BioMed Research International
Volume 2017 (2017), Article ID 7039245, 14 pages
https://doi.org/10.1155/2017/7039245

Research Article

Mining of Microbial Genomes for the Novel Sources of Nitrilases

Nikhil Sharma,¹ Neerja Thakur,² Tilak Raj,¹ Savitri,² and Tek Chand Bhalla²

¹Sub-Distributed Information Centre, Himachal Pradesh University, Summer Hill, Shimla 171005, India
²Department of Biotechnology, Himachal Pradesh University, Summer Hill, Shimla 171005, India

Correspondence should be addressed to Tek Chand Bhalla; bhallatc@rediffmail.com

Received 25 October 2016; Revised 14 February 2017; Accepted 7 March 2017; Published 12 April 2017

Academic Editor: Jiangke Yang

Copyright © 2017 Nikhil Sharma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Next-generation DNA sequencing (NGS) has made it feasible to sequence large number of microbial genomes and advancements in computational biology have opened enormous opportunities to mine genome sequence data for novel genes and enzymes or their sources. In the present communication in silico mining of microbial genomes has been carried out to find novel sources of nitrilases. The sequences selected were analyzed for homology and considered for designing motifs. The manually designed motifs based on amino acid sequences of nitrilases were used to screen 2000 microbial genomes (translated to proteomes). This resulted in identification of one hundred thirty-eight putative/hypothetical sequences which could potentially code for nitrilase activity. In vitro validation of nine predicted sources of nitrilases was done for nitrile/cyanide hydrolyzing activity. Out of nine predicted nitrilases, Gluconacetobacter diazotrophicus, Sphingopyxis alaskensis, Saccharomonospora viridis, and Shimwellia blattae were specific for aliphatic nitriles, whereas nitrilases from Geodermatophilus obscurus, Nocardiopsis dassonvillei, Runella slithyformis, and Streptomyces albus possessed activity for aromatic nitriles. Flavobacterium indicum was specific towards potassium cyanide (KCN) which revealed the presence of nitrilase homolog, that is, cyanide dihydratase with no activity for either aliphatic, aromatic, or aryl nitriles. The present study reports the novel sources of nitrilases and cyanide dihydratase which were not reported hitherto by in silico or in vitro studies.

1. Introduction

Advancement in the DNA sequencing technologies has led to sequencing of large number of genomes and the enormous sequence data are available in the public domain. The fourth-generation DNA sequencing has made it possible to sequence a bacterial genome within a few hours at a reasonably low cost [1–4]. As of today 5293 prokaryotic and 22 eukaryotic genomes have been completely sequenced and the sequence data are easily accessible in databases such as NCBI, GOLD, and IMG/ER. It is evident from previous studies that not all the gene/protein sequences in the databases are functionally characterized, which make these repositories a rich source for the discovery of novel genes and proteins [5, 6]. Genome mining has emerged as an alternate approach to find novel sources of desired genes/proteins as the conventional screening methods which involve isolation of microbes and their screening for desired products are time consuming, tedious, and cost intensive [7, 8].

Microbial nitrilases are considered to be the most important enzymes in the nitrilase superfamily that find application in the synthesis of fine chemicals, production of some important acids, and drug intermediates and in green chemistry [9–13]. Besides their wide applications nitrilases are prone to certain limitations, for example, their inactivation or inhibition by the acidic product, extremes of pH, temperature, and organic solvent [14, 15]. These limitations are being addressed either by the isolation of microorganisms from the extreme habitat or by enrichment techniques for specific substrate using conventional microbiological procedures [6] prone to limitation as mentioned above. The present communication focuses on in silico screening of publicly available bacterial genomes for nitrilase genes and in vitro validation of the predicted novel sources of nitrilases.

2. Material and Methods

2.1. Genome Screening Using Homology and Motif Based Approach

Primary screening of microbial genomes (data given as supplementary material in Supplementary Material available online at https://doi.org/10.1155/2017/7039245) was done using homology based approach. Tblastn and blastp were used to screen the sequenced genomes with query sequence to identify the presence and position of similar genes in the genome. Computationally predicted proteins from the bacterial genomes with keyword “nitrilase/cyanide dihydratase” were also downloaded using advanced search options in the IMG/ER database. Sequences with low (30%) and high similarity (80%) were discarded. Nitrilase gene in contigs showing the presence of nitrilase homologs was downloaded from IMG/ER. GenMark S tool was used to predict the ORFs in each contig, and the output was downloaded selecting protein sequence as output option. Amino acid sequences less than 100 amino acids were considered to be as false positive (FP) and were discarded. Small amino acid sequence database was created which was further subjected to local blast, to confirm the presence of nitrilase homolog in the contigs of the individual genome.

On the other hand, protein based manually designed motifs (MDMs) were used to screen the bacterial genome to search for the presence of conserved motifs using MAST (Motif Alignment and Search Tool) at MEME (Multiple Em for Motif Elicitation) suite. The motifs used are already described in our previous communication [12]. Motifs identified in sequences less than hundred amino acids were rejected, considered to be false positive (FP). Sequences above 100 amino acids were taken to be as true positive (TP).

2.2. Study of Physiochemical Properties and Phylogenetic Analysis of Predicted Nitrilases

Physiochemical data of the in silico predicted nitrilases were generated from the ProtParam software using ExPASy server and compared to the values deduced from the previous nitrilase study [16]. Some important physiochemical properties such as number of amino acids, molecular weight (kda), isoelectric point (pI), computing pI/Mw and the atomic compositions, values of instability index, aliphatic index, and grand average of hydropathicity (GRAVY) were calculated. A comparative chart was drawn between previously characterized and predicted nitrilases.

An output file of multiple aligned sequences using Clustal W for both previously characterized and predicted nitrilases was used to generate the Neighbor Joining (NJ) tree using MEGA 6 version. Phylogenetic tree was generated in order to predict the sequences as aliphatic or aromatic with previously characterized nitrilases.

2.3. Nitrilase Activity Assay

Culture of some of the bacteria predicted to have nitrilase gene (Shimwellia blattae, Runella slithyformis, Geodermatophilus obscurus, Nocardiopsis dassonvillei, Streptomyces albus, Flavobacterium indicum, Saccharomonospora viridis, Sphingopyxis alaskensis, and Gluconacetobacter diazotrophicus) was procured from Microbial Type Culture Collection (MTCC); Chandigarh Escherichia coli BL21 (DE3) from Invitrogen was used as negative control as this organism does not have nitrilase gene. These cultures were grown in the laboratory using different media (Table 1) for the production of nitrilase activity following the procedures described earlier [17–19]. Nitrilase activity was assayed in 1.0 mL reaction mixture containing nitrile as substrate (1–10 mM) and 0.1 mL resting cells. After 30 min of incubation at 30°C the reaction was quenched with 0.1 M HCl and the amount of ammonia released was estimated using nitrilase assay, that is, modified phenate-hypochlorite method described by Dennett and Blamey [20]. One unit of nitrilase activity was defined as the amount of enzyme required to release 1 μmole of ammonia per min under the assay conditions.

Table 1: Composition of various media used to cultivate procured strains for nitrilase production.

Name of the organism
MTCC number
Composition ()
pH
Growth temperature

Shimwellia blattae 
ATCC 29907
4155
Beef extract: 1.0 g
Yeast extract: 2.0 g
Peptone: 5.0 g
NaCl: 5.0 g
Agar: 15.0 g
7.0–7.5
37°C

Runella slithyformis 
ATCC 29530
9504
Glucose: 1.0 g
Peptone: 1.0 g
Yeast extract: 1.0 g
Agar: 15.0 g
Glucose: 4.0 g
7.0–7.5
26°C

Geodermatophilus obscurus 
DSM 43160
4040
Yeast extract: 4.0 g
Malt extract: 10.0 g
CaCO₃: 2.0 g
Agar: 12.0 g
7.2–7.5
28°C

Nocardiopsis dassonvillei 
DSM 43111
1411
Yeast extract: 4.0 g
Malt extract: 1.0
Glucose: 4.0 g
Agar: 20.0 g
7.2–7.4
28°C

Streptomyces albus 
J1074
1138
Yeast extract: 4.0 g
Malt extract: 1.0 g
Glucose: 4.0 g
Agar: 20.0 g
7.2–7.4
25°C

Flavobacterium indicum 
DSM 17447
6936
Tryptic soy broth with agar
(TSBA-100)
7.3–7.5
30°C

Saccharomonospora viridis 
ATCC 15386
320
Yeast extract: 4.0 g
Malt extract: 1.0 g
Glucose: 4.0 g
Agar: 20.0 g
7.2–7.4
45°C

Sphingopyxis alaskensis 
DSM 13593
7504
Beef extract: 1.0 g
Yeast extract: 2.0 g
Peptone: 5.0 g
NaCl: 5.0 g
Agar: 15.0 g
7.0–7.5
30°C

Gluconacetobacter diazotrophicus 
ATCC 49037
1224
Yeast extract: 5.0 g
Peptone: 3.0 g
Mannitol: 25.0 g
Agar: 15.0 g
7.0–7.3
28°C

Escherichia coli 
BL21 (DE3)
—
Yeast extract: 5.0 g
NaCl: 10.0 g 
Casein enzymatic hydrolysate: 10.0 g
7.0–7.5
37°C

Negative control.

3. Results

3.1. Genome Screening Using Conserved Motifs and Homology Search

As many as 138 candidate sequences were identified using tblastn and blastp at IMG/ER on both gene and protein level. Identification of potentially coding nitrilase genes was done using homology based approach (blastp and tblastn) allowing the identification of nitrilase sequences. To identify newer sources of nitrilases, candidate sequences bearing unassigned functions (hypothetical, uncharacterized, or putative) were selected from the translated genomes (Table 2). The identified sequences shared 30–50% sequence identity to biochemically characterized Rhodococcus rhodochrous J1 nitrilase which was taken as query sequence. Catalytic residues were found to be conserved in all the predicted proteins. Nine predicted and translated sequences were further chosen for their in silico and in vitro validation based on the manually designed motifs (MDMs) (Tables 3 and 4) identified from previous study [12].

Table 2: Prediction of ORFs length in the individual scaffold for prediction of coding sequence for nitrilase using IMG/ER.

Name of organism
Scaffold or genome length (bp) with accession number
Total number of ORF’s predicted in scaffold of complete genome
Predicted coding region for nitrilase
Number of
base-pairs

Acaryochloris marina 
MBIC11017
NC_009925
(6503724 bp)
152
200001–200999
999

Acetobacter pasteurianus 
IFO 3283-32
AP011157
(191443 bp)
120
174107–173133
974

Achromobacter xylosoxidans 
A8
NC_014640
(7013095 bp)
406
200001–200960
960

Acidovorax avenae avenae 
ATCC 19860
NC_015138
(5482170 bp)
188
201035–200001
1035

Acidothermus cellulolyticus 
11B
NC_008578
(2443540 bp)
403
200001–201131
1131

Acidaminococcus fermentans 
VR4
NC_013740
(2329769 bp)
293
200924–200001
924

Alcanivorax dieselolei 
B5
CP003466
(4928223 bp)
343
200001–200981
981

Arthrobacter aurescens 
TC1
NC_008711
(4597686 bp)
385
200001–200930
930

Azorhizobium caulinodans 
ORS 571
NC_009937
(5369772 bp)
262
89665–88580
1083

Azospirillum sp.
B510
NC_013854
(3311395 bp)
402
200001–200921
921

Bacillus pumilus 
SAFR-032
NC_009848
(3704465 bp)
73
201026–200001
1026

Bradyrhizobium japonicum 
USDA 110
NC_004463
(9105828 bp)
387
200001–200966
966

Bradyrhizobium sp.  
BTAi1
NC_009485
(8264687 bp)
392
201146–200001
1146

Bradyrhizobium sp.  
ORS278
NC_009445
(7456587 bp)
395
201041–200001
1041

Brevibacillus brevis 
NBRC 100599
NC_012491
(6296436 bp)
182
200001–200960
960

Flavobacterium indicum 
GPTSA100-9
HE774682
(2993089 bp)
317
200001–200981
981

Saccharomonospora viridis 
P101
NC_013159
(4308349 bp)
315
200001–200996
996

Sphingopyxis alaskensis 
DSM13593
NC_008048
(3345170 bp)
387
200001–201017
1017

Burkholderia cenocepacia 
J2315
NC_011000
(3870082 bp)
393
199944–201050
1050

Burkholderia glumae 
BGR1
NC_012720
(141067 bp)
154
47491–48477
1017

Burkholderia gladioli 
BSR3
NC_015376
(3700833 bp)
338
200001–201014
1014

Burkholderia phymatum
NC_010623
(2697374 bp)
375
199971–201023
1023

Burkholderia phytofirmans
NC_010681
(4467537 bp)
357
200001–201035
1035

Burkholderia sp.  
CCGE1002
NC_014119
(1282816 bp)
280
72013–73041
1020

Burkholderia sp.  
CCGE1003
NC_014540
(2966498 bp)
344
200019–201041
1022

Burkholderia vietnamiensis G4
NC_009254
(1241007 bp)
436
199986–201023
1037

Burkholderia xenovorans 
LB400
NC_007951
(4895836 bp)
396
200001–200996
996

Caulobacter sp. K31
NC_010335
(233649 bp)
219
180936–181871
935

Chlorobium phaeobacteroides 
BS1
NC_010831
(2736403 bp)
382
200001–200936
936

Clostridium difficile 630
NC_009089
(4290252 bp)
364
200001–200927
927

Clostridium difficile 
CD196
NC_013315
(4110554 bp)
308
200001–200927
927

Clostridium difficile 
R20291
NC_013316
(4191339 bp)
329
200001–200927
927

Clostridium kluyveri 
NBRC 12016
NC_011837
(3896121 bp)
442
200001–200930
957

Clostridium kluyveri 
ATCC 8527
NC_009706
(3964618 bp)
491
200001–200930
930

Conexibacter woesei 
DSM 14684
NC_013739
(6359369 bp)
388
200001–200942
942

Cupriavidus necator 
ATCC 17699
NC_008313
(4052032 bp)
318
200001–201017
1017

Cupriavidus necator 
ATCC 43291
NC_015726
(3872936 bp)
318
200001–201017
1017

Cyanobium gracile 
ATCC 27147
Cyagr_Contig81
(3342364 bp)
405
200001–200999
999

Deinococcus deserti 
(strain VCD115)
NC_012529
(314317 bp)
269
200001–200951
951

Deinococcus peraridilitoris 
DSM 19664
Deipe_Contig72.1
(3881839 bp)
412
200001–200951
951

Desulfomonile tiedjei 
ATCC 49306
Desti_Contig107.1
(6500104 bp)
379
200001–201029
1029

Dickeya zeae Ech1591
NC_012912
(4813854 bp)
194
200001–200927
927

Erwinia billingiae Eb661
NC_014305
(169778 bp)
194
87964–88965
1001

Erythrobacter litoralis 
HTCC2594
NC_007722
(3052398 bp)
411
200001–200969
969

Flavobacterium indicum 
DSM 17447
HE774682
(2993089 bp)
317
200001–200981
981

Frateuria aurantia 
ATCC 33424
Fraau_Contig24.1
(3603458 bp)
366
200001–200924
924

Geobacillus sp.  
Y4.1MC1
NC_014650
(3840330 bp)
434
200001–200966
966

Geobacillus thermoglucosidasius 
C56-YS93
NC_015660
(3893306 bp)
446
200001–200966
966

Geodermatophilus obscurus 
DSM 43160
NC_013757
(5322497 bp)
244
54102–54884
783

Gluconacetobacter diazotrophicus 
ATCC 49037
NC_010125
(3944163 bp)
333
200001–200960
960

Haliangium ochraceum 
DSM 14365
CP002175
(2309262 bp)
377
200001–200957
957

Halanaerobium praevalens 
ATCC 33744
NC_013440
(9446314 bp)
262
200001–200999
999

Hyphomicrobium sp.  
MC1
NC_015717
(4757528 bp)
392
200001–200984
984

Janthinobacterium sp.  
Marseille
NC_009659
(4110251 bp)
398
200001–201068
1068

Jannaschia sp.  
CCS1
NC_007802
(4317977 bp)
382
200001–201026
1026

Maricaulis maris 
MCS10
NC_008347
(3368780 bp)
392
200001–200933
933

Methylobacterium extorquens CM4
NC_011758
(380207 bp)
211
7191–8267
1077

Methylobacterium extorquens 
ATCC 14718
NC_012811
(1261460 bp)
436
200001–201077
1077

Methylobacterium extorquens DM4
NC_012988
(5943768 bp)
378
200001–200918
918

Methylobacterium extorquens PA1
NC_010172
(5471154 bp)
354
200001–201110
1110

Methylomonas methanica 
MC09
Contig38
(5051681 bp)
402
200001–200996
996

Methylobacterium nodulans ORS2060
NC_011892
(487734 bp)
425
200001–201116
1116

Methylobacterium populi 
ATCC BAA-705
NC_010725
(5800441 bp)
193
61617–62693
1077

Methylibium petroleiphilum PM1
NC_008825
(4044195 bp)
364
200001–201074
1074

Methylobacterium radiotolerans 
ATCC 27329
NC_010505
(6077833 bp)
377
200001–201077
1077

Methylocella silvestris 
BL2
NC_011666
(4305430 bp)
439
199971–201029
1029

Mycobacterium intracellulare 
ATCC 13950
CP003322
(5402402 bp)
383
199938–200897
897

Mycobacterium liflandii 
128FXT
CP003899
(6208955 bp)
405
200001–201059
1059

Mycobacterium rhodesiae NBB3
MycrhN_Contig54.1
(6415739 bp)
267
200001–200957
957

Mycobacterium smegmatis 
ATCC 700084
CP001663
(6988208 bp)
377
200001–200978
978

Natranaerobius thermophilus 
ATCC BAA-1301
NC_010718
(3165557 bp)
387
200001–200930
930

Nocardia farcinica 
IFM 10152
NC_006361
(6021225 bp)
390
198993–199811
818

Nocardiopsis dassonvillei 
DSM 43111
NC_014211
(775354 bp)
353
201134–200001
843

Oligotropha carboxidovorans 
ATCC 49405
CP002826
(3595748 bp)
372
200001–201065
1065

Pantoea sp. At-9b
NC_014839
(394054 bp)
349
114577–115581
1005

Peptoniphilus duerdenii 
ATCC BAA-1640
NZ_AEEH01000050
(96694 bp)
80
52942–53863
921

Photorhabdus asymbiotica 
ATCC 43949
NC_012962
(5064808 bp)
338
200001–201050
1050

Pirellula staleyi 
ATCC 27377
NC_013720
(6196199 bp)
338
200001–200909
909

Polaromonas naphthalenivorans 
CJ2
NC_008781
(4410291 bp)
389
200001–201041
1062

Polaromonas sp. JS666
NC_007948
(5200264 bp)
398
200001–200942
942

Pseudomonas syringae pv. lachrymans 
M302278PT
Lac106_115287.20
(115287 bp)
107
47704–48747
1043

Pseudoalteromonas atlantica 
ATCC BAA-1087
NC_008228
(5187005 bp)
397
200001–200921
921

Pseudomonas aeruginosa 
P7-L633/96
Ga0060317_132
(369634 bp)
270
91986–92801
816

Pseudomonas brassicacearum 
NFM421
NC_015379
(6843248 bp)
377
200001–201026
1026

Pseudomonas sp. TJI-51
AEWE01000051
(6502 bp)
05
1482–2498
1017

Pseudomonas fluorescens 
Pf-5
NC_007492
(6438405 bp)
349
200001–200924
924

Pseudomonas fluorescens 
SBW25
NC_012660
(6722539 bp)
376
200043–200930
888

Pseudomonas mendocina 
NK-01
NC_015410
(5434353 bp)
376
200001–200883
883

Pseudomonas syringae 
pv. tomato DC 3000
PSPTOimg_DC3000
(6397126 bp)
377
200001–201011
1011

Pseudomonas syringae 
pv. syringae B728a
NC_007005
(6093698 bp)
196
8233–9231
999

Pseudoxanthomonas suwonensis11-1
NC_014924
(3419049 bp)
362
200001–200885
885

Pseudonocardia dioxanivorans 
ATCC 55486
CP002593
(7096571 bp)
386
200001–201008
1008

Ralstonia solanacearum 
GMI1000
NC_003295
(3716413 bp)
343
200001–201032
1032

Rhizobium hainanense 
CCBAU 57015
Ga0061100_113
(148344 bp)
146
61240–62280
1040

Rhizobium leguminosarum bv. Viciae 3841
NC_008380
(5057142 bp)
397
200001–201047
1047

Rhizobium leguminosarum bv. trifolii 
WSM1325
NC_012850
(4767043 bp)
210
18450–19442
993

Rhodopseudomonaspalustris 
TIE-1
NC_011004
(5744041 bp)
387
199980–201050
1070

Rhodopseudomonas palustris 
DX-1
NC_014834
(5404117 bp)
390
200001–200954
954

Rubrobacter xylanophilus 
DSM 9941
NC_008148
(3225748 bp)
385
200001–201080
1080

Ruegeria pomeroyi 
ATCC 700808
NC_006569
(491611 bp)
308
118859–119893
1035

Runella slithyformis 
ATCC 29530
Unknown
(6568739 bp)
362
200001–200933
933

Saccharothrix espanaensis 
ATCC 51144
HE804045
(9360653 bp)
347
200001–201020
1020

Saccharomonospora viridis ATCC 15386
NC_013159
(4308349 bp)
315
200001–200996
996

Shewanella halifaxensis 
HAW-EB4
NC_010334
(5226917 bp)
337
200001–200945
945

Shewanella pealeana 
ATCC 700345
NC_009901
(5174581 bp)
333
200001–200945
945

Shewanella sediminis 
HAW-EB3
NC_009831
(5517674 bp)
337
200001–200954
954

Shewanella violacea 
JCM 1017
NC_014012
(4962103 bp)
307
200001–200936
936

Shewanella woodyi 
ATCC 51908
NC_010506
(5935403 bp)
327
200001–201005
1005

Shimwellia blattae 
ATCC 29907
EBLc (4158725 bp)
376
200001–201029
1029

Singulisphaera acidiphila 
ATCC 1392
Sinac_Contig49.1
(9629675 bp)
337
200001–201014
1014

Sorangium cellulosum Soce56
NC_010162
(13033779 bp)
329
200001–201029
1029

Sphingopyxis alaskensis 
DSM 13593
NC_008048
(3345170 bp)
387
200001–201017
1016

Sphaerobacter thermophilus 
DSM 20745
NC_013524
(1252731 bp)
335
200097–201092
995

Sphingomonas wittichii 
RW1
NC_009511
(5382261 bp)
354
200001–201026
1026

Spirosoma linguale 
ATCC 33905
NC_013730
(8078757 bp)
339
200001–200906
906

Starkeya novella 
ATCC 8093
NC_007604
(2695903 bp)
402
200001–201005
1005

Streptomyces albus J1074
CP004370
(6841649 bp)
252
1635309–1636256
948

Synechococcus elongatus 
PCC 7942
NC_007604
(2695903 bp)
402
200001–201005
1005

Syntrophobacter fumaroxidans 
DSM 10017
NC_008554
(4990251 bp)
337
200001–200987
987

Synechococcus sp.  
ATCC 27264
NC_010475
(3008047 bp)
431
200001–201008
1008

Synechococcus elongatus 
PCC 6301
NC_006576
(2696255 bp)
402
200001–201005
1005

Synechococcus sp.  
PCC 7002
NC_010475
(3008047 bp)
431
200001–201008
1008

Synechococcus sp.  
WH8102
NC_005070
(2434428 bp)
537
200001–201017
1017

Synechocystis sp.
CP003265
(3569561 bp)
371
200001–201026
1026

Synechocystis sp.  
PCC 6803
NC_017052
(3570103 bp)
374
200001–201026
1026

Terriglobus roseus 
KBS 63
Terro_Contig51.1
(5227858 bp)
354
200001–200873
873

Tistrella mobilis 
KA081020-065
CP003239
(1126962 bp)
379
200001–201077
1077

Variovorax paradoxus (strain EPS)
NC_014931
(6550056 bp)
360
200001–201035
1035

Variovorax paradoxus 
S110
NC_012791
(5626353 bp)
420
200001–201053
1053

Verminephrobacter eiseniae EF01-2
NC_008786
(5566749 bp)
337
200001–200987
1020

Zobellia galactanivorans 
DSM 12802
FG20DRAFT
(5340688 bp)
331
200001–200951
951

Zymomonas mobilis subsp. Mobilis 
ATCC 10988
NZ_ACQU01000006
(113352 bp)
113
82520–83509
990

Table 3: Manually designed motifs (MDMs) for aliphatic and aromatic nitrilases showing the presence of essential catalytic triad (E, K, and C).

Nitrilases
Manually designed motif

Aliphatic
[FL]-[ILV]-[AV]-F-P-E-[VT]-[FW]-[IL]-P-[GY]-Y-P-[WY]

R-R-K-[LI]-[KRI]-[PA]-T-[HY]-[VAH]-E-R

C-W-E-H-[FLX]-[NQ]-[PT]-L

[VA]-A-X-[AV]-Q-[AI]-X-P-[VA]-X-[LF]-[SD]

Aromatic
[ALV]-[LV]-[FLM]-P-E-[AS]-[FLV]-[LV]-[AGP]-[AG]-Y-P

[AGN]-[KR]-H-R-K-L-[MK]-P-T-[AGN]-X-E-R

C-W-E-N-[HY]-M-P-[LM]-[AL]-R-X-X-[ML]-Y

A-X-E-G-R-C-[FW]-V-[LIV]

Table 4: Aliphatic and aromatic nitrilase motif patterns with bold letter depicting catalytic center (E, K, and C) in predicted nitrilases.

Nitrilases
Manually Designed motif
1
2
3
4
5
6
7
8
9

Aliphatic
[FL]-[ILV]-[AV]-F-P-E-[VT]-[FW]-[IL]-P-[GY]-Y-P-[WY]
A-F-P-E-V-F-V-P-A-Y-P-Y
F-P-E-L-W-L-P-G-Y-P-I-F
F-P-E-V-F-I-S-G-Y-P-Y-W-N-W

F-P-E-V-F-I-A-G-Y
F-P-E-T-F-V-P-Y-Y-P-Y

R-R-K-[LI]-[KRI]-[PA]-T-[HY]-[VAH]-E-R
L-R-R-K-L-V-P-T-W
R-R-K-L-K-P-T-H-V-E-R
R-K-L-V-P-T-W-A-E-K-L-T

R-H-R-K-L-V-P-T-W-A-E-R
R-R-K-I-T-P-T-Y-H-E-R

C-W-E-H-[FLX]-[NQ]-[PT]-L
C-G-E-N-T-N-T-L-A
C-A-E-N-M-Q-P-L
C-G-E-N-T-N-T-L-A

C-G-E-N-T-N-T-L-A-R-F-S
C-W-E-H-Y-N-P-L-

[VA]-A-X-[AV]-Q-[AI]- X- P-[VA]-X-[LF]-[SD]
V-A-A-V-Q-A-A-P-V-F-L-D-P
V-A-S-V-Q-A-E
V-Q-T-A-P-V-F-L-N-V-E

A-A-V-Q-A-A-P-V-F-L
A-A-V-Q-I-S-P-V-L-

Aromatic
[ALV]-[LV]-[FLM]-P-E-[AS]-[FLV]-[LV]-[AGP]-[AG]-Y-P

F-Q-E-V-F-N-A
P-E-S-F-I-P-C-Y-P-R-G
F-P-E-A-F-L-G-T-Y-P

S-E-T-F-S-T-G

[AGN]-[KR]-H-R-K-L-[MK]-P-T-[AGN]-X-E-R

R-K-H-H-I-P-Q-V
H-R-K-L-K-P-T-G-L-E-R
H-R-K-V-M-P-T-G-A-E-R

R-K-L-H-P-F-T

C-W-E-N-[HY]-M-P-[LM]-[AL]-R-X-X-[ML]-Y

C-Y-D-R-H
C-W-E-N-Y-M-P-L-A-R-M
C-W-E-N-Y-M-P-L-L-R-A

C-Y-D-L-R-F-A

A-X-E-G-R-C-[FW]-V-[LIV]

A-H-L-W-K-L-E
A-L-E-G-R-C-F-V-L-A
A-L-E-G-R-C-W-V

A-I-E-N-Q-A-Y-V

3.2. Physiochemical Parameters and Phylogenetic Analysis

In silico identified nitrilases were analyzed for their physiochemical properties using ProtParam, an online tool at the ExPASy proteomic server. The selected candidates values for various properties were found to be very much similar to those with earlier published data by Sharma and Bhalla [16] as mentioned in Table 5. Average values deduced for aliphatic and aromatic nitrilases from earlier characterized proteins were taken as standard for the comparison of a predicted set of nitrilase. The values of the same were found to be very much similar to those with earlier published data by Sharma and Bhalla [16] as mentioned in Table 5. The total number of amino acids ranged from 260 amino acids (Nocardiopsis dassonvillei) to 342 amino acids (Shimwellia blattae) with different molecular weight. Isoelectric point ranged between 4.8 and 5.8 which is found to be closer to the consensus value, that is, the average data value from previously characterized aliphatic or aromatic nitrilases.

Table 5: Comparison of physiochemical properties of aliphatic, aromatic, and predicted nitrilase from the average consensus values reported by Sharma and Bhalla [16].

Parameters
Average value for aliphatic
Average value for aromatic
1
2
3
4
5
6
7
8
9

Number of amino acids
352.2
309.8
338.0
331.0
326.0
260.0
280.0
310.0
315.0
342.0
319.0

Molecular weight (Da)
38274.0
33693.5
36154.9
36491.2
36364.7
27903.3
31464.1
34938.1
33821.5
37472.7
34678.7

Theoretical
pI
5.5
5.5
5.0
4.9
6.2
5.2
5.6
5.4
4.8
5.4
5.8

NCR
41.7
35.8
41.0
44.0
40.0
32.0
36.0
43.0
43.0
41.0
39.0

PCR
30.3
29.2
26.0
25.0
37.0
21.0
27.0
34.0
29.0
30.0
32.0

Extinction coefficients 
(M⁻¹ cm⁻¹) at 280 nm
50213.3
43975.0
45295.0
33015.0
43890.0
35200.0
62465.0
53400.0
47900.0
38305.0
31775.0

Instability index
41.2
38.5
30.1
52.5
27.0
27.7
28.6
39.6
46.6
36.6
38.5

Aliphatic index
89.40
89.90
94.1
87.9
93.6
81.1
76.0
90.9
86.2
92.8
89.3

Grand average of hydropathicity (GRAVY)
00.10
00.01
0.027
−0.17
−0.14
−0.051
−0.283
−0.109
0.045
−0.052
−0.002

NCR: negatively charged residues; PCR: positively charged residues.

Neighbor Joining (NJ) tree using MEGA 6 shows the phylogenetic analysis with in silico predicted sequences from completely sequenced microbial genomes with that of previously characterized nitrilase sequences. They were distinguished either as aliphatic or aromatic according to their position in the phylogenetic tree (Figure 1).

Figure 1: Neighbor Joining (NJ) method differentiating characterized and in silico predicted as aliphatic and aromatic nitrilases.

3.3. In Vitro Validation of Some In Silico Predicted Nitrilases

To validate for nitrile transforming activity of nine predicted novel sources of nitrilases, these were tested against common aliphatic, aromatic, and aryl nitriles and potassium cyanide (KCN). Gluconacetobacter diazotrophicus, Sphingopyxis alaskensis, Saccharomonospora viridis, and Shimwellia blattae were found to be more specific for aliphatic nitriles. On the other hand, Geodermatophilus obscurus, Nocardiopsis dassonvillei, Runella slithyformis, and Streptomyces albus exhibited nitrilase activity for aromatic nitriles. Flavobacterium indicum was the only organism which showed no activity for either aliphatic, aromatic, or aryl nitriles but was specific towards the degradation of the potassium cyanide (KCN) (Table 6). On the other hand, negative control, that is, Escherichia coli BL21 (DE3), showed no activity for any of the nitriles/substrates tested.

Table 6: Nitrilase activity of in silico predicted microbial sources of nitrilases assayed using common aliphatic, aromatic, aryl aliphatic, and KCN as substrate.

Organisms
Substrates

Valeronitrile
Benzonitrile
Mandelonitrile
Isobutyronitrile
Adiponitrile
2-Cyanopyridine
Propionitrile
Acrylonitrile
KCN

Streptomyces albus 
J1074
0.0015
0.0027
ND
0.0014
ND
ND
ND
ND
ND

Nocardiopsis dassonvillei 
DSM 43111
ND
0.0040
0.0024
ND
ND
ND
ND
ND
ND

Geodermatophilus obscurus 
DSM 43160
ND
0.0043
0.0021
ND
ND
ND
ND
ND
ND

Shimwellia blattae 
ATCC 29907
0.0028
ND
0.0016
0.0019
ND
ND
ND
ND
ND

Runella slithyformis 
ATCC 29530
ND
0.0297
0.0152
0.0095
ND
ND
0.0169
ND
ND

Gluconacetobacter diazotrophicus 
ATCC 49037
ND
0.0016
0.0020
0.0051
0.0048
ND
ND
ND
ND

Sphingopyxis alaskensis 
DSM 13593
ND
0.00073
ND
0.0024
0.00075
ND
ND
ND
ND

Saccharomonospora viridis 
ATCC 15386
ND
ND
ND
0.0030
ND
ND
ND
ND
ND

Flavobacterium indicum 
DSM 17447
ND
ND
ND
ND
ND
ND
ND
ND
0.25

Escherichia coli 
BL21 (DE3)
ND
ND
ND
ND
ND
ND
ND
ND
ND

Expressed as µmole of ammonia released/min/mg dcw under the assay conditions; ND = not detected; negative control.

4. Discussion

Annotation of sequenced genomes to identify new genes has become integral part of the research in bioinformatics [21–24]. The present investigation has revealed some novel sources of nitrilases. Homology and conserved motif approach screened microbial genomes and proteins predicted as nitrilase or cyanide dihydratase or carbon-nitrogen hydrolase in 138 prokaryotic bacterial genomes. Manually designed motifs (MDMs) also differentiated the in silico predicted nitrilases as aliphatic or aromatic [12] as the designed motifs are class specific. All the four motifs identified were uniformly conserved throughout the two sets of aliphatic and aromatic nitrilases as mentioned in Table 4.

The sequences belonged to the nitrilase superfamily, showing the presence of the catalytic triad Glu (E), Lys (K), and Cys (C) to be conserved throughout. Phylogenetic analysis using the MEGA 6.0 version for the aliphatic and aromatic set of protein sequences revealed two major clusters. Neighbor Joining (NJ) tree used for phylogenetic analysis revealed that in silico predicted proteins (this study) and previously identified nitrilases as aliphatic and aromatic [16] were found to be grouped in their respective clusters (Figure 1).

Aliphaticity and aromaticity of in silico predicted and characterized nitrilases were differentiated based on their physiochemical properties. The physicochemical properties of the predicted set of nitrilase were deduced using the ProtParam subroutine of Expert Protein Analysis System (ExPASy) from the proteomic server of the Swiss Institute of Bioinformatics (SIB), in order to predict aromaticity or aliphaticity. Several of the parameters (number of amino acids, molecular weight, number of negatively charged residues, extinction coefficients, and grand average of hydropathicity) listed in Table 5 are closer to the consensus values reported for aromatic and aliphatic nitrilases, supporting that the predicted set of nitrilase has aromatic or aliphatic substrate specificity (Table 5).

In silico predictions were verified by in vitro validation of the predicted proteins. Common nitriles (aliphatic, aromatic, and aryl nitriles) and potassium cyanide (KCN) were tested to check for the nitrile/cyanide transforming ability of the predicted proteins. Out of nine predicted proteins eight were found active for different nitriles, whereas Flavobacterium indicum was found to hydrolyze toxic cyanide (KCN) into nontoxic form (Table 6). The present approach contributed to finding novel sources of desired nitrilase from microbial genome database.

5. Conclusion

Genome mining for novel sources of nitrilases has predicted 138 sources for nitrilases. In vitro validation of the selected nine predicted sources of nitrilases for nitrile/cyanide hydrolyzing activity has furthered the scope of genome mining approaches for the discovery of novel sources of enzymes.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

The authors are thankful to the Department of Biotechnology (DBT), New Delhi, for the continuous support to the Bioinformatics Centre, Himachal Pradesh University, Summer Hill, Shimla, India.

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