ArticleBMC bioinformatics2006
A computational approach to discovering the functions of bacterial phytochromes by analysis of homolog distributions.
Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 10 citations in OpenAlex.
- Phytochrome-mediated shade avoidance responses impact the structure and composition of the bacterial phyllosphere microbiome of Arabidopsis.Environmental microbiome · 2025Article
- Phytochromes inFrontiers in plant science · 2021Review
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1 author at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundPhytochromes are photoreceptors, discovered in plants, that control a wide variety of developmental processes. They have also been found in bacteria and fungi, but for many species their biological role remains obscure. This work concentrates on the phytochrome system of Agrobacterium tumefaciens, a non-photosynthetic soil bacterium with two phytochromes. To identify proteins that might share common functions with phytochromes, a co-distribution analysis was performed on the basis of protein sequences from 138 bacteria.
resultsA database of protein sequences from 138 bacteria was generated. Each sequence was BLASTed against the entire database. The homolog distribution of each query protein was then compared with the homolog distribution of every other protein (target protein) of the same species, and the target proteins were sorted according to their probability of co-distribution under random conditions. As query proteins, phytochromes from Agrobacterium tumefaciens, Pseudomonas aeruginosa, Deinococcus radiodurans and Synechocystis PCC 6803 were chosen along with several phytochrome-related proteins from A. tumefaciens. The Synechocystis photosynthesis protein D1 was selected as a control. In the D1 analyses, the ratio between photosynthesis-related proteins and those not related to photosynthesis among the top 150 in the co-distribution tables was > 3:1, showing that the method is appropriate for finding partner proteins with common functions. The co-distribution of phytochromes with other histidine kinases was remarkably high, although most co-distributed histidine kinases were not direct BLAST homologs of the query protein. This finding implies that phytochromes and other histidine kinases share common functions as parts of signalling networks. All phytochromes tested, with one exception, also revealed a remarkably high co-distribution with glutamate synthase and methionine synthase. This result implies a general role of bacterial phytochromes in ammonium assimilation and amino acid metabolism.
conclusionIt was possible to identify several proteins that might share common functions with bacterial phytochromes by the co-distribution approach. This computational approach might also be helpful in other cases.
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