Trending and strain-typing microbes

Published: 7-May-2012

In industrial settings characterisation of micro-organisms is an important part of the comprehensive environmental monitoring programme. Strain-typing is the best resource in the case of a major excursion or sterility failure where characterisation to the strain level can be critical. Currently, there are two methods primarily used to differentiate accurately and reproducibly between closely related micro-organisms: ribotyping and single- and multi-locus sequence typing (S/MLST).

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In this second article on microbial identification methods, Accugenix describes methods of tracking and trending organisms at species level and strain-typing in the case of sterility failure or for probiotic health claims.

In industrial settings, such as those for dietary supplement manufacture, strain- typing, or characterisation of micro-organisms, is an important part of the comprehensive environmental monitoring (EM) programme. Of equal importance to the probiotics and nutraceutical industries is the confirmation of specific bacterial strains used for production.

While standard genotypic and proteotypic identification methods increase the ability to identify accurately and consistently and track and trend micro-organisms at the species level, some common microbes cannot be resolved with these approaches alone. Furthermore, strain-typing is the best resource in the case of a major excursion or sterility failure where characterisation to the strain level can be critical.

Subspecies level identification or strain- typing of micro-organisms, as well as discrimination between closely related species, is a challenging goal but necessary since this analysis is very important in investigating a root cause. Some of the common approaches used to differentiate closely related strains compare organisms by considering their genotypic, phenotypic, serological, spatial or temporal characteristics. While the combination of these traits can result in subspecies level identifications, the analysis of multiple characteristics increases the time, labour and expense needed to differentiate isolates, as well as increasing the errors that can arise from qualitative and subjective analyses.

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