdentiWcation of CA747470, a gene involved in AF production

We identiWed a gene, CA747470, whose expressionwas inversely correlated to AF production. As notedabove, this gene has no homology to known sequencesand is highly expressed in all conditions presented here(Fig. 5). We designed an overexpression construct,p01H11OE, to investigate the eVect of elevated expres-sion of this gene on AF production under conduciveconditions. Four transformants were obtained whichpossessed the construct and were restored to uracil pro-totrophy. Of these, one transformant exhibited a “XuVy”growth phenotype similar to the previously describedXbA deletion mutant (Yu et al., 1996). Both the �XbAstrain and the p01H11OE transformant 3-1 fail to makeAF. Therefore, 3-1 was not investigated further.

As shown in Table 2, CA747470 overexpression wasdetected by qPCR. Interestingly, strain 1-3 producednear wild-type levels of AF, while strains 3-2 and 3-3produced 8 and 0.3% of wild-type AF levels, respectively.This gene appears to be highly expressed natively, evenunder conducive AF conditions. Therefore, activity ofthe CA747470 gene product may be controlled by amechanism like protein phosphorylation. If gene expres-sion outpaces inactivation suYciently, then AF produc-tion is reduced. This may explain how 1-3 makes nearwild-type levels of AF while CA747470 is overexpressed67-fold. In strains 3-2 and 3-3, this gene is overexpressedmore than 90-fold, and conceivably may outpace thecells ability to suppress its activity. Furthermore, Theamount of fold change appears to inversely correlate toreduction in toxin (r2 D 0.8). These data taken as a wholesuggest that CA747470 is involved in either suppressingor delaying AF production.

Finally, the eVect of overexpressing CA747470 ongrowth was determined using MM amended with CuSO4or KCl, or by changing pH. Transformant strains 3-2


and 3-3 grew better than 3357-5 in every case except on5 mM CuSO4 (Fig. 6). In all cases, 3-2 and 3-3 grew aswell as or better than the parental wild-type strain 3357.

Table 2Expression of CA747470 in p01H11OE transformed strains

Strain Mean AF(ng/mL)

ComparativeCA747470 C(T)

Foldchange

1-3 32343 6.07 673-2 3460 6.5320001 933-3 141 6.5983334 973357-5 42522 0 1

These data suggest that CA747470 may play a role invegetative growth. Overexpression of this gene maymimic vegetative growth signals in the fungus, whichresults in suppressed AF production. Further studies ofthis gene are underway.

In conclusion, we have used a targeted cDNA micro-array to examine transcriptional diVerences in A. para-siticus due to conducive and non-conducive conditionsfor AF production. DiVerences in gene expressionbetween AF pathway genes within treatments wererevealed, with the AF pathway genes exhibiting Wve

Fig. 5. Relative expression levels in all treatments for select genes of interest. Least squared means estimates of expression obtained from the mixed-model analysis of the microarray data (see Section 2 for explanation and for relationship to fold changes) were plotted for select genes of interest.Included in the plot are three AF pathway genes (CA747495, CA747496, and CA747926) as references.

Fig. 6. Growth of CA747470 overexpression transformants on MM supplemented with various amendments. Radial growth was recorded as themean of cross-wise measurements from three replicate plates after 5 days incubation at 28 °C. Strains are designated as follows: transformant strain
1-3 , 3-2 , 3-3 ; wild-type strains 3357 , 3357-5 .


diVerent patterns of gene expression. Genes were identi-Wed with patterns of expression similar to the AF path-way genes (Fig. 4). These newly identiWed genes are ofinterest for further investigation. Genes were also identi-Wed which respond to the treatments evaluated in thisstudy (Fig. 3), and will be targets for investigating therole of carbon source, etc., in secondary metabolism.Furthermore, we identiWed a gene, CA747470, whoseexpression was inversely correlated to AF production(Fig. 5, Table 2). Overexpression of this gene resulted inlower AF production, suggesting this gene may play arole in regulating the AF pathway. CA747470 appears tobe involved in vegetative growth, which may explain itsnegative eVect on AF production. Future experiments onthis gene will involve gene deletion and microarray stud-ies to determine the eVect of CA747470 overexpressionand deletion on the transcriptome.

AF production by species of Aspergillus is a highlyregulated process, involving multiple layers of tran-scriptional and post-transcriptional regulation(Buchanan et al., 1987; Butchko et al., 1999; Calvo et al.,2002; Chang et al., 1999; Chiou et al., 2002; Feng andLeonard, 1998; Hicks et al., 1997; Keller et al., 1997;Shimizu and Keller, 2001; Shimizu et al., 2003; Wolo-shuk et al., 1994). Examples of regulatory cross-talkbetween growth conditions are also observed (Cotty,1988). All of this regulation is focused through the AFpathway-speciWc transcriptional regulator aXR (Changet al., 1993; Payne et al., 1993). In the last 10 years muchprogress has been made in understanding the regulationand production of AF in A. Xavus and sterigmatocystin(ST) in A. nidulans. Virtually all of the enzymatic stepshave been characterized (Price and Payne, 2004; Sakunoet al., 2003). However, much remains to be describedabout the regulatory networks involved in AF biosyn-thesis, and how other cellular processes are inXuencedby these networks. This study has just begun to uncoverthe regulatory network inXuencing AF production andgrowth in Aspergilli. Future work will include time-dependent analysis of AF-conducive conditions utiliz-ing arrays with larger numbers of genes. The researchpresented here should lay a Wrm foundation upon whichfurther exploration of the factors inXuencing AF bio-synthesis may be conducted.

Acknowledgments

The authors thank Kim Schwartzburg, Carrie Jaco-bus, Rob Holmes, and Greg OBrian for their critique ofthe manuscript. The authors would additionally like tothank Matt Johnson and Clemente Montero for theirassistance in the construction and hybridization of themicroarrays. This research was supported by Grant 99-35201-8073 from the USDA/NRI Competitive GrantsProgram.

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