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Current Proteomics

Editor-in-Chief

ISSN (Print): 1570-1646
ISSN (Online): 1875-6247

Proteomics as a Tool to Study Microbial Interactions

Author(s): Petter Melin

Volume 1, Issue 1, 2004

Page: [27 - 34] Pages: 8

DOI: 10.2174/1570164043488261

Abstract

In microbial ecology, researchers have started to use a great variety of methods initially developed by molecular biologists. Mostly, these studies have dealt with microbial diversity in specific environments. Recently, new questions have been raised, e.g. what changes occur within a microbial community during competition or after a change in the surrounding environment? For this, molecular tools such as mRNA differential display, microarrays and proteomics can be employed. In this review, the use of proteomics for studies of microbial interactions is discussed. One aspect of competition between microbes can be simulated by treatment of one microbe with antibiotics produced by a competing microbe. A more complicated approach involves co-cultivation of the competitors. In order to reveal species-specific protein patterns, it is advisable to maintain the organisms separated. In a somewhat reversed experimental design, the target gene for an antibiotic is disrupted, and changes in the mutant proteome are subsequently screened for. Generally, a proteomic study will reveal proteins with both expected and surprising changes in abundance upon competition, but also previously unknown proteins are likely to be identified. It is obvious that most antibiotics can trigger secondary responses, which will result in a change of abundance of several proteins. However, an approach based on proteomics alone may not be sufficient to obtain a complete data set for describing microbial interactions. Therefore, further studies are necessary for proteins whose quantitative profile changes, e.g. by generating knockout strains for phenotypic analysis. Despite some inherent limitations, proteomics is a useful method, and an important complement to other approaches for studies of microbial interactions.

Keywords: proteomics, proteome analysis, microbial interactions, microorganisms, fungi, yeasts, bacteria, antibiotics


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