PL EN


Preferences help
enabled [disable] Abstract
Number of results
2016 | 3 | 26-38
Article title

Bacterial species identification

Content
Title variants
Languages of publication
EN
Abstracts
EN
The traditional methods of bacterial identification are based on observation of either the morphology of single cells or colony characteristics. However, the adoption of newer and automated methods offers advantage in terms of rapid and reliable identification of bacterial species. The review provides a comprehensive appreciation of new and improved technologies such fatty acid profiling, sequence analysis of the 16S rRNA gene, matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF), metabolic finger profiling using BIOLOG, ribotyping, together with the computational tools employed for querying the databases that are associated with these identification tools and high throughput genomic sequencing in bacterial identification. It is evident that with the increase in the adoption of new technologies, bacterial identification is becoming easier.
Discipline
Year
Volume
3
Pages
26-38
Physical description
Contributors
  • Department of Agriculture and Animal Health, University of South Africa, Private Bag X6, Florida, 1710, South Africa
  • Department of Agriculture and Animal Health, University of South Africa, Private Bag X6, Florida, 1710, South Africa, ronaldk@daff.gov.za
References
  • [1] Adams DJ, Gurr S, Hogge J (2004). Cellular Fatty-Acid Analysis of Bacillus thuringiensis Var. kurstaki Commercial Preparations. J. Agric. Food Chem., 53(3): 512-517.
  • [2] Alexandrov T (2012). MALDI imaging mass spectrometry:statistical data analysis and current computational challenges. BMC Bioinformatics 13 (Suppl 16): S11.
  • [3] Barbuddhe S.B., Maier T., Schwarz G., Kostrzewa M., Hof H., Domann E., Chakraborty T., Hain T. (2008). Rapid identification and typing of listeria species by matrix-assisted laser desorption ionization-time of flight mass spectrometry. Appl. Environ. Microbiol. 74(17): 5402-5407.
  • [4] Barghoutti S. A. (2011). A Universal Method for the Identification of Bacteria Based on General PCR Primers. Indian J Microbiol. 51(4): 430- 444.
  • [5] Bentley D. R, Balasubramanian S, Swerdlow HP, et al. (2008). Accuratewhole human genome sequencing using reversible terminator chemistry. Nature 456: 5359.
  • [6] Bergmans L., Moisiadis P., Van Meerbeek B., Quirynen M., Lambrecht P. (2005). Microscopic observation of bacteria:review highlighting the use of environmental SEM. Int. Endod. J. 38: 775-788.
  • [7] Bhore S. J., Nythia R, Loh C. Y. (2010). Screening of endophytic bacteria G isolated from leaves of sambung nyawa [Gynura procumbens (Lour.) Merr.] for cytokininlike compounds. Bioinformation 5(5): 191-197.
  • [8] Cabeen M. T., Jacobs-Wagner C. (2005). Bacterial cell shape. Nat. Rev. Microbiol. 3(8): 601-610.
  • [9] Cambray G. (2006). Basic and applied microbiology. Eds., Cloete TE, Atlas RM Van Schaik Publishers.
  • [10] Chakravorty S,, Helb D,, Burday M,, Connell N,, Alland D, (2007). A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria. J. Microbiol. Methods 69(2): 330-339.
  • [11] Chanama S (1999). Comparative 16S rRNA sequence analysis. Warasan Wichai Witthayasat Kanphaet 13: 107-117.
  • [12] Christopher K, Bruno E (2003). Identification of bacterial species. In Tested studies for laboratory teaching. Ed., O’Donnell MA. Proceedings of the 24th Workshop/Conference of the Association for Biology Laboratory Education 24: 103-130.
  • [13] Davis CL, Brlansky RH (1991). Use of Immunogold Labelling with Scanning Electron Microscopy To Identify Phytopathogenic Bacteria on Leaf Surfaces. Appl. Environ. Microbiol. 57(10): 3052-3055.
  • [14] De Bruyne K, Slabbincka B, Waegeman W, Vauterin P, De Baets B, Vandamme P (2011). Bacterial species identification from MALDITOF mass spectra through data analysis and machine learning. Syst. Appl. Microbiol. 34: 2029.
  • [15] Eren AM, Ferris MJ, Taylor CM (2011). A framework for analysis of metagenomic sequencing data. Pac. Symp. Biocomput. 131-141.
  • [16] Fagerquist CK, Yee E, Miller WG (2007). Composite sequence proteomic analysis of protein biomarkers of Campylobacter coli, C. lari and C. concisus for bacterial identification. Analyst 132(10): 1010-1023.
  • [17] Fogel GB, Collins CR, Li J, Brunk CF (1999). Prokaryotic genome size and SSU rDNA copy number:estimation of microbial relative abundance from a mixed population. Microb. Ecol. 38: 93-113.
  • [18] Giacomini M, Ruggiero C, Calegari L, Bertone S (2000). Artificial neural network based identification of environmental bacteria by gaschromatographic and electrophoretic data. J. Microbiol Methods 43(1): 45-54.
  • [19] Glimm E, Heuerh, Engelen B, Smalla K, Backhaus H (1997). Statistical comparisons of community catabolic profiles. J. Microbiol. Methods 30: 71.
  • [20] Grosse-Herrenthey A, Maier T, Gessler F, Schaumann R, Böhnel H, Kostrzewa M, Krüger M (2008). Challenging the problem of clostridial identification with matrix-assisted laser desorption and ionizationtime-of-flight mass spectrometry (MALDI-TOF MS). Anaerobe 14(4): 242-249.
  • [21] Heyrman J, Mergaert J, Denys R, Swings J (1999). The use of fatty acid methyl ester analysis (FAME) for the identification of heterotrophic bacteria present on three mural paintings showing severe damage by microorganisms. FEMS Microbiol. Lett. 181: 55-62.
  • [22] Hiremath PS, Bannigidad P, Yelgond SS (2013). An Improved Automated Method for Identification of Bacterial Cell Morphological Characteristics. International Journal of Advanced Trends in Computer Science and Engineering, Vol. 2, No. 1: 11-16.
  • [23] Holmes B, Costas M, Ganner M, On SL, Stevens M (1994). Evaluation of Biolog system for identification of some Gram-negative bacteria of clinical importance. J. Clin. Microbiol. 32: 1970-1975.
  • [24] Hung PQ, Annapurna K (2004). Isolation and characterization of endophytic bacteria in soybean (Glycine sp.). Omonrice, 12: 92-101.
  • [25] Inglis TJJ, O’Reilly L, Foster N, Adele CA, Sampson J (2002). Comparison of rapid, automated ribotyping and DNA macro restriction analysis of Burkholderia pseudomallei. J. Clin. Microbiol., 40(9): 3198-3203.
  • [26] Janda JM, Abbot SL (2007). 16S rRNA gene sequencing for bacterial identification in the diagnostic laboratory: pluses, perils, and pitfalls. J. Clin. Microbiol., 45(9): 2761-2764.
  • [27] Kenzaka T, Tani K (2012). Scanning Electron Microscopy Imaging of Bacteria Based on Nucleic Acid Sequences, Scanning Electron Microscopy, Dr. Viacheslav Kazmiruk (Ed.), ISBN: 978-953-51- 0092-8, InTech, Available from: http://www.intechopen.com/books/scanning-electron-microscopy/ scanningelectron-microscope-imaging-of-bacteria-based-on-nucleicacidsequences.
  • [28] Kivanç M, Vilmaz M, Cakir E (2011). Isolation and identification of lactic acid bacteria from boza, and their microbial activity against several reporter strains. Turk. J. Biol. 35: 313-324.
  • [29] Kloepper JW, McInroy JA, Bowen KL (1992). Comparative identification by fatty acid analysis of soil, rhizosphere, and geocarposphere bacteria of peanut (Arachis hypogaea L.). Plant Soil 139: 85-90.
  • [30] Kumrapich B, Klayraung S, Wongkattiya N, Topoonyanont N (2011). Diversity of bacteria isolated from leaves and stems of sugarcane (Saccharum sp. Var. LK9211). 37th Congress on Science and Technology of Thailand.
  • [31] Massomo SMS, Nielsen H, Mabagala RB, Mansfeld-Giese K, Hockenhull J, Mortensen CN (2003). Identification and characterisation of Xanthomonas campestris pv. campestris strains from Tanzania by pathogenicity tests, Biolog, rep-PCR and fatty acid methyl ester analysis. Eur. J. Plant Pathol. 109: 775-789.
  • [32] Miller JM, Rhoden DL (1991). Preliminary evaluation of Biolog, a carbon source utilization method for bacterial identification. J. Clin. Microbiol., 29, 1143-1147.
  • [33] Mizrahi-Man O, Davenport ER, Gilad Y (2013). Taxonomic Classification of Bacterial 16S rRNA Genes Using Short Sequencing Reads: Evaluation of Effective Study Designs. PLoS ONE 8(1).
  • [34] Morgan MC, Boyette M, Goforth C, Sperry KV, Greene SR (2009). Comparison of the Biolog OmniLog Identification System and 16S ribosomal RNA gene sequencing for accuracy in identification of atypical bacteria of clinical origin. J. Microbiol. Methods, 79: 336-343.
  • [35] Moura H, Woolfitt, AR, Carvalho MG, Pavlopoulos A, Teixeira LM, Satten GA, Barr JR (2008). MALDI-TOF mass spectrometry as a tool for differentiation of invasive and noninvasive Streptococcus pyogenes isolates. FEMS Immunol. Med. Microbiol. 53(3): 333-342.
  • [36] Muzzamal H, Sarwar R, Sajid I, Hasnain S (2012). Isolation, identification and screening of endophytic bacteria antagonistic to biofilm formers. Pakistan J. Zool., 44(1): 249-257.
  • [37] Núñez-Cardona MT (2012). Fatty acids analysis of photosynthetic sulfur bacteria by gas chromatography, gas chromatography - biochemicals, narcotics and essential oils. Ed. Salih B. InTech.
  • [38] Petrosino JF, Highlander S, Luna RA, Gibbs RA, Versalovic J (2009). Metagenomic pyrosequencing and microbial identification. Clin. Chem., 55(5): 856-866.
  • [39] Pires MN, Seldin L (1997). Evaluation of Biolog system for identification of strains of Paenibacillus azotofixans. Antonie Leeuwenhoek, 71: 195-200.
  • [40] Purcaro G, Tranchida PQ, Dugo P, La Camera E, Bisignano G, Conte L, Mondello L (2010). Characterization of bacterial lipid profiles by using rapid sample preparation and fast comprehensive twodimensional gas chromatography in combination with mass spectrometry. J. Sep. Sci., 33(15): 2334-2340.
  • [41] Sasser M (2011). Identification of bacteria by gas chromatography of cellular fatty acids. MIDI Technical Note #101.
  • [42] Shah N, Tang H, Doak TG, Ye H (2010). Comparing bacterial communities inferred from 16S rRNA gene sequencing and shotgun metagenomics. Pac. Symp. Biocomput., 2011: 165-176.
  • [43] Shendure J, Porreca GJ, Reppas (2005). Accurate multiplex polony sequencingof an evolved bacterial genome. Science 309: 1728-1732.
  • [44] Smole SC, King LA, Leopold PE, Arbeit RD (2002). Sample preparation of Grampositive bacteria for identification by matrix assisted laser desorption/ionization time-of-flight. J. Microbiol. Methods 48(2-3): 107115.
  • [45] Song Y, Liu C, McTeague M, Finegold SM (2003). 16S ribosomal DNA sequencebased analysis of clinically significant gram-positive anaerobic cocci. J Clin Microbiol., 41(4): 1363-1369.
  • [46] Stager CE, Davis JR (1992). Automated systems for identification of microorganisms. Clin. Microbiol. Rev. 5: 302-327.
  • [47] Vanlaere E, Sergeant K, Dawyndt P, Devreese B, Vandamme P (2006). Identification of Burkholderia cepacia complex using MALDI-TOF mass spectrometry. J. Cyst. Fibr. 5(Suppl. 1): S34-S134.
  • [48] Vargha M, Takats Z, Konopka A, Nakatsu CH (2006). Optimization of MALDITOF MS for strain level differentiation of Arthrobacter isolates. J. Microbiol. Methods, 66: 399-409.
  • [49] Welch DF (1991). Application of cellular fatty acid analysis. Clin Microbiol. Rev. 4(4): 422-438.
  • [50] Williams TL, Andrzejewski D, Lay JO, Musser SM (2003). Experimental factors affecting the quality and reproducibility of MALDI TOF mass spectra obtained from whole bacteria cells. J. Am. Soc. Mass Spectrom. 14(4): 342-351.
  • [51] Woese CR (1987). Bacterial evolution. Microbiol. Rev. 51(2): 221-271.
Document Type
article
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.psjd-481c4234-c518-4685-918c-47aec7596b9a
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.