1
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Hustmyer CM, Landick R. Bacterial chromatin proteins, transcription, and DNA topology: Inseparable partners in the control of gene expression. Mol Microbiol 2024. [PMID: 38847475 DOI: 10.1111/mmi.15283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 05/10/2024] [Accepted: 05/13/2024] [Indexed: 06/15/2024]
Abstract
DNA in bacterial chromosomes is organized into higher-order structures by DNA-binding proteins called nucleoid-associated proteins (NAPs) or bacterial chromatin proteins (BCPs). BCPs often bind to or near DNA loci transcribed by RNA polymerase (RNAP) and can either increase or decrease gene expression. To understand the mechanisms by which BCPs alter transcription, one must consider both steric effects and the topological forces that arise when DNA deviates from its fully relaxed double-helical structure. Transcribing RNAP creates DNA negative (-) supercoils upstream and positive (+) supercoils downstream whenever RNAP and DNA are unable to rotate freely. This (-) and (+) supercoiling generates topological forces that resist forward translocation of DNA through RNAP unless the supercoiling is constrained by BCPs or relieved by topoisomerases. BCPs also may enhance topological stress and overall can either inhibit or aid transcription. Here, we review current understanding of how RNAP, BCPs, and DNA topology interplay to control gene expression.
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Affiliation(s)
- Christine M Hustmyer
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Robert Landick
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, USA
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2
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Pan RW, Röschinger T, Faizi K, Garcia H, Phillips R. Deciphering regulatory architectures from synthetic single-cell expression patterns. ARXIV 2024:arXiv:2401.15880v2. [PMID: 38351929 PMCID: PMC10862939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
For the vast majority of genes in sequenced genomes, there is limited understanding of how they are regulated. Without such knowledge, it is not possible to perform a quantitative theory-experiment dialogue on how such genes give rise to physiological and evolutionary adaptation. One category of high-throughput experiments used to understand the sequence-phenotype relationship of the transcriptome is massively parallel reporter assays (MPRAs). However, to improve the versatility and scalability of MPRA pipelines, we need a "theory of the experiment" to help us better understand the impact of various biological and experimental parameters on the interpretation of experimental data. These parameters include binding site copy number, where a large number of specific binding sites may titrate away transcription factors, as well as the presence of overlapping binding sites, which may affect analysis of the degree of mutual dependence between mutations in the regulatory region and expression levels. To that end, in this paper we create tens of thousands of synthetic single-cell gene expression outputs using both equilibrium and out-of-equilibrium models. These models make it possible to imitate the summary statistics (information footprints and expression shift matrices) used to characterize the output of MPRAs and from this summary statistic to infer the underlying regulatory architecture. Specifically, we use a more refined implementation of the so-called thermodynamic models in which the binding energies of each sequence variant are derived from energy matrices. Our simulations reveal important effects of the parameters on MPRA data and we demonstrate our ability to optimize MPRA experimental designs with the goal of generating thermodynamic models of the transcriptome with base-pair specificity. Further, this approach makes it possible to carefully examine the mapping between mutations in binding sites and their corresponding expression profiles, a tool useful not only for better designing MPRAs, but also for exploring regulatory evolution.
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Affiliation(s)
- Rosalind Wenshan Pan
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Tom Röschinger
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Kian Faizi
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Hernan Garcia
- Biophysics Graduate Group, University of California, Berkeley, CA
- Department of Physics, University of California, Berkeley, CA
- Department of Molecular and Cell Biology, University of California, Berkeley, CA
- Institute for Quantitative Biosciences-QB3, University of California, Berkeley, CA
| | - Rob Phillips
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
- Department of Physics, California Institute of Technology, Pasadena, CA
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3
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Pan RW, Röschinger T, Faizi K, Garcia H, Phillips R. Deciphering regulatory architectures from synthetic single-cell expression patterns. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.28.577658. [PMID: 38352569 PMCID: PMC10862715 DOI: 10.1101/2024.01.28.577658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
For the vast majority of genes in sequenced genomes, there is limited understanding of how they are regulated. Without such knowledge, it is not possible to perform a quantitative theory-experiment dialogue on how such genes give rise to physiological and evolutionary adaptation. One category of high-throughput experiments used to understand the sequence-phenotype relationship of the transcriptome is massively parallel reporter assays (MPRAs). However, to improve the versatility and scalability of MPRA pipelines, we need a "theory of the experiment" to help us better understand the impact of various biological and experimental parameters on the interpretation of experimental data. These parameters include binding site copy number, where a large number of specific binding sites may titrate away transcription factors, as well as the presence of overlapping binding sites, which may affect analysis of the degree of mutual dependence between mutations in the regulatory region and expression levels. To that end, in this paper we create tens of thousands of synthetic single-cell gene expression outputs using both equilibrium and out-of-equilibrium models. These models make it possible to imitate the summary statistics (information footprints and expression shift matrices) used to characterize the output of MPRAs and from this summary statistic to infer the underlying regulatory architecture. Specifically, we use a more refined implementation of the so-called thermodynamic models in which the binding energies of each sequence variant are derived from energy matrices. Our simulations reveal important effects of the parameters on MPRA data and we demonstrate our ability to optimize MPRA experimental designs with the goal of generating thermodynamic models of the transcriptome with base-pair specificity. Further, this approach makes it possible to carefully examine the mapping between mutations in binding sites and their corresponding expression profiles, a tool useful not only for better designing MPRAs, but also for exploring regulatory evolution. Author summary With the rapid advancement of sequencing technology, there has been an exponential increase in the amount of data on the genomic sequences of diverse organisms. Nevertheless, deciphering the sequence-phenotype mapping of the genomic data remains a formidable task, especially when dealing with non-coding sequences such as the promoter. In current databases, annotations on transcription factor binding sites are sorely lacking, which creates a challenge for developing a systematic theory of transcriptional regulation. To address this gap in knowledge, high-throughput methods such as massively parallel reporter assays (MPRAs) have been employed to decipher the regulatory genome. In this work, we make use of thermodynamic models to computationally simulate MPRAs in the context of transcriptional regulation and produce thousands of synthetic MPRA datasets. We examine how well typical experimental and data analysis procedures of MPRAs are able to recover common regulatory architectures under different sets of experimental and biological parameters. By establishing a dialogue between high-throughput experiments and a physical theory of transcription, our efforts serve to both improve current experimental procedures and enhancing our broader understanding of the sequence-function landscape of regulatory sequences.
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4
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Singh M, Chandra D, Jagdish S, Nandi D. Global transcriptome analysis reveals Salmonella Typhimurium employs nitrate metabolism to combat bile stress. FEBS Lett 2024. [PMID: 38503554 DOI: 10.1002/1873-3468.14853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 02/20/2024] [Accepted: 02/21/2024] [Indexed: 03/21/2024]
Abstract
Salmonella Typhimurium is an enteric pathogen that is highly tolerant to bile. Next-generation mRNA sequencing was performed to analyze the adaptive responses to bile in two S. Typhimurium strains: wild type (WT) and a mutant lacking cold shock protein E (ΔcspE). CspE is an RNA chaperone which is crucial for survival of S. Typhimurium during bile stress. This study identifies transcriptional responses in bile-tolerant WT and bile-sensitive ΔcspE. Upregulation of several genes involved in nitrate metabolism was observed, including fnr, a global regulator of nitrate metabolism. Notably, Δfnr was susceptible to bile stress. Also, complementation with fnr lowered reactive oxygen species and enhanced the survival of bile-sensitive ΔcspE. Importantly, intracellular nitrite amounts were highly induced in bile-treated WT compared to ΔcspE. Also, the WT strain pre-treated with nitrate displayed better growth with bile. These results demonstrate that nitrate-dependent metabolism promotes adaptation of S. Typhimurium to bile.
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Affiliation(s)
- Madhulika Singh
- Department of Biochemistry, Indian Institute of Science, Bangalore, India
| | - Deepti Chandra
- Department of Biochemistry, Indian Institute of Science, Bangalore, India
| | - Sirisha Jagdish
- Department of Biochemistry, Indian Institute of Science, Bangalore, India
| | - Dipankar Nandi
- Department of Biochemistry, Indian Institute of Science, Bangalore, India
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5
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Yang H, Zhang B, Wu Z, Pan J, Chen L, Xiu X, Cai X, Liu Z, Zheng Y. Synergistic application of atmospheric and room temperature plasma mutagenesis and adaptive laboratory evolution improves the tolerance of Escherichia coli to L-cysteine. Biotechnol J 2024; 19:e2300648. [PMID: 38403408 DOI: 10.1002/biot.202300648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 01/16/2024] [Accepted: 01/27/2024] [Indexed: 02/27/2024]
Abstract
L-Cysteine production through fermentation stands as a promising technology. However, excessive accumulation of L-cysteine poses a challenge due to the potential to inflict damage on cellular DNA. In this study, we employed a synergistic approach encompassing atmospheric and room temperature plasma mutagenesis (ARTP) and adaptive laboratory evolution (ALE) to improve L-cysteine tolerance in Escherichia coli. ARTP-treated populations obtained substantial enhancement in L-cysteine tolerance by ALE. Whole-genome sequencing, transcription analysis, and reverse engineering, revealed the pivotal role of an effective export mechanism mediated by gene eamB in augmenting L-cysteine resistance. The isolated tolerant strain, 60AP03/pTrc-cysEf , achieved a 2.2-fold increase in L-cysteine titer by overexpressing the critical gene cysEf during batch fermentation, underscoring its enormous potential for L-cysteine production. The production evaluations, supplemented with L-serine, further demonstrated the stability and superiority of tolerant strains in L-cysteine production. Overall, our work highlighted the substantial impact of the combined ARTP and ALE strategy in increasing the tolerance of E. coli to L-cysteine, providing valuable insights into improving L-cysteine overproduction, and further emphasized the potential of biotechnology in industrial production.
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Affiliation(s)
- Hui Yang
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
| | - Bo Zhang
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
| | - Zidan Wu
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
| | - Jiayuan Pan
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
| | - Lifeng Chen
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
| | - Xiaoling Xiu
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
| | - Xue Cai
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
| | - Zhiqiang Liu
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
| | - Yuguo Zheng
- The National and Local Joint Engineering Research Center for Biomanufacturing of Chiral Chemicals, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
- Key Laboratory of Bioorganic Synthesis of Zhejiang Province, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, P. R. China
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Salgado H, Gama-Castro S, Lara P, Mejia-Almonte C, Alarcón-Carranza G, López-Almazo AG, Betancourt-Figueroa F, Peña-Loredo P, Alquicira-Hernández S, Ledezma-Tejeida D, Arizmendi-Zagal L, Mendez-Hernandez F, Diaz-Gomez AK, Ochoa-Praxedis E, Muñiz-Rascado LJ, García-Sotelo JS, Flores-Gallegos FA, Gómez L, Bonavides-Martínez C, del Moral-Chávez VM, Hernández-Alvarez AJ, Santos-Zavaleta A, Capella-Gutierrez S, Gelpi JL, Collado-Vides J. RegulonDB v12.0: a comprehensive resource of transcriptional regulation in E. coli K-12. Nucleic Acids Res 2024; 52:D255-D264. [PMID: 37971353 PMCID: PMC10767902 DOI: 10.1093/nar/gkad1072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/25/2023] [Accepted: 11/02/2023] [Indexed: 11/19/2023] Open
Abstract
RegulonDB is a database that contains the most comprehensive corpus of knowledge of the regulation of transcription initiation of Escherichia coli K-12, including data from both classical molecular biology and high-throughput methodologies. Here, we describe biological advances since our last NAR paper of 2019. We explain the changes to satisfy FAIR requirements. We also present a full reconstruction of the RegulonDB computational infrastructure, which has significantly improved data storage, retrieval and accessibility and thus supports a more intuitive and user-friendly experience. The integration of graphical tools provides clear visual representations of genetic regulation data, facilitating data interpretation and knowledge integration. RegulonDB version 12.0 can be accessed at https://regulondb.ccg.unam.mx.
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Affiliation(s)
- Heladia Salgado
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Socorro Gama-Castro
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Paloma Lara
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Citlalli Mejia-Almonte
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Gabriel Alarcón-Carranza
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Andrés G López-Almazo
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Felipe Betancourt-Figueroa
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Pablo Peña-Loredo
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | | | - Daniela Ledezma-Tejeida
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Lizeth Arizmendi-Zagal
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Francisco Mendez-Hernandez
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Ana K Diaz-Gomez
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Elizabeth Ochoa-Praxedis
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Luis J Muñiz-Rascado
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Jair S García-Sotelo
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Querétaro 76230, Querétaro, Mexico
| | - Fanny A Flores-Gallegos
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Laura Gómez
- Instituto Nacional de Medicina Genómica, Periférico Sur 4809, Arenal Tepepan, Tlalpan, 14610 Ciudad de México, Mexico
- Escuela de Medicina, Tecnológico de Monterrey, Campus Ciudad de México, CDMX 14380, Meéxico
| | - César Bonavides-Martínez
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | - Víctor M del Moral-Chávez
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
| | | | - Alberto Santos-Zavaleta
- Instituto de Energías Renovables, Universidad Nacional Autónoma de México, Temixco, Morelos 62580, Meéxico
| | | | - Josep Lluis Gelpi
- Department of Biochemistry and Molecular Biomedicine. Univ. of Barcelona. Av. Diagonal 643, 08028, Barcelona, Spain
- Centre for Genomic Regulation (CRG), Universitat Pompeu Fabra(UPF), Dr. Aiguader 88, Barcelona, 08003, Barcelona, Spain
| | - Julio Collado-Vides
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos 62210, Mexico
- Centre for Genomic Regulation (CRG), Universitat Pompeu Fabra(UPF), Dr. Aiguader 88, Barcelona, 08003, Barcelona, Spain
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall. Boston, MA 02215, USA
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7
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Huang Y, Wipat A, Bacardit J. Transcriptional biomarker discovery toward building a load stress reporting system for engineered Escherichia coli strains. Biotechnol Bioeng 2024; 121:355-365. [PMID: 37807718 PMCID: PMC10953381 DOI: 10.1002/bit.28567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 09/15/2023] [Accepted: 09/25/2023] [Indexed: 10/10/2023]
Abstract
Foreign proteins are produced by introducing synthetic constructs into host bacteria for biotechnology applications. This process can cause resource competition between synthetic circuits and host cells, placing a metabolic burden on the host cells which may result in load stress and detrimental physiological changes. Consequently, the host bacteria can experience slow growth, and the synthetic system may suffer from suboptimal function. To help in the detection of bacterial load stress, we developed machine-learning strategies to select a minimal number of genes that could serve as biomarkers for the design of load stress reporters. We identified pairs of biomarkers that showed discriminative capacity to detect the load stress states induced in 41 engineered Escherichia coli strains.
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Affiliation(s)
- Yiming Huang
- Interdisciplinary Computing and Complex BioSystems GroupNewcastle UniversityNewcastle upon TyneUK
| | - Anil Wipat
- Interdisciplinary Computing and Complex BioSystems GroupNewcastle UniversityNewcastle upon TyneUK
| | - Jaume Bacardit
- Interdisciplinary Computing and Complex BioSystems GroupNewcastle UniversityNewcastle upon TyneUK
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Li C, Yin L, He X, Jin Y, Zhu X, Wu R. Competition-cooperation mechanism between Escherichia coli and Staphylococcus aureus based on systems mapping. Front Microbiol 2023; 14:1192574. [PMID: 38029174 PMCID: PMC10657823 DOI: 10.3389/fmicb.2023.1192574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 10/23/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction Interspecies interactions are a crucial driving force of species evolution. The genes of each coexisting species play a pivotal role in shaping the structure and function within the community, but how to identify them at the genome-wide level has always been challenging. Methods In this study, we embed the Lotka-Volterra ordinary differential equations in the theory of community ecology into the systems mapping model, so that this model can not only describe how the quantitative trait loci (QTL) of a species directly affects its own phenotype, but also describe the QTL of the species how to indirectly affect the phenotype of its interacting species, and how QTL from different species affects community behavior through epistatic interactions. Results By designing and implementing a co-culture experiment for 100 pairs of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), we mapped 244 significant QTL combinations in the interaction process of the two bacteria using this model, including 69 QTLs from E. coli and 59 QTLs from S. aureus, respectively. Through gene annotation, we obtained 57 genes in E. coli, among which the genes with higher frequency were ypdC, nrfC, yphH, acrE, dcuS, rpnE, and ptsA, while we obtained 43 genes in S. aureus, among which the genes with higher frequency were ebh, SAOUHSC_00172, capF, gdpP, orfX, bsaA, and phnE1. Discussion By dividing the overall growth into independent growth and interactive growth, we could estimate how QTLs modulate interspecific competition and cooperation. Based on the quantitative genetic model, we can obtain the direct genetic effect, indirect genetic effect, and genome-genome epistatic effect related to interspecific interaction genes, and then further mine the hub genes in the QTL networks, which will be particularly useful for inferring and predicting the genetic mechanisms of community dynamics and evolution. Systems mapping can provide a tool for studying the mechanism of competition and cooperation among bacteria in co-culture, and this framework can lay the foundation for a more comprehensive and systematic study of species interactions.
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Affiliation(s)
- Caifeng Li
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Lixin Yin
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Xiaoqing He
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, Beijing Forestry University, Beijing, China
- The Tree and Ornamental Plant Breeding and Biotechnology, Laboratory of National Forestry and Grassland Administration, Beijing Forestry University, Beijing, China
| | - Yi Jin
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, Beijing Forestry University, Beijing, China
- The Tree and Ornamental Plant Breeding and Biotechnology, Laboratory of National Forestry and Grassland Administration, Beijing Forestry University, Beijing, China
| | - Xuli Zhu
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, Beijing Forestry University, Beijing, China
- The Tree and Ornamental Plant Breeding and Biotechnology, Laboratory of National Forestry and Grassland Administration, Beijing Forestry University, Beijing, China
| | - Rongling Wu
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, Beijing Forestry University, Beijing, China
- The Tree and Ornamental Plant Breeding and Biotechnology, Laboratory of National Forestry and Grassland Administration, Beijing Forestry University, Beijing, China
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9
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Lamoureux CR, Decker KT, Sastry AV, Rychel K, Gao Y, McConn J, Zielinski D, Palsson BO. A multi-scale expression and regulation knowledge base for Escherichia coli. Nucleic Acids Res 2023; 51:10176-10193. [PMID: 37713610 PMCID: PMC10602906 DOI: 10.1093/nar/gkad750] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/02/2023] [Accepted: 09/05/2023] [Indexed: 09/17/2023] Open
Abstract
Transcriptomic data is accumulating rapidly; thus, scalable methods for extracting knowledge from this data are critical. Here, we assembled a top-down expression and regulation knowledge base for Escherichia coli. The expression component is a 1035-sample, high-quality RNA-seq compendium consisting of data generated in our lab using a single experimental protocol. The compendium contains diverse growth conditions, including: 9 media; 39 supplements, including antibiotics; 42 heterologous proteins; and 76 gene knockouts. Using this resource, we elucidated global expression patterns. We used machine learning to extract 201 modules that account for 86% of known regulatory interactions, creating the regulatory component. With these modules, we identified two novel regulons and quantified systems-level regulatory responses. We also integrated 1675 curated, publicly-available transcriptomes into the resource. We demonstrated workflows for analyzing new data against this knowledge base via deconstruction of regulation during aerobic transition. This resource illuminates the E. coli transcriptome at scale and provides a blueprint for top-down transcriptomic analysis of non-model organisms.
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Affiliation(s)
- Cameron R Lamoureux
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Katherine T Decker
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Anand V Sastry
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Kevin Rychel
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Ye Gao
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - John Luke McConn
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Daniel C Zielinski
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Bernhard O Palsson
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kgs. Lyngby, Denmark
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10
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Trouillon J, Doubleday PF, Sauer U. Genomic footprinting uncovers global transcription factor responses to amino acids in Escherichia coli. Cell Syst 2023; 14:860-871.e4. [PMID: 37820729 DOI: 10.1016/j.cels.2023.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 09/01/2023] [Accepted: 09/19/2023] [Indexed: 10/13/2023]
Abstract
Our knowledge of transcriptional responses to changes in nutrient availability comes primarily from few well-studied transcription factors (TFs), often lacking an unbiased genome-wide perspective. Leveraging recent advances allowing bacterial genomic footprinting, we comprehensively mapped the genome-wide regulatory responses of Escherichia coli to exogenous leucine, methionine, alanine, and lysine. The global TF Lrp was found to individually sense three amino acids and mount three different target gene responses. Overall, 531 genes had altered RNA polymerase occupancy, and 32 TFs responded directly or indirectly to the presence of amino acids, including regulators of membrane and osmotic pressure homeostasis. About 70% of the detected TF-DNA interactions had not been reported before. We thus identified 682 previously unknown TF-binding locations, for a subset of which the involved TFs were identified by affinity purification. This comprehensive map of amino acid regulation illustrates the incompleteness of the known transcriptional regulation network, even in E. coli.
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Affiliation(s)
- Julian Trouillon
- Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland
| | - Peter F Doubleday
- Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland
| | - Uwe Sauer
- Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland.
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11
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Baugh AC, Momany C, Neidle EL. Versatility and Complexity: Common and Uncommon Facets of LysR-Type Transcriptional Regulators. Annu Rev Microbiol 2023; 77:317-339. [PMID: 37285554 DOI: 10.1146/annurev-micro-050323-040543] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
LysR-type transcriptional regulators (LTTRs) form one of the largest families of bacterial regulators. They are widely distributed and contribute to all aspects of metabolism and physiology. Most are homotetramers, with each subunit composed of an N-terminal DNA-binding domain followed by a long helix connecting to an effector-binding domain. LTTRs typically bind DNA in the presence or absence of a small-molecule ligand (effector). In response to cellular signals, conformational changes alter DNA interactions, contact with RNA polymerase, and sometimes contact with other proteins. Many are dual-function repressor-activators, although different modes of regulation may occur at multiple promoters. This review presents an update on the molecular basis of regulation, the complexity of regulatory schemes, and applications in biotechnology and medicine. The abundance of LTTRs reflects their versatility and importance. While a single regulatory model cannot describe all family members, a comparison of similarities and differences provides a framework for future study.
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Affiliation(s)
- Alyssa C Baugh
- Department of Microbiology, University of Georgia, Athens, Georgia, USA;
| | - Cory Momany
- Department of Pharmaceutical and Biomedical Sciences, University of Georgia, Athens, Georgia, USA
| | - Ellen L Neidle
- Department of Microbiology, University of Georgia, Athens, Georgia, USA;
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12
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Sajid S, Mashkoor M, Jørgensen MG, Christensen LP, Hansen PR, Franzyk H, Mirza O, Prabhala BK. The Y-ome Conundrum: Insights into Uncharacterized Genes and Approaches for Functional Annotation. Mol Cell Biochem 2023:10.1007/s11010-023-04827-8. [PMID: 37610616 DOI: 10.1007/s11010-023-04827-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 08/09/2023] [Indexed: 08/24/2023]
Abstract
The ever-increasing availability of genome sequencing data has revealed a substantial number of uncharacterized genes without known functions across various organisms. The first comprehensive genome sequencing of E. coli K12 revealed that more than 50% of its open reading frames corresponded to transcripts with no known functions. The group of protein-coding genes without a functional description and/or a recognized pathway, beginning with the letter "Y", is classified as the "y-ome". Several efforts have been made to elucidate the functions of these genes and to recognize their role in biological processes. This review provides a brief update on various strategies employed when studying the y-ome, such as high-throughput experimental approaches, comparative omics, metabolic engineering, gene expression analysis, and data integration techniques. Additionally, we highlight recent advancements in functional annotation methods, including the use of machine learning, network analysis, and functional genomics approaches. Novel approaches are required to produce more precise functional annotations across the genome to reduce the number of genes with unknown functions.
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Affiliation(s)
- Salvia Sajid
- Department of Drug Design and Pharmacology, University of Copenhagen, Universitetsparken 2, 2100, Copenhagen Ø, Denmark
- Department of Physics, Chemistry, and Pharmacy, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark
| | - Maliha Mashkoor
- Department of Surgery, Center for Surgical Sciences, Zealand University Hospital, Lykkebækvej 1, 4600, Køge, Denmark
| | - Mikkel Girke Jørgensen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark
| | - Lars Porskjær Christensen
- Department of Physics, Chemistry, and Pharmacy, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark
| | - Paul Robert Hansen
- Department of Drug Design and Pharmacology, University of Copenhagen, Universitetsparken 2, 2100, Copenhagen Ø, Denmark
| | - Henrik Franzyk
- Department of Drug Design and Pharmacology, University of Copenhagen, Universitetsparken 2, 2100, Copenhagen Ø, Denmark
| | - Osman Mirza
- Department of Drug Design and Pharmacology, University of Copenhagen, Universitetsparken 2, 2100, Copenhagen Ø, Denmark
| | - Bala Krishna Prabhala
- Department of Physics, Chemistry, and Pharmacy, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark.
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13
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Laboratory evolution reveals general and specific tolerance mechanisms for commodity chemicals. Metab Eng 2023; 76:179-192. [PMID: 36738854 DOI: 10.1016/j.ymben.2023.01.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 01/06/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023]
Abstract
Although strain tolerance to high product concentrations is a barrier to the economically viable biomanufacturing of industrial chemicals, chemical tolerance mechanisms are often unknown. To reveal tolerance mechanisms, an automated platform was utilized to evolve Escherichia coli to grow optimally in the presence of 11 industrial chemicals (1,2-propanediol, 2,3-butanediol, glutarate, adipate, putrescine, hexamethylenediamine, butanol, isobutyrate, coumarate, octanoate, hexanoate), reaching tolerance at concentrations 60%-400% higher than initial toxic levels. Sequencing genomes of 223 isolates from 89 populations, reverse engineering, and cross-compound tolerance profiling were employed to uncover tolerance mechanisms. We show that: 1) cells are tolerized via frequent mutation of membrane transporters or cell wall-associated proteins (e.g., ProV, KgtP, SapB, NagA, NagC, MreB), transcription and translation machineries (e.g., RpoA, RpoB, RpoC, RpsA, RpsG, NusA, Rho), stress signaling proteins (e.g., RelA, SspA, SpoT, YobF), and for certain chemicals, regulators and enzymes in metabolism (e.g., MetJ, NadR, GudD, PurT); 2) osmotic stress plays a significant role in tolerance when chemical concentrations exceed a general threshold and mutated genes frequently overlap with those enabling chemical tolerance in membrane transporters and cell wall-associated proteins; 3) tolerization to a specific chemical generally improves tolerance to structurally similar compounds whereas a tradeoff can occur on dissimilar chemicals, and 4) using pre-tolerized starting isolates can hugely enhance the subsequent production of chemicals when a production pathway is inserted in many, but not all, evolved tolerized host strains, underpinning the need for evolving multiple parallel populations. Taken as a whole, this study provides a comprehensive genotype-phenotype map based on identified mutations and growth phenotypes for 223 chemical tolerant isolates.
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14
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Gao R, Brokaw SE, Li Z, Helfant LJ, Wu T, Malik M, Stock AM. Exploring the mono-/bistability range of positively autoregulated signaling systems in the presence of competing transcription factor binding sites. PLoS Comput Biol 2022; 18:e1010738. [PMID: 36413575 PMCID: PMC9725139 DOI: 10.1371/journal.pcbi.1010738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 12/06/2022] [Accepted: 11/14/2022] [Indexed: 11/23/2022] Open
Abstract
Binding of transcription factor (TF) proteins to regulatory DNA sites is key to accurate control of gene expression in response to environmental stimuli. Theoretical modeling of transcription regulation is often focused on a limited set of genes of interest, while binding of the TF to other genomic sites is seldom considered. The total number of TF binding sites (TFBSs) affects the availability of TF protein molecules and sequestration of a TF by TFBSs can promote bistability. For many signaling systems where a graded response is desirable for continuous control over the input range, biochemical parameters of the regulatory proteins need be tuned to avoid bistability. Here we analyze the mono-/bistable parameter range for positively autoregulated two-component systems (TCSs) in the presence of different numbers of competing TFBSs. TCS signaling, one of the major bacterial signaling strategies, couples signal perception with output responses via protein phosphorylation. For bistability, competition for TF proteins by TFBSs lowers the requirement for high fold change of the autoregulated transcription but demands high phosphorylation activities of TCS proteins. We show that bistability can be avoided with a low phosphorylation capacity of TCSs, a high TF affinity for the autoregulated promoter or a low fold change in signaling protein levels upon induction. These may represent general design rules for TCSs to ensure uniform graded responses. Examining the mono-/bistability parameter range allows qualitative prediction of steady-state responses, which are experimentally validated in the E. coli CusRS system.
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Affiliation(s)
- Rong Gao
- Center for Advanced Biotechnology and Medicine, Department of Biochemistry and Molecular Biology, Rutgers University - Robert Wood Johnson Medical School, Piscataway, New Jersey, United States of America
| | - Samantha E. Brokaw
- Center for Advanced Biotechnology and Medicine, Department of Biochemistry and Molecular Biology, Rutgers University - Robert Wood Johnson Medical School, Piscataway, New Jersey, United States of America
| | - Zeyue Li
- Center for Advanced Biotechnology and Medicine, Department of Biochemistry and Molecular Biology, Rutgers University - Robert Wood Johnson Medical School, Piscataway, New Jersey, United States of America
| | - Libby J. Helfant
- Center for Advanced Biotechnology and Medicine, Department of Biochemistry and Molecular Biology, Rutgers University - Robert Wood Johnson Medical School, Piscataway, New Jersey, United States of America
| | - Ti Wu
- Center for Advanced Biotechnology and Medicine, Department of Biochemistry and Molecular Biology, Rutgers University - Robert Wood Johnson Medical School, Piscataway, New Jersey, United States of America
| | - Muhammad Malik
- Center for Advanced Biotechnology and Medicine, Department of Biochemistry and Molecular Biology, Rutgers University - Robert Wood Johnson Medical School, Piscataway, New Jersey, United States of America
| | - Ann M. Stock
- Center for Advanced Biotechnology and Medicine, Department of Biochemistry and Molecular Biology, Rutgers University - Robert Wood Johnson Medical School, Piscataway, New Jersey, United States of America
- * E-mail:
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15
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Wisniewska A, Wons E, Potrykus K, Hinrichs R, Gucwa K, Graumann PL, Mruk I. Molecular basis for lethal cross-talk between two unrelated bacterial transcription factors - the regulatory protein of a restriction-modification system and the repressor of a defective prophage. Nucleic Acids Res 2022; 50:10964-10980. [PMID: 36271797 DOI: 10.1093/nar/gkac914] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 09/29/2022] [Accepted: 10/06/2022] [Indexed: 11/13/2022] Open
Abstract
Bacterial gene expression depends on the efficient functioning of global transcriptional networks, however their interconnectivity and orchestration rely mainly on the action of individual DNA binding proteins called transcription factors (TFs). TFs interact not only with their specific target sites, but also with secondary (off-target) sites, and vary in their promiscuity. It is not clear yet what mechanisms govern the interactions with secondary sites, and how such rewiring affects the overall regulatory network, but this could clearly constrain horizontal gene transfer. Here, we show the molecular mechanism of one such off-target interaction between two unrelated TFs in Escherichia coli: the C regulatory protein of a Type II restriction-modification system, and the RacR repressor of a defective prophage. We reveal that the C protein interferes with RacR repressor expression, resulting in derepression of the toxic YdaT protein. These results also provide novel insights into regulation of the racR-ydaST operon. We mapped the C regulator interaction to a specific off-target site, and also visualized C protein dynamics, revealing intriguing differences in single molecule dynamics in different genetic contexts. Our results demonstrate an apparent example of horizontal gene transfer leading to adventitious TF cross-talk with negative effects on the recipient's viability. More broadly, this study represents an experimentally-accessible model of a regulatory constraint on horizontal gene transfer.
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Affiliation(s)
- Aleksandra Wisniewska
- Department of Microbiology, Faculty of Biology, University of Gdansk, Wita Stwosza 59, Gdansk 80-308, Poland
| | - Ewa Wons
- Department of Microbiology, Faculty of Biology, University of Gdansk, Wita Stwosza 59, Gdansk 80-308, Poland
| | - Katarzyna Potrykus
- Department of Bacterial Molecular Genetics, Faculty of Biology, University of Gdansk, Wita Stwosza 59, Gdansk 80-308, Poland
| | - Rebecca Hinrichs
- SYNMIKRO, LOEWE Center for Synthetic Microbiology, Philipps Universität Marburg, Germany.,Department of Chemistry, Philipps Universität Marburg, Hans-Meerwein-Strasse 6, 35032 Marburg, Germany
| | - Katarzyna Gucwa
- Department of Microbiology, Faculty of Biology, University of Gdansk, Wita Stwosza 59, Gdansk 80-308, Poland
| | - Peter L Graumann
- SYNMIKRO, LOEWE Center for Synthetic Microbiology, Philipps Universität Marburg, Germany.,Department of Chemistry, Philipps Universität Marburg, Hans-Meerwein-Strasse 6, 35032 Marburg, Germany
| | - Iwona Mruk
- Department of Microbiology, Faculty of Biology, University of Gdansk, Wita Stwosza 59, Gdansk 80-308, Poland
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16
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Duarte-Velázquez I, de la Mora J, Ramírez-Prado JH, Aguillón-Bárcenas A, Tornero-Gutiérrez F, Cordero-Loreto E, Anaya-Velázquez F, Páramo-Pérez I, Rangel-Serrano Á, Muñoz-Carranza SR, Romero-González OE, Cardoso-Reyes LR, Rodríguez-Ojeda RA, Mora-Montes HM, Vargas-Maya NI, Padilla-Vaca F, Franco B. Escherichia coli transcription factors of unknown function: sequence features and possible evolutionary relationships. PeerJ 2022; 10:e13772. [PMID: 35880217 PMCID: PMC9308461 DOI: 10.7717/peerj.13772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 07/01/2022] [Indexed: 01/17/2023] Open
Abstract
Organisms need mechanisms to perceive the environment and respond accordingly to environmental changes or the presence of hazards. Transcription factors (TFs) are required for cells to respond to the environment by controlling the expression of genes needed. Escherichia coli has been the model bacterium for many decades, and still, there are features embedded in its genome that remain unstudied. To date, 58 TFs remain poorly characterized, although their binding sites have been experimentally determined. This study showed that these TFs have sequence variation at the third codon position G+C content but maintain the same Codon Adaptation Index (CAI) trend as annotated functional transcription factors. Most of these transcription factors are in areas of the genome where abundant repetitive and mobile elements are present. Sequence divergence points to groups with distinctive sequence signatures but maintaining the same type of DNA binding domain. Finally, the analysis of the promoter sequences of the 58 TFs showed A+T rich regions that agree with the features of horizontally transferred genes. The findings reported here pave the way for future research of these TFs that may uncover their role as spare factors in case of lose-of-function mutations in core TFs and trace back their evolutionary history.
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Affiliation(s)
- Isabel Duarte-Velázquez
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
| | - Javier de la Mora
- Departamento de Genética Molecular, Instituto de Fisiología Celular, Universidad Nacional Autonoma de Mexico, Mexico City, México
| | | | - Alondra Aguillón-Bárcenas
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
| | - Fátima Tornero-Gutiérrez
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
| | - Eugenia Cordero-Loreto
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
| | - Fernando Anaya-Velázquez
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
| | - Itzel Páramo-Pérez
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
| | - Ángeles Rangel-Serrano
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
| | | | | | - Luis Rafael Cardoso-Reyes
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
| | | | - Héctor Manuel Mora-Montes
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
| | - Naurú Idalia Vargas-Maya
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
| | - Felipe Padilla-Vaca
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
| | - Bernardo Franco
- Biology, División de Ciencias Naturales y Exactas, Universidad de Guanajuato, Guanajuato, Guanajuato, México
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17
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Gagarinova A, Hosseinnia A, Rahmatbakhsh M, Istace Z, Phanse S, Moutaoufik MT, Zilocchi M, Zhang Q, Aoki H, Jessulat M, Kim S, Aly KA, Babu M. Auxotrophic and prototrophic conditional genetic networks reveal the rewiring of transcription factors in Escherichia coli. Nat Commun 2022; 13:4085. [PMID: 35835781 PMCID: PMC9283627 DOI: 10.1038/s41467-022-31819-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 07/05/2022] [Indexed: 11/25/2022] Open
Abstract
Bacterial transcription factors (TFs) are widely studied in Escherichia coli. Yet it remains unclear how individual genes in the underlying pathways of TF machinery operate together during environmental challenge. Here, we address this by applying an unbiased, quantitative synthetic genetic interaction (GI) approach to measure pairwise GIs among all TF genes in E. coli under auxotrophic (rich medium) and prototrophic (minimal medium) static growth conditions. The resulting static and differential GI networks reveal condition-dependent GIs, widespread changes among TF genes in metabolism, and new roles for uncharacterized TFs (yjdC, yneJ, ydiP) as regulators of cell division, putrescine utilization pathway, and cold shock adaptation. Pan-bacterial conservation suggests TF genes with GIs are co-conserved in evolution. Together, our results illuminate the global organization of E. coli TFs, and remodeling of genetic backup systems for TFs under environmental change, which is essential for controlling the bacterial transcriptional regulatory circuits. The bacterium E. coli has around 300 transcriptional factors, but the functions of many of them, and the interactions between their respective regulatory networks, are unclear. Here, the authors study genetic interactions among all transcription factor genes in E. coli, revealing condition-dependent interactions and roles for uncharacterized transcription factors.
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Affiliation(s)
- Alla Gagarinova
- Department of Biochemistry, University of Regina, Regina, SK, Canada
| | - Ali Hosseinnia
- Department of Biochemistry, University of Regina, Regina, SK, Canada
| | | | - Zoe Istace
- Department of Biochemistry, University of Regina, Regina, SK, Canada
| | - Sadhna Phanse
- Department of Biochemistry, University of Regina, Regina, SK, Canada
| | | | - Mara Zilocchi
- Department of Biochemistry, University of Regina, Regina, SK, Canada
| | - Qingzhou Zhang
- Department of Biochemistry, University of Regina, Regina, SK, Canada
| | - Hiroyuki Aoki
- Department of Biochemistry, University of Regina, Regina, SK, Canada
| | - Matthew Jessulat
- Department of Biochemistry, University of Regina, Regina, SK, Canada
| | - Sunyoung Kim
- Department of Biochemistry, University of Regina, Regina, SK, Canada
| | - Khaled A Aly
- Department of Biochemistry, University of Regina, Regina, SK, Canada
| | - Mohan Babu
- Department of Biochemistry, University of Regina, Regina, SK, Canada.
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18
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L.B. Almeida B, M. Bahrudeen MN, Chauhan V, Dash S, Kandavalli V, Häkkinen A, Lloyd-Price J, S.D. Cristina P, Baptista ISC, Gupta A, Kesseli J, Dufour E, Smolander OP, Nykter M, Auvinen P, Jacobs HT, M.D. Oliveira S, S. Ribeiro A. The transcription factor network of E. coli steers global responses to shifts in RNAP concentration. Nucleic Acids Res 2022; 50:6801-6819. [PMID: 35748858 PMCID: PMC9262627 DOI: 10.1093/nar/gkac540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 06/02/2022] [Accepted: 06/14/2022] [Indexed: 12/24/2022] Open
Abstract
The robustness and sensitivity of gene networks to environmental changes is critical for cell survival. How gene networks produce specific, chronologically ordered responses to genome-wide perturbations, while robustly maintaining homeostasis, remains an open question. We analysed if short- and mid-term genome-wide responses to shifts in RNA polymerase (RNAP) concentration are influenced by the known topology and logic of the transcription factor network (TFN) of Escherichia coli. We found that, at the gene cohort level, the magnitude of the single-gene, mid-term transcriptional responses to changes in RNAP concentration can be explained by the absolute difference between the gene's numbers of activating and repressing input transcription factors (TFs). Interestingly, this difference is strongly positively correlated with the number of input TFs of the gene. Meanwhile, short-term responses showed only weak influence from the TFN. Our results suggest that the global topological traits of the TFN of E. coli shape which gene cohorts respond to genome-wide stresses.
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Affiliation(s)
- Bilena L.B. Almeida
- Correspondence may also be addressed to Bilena L.B. Almeida. Tel: +358 2945211;
| | | | | | | | - Vinodh Kandavalli
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Antti Häkkinen
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, FI-00014 Helsinki, Finland
| | | | - Palma S.D. Cristina
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Ines S C Baptista
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Abhishekh Gupta
- Center for Quantitative Medicine and Department of Cell Biology, University of Connecticut School of Medicine, 263 Farmington Av., Farmington, CT 06030-6033, USA
| | - Juha Kesseli
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Tays Cancer Center, Tampere University Hospital, Tampere, Finland
| | - Eric Dufour
- Mitochondrial bioenergetics and metabolism, BioMediTech, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli-Pekka Smolander
- Department of Chemistry and Biotechnology, Tallinn University of Technology, Tallinn, Estonia
- Institute of Biotechnology, University of Helsinki, Viikinkaari 5D, 00790 Helsinki, Finland
| | - Matti Nykter
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Tays Cancer Center, Tampere University Hospital, Tampere, Finland
| | - Petri Auvinen
- Institute of Biotechnology, University of Helsinki, Viikinkaari 5D, 00790 Helsinki, Finland
| | - Howard T Jacobs
- Faculty of Medicine and Health Technology, FI-33014 Tampere University, Finland; Department of Environment and Genetics, La Trobe University, Melbourne, Victoria 3086, Australia
| | - Samuel M.D. Oliveira
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA
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19
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Tierrafría VH, Rioualen C, Salgado H, Lara P, Gama-Castro S, Lally P, Gómez-Romero L, Peña-Loredo P, López-Almazo AG, Alarcón-Carranza G, Betancourt-Figueroa F, Alquicira-Hernández S, Polanco-Morelos JE, García-Sotelo J, Gaytan-Nuñez E, Méndez-Cruz CF, Muñiz LJ, Bonavides-Martínez C, Moreno-Hagelsieb G, Galagan JE, Wade JT, Collado-Vides J. RegulonDB 11.0: Comprehensive high-throughput datasets on transcriptional regulation in Escherichia coli K-12. Microb Genom 2022; 8. [PMID: 35584008 PMCID: PMC9465075 DOI: 10.1099/mgen.0.000833] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Genomics has set the basis for a variety of methodologies that produce high-throughput datasets identifying the different players that define gene regulation, particularly regulation of transcription initiation and operon organization. These datasets are available in public repositories, such as the Gene Expression Omnibus, or ArrayExpress. However, accessing and navigating such a wealth of data is not straightforward. No resource currently exists that offers all available high and low-throughput data on transcriptional regulation in Escherichia coli K-12 to easily use both as whole datasets, or as individual interactions and regulatory elements. RegulonDB (https://regulondb.ccg.unam.mx) began gathering high-throughput dataset collections in 2009, starting with transcription start sites, then adding ChIP-seq and gSELEX in 2012, with up to 99 different experimental high-throughput datasets available in 2019. In this paper we present a radical upgrade to more than 2000 high-throughput datasets, processed to facilitate their comparison, introducing up-to-date collections of transcription termination sites, transcription units, as well as transcription factor binding interactions derived from ChIP-seq, ChIP-exo, gSELEX and DAP-seq experiments, besides expression profiles derived from RNA-seq experiments. For ChIP-seq experiments we offer both the data as presented by the authors, as well as data uniformly processed in-house, enhancing their comparability, as well as the traceability of the methods and reproducibility of the results. Furthermore, we have expanded the tools available for browsing and visualization across and within datasets. We include comparisons against previously existing knowledge in RegulonDB from classic experiments, a nucleotide-resolution genome viewer, and an interface that enables users to browse datasets by querying their metadata. A particular effort was made to automatically extract detailed experimental growth conditions by implementing an assisted curation strategy applying Natural language processing and machine learning. We provide summaries with the total number of interactions found in each experiment, as well as tools to identify common results among different experiments. This is a long-awaited resource to make use of such wealth of knowledge and advance our understanding of the biology of the model bacterium E. coli K-12.
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Affiliation(s)
- Víctor H Tierrafría
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico.,Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA
| | - Claire Rioualen
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Heladia Salgado
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Paloma Lara
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Socorro Gama-Castro
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Patrick Lally
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA
| | - Laura Gómez-Romero
- Instituto Nacional de Medicina Genómica, INMEGEN, Periférico Sur 4809, Arenal Tepepan, Tlalpan 14610, CDMX, Mexico
| | - Pablo Peña-Loredo
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Andrés G López-Almazo
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Gabriel Alarcón-Carranza
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Felipe Betancourt-Figueroa
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Shirley Alquicira-Hernández
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - J Enrique Polanco-Morelos
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Jair García-Sotelo
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Querétaro 76230, Querétaro, Mexico
| | - Estefani Gaytan-Nuñez
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Carlos-Francisco Méndez-Cruz
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Luis J Muñiz
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - César Bonavides-Martínez
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico
| | - Gabriel Moreno-Hagelsieb
- Department of Biology, Wilfrid Laurier University, 75 University Ave W, Waterloo, ON N2L 3C5, Canada
| | - James E Galagan
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA
| | - Joseph T Wade
- Wadsworth Center, New York State Department of Health, Albany, NY, USA.,Department of Biomedical Sciences, University at Albany, SUNY, Albany, NY, USA
| | - Julio Collado-Vides
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, Mexico.,Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA.,Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Universitat Pompeu Fabra(UPF), Barcelona, Spain
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20
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High Abundance of Transcription Regulators Compacts the Nucleoid in Escherichia coli. J Bacteriol 2022; 204:e0002622. [PMID: 35583339 DOI: 10.1128/jb.00026-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
In enteric bacteria organization of the circular chromosomal DNA into a highly dynamic and toroidal-shaped nucleoid involves various factors, such as DNA supercoiling, nucleoid-associated proteins (NAPs), the structural maintenance of chromatin (SMC) complex, and macrodomain organizing proteins. Here, we show that ectopic expression of transcription regulators at high levels leads to nucleoid compaction. This serendipitous result was obtained by fluorescence microscopy upon ectopic expression of the transcription regulator and phosphodiesterase PdeL of Escherichia coli. Nucleoid compaction by PdeL depends on DNA-binding, but not on its enzymatic phosphodiesterase activity. Nucleoid compaction was also observed upon high-level ectopic expression of the transcription regulators LacI, RutR, RcsB, LeuO, and Cra, which range from single-target gene regulators to global regulators. In the case of LacI, its high-level expression in the presence of the gratuitous inducer IPTG (isopropyl-β-d-thiogalactopyranoside) also led to nucleoid compaction, indicating that compaction is caused by unspecific DNA-binding. In all cases nucleoid compaction correlated with misplacement of the FtsZ ring and loss of MukB foci, a subunit of the SMC complex. Thus, high levels of several transcription regulators cause nucleoid compaction with consequences for replication and cell division. IMPORTANCE The bacterial nucleoid is a highly organized and dynamic structure for simultaneous transcription, replication, and segregation of the bacterial genome. Compaction of the nucleoid and disturbance of DNA segregation and cell division by artificially high levels of transcription regulators, as described here, reveals that an excess of DNA-binding protein disturbs nucleoid structuring. The results suggest that ectopic expression levels of DNA-binding proteins for genetic studies of their function but also for their purification should be carefully controlled and adjusted.
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21
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Rodionova IA, Gao Y, Monk J, Hefner Y, Wong N, Szubin R, Lim HG, Rodionov DA, Zhang Z, Saier MH, Palsson BO. A systems approach discovers the role and characteristics of seven LysR type transcription factors in Escherichia coli. Sci Rep 2022; 12:7274. [PMID: 35508583 PMCID: PMC9068703 DOI: 10.1038/s41598-022-11134-7] [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: 11/16/2021] [Accepted: 04/14/2022] [Indexed: 11/24/2022] Open
Abstract
Although Escherichia coli K-12 strains represent perhaps the best known model bacteria, we do not know the identity or functions of all of their transcription factors (TFs). It is now possible to systematically discover the physiological function of TFs in E. coli BW25113 using a set of synergistic methods; including ChIP-exo, growth phenotyping, conserved gene clustering, and transcriptome analysis. Among 47 LysR-type TFs (LTFs) found on the E. coli K-12 genome, many regulate nitrogen source utilization or amino acid metabolism. However, 19 LTFs remain unknown. In this study, we elucidated the regulation of seven of these 19 LTFs: YbdO, YbeF, YcaN, YbhD, YgfI, YiaU, YneJ. We show that: (1) YbdO (tentatively re-named CitR) regulation has an effect on bacterial growth at low pH with citrate supplementation. CitR is a repressor of the ybdNM operon and is implicated in the regulation of citrate lyase genes (citCDEFG); (2) YgfI (tentatively re-named DhfA) activates the dhaKLM operon that encodes the phosphotransferase system, DhfA is involved in formate, glycerol and dihydroxyacetone utilization; (3) YiaU (tentatively re-named LpsR) regulates the yiaT gene encoding an outer membrane protein, and waaPSBOJYZU operon is also important in determining cell density at the stationary phase and resistance to oxacillin microaerobically; (4) YneJ, re-named here as PtrR, directly regulates the expression of the succinate-semialdehyde dehydrogenase, Sad (also known as YneI), and is a predicted regulator of fnrS (a small RNA molecule). PtrR is important for bacterial growth in the presence of l-glutamate and putrescine as nitrogen/energy sources; and (5) YbhD and YcaN regulate adjacent y-genes on the genome. We have thus established the functions for four LTFs and identified the target genes for three LTFs.
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Affiliation(s)
- Irina A Rodionova
- Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093-0116, USA. .,Division of Biological Sciences, Department of Molecular Biology, University of California San Diego, La Jolla, CA, 92093-0116, USA.
| | - Ye Gao
- Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093-0116, USA.,Division of Biological Sciences, Department of Molecular Biology, University of California San Diego, La Jolla, CA, 92093-0116, USA
| | - Jonathan Monk
- Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093-0116, USA
| | - Ying Hefner
- Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093-0116, USA
| | - Nicholas Wong
- Division of Biological Sciences, Department of Molecular Biology, University of California San Diego, La Jolla, CA, 92093-0116, USA
| | - Richard Szubin
- Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093-0116, USA
| | - Hyun Gyu Lim
- Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093-0116, USA
| | - Dmitry A Rodionov
- Sanford-Burnham-Prebys Medical Discovery Institute, La Jolla, CA, 92037, USA
| | - Zhongge Zhang
- Division of Biological Sciences, Department of Molecular Biology, University of California San Diego, La Jolla, CA, 92093-0116, USA
| | - Milton H Saier
- Division of Biological Sciences, Department of Molecular Biology, University of California San Diego, La Jolla, CA, 92093-0116, USA
| | - Bernhard O Palsson
- Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093-0116, USA. .,Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA. .,Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Lyngby, Denmark.
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22
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Lim HG, Rychel K, Sastry AV, Bentley GJ, Mueller J, Schindel HS, Larsen PE, Laible PD, Guss AM, Niu W, Johnson CW, Beckham GT, Feist AM, Palsson BO. Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network. Metab Eng 2022; 72:297-310. [PMID: 35489688 DOI: 10.1016/j.ymben.2022.04.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 03/23/2022] [Accepted: 04/23/2022] [Indexed: 11/17/2022]
Abstract
Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida KT2440 and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.
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Affiliation(s)
- Hyun Gyu Lim
- Department of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA; Joint BioEnergy Institute, 5885 Hollis Street, 4th Floor, Emeryville, CA, 94608, USA
| | - Kevin Rychel
- Department of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA
| | - Anand V Sastry
- Department of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA
| | - Gayle J Bentley
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO, 80401, USA; Agile BioFoundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Emeryville, CA, 94720, USA
| | - Joshua Mueller
- Department of Chemical & Biomolecular Engineering, University of Nebraska-Lincoln, 1400 R St, Lincoln, NE, 68588, USA
| | - Heidi S Schindel
- Biosciences Division, Oak Ridge National Laboratory, 5200 Bethel Valley Rd, Oak Ridge, TN, 37830, USA
| | - Peter E Larsen
- Biosciences Division, Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL, 60539, USA
| | - Philip D Laible
- Biosciences Division, Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL, 60539, USA
| | - Adam M Guss
- Agile BioFoundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Emeryville, CA, 94720, USA; Biosciences Division, Oak Ridge National Laboratory, 5200 Bethel Valley Rd, Oak Ridge, TN, 37830, USA
| | - Wei Niu
- Department of Chemical & Biomolecular Engineering, University of Nebraska-Lincoln, 1400 R St, Lincoln, NE, 68588, USA
| | - Christopher W Johnson
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO, 80401, USA; Agile BioFoundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Emeryville, CA, 94720, USA
| | - Gregg T Beckham
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO, 80401, USA; Agile BioFoundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Emeryville, CA, 94720, USA
| | - Adam M Feist
- Department of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA; Joint BioEnergy Institute, 5885 Hollis Street, 4th Floor, Emeryville, CA, 94608, USA; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Kgs, Lyngby, Denmark
| | - Bernhard O Palsson
- Department of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA; Joint BioEnergy Institute, 5885 Hollis Street, 4th Floor, Emeryville, CA, 94608, USA; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Kgs, Lyngby, Denmark; Department of Pediatrics, University of California, San Diego, CA, 92093, USA.
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23
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Shimada T, Murayama R, Mashima T, Kawano N, Ishihama A. Regulatory role of CsuR (YiaU) in determination of cell surface properties of Escherichia coli K-12. MICROBIOLOGY (READING, ENGLAND) 2022; 168. [PMID: 35438626 DOI: 10.1099/mic.0.001166] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Genomic SELEX screening was performed to identify the binding sites of YiaU, an uncharacterized LysR family transcription factor, on the Escherichia coli K-12 genome. Five high-affinity binding targets of YiaU were identified, all of which were involved in the structures of the bacterial cell surface such as outer and inner membrane proteins, and lipopolysaccharides. Detailed in vitro and in vivo analyses suggest that YiaU activates these target genes. To gain insight into the effects of YiaU in vivo on physiological properties, we used phenotype microarrays, biofilm screening assays and the sensitivity against serum complement analysed using a yiaU deletion mutant or YiaU expression strain. Together, these results suggest that the YiaU regulon confers resistance to some antibiotics, and increases biofilm formation and complement sensitivity. We propose renaming YiaU as CsuR (regulator of cell surface).
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Affiliation(s)
- Tomohiro Shimada
- Meiji University, School of Agriculture, Kawasaki, Kanagawa 214-8571, Japan.,Hosei University, Department of Frontier Bioscience, Koganei, Tokyo 184-8584, Japan
| | - Rie Murayama
- Hosei University, Research Institute of Micro-Nano Technology, Koganei, Tokyo 184-0003, Japan
| | - Tomoki Mashima
- Meiji University, School of Agriculture, Kawasaki, Kanagawa 214-8571, Japan
| | - Natsuko Kawano
- Meiji University, School of Agriculture, Kawasaki, Kanagawa 214-8571, Japan
| | - Akira Ishihama
- Hosei University, Department of Frontier Bioscience, Koganei, Tokyo 184-8584, Japan.,Hosei University, Research Institute of Micro-Nano Technology, Koganei, Tokyo 184-0003, Japan
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24
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Femerling G, Gama-Castro S, Lara P, Ledezma-Tejeida D, Tierrafría VH, Muñiz-Rascado L, Bonavides-Martínez C, Collado-Vides J. Sensory Systems and Transcriptional Regulation in Escherichia coli. Front Bioeng Biotechnol 2022; 10:823240. [PMID: 35237580 PMCID: PMC8882922 DOI: 10.3389/fbioe.2022.823240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 01/18/2022] [Indexed: 11/13/2022] Open
Abstract
In free-living bacteria, the ability to regulate gene expression is at the core of adapting and interacting with the environment. For these systems to have a logic, a signal must trigger a genetic change that helps the cell to deal with what implies its presence in the environment; briefly, the response is expected to include a feedback to the signal. Thus, it makes sense to think of genetic sensory mechanisms of gene regulation. Escherichia coli K-12 is the bacterium model for which the largest number of regulatory systems and its sensing capabilities have been studied in detail at the molecular level. In this special issue focused on biomolecular sensing systems, we offer an overview of the transcriptional regulatory corpus of knowledge for E. coli that has been gathered in our database, RegulonDB, from the perspective of sensing regulatory systems. Thus, we start with the beginning of the information flux, which is the signal’s chemical or physical elements detected by the cell as changes in the environment; these signals are internally transduced to transcription factors and alter their conformation. Signals transduced to effectors bind allosterically to transcription factors, and this defines the dominant sensing mechanism in E. coli. We offer an updated list of the repertoire of known allosteric effectors, as well as a list of the currently known different mechanisms of this sensing capability. Our previous definition of elementary genetic sensory-response units, GENSOR units for short, that integrate signals, transport, gene regulation, and the biochemical response of the regulated gene products of a given transcriptional factor fit perfectly with the purpose of this overview. We summarize the functional heterogeneity of their response, based on our updated collection of GENSORs, and we use them to identify the expected feedback as part of their response. Finally, we address the question of multiple sensing in the regulatory network of E. coli. This overview introduces the architecture of sensing and regulation of native components in E.coli K-12, which might be a source of inspiration to bioengineering applications.
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Affiliation(s)
- Georgette Femerling
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, México
| | - Socorro Gama-Castro
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, México
| | - Paloma Lara
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, México
| | | | - Víctor H. Tierrafría
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, México
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
| | - Luis Muñiz-Rascado
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, México
| | | | - Julio Collado-Vides
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, México
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Universitat Pompeu Fabra (UPF), Barcelona, Spain
- *Correspondence: Julio Collado-Vides,
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25
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Decker KT, Gao Y, Rychel K, Al Bulushi T, Chauhan S, Kim D, Cho BK, Palsson B. proChIPdb: a chromatin immunoprecipitation database for prokaryotic organisms. Nucleic Acids Res 2022; 50:D1077-D1084. [PMID: 34791440 PMCID: PMC8728212 DOI: 10.1093/nar/gkab1043] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 10/05/2021] [Accepted: 10/14/2021] [Indexed: 12/03/2022] Open
Abstract
The transcriptional regulatory network in prokaryotes controls global gene expression mostly through transcription factors (TFs), which are DNA-binding proteins. Chromatin immunoprecipitation (ChIP) with DNA sequencing methods can identify TF binding sites across the genome, providing a bottom-up, mechanistic understanding of how gene expression is regulated. ChIP provides indispensable evidence toward the goal of acquiring a comprehensive understanding of cellular adaptation and regulation, including condition-specificity. ChIP-derived data's importance and labor-intensiveness motivate its broad dissemination and reuse, which is currently an unmet need in the prokaryotic domain. To fill this gap, we present proChIPdb (prochipdb.org), an information-rich, interactive web database. This website collects public ChIP-seq/-exo data across several prokaryotes and presents them in dashboards that include curated binding sites, nucleotide-resolution genome viewers, and summary plots such as motif enrichment sequence logos. Users can search for TFs of interest or their target genes, download all data, dashboards, and visuals, and follow external links to understand regulons through biological databases and the literature. This initial release of proChIPdb covers diverse organisms, including most major TFs of Escherichia coli, and can be expanded to support regulon discovery across the prokaryotic domain.
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Affiliation(s)
- Katherine T Decker
- Department of Bioengineering, University of California, San Diego, La Jolla, CA92093, USA
| | - Ye Gao
- Department of Bioengineering, University of California, San Diego, La Jolla, CA92093, USA
| | - Kevin Rychel
- Department of Bioengineering, University of California, San Diego, La Jolla, CA92093, USA
| | - Tahani Al Bulushi
- Department of Bioengineering, University of California, San Diego, La Jolla, CA92093, USA
| | - Siddharth M Chauhan
- Department of Bioengineering, University of California, San Diego, La Jolla, CA92093, USA
| | - Donghyuk Kim
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
| | - Byung-Kwan Cho
- Department of Biological Sciences and KI for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon34141, Republic of Korea
| | - Bernhard O Palsson
- Department of Bioengineering, University of California, San Diego, La Jolla, CA92093, USA
- Department of Pediatrics, University of California, San Diego, La Jolla, CA92093, USA
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Building 220, Kemitorvet, 2800 Kgs. Lyngby, Denmark
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