Chapter title |
Bacterial Interactomes: From Interactions to Networks
|
---|---|
Chapter number | 2 |
Book title |
Bacterial Molecular Networks
|
Published in |
Methods in molecular biology, January 2012
|
DOI | 10.1007/978-1-61779-361-5_2 |
Pubmed ID | |
Book ISBNs |
978-1-61779-360-8, 978-1-61779-361-5
|
Authors |
Emmanuelle Bouveret, Christine Brun, Bouveret, Emmanuelle, Brun, Christine |
Abstract |
In order to ensure their function(s) in the cell, proteins are organized in machineries, underlaid by a complex network of interactions. Identifying protein interactions is thus crucial to our understanding of cell functioning. Technical advances in molecular biology and genomic technology now allow for the systematic study of the interactions occurring in a given organism. This review first presents the techniques readily available to microbiologists for studying protein-protein interactions in bacteria, as well as their usability for high-throughput studies. Two types of techniques need to be considered: (1) the isolation of protein complexes from the organism of interest by affinity purification, and subsequent identification of the complex partners by mass spectrometry and (2) two-hybrid techniques, in general based on the production of two recombinant proteins whose interaction has to be tested in a reporter cell. Next, we summarize the bacterial interactomes already published. Finally, the strengths and pitfalls of the techniques are discussed, together with the potential prospect of interactome studies in bacteria. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
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Scientists | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 2 | 6% |
Turkey | 1 | 3% |
Unknown | 32 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 10 | 29% |
Researcher | 9 | 26% |
Student > Postgraduate | 3 | 9% |
Student > Bachelor | 2 | 6% |
Professor | 2 | 6% |
Other | 6 | 17% |
Unknown | 3 | 9% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 15 | 43% |
Biochemistry, Genetics and Molecular Biology | 4 | 11% |
Computer Science | 3 | 9% |
Veterinary Science and Veterinary Medicine | 1 | 3% |
Social Sciences | 1 | 3% |
Other | 3 | 9% |
Unknown | 8 | 23% |