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Chaignaud P, Gruffaz C, Borreca A, Fouteau S, Kuhn L, Masbou J, Rouy Z, Hammann P, Imfeld G, Roche D, Vuilleumier S. A Methylotrophic Bacterium Growing with the Antidiabetic Drug Metformin as Its Sole Carbon, Nitrogen and Energy Source. Microorganisms 2022; 10:2302. [PMID: 36422372 PMCID: PMC9699525 DOI: 10.3390/microorganisms10112302] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 08/31/2023] Open
Abstract
Metformin is one of the most prescribed antidiabetic agents worldwide and is also considered for other therapeutic applications including cancer and endocrine disorders. It is largely unmetabolized by human enzymes and its presence in the environment has raised concern, with reported toxic effects on aquatic life and potentially also on humans. We report on the isolation and characterisation of strain MD1, an aerobic methylotrophic bacterium growing with metformin as its sole carbon, nitrogen and energy source. Strain MD1 degrades metformin into dimethylamine used for growth, and guanylurea as a side-product. Sequence analysis of its fully assembled genome showed its affiliation to Aminobacter niigataensis. Differential proteomics and transcriptomics, as well as mini-transposon mutagenesis of the strain, point to genes and proteins essential for growth with metformin and potentially associated with hydrolytic C-N cleavage of metformin or with cellular transport of metformin and guanylurea. The obtained results suggest the recent evolution of the growth-supporting capacity of strain MD1 to degrade metformin. Our results identify candidate proteins of the enzymatic system for metformin transformation in strain MD1 and will inform future research on the fate of metformin and its degradation products in the environment and in humans.
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Affiliation(s)
- Pauline Chaignaud
- Génétique Moléculaire, Génomique, Microbiologie, UMR 7156 CNRS, Université de Strasbourg, 67000 Strasbourg, France
| | - Christelle Gruffaz
- Génétique Moléculaire, Génomique, Microbiologie, UMR 7156 CNRS, Université de Strasbourg, 67000 Strasbourg, France
| | - Adrien Borreca
- Génétique Moléculaire, Génomique, Microbiologie, UMR 7156 CNRS, Université de Strasbourg, 67000 Strasbourg, France
- Institut Terre et Environnement de Strasbourg, UMR 7063 CNRS, ENGEES, Université de Strasbourg, 67000 Strasbourg, France
| | - Stéphanie Fouteau
- Génomique Métabolique, Genoscope, Institut de Biologie François Jacob, Commissariat à l’Energie Atomique (CEA), Centre National de la Recherche Scientifique (CNRS), Université d’Evry, Université Paris-Saclay, CEDEX, 91057 Evry, France
| | - Lauriane Kuhn
- Plateforme Protéomique Strasbourg-Esplanade, Institut de Biologie Moléculaire et Cellulaire, FR 1589 CNRS, CEDEX, 67084 Strasbourg, France
| | - Jérémy Masbou
- Institut Terre et Environnement de Strasbourg, UMR 7063 CNRS, ENGEES, Université de Strasbourg, 67000 Strasbourg, France
| | - Zoé Rouy
- Génomique Métabolique, Genoscope, Institut de Biologie François Jacob, Commissariat à l’Energie Atomique (CEA), Centre National de la Recherche Scientifique (CNRS), Université d’Evry, Université Paris-Saclay, CEDEX, 91057 Evry, France
| | - Philippe Hammann
- Plateforme Protéomique Strasbourg-Esplanade, Institut de Biologie Moléculaire et Cellulaire, FR 1589 CNRS, CEDEX, 67084 Strasbourg, France
| | - Gwenaël Imfeld
- Institut Terre et Environnement de Strasbourg, UMR 7063 CNRS, ENGEES, Université de Strasbourg, 67000 Strasbourg, France
| | - David Roche
- Génomique Métabolique, Genoscope, Institut de Biologie François Jacob, Commissariat à l’Energie Atomique (CEA), Centre National de la Recherche Scientifique (CNRS), Université d’Evry, Université Paris-Saclay, CEDEX, 91057 Evry, France
| | - Stéphane Vuilleumier
- Génétique Moléculaire, Génomique, Microbiologie, UMR 7156 CNRS, Université de Strasbourg, 67000 Strasbourg, France
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Genome-Wide Transcription Start Sites Mapping in Methylorubrum Grown with Dichloromethane and Methanol. Microorganisms 2022; 10:microorganisms10071301. [PMID: 35889020 PMCID: PMC9320726 DOI: 10.3390/microorganisms10071301] [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: 06/01/2022] [Revised: 06/17/2022] [Accepted: 06/22/2022] [Indexed: 02/04/2023] Open
Abstract
Dichloromethane (DCM, methylene chloride) is a toxic halogenated volatile organic compound massively used for industrial applications, and consequently often detected in the environment as a major pollutant. DCM biotransformation suggests a sustainable decontamination strategy of polluted sites. Among methylotrophic bacteria able to use DCM as a sole source of carbon and energy for growth, Methylorubrum extorquens DM4 is a longstanding reference strain. Here, the primary 5′-ends of transcripts were obtained using a differential RNA-seq (dRNA-seq) approach to provide the first transcription start site (TSS) genome-wide landscape of a methylotroph using DCM or methanol. In total, 7231 putative TSSs were annotated and classified with respect to their localization to coding sequences (CDSs). TSSs on the opposite strand of CDS (antisense TSS) account for 31% of all identified TSSs. One-third of the detected TSSs were located at a distance to the start codon inferior to 250 nt (average of 84 nt) with 7% of leaderless mRNA. Taken together, the global TSS map for bacterial growth using DCM or methanol will facilitate future studies in which transcriptional regulation is crucial, and efficient DCM removal at polluted sites is limited by regulatory processes.
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Tang Y, Wang Y, Wang J, Li M, Peng L, Wei G, Zhang Y, Li J, Gao Z. TruNeo: an integrated pipeline improves personalized true tumor neoantigen identification. BMC Bioinformatics 2020; 21:532. [PMID: 33208106 PMCID: PMC7672179 DOI: 10.1186/s12859-020-03869-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 11/09/2020] [Indexed: 12/30/2022] Open
Abstract
Background Neoantigen-based personal vaccines and adoptive T cell immunotherapy have shown high efficacy as a cancer treatment in clinical trials. Algorithms for the accurate prediction of neoantigens have played a pivotal role in such studies. Some existing bioinformatics methods, such as MHCflurry and NetMHCpan, identify neoantigens mainly through the prediction of peptide-MHC binding affinity. However, the predictive accuracy of immunogenicity of these methods has been shown to be low. Thus, a ranking algorithm to select highly immunogenic neoantigens of patients is needed urgently in research and clinical practice. Results We develop TruNeo, an integrated computational pipeline to identify and select highly immunogenic neoantigens based on multiple biological processes. The performance of TruNeo and other algorithms were compared based on data from published literature as well as raw data from a lung cancer patient. Recall rate of immunogenic ones among the top 10-ranked neoantigens were compared based on the published combined data set. Recall rate of TruNeo was 52.63%, which was 2.5 times higher than that predicted by MHCflurry (21.05%), and 2 times higher than NetMHCpan 4 (26.32%). Furthermore, the positive rate of top 10-ranked neoantigens for the lung cancer patient were compared, showing a 50% positive rate identified by TruNeo, which was 2.5 times higher than that predicted by MHCflurry (20%). Conclusions TruNeo, which considers multiple biological processes rather than peptide-MHC binding affinity prediction only, provides prioritization of candidate neoantigens with high immunogenicity for neoantigen-targeting personalized immunotherapies.
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Affiliation(s)
- Yunxia Tang
- YuceBio, 2002#, ShenYan Road, Dabaihui Center, Yantian distict, Shenzhen, 518020, China.,Yutai Antigen Science, Building A28, Life Science Park, 140 Jinye Road, Dapeng New District, Shenzhen, 518000, China.,BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, 518083, China
| | - Yu Wang
- YuceBio, 2002#, ShenYan Road, Dabaihui Center, Yantian distict, Shenzhen, 518020, China.,Yutai Antigen Science, Building A28, Life Science Park, 140 Jinye Road, Dapeng New District, Shenzhen, 518000, China
| | - Jiaqian Wang
- Yutai Antigen Science, Building A28, Life Science Park, 140 Jinye Road, Dapeng New District, Shenzhen, 518000, China.,Cancer Research Institute of Yucebio, 2002#, ShenYan Road, Dabaihui Center, Yantian distict, Shenzhen, 518020, China
| | - Miao Li
- YuceBio, 2002#, ShenYan Road, Dabaihui Center, Yantian distict, Shenzhen, 518020, China
| | - Linmin Peng
- Yutai Antigen Science, Building A28, Life Science Park, 140 Jinye Road, Dapeng New District, Shenzhen, 518000, China
| | - Guochao Wei
- Yutai Antigen Science, Building A28, Life Science Park, 140 Jinye Road, Dapeng New District, Shenzhen, 518000, China
| | - Yixing Zhang
- Yutai Antigen Science, Building A28, Life Science Park, 140 Jinye Road, Dapeng New District, Shenzhen, 518000, China
| | - Jin Li
- Department of Pulmonary and Critical Care Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, China
| | - Zhibo Gao
- YuceBio, 2002#, ShenYan Road, Dabaihui Center, Yantian distict, Shenzhen, 518020, China. .,Yutai Antigen Science, Building A28, Life Science Park, 140 Jinye Road, Dapeng New District, Shenzhen, 518000, China. .,Cancer Research Institute of Yucebio, 2002#, ShenYan Road, Dabaihui Center, Yantian distict, Shenzhen, 518020, China.
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4
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Propionibacterium acnes and Acne Vulgaris: New Insights from the Integration of Population Genetic, Multi-Omic, Biochemical and Host-Microbe Studies. Microorganisms 2019; 7:microorganisms7050128. [PMID: 31086023 PMCID: PMC6560440 DOI: 10.3390/microorganisms7050128] [Citation(s) in RCA: 100] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 05/08/2019] [Accepted: 05/09/2019] [Indexed: 12/25/2022] Open
Abstract
The anaerobic bacterium Propionibacterium acnes is believed to play an important role in the pathophysiology of the common skin disease acne vulgaris. Over the last 10 years our understanding of the taxonomic and intraspecies diversity of this bacterium has increased tremendously, and with it the realisation that particular strains are associated with skin health while others appear related to disease. This extensive review will cover our current knowledge regarding the association of P. acnes phylogroups, clonal complexes and sequence types with acne vulgaris based on multilocus sequence typing of isolates, and direct ribotyping of the P. acnes strain population in skin microbiome samples based on 16S rDNA metagenomic data. We will also consider how multi-omic and biochemical studies have facilitated our understanding of P. acnes pathogenicity and interactions with the host, thus providing insights into why certain lineages appear to have a heightened capacity to contribute to acne vulgaris development, while others are positively associated with skin health. We conclude with a discussion of new therapeutic strategies that are currently under investigation for acne vulgaris, including vaccination, and consider the potential of these treatments to also perturb beneficial lineages of P. acnes on the skin.
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Plágaro AH, Pearman PB, Kaberdin VR. Defining the transcription landscape of the Gram-negative marine bacterium Vibrio harveyi. Genomics 2018; 111:1547-1556. [PMID: 30423347 DOI: 10.1016/j.ygeno.2018.10.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 09/13/2018] [Accepted: 10/23/2018] [Indexed: 12/13/2022]
Abstract
Vibrio harveyi is a Gram-negative pathogenic bacterium ubiquitously present in natural aquatic systems. Although environmental adaptability in V. harveyi may be enabled by profound reprogramming of gene expression previously observed during responses to starvation, suboptimal temperatures and other stress factors, the key characteristics of V. harveyi transcripts and operons, such as their boundaries and size as well as location of small RNA genes, remain largely unknown. To reveal the main features of the V. harveyi transcriptome, total RNA of this organism was analyzed by differential RNA sequencing (dRNA-seq). Analysis of the dRNA-seq data made it possible to define the primary transcriptome of V. harveyi along with cis-acting regulatory elements (riboswitches and leader sequences) and new genes. The latter encode a number of putative polypeptides and new phylogenetically conserved antisense RNAs potentially involved in the post-transcriptional control of gene expression.
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Affiliation(s)
- Ander Hernández Plágaro
- Department of Immunology, Microbiology and Parasitology, University of the Basque Country UPV/EHU, 48940 Leioa, Spain.
| | - Peter B Pearman
- Department of Plant Biology and Ecology, University of the Basque Country UPV/EHU, 48940 Leioa, Spain; IKERBASQUE, Basque Foundation for Science, Maria Diaz de Haro 3, 48013 Bilbao, Spain
| | - Vladimir R Kaberdin
- Department of Immunology, Microbiology and Parasitology, University of the Basque Country UPV/EHU, 48940 Leioa, Spain; IKERBASQUE, Basque Foundation for Science, Maria Diaz de Haro 3, 48013 Bilbao, Spain; Research Centre for Experimental Marine Biology and Biotechnology (PIE-UPV/EHU), 48620 Plentzia, Spain.
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Determination of the Genome and Primary Transcriptome of Syngas Fermenting Eubacterium limosum ATCC 8486. Sci Rep 2017; 7:13694. [PMID: 29057933 PMCID: PMC5651825 DOI: 10.1038/s41598-017-14123-3] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Accepted: 10/03/2017] [Indexed: 01/05/2023] Open
Abstract
Autotrophic conversion of CO2 to value-added biochemicals has received considerable attention as a sustainable route to replace fossil fuels. Particularly, anaerobic acetogenic bacteria are naturally capable of reducing CO2 or CO to various metabolites. To fully utilize their biosynthetic potential, an understanding of acetogenesis-related genes and their regulatory elements is required. Here, we completed the genome sequence of the syngas fermenting Eubacterium limosum ATCC 8486 and determined its transcription start sites (TSS). We constructed a 4.4 Mb long circular genome with a GC content of 47.2% and 4,090 protein encoding genes. To understand the transcriptional and translational regulation, the primary transcriptome was augmented, identifying 1,458 TSSs containing a high pyrimidine (T/C) and purine nucleotide (A/G) content at the −1 and +1 position, respectively, along with 1,253 5′-untranslated regions, and principal promoter elements such as −10 (TATAAT) and −35 (TTGACA), and Shine-Dalgarno motifs (GGAGR). Further analysis revealed 93 non-coding RNAs, including one for potential transcriptional regulation of the hydrogenase complex via interaction with molybdenum or tungsten cofactors, which in turn controls formate dehydrogenase activity of the initial step of Wood-Ljungdahl pathway. Our results provide comprehensive genomic information for strain engineering to enhance the syngas fermenting capacity of acetogenic bacteria.
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Hücker SM, Ardern Z, Goldberg T, Schafferhans A, Bernhofer M, Vestergaard G, Nelson CW, Schloter M, Rost B, Scherer S, Neuhaus K. Discovery of numerous novel small genes in the intergenic regions of the Escherichia coli O157:H7 Sakai genome. PLoS One 2017; 12:e0184119. [PMID: 28902868 PMCID: PMC5597208 DOI: 10.1371/journal.pone.0184119] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Accepted: 08/20/2017] [Indexed: 12/29/2022] Open
Abstract
In the past, short protein-coding genes were often disregarded by genome annotation pipelines. Transcriptome sequencing (RNAseq) signals outside of annotated genes have usually been interpreted to indicate either ncRNA or pervasive transcription. Therefore, in addition to the transcriptome, the translatome (RIBOseq) of the enteric pathogen Escherichia coli O157:H7 strain Sakai was determined at two optimal growth conditions and a severe stress condition combining low temperature and high osmotic pressure. All intergenic open reading frames potentially encoding a protein of ≥ 30 amino acids were investigated with regard to coverage by transcription and translation signals and their translatability expressed by the ribosomal coverage value. This led to discovery of 465 unique, putative novel genes not yet annotated in this E. coli strain, which are evenly distributed over both DNA strands of the genome. For 255 of the novel genes, annotated homologs in other bacteria were found, and a machine-learning algorithm, trained on small protein-coding E. coli genes, predicted that 89% of these translated open reading frames represent bona fide genes. The remaining 210 putative novel genes without annotated homologs were compared to the 255 novel genes with homologs and to 250 short annotated genes of this E. coli strain. All three groups turned out to be similar with respect to their translatability distribution, fractions of differentially regulated genes, secondary structure composition, and the distribution of evolutionary constraint, suggesting that both novel groups represent legitimate genes. However, the machine-learning algorithm only recognized a small fraction of the 210 genes without annotated homologs. It is possible that these genes represent a novel group of genes, which have unusual features dissimilar to the genes of the machine-learning algorithm training set.
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Affiliation(s)
- Sarah M. Hücker
- Chair for Microbial Ecology, Technische Universität München, Freising, Germany
- ZIEL - Institute for Food & Health, Technische Universität München, Freising, Germany
| | - Zachary Ardern
- Chair for Microbial Ecology, Technische Universität München, Freising, Germany
- ZIEL - Institute for Food & Health, Technische Universität München, Freising, Germany
| | - Tatyana Goldberg
- Department of Informatics—Bioinformatics & TUM-IAS, Technische Universität München, Garching, Germany
| | - Andrea Schafferhans
- Department of Informatics—Bioinformatics & TUM-IAS, Technische Universität München, Garching, Germany
| | - Michael Bernhofer
- Department of Informatics—Bioinformatics & TUM-IAS, Technische Universität München, Garching, Germany
| | - Gisle Vestergaard
- Research Unit Environmental Genomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Chase W. Nelson
- Sackler Institute for Comparative Genomics, American Museum of Natural History New York, New York, United States of America
| | - Michael Schloter
- Research Unit Environmental Genomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Burkhard Rost
- Department of Informatics—Bioinformatics & TUM-IAS, Technische Universität München, Garching, Germany
| | - Siegfried Scherer
- Chair for Microbial Ecology, Technische Universität München, Freising, Germany
- ZIEL - Institute for Food & Health, Technische Universität München, Freising, Germany
| | - Klaus Neuhaus
- Chair for Microbial Ecology, Technische Universität München, Freising, Germany
- Core Facility Microbiome/NGS, ZIEL - Institute for Food & Health, Technische Universität München, Freising, Germany
- * E-mail:
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Grüll MP, Peña-Castillo L, Mulligan ME, Lang AS. Genome-wide identification and characterization of small RNAs in Rhodobacter capsulatus and identification of small RNAs affected by loss of the response regulator CtrA. RNA Biol 2017; 14:914-925. [PMID: 28296577 PMCID: PMC5546546 DOI: 10.1080/15476286.2017.1306175] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/30/2022] Open
Abstract
Small non-coding RNAs (sRNAs) are involved in the control of numerous cellular processes through various regulatory mechanisms, and in the past decade many studies have identified sRNAs in a multitude of bacterial species using RNA sequencing (RNA-seq). Here, we present the first genome-wide analysis of sRNA sequencing data in Rhodobacter capsulatus, a purple nonsulfur photosynthetic alphaproteobacterium. Using a recently developed bioinformatics approach, sRNA-Detect, we detected 422 putative sRNAs from R. capsulatus RNA-seq data. Based on their sequence similarity to sRNAs in a sRNA collection, consisting of published putative sRNAs from 23 additional bacterial species, and RNA databases, the sequences of 124 putative sRNAs were conserved in at least one other bacterial species; and, 19 putative sRNAs were assigned a predicted function. We bioinformatically characterized all putative sRNAs and applied machine learning approaches to calculate the probability of a nucleotide sequence to be a bona fide sRNA. The resulting quantitative model was able to correctly classify 95.2% of sequences in a validation set. We found that putative cis-targets for antisense and partially overlapping sRNAs were enriched with protein-coding genes involved in primary metabolic processes, photosynthesis, compound binding, and with genes forming part of macromolecular complexes. We performed differential expression analysis to compare the wild type strain to a mutant lacking the response regulator CtrA, an important regulator of gene expression in R. capsulatus, and identified 18 putative sRNAs with differing levels in the two strains. Finally, we validated the existence and expression patterns of four novel sRNAs by Northern blot analysis.
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Affiliation(s)
- Marc P Grüll
- a Department of Biology , Memorial University of Newfoundland , St. John's , NL , Canada
| | - Lourdes Peña-Castillo
- a Department of Biology , Memorial University of Newfoundland , St. John's , NL , Canada.,b Department of Computer Science , Memorial University of Newfoundland , St. John's , NL , Canada
| | - Martin E Mulligan
- c Department of Biochemistry , Memorial University of Newfoundland , St. John's , NL , Canada
| | - Andrew S Lang
- a Department of Biology , Memorial University of Newfoundland , St. John's , NL , Canada
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Kwon HH, Suh DH. Recent progress in the research aboutPropionibacterium acnesstrain diversity and acne: pathogen or bystander? Int J Dermatol 2016; 55:1196-1204. [DOI: 10.1111/ijd.13282] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2015] [Revised: 11/10/2015] [Accepted: 12/05/2015] [Indexed: 12/25/2022]
Affiliation(s)
- Hyuck Hoon Kwon
- Department of Dermatology; Seoul National University College of Medicine and Acne & Rosacea Research Laboratory, Seoul National University Hospital; Seoul Korea
| | - Dae Hun Suh
- Department of Dermatology; Seoul National University College of Medicine and Acne & Rosacea Research Laboratory, Seoul National University Hospital; Seoul Korea
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10
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Sass AM, Van Acker H, Förstner KU, Van Nieuwerburgh F, Deforce D, Vogel J, Coenye T. Genome-wide transcription start site profiling in biofilm-grown Burkholderia cenocepacia J2315. BMC Genomics 2015; 16:775. [PMID: 26462475 PMCID: PMC4603805 DOI: 10.1186/s12864-015-1993-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2015] [Accepted: 10/06/2015] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Burkholderia cenocepacia is a soil-dwelling Gram-negative Betaproteobacterium with an important role as opportunistic pathogen in humans. Infections with B. cenocepacia are very difficult to treat due to their high intrinsic resistance to most antibiotics. Biofilm formation further adds to their antibiotic resistance. B. cenocepacia harbours a large, multi-replicon genome with a high GC-content, the reference genome of strain J2315 includes 7374 annotated genes. This study aims to annotate transcription start sites and identify novel transcripts on a whole genome scale. METHODS RNA extracted from B. cenocepacia J2315 biofilms was analysed by differential RNA-sequencing and the resulting dataset compared to data derived from conventional, global RNA-sequencing. Transcription start sites were annotated and further analysed according to their position relative to annotated genes. RESULTS Four thousand ten transcription start sites were mapped over the whole B. cenocepacia genome and the primary transcription start site of 2089 genes expressed in B. cenocepacia biofilms were defined. For 64 genes a start codon alternative to the annotated one was proposed. Substantial antisense transcription for 105 genes and two novel protein coding sequences were identified. The distribution of internal transcription start sites can be used to identify genomic islands in B. cenocepacia. A potassium pump strongly induced only under biofilm conditions was found and 15 non-coding small RNAs highly expressed in biofilms were discovered. CONCLUSIONS Mapping transcription start sites across the B. cenocepacia genome added relevant information to the J2315 annotation. Genes and novel regulatory RNAs putatively involved in B. cenocepacia biofilm formation were identified. These findings will help in understanding regulation of B. cenocepacia biofilm formation.
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Affiliation(s)
- Andrea M Sass
- Laboratory of Pharmaceutical Microbiology, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium.
| | - Heleen Van Acker
- Laboratory of Pharmaceutical Microbiology, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium.
| | - Konrad U Förstner
- Core Unit Systems Medicine, University of Würzburg, Würzburg, Germany.
| | | | - Dieter Deforce
- Laboratory of Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium.
| | - Jörg Vogel
- Institute for Molecular Infection Biology, University of Würzburg, Würzburg, Germany.
| | - Tom Coenye
- Laboratory of Pharmaceutical Microbiology, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium.
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Bischler T, Tan HS, Nieselt K, Sharma CM. Differential RNA-seq (dRNA-seq) for annotation of transcriptional start sites and small RNAs in Helicobacter pylori. Methods 2015; 86:89-101. [PMID: 26091613 DOI: 10.1016/j.ymeth.2015.06.012] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2015] [Revised: 06/07/2015] [Accepted: 06/09/2015] [Indexed: 12/29/2022] Open
Abstract
The global mapping of transcription boundaries is a key step in the elucidation of the full complement of transcriptional features of an organism. It facilitates the annotation of operons and untranslated regions as well as novel transcripts, including cis- and trans-encoded small RNAs (sRNAs). So called RNA sequencing (RNA-seq) based on deep sequencing of cDNAs has greatly facilitated transcript mapping with single nucleotide resolution. However, conventional RNA-seq approaches typically cannot distinguish between primary and processed transcripts. Here we describe the recently developed differential RNA-seq (dRNA-seq) approach, which facilitates the annotation of transcriptional start sites (TSS) based on deep sequencing of two differentially treated cDNA library pairs, with one library being enriched for primary transcripts. Using the human pathogen Helicobacter pylori as a model organism, we describe the application of dRNA-seq together with an automated TSS annotation approach for generation of a genome-wide TSS map in bacteria. Besides a description of transcriptome and regulatory features that can be identified by this approach, we discuss the impact of different library preparation protocols and sequencing platforms as well as manual and automated TSS annotation. Moreover, we have set up an easily accessible online browser for visualization of the H. pylori transcriptome data from this and our previous H. pylori dRNA-seq study.
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Affiliation(s)
- Thorsten Bischler
- Research Center for Infectious Diseases (ZINF), University of Würzburg, Josef-Schneider-Str. 2/Bau D15, 97080 Würzburg, Germany
| | - Hock Siew Tan
- Research Center for Infectious Diseases (ZINF), University of Würzburg, Josef-Schneider-Str. 2/Bau D15, 97080 Würzburg, Germany
| | - Kay Nieselt
- Integrative Transcriptomics, ZBIT (Center for Bioinformatics Tübingen), University of Tübingen, Sand 14, D-72076 Tübingen, Germany
| | - Cynthia M Sharma
- Research Center for Infectious Diseases (ZINF), University of Würzburg, Josef-Schneider-Str. 2/Bau D15, 97080 Würzburg, Germany.
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12
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Creecy JP, Conway T. Quantitative bacterial transcriptomics with RNA-seq. Curr Opin Microbiol 2014; 23:133-40. [PMID: 25483350 DOI: 10.1016/j.mib.2014.11.011] [Citation(s) in RCA: 85] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2014] [Revised: 11/11/2014] [Accepted: 11/12/2014] [Indexed: 02/06/2023]
Abstract
RNA sequencing has emerged as the premier approach to study bacterial transcriptomes. While the earliest published studies analyzed the data qualitatively, the data are readily digitized and lend themselves to quantitative analysis. High-resolution RNA sequence (RNA-seq) data allows transcriptional features (promoters, terminators, operons, among others) to be pinpointed on any bacterial transcriptome. Once the transcriptome is mapped, the activity of transcriptional features can be quantified. Here we highlight how quantitative transcriptome analysis can reveal biological insights and briefly discuss some of the challenges to be faced by the field of bacterial transcriptomics in the near future.
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Affiliation(s)
- James P Creecy
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, United States; Department of Biology, University of Central Oklahoma, Edmond, OK 73034, United States
| | - Tyrrell Conway
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, United States.
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Clarke JE, Kime L, Romero A D, McDowall KJ. Direct entry by RNase E is a major pathway for the degradation and processing of RNA in Escherichia coli. Nucleic Acids Res 2014; 42:11733-51. [PMID: 25237058 PMCID: PMC4191395 DOI: 10.1093/nar/gku808] [Citation(s) in RCA: 74] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2014] [Revised: 08/20/2014] [Accepted: 08/21/2014] [Indexed: 12/20/2022] Open
Abstract
Escherichia coli endoribonuclease E has a major influence on gene expression. It is essential for the maturation of ribosomal and transfer RNA as well as the rapid degradation of messenger RNA. The latter ensures that translation closely follows programming at the level of transcription. Recently, one of the hallmarks of RNase E, i.e. its ability to bind via a 5'-monophosphorylated end, was shown to be unnecessary for the initial cleavage of some polycistronic tRNA precursors. Here we show using RNA-seq analyses of ribonuclease-deficient strains in vivo and a 5'-sensor mutant of RNase E in vitro that, contrary to current models, 5'-monophosphate-independent, 'direct entry' cleavage is a major pathway for degrading and processing RNA. Moreover, we present further evidence that direct entry is facilitated by RNase E binding simultaneously to multiple unpaired regions. These simple requirements may maximize the rate of degradation and processing by permitting multiple sites to be surveyed directly without being constrained by 5'-end tethering. Cleavage was detected at a multitude of sites previously undescribed for RNase E, including ones that regulate the activity and specificity of ribosomes. A potentially broad role for RNase G, an RNase E paralogue, in the trimming of 5'-monophosphorylated ends was also revealed.
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Affiliation(s)
- Justin E Clarke
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
| | - Louise Kime
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
| | - David Romero A
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
| | - Kenneth J McDowall
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
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14
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Romero DA, Hasan AH, Lin YF, Kime L, Ruiz-Larrabeiti O, Urem M, Bucca G, Mamanova L, Laing EE, van Wezel GP, Smith CP, Kaberdin VR, McDowall KJ. A comparison of key aspects of gene regulation in Streptomyces coelicolor and Escherichia coli using nucleotide-resolution transcription maps produced in parallel by global and differential RNA sequencing. Mol Microbiol 2014; 94:963-987. [PMID: 25266672 PMCID: PMC4681348 DOI: 10.1111/mmi.12810] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/27/2014] [Indexed: 12/12/2022]
Abstract
Streptomyces coelicolor is a model for studying bacteria renowned as the foremost source of natural products used clinically. Post-genomic studies have revealed complex patterns of gene expression and links to growth, morphological development and individual genes. However, the underlying regulation remains largely obscure, but undoubtedly involves steps after transcription initiation. Here we identify sites involved in RNA processing and degradation as well as transcription within a nucleotide-resolution map of the transcriptional landscape. This was achieved by combining RNA-sequencing approaches suited to the analysis of GC-rich organisms. Escherichia coli was analysed in parallel to validate the methodology and allow comparison. Previously, sites of RNA processing and degradation had not been mapped on a transcriptome-wide scale for E. coli. Through examples, we show the value of our approach and data sets. This includes the identification of new layers of transcriptional complexity associated with several key regulators of secondary metabolism and morphological development in S. coelicolor and the identification of host-encoded leaderless mRNA and rRNA processing associated with the generation of specialized ribosomes in E. coli. New regulatory small RNAs were identified for both organisms. Overall the results illustrate the diversity in mechanisms used by different bacterial groups to facilitate and regulate gene expression.
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Affiliation(s)
- David A Romero
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of LeedsLeeds, LS2 9JT, UK
| | - Ayad H Hasan
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of LeedsLeeds, LS2 9JT, UK
| | - Yu-fei Lin
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of LeedsLeeds, LS2 9JT, UK
| | - Louise Kime
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of LeedsLeeds, LS2 9JT, UK
| | - Olatz Ruiz-Larrabeiti
- Department of Immunology, Microbiology and Parasitology, University of the Basque Country UPV/EHULeioa, Spain
| | - Mia Urem
- Institute of Biology, Sylvius Laboratories, Leiden UniversityLeiden, NL-2300 RA, The Netherlands
| | - Giselda Bucca
- Department of Microbial & Cellular Sciences, Faculty of Health & Medical Sciences, University of SurreyGuildford, GU2 7XH, UK
| | - Lira Mamanova
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome CampusHinxton, Cambridge, CB10 1SA, UK
| | - Emma E Laing
- Department of Microbial & Cellular Sciences, Faculty of Health & Medical Sciences, University of SurreyGuildford, GU2 7XH, UK
| | - Gilles P van Wezel
- Institute of Biology, Sylvius Laboratories, Leiden UniversityLeiden, NL-2300 RA, The Netherlands
| | - Colin P Smith
- Department of Microbial & Cellular Sciences, Faculty of Health & Medical Sciences, University of SurreyGuildford, GU2 7XH, UK
| | - Vladimir R Kaberdin
- Department of Immunology, Microbiology and Parasitology, University of the Basque Country UPV/EHULeioa, Spain
- IKERBASQUE, Basque Foundation for Science48011, Bilbao, Spain
| | - Kenneth J McDowall
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of LeedsLeeds, LS2 9JT, UK
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15
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Global transcriptional start site mapping using differential RNA sequencing reveals novel antisense RNAs in Escherichia coli. J Bacteriol 2014; 197:18-28. [PMID: 25266388 DOI: 10.1128/jb.02096-14] [Citation(s) in RCA: 218] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
While the model organism Escherichia coli has been the subject of intense study for decades, the full complement of its RNAs is only now being examined. Here we describe a survey of the E. coli transcriptome carried out using a differential RNA sequencing (dRNA-seq) approach, which can distinguish between primary and processed transcripts, and an automated prediction algorithm for transcriptional start sites (TSS). With the criterion of expression under at least one of three growth conditions examined, we predicted 14,868 TSS candidates, including 5,574 internal to annotated genes (iTSS) and 5,495 TSS corresponding to potential antisense RNAs (asRNAs). We examined expression of 14 candidate asRNAs by Northern analysis using RNA from wild-type E. coli and from strains defective for RNases III and E, two RNases reported to be involved in asRNA processing. Interestingly, nine asRNAs detected as distinct bands by Northern analysis were differentially affected by the rnc and rne mutations. We also compared our asRNA candidates with previously published asRNA annotations from RNA-seq data and discuss the challenges associated with these cross-comparisons. Our global transcriptional start site map represents a valuable resource for identification of transcription start sites, promoters, and novel transcripts in E. coli and is easily accessible, together with the cDNA coverage plots, in an online genome browser.
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Sharma CM, Vogel J. Differential RNA-seq: the approach behind and the biological insight gained. Curr Opin Microbiol 2014; 19:97-105. [PMID: 25024085 DOI: 10.1016/j.mib.2014.06.010] [Citation(s) in RCA: 142] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2014] [Revised: 06/15/2014] [Accepted: 06/19/2014] [Indexed: 01/14/2023]
Abstract
RNA-sequencing has revolutionized the quantitative and qualitative analysis of transcriptomes in both prokaryotes and eukaryotes. It provides a generic approach for gene expression profiling, annotation of transcript boundaries and operons, as well as identifying novel transcripts including small noncoding RNA molecules and antisense RNAs. We recently developed a differential RNA-seq (dRNA-seq) method which in addition to the above, yields information as to whether a given RNA is a primary or processed transcript. Originally applied to describe the primary transcriptome of the gastric pathogen Helicobacter pylori, dRNA-seq has since provided global maps of transcriptional start sites in diverse species, informed new biology in the CRISPR-Cas9 system, advanced to a tool for comparative transcriptomics, and inspired simultaneous RNA-seq of pathogen and host.
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Affiliation(s)
- Cynthia M Sharma
- University of Würzburg, Institute for Molecular Infection Biology & Research Center for Infectious Diseases, Josef-Schneider-Straße 2/D15, D-97080 Würzburg, Germany.
| | - Jörg Vogel
- University of Würzburg, Institute for Molecular Infection Biology & Research Center for Infectious Diseases, Josef-Schneider-Straße 2/D15, D-97080 Würzburg, Germany.
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Unprecedented high-resolution view of bacterial operon architecture revealed by RNA sequencing. mBio 2014; 5:e01442-14. [PMID: 25006232 PMCID: PMC4161252 DOI: 10.1128/mbio.01442-14] [Citation(s) in RCA: 128] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
We analyzed the transcriptome of Escherichia coli K-12 by strand-specific RNA sequencing at single-nucleotide resolution during steady-state (logarithmic-phase) growth and upon entry into stationary phase in glucose minimal medium. To generate high-resolution transcriptome maps, we developed an organizational schema which showed that in practice only three features are required to define operon architecture: the promoter, terminator, and deep RNA sequence read coverage. We precisely annotated 2,122 promoters and 1,774 terminators, defining 1,510 operons with an average of 1.98 genes per operon. Our analyses revealed an unprecedented view of E. coli operon architecture. A large proportion (36%) of operons are complex with internal promoters or terminators that generate multiple transcription units. For 43% of operons, we observed differential expression of polycistronic genes, despite being in the same operons, indicating that E. coli operon architecture allows fine-tuning of gene expression. We found that 276 of 370 convergent operons terminate inefficiently, generating complementary 3′ transcript ends which overlap on average by 286 nucleotides, and 136 of 388 divergent operons have promoters arranged such that their 5′ ends overlap on average by 168 nucleotides. We found 89 antisense transcripts of 397-nucleotide average length, 7 unannotated transcripts within intergenic regions, and 18 sense transcripts that completely overlap operons on the opposite strand. Of 519 overlapping transcripts, 75% correspond to sequences that are highly conserved in E. coli (>50 genomes). Our data extend recent studies showing unexpected transcriptome complexity in several bacteria and suggest that antisense RNA regulation is widespread. We precisely mapped the 5′ and 3′ ends of RNA transcripts across the E. coli K-12 genome by using a single-nucleotide analytical approach. Our resulting high-resolution transcriptome maps show that ca. one-third of E. coli operons are complex, with internal promoters and terminators generating multiple transcription units and allowing differential gene expression within these operons. We discovered extensive antisense transcription that results from more than 500 operons, which fully overlap or extensively overlap adjacent divergent or convergent operons. The genomic regions corresponding to these antisense transcripts are highly conserved in E. coli (including Shigella species), although it remains to be proven whether or not they are functional. Our observations of features unearthed by single-nucleotide transcriptome mapping suggest that deeper layers of transcriptional regulation in bacteria are likely to be revealed in the future.
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18
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Neshat A, Mentz A, Rückert C, Kalinowski J. Transcriptome sequencing revealed the transcriptional organization at ribosome-mediated attenuation sites in Corynebacterium glutamicum and identified a novel attenuator involved in aromatic amino acid biosynthesis. J Biotechnol 2014; 190:55-63. [PMID: 24910972 DOI: 10.1016/j.jbiotec.2014.05.033] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Revised: 05/02/2014] [Accepted: 05/14/2014] [Indexed: 11/27/2022]
Abstract
The Gram-positive bacterium Corynebacterium glutamicum belongs to the order Corynebacteriales and is used as a producer of amino acids at industrial scales. Due to its economic importance, gene expression and particularly the regulation of amino acid biosynthesis has been investigated extensively. Applying the high-resolution technique of transcriptome sequencing (RNA-seq), recently a vast amount of data has been generated that was used to comprehensively analyze the C. glutamicum transcriptome. By analyzing RNA-seq data from a small RNA cDNA library of C. glutamicum, short transcripts in the known transcriptional attenuators sites of the trp operon, the ilvBNC operon and the leuA gene were verified. Furthermore, whole transcriptome RNA-seq data were used to elucidate the transcriptional organization of these three amino acid biosynthesis operons. In addition, we discovered and analyzed the novel attenuator aroR, located upstream of the aroF gene (cg1129). The DAHP synthase encoded by aroF catalyzes the first step in aromatic amino acid synthesis. The AroR leader peptide contains the amino acid sequence motif F-Y-F, indicating a regulatory effect by phenylalanine and tyrosine. Analysis by real-time RT-PCR suggests that the attenuator regulates the transcription of aroF in dependence of the cellular amount of tRNA loaded with phenylalanine when comparing a phenylalanine-auxotrophic C. glutamicum mutant fed with limiting and excess amounts of a phenylalanine-containing dipeptide. Additionally, the very interesting finding was made that all analyzed attenuators are leaderless transcripts.
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Affiliation(s)
- Armin Neshat
- Microbial Genomics and Biotechnology, Center for Biotechnology, Bielefeld University, Universitätsstraße 27, 33615 Bielefeld, Germany
| | - Almut Mentz
- Microbial Genomics and Biotechnology, Center for Biotechnology, Bielefeld University, Universitätsstraße 27, 33615 Bielefeld, Germany
| | - Christian Rückert
- Microbial Genomics and Biotechnology, Center for Biotechnology, Bielefeld University, Universitätsstraße 27, 33615 Bielefeld, Germany; Technology Platform Genomics, Center for Biotechnology, Bielefeld University, Universitätsstraße 27, 33615 Bielefeld, Germany
| | - Jörn Kalinowski
- Microbial Genomics and Biotechnology, Center for Biotechnology, Bielefeld University, Universitätsstraße 27, 33615 Bielefeld, Germany; Technology Platform Genomics, Center for Biotechnology, Bielefeld University, Universitätsstraße 27, 33615 Bielefeld, Germany.
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Mirauta B, Nicolas P, Richard H. Parseq: reconstruction of microbial transcription landscape from RNA-Seq read counts using state-space models. ACTA ACUST UNITED AC 2014; 30:1409-16. [PMID: 24470570 DOI: 10.1093/bioinformatics/btu042] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
MOTIVATION The most common RNA-Seq strategy consists of random shearing, amplification and high-throughput sequencing of the RNA fraction. Methods to analyze transcription level variations along the genome from the read count profiles generated by the RNA-Seq protocol are needed. RESULTS We developed a statistical approach to estimate the local transcription levels and to identify transcript borders. This transcriptional landscape reconstruction relies on a state-space model to describe transcription level variations in terms of abrupt shifts and more progressive drifts. A new emission model is introduced to capture not only the read count variance inside a transcript but also its short-range autocorrelation and the fraction of positions with zero counts. The estimation relies on a particle Gibbs algorithm whose running time makes it more suited to microbial genomes. The approach outperformed read-overlapping strategies on synthetic and real microbial datasets. AVAILABILITY A program named Parseq is available at: http://www.lgm.upmc.fr/parseq/. CONTACT bodgan.mirauta@upmc.fr SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Bogdan Mirauta
- Biologie Computationnelle et Quantitative, UPMC and CNRS UMR7238, Paris, France and Mathématique Informatique et Génome, INRA UR1077, Jouy-en-Josas, France
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