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      Global Analysis of Photosynthesis Transcriptional Regulatory Networks

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          Abstract

          Photosynthesis is a crucial biological process that depends on the interplay of many components. This work analyzed the gene targets for 4 transcription factors: FnrL, PrrA, CrpK and MppG (RSP_2888), which are known or predicted to control photosynthesis in Rhodobacter sphaeroides. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) identified 52 operons under direct control of FnrL, illustrating its regulatory role in photosynthesis, iron homeostasis, nitrogen metabolism and regulation of sRNA synthesis. Using global gene expression analysis combined with ChIP-seq, we mapped the regulons of PrrA, CrpK and MppG. PrrA regulates ∼34 operons encoding mainly photosynthesis and electron transport functions, while CrpK, a previously uncharacterized Crp-family protein, regulates genes involved in photosynthesis and maintenance of iron homeostasis. Furthermore, CrpK and FnrL share similar DNA binding determinants, possibly explaining our observation of the ability of CrpK to partially compensate for the growth defects of a ΔFnrL mutant. We show that the Rrf2 family protein, MppG, plays an important role in photopigment biosynthesis, as part of an incoherent feed-forward loop with PrrA. Our results reveal a previously unrealized, high degree of combinatorial regulation of photosynthetic genes and significant cross-talk between their transcriptional regulators, while illustrating previously unidentified links between photosynthesis and the maintenance of iron homeostasis.

          Author Summary

          Photosynthetic organisms are among the most abundant life forms on earth. Their unique ability to harvest solar energy and use it to fix atmospheric carbon dioxide is at the foundation of the global food chain. This paper reports the first comprehensive analysis of networks that control expression of photosynthesis genes using Rhodobacter sphaeroides, a microbe that has been studied for decades as a model of solar energy capture and other aspects of the photosynthetic lifestyle. We find a previously unappreciated complexity in the level of control of photosynthetic genes, while identifying new links between photosynthesis and central processes like iron availability. This organism is an ancestor of modern day plants, so our data can inform studies in other photosynthetic organisms and improve our ability to harness solar energy for food and industrial processes.

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          The Pfam protein families database.

          Pfam is a large collection of protein families and domains. Over the past 2 years the number of families in Pfam has doubled and now stands at 6190 (version 10.0). Methodology improvements for searching the Pfam collection locally as well as via the web are described. Other recent innovations include modelling of discontinuous domains allowing Pfam domain definitions to be closer to those found in structure databases. Pfam is available on the web in the UK (http://www.sanger.ac.uk/Software/Pfam/), the USA (http://pfam.wustl.edu/), France (http://pfam.jouy.inra.fr/) and Sweden (http://Pfam.cgb.ki.se/).
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            Signal processing in complex chemotaxis pathways.

            Bacteria use chemotaxis to migrate towards environments that are better for growth. Chemoreceptors detect changes in attractant levels and signal through two-component systems to control swimming direction. This basic pathway is conserved across all chemotactic bacteria and archaea; however, recent work combining systems biology and genome sequencing has started to elucidate the additional complexity of the process in many bacterial species. This article focuses on one of the best understood complex networks, which is found in Rhodobacter sphaeroides and integrates sensory data about the external environment and the metabolic state of the cell to produce a balanced response at the flagellar motor.
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              The bacterial LexA transcriptional repressor.

              Bacteria respond to DNA damage by mounting a coordinated cellular response, governed by the RecA and LexA proteins. In Escherichia coli, RecA stimulates cleavage of the LexA repressor, inducing more than 40 genes that comprise the SOS global regulatory network. The SOS response is widespread among bacteria and exhibits considerable variation in its composition and regulation. In some well-characterised pathogens, induction of the SOS response modulates the evolution and dissemination of drug resistance, as well as synthesis, secretion and dissemination of the virulence. In this review, we discuss the structure of LexA protein, particularly with respect to distinct conformations that enable repression of SOS genes via specific DNA binding or repressor cleavage during the response to DNA damage. These may provide new starting points in the battle against the emergence of bacterial pathogens and the spread of drug resistance among them.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                December 2014
                11 December 2014
                : 10
                : 12
                : e1004837
                Affiliations
                [1 ]Program in Cellular and Molecular Biology, University of Wisconsin – Madison, Madison, Wisconsin, United States of America
                [2 ]Department of Bacteriology, University of Wisconsin – Madison, Wisconsin Energy Institute, Madison, Wisconsin, United States of America
                [3 ]DOE Great Lakes Bioenergy Research Center, University of Wisconsin – Madison, Madison, Wisconsin, United States of America
                [4 ]Department of Civil and Environmental Engineering, University of Wisconsin – Madison, Madison, Wisconsin, United States of America
                University of Geneva Medical School, Switzerland
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: SI DRN TJD. Performed the experiments: SI. Analyzed the data: SI DRN TJD. Contributed reagents/materials/analysis tools: SI. Wrote the paper: SI DRN TJD.

                Article
                PGENETICS-D-14-00876
                10.1371/journal.pgen.1004837
                4263372
                25503406
                436fb9b3-ff5d-4fed-ad7d-0593d96e6c4b
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 29 March 2014
                : 20 October 2014
                Page count
                Pages: 21
                Funding
                This work was funded in part by the DOE Great Lakes Bioenergy Research Center (DOE Office of Science BER DE- FC02 - ­ 07ER64494). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and life sciences
                Biochemistry
                Proteins
                DNA-binding proteins
                Transcription Factors
                Transcription Activators
                Computational Biology
                Genome Analysis
                Transcriptome Analysis
                Genome Expression Analysis
                Next-Generation Sequencing
                Genetic Networks
                Comparative Genomics
                Gene Regulatory Networks
                Genome Evolution
                Genetics
                Gene expression
                DNA transcription
                Gene regulation
                Genomics
                Microbial Genomics
                Gene Function
                Gene Identification and Analysis
                Microbiology
                Bacteriology
                Bacterial Physiology
                Microbial Physiology
                Microbial Metabolism
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All microarray and ChIP-seq datasets generated for this study have been deposited in GEO under the accession GSE58717.

                Genetics
                Genetics

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