Next Article in Journal
Oligopeptides as Biomarkers of Cyanobacterial Subpopulations. Toward an Understanding of Their Biological Role
Previous Article in Journal
Impact of Nitrogen Sources on Gene Expression and Toxin Production in the Diazotroph Cylindrospermopsis raciborskii CS-505 and Non-Diazotroph Raphidiopsis brookii D9
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Communication

Comparison of Expression of Secondary Metabolite Biosynthesis Cluster Genes in Aspergillus flavus, A. parasiticus, and A. oryzae

Southern Regional Research Center, Agricultural Research Service, United States Department of Agriculture, New Orleans, LA 70124, USA
*
Author to whom correspondence should be addressed.
Toxins 2014, 6(6), 1916-1928; https://doi.org/10.3390/toxins6061916
Submission received: 21 March 2014 / Revised: 9 June 2014 / Accepted: 13 June 2014 / Published: 23 June 2014

Abstract

:
Fifty six secondary metabolite biosynthesis gene clusters are predicted to be in the Aspergillus flavus genome. In spite of this, the biosyntheses of only seven metabolites, including the aflatoxins, kojic acid, cyclopiazonic acid and aflatrem, have been assigned to a particular gene cluster. We used RNA-seq to compare expression of secondary metabolite genes in gene clusters for the closely related fungi A. parasiticus, A. oryzae, and A. flavus S and L sclerotial morphotypes. The data help to refine the identification of probable functional gene clusters within these species. Our results suggest that A. flavus, a prevalent contaminant of maize, cottonseed, peanuts and tree nuts, is capable of producing metabolites which, besides aflatoxin, could be an underappreciated contributor to its toxicity.

1. Introduction

Biosynthesis of many fungal secondary metabolites, including mycotoxins, typically requires enzymes encoded by sets of clustered genes [1]. With the availability of full genome sequences, genes can be associated with secondary metabolite biosynthesis by use of the software program SMURF [2]. This program allows automated search of the genome to identify sets of contiguous genes that include a “backbone” gene encoding a protein required for biosynthesis of a metabolite precursor [3], a transcription factor for regulation of gene expression, oxidases or reductases for modification of the metabolite precursor and transporters for export or for moving the metabolite to vacuoles or vesicles within the cell [3,4]. For secondary metabolite formation, typical backbone enzymes include non-ribosomal peptide synthases (NRPSs), polyketide synthases (PKSs) [5,6] or geranylgeranyl pyrophosphate synthases (GGPSs) [7] for one or more of the biosynthesis steps. Also, characteristic of some NRPS-derived metabolites is a step involving tryptophan prenylation, which is catalyzed by a cluster-associated dimethylallyltryptophan synthase (DMATS) [8]. The ability of fungi to co-ordinately regulate transcription of clustered genes usually depends on a single sequence-specific DNA-binding protein of the Zn2Cys6-type unique to a given cluster [9]. Expression of genes controlled by such transcription factors should define the boundaries for the gene cluster [10]. A method that combined SMURF with microarray expression analysis was recently described that also could help to better define the cluster boundaries for genes in secondary metabolite biosynthesis clusters [11].
In the present study expression analysis by RNA-seq was performed on two sclerotial size variants of A. flavus (called S and L strains) and the non-aflatoxigenic variant, A. oryzae. These A. flavus variants are morphologically and phylogenetically distinct [12]. Analysis was also done on A. parasiticus, a close relative of A. flavus that produces G- in addition to B-aflatoxins. Although RNA-seq data were available for isolates of an A. flavus L strain and A. oryzae [13,14,15], they were not available for an S strain A. flavus or for A. parasiticus. The comparison of RNA-seq data described in this paper evaluates the potential of these fungi to produce secondary metabolites when grown on a typical fungal growth medium. Such identification is the first step for rational assignment of a biosynthetic gene cluster to production of a specific metabolite.

2. Results and Discussion

2.1. Types of Backbone Genes

The gene clusters for secondary metabolism in A. flavus NRRL3357 previously identified by SMURF [16] were used for identification and annotation of homologous clusters in the related species: A. parasiticus, two variant A. flavus S strain isolates and A. oryzae. Putative backbone genes for gene clusters identified in A. flavus NRRL3357 are given in Table 1, Table 2 and Table 3. The PKS-encoding backbone genes in Table 1 are arranged by types of proteins predicted to be produced by these genes. Those encoding polyketide synthases with reducing domains are distinguished from those encoding proteins that lack such domains. The NRPS genes are arranged in Table 2 by those predicted to encode proteins with repeated condensation (C) domains and those predicted to encode proteins with single or no C domains. For both types of secondary metabolite, putative PKSs and NRPSs with only a single, or at most two, catalytic domains are listed separately. Genes for clusters 23 and 55 are predicted to encode a single polypeptide containing both PKS and NRPS catalytic domains. In Table 1 and Table 2 transcription factors associated with the putative gene clusters are listed separately. Only some of the gene clusters contain transcription factors within the putative cluster [10]. Gene clusters containing the biosynthetic enzymes for production of GGPSs and DMATSs are listed in Table 3. One secondary metabolite whose biosynthesis has recently been studied, kojic acid, is derived from glucose [17]. Because of this difference in biosynthesis it is not shown in these lists or in Table S1.
Table 1. Putative polyketide synthase backbone genes in SMURF-identified secondary metabolite clusters in A. flavus.
Table 1. Putative polyketide synthase backbone genes in SMURF-identified secondary metabolite clusters in A. flavus.
Cluster NumberTypeA. flavus NRRL3357A. flavus AF70A oryzae RIB40A. parasiticus BN9Transcription Factor(s) in AF-3357 Cluster
aa aDomainsGeneRPKM cGeneRPKMGeneRPKMGeneRPKM
Reducing PKS
12432KS-AT-DH-MT-PP bAFLA_0029002.03.m0008411.9AO0901020001664.614.m0046615.2not found
172895KS-AT-DH-MT-ER-KR-NADB/TEAFLA_0538700.776.m0002610.5AO0900090000711.19.m0060820.9AFLA_053760
202355KS-AT-DH-MT-KR-ER-KR-PPAFLA_0628201.1310.m00010812.0AO0907010008262.53.m00825418.0AFLA-62960
232462KS-AT-DH-MT-KR-PPAFLA_0669803.7401.m0000992.0AO0900010002932.2not foundAFLA-066830,066960,066900
402137KS-AT-DH-PPAFLA_1128400.5148.m0002280.5AO0900230008770.6not foundAFLA-112830
462460KS-AT-DH-MT-ER-KR-PPAFLA_1189400.14.m0008220.0AO0900100004020.111.m00655219.1not found
502505KS-AT-DH-MT-ER-KRAFLA_1267101.2217.m0001430.0AO0900380002101.16.m0073932.0AFLA-126910
522591KS-AT-DH-MT-ER-TE-PPAFLA_1280600.3182.m0001660.7AO0900010005061.86.m0075429.2AFLA-128150,128160
Non-reducing PKS
52141KS-AT-PP-PP-TEAFLA_0061701.329.m0004591.1AO0901020005451.214.m00433842.8AFLA-006240
202245KS-AT-PP-TEAFLA_0628602.1310.m00010434.9AO0907010008316.53.m00825038.9AFLA-062960
272045KS-AT-PP-TEAFLA_0821500.38.m0006091.6AO0900050009610.03.m0086871.2AFLA-082140
33947KS-ATAFLA_0967700.0513.m0000310.0AO0901130002090.0not found dnot found
382475KS-AT-MT-MT-KRAFLA_1054504.2655.m0000420.8not foundnot foundnot found
391751KS-AT-PPAFLA_1085500.0152.m0002230.0AO0900230004440.216.m0040600.1not found
411120KS-AT-KR-PPAFLA_1148202.4255.m0001140.8AO0902060000741.521.m0010601.6not found
422104KS-AT-PP-TEAFLA_1162200.04.m0008880.1AO0900100000480.011.m0062800.1AFLA-116230
442580KS-AT-PP-MT-TEAFLA_1168900.24.m0008241.0AO0900100001140.311.m0063440.0AFLA-116880
462253KS-AT-PP-MTAFLA_1189600.139.m0004150.2AO0900100004040.211.m00655421.8not found
512586KS-AT-PP-TEAFLA_1270900.2268.m0001660.2AO0900010004021.36.m0074383.5AFLA-126990
542109KS-AT-PPAFLA_139410197.0210.m0001221.4AO0900260000094.25.m007293194.0AFLA-139360
Short PKS
7396KS-PPAFLA_0091400.419.m0004161.0AO0901030003130.215.m0041540.0not found
8396KS-AT-DH-MTAFLA_0100000.4365.m0000721.4AO0901030002240.8not foundnot found
17327DHAFLA_0537800.0169.m0002080.0AO0900090000780.0not foundAFLA-053760
26207TE-PPAFLA_0793600.0803.m0000230.0AO0900050006870.08.m0063200.0AFLA-079320
36689KSAFLA_1042100.0201.m0001780.1not foundnot foundnot found
36301KSAFLA_1042402.6201.m0001810.2not foundnot foundnot found
36696ERAFLA_1042505.2not foundnot foundnot foundAFLA-104220
43413KR-PPAFLA_1165000.04.m0008630.0not foundnot foundnot found
49426KR-PPAFLA_1256300.0not foundnot found6.m0072620.0not found
49708AT-DHAFLA_1256400.0376.m0000990.0AO0900380000860.0not foundAFLA-125590
Notes: a aa-length in amino acids; b Domains: KS-ketosynthase; AT-acyltransferase; DH-dehydratase; ER-enoyl reductase; KR-ketoreductase; PP-Phosphopantetheine attachment site; MT-methyltransferase; TE-thioesterase; c RPKM values are from cultures grown on potato dextrose agar medium in the dark for two days. RPKM vaues >1 are shown in bold font; d not found: BLASTN search against the A. flavus NRRL3357 genome produced no alignments with E value below 1e-10 and a percent identity above 80%.
Table 2. Putative non-ribosomal peptide synthase backbone genes in SMURF-identified secondary metabolite clusters in A. flavus.
Table 2. Putative non-ribosomal peptide synthase backbone genes in SMURF-identified secondary metabolite clusters in A. flavus.
Cluster NumberTypeA. flavus NRRL3357A. flavus AF70A. oryzae RIB40A. parasiticus BN9Transcription factor in AF-3357 cluster
aa aDomains bgeneRPKM cgeneRPKMgeneRPKMgeneRPKM
Large NRPSs-di, tri,tetra peptide types a
35011C-A-T-C-C-A-T-C-A-T-C-A-TAFLA_0044502.311.m0005360.2AO0901020003382.914.m0045042.6AFLA_005290
42621C-A-T-C-A-T-CAFLA_0054401.0507.m0000460.2AO0901020004650.1not foundAFLA_005520
65209A-C-C-A-T-C-A-T-C-A-T-C-CAFLA_0087700.119.m0004490.0AO0901030003550.015.m0041270.4
97763A-C-A-C-C-A-T-C-A-C-A-M-C-A-RAFLA_0105801.4115.m0001772.6not found15.m0042890.5
92100A-T-C-A-T-CAFLA_0106200.9115.m0001730.6AO0901030001677.815.m0042940.6
132975A-T-C-A-T-C-AAFLA_0386000.2124.m0001812.4AO0900110000431.94.m0089174.2
212074A-T-C-A-T-CpartialAFLA_06424016.362.m0003771.3AO0900010000091.712.m00634915.8AFLA_064370
225326A-T-C-A-T-C-A-C-A-T-C-A-T-CAFLA_0667200.3123.m0001880.1AO0900010002620.5not found
245186A-T-C-C-A-T-C-A-T-C-C-T-CAFLA_06933017.2100.m00022822.0AO0900380003902.118.m00339041.1
Single A-domains-A-C
81626T-C-A-T-RAFLA_0100101.1not foundnot found15.m0042420.0
81338A-T-CAFLA_0100201.8579.m0000302.1AO0901030002232.215.m0042430.6
341225A-T-CAFLA_1003400.0not found dnot found6.m0072730.8AFLA_100300
531071A-T-CAFLA_1354900.1not foundnot foundnot found
211621T-C-A-CAFLA_0645600.562.m0004090.1AO0900010000436.812.m0063182.0
301735A-T-C-T-CAFLA_0902000.0215.m0002470.1AO0901200000240.07.m0072600.1
Single A-domains-A-T
111021A-T-SDR_e1AFLA_0230200.120.m0004660.0AO0900030015450.01.m0128691.3AFLA_023040
121011A-T-RAFLA_0287201.5242.m0001700.1AO0900030009450.21.m0134295.2
181251A-T-R-gntKAFLA_0542700.1307.m0001710.0AO0900090000330.39.m0060430.0AFLA_054310
251008A-TEAFLA_0709200.1304.m0001100.0AO0900380005500.019.m0022121.7
26957A-T-RAFLA_0793800.9333.m0001205.4AO0900050006888.68.m0063191.8
261278A-T-SDR_e1AFLA_0794005.2333.m0001187.4AO09000500069016.28.m00631720.9AFLA_079320
371055A-RAFLA_1051900.9348.m0001250.6AO0900230000826.017.m00374013.7AFLA_118300
451048C-A-T-RAFLA_1184400.2137.m0002470.0AO0900100003490.011.m0065070.0
471043A-T-RAFLA_1191100.1395.m0001060.1AO0900100004260.011.m0065880.0
351042A-T-SDR-e1AFLA_1017000.81.m0009781.1AO0900200002400.710.m0065790.0
481007A-T-SDR-e1AFLA_1215200.6not found not found not found
Short NRPSs
7611A-T-epimeraseAFLA_0091200.519.m0004184.9AO0901030003160.4not found
28396T-CAFLA_0824800.0not found AO0900050009930.0not found
33163TAFLA_0967000.036.m000454*0.0AO0901130002000.07.m0066390.0
33317CAFLA_0967100.0not found AO0901130002010.57.m0066380.0
Hybrid PKS/NRPSs
233946KS-AT-DH-M-KR-T-C-A-T-T-RAFLA_0668400.7123.m0001750.7AO0900010002770.912.m0060792.8AFLA_066830,066860,066900
553851KS-AT-DH-M-KR-T-C-A-T-RAFLA_1394906.0210.m0001302.7AO0900260000010.55.m0072881.2AFLA_139500
Notes: a length in amino acids; b Domain abbreviations: A-adenylation; C-condensation; T-thiolation; M-methyltransferase; R-reductase; T-thioesterase; SDR_e1-short-chain dehydrogenases/reductases; gntK-gluconokinase; KS-ketosynthase; AT-acytransferase; DH-dehydratase; KR-ketoreductase; c RPKM values are from cultures grown on potato dextrose agar medium in the dark for two days. RPKM vaues >1 are shown in bold font; d not found: BLASTN search did not give hits with E value below 1e-10 and a percent identity above 80%.
Table 3. Putative GGPS or DMATS backbone genes in SMURF-identified secondary metabolite clusters in A. flavus NRRL3357.
Table 3. Putative GGPS or DMATS backbone genes in SMURF-identified secondary metabolite clusters in A. flavus NRRL3357.
Cluster NumberTypeA. flavus NRRL3357A. flavus AF70A. flavus CA14A. oryzae RIB40A. parasiticus BN9Transcription factor in cluster
GeneRPKM aGeneRPKM aRPKM bGeneRPKM aGeneRPKM a
2DMATSAFLA_0043000.011.m0005530.00.1AO0901020003220.014.m0045230.0AFLA_004280
15DMATSAFLA_0454900.024.m0004770.2104.3AO0900110007380.04.m0082550.0
19DMATSAFLA_06068068.8165.m00019637.20.6AO090701000600134.83.m00845419.7
22GGPSAFLA_0667800.6123.m0001810.50.3AO0900010002681.3not found
32GGPSAFLA_0963900.036.m0004820.0129.4AO0901130001710.07.m0066730.0AFLA_096370
37GGPSAFLA_10505010.050.m0003561.00.4AO09002300007013.717.m0037551.6
43DMATSAFLA_1166002.64.m0008530.51.0AO09001000008217.311.m0063150.4
Notes: a RPKM values were determined for cultures grown for 40 h on PDA medium; b RPKM values were determined for cultures grown for 168 h; CA42 is an S-strain isolate similar to AF70.
Table 4. Secondary metabolite backbone genes not assigned to A. flavus SMURF-identified gene clusters.
Table 4. Secondary metabolite backbone genes not assigned to A. flavus SMURF-identified gene clusters.
TypeA. flavus NRRL3357A. flavus AF70 geneA. oryzae RIB40A. parasiticus BN9
aa aDomains bGeneRPKM cGeneRPKMGeneRPKMGeneRPKM
Polyketide synthase
2595KS-AT-DH-M-ER-PPAFLA_0053203.4not foundnot foundnot found
1481KS-DH-ER-ER-KR-PPAFLA_0383101.7186.m0001720.4AO0900110000150.64.m0089440.9
2895KS-AT-DH-M-ER-NADP-SDR_e1AFLA_0538700.776.m0002610.5AO0900090000711.19.m0060820.9
2574KS-A-DH-MT-ER-ER-FabG-PPAFLA_0540900.076.m0002800.0AO0900090000520.09.m0060600.1
1254KS-AT-PPAFLA_0600200.1407.m0000892.9AO0907010005304.713.m0052080.2
2581KS-AT-DH-M-ER-ER-KR-PPAFLA_0804900.034.m0003940.0AO0900050007980.08.m0062220.0
2390KS-AT-DH-ER-KR-FabG-PPAFLA_1378702.735.m0004270.5AO0900260001494.35.m0074454.0
2569KS-AT-DH-M-ER-KRnot foundd220.m0001810.0not foundnot found
2609KS-AT-M-ER-KRnot found59.m0003470.0not foundnot found
2648KR-KS-AT-PP-TEnot found71.m0003530.0not found9.m0061480.0
2122KS-AT-PP-PPnot foundnot foundnot found4.m0087360.0
2482KS-AT-DH-M-ER-KR-PPnot foundnot foundnot found3.m0084130.0
2441KS-AT-DH-M-ER-KR-PPnot foundnot foundnot found2.m0097770.0
Non-ribosomal peptide synthase
1000A-T-TEAFLA_0178403.453.m0003652.4not found2.m00962914.8
950A-T-NADBAFLA_0416100.175.m0003400.0AO0900110003280.14.m0086220.5
677A-T-TEAFLA_0820500.08.m0006010.1AO0900050009520.03.m0086800.0
4760A-C-A-C-A-C-C-CAFLA_1094302.7119.m0002130.2AO0900230005285.616.m0039721.1
1048A-TEAFLA_1184400.2137.m0002470.0AO0900100003490.011.m0065070.0
690A-SDR_e1AFLA_1198202.22.m0008790.3AO0900100004981.611.m0066510.0
1068CaiC-A-TEAFLA_1281700.4182.m0001551.9AO0900010005161.86.m0075530.0
2465A-T-C-T-C-TE-T-CAFLA_1396700.0not foundnot found12.m0063590.1
3987A-C-A-M-C-A-TEnot foundnot foundnot found6.m0072740.0
476Anot foundnot foundnot found4.m0089520.0
1015A-T-Cnot foundnot foundnot found4.m0088580.0
986A-T-Rnot foundnot foundnot found6.m0071760.0
1338A-T-Cnot foundnot foundnot found5.m0078340.0
1848Anot found281.m000120not found6.m0073310.0
Dimethylallyltryptophan synthase
435DMATSAFLA_0832500.2118.m0002461.5AO0900050010790.27.m0066740.0
290DMATSAFLA_0840800.083.m0003210.0AO0900050011680.03.m0084540.0
354DMATSAFLA_0901900.0215.m0002480.0AO0901200000230.03.m0088620.0
435DMATSAFLA_0832500.2not found1.5not found0.23.m0087840.0
474DMATSnot foundnot foundnot found14.m0044130.0
Geranylgeranylpyrophosphate synthase
389GGPSAFLA_01831018.5357.m0001348.3AO09001200057316.02.m00958031.8
444GGPSAFLA_0387206.9248.m0001850.5AO09001100005418.42.m0094763.4
369GGPSAFLA_0536202.1169.m0002253.3AO0900090000936.27.m0072245.7
728GGPSAFLA_05682023.9235.m0001589.6not found4.m00890729.7
387GGPSAFLA_0667800.6not foundAO0900010002681.3not found
271GGPSAFLA_0703700.0138.m0002380.0not found19.m0021580.0
497GGPSAFLA_0703800.0138.m0002380.2AO0900380004950.013.m0048910.0
315GGPSAFLA_0737409.7369.m00010637.8AO09000500013213.08.m00685051.0
273GGPSAFLA_0906400.0143.m0002550.7AO0901200000640.04.m0089062.3
Notes: a aaa-length in amino acids; b Domains: KS-ketosynthase; AT-acyltransferase; DH-dehydratase; ER-enoyl reductase; KR-ketoreductase; PP-Phosphopantetheine attachment site; M-methyltransferase; TE-thioesterase. A-adenylation; C-condensation; T-thiolation; R-reductase; SDR_e1-short-chain dehydrogenases/reductase; FabG-3-oxoacyl-(acyl-carrier-protein) reductase; CaiC-carnitine CoA ligase; NADB-NAD-binding; c RPKM values were determined for cultures grown for 40 h on PDA medium; d not found-tBlastX search did not give hits with E value = 0.

2.2. Comparison of Putative Secondary Metabolite Clusters from A. oryzae, A. flavus S and L morphotype Isolates and A. parasiticus

Table 1, Table 2 and Table 3 compare secondary metabolite backbone genes in the SMURF-identified gene clusters in A. flavus NRRL3357 [16] with homologs in the other isolates. Homologs were determined by reciprocal best hit BLASTN search against the Genbank database for A. flavus NRRL3357. Additionally, we selected only the BLAST hits that had an expect (E) value below 1e-10 and a percent identity above 80%. By this criterion, the PKSs encoded by genes in clusters 23, 33, 36, 38, 40, 43, and 49 were not identified in the A. parasiticus genome and PKSs in clusters 36 and 43 were not identified in A. oryzae (Table 1). Of the NRPS clusters, A. flavus backbone genes in clusters 4, 7, 22, 28, 48 and 53 in A. parasiticus, in 34, 48, and 53 in AF70, and in 9 and 48 in A. oryzae were not identified in the genomes of these isolates (Table 2). The GGPS gene associated with cluster 22 was not identified in A. parasiticus (Table 3). NRPS, PKS, DMATS and GGPS genes that were not recognized by SMURF as being in a secondary metabolite gene cluster in A. flavus NRRL3357 are shown in Table 4 with their putative homologs in the other isolates. Some of these genes may be in, as yet, unrecognized secondary metabolite biosynthesis clusters. While many of these genes are present in all isolates, seven are found only in A. parasiticus. These may represent genes encoding biosynthesis of metabolites unique to A. parasiticus. Supplementary Table S2 lists the genes surrounding some of these backbone genes.

2.3. RNA-seq Analyses

For RNA-seq analysis we grew the fungi on PDA, a medium previously found to stimulate production of a wide variety of fungal secondary metabolites, including the aflatoxins [18], to determine which backbone genes clusters are actively transcribed. RNA-seq RPKM values are given in Table 1, Table 2, Table 3 and Table 4 and in Supplemental Tables S1 and Supplemental Tables S2. For the purpose of comparison of these data, we consider that an RPKM value less than 1 represents, at most, only a low level of expression, whereas an RPKM value greater than 1 represents detectable expression. Based on these criteria, the RPKM values shown in Table 1 suggest that under our growth conditions, only half of the 29 PKSs and 26 NRPSs for any one isolate can be considered to be expressed and in some cases, the backbone genes that were expressed in the different isolates had markedly different RPKM values. The most prominent differences were found for PKSs in clusters 5, 38, 46, and 52 (Table 1) and for NRPSs in clusters 21, 26, 37, and 55 (Table 2). Some of the backbone genes not previously assigned to gene clusters (Table 4) have RPKM values >1 and potentially could express genes that encode secondary metabolite biosynthesis enzymes. A. flavus CA42, an S strain isolate similar to AF70 (shown only in Table 3 and Table S1) gives much higher RPKM values for the PKS genes in clusters 1, 27 and 39, the NRPS genes in clusters 12, 23, 25, 35, 37 and 55, and the DMATS and GGPS genes for aflatrem production in clusters 15 and 32 when grown for 168 h than when grown for only 40 h. At these longer times S strain A. flavus produce abundant sclerotia. It is possible that timing of expression for some of the gene clusters is coordinated with sclerotial production and that the associated metabolites accumulate preferentially in sclerotia. To support this conjecture we found, in a separate study, that aflatrem was produced abundantly by both S strain isolates only when sclerotia are formed (Ehrlich and DianaDiMavungu, unpublished results) and under these conditions the genes for the aflatrem biosynthesis (in clusters 15 and 32) were expressed with high RPKM values. Also, the gene for cluster 27 PKS, which was shown to be necessary for most sclerotial pigmentation [19], only is expressed highly in cultures undergoing sclerotial formation (A. flavus CA42 in Table S1). Several of the non-reducing PKS genes that are differentially expressed in the different isolates, based on homology to genes in other fungi [20], are predicted to be associated with production of polyketides required for pigment formation, for example, those in clusters 5, 36, 39 and 42. The gene for the DMATS in cluster 19 was expressed at a high RPKM level in most isolates while the GGPS of cluster 37 (an NRPS cluster) was expressed at the highest level in NRRL3357.
These data show that the combination of RNA-seq analysis of secondary metabolite gene expression with SMURF-derived tabulation of putative backbone biosynthetic genes and their clustered common decorating genes is able to provide an accurate way to assess which secondary metabolite biosynthesis gene clusters encode the genes for metabolite production under a given set of growth conditions. However, it is possible that, even if the genes in a cluster are expressed, the resulting protein(s) may not be functional. Most of the PKS and NRPS genes listed in Table 1 and Table 2 as short sequences and which only encode one or two domains of a PKS or NRPS gave no or low RPKM values in our study with the exception of the putative ketosynthase and enoyl reductase genes in cluster 36, the ketosynthase genes in clusters 7 and 8, and the epimerase gene in cluster 7 (Table 1 and Table 2). While these backbone genes are annotated in the databases as PKS- or NRPS-encoding genes, usually such genes are quite large and encode multifunctional enzymes [5,6]. It is possible that for some of these clusters the genes were not annotated correctly in the database and that neighboring sequence should be included in establishing the identity of these protein-coding regions. However, given the lack of expression of most of these genes and their abnormal size, it is likely that such gene clusters, by themselves, do not encode proteins involved in formation of a secondary metabolite.
To prove that a gene cluster actually is involved in biosynthesis of a particular metabolite produced by these closely related Aspergilli (for a list of metabolites known to be produced by the isolates examined, see Supplemental Table S3), gene knockout and add back experiments must be done to show that the knockout mutant loses and regains, respectively, the ability to produce the metabolite. Such knockout gene experiments have been done, so far, to confirm the roles of clusters 15 and 32 in production of aflatrem [7], clusters 35 and 48 in production of two related piperazines [21], cluster 27 in production of asparasone [19], cluster 54 in production of aflatoxin [22], and cluster 55 [8] in production of cyclopiazonic acid. In studies of A. flavus, A. oryzae and A. parasiticus, about 20 different classes of metabolites have been isolated from culture extracts [18,23]. Because the types of backbone biosynthetic enzymes often indicate the probable type of metabolite that can be produced based on the catalytic properties of the main PKS or NRPS in the cluster [24,25] the RNA-seq data are consistent with production of about 20 different classes of metabolites. Since many of the putative backbone genes listed in Table 1, Table 2, Table 3 and Table 4 were not expressed, it is possible that these inactive clusters could become active under different growth conditions. In the present study only one growth condition (PDA) was used. It was previously found that gene activity can be induced by association of fungi with the proper microbial or nutritional environment or by artificial alteration of the chromatin state of the genes in the cluster [24,26,27]. The availability of RNA-seq data should improve the chances of being able to select a secondary metabolite backbone gene, that when disrupted, will actually result in loss of production of a specific metabolite.

3. Experimental Section

3.1. Aspergillus Species Chosen for Comparison

S strain A. flavus isolate, CA42, was obtained from almonds in California [28] and AF70 from cotton in Arizona [29]. A. parasiticus BN009E (BN9) was collected from ground nuts in Benin and was used for several studies of aflatoxin production by A. parasiticus [30,31]. Spore stocks were maintained on potato dextrose agar (PDA, Difco, Becton, Dickinson, Sparks, MD, USA) and V8 (5% V8 juice 2% agar) plates.

3.2. RNA-seq Experiments

For RNA-seq studies A. flavus CA42, A. flavus AF70 and A. parasiticus BN9 were grown on PDA for 168, 40, and 40 h respectively. PolyA-mRNA was extracted from liquid nitrogen ground mycelia using a Dynabeads mRNA Direct Kit from Life Technologies [32]. cDNA libraries were prepared using the Ion Total RNA-seq Kit v2 from Life Technologies. Sequencing was done on an Ion Personal Genome Machine (Life Technologies). The RNA-seq data have been deposited at the National Center for Biotechnological Information (NCBI) Sequence Read Archive (SRA) with accession numbers of SRX470276 for A. flavus AF70, SRX470271 for A. parasiticus BN9 and SRX471362 for A. flavus CA42. The publicly available RNA-seq data for A. oryzae RIB40 (SRR610543) and A. flavus NRRL3357 (SRR610538) were obtained from the European Nucleotide Archive [33].

3.3. Databases Used for Annotation

Genome sequences and annotations for A. flavus NRRL3357 were acquired from NCBI [34]. Genome sequence for A. oryzae was acquired from AspGD [35]. Genome sequences for A. parasiticus and A. flavus AF70 were acquired from J. Craig Ventor Institute (JCVI) [36]. The RNA-seq data for all four organisms were mapped to the exons of each respective annotated genome using CLC Genomics Workbench, which calculated the RPKM (Reads Per Kilobase of exon model per Million mapped reads) value for each gene. The number of reads mapped to exons were 1.9, 2.9, 1.2, 0.7, and 1.2 million for A. flavus NRRL3357, A. oryzae RIB40, A. flavus AF70, A. parasiticus BN9, and A. flavus CA42, respectively. Domain predictions were done using the Conserved Domain Database (CDD) at NCBI [37].

4. Conclusions

The closely related A. flavus, A. oryzae and A. parasiticus genomes likely produce markedly different families of metabolites when grown on the same medium. These differences could help explain why A. flavus is more commonly associated with agricultural contamination events than is A. parasiticus.
It is generally supposed that ingestion of aflatoxins in cereal grains is responsible for the observed toxic effects caused by A. flavus on humans and animals [38,39]. That the A. flavus genome is able to encode enzymes that catalyze the production of non-aflatoxin toxic secondary metabolites indicates the importance of looking for additional toxins in contaminated cereal grains.

Supplementary Files

  • Supplementary File 1:

    Supplementary Table 1 (XLSX, 73 KB)

  • Supplementary File 1:

    Supplementary Table 2 (XLSX, 19 KB)

  • Supplementary File 1:

    Supplementary Table 3 (XLSX, 11 KB)

  • Acknowledgments

    We thank Natalie Fedorova, J. Craig Venter Institute (JCVI), Rockville, MD, USA (now at National Institutes of Health) for kindly supplying a Table listing the genes in the 55 A. flavus gene clusters and also to Perng-Kuang Chang and Lester L. Scharfenstein (Southern Regional Research Center/United States Department of Agriculture) for obtaining the RNA-seq data on A. flavus CA42.

    Author Contributions

    Kenneth C. Ehrlich wrote the paper and provided guidance for the analyses. Brian M. Mack performed the RNA-seq experiments and analyzed the data.

    Conflicts of Interest

    The authors declare no conflict of interest.

    References

    1. Osbourn, A. Secondary metabolic gene clusters: Evolutionary toolkits for chemical innovation. Trends Genet. 2012, 26, 449–457. [Google Scholar] [CrossRef]
    2. SMURF., J. Craig Ventor Institute, Secondary Metabolite Unique Regions Finder. Available online: http://www.jcvi.org/smurf/ (accessed on 16 June 2014).
    3. Khaldi, N.; Seifuddin, F.T.; Turner, G.; Haft, D.; Nierman, W.C.; Wolfe, K.H.; Fedorova, N.D. SMURF: Genomic mapping of fungal secondary metabolite clusters. Fungal Genet. Biol. 2010, 47, 736–741. [Google Scholar] [CrossRef]
    4. Fedorova, N.D.; Khaldi, N.; Joardar, V.S.; Maiti, R.; Amedeo, P.; Anderson, M.J.; Crabtree, J.; Silva, J.C.; Badger, J.H.; Albarraq, A.; et al. Genomic islands in the pathogenic filamentous fungus Aspergillus fumigatus. PLoS Genet. 2008, 4, e1000046. [Google Scholar] [CrossRef]
    5. Chiang, Y.M.; Oakley, B.R.; Keller, N.P.; Wang, C.C.C. Unraveling polyketide synthesis in members of the genus Aspergillus. Appl. Microbiol. Biotechnol. 2010, 86, 1719–1736. [Google Scholar] [CrossRef]
    6. Von Dohren, H. A survey of nonribosomal peptide synthetase (NRPS) genes in Aspergillus nidulans. Fungal Genet. Biol. 2009, 46, S45–S52. [Google Scholar] [CrossRef]
    7. Nicholson, M.J.; Koulman, A.; Monahan, B.J.; Pritchard, B.L.; Payne, G.A.; Scott, B. Identification of two aflatrem biosynthesis gene loci in Aspergillus flavus and metabolic engineering of Penicillium paxilli to elucidate their function. Appl. Environ. Microbiol. 2009, 75, 7469–7481. [Google Scholar] [CrossRef]
    8. Chang, P.-K.; Ehrlich, K.C. Cyclopiazonic acid biosynthesis by Aspergillus flavus. Toxin Rev. 2011, 30, 79–89. [Google Scholar] [CrossRef]
    9. Chang, P.K.; Ehrlich, K.C. Genome-wide analysis of the Zn(II)2Cys6 zinc cluster-encoding gene family in Aspergillus flavus. Appl. Microbiol. Biotechnol. 2013, 97, 4289–4300. [Google Scholar] [CrossRef]
    10. Ehrlich, K.C.; Mack, B.M.; Cary, J.W.; Bhatnagar, D.; Kale, S.P. A hypothesis to explain how LaeA specifically regulates certain secondary metabolite biosynthesis gene clusters. World Mycotoxin J. 2011, 4, 53–58. [Google Scholar]
    11. Andersen, M.R.; Nielsen, J.B.; Klitgaard, A.; Petersen, L.M.; Zachariasen, M.; Hansen, T.J.; Blicher, L.H.; Gotfredsen, C.H.; Larsen, T.O.; Nielsen, K.F.; et al. Accurate prediction of secondary metabolite gene clusters in filamentous fungi. Proc. Natl. Acad. Sci. USA 2012, 110, E99–E107. [Google Scholar]
    12. Cotty, P.J.; Bayman, D.S.; Egel, D.S.; Elias, K.S. Agriculture, aflatoxins and Aspergillus. In The Genus Aspergillus; Powell, K., Ed.; Plenum Press: New York, NY, USA, 1994; pp. 1–27. [Google Scholar]
    13. Ahuja, M.; Chiang, Y.M.; Chang, S.L.; Praseuth, M.B.; Entwistle, R.; Sanchez, J.F.; Lo, H.C.; Yeh, H.H.; Oakley, B.R.; Wang, C.C.C. Illuminating the diversity of aromatic polyketide synthases in Aspergillus nidulans. J. Am. Chem. Soc. 2012, 134, 8212–8221. [Google Scholar] [CrossRef]
    14. Lin, J.Q.; Zhao, X.X.; Zhi, Q.Q.; Zhao, M.; He, Z.M. Transcriptomic profiling of Aspergillus flavus in response to 5-azacytidine. Fungal Genet. Biol. 2013, 56, 78–86. [Google Scholar] [CrossRef]
    15. Gibbons, J.G.; Salichos, L.; Slot, J.C.; Rinker, D.C.; McGary, K.L.; King, J.G.; Klich, M.A.; Tabb, D.L.; McDonald, W.H.; Rokas, A. The evolutionary imprint of domestication on genome variation and function of the filamentous fungus Aspergillus oryzae. Curr. Biol. 2012, 22, 1403–1409. [Google Scholar] [CrossRef]
    16. Georgianna, D.R.; Fedorova, N.D.; Burroughs, J.L.; Dolezal, A.L.; Bok, J.W.; Horowitz-Brown, S.; Woloshuk, C.P.; Yu, J.J.; Keller, N.P.; Payne, G.A. Beyond aflatoxin: Four distinct expression patterns and functional roles associated with Aspergillus flavus secondary metabolism gene clusters. Mol. Plant Pathol. 2010, 11, 213–226. [Google Scholar] [CrossRef]
    17. Terabayashi, Y.; Sano, M.; Yamane, N.; Marui, J.; Tamano, K.; Sagara, J.; Dohmoto, M.; Oda, K.; Ohshima, E.; Tachibana, K.; et al. Identification and characterization of genes responsible for biosynthesis of kojic acid, an industrially important compound from Aspergillus oryzae. Fungal Genet. Biol. 2010, 47, 953–961. [Google Scholar] [CrossRef]
    18. Rank, C.; Klejnstrup, M.L.; Petersen, L.M.; Kildgaard, S.; Frisvad, J.C.; Gotfredsen, C.H.; Larsen, T.O. Comparative Chemistry of Aspergillus oryzae (RIB40) and A. flavus (NRRL 3357). Metabolites 2012, 2, 39–56. [Google Scholar] [CrossRef]
    19. Malysheva, S.; Arroyo-Manzanaresb, N.; Cary, J.; Ehrlich, K.; van den Bussched, J.; Vanhaecked, L.; Bhatnagar, D.; Diana di Mavungu, J.; de Saeger, S. Identification of novel metabolites from Aspergillus flavus by high resolution and multiple stage mass spectrometry. Food Addit. Contam. Part A 2014, 31, 111–120. [Google Scholar] [CrossRef]
    20. Fujii, I. Functional analysis of fungal polyketide biosynthesis genes. J. Antibiot. Tokyo 2010, 63, 207–218. [Google Scholar] [CrossRef]
    21. Forseth, R.R.; Amaike, S.; Schwenk, D.; Affeldt, K.J.; Hoffmeister, D.; Schroeder, F.C.; Keller, N.P. Homologous NRPS-like gene clusters mediate redundant small-molecule biosynthesis in Aspergillus flavus. Angew. Chem. Int. Ed. Engl. 2013, 52, 1590–1594. [Google Scholar] [CrossRef]
    22. Yu, J.; Bhatnagar, D.; Cleveland, T.E. Completed sequence of the aflatoxin pathway gene cluster in Aspergillus parasiticus. FEBS Lett. 2004, 564, 126–130. [Google Scholar] [CrossRef]
    23. Turner, W.B.; Aldridge, D.C. Fungal Metabolites II; Academic Press: London, UK, 1983. [Google Scholar]
    24. Sanchez, J.F.; Somoza, A.D.; Keller, N.P.; Wang, C.C. Advances in Aspergillus secondary metabolite research in the post-genomic era. Nat. Prod. Rep. 2012, 29, 351–371. [Google Scholar] [CrossRef]
    25. Brakhage, A.A.; Schroeckh, V. Fungal secondary metabolites—Strategies to activate silent gene clusters. Fungal Genet. Biol. 2010, 48, 15–22. [Google Scholar] [CrossRef]
    26. Konig, C.C.; Scherlach, K.; Schroeckh, V.; Horn, F.; Nietzsche, S.; Brakhage, A.A.; Hertweck, C. Bacterium induces cryptic meroterpenoid pathway in the pathogenic fungus Aspergillus fumigatus. Chembiochem 2013, 14, 938–942. [Google Scholar] [CrossRef]
    27. Vodisch, M.; Scherlach, K.; Winkler, R.; Hertweck, C.; Braun, H.P.; Roth, M.; Haas, H.; Werner, E.R.; Brakhage, A.A.; Kniemeyer, O. Analysis of the Aspergillus fumigatus proteome reveals metabolic changes and the activation of the pseurotin A biosynthesis gene cluster in response to hypoxia. J. Proteome Res. 2012, 10, 2508–2524. [Google Scholar]
    28. Hua, S.S.; McAlpin, C.E.; Chang, P.K.; Sarreal, S.B. Characterization of aflatoxigenic and non-aflatoxigenic Aspergillus flavus isolates from pistachio. Mycotoxin Res. 2012, 28, 67–75. [Google Scholar] [CrossRef]
    29. Ehrlich, K.C.; Montalbano, B.G.; Cotty, P.J. Divergent regulation of aflatoxin production at acidic pH by two Aspergillus strains. Mycopathologia 2005, 159, 579–581. [Google Scholar] [CrossRef]
    30. Cary, J.W.; Harris-Coward, P.Y.; Ehrlich, K.C.; Mack, B.M.; Kale, S.P.; Larey, C.; Calvo, A.M. NsdC and NsdD affect Aspergillus flavus morphogenesis and aflatoxin production. Eukaryot. Cell 2012, 11, 1104–1111. [Google Scholar] [CrossRef]
    31. Ehrlich, K.C.; Li, P.; Scharfenstein, L.; Chang, P.-K. HypC is the anthrone oxidase involved in aflatoxin production. Appl. Environ. Microbiol. 2010, 76, 3374–3377. [Google Scholar] [CrossRef]
    32. Life Technologies Inc. Available online: http://www.lifetechnologies.com/us/en/home.html (accessed on 16 June 2014).
    33. European Nucleotide Archive. Available online: http://www.ebi.ac.uk/ena/ (accessed on 16 June 2014).
    34. National Center for Biotechnology Information. Available online: http://www.ncbi.nlm.nih.gov (accessed on 16 June 2014).
    35. AspGD. Aspergillus Genome Database. Available online: http://www.aspgd.org (accessed on 16 June 2014).
    36. Index of Aspergillus flavus Genome Files Deposited at the J. Craig Ventor Institute. Available online: ftp://ftp.jcvi.org/pub/data/a_flavus/ (accessed on 16 June 2014).
    37. Conserved Domain Database (CDD) at national Center for Biotechnoloy Information. Available online: http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi (accessed on 16 June 2014).
    38. Wu, F.; Khlangwiset, P. Health economic impacts and cost-effectiveness of aflatoxin-reduction strategies in Africa: Case studies in biocontrol and post-harvest interventions. Food Addit. Contam. Part A Chem. Anal. Control Expo. Risk Assess. 2010, 27, 496–509. [Google Scholar] [CrossRef]
    39. Probst, C.; Schulthess, F.; Cotty, P.J. Impact of Aspergillus section Flavi community structure on the development of lethal levels of aflatoxins in Kenyan maize (Zea mays). J. Appl. Microbiol. 2010, 108, 600–610. [Google Scholar] [CrossRef]

    Share and Cite

    MDPI and ACS Style

    Ehrlich, K.C.; Mack, B.M. Comparison of Expression of Secondary Metabolite Biosynthesis Cluster Genes in Aspergillus flavus, A. parasiticus, and A. oryzae. Toxins 2014, 6, 1916-1928. https://doi.org/10.3390/toxins6061916

    AMA Style

    Ehrlich KC, Mack BM. Comparison of Expression of Secondary Metabolite Biosynthesis Cluster Genes in Aspergillus flavus, A. parasiticus, and A. oryzae. Toxins. 2014; 6(6):1916-1928. https://doi.org/10.3390/toxins6061916

    Chicago/Turabian Style

    Ehrlich, Kenneth C., and Brian M. Mack. 2014. "Comparison of Expression of Secondary Metabolite Biosynthesis Cluster Genes in Aspergillus flavus, A. parasiticus, and A. oryzae" Toxins 6, no. 6: 1916-1928. https://doi.org/10.3390/toxins6061916

    Article Metrics

    Back to TopTop