Abstract
All the genetic potential and the intelligence a bacteria can showcase in a given environment are embedded in its genome. In this study, we have presented systematic guidelines to understand a bacterial genome with the relevant set of in silico tools using a novel bacteria as an example. This study presents a multi-dimensional approach from genome annotation to tracing genes and their network of metabolism operating in an organism. It also shows how the sequence can be used to mine the enzymes and construction of its 3-dimensional structure so that its functional behavior can be predicted and compared. The discriminating algorithm allows analysis of the promoter region and provides the insight in the regulation of genes in spite of the similarity in its sequences. The ecological niche specific bacterial behavior and adapted altered physiology can be understood through the presence of secondary metabolite, antibiotic resistance genes, and viral genes; and it helps in the valorization of genetic information for developing new biological application/processes. This study provides an in silico work plan and necessary steps for genome analysis of novel bacteria without any rigorous wet lab experiments.
Similar content being viewed by others
References
Purohit HJ, Tikariha H, Kalia VC (2018) Current scenario on application of computational tools in biological systems. In: Soft computing for biological systems, Springer, Singapore, pp 1–12
Claesson MJ, Wang Q, O’sullivan O, Greene-Diniz R, Cole JR, Ross RP, O’toole PW (2010) Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions. Nucleic Acids Res 38:e200–e200. https://doi.org/10.1093/nar/gkq873
Kapley A, Jadeja NB, Paliwal V, Yadav TC, Purohit HJ (2016) Microbial genomics and bioremediation of industrial wastewater, chap 8. In: Chandra R (ed) Environmental Waste Management. CRC Press, Boca Raton, pp 185–216
Khardenavis AA, Kapley A, Purohit HJ (2010) Salicylic-acid-mediated enhanced biological treatment of wastewater. Appl Biochem Biotechnol 160:704–718. https://doi.org/10.1007/s12010-009-8538-7
Van Toan P (2016) Biofertilizer research, development, and application in Vietnam. In: Agriculturally important microorganisms, Springer, Singapore, pp 197–217
Parakhia MV, Tomar RS, Vadukia MR, Malviya BJ, Rathod VM, Thakkar JR, Golakiya BA (2014) Draft genome sequence of the methyl parathion (pesticide) degrading bacterium Pseudomonas spp. MR3. Indian J Microbiol 54:120–121. https://doi.org/10.1007/s12088-013-0433-9
Chen AJ, Boudreau MC, Watson RT (2008) Information systems and ecological sustainability. J Syst Inf Technol 10:186–201. https://doi.org/10.1108/13287260810916907
Bhushan A, Joshi J, Shankar P, Kushwah J, Raju SC, Purohit HJ, Kalia VC (2013) Development of genomic tools for the identification of certain Pseudomonas up to species level. Indian J Microbiol 53:253–263. https://doi.org/10.1007/s12088-013-0412-1
Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Huttley GA (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335. https://doi.org/10.1038/nmeth.f.303
Brettin T, Davis JJ, Disz T, Edwards RA, Gerdes S, Olsen GJ, Shukla M (2015) RASTtk: a modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes. Sci Rep 5:8365. https://doi.org/10.1038/srep08365
Pal RR, Khardenavis AA, Purohit HJ (2015) Identification and monitoring of nitrification and denitrification genes in Klebsiella pneumoniae EGD-HP19-C for its ability to perform heterotrophic nitrification and aerobic denitrification. Funct Integr Genomics 15:63–76. https://doi.org/10.1007/s10142-014-0406-z
Fuke P, Pal RR, Khardenavis AA, Purohit HJ (2018) In silico characterization of broad range proteases produced by Serratia marcescens EGD-HP20. J Basic Microbiol. https://doi.org/10.1002/jobm.201700474
Puranik S, Talkal R, Qureshi A, Khardenavis A, Kapley A, Purohit HJ (2013) Genome sequence of the pigment-producing bacterium Pseudogulbenkiania ferrooxidans, isolated from Loktak Lake. Genome Announc 1:e01113–e01115. https://doi.org/10.1128/genomeA.01115-13
Caldas LR, Leitã AAC, Santos SM, Tyrrell RM (1978) Preliminary experiments on the photobiological properties of violacein. In: Tyrrell RM (ed) Proceedings of international symposium on current topics in radiology and photobiology, Rio de Janeiro, Academia Brasileira de Ciências, pp 121–126
Venil CK, Zakaria ZA, Ahmad WA (2013) Bacterial pigments and their applications. Process Biochem 48:1065–1079. https://doi.org/10.1016/j.procbio.2013.06.006
Byrne-Bailey KG, Weber KA, Coates JD (2012) Draft genome sequence of the anaerobic, nitrate-dependent, Fe(II)-oxidizing bacterium Pseudogulbenkiania ferrooxidans strain 2002. J Bacteriol 194:2400–2401. https://doi.org/10.1128/JB.00214-12
Angiuoli SV, Gussman A, Klimke W, Cochrane G, Field D, Garrity GM, Tatusova T (2008) Toward an online repository of standard operating procedures (SOPs) for (meta) genomic annotation. OMICS 12:137–141. https://doi.org/10.1089/omi.2008.0017
Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, Vonstein V (2013) The SEED and the rapid annotation of microbial genomes using subsystems technology (RAST). Nucleic Acids Res 42:D206–D214. https://doi.org/10.1093/nar/gkt1226
Wattam AR, Foster JT, Mane SP, Beckstrom-Sternberg SM, Beckstrom-Sternberg JM, Dickerman AW, Williams KP (2014) Comparative phylogenomics and evolution of the Brucellae reveal a path to virulence. J Bacteriol 196:920–930. https://doi.org/10.1128/JB.01091-13
Paliwal V, Raju SC, Modak A, Phale PS, Purohit HJ (2014) Pseudomonas putida CSV86: a candidate genome for genetic bioaugmentation. PLoS ONE 9:e84000. https://doi.org/10.1371/journal.pone.0084000
Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, Meyer F (2008) The RAST server: rapid annotations using subsystems technology. BMC Genom 9:75. https://doi.org/10.1186/1471-2164-9-75
Morohoshi T, Fukamachi K, Kato M, Kato N, Ikeda T (2010) Regulation of the violacein biosynthetic gene cluster by acylhomoserine lactone-mediated quorum sensing in Chromobacterium violaceum ATCC 12472. Biosci Biotechnol Biochem 74:2116–2119. https://doi.org/10.1271/bbb.100385
Hirano S, Asamizu S, Onaka H, Shiro Y, Nagano S (2008) Crystal structure of VioE, a key player in the construction of the molecular skeleton of violacein. J Biol Chem 283:6459–6466. https://doi.org/10.1074/jbc.M708109200
Durán N, Marcato PD, De Souza GI, Alves OL, Esposito E (2007) Antibacterial effect of silver nanoparticles produced by fungal process on textile fabrics and their effluent treatment. J Biomed Nanotechnol 3:203–208. https://doi.org/10.1166/jbn.2007.022
Balibar CJ, Walsh CT (2006) In vitro biosynthesis of violacein from l-tryptophan by the enzymes VioA-E from Chromobacterium violaceum. Biochemistry 45:15444–15457. https://doi.org/10.1021/bi061998z
Sanchez L, Petkov N, Alegre E (2006) Statistical approach to boar semen evaluation using intracellular intensity distribution of head images. Cell Mol Biol (Noisy-le-grand) 52:38–43. https://doi.org/10.1170/T736
Weber T, Blin K, Duddela S, Krug D, Kim HU, Bruccoleri R, Breitling R (2015) antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters. Nucleic Acids Res 43:W237–W243. https://doi.org/10.1093/nar/gkv437
Markowitz VM, Chen IMA, Palaniappan K, Chu K, Szeto E, Grechkin Y, Huntemann M (2011) IMG: the integrated microbial genomes database and comparative analysis system. Nucleic Acids Res 40:D115–D122. https://doi.org/10.1093/nar/gkr1044
Mandryk-Litvinkovich MN, Muratova AA, Nosonova TL, Evdokimova OV, Valentovich LN, Titok MA, Kolomiets EI (2017) Molecular genetic analysis of determinants defining synthesis of 2, 4-diacetylphloroglucinol by Pseudomonas brassicacearum BIM B-446 bacteria. Appl Biochem Microbiol 53:31–39. https://doi.org/10.1093/nar/gkv437
Tamura K, Stecher G, Peterson D, Filipski A, Kumar S (2013) MEGA6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol 30:2725–2729. https://doi.org/10.1093/molbev/mst197
Gemiarto AT, Ninyio NN, Lee SW, Logis J, Fatima A, Chan EWC, Lim CSY (2015) Isoprenyl caffeate, a major compound in manuka propolis, is a quorum-sensing inhibitor in Chromobacterium violaceum. Antonie Van Leeuwenhoek 108:491–504. https://doi.org/10.1007/s10482-015-0503-6
Achkar J, Xian M, Zhao H, Frost JW (2005) Biosynthesis of phloroglucinol. J Am Chem Soc 127:5332–5333. https://doi.org/10.1021/ja042340g
Kidarsa TA, Goebel NC, Zabriskie TM, Loper JE (2011) Phloroglucinol mediates cross-talk between the pyoluteorin and 2, 4-diacetylphloroglucinol biosynthetic pathways in Pseudomonas fluorescens Pf-5. Mol Microbiol 81:395–414. https://doi.org/10.1111/j.1365-2958.2011.07697.x
Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Bourne PE (2006) The protein data bank, 1999. In: International tables for crystallography volume f: crystallography of biological macromolecules, Springer, Netherlands, pp 675–684
Källberg M, Wang H, Wang S, Peng J, Wang Z, Lu H, Xu J (2012) Template-based protein structure modeling using the RaptorX web server. Nat Protoc 7:1511. https://doi.org/10.1038/nprot.2012.085
Yang QJ, Jerath A, Bies RR, Wąsowicz M, Pang KS (2015) Pharmacokinetic modeling of tranexamic acid for patients undergoing cardiac surgery with normal renal function and model simulations for patients with renal impairment. Biopharm Drug Dispos 36:294–307. https://doi.org/10.1002/bdd.1941
Tikariha H, Pal RR, Qureshi A, Kapley A, Purohit HJ (2016) In silico analysis for prediction of degradative capacity of Pseudomonas putida SF1. Gene 591:382–392. https://doi.org/10.1016/j.gene.2016.06.028
Laskowski RA, Chistyakov VV, Thornton JM (2005) PDBsum more: new summaries and analyses of the known 3D structures of proteins and nucleic acids. Nucleic Acids Res 33:D266–D268. https://doi.org/10.1093/nar/gki001
Wiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35:W407–W410. https://doi.org/10.1093/nar/gkm290
Wei S, Whittaker CA, Xu G, Bridges LC, Shah A, White JM, DeSimone DW (2010) Conservation and divergence of ADAM family proteins in the Xenopus genome. BMC Evol Biol 10:211. https://doi.org/10.1186/1471-2148-10-211
Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004) UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612. https://doi.org/10.1002/jcc.20084
Kothari V, Patel P, Joshi C, Mishra B, Dubey S, Mehta M (2017) Sonic stimulation can affect production of quorum sensing regulated pigment in serratia marcescens and Pseudomonas aeruginosa. Curr Trends Biotechnol Pharm 11:121–128. https://doi.org/10.1101/072850
Hall T (2011) BioEdit: an important software for molecular biology. GERF Bull Biosci 2:60–61
Abbas ZG, Gill GV, Archibald LK (2002) The epidemiology of diabetic limb sepsis: an African perspective. Diabet Med 19:895–899. https://doi.org/10.1046/j.1464-5491.2002.00825.x
Hulo C, DeCastro E, Masson P, Bougueleret L, Bairoch A, Xenarios I, Le Mercier P (2010) ViralZone: a knowledge resource to understand virus diversity. Nucleic Acids Res 39:D576–D582. https://doi.org/10.1093/nar/gkq901
Puranik S, Purohit HJ (2014) Dependency of cellular decision making in physiology and influence of preceding growth conditions. Appl Biochem Biotechnol 174(5):1982–1997. https://doi.org/10.1007/s12010-014-1167-9
Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120. https://doi.org/10.1093/bioinformatics/btu170
Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 28:2731–2739. https://doi.org/10.1093/molbev/msr121
Acknowledgements
Miss Reshma talkal acknowledge DBT for providing stipend and Mr. Hitesh Tikariha acknowledge the Senior Research Fellowship (SRF) from the University Grants Commission (UGC) of India for carrying out the research work. Author also thanks CSIR-NEERI for providing facilty to carry out the research work and KRC for plagiarsim check [KRC No.: CSIR-NEERI/KRC/2018/APRIL/EBGD/1].
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Supplementary Table
1 Table showing the list of all phage genes found to be present in bacterial genome under study. The phage genes were distributed in different contigs. (DOCX 17 kb)
Supplementary Fig.
1 Subsystem classification of the annotated genome by RAST (JPEG 613 kb)
Supplementary Fig.
2 Phylogenetic tree of all the vio genes constructed separately using MEGA 6. The gene from P. ferroxidans EGD-HP2 are shown in red box and the nearest member is shown with blue arrow. (JPEG 756 kb)
Supplementary Fig.
3 Phylogenetic tree of phlD gene generated using MEGA 6. The gene under study is shown in red box. The different cluster that are formed in the tree are grouped as represented with yellow boxes. (JPEG 358 kb)
Rights and permissions
About this article
Cite this article
Talkal, R., Tikariha, H. & Purohit, H. An Approach to In Silico Dissection of Bacterial Intelligence Through Selective Genomic Tools. Indian J Microbiol 58, 278–286 (2018). https://doi.org/10.1007/s12088-018-0726-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12088-018-0726-0