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  • Research article
  • Open Access

Do environmentally induced DNA variations mediate adaptation in Aspergillus flavus exposed to chromium stress in tannery sludge?

  • 1,
  • 1,
  • 1 and
  • 1Email author
BMC Genomics201819:868

https://doi.org/10.1186/s12864-018-5244-2

  • Received: 13 February 2018
  • Accepted: 14 November 2018
  • Published:

Abstract

Background

Environmental stress induced genetic polymorphisms have been suggested to arbitrate functional modifications influencing adaptations in microbes. The relationship between the genetic processes and concomitant functional adaptation can now be investigated at a genomic scale with the help of next generation sequencing (NGS) technologies. Using a NGS approach we identified genetic variations putatively underlying chromium tolerance in a strain of Aspergillus flavus isolated from a tannery sludge. Correlation of nsSNPs in the candidate genes (n = 493) were investigated for their influence on protein structure and possible function. Whole genome sequencing of chromium tolerant A. flavus strain (TERIBR1) was done (Illumina HiSeq2000). The alignment of quality trimmed data of TERIBR1 with reference NRRL3357 (accession number EQ963472) strain was performed using Bowtie2 version 2.2.8. SNP with a minimum read depth of 5 and not in vicinity (10 bp) of INDEL were filtered. Candidate genes conferring chromium resistance were selected and SNPs were identified. Protein structure modeling and interpretation for protein-ligand (CrO4− 2) docking for selected proteins harbouring non-synonymous substitutions were done using Phyre2 and PatchDock programs.

Results

High rate of nsSNPs (approximately 11/kb) occurred in selected candidate genes for chromium tolerance. Of the 16 candidate genes selected for studying effect of nsSNPs on protein structure and protein-ligand interaction, four proteins belonging to the Major Facilitator Superfamily (MFS) and recG protein families showed significant interaction with chromium ion only in the chromium tolerant A. flavus strain TERIBR1.

Conclusions

Presence of nsSNPs and subsequent amino-acid alterations evidently influenced the 3D structures of the candidate proteins, which could have led to improved interaction with (CrO4− 2) ion. Such structural modifications might have enhanced chromium efflux efficiency of A. flavus (TERIBR1) and thereby offered the adaptation benefits in counteracting chromate stress. Our findings are of fundamental importance to the field of heavy-metal bio-remediation.

Keywords

  • Non synonymous SNPs (nsSNPs)
  • Mutation
  • Protein structure and function
  • Protein-ligand interaction
  • Adaptation

Background

Bioremediation of heavy metals by microbial cells has been recognized as a potential alternative to the existing physico-chemical technologies for recovery of heavy metals from industrial effluents [1]. Metal uptake in microorganisms takes place either actively (bioaccumulation) or passively (biosorption) [26]. Several species of bacteria and fungi have been identified for their bioaccumulation or absorption potentials and reduced cost and toxicity achieved by microbial bioremediation approach are appreciated over the conventional methods [7]. Various bacterial species detoxify chromium by periplasmic absorption, intracellular bioaccumulation and biotransformation through direct enzymatic reaction or indirectly with metabolites. Filamentous fungi have been identified as a potential biomass for removal of heavy metals from solutions and species of Aspergillus, Rhizopus and Penicillium are reported useful in biological treatment of the sludge [811], Several reports support the prominent ability of Aspergillus flavus in detoxification of chromium and other heavy metals [12]. However, the molecular mechanisms underlying heavy metal detoxification in fungi are largely unknown. Understanding the genes and pathways involved in metal accumulation/tolerance in fungi has several biotechnological implications for bioremediation of heavy metal-contaminated sites.

The extensive use of chromium in diverse industrial processes has made it a significant environmental contaminant. Chromium is a Class A human carcinogen [13, 14] and exists in eleven valence states (from −IV to +VI), among which Cr (III) and Cr (VI) are the most stable forms in the environment. Due to high water solubility Cr (VI) is 100-folds more toxic over Cr (III). As per the United States Environmental Protection Agency (US EPA) the maximum contaminant level for Cr (VI) and total chromium content in domestic water supplies is 0.05 and 2 mg/l respectively [15]. Cr (VI) actively crosses biological membranes [16] and generates active intermediates Cr (V) and/or Cr (IV), free radicals, and Cr (III). Cellular accumulation of Cr (III) causes damage to DNA and alters the structure and activity of proteins [17, 18]. The existing physico-chemical processes for treating chromium-contaminated water bodies include precipitation, ion exchange, reverse osmosis, evaporation and electro dialysis, which are reported to display poor efficiency [14, 1924].

For survival in Cr (VI) contaminated environments, microorganisms must develop efficient systems to detoxify the effects of chromium. These mechanisms involve detoxification or repair strategies such as Cr (VI) efflux pumps, Cr (VI) reduction to Cr (III), and activation of enzymes involved in the detoxifying processes, repair of DNA lesions, sulfur metabolism, and iron homeostasis [16, 18, 25]. Additionally, alterations in gene function due to mutation have been suggested to support survival under chromium toxic conditions [26]. Biotransformation and biosorption are suggested as the putative fungal processes that help them transform or adsorb heavy metals [27]. The fungal cell walls predominantly consist of chitins, glucans, mannans and proteins in addition to other polysaccharides, lipids and pigments [28, 29]. The functional groups on these structural components enable binding of metal ions on the fungal cell walls [30]. Uptake and reduction of hexavalent chromium has been suggested as the mechanisms for chromium tolerance in Aspergillus sp. [27, 31].

Information on genes supporting survival under environmental stress in bacterial system has been recently curated in BacMet database ( http://bacmet.biomedicine.gu.se ) which primarily contains several experimentally verified Chromate ion transporter (CHR) genes [32] responsible for chromium efflux, transport or binding, and other enzymes involved in chromium uptake. However, very less knowledge is available on genetic mechanisms responsible for chromium tolerance in fungi. In the Neurospora crassa strain 74-A, chr-1 gene that encodes a putative CHR-1 protein and belongs to the CHR superfamily was identified [33]. However, contrary to the bacterial ChrA (chromate transport protein) homologues that confer chromate resistance by exporting chromate ions from the cell’s cytoplasm, the experimental data suggested that the N. crassa CHR-1 protein functions as a transporter that takes up chromate [34]. The presence of CHR-1 protein was reported to cause chromate sensitivity and chromium accumulation in N. crassa.

Experimental evidences in a recent study suggested that environmental stress could induce adaptation in a wide range of micro-organisms by extensive positive pleiotropy in a manner that multiple beneficial mutations dramatically enhance numerous fitness components simultaneously [35]. Environmentally induced mutations and polymorphisms in DNA and subsequently the alteration in proteins are hypothesized to offer a significant evolutionary advantage by enabling faster adaptation to toxic conditions [36]. We identified a high chromium tolerant Aspergillus flavus strain (TERIBR1) from a tannery sludge in Kanpur, Uttar Pradesh, India. TERIBR1 showed accumulation of Cr (III) in its biomass while growing in Cr containing media. It showed no toxic effect of Cr (VI) up to 250 mg/l. In order to identify the genetic factors underlying chromium tolerance in TERIBR1, we investigated effects of nonsynonymous variations (nsSNPs) in candidate genes on protein structure and their interaction with chromate ion.

Our study comprises whole genome sequencing of A. flavus strain TERIBR1 followed by single nucleotide polymorphism (SNPs) analysis in candidate genes for chromium-resistance. Protein modeling for candidate genes with nsSNPs was done and interactions between modeled proteins and the ligand (CrO4− 2) were assessed by protein-ligand docking. For all comparative genomics and genetics analyses the A. flavus strain TERIBR1 was considered as the “test” and previously sequenced strain NRRL3357 as the “reference” type.

Materials and methods

Fungal strain and DNA extraction

The protocol followed for isolation and characterization of fungi from a tannery sludge is previously described [37]. Briefly, the Cr-resistant fungi were isolated from a tannery sludge [containing 250 mg/l of Cr (III)] through an enrichment culture technique. The sludge sample was collected from a tannery waste disposal site in Kanpur, India. Pure culture of the isolated A. flavus strain (TERIBR1) was grown in potato dextrose broth (PDB) at 28 °C in a shaking incubator (100 rpm) for 72 h in dark condition. After incubation, culture was centrifuged at 5000 g for 10 min at room temperature. The pellet was washed thrice with sterile distilled water to remove any media components and was further used for DNA extraction. Genomic DNA was extracted using the DNeasy plant mini kit (QIAGEN, USA), according to the manufacturer’s instructions. Genetic characterization of isolated fungi was done using universal fungal ITS (nuclear ribosomal internal transcribed spacer) primer set [ITS1: 5’ TCCGTAGGTGAACCTGCGG, 3′ and ITS4: 5’ TCCTCCGCTTATTGATATGC 3′; [38] that amplified the ITS1, 5.8S and ITS2 regions of the nuclear ribosomal RNA genes.

Growth kinetics and sensitivity to Cr (VI)

The effect of different concentrations of chromium [Cr (VI)], 0 mg/l, 100 mg/l and 250 mg/l, on the growth of A. flavus strains TERIBR1 and NRRL3357 was compared. The strains were grown in PDB and mycelial biomass (dry weight) was measured at different time periods (0, 1, 2, 3, 4 and 5 days).

Genome sequencing and assembly

Genome sequencing was performed at MOgene LC, USA, using next generation sequencing technology Illumina as reported previously [39]. Two paired end libraries (insert sizes 180 bp and 500 bp) and one mate pair library (5 kb) were constructed. DNA libraries were purified using AMPure XP beads. KAPA was done to quantify the libraries, which were then normalized and pooled at 4 nM concentration.

A total of 8 GB raw data was subjected to adaptor- and quality-based trimming. Quality-passed data was assembled using the de novo genome assembler AllpathsLG [40]. Reads with overlaps were first combined to form contigs. The reads were mapped back to contigs. With paired-end reads, contigs from the same transcript, as well as the distances between these contigs, were detected. In order to generate scaffolds, contigs were connected using “N” to represent unknown sequences between two contigs. Mate-pair reads were used for gap filling of scaffolds in order to get sequences with minimal N’s and the longest length. The whole genome project has been deposited at https://submit.ncbi.nlm.nih.gov/subs/wgs/ under Bioproject PRJNA362980.

Structural and functional annotation of A. flavus TERIBR1 genome was done using MAKER [41] pipeline, InterProScan [42] and nrBlast [39] as described previously.

Identification of single nucleotide polymorphisms (SNPs)

Genome and protein sequences for reference genome were retrieved from the Aspergillus flavus Database (http://fungidb.org/fungidb/app/record/organism/aflaNRRL3357). The alignment of quality trimmed data of TERIBR1 with NRRL3357 (assembly) was performed using Bowtie2 version 2.2.8 [43]. Samtools [ http://samtools.sourceforge.net/ ] was used for SNP identification.

SNP analysis in candidate genes for chromium resistance

Genes conferring chromium resistance in bacterial system were selected from BacMet database [32]. BacMet is freely available antibacterial biocide and metal resistance genes database for bacteria. InterProScan analysis [42] was performed to identify A. flavus genes harbouring atleast one IPR domains that are present in the chromium resistance genes documented in the BacMet database. SNPs were identified in the selected candidate genes using variant calling format (VCF) file and Blastn tool. SNPs were further annotated as synonymous or non-synonymous (nsSNPs) using an in-house perl script.

Protein structure modeling

Protein modeling was done by fold recognition methods through Phyre2 server [44]. The amino acid sequences of candidate genes in both the reference (NRRL3357) and the test strains were modeled. The top model with highest confidence and coverage was selected for each protein. The predicted confidence score and coverage for all the final structures were recorded. To assess the reliability of all the predicted models, structural analysis and verification was exercised. The selected models were validated using the PROCHECK [45] and ERRAT [46] to estimate the stereo chemical figures, geometry, and hydrogen bonding energy, torsion angles and error rate of the predicted structures. In addition, energy minimization was performed with in vacuo GROMOS96 43B1 parameters set using GROMOS96 implementation in Swiss-Pdb Viewer [47]. The energy optimized protein structures were used for protein-small ligand docking.

Prediction of ligand binding sites

Prior to docking, a web based approach 3DLigandSite [48] was used to predict the ligand binding sites. 3DLigandSite utilizes protein-structure prediction to provide structural models for proteins that have not been solved. Ligands bound to structures similar to the query are superimposed onto the model and used to predict the binding site.

Protein- ligand docking

In order to investigate protein–ligand interactions, proteins were docked with the chromate ion (CrO4− 2) through a rigid docking protocol using PatchDock (http://bioinfo3d.cs.tau.ac.il/PatchDock/) [49, 50] which docks the ligand with the protein based on structure complementarity. Also, binding sites predicted by 3DLigandSite in the receptor/proteins were specified and uploaded in PatchDock analysis. The protein-ligand interactions were interpreted based on Atomic Contact Energy (ACE) and docking score. The pdb file of chromate ion was downloaded from the RCSB PDB (research collaborator fo structural Bioinformatics protein data bank) site [51]. The PDB structures of target proteins and protein-ligand interaction were visualized using the PyMOL [52].

Results

Growth kinetics and sensitivity to Cr (VI)

Dry weight of fungal biomass was recorded at different time periods (from 1 to 5 days) for both the strains under the conditions mentioned above. No significant difference in growth was observed between the two strains under the control condition (Fig. 1). However, stark difference in the mycelial biomass (dry weight) between the reference strain (NRRL3357) and the test strain (TERIBR1) was observed when potato dextrose broth was amended with chromium 100 mg/l and 250 mg/l. Growth kinetics of the TERIBR1 strain at chromium concentration of 100 mg/l were similar to that observed under control condition (no chromium). The reference strain exhibited delayed growth response with concomitant decrease in biomass in comparison to the test strain at different time intervals (between day 1 and day 5) when the growth media was amended with chromium at concentrations of 100 mg/l and 250 mg/l.
Fig. 1
Fig. 1

Chromium [Cr (VI)] dose response exhibited by TERIBR1 and NRRL3357 strains of A. flavus. Chromium dose/growth response (measured by dry weight) exhibited by TERIBR1 and NRRL3357 strains of A. flavus grown up to 5 days in potato dextrose broth supplemented with Cr (VI): (a) 0 mg/l, (b) 100 mg/l and 250 mg/l

Global genome structure

The genome of A. flavus strain TERIBR1 was sequenced to 200x coverage and reads were assembled into 322 scaffolds. The sum of the scaffolds length is equal to 38.2 Mb. The three largest scaffolds are 2.76 kb, 2.64 kb, and 2.50 kb in size. The MAKER annotation pipeline predicted 13,587 protein coding genes as compared to 13,659 in NRRL3357. Gain or loss of unique genes, DNA duplication, gene family expansion, and translocation of transposon-like elements are often observed between different isolates of a fungal species [53]. This may suggest that some of the genes present in NRRL3357 could have been lost in TERIBR1, possibly during environmental adaptations.

Identification of candidate genes in A. flavus

No homologue of CHR-1 protein (XP_961667.3) coded by N. crassa was identified in both the A. flavus strains included in this study. A total of 34 InterProScan domains coding for transporter or regulator proteins responsible for chromium bio-accumulation or tolerance in bacteria were reported in the BacMet database. nrBlast was performed to identify genes containing at least one IPR domain associated with chromium tolerance in the genome of A.

Flavus strain TERIBR1, NRRL3357 (http://fungidb.org/fungidb/app/record/organism/aflaNRRL3357) and AF70 (https://www.ncbi.nlm.nih.gov/assembly/GCA_000952835.1). 23/34 bacterial IPR domains were not found in any of the three strains of A. flavus. A total of 493 candidate genes was identified to harbor one or more IPR domains of interest in TERIBR1(Table 1). IPR domains mdrL/yfmO (IPR011701; n = 334), recG (IPR001650; n = 71), ruvB (IPR003959; n = 45) and recG (IPR011545; n = 44) were among the maximally present protein domains related to chromium resistance.
Table 1

Distribution of IPR domains important in chromium bio-accumulation in A. flavus strains TERIBR1, NRRL3357 & AF70

Gene Family (BacMet db)

Description

Interproscan Domain

# of Genes containing IPR domains of interest

   

NRRL3357

TERIBR1

AF70

Chromate ion transporter (CHR) family (chrA)

Efflux

IPR003370

1

1

2

Rhodanese family (chrE)

Enzyme

IPR001763

9

6

10

NADH_dh2 family (chrR)

Enzyme

IPR005025

4

4

4

  

IPR000415

0

3

0

MFS superfamily (mdrL/yfmO)

Efflux

IPR011701

374

334

394

Contains 1 DEAD/DEAH box helicase domain (recG)

Enzyme

IPR011545

43

44

42

  

IPR001650

74

71

80

  

IPR004365

2

5

4

RuvB family (ruvB)

Enzyme

IPR003959

47

45

48

  

IPR012301

2

2

2

Identification of single nucleotide polymorphisms (SNPs)

The read alignment rate of TERIBR1 with NRRL3357 (assembly) was 78.62% (29,001,807 / 36,890,268) of which 78.23% (22,681,743) were uniquely mapped reads. A total of 201,145 SNPs (read depth > 5) was identified at a frequency of ~ 5 SNPs per Kb of the TERIBR1 genome. SNP mapping in n = 493 candidate genes, homologous among A. flavus NRRL3357 and TERIBR1 isolates was done using Samtools. No SNP was identified in 325/493 genes. SNPs identified in the remaining n = 168 genes were annotated as synonymous or non-synonymous (Additional file 1: Table S1). 28/168 candidate genes contained only synonymous polymorphisms whereas 16/168 candidate genes, belonging to MFS (n = 12), recG (n = 3) and chrE (n = 1) protein families, showed higher rate of nsSNP as compared to other candidate genes (Additional file 2: Table S2).

Protein- ligand docking

For studying protein-chromate ion interaction, we predicted tertiary protein structures of homologous pairs of the 16 highly polymorphic proteins (Additional file 2: Table S2) using Phyre2 server (Additional file 3: Table S3). Prediction for Cr binding sites in the target proteins was done by 3DLigandSite (Table 2). Strength of protein-ligand interaction was measured based on the atomic contact energy (ACE) in the PatchDock score (Table 3). Also change in free energy (ΔG) of the amino acid residues present in the predicted binding and ligand docking sites was recorded (Fig. 2). Structures of 8 proteins in both the reference and test strains did not show any possible interaction between the ligand and the target proteins. Ligand docking was observed in both the strains for four proteins (g8975, g685, g6212, g9525; Additional file 4: Figure S1). Binding residues that showed a drop in free energy on chromate docking in PatchDock analysis are depicted on the 3D structures of these four proteins (Additional file 4: Figure S1).
Table 2

Prediction of binding site and protein – ligand interaction using 3DLigandSite and PatchDock softwares respectively

Protein ID

nsSNP

Predicted binding sites

Docking status and residues in recognition cavity

# nsSNP

Gene

Family

NRRL3357

TERI

BRI

NRRL

3357

TERI

BR1

NRRL3357

TERIBR1

  

AFL2G_00299

g652

A346D, D351N, M389 T

A261, G262, I263

No B.S.

N/A

≤2

mdrL/ yfmO

AFL2G_04853

g9548

P254L, K261I, K263E, A262D, M34 T

T67, F68, V69, S70, P71, L72, A73, S74, S75, L104, Y107, V108, P111, G161, C164, L165, W188, P192, Y280, L283, Y284, T288, Y393, T416, A417, S420, L421, V422, A424, L425, L426

Y122, W203, P207, Y319, L322, Y323

N/A

2 to 5

mdrL/ yfmO

AFL2G_04391

g8975

P341A, D349E, H356Y, P373L, P374L

Q119, F240, H403, T404, N405, V407, Q408, L454, F477, S481, Y485, V508, L511, Q512, V514, S515, R516, F518, V519, L520, P521, S524

Q115, F240, N405, A406, Q408, T409, L454, F477, S481, Y485, V508, L511, Q512, V514, S515, R516, F518, V519, L520, P521, S524, R552

Dock

2 to 5

mdrL/ yfmO

AFL2G_02473

g5755

K53 N, N59D, K213 M, V293I, K340R

H97, W124, I125, L126, V127, M128, F129, F130, A131, L132, N133, I134, D135, I183, G184, P185, D186, R187, W188, I189, P190, I191, Q192, I193, I194, L195, S197, F226, D229, V253, S257, A288, S291, I292, G295, F296, S298, F299, L302

W115, I116, L117, V118, M119, F120, A122, I174, G175, P176, D177, R178, W179, I180, P181, I182, Q183, I184, I185, L186, F217, S282, G286, S289, F290, L293, V294

N/A

2 to 5

mdrL/ yfmO

AFL2G_00264

g685

S126G, T139A, G179E, Y112F

T334, L335, G400, K401, S402, L403, E461, H465, F680, G681, R711

T321, L322, M386, G387, K388, S389, L390, E442, H446, F726, G727, R757

Dock

2 to 5

recG

AFL2G_05826

g6641

P307L, Q11P, V19G, E102D, V126A, A129V

No B.S.

S270, M273, I274, Q396

N/A

> 5

mdrL/ yfmO

AFL2G_09247

g6212

R471H, R437Q, S837P, L1229 V, V192I, L233S

K272, L273, L274, Q277, G309, L310, G311, K312, T313, V314, E380, K384, L919, G920, L921, N922, R947, R950, L951

L544, V546, K547, L548, L549, Q552, G584, L585, G586, K587, T588, V589, E655, K659, L1194, G1195, N1197, R1222, R1225, L1226

Dock

> 5

recG

AFL2G_08767

g9986

F222I, A244P, Q270P, G340R, A342G, F431 L, S472I

W290, L291, Y292, L294, M295, I353, L354, V355, M356, H357, L358, W359, T360, P362, P363, F401, I404, Y455, M458, N459, L462, T465, R466

K277, Y278, Q279, V281, E282, A283, T285, I288, A337, V338, M339, V340, G341, G342, A343, S344, P346, P347, F385, I388, N443, L446, L447, R450, L453, I454

N/A

Dock

K277, Q279, T285, L446

> 5

mdrL/ yfmO

AFL2G_05032

g9401

N373D, S445 N, E503G, S535 L, V572G, F592Y, K610E, I50M

H614, H616, L666, H668, H670

C97, A98, F100, L101, Y104, I107, M159, A160, I161, I162, Y164, S165, A168, I169, F198, A202, V205, S257, T260, H261, A264, N267, K268

N/A

> 5

mdrL/ yfmO

AFL2G_06586

g3683

S517 N, Q324E, L899S, S57 L, D63G, T18I, K285R

Q193, L194, K195, Q198, M221, G222, L223, G224, K225, T226, I227, E266, I643

L145, S147, Q148, L149, G179, K180, T181, I182, E221, K224, W225, E573, G574, R604

N/A

Dock

L149, K180, T181, I182

> 5

recG

AFL2G_11779

g4359

G294D, K360E, V388I, F393 L, L468P, Q66H, R19K, V637I, A646T

L582, V586, M589, N590, M593, A621, Y623, L631, H632, A635, H636, H640, W647, I659

R34, T36, A94, V95, Y100, S101, A178, I206, P207, L208, A209, V211

N/A

> 5

chrE

AFL2G_09661

g4104

R80M, L110 V, V144 L, N150S, F191 L, G198R, Y199C, E407G, G5E, I25N

No B.S.

N/A

Dock V144 L, N150S

> 5

mdrL/ yfmO

AFL2G_04878

g9525

G210S, C363W, I368S, H438Y, M484, P106A, V131I, V146A, N156S, F163 L, L182F, Q59H

S63, I66, F92

S141, I144, F170

Dock

> 5

mdrL/ yfmO

AFL2G_00229

g712

R163L, G180C, S215C, S220Y, A226P, V693I, S765 N, F834I, Q854H, C938S, V121A

G570, A571, N572, S573, G574, L575, V595, R596, S597, K600, L624, D625, M626, L627, N652, A653, G654, I655, V673, V704, G705, S706, Y745, K749, P780, G781, P782, T783, S785, G786, L787

G666, A667, N668, S669, G670, L671, V691, R692, K696, L720, D721, M722, L723, N748, A749, G750, I751, V769, V800, G801, S802, Y841, K845, P876, G877, P878, T879, S881, G882, L883

N/A

> 5

mdrL/ yfmO

AFL2G_04255

g9088

L52 V, S101G, A212T, F214 L, T217A, S237 L, A250V, P252L, P271S, M280 T, K292 N, S297R, V303I

A104, L105, P108, S110, L138, I139, V141, G142, M165, M169, A226, I256, F338, L341, N342, M367, Y477, G481, L483

A195, P198

N/A

> 5

mdrL/ yfmO

AFL2G_11442

g4641

M254I, P321T, I433V, D661G, P675Q, F682 L, D110N, A111V, I114V, K143 T, T3A, H13Q, T24A, C46S, K826R

A120, F121, V122, V123, S124, A125, A126, S127, S128, L156, F159, A160, S163, M187, P216, L217, Y240, S244, Y355, F359, D363, T513, V514, Y517, C518, A519, G521, G522, M523

S372, A492, V493, L494, P496, F603, F606, W628, V629, A630, M631, Y632, V633, G634, I635, M636, L637, L640, S724

N/A

Dock

Y632, F606, W628, A492

> 5

mdrL/ yfmO

SNPs marked in bold were predicted binding site present in the predicted recognition cavity of the protein. B.S. stands for binding site

Fig. 2
Fig. 2

Protein-chromate ion interaction observed with four MFS transporter proteins of A. flavus strain TERIBR1. Docking of chromate ion with MFS transporter proteins in occluded conformation. The chromate ion is depicted as a sphere model. The amino acids of the interacting protein showing negative energy are depicted as bright orange sticks and the interacting binding sites as green sticks. Presence of nsSNPs in the protein sequence is shown in magenta. Amino-acids present in the close vicinity of the binding sites are marked in black (sSNP) and magenta (nsSNP). Figure was produced using the PyMOL Molecular Graphics System

Interestingly, the presence of non-synonymous mutations correlated with change in bioactive conformation and drop in free energy (ΔG) of four proteins (g9986, g3683, g4104, g4641) belonging to three MFS and one recG (helicase) superfamilies in the test strain only (Fig. 2). The structural changes in these proteins lead to successful protein-ligand interactions.

Discussion

As expected for functional conservation, majority of candidate genes in the TERIBR1 genome showed the presence of a large number of sSNPs and a few nsSNPs. Notably, 28/168 candidate genes contained only synonymous polymorphisms. Synonymous codon positions, though do not alter amino acid sequences of the encoded proteins, they may determine secondary structure, stability and translation rate of the mRNA [54]. Presence of sSNPs in the chromium tolerance candidate genes in the test strain could have affected folding and post-translational modifications of the nascent polypeptides which could in turn affect candidate protein expression and function towards Cr tolerance.

The polymorphism rate in 16 candidate genes that showed a high frequency of nsSNPs as compared to synonymous changes (Table 2) was ~ 16 SNPs/Kb with a frequency of ~ 11 nsSNPs/Kb. The observed high rate of nsSNPs in chromium-tolerance candidate genes of TERIBR1 as compared to the housekeeping genes (0.4 nsSNPs/kb; Table 4) could mirror environmental stress induced DNA variations and might provide an advantage in counteracting chromate stress. These included genes from mdrL/yfmO (12), recG (3) and chrE (1) families. The mdrL/yfmO genes belonged to the major facilitator superfamily (MFS), which codes for a metal ion-specific efflux protein [55]. High frequency of nsSNPs observed in the mdrL/yfmO genes in TERIBR1 could have led to altered protein structure and subsequent chromium efflux efficacy under extreme environmental condition, which we discussed in detail under the protein-ligand docking section. recG is a conserved enzyme present in bacteria, archaea, and eukaryota. recG encodes for the ATP-dependent recG DNA helicase which plays a critical role in DNA recombination and repair [56]. In vivo experiments conducted in E. coli showed that chromium salt stimulates several stress promoters associated with different types of DNA damage, indicating that DNA is one of the main targets for Cr (III) inside the cell [57]. After being internalized in cells Cr (VI) is reduced to Cr (III); recG eliminates polymerase arresting lesions (PALs), caused by Cr (III). The observed high frequency of nsSNPs in recG genes observed in our study might have resulted in higher efficiency of the enzyme to remove PAL lesions, thus mediating chromium stress tolerance in the fungal strain. In congruence, a study in Pseudomonas corrugata suggested that recG helicase played a crucial role in chromium tolerance by dismissing PAL lesions caused by Cr (VI)/Cr (III) [58]. The chrE gene encodes a rhodanese type enzyme [59]. Rhodanese protein subfamilies are suggested to be involved in different biological functions including cyanide detoxification, arsenic resistance and chromate responsive DNA-binding regulator. In addition, UniProt database defines ChrE as proteins involved in the processing of chromium-glutathione-complexes. An abundance of nsSNPs in these candidate genes for chromium tolerance could be the result of environment induced variations, perhaps for achieving functional relevance in TERIBR1. Environmentally guided changes in DNA and subsequently the proteins could be advantageous and may enable functional adaptation to extreme environmental influences [36].
Table 3

Docking analysis using PatchDock for selected proteins of A. flavus strain TERIBR1

Protein ID TERIBR1

Score

Area

ACE (kcal/mol)

g652

2764

330.5

−13.58

g9548

2496

304.5

−58.67

bg8975

2806

333.4

−29.90

g5755

2746

329.6

31.22

bg685

2576

321.4

−1.40

g641

2846

322.9

19.42

bg6212

2924

326.8

−62.95

a g9986

2644

296.6

−46.56

g9401

2594

324.6

−77.47

a g3683

2788

306.3

−30.21

g4359

2664

285.8

−60.63

a g4104

3034

335.4

−72.70

bg9525

2966

362.2

−83.82

g712

2454

299.4

−7.63

g9088

2368

258

−62.84

a g4641

2772

302.9

−66.10

aProtein - ligand interaction observed only in A. flavus strain TERIBR1

bProtein - ligand interaction observed in both the strains of A. flavus

The entries marked in bold indicate significant interaction of ligand with the protein

Table 4

SNP frequency in housekeeping genes in A. flavus

Gene ID NRRL3357

Gene ID TERIBR1

Annotation

Gene length (nucl)

change in nucl

change in aa

status of SNPs

AFL2T_10032

g899

Calmodulin

4047

0

0

0

AFL2T_10117

g962

RPL5 (ribosomal protein)

1071

0

0

0

AFL2T_03358

g2143

Polyketide Synthase Acetate

1692

0

0

0

AFL2T_03019

g2421

Chitin Synthase 1

2655

0

0

0

AFL2T_08232

g3003

cyclophilin

522

0

0

0

AFL2T_08160

g3065

Ubiquitin-conjugating enzyme

450

0

0

0

AFL2T_01340

g5399

Vacuolar protein sorting association protein

324

0

0

0

AFL2T_01191

g5533

Cytochrome oxidase

348

0

0

0

AFL2T_12005

g6415

Ubiquitin-conjugating enzyme

510

0

0

0

AFL2T_02547

g6955

Ubiquitin-conjugating enzyme

513

0

0

0

AFL2T_02762

g7132

L- Asparaginase

690

0

0

0

AFL2T_09767

g7323

ATP_D (ATP synthase subunit beta)

1821

0

0

0

AFL2T_06390

g8072

Polyketide Synthase Acetate

2529

0

0

0

AFL2T_09983

g10276

Ubiquitin-conjugating enzyme

501

0

0

0

AFL2T_09876

g10370

L- Asparaginase

1677

0

0

0

AFL2T_07389

g10698

Elongation Factor Alpha like protein

1185

0

0

0

AFL2T_06969

g3347

ATP_D (Atp synthase subunit beta)

1539

0

0

0

AFL2T_06937

g3377

Chitin Synthase 1

5283

0

0

0

AFL2T_05991

g6789

GAPDH/Glyceraldehyde 3-phosphate dehydrogenase

1524

0

0

0

AFL2T_02677

g7061

Vacuolar protein sorting association protein

1563

0

0

0

AFL2T_05240

g3927

cyclophilin

1122

0

0

0

AFL2T_02454

g5775

TBPI (tata box binding protein)

690

0

0

0

AFL2T_03769

g1786

Actin interacting protein 3

2931

0

0

0

AFL2T_05664

g6503

Histone

807

0

0

0

AFL2T_11201

g8361

Ubiquitin-conjugating enzyme

333

0

0

0

AFL2T_12447

g9127

Ubiquitin-conjugating enzyme

837

0

0

0

AFL2T_12048

g11077

DNA Topoisomerase II

1032

0

0

0

AFL2T_04711

g9681

Ubiquitin-conjugating enzyme

450

0

0

0

AFL2T_07021

g3301

Ubiquitin-conjugating enzyme

474

0

0

0

AFL2T_07052

g3271

Lactate Dehydrogenase A

1065

0

0

0

AFL2T_11998

g6422

Ubiquitin-conjugating enzyme

456

0

0

0

AFL2T_05713

g6542

Vacuolar protein sorting association protein

387

0

0

0

AFL2T_03033

g2409

Chitin Synthase 1

1671

0

0

0

AFL2T_08388

g2865

Vacuolar protein sorting association protein

2022

0

0

0

AFL2T_08078

g3130

Histone

429

0

0

0

AFL2T_05673

g6508

28 s rRNA

450

0

0

0

AFL2T_04621

g9757

cyclophilin

630

0

0

0

AFL2T_07907

g4829

Vacuolar protein sorting association protein

351

0

0

0

AFL2T_01105

g5607

Ubiquitin-conjugating enzyme

1167

0

0

0

AFL2T_09240

g6218

Ubiquitin-conjugating enzyme

558

0

0

0

AFL2T_09015

g9269

Polyketide Synthase Acetate

6828

0

0

0

AFL2T_10236

g1076

Vacuolar protein sorting association protein

2313

0

0

0

AFL2T_05795

g6613

28 s rRNA

1815

0

0

0

AFL2T_03329

g2169

Ubiquitin-conjugating enzyme

2631

0

0

0

AFL2T_09350

g6131

18 s rRNA

2382

0

0

0

AFL2T_00575

g419

Chitin Synthase 1

3588

C150T

H50H

sSNPs

AFL2T_00433

g530

Vacuolar protein sorting association protein

2562

C1483G

P496A

nsSNPs

AFL2T_02076

g8000

Elongation Factor Alpha like protein

3222

A890C

K297Q

nsSNPs

AFL2T_09781

g7310

Vacuolar protein sorting association protein

2925

T1645C

S548S

sSNPs

AFL2T_09150

g8774

Polyketide Synthase Acetate

7425

T5820C

L1938 L

sSNPs

AFL2T_06936

g3378

Chitin Synthase 1

5574

A315G, C2100T, A2841T

G105G, D700D, I947I

sSNPs

AFL2T_06204

g8236

Chitin Synthase 1

3315

C1668T

L556 L

sSNPs

AFL2T_02195

g6007

Vacuolar protein sorting association protein

4545

A2925G, C4044T

E975E, F1348F

sSNPs

AFL2T_08239

g2996

Calmodulin

5103

A260G, T2232C, C2757G

D87G, T744 T, L919 L

nsSNPs, sSNPs, sSNPs

AFL2T_07518

g5174

Polyketide Synthase Acetate

6366

G1575A, G3053A

S525 N, S1018 N

nsSNPs

AFL2T_00612

g388

ATP_D (Atp synthase subunit beta)

1671

A1515C

A505A

sSNPs

AFL2T_05167

g3861

Vacuolar protein sorting association protein

3528

G456 T, G807A

G152G, T269 T

sSNPs

AFL2T_04317

g9038

Vacuolar protein sorting association protein

1920

T1383C

I461I

sSNPs

AFL2T_12048

g6382

DNA Topoisomerase II

3183

T1871C

V624A

nsSNPs

AFL2T_12403

g9165

Polyketide Synthase Acetate

4944

T1265C, C2231T, Y2271G

M422 T, T744I, X757K

nsSNPs

AFL2T_08114

g3103

Elongation Factor Alpha like protein

1383

T273A

I91I

sSNPs

AFL2T_02416

g5810

Vacuolar protein sorting association protein

2124

C1606T

L536 L

sSNPs

AFL2T_06144

g8287

aflatoxin regulatory protein

945

C46T

L16F

nsSNPs

AFL2T_07648

g5058

Ubiquitin-conjugating enzyme

1278

T570C

G190G

sSNPs

AFL2T_03037

g2405

secretory lipase

1353

W1271A

X424N

nsSNPs

AFL2T_05603

g4255

Vacuolar protein sorting association protein

2757

C1164T, G1491 T, C1884T

I388I, T497 T, I628I

sSNPs

AFL2T_09157

g8767

Ras protein

6435

C1509T, A2193G, G2304A, T2358C, G3018C, G4056A

S503S, S731S, L768 L, N786 N, T1006 T, P1352P

sSNPs

AFL2T_12399

g9169

Chitin Synthase 1

3222

C1317G

V439 V

sSNPs

AFL2T_06989

g3329

Elongation Factor Alpha like protein

2583

T1461C

T487 T

sSNPs

AFL2T_11104

g8446

Polyketide Synthase Acetate

7482

T3962C, A5970G, A5981G

M1320 T, I1990M, D1994G

nsSNPs

AFL2T_01971

g7909

Vacuolar protein sorting association protein

5862

G281A, A2246T, A2316G, C2766T, T3135A

R94K, N749I, S772S, I922I, D1045E

nsSNPs, nsSNPs, sSNPs, sSNPs, nsSNPs

AFL2T_01302

g5433

Vacuolar protein sorting association protein

2457

C704T, T828C

A235V, G276G

nsSNPs

AFL2T_11645

g4481

ATP_D (Atp synthase subunit beta)

1116

T972C

I324I

sSNPs

AFL2T_04569

g9796

Elongation Factor Alpha like protein

2400

C546T, T1785C, T2253C

D182D, L595 L, F751F

sSNPs

AFL2T_05904

g6711

Elongation Factor Alpha like protein

2730

T146C, C1836T, G2002A, A2435G

F49S, P612P, V668I, D812G

nsSNPs, sSNPs, nsSNPs, nsSNPs

AFL2T_02030

g7958

Ubiquitin-conjugating enzyme

1176

T641C

V214A

nsSNPs

AFL2T_09952

g10303

TBPI (tata box binding protein)

1338

T789G

Y263Y

sSNPs

AFL2T_02696

g7079

Elongation Factor Alpha like protein

2169

T576C, A825T, G1332A, T1557C

D192D, I275I, E444E, F519F

sSNPs

AFL2T_12346

g8605

Elongation Factor Alpha like protein

2874

A1914G

E638E

sSNPs

AFL2T_10814

g1537

Ubiquitin-conjugating enzyme

708

C507T

D169D

sSNPs

AFL2T_07094

g3237

Polyketide Synthase Acetate

6606

T3478A, T4780C, G4927A, A5446G, G5677A, T5862C,T6264C

C1160S, Y1594H, E1643K, N1816D, A1893T, S1954S, C2088C

nsSNPs, nsSNPs, nsSNPs, nsSNPs, nsSNPs, sSNPs, sSNPs

AFL2T_02027

g7956

Vacuolar protein sorting association protein

1044

T663C

Y221Y

sSNPs

AFL2T_06635

g3639

L- Asparaginase

1074

A257G, C663A

D86G, N221 K

nsSNPs

AFL2T_09646

g7430

Ubiquitin-conjugating enzyme

921

T6C, G36C

S2S, A12A

sSNPs

AFL2T_01296

g5440

Vacuolar protein sorting association protein

876

C93T, G369A

T31 T, L123 L

sSNPs

AFL2T_05777

g6597

Vacuolar protein sorting association protein

2058

T538C, G1317A, G1438A, G1938C

Y180H, S439S, E480K, K646 N

nsSNPs, sSNPs, nsSNPs, nsSNPs

AFL2T_08606

g2683

Chitin Synthase 1

5172

G3339A, G3618A, A3831G, G4764C, G4952A

T1113 T, L1206 L, L1277 L, P1588P, R1651Q

sSNPs, sSNPs, sSNPs, sSNPs, nsSNPs

AFL2T_09101

g9340

Elongation Factor Alpha like protein

2859

C1173T, G1275A, T1895C, G1947A, A2172G, C2670T

D391D, L425 L, V632A, R649R, V724 V

sSNPs, sSNPs, nsSNPs, sSNPs, sSNPs

AFL2T_08131

g3088

cyclophilin

486

C158T

A53V

nsSNPs

AFL2T_00781

g238

Polyketide Synthase Acetate

6951

G2689A, C3072T, A3121G, A3864G

V897I, F1024F, F1041A, K1288 K

nsSNPs, sSNPs, nsSNPs, nsSNPs

AFL2T_01027

g12

Vacuolar protein sorting association protein

732

K401C

X134A

nsSNPs

AFL2T_00198

g739

Ubiquitin-conjugating enzyme

3240

C849A, T852A, G1475C, T1905C, A2459G, G2659A

F283 L, I284I, R492P, G635G, N820S, A887T

nsSNPs, sSNPs, nsSNPs, sSNPs, nsSNPs, nsSNPs

AFL2T_11313

g4750

aflatoxin regulatory protein

1164

T208C, C889A, G922A

S70P, E297E, G308R

nsSNPs, sSNPs, nsSNPs

AFL2T_08488

g2771

Elongation Factor Alpha like protein

3249

G1398A, A1683A, G2161A, G2328A

E466E, V561 V, A721T, Q776Q

sSNPs, sSNPs, nsSNPs, sSNPs

AFL2T_07094

g10842

Polyketide Synthase Acetate

1455

G526A, T711C, T1113C, A295G

A176T, S237S, L371 L

nsSNPs, sSNPs, sSNPs

AFL2T_06011

g6804

Ubiquitin-conjugating enzyme

504

A210G

P70P

sSNPs

AFL2T_01283

g5448

Chitin Synthase 1

2589

T1072C, A1536G

N358 N, K512 K

sSNPs

AFL2T_02416

g10910

Vacuolar protein sorting association protein

370

A55T

L18 L

sSNPs

AFL2T_05917

g6723

Ubiquitin-conjugating enzyme

741

A567G

K189 K

sSNPs

AFL2T_11034

g8506

GAPDH/Glyceraldehyde 3-phosphate dehydrogenase

1077

C237T, C357A

H79H, G119G

sSNPs

AFL2T_02787

g7154

Cytochrome oxidase

1482

A849G, C857T, A1003T,

E283E, T286I, T335F

sSNPs, nsSNPs, nsSNPs

AFL2T_03260

g2222

secretory lipase

1365

C936T, G985A, T990C, G1286A, T1291C

N312 N, G329R, T330 T, G429D, L431 L

sSNPs, nsSNPs, sSNPs, nsSNPs, sSNPs

AFL2T_07361

g10719

Lactate Dehydrogenase A

933

G702C, C753T, G879A

G234G, F251F, V293 V

sSNPs

AFL2T_09556

g7507

Ras protein

1458

C565T, G681A, T771C, T1047A

L189 L, T227 T, T257 T, P349P

sSNPs

AFL2T_03516

g2002

Vacuolar protein sorting association protein

2853

A1176C, C1180T

G392G, L394 L

sSNPs

AFL2T_04629

g9750

Elongation Factor Alpha like protein

1443

T475G, C543T, G1185C, T1302C

T181 T, V395 V, A434A

sSNPs

AFL2T_01738

g8814

cyclophilin

1638

A501C, A513G, A522G, A624G, T1011C, A1043G, T1176C

V167 V, E171E, V174 V, E208E, A337A, K348R, L392 L

sSNPs, sSNPs, sSNPs, sSNPs, sSNPs, nsSNPs, sSNPs

AFL2T_04801

g9604

Cytochrome oxidase

555

T207A, T463G

G69G, F155C

sSNPs, nsSNPs

AFL2T_12397

g9171

Vacuolar protein sorting association protein

1758

T1659C

G553G

sSNPs

AFL2T_08911

g9862

Polyketide Synthase Acetate

7170

T3097C, A3519C, G3689A, A3761T

W1033R, T1173 T, R1230Q, Y1254F

nsSNPs, sSNPs, nsSNPs, nsSNPs

AFL2T_00897

g134

cyclophilin

1893

G616 T, C855T, T1191C, A1222G

V206 L, F285F, Y397Y, T408A

nsSNPs, sSNPs, sSNPs, nsSNPs

AFL2T_04106

g10177

cyclophilin

642

A72T

T24 T

sSNPs

AFL2T_06925

g3387

Cytochrome oxidase

348

C63A

V21 V

sSNPs

AFL2T_07038

g3286

Chitin Synthase 1

2076

G1794A

T598 T

sSNPs

AFL2T_08473

g2782

cyclophilin

498

C320G

T107 T

sSNPs

AFL2T_01646

g2579

secretory lipase

909

C10T, T309C, G509C, C646T

L4L, H103H, R170P, L216 L

sSNPs, sSNPs, nsSNPs, sSNPs

AFL2T_03998

g10190

Histone

768

C96T, A255G, C391T

F32F, S85S, P131S

sSNPs, sSNPs, nsSNPs

AFL2T_07224

g5682

aflatoxin regulatory protein

1218

C318G, G408C, G552 T, C581T, A794G, A979G, G1075A, C1137T

T106 T, P136P, S184S, A194V, Y265C, S327G, V359 M, S379S

sSNPs, sSNPs, sSNPs, nsSNPs, nsSNPs, nsSNPs, nsSNPs, sSNPs

AFL2T_00797

g223

L- Asparaginase

1137

T426C, T693C, G831C, C855T, T858C

G142G, G231G, Q277H, I285I, D286D

sSNPs, sSNPs, nsSNPs, sSNPs, sSNPs

AFL2T_08030

g3169

secretory lipase

1269

A642G, A795G, T903C, A904G, A913G, T927C, T933C, T963C, C1140T

A214A, L265 L, Y301Y, N302D, I305V, D309D, F311F, N321 N, G380G

sSNPs, sSNPs, sSNPs, sSNPs, nsSNPs, sSNPs, sSNPs, sSNPs, sSNPs

AFL2T_08467

g2788

cyclophilin

1641

T83C, C408A, G610A, G655A, T666C, C690T, T750A, A789G

V28A, L136 L, A204T, A219T, F222F, Y230Y, T250 T, E263E

nsSNPs, sSNPs, nsSNPs, nsSNPs, sSNPs, sSNPs, sSNPs, sSNPs

AFL2T_04948

g9453

Polyketide Synthase Acetate

1977

C1314G, T1444C, G1519A, A1590G, C1767A, C1854T, G1962A

R438R, W482R, V507I, L530 L, I589I, N618 N, R654R

sSNPs, nsSNPs, nsSNPs, sSNPs, sSNPs, sSNPs, sSNPs

AFL2T_07791

g4925

Vacuolar protein sorting association protein

3813

G39A, C213G, G234A, A291G, C354T

L13 L, S71S, Q78Q, E97E, H118H

sSNPs

AFL2T_12205

g8728

secretory lipase

939

T25C, G182A, T380C, C435T, T699C, T714G, G768A, G828A

L8L, S61 N, I127T, S145S, I233I, L238 L, P256P, A276A

sSNPs, nsSNPs, nsSNPs, sSNPs, sSNPs, sSNPs, sSNPs, sSNPs

AFL2T_01987

g7921

cyclophilin

537

A504G

,K168 K

sSNPs

AFL2T_05263

g3947

Vacuolar protein sorting association protein

891

G301A, G401A, C558T, C654T, T749G, A750G, A775G

A101T, G134D, D186D, I218I, I250R, I250R, M259 V

nsSNPs, nsSNPs, sSNPs, sSNPs, nsSNPs, nsSNPs, nsSNPs

AFL2T_01745

g8808

GAPDH/Glyceraldehyde 3-phosphate dehydrogenase

1041

C192G, T222C, C345T, C348T, C393T, T474C

D64E, I74I,G115G, A116A, F113F, A158A

nsSNPs, sSNPs, sSNPs, sSNPs, sSNPs, sSNPs

AFL2T_04609

g9767

RPL5 (ribosomal protein)

531

C153T

Y51Y

sSNPs

Frequency of SNPs = 0.9 SNPs/kb

Frequency of sSNPs = 0.7 SNPs/kb

Frequency of nsSNP = 0.4 SNPs/kb

Several studies have shown that non-synonymous substitutions are likely to affect protein structure [60]. Mapping of nsSNPs to a known 3D structure reveals whether the replacement is likely to destroy the hydrophobic property of a protein, electrostatic interactions or interactions with ligands. Many nsSNPs have been found near or inside the protein-protein interaction interfaces that alter the protein function [61]. Sequence-based structure predictions help in identifying the positions of a protein that are located in the active site. Protein – ligand docking analysis further helps in identifying crucial amino-acids that are involved in ligand binding.

Non-synonymous mutations mediated change in free energy (ΔG) and concomitant bioactive conformation of four proteins (g9986, g3683, g4104, g4641) belonging to the MFS and recG helicase super families were noteworthy. A decrease in free energy and atomic contact energy (ACE) putatively resulted in target-ligand interaction with a significant PatchDock score in the case of the proteins coded by the chromium tolerant strain, TERIBR1 (Table 2); whereas no ligand interaction was observed in the corresponding proteins coded by reference strain. Figure 2 shows the results of the molecular docking studies of the four proteins (g9986, g4104, g4641, g3683) coded by TERIBR1 strain. Ligand binding free energy estimates (ACE) indicated a significant decrease in free energy of these proteins (Table 3). The nsSNPs in the candidate genes of the chromium tolerant A. flavus strain TERIBR1 seemed to have influenced protein structure that could have mediated protein and chromium interaction. However, not much overlapping between the predicted binding sites (by 3DLigandSite) and the ligand docking position was observed for these proteins. The multidrug transporters of the MFS superfamily are polyspecific and can extrude a remarkably diverse range of substrates. However, discussions pertaining to multi-substrate recognition and transport by members of the MFS are still open and it is not clear if the same amino acid residues are involved in substrate recognition and binding in varying conformations of the protein [62]. Biochemical studies on the Escherichia coli MFS drug/H+ antiporter concluded that the structural basis of substrate promiscuity is governed by a large, flexible and complex substrate recognition cavity within the protein, which enables different substrates to interact with different amino acid residues of the cavity, and to form different interactions with MFS transporter [63, 64]. The putative correlation between the influence of genetic polymorphisms on the structure and function of MFS transporters and chromium tolerance in A. flavus suggested the importance of efflux mechanism in microbial chromium tolerance. Our results supported previous reports of heavy metal efflux as one of the primary mechanisms of tolerance in microbial systems [65, 66]. Furthermore, ligand docking was observed in four proteins (g8975, g685, g6212, g9525) and their homologs coded by the test and the reference strains respectively. The non-synonymous amino acid changes in these cases seemed to have no influence on protein-ligand interaction.

In a recent study four populations of yeast, exposed to arsenic in its most toxic form, As (III), accumulated changes in DNA, adapted faster and went from poor to optimal performance for fitness components (length of lag phase, population doubling time and efficiency of growth) within just a few mitotic divisions. The study concluded that fitness component enhancements in yeast populations were adaptive responses to arsenic and not to other selective pressures [35]. The observed high rate of variations in the DNA of A. flavus strain TERIBR1 in our study, especially nsSNP polymorphisms, highlights the scope for additional research on genetic mechanisms operating in A. flavus in order to conclude on the role of stress mediated alterations in DNA on adaptation in micro-organisms.

Conclusions

Changes in DNA, guided by extreme environmental conditions, could influence the structure of proteins important in chromium stress tolerance in Aspergillus flavus. The structural changes in transporter proteins and enzymes are expected to have potential influence on their functional efficacy. Our study provided insights into the genetic factors governing heavy metal tolerance, which may aid in the development of future heavy metal bio-remediation technologies. Further, to ensure that the genes presenting nsSNPs are involved in the tolerance to chromium of the TERIBR1 strain, the results obtained in the present study demand cross validation by a proteome analysis.

Abbreviations

ACE: 

Atomic Contact Energy

BacMetdbs: 

Antibacterial Biocide & Metal Resistance Genes Database

CHR: 

Chromate Transport Protein

MFS: 

Major Facilitator Superfamily

NrBlast: 

Non Redundant Basic Local Alignment Search Tool

nsSNPs: 

Non Synonymous Single Nucleotide Polymorphisms

Phyre2: 

Protein Homology/AnalogY Recognition server

RCSB PDB: 

Research Collaboratory for Structural Bioinformatics Protein Data Bank

sSNPs: 

Synonymous Single Nucleotide Polymorphisms

Declarations

Acknowledgements

The authors are thankful to the TERI-Deakin Nanobiotechnology Research Centre, India for providing necessary infrastructure to carry out the required research work.

Funding

The manuscript consists of research work carried out in-house at the TERI-Deakin Nanobiotechnology Research Centre, India and was not supported by a particular funding source.

Availability of data and materials

The whole genome project has been deposited at https://submit.ncbi.nlm.nih.gov/subs/wgs/under Bioproject PRJNA362980.

Authors’ contributions

All authors have read and approved the final manuscript. AJ was involved in bio-informatics and proteomics data analyses, data compilation and manuscript writing. DV supported genomics data analysis. AA isolated the A. flavus strain TERIBR1 and supervised wet lab assays for chromium resistance. PP was the coordinator of the project, involved in conceptualization of the project, study design, data analyses, data compilation, manuscript writing, critical inputs and finalization of the manuscript.

Ethics approval and consent to participate

Not Applicable.

Consent for publication

Not Applicable.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
TERI-Deakin Nanobiotechnology Centre, TERI Gram, The Energy and Resources Institute, Gual Pahari, Gurgaon Faridabad Road, Gurgaon, Haryana, 122 001, India

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