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Taboada-Castro H, Gil J, Gómez-Caudillo L, Escorcia-Rodríguez JM, Freyre-González JA, Encarnación-Guevara S. Rhizobium etli CFN42 proteomes showed isoenzymes in free-living and symbiosis with a different transcriptional regulation inferred from a transcriptional regulatory network. Front Microbiol 2022; 13:947678. [PMID: 36312930 PMCID: PMC9611204 DOI: 10.3389/fmicb.2022.947678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 09/05/2022] [Indexed: 11/13/2022] Open
Abstract
A comparative proteomic study at 6 h of growth in minimal medium (MM) and bacteroids at 18 days of symbiosis of Rhizobium etli CFN42 with the Phaseolus vulgaris leguminous plant was performed. A gene ontology classification of proteins in MM and bacteroid, showed 31 and 10 pathways with higher or equal than 30 and 20% of proteins with respect to genome content per pathway, respectively. These pathways were for energy and environmental compound metabolism, contributing to understand how Rhizobium is adapted to the different conditions. Metabolic maps based on orthology of the protein profiles, showed 101 and 74 functional homologous proteins in the MM and bacteroid profiles, respectively, which were grouped in 34 different isoenzymes showing a great impact in metabolism by covering 60 metabolic pathways in MM and symbiosis. Taking advantage of co-expression of transcriptional regulators (TF’s) in the profiles, by selection of genes whose matrices were clustered with matrices of TF’s, Transcriptional Regulatory networks (TRN´s) were deduced by the first time for these metabolic stages. In these clustered TF-MM and clustered TF-bacteroid networks, containing 654 and 246 proteins, including 93 and 46 TFs, respectively, showing valuable information of the TF’s and their regulated genes with high stringency. Isoenzymes were specific for adaptation to the different conditions and a different transcriptional regulation for MM and bacteroid was deduced. The parameters of the TRNs of these expected biological networks and biological networks of E. coli and B. subtilis segregate from the random theoretical networks. These are useful data to design experiments on TF gene–target relationships for bases to construct a TRN.
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Affiliation(s)
- Hermenegildo Taboada-Castro
- Proteomics Laboratory, Program of Functional Genomics of Prokaryotes, Center for Genomic Sciences, National Autonomous University of Mexico, Cuernavaca, Morelos, Mexico
| | - Jeovanis Gil
- Division of Oncology, Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Lund, Sweden
| | - Leopoldo Gómez-Caudillo
- Proteomics Laboratory, Program of Functional Genomics of Prokaryotes, Center for Genomic Sciences, National Autonomous University of Mexico, Cuernavaca, Morelos, Mexico
| | - Juan Miguel Escorcia-Rodríguez
- Regulatory Systems Biology Research Group, Program of Systems Biology, Center for Genomic Sciences, National Autonomous University of Mexico, Mexico City, Mexico
| | - Julio Augusto Freyre-González
- Regulatory Systems Biology Research Group, Program of Systems Biology, Center for Genomic Sciences, National Autonomous University of Mexico, Mexico City, Mexico
| | - Sergio Encarnación-Guevara
- Proteomics Laboratory, Program of Functional Genomics of Prokaryotes, Center for Genomic Sciences, National Autonomous University of Mexico, Cuernavaca, Morelos, Mexico
- *Correspondence: Sergio Encarnacion Guevara,
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Ma JX, Yang Y, Li G, Ma BG. Computationally Reconstructed Interactome of Bradyrhizobium diazoefficiens USDA110 Reveals Novel Functional Modules and Protein Hubs for Symbiotic Nitrogen Fixation. Int J Mol Sci 2021; 22:11907. [PMID: 34769335 PMCID: PMC8584416 DOI: 10.3390/ijms222111907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 10/22/2021] [Accepted: 10/28/2021] [Indexed: 11/16/2022] Open
Abstract
Symbiotic nitrogen fixation is an important part of the nitrogen biogeochemical cycles and the main nitrogen source of the biosphere. As a classical model system for symbiotic nitrogen fixation, rhizobium-legume systems have been studied elaborately for decades. Details about the molecular mechanisms of the communication and coordination between rhizobia and host plants is becoming clearer. For more systematic insights, there is an increasing demand for new studies integrating multiomics information. Here, we present a comprehensive computational framework integrating the reconstructed protein interactome of B. diazoefficiens USDA110 with its transcriptome and proteome data to study the complex protein-protein interaction (PPI) network involved in the symbiosis system. We reconstructed the interactome of B. diazoefficiens USDA110 by computational approaches. Based on the comparison of interactomes between B. diazoefficiens USDA110 and other rhizobia, we inferred that the slow growth of B. diazoefficiens USDA110 may be due to the requirement of more protein modifications, and we further identified 36 conserved functional PPI modules. Integrated with transcriptome and proteome data, interactomes representing free-living cell and symbiotic nitrogen-fixing (SNF) bacteroid were obtained. Based on the SNF interactome, a core-sub-PPI-network for symbiotic nitrogen fixation was determined and nine novel functional modules and eleven key protein hubs playing key roles in symbiosis were identified. The reconstructed interactome of B. diazoefficiens USDA110 may serve as a valuable reference for studying the mechanism underlying the SNF system of rhizobia and legumes.
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Affiliation(s)
| | | | | | - Bin-Guang Ma
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China; (J.-X.M.); (Y.Y.); (G.L.)
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Taboada-Castro H, Castro-Mondragón JA, Aguilar-Vera A, Hernández-Álvarez AJ, van Helden J, Encarnación-Guevara S. RhizoBindingSites, a Database of DNA-Binding Motifs in Nitrogen-Fixing Bacteria Inferred Using a Footprint Discovery Approach. Front Microbiol 2020; 11:567471. [PMID: 33250866 PMCID: PMC7674921 DOI: 10.3389/fmicb.2020.567471] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 10/13/2020] [Indexed: 11/30/2022] Open
Abstract
Basic knowledge of transcriptional regulation is needed to understand the mechanisms governing biological processes, i.e., nitrogen fixation by Rhizobiales bacteria in symbiosis with leguminous plants. The RhizoBindingSites database is a computer-assisted framework providing motif-gene-associated conserved sequences potentially implicated in transcriptional regulation in nine symbiotic species. A dyad analysis algorithm was used to deduce motifs in the upstream regulatory region of orthologous genes, and only motifs also located in the gene seed promoter with a p-value of 1e-4 were accepted. A genomic scan analysis of the upstoream sequences with these motifs was performed. These predicted binding sites were categorized according to low, medium and high homology between the matrix and the upstream regulatory sequence. On average, 62.7% of the genes had a motif, accounting for 80.44% of the genes per genome, with 19613 matrices (a matrix is a representation of a motif). The RhizoBindingSites database provides motif and gene information, motif conservation in the order Rhizobiales, matrices, motif logos, regulatory networks constructed from theoretical or experimental data, a criterion for selecting motifs and a guide for users. The RhizoBindingSites database is freely available online at rhizobindingsites.ccg.unam.mx.
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Affiliation(s)
| | | | - Alejandro Aguilar-Vera
- Center for Genomic Sciences, National Autonomous University of Mexico, Cuernavaca, Mexico
| | | | - Jacques van Helden
- CNRS, IFB-core, UMS 3601, Institut Français de Bioinformatique, Évry, France.,Laboratoire Theory and Approaches of Genome Complexity (TAGC), Inserm, Aix-Marseille Univ, Marseille, France
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Clark TJ, Friel CA, Grman E, Shachar‐Hill Y, Friesen ML. Modelling nutritional mutualisms: challenges and opportunities for data integration. Ecol Lett 2017; 20:1203-1215. [DOI: 10.1111/ele.12810] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2016] [Revised: 08/23/2016] [Accepted: 06/12/2017] [Indexed: 01/09/2023]
Affiliation(s)
- Teresa J. Clark
- Department of Plant Biology Michigan State University 612 Wilson Rd. East Lansing MI48824 USA
| | - Colleen A. Friel
- Department of Plant Biology Michigan State University 612 Wilson Rd. East Lansing MI48824 USA
| | - Emily Grman
- Biology Department Eastern Michigan University 441 Mark Jefferson Science Complex Ypsilanti MI48197 USA
| | - Yair Shachar‐Hill
- Department of Plant Biology Michigan State University 612 Wilson Rd. East Lansing MI48824 USA
| | - Maren L. Friesen
- Department of Plant Biology Michigan State University 612 Wilson Rd. East Lansing MI48824 USA
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Peng J, Hao B, Liu L, Wang S, Ma B, Yang Y, Xie F, Li Y. RNA-Seq and microarrays analyses reveal global differential transcriptomes of Mesorhizobium huakuii 7653R between bacteroids and free-living cells. PLoS One 2014; 9:e93626. [PMID: 24695521 PMCID: PMC3973600 DOI: 10.1371/journal.pone.0093626] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2013] [Accepted: 03/04/2014] [Indexed: 11/18/2022] Open
Abstract
Mesorhizobium huakuii 7653R occurs either in nitrogen-fixing symbiosis with its host plant, Astragalus sinicus, or free-living in the soil. The M. huakuii 7653R genome has recently been sequenced. To better understand the complex biochemical and developmental changes that occur in 7653R during bacteroid development, RNA-Seq and Microarrays were used to investigate the differential transcriptomes of 7653R bacteroids and free-living cells. The two approaches identified several thousand differentially expressed genes. The most prominent up-regulation occurred in the symbiosis plasmids, meanwhile gene expression is concentrated to a set of genes (clusters) in bacteroids to fulfill corresponding functional requirements. The results suggested that the main energy metabolism is active while fatty acid metabolism is inactive in bacteroid and that most of genes relevant to cell cycle are down-regulated accordingly. For a global analysis, we reconstructed a protein-protein interaction (PPI) network for 7653R and integrated gene expression data into the network using Cytoscape. A highly inter-connected subnetwork, with function enrichment for nitrogen fixation, was found, and a set of hubs and previously uncharacterized genes participating in nitrogen fixation were identified. The results described here provide a broader biological landscape and novel insights that elucidate rhizobial bacteroid differentiation, nitrogen fixation and related novel gene functions.
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Affiliation(s)
- Jieli Peng
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, P. R. China
| | - Baohai Hao
- Center for Bioinformatics, School of Life Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, P. R. China
| | - Liu Liu
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, P. R. China
| | - Shanming Wang
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, P. R. China
| | - Binguang Ma
- Center for Bioinformatics, School of Life Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, P. R. China
| | - Yi Yang
- Center for Bioinformatics, School of Life Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, P. R. China
| | - Fuli Xie
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, P. R. China
| | - Youguo Li
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, P. R. China
- * E-mail:
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Black M, Moolhuijzen P, Chapman B, Barrero R, Howieson J, Hungria M, Bellgard M. The genetics of symbiotic nitrogen fixation: comparative genomics of 14 rhizobia strains by resolution of protein clusters. Genes (Basel) 2012; 3:138-66. [PMID: 24704847 PMCID: PMC3899959 DOI: 10.3390/genes3010138] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2012] [Revised: 02/10/2012] [Accepted: 02/13/2012] [Indexed: 11/16/2022] Open
Abstract
The symbiotic relationship between legumes and nitrogen fixing bacteria is critical for agriculture, as it may have profound impacts on lowering costs for farmers, on land sustainability, on soil quality, and on mitigation of greenhouse gas emissions. However, despite the importance of the symbioses to the global nitrogen cycling balance, very few rhizobial genomes have been sequenced so far, although there are some ongoing efforts in sequencing elite strains. In this study, the genomes of fourteen selected strains of the order Rhizobiales, all previously fully sequenced and annotated, were compared to assess differences between the strains and to investigate the feasibility of defining a core ‘symbiome’—the essential genes required by all rhizobia for nodulation and nitrogen fixation. Comparison of these whole genomes has revealed valuable information, such as several events of lateral gene transfer, particularly in the symbiotic plasmids and genomic islands that have contributed to a better understanding of the evolution of contrasting symbioses. Unique genes were also identified, as well as omissions of symbiotic genes that were expected to be found. Protein comparisons have also allowed the identification of a variety of similarities and differences in several groups of genes, including those involved in nodulation, nitrogen fixation, production of exopolysaccharides, Type I to Type VI secretion systems, among others, and identifying some key genes that could be related to host specificity and/or a better saprophytic ability. However, while several significant differences in the type and number of proteins were observed, the evidence presented suggests no simple core symbiome exists. A more abstract systems biology concept of nitrogen fixing symbiosis may be required. The results have also highlighted that comparative genomics represents a valuable tool for capturing specificities and generalities of each genome.
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Affiliation(s)
- Michael Black
- Centre for Comparative Genomics, Murdoch University, South Street, Murdoch, Perth, WA 6150, Australia.
| | - Paula Moolhuijzen
- Centre for Comparative Genomics, Murdoch University, South Street, Murdoch, Perth, WA 6150, Australia.
| | - Brett Chapman
- Centre for Comparative Genomics, Murdoch University, South Street, Murdoch, Perth, WA 6150, Australia.
| | - Roberto Barrero
- Centre for Comparative Genomics, Murdoch University, South Street, Murdoch, Perth, WA 6150, Australia.
| | - John Howieson
- Centre for Rhizobium Studies, Murdoch University, South Street, Murdoch, Perth, WA 6150, Australia.
| | | | - Matthew Bellgard
- Centre for Comparative Genomics, Murdoch University, South Street, Murdoch, Perth, WA 6150, Australia.
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Cloots L, Marchal K. Network-based functional modeling of genomics, transcriptomics and metabolism in bacteria. Curr Opin Microbiol 2011; 14:599-607. [DOI: 10.1016/j.mib.2011.09.003] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2011] [Revised: 08/28/2011] [Accepted: 09/05/2011] [Indexed: 01/10/2023]
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Zhang W, Li F, Nie L. Integrating multiple 'omics' analysis for microbial biology: application and methodologies. MICROBIOLOGY-SGM 2009; 156:287-301. [PMID: 19910409 DOI: 10.1099/mic.0.034793-0] [Citation(s) in RCA: 356] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Recent advances in various 'omics' technologies enable quantitative monitoring of the abundance of various biological molecules in a high-throughput manner, and thus allow determination of their variation between different biological states on a genomic scale. Several popular 'omics' platforms that have been used in microbial systems biology include transcriptomics, which measures mRNA transcript levels; proteomics, which quantifies protein abundance; metabolomics, which determines abundance of small cellular metabolites; interactomics, which resolves the whole set of molecular interactions in cells; and fluxomics, which establishes dynamic changes of molecules within a cell over time. However, no single 'omics' analysis can fully unravel the complexities of fundamental microbial biology. Therefore, integration of multiple layers of information, the multi-'omics' approach, is required to acquire a precise picture of living micro-organisms. In spite of this being a challenging task, some attempts have been made recently to integrate heterogeneous 'omics' datasets in various microbial systems and the results have demonstrated that the multi-'omics' approach is a powerful tool for understanding the functional principles and dynamics of total cellular systems. This article reviews some basic concepts of various experimental 'omics' approaches, recent application of the integrated 'omics' for exploring metabolic and regulatory mechanisms in microbes, and advances in computational and statistical methodologies associated with integrated 'omics' analyses. Online databases and bioinformatic infrastructure available for integrated 'omics' analyses are also briefly discussed.
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Affiliation(s)
- Weiwen Zhang
- Center for Ecogenomics, Biodesign Institute, Arizona State University, Tempe, AZ 85287-6501, USA
| | - Feng Li
- Division of Biometrics II, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA
| | - Lei Nie
- Division of Biometrics IV, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD 20993-0002, USA
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