Bioinformatics in the identification of microorganisms
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microbe identification
genotypic methods
proteomic technologies

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Yeoh, C. Y. ., & Cheah, Y. K. (2020). Bioinformatics in the identification of microorganisms. Life Sciences, Medicine and Biomedicine, 4(9).


Rapid and accurate identification of microorganisms can be of great value for clinical management. For many fastidious and slow-growing microorganisms, the conventional method used for detection is time-consuming, costly and labour-intensive. Hence, the development of new and improved microbial identification methods are necessary to overcome this bottleneck. Current trend has shifted towards the use of new molecular technologies in genomics and proteomics for bacterial identification and characterization. This mini review will focus on summarizing different types of genotypic and proteomics identification methods, as well as bioinformatics tools used for rapid identification and characterization of microorganisms from various specimens.
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Aagaard, K., Petrosino, J., Keitel, W., Watson, M., Katancik, J., Garcia, N., Patel, S., Cutting, M., Madden, T., Hamilton, H., Harris, E., Gevers, D., Simone, G., McInnes, P., & Versalovic, J. (2013). The human microbiome project strategy for comprehensive sampling of the human microbiome and why it matters. FASEB Journal, 27(3), 1012-1022.

Abbasian, F., Lockington, R., Megharaj, M., & Naidu, R. (2015). The integration of sequencing and bioinformatics in metagenomics. Reviews in Environmental Science and Biotechnology, 14(3), 357-383.

Apweiler, R., Bairoch, A., Wu, C. H., Barker, W. C., Boeckmann, B., Ferro, S., Gasteiger, E., Huang, H., Lopez, R., Magrane, M., Martin, M. J., Natale, D. A., O'Donovan, C., Redaschi, N., & Yeh, L.-S. L. (2004). UniProt: The Universal Protein knowledgebase. Nucleic Acids Research, 32, 115-119.

Arango, C., Acosta-Gonzalez, A., Parra-Giraldo, C. M., Sánchez-Quitian, Z. A., Kerr, R., & Diaz, L. E. (2018). Characterization of actinobacterial communities from Arauca river sediments (Colombia) reveals antimicrobial potential presented in low abundant isolates. The Open Microbiology Journal, 12, 181-194.

Bansal, A. K. (2005). Bioinformatics in microbial biotechnology--a mini review. Microbial Cell Factories, 4, 19.

Barba, M. J., Fernández, A., Oviaño, M., Fernández, B., Velasco, D., & Bou, G. (2014). Evaluation of MALDI-TOF mass spectrometry for identification of anaerobic bacteria. Anaerobe, 30, 126-128.

Biswas, S., & Rolain, J. M. (2013). Use of MALDI-TOF mass spectrometry for identification of bacteria that are difficult to culture. Journal of Microbiological Methods, 92(1), 14-24.

Borneman, J., & Hartin, R. J. (2000). PCR primers that amplify fungal rRNA genes from environmental samples. Applied and Environmental Microbiology, 66(10), 4356-4360.

Clarridge, J. E., & Alerts, C. (2004). Impact of 16S rRNA gene sequence analysis for identification of bacteria on clinical microbiology and infectious diseases. Clinical Microbiology Reviews, 17(4), 840-862.

DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., Huber, T., Dalevi, D., Hu, P., & Andersen, G. L. (2006). Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied and Environmental Microbiology, 72(7), 5069-5072.

Devulder, G., Perrière, G., Baty, F., & Flandrois, J. P. (2003). BIBI, a bioinformatics bacterial identification tool. Journal of Clinical Microbiology, 41(4), 1785-1787.

Diament, B. J., & Noble, W. S. (2011). Faster SEQUEST searching for peptide identification from tandem mass spectra. Journal of Proteome Research, 10(9), 3871-3879.

Dieckmann, R., & Malorny, B. (2011). Rapid screening of epidemiologically important Salmonella enterica subsp. enterica serovars by whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry. Applied and Environmental Microbiology, 77(2), 4136-4146.

Dinsdale, E. A., Edwards, R. A., Hall, D., Angly, F., Breitbart, M., Brulc, J. M., Furlan, M., Desnues, C., Haynes, M., Li, L., McDaniel, L., Moran, M. A., Nelson, K. E., Nilsson, C., Olson, R., Paul, J., Brito, B. R., Ruan, Y., Swan, B. K., Stevens, R., Valentine, D. L., Thurber, R. V., Wegley, L., White, B. A., & Rohwer, F. (2008). Functional metagenomic profiling of nine biomes. Nature, 452(7187), 629-632.

Emerson, D., Agulto, L., Liu, H., & Liu, L. (2008). Identifying and characterizing bacteria in an era of genomics and proteomics. Bioscience, 58(10), 925.

Feil, E. J., Li, B. C., Aanensen, D. M., Hanage, W. P., & Spratt, B. G. (2004). eBURST: Inferring patterns of evolutionary descent among clusters of related bacterial genotypes from multilocus sequence typing data. Journal of Bacteriology, 186(5), 1518-1530.

Fleischmann, R. D., Adams, M. D., White, O., Clayton, R. A., Kirkness, E. F., Kerlavage, A. R., Bult, C. J., Tomb, J. F., Dougherty, B. A., Merrick, J. M., Mckenney, K., Sutton, G., Fitzhugh, W., Fields, C., Gocayne, J. D., Scott, J., Shirley, R., Liu, L. I., Glodek, A., Kelley, J. M., Weidman, J. F., Phillips, C. A., Spriggs, T., Hedblom, E., Cotton, M. D., Utterback, T. R., Hanna, M. C., Nguyen, D. T., Saudek, D. M., Brandon, R. C., Fine, L. D., Fritchman, J. L., Fuhrmann, J. L., Geoghagen, N. S. M., Gnehm, C. L., Mcdonald, L. A., Small, K. V, Fraser, C. M., Smith, H. O., & Venter, J. C. (1995). Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. Science, 269(5223), 496-512.

Foxman, B., Zhang, L., Koopman, J. S., Manning, S. D., & Marrs, C. F. (2005). Choosing an appropriate bacterial typing technique for epidemiologic studies. Epidemiologic Perspectives and Innovations, 2, 10.

Gevers, D., Cohan, F. M., Lawrence, J. G., Spratt, B. G., Coenye, T., Feil, E. J., Stackebrandt, E., Van de Peer, Y., Vandamme, P., Thompson, F. L., & Swings, J. (2005). Opinion: Re-evaluating prokaryotic species. Nature Reviews Microbiology, 3(9), 733-739.

Girard, G., Traag, B. A., Sangal, V., Mascini, N., Hoskisson, P. A., Goodfellow, M., & van Wezel, G. P. (2013). A novel taxonomic marker that discriminates between morphologically complex actinomycetes. Open Biology, 3(10), 130073.

Glish, G. L., & Vachet, R. W. (2003). The basics of mass spectrometry in the twenty-first century. Nature Reviews Drug Discovery, 2(2), 140-150.

Gresham, D., Dunham, M. J., & Botstein, D. (2008). Comparing whole genomes using DNA microarrays. Nature Reviews Genetics, 9(4), 291-302.

Hamady, M., & Knight, R. (2009). Microbial community profiling for human microbiome projects: Tools, techniques, and challenges. Genome Research, 19(7), 1141-1152.

Haneef, J., Shaharyar, M., Husain, A., Rashid, M., Mishra, R., Parveen, S., Ahmed, N., Pal, M., & Kumar, D. (2013). Application of LC-MS/MS for quantitative analysis of glucocorticoids and stimulants in biological fluids. Journal of Pharmaceutical Analysis, 3(5), 341-348.

He, Z., Gentry, T. J., Schadt, C. W., Wu, L., Liebich, J., Chong, S. C., Huang, Z., Wu, W., Gu, B., Jardine, P., Criddle, C., & Zhou, J. (2007). GeoChip: A comprehensive microarray for investigating biogeochemical, ecological and environmental processes. The ISME Journal, 1(1), 67-77.

Huson, D. H., Auch, A. F., Qi, J., & Schuster, S. C. (2007). MEGAN analysis of metagenomic data. Genome Research, 17(3), 377-386.

Jolley, K. A., Bliss, C. M., Bennett, J. S., Bratcher, H. B., Brehony, C., Colles, F. M., Wimalarathna, H., Harrison, O. B., Sheppard, S. K., Cody, A. J., Maiden, M. C. J. (2012). Ribosomal multilocus sequence typing: Universal characterization of bacteria from domain to strain. Microbiology, 158, 1005-1015.

Kim, O. S., Cho, Y. J., Lee, K., Yoon, S. H., Kim, M., Na, H., Park, S.-C., Jeon, Y. S., Lee, J.-H., Yi, H., Won, S., & Chun, J. (2012). Introducing EzTaxon-e: A prokaryotic 16S rRNA gene sequence database with phylotypes that represent uncultured species. International Journal of Systematic and Evolutionary Microbiology, 62, 716-721.

Lozupone, C. A., Hamady, M., Kelley, S. T., & Knight, R. (2007). Quantitative and qualitative diversity measures lead to different insights into factors that structure microbial communities. Applied and Environmental Microbiology, 73(5), 1576-1585.

Magdeldin, S., Enany, S., Yoshida, Y., Xu, B., Zhang, Y., Zureena, Z., Lokamani, I., Yaoita, E., & Yamamoto, T. (2014). Basics and recent advances of two dimensional- polyacrylamide gel electrophoresis. Clinical Proteomics, 11(1), 16.

Markowitz, V. M., Chen, I. M. A., Chu, K., Szeto, E., Palaniappan, K., Grechkin, Y., Ratner, A., Jacob, B., Pati, A., Huntemann, M., Liolios, K., Pagani, I., Anderson, I., Mavromatis, K., Ivanova, N. N., & Kyrpides, N. C. (2012). IMG/M: The integrated metagenome data management and comparative analysis system. Nucleic Acids Research, 40(1), 123-129.

Meyer, F., Paarmann, D., D'Souza, M., Olson, R., Glass, E., Kubal, M., Paczian, T., Rodriguez, A., Stevens, R., Wilke, A., Wilkening, J., & Edwards, R. (2008). The metagenomics RAST server ˗ a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics, 9(1), 386.

Millar, B. C., Xu, J., & Moore, E. (2007). Molecular diagnostics of medically important bacterial infections. Current Issues in Molecular Biology, 9, 21-40.

Mocali, S., & Benedetti, A. (2010). Exploring research frontiers in microbiology: The challenge of metagenomics in soil microbiology. Research in Microbiology, 161(6), 497-505.

Nagarajan, K., Loh, K.-C., & Swarup, S. (2013). Bioinformatics and molecular biology for the quantification of closely related bacteria. Applied Microbiology and Biotechnology, 97(14), 6489-6502.

Nilsen, M. M., Uleberg, K.-E., Janssen, E. A. M., Baak, J. P. A., Andersen, O. K., & Hjelle, A. (2011). From SELDI-TOF MS to protein identification by on-chip elution. Journal of Proteomics, 74(12), 2995-2998.

Pandey, A., & Mann, M. (2000). Proteomics to study genes and genomes. Nature, 405(6788), 837-846.

Perkins, D. N., Pappin, D. J., Creasy, D. M., & Cottrell, J. S. (1999). Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis, 20(18), 3551-3567.<3551::AID-ELPS3551>3.0.CO;2-2

Proctor, L. M. (2011). The human microbiome project in 2011 and beyond. Cell Host and Microbe, 10(4), 287-291.

Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., Glockner, F. O. (2013). The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Research, 41(1), 590-596.

Rastogi, G., & Sani, R. K. (2011). Molecular Techniques to Assess Microbial Community Structure, Function, and Dynamics in the Environment. In I. Ahmad., F. Ahmad., & J. Pichtel (Eds), Microbes and Microbial Technology, pp. 29-58. New York: Springer.

Rodrigo, M. A. M., Zitka, O., Krizkova, S., Moulick, A., Adam, V., & Kizek, R. (2014). MALDI-TOF MS as evolving cancer diagnostic tool: A review. Journal of Pharmaceutical and Biomedical Analysis, 95, 245-255.

Rong, X., & Huang, Y. (2010). Taxonomic evaluation of the Streptomyces griseus clade using multilocus sequence analysis and DNA-DNA hybridization, with proposal to combine 29 species and three subspecies as 11 genomic species. International Journal of Systematic and Evolutionary Microbiology, 60, 696-703.

Ruiz-Garbajosa, P., Bonten, M. J. M., Robinson, D. A., Top, J., Nallapareddy, S. R., Torres, C., Coque, T. M., Canton, R., Baquero, F., Murray, B. E., del Campo, R., & Willems, R. J. L. (2006). Multilocus sequence typing scheme for Enterococcus faecalis reveals hospital-adapted genetic complexes in a background of high rates of recombination. Journal of Clinical Microbiology, 44(6), 2220-2228.

Santos, T., Capelo, J. L., Santos, H. M., Oliveira, I., Marinho, C., Gonçalves, A., Araújo, J. E., Poeta, P., & Igrejas, G. (2015). Use of MALDI-TOF mass spectrometry fingerprinting to characterize Enterococcus spp. and Escherichia coli isolates. Journal of Proteomics, 127, 321-331.

Singh, A., & Kumar, N. (2013). A review on DNA microarray technology. International Journal of Current Research and Review, 5(22), 1-5.

Smith, F. M., Gallagher, W. M., Fox, E., Stephens, R. B., Rexhepaj, E., Petricoin, E. F., Liotta, L., Kennedy, M. J., & Reynolds, J. V. (2007). Combination of SELDI-TOF-MS and data mining provides early-stage response prediction for rectal tumors undergoing multimodal neoadjuvant therapy. Annals of Surgery, 245(2), 259-266.

Stoddard, S. F., Smith, B. J., Hein, R., Roller, B. R. K., & Schmidt, T. M. (2015). rrnDB: Improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development. Nucleic Acids Research, 43(1), 593-598.

Sun, J. F., Ke, B. X., Huang, Y. H., He, D. M., Li, X., Liang, Z. M., & Ke, C. W. (2014). The molecular epidemiological characteristics and genetic diversity of Salmonella Typhimurium in Guangdong, China. PLoS One, 9(11), e113145.

Sun, S., Chen, J., Li, W., Altintas, I., Lin, A., Peltier, S., Stocks, K., Allen, E. E., Ellisman, M., Grethe, J., & Wooley, J. (2011). Community cyberinfrastructure for advanced microbial ecology research and analysis: The CAMERA resource. Nucleic Acids Research, 39, 546-551.

Tabish, M., Azim, S., Hussain, M. A., Rehman, S. U., Sarwar, T., & Ishqi, H. M. (2013). Bioinformatics Approaches in Studying Microbial Diversity. In A, Malik., E. Grohmann., & M. Alves (Eds), Management of Microbial Resources in the Environment, pp. 119-140. Dordrecht: Springer.

Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., & Kumar, S. (2011). MEGA5: Molecular evolutionary genetics analysis using maximum likelihood, evolutioanry distance, and maximum parsimony methods. Molecular Biology and Evolution, 28(10), 2731-2739.

Tang, Y. -W., Ellis, N. M., Hopkins, M. K., Smith, D. H., Dodge, D. E., & Persing, D. H. (1998). Comparison of phenotypic and genotypic techniques for identification of unusual aerobic pathogenic gram-negative bacilli. Journal of Clinical Microbiology, 36(12), 3674-3679.

Tatusova, T., Ciufo, S., Federhen, S., Fedorov, B., McVeigh, R., O'Neill, K., Tolstoy, I., & Zaslavsky, L. (2015). Update on RefSeq microbial genomes resources. Nucleic Acids Research, 43(1), 599-605.

Turnbaugh, P. J., Ley, R. E., Hamady, M., Fraser-liggett, C., Knight, R., & Gordon, J. I. (2007). The human microbiome project: Exploring the microbial part of ourselves in a changing world. Nature, 449(7164), 804-810.

Uchiyama, I., Mihara, M., Nishide, H., & Chiba, H. (2015). MBGD update 2015: Microbial genome database for flexible ortholog analysis utilizing a diverse set of genomic data. Nucleic Acids Research, 43(1), 270-276.

Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007). Naive bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology, 73(16), 5261-5267.

Wilson, K. H., Wilson, W. J., Jennifer, L., Desantis, T. Z., Viswanathan, V. S., Kuczmarski, T. A., Andersen, G. L., & Radosevich, J. L. (2002). High-density microarray of small-subunit ribosomal DNA probes. Applied and Environmental Microbiology, 68(5), 2535-2541.

Wolters, M., Rohde, H., Maier, T., Belmar-Campos, C., Franke, G., Scherpe, S., Aepfelbacher, M., & Christner, M. (2011). MALDI-TOF MS fingerprinting allows for discrimination of major methicillin-resistant Staphylococcus aureus lineages. International Journal of Medical Microbiology, 301(1), 64-68.

Yadav, A. K., Kumar, D., & Dash, D. (2011). MassWiz: A novel scoring algorithm with target-decoy based analysis pipeline for tandem mass spectrometry. Journal of Proteome Research, 10(5), 2154-2160.

Zhang, J., Xin, L., Shan, B., Chen, W., Xie, M., Yuen, D., Zhang, W., Zhang, Z., Lajoie, G.A., & Ma, B. (2011). PEAKS DB: De Novo sequencing assisted database search for sensitive and accurate peptide identification. Molecular & Cellular Proteomics, 11(4), M111.010587.

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