Skip to main content
ARS Home » Southeast Area » Auburn, Alabama » Aquatic Animal Health Research » Research » Publications at this Location » Publication #162007


item Shoemaker, Craig
item Evans, Joyce
item Klesius, Phillip

Submitted to: Alabama Chapter of the American Fisheries Association Regional Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 2/6/2003
Publication Date: 2/24/2003
Citation: ARIAS, C., SHOEMAKER, C.A., EVANS, J.J., KLESIUS, P.H. POLYPHASIC APPROACH TO FISH PATHOGENS IDENTIFICATION. Alabama Chapter of the American Fisheries Association Regional Meeting. 2003.

Interpretive Summary:

Technical Abstract: Bacteria identification constitutes one the main challenging areas in microbiology. Working with bacterial pathogens requires rapid and accurate methods for identification. Moreover, identification at species level is usually not enough since most pathogens should be typed at strain level. Different strains among the same species can show different level of virulence, therefore pathogen identification at strain level is crucial in epidemiological studies. Identification under species level is commonly known as bacterial typing. Although there are numerous typing methods, they all can be subdivided into phenotypic and genotypic methods. The best approach for strain identification is to combine profiles or fingerprints generated by both phenotypic and genotypic techniques. In our lab we are using three semi-automatic techniques applied to fish pathogens identification. We are using two techniques based on phenotypic characters and one genomic method. The fist phenotypic method involves the analysis of the cellular Fatty Acid Methyl Ester (FAME) composition. The second phenotypic method is the commercial method Biolog. It is based on the ability of the cells to utilize different compounds as sole carbon source. Finally, the genomic method we are using generates fingerprints based on genome composition and is known as Amplifies Fragment Length Polymorphisms (AFLP). All the information generated is combined in one single computerized library that can be used as an identification library for epidemiological or virulence studies.