Abstract
A better understanding of essential cellular functions in pathogenic bacteria is important for the development of more effective antimicrobial agents. We performed a comprehensive identification of essential genes in Mycobacterium tuberculosis, the major causative agent of tuberculosis, using a combination of transposon insertion sequencing (Tn-seq) and comparative genomic analysis. To identify conditionally essential genes by Tn-seq, we used media with different nutrient compositions. Although many conditional gene essentialities were affected by the presence of relevant nutrient sources, we also found that the essentiality of genes in a subset of metabolic pathways was unaffected by metabolite availability. Comparative genomic analysis revealed that not all essential genes identified by Tn-seq were fully conserved within the M. tuberculosis complex, including some existing antitubercular drug target genes. In addition, we utilized an available M. tuberculosis genome-scale metabolic model, iSM810, to predict M. tuberculosis gene essentiality in silico. Comparing the sets of essential genes experimentally identified by Tn-seq to those predicted in silico reveals the capabilities and limitations of gene essentiality predictions, highlighting the complexity of M. tuberculosis essential metabolic functions. This study provides a promising platform to study essential cellular functions in M. tuberculosis. IMPORTANCE Mycobacterium tuberculosis causes 10 million cases of tuberculosis (TB), resulting in over 1 million deaths each year. TB therapy is challenging because it requires a minimum of 6 months of treatment with multiple drugs. Protracted treatment times and the emergent spread of drug-resistant M. tuberculosis necessitate the identification of novel targets for drug discovery to curb this global health threat. Essential functions, defined as those indispensable for growth and/or survival, are potential targets for new antimicrobial drugs. In this study, we aimed to define gene essentialities of M. tuberculosis on a genomewide scale to comprehensively identify potential targets for drug discovery. We utilized a combination of experimental (functional genomics) and in silico approaches (comparative genomics and flux balance analysis). Our functional genomics approach identified sets of genes whose essentiality was affected by nutrient availability. Comparative genomics revealed that not all essential genes were fully conserved within the M. tuberculosis complex. Comparing sets of essential genes identified by functional genomics to those predicted by flux balance analysis highlighted gaps in current knowledge regarding M. tuberculosis metabolic capabilities. Thus, our study identifies numerous potential antitubercular drug targets and provides a comprehensive picture of the complexity of M. tuberculosis essential cellular functions.
Original language | English (US) |
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Article number | e00070-19 |
Journal | mSystems |
Volume | 4 |
Issue number | 4 |
DOIs | |
State | Published - Jun 25 2019 |
Bibliographical note
Funding Information:This study was supported by funds from the Minnesota Partnership for Biotechnology and Medical Genomics (ML2012, chapter 5, article 1, section 5, subdivision 5e, to A.D.B.), the American Lung Association (to A.D.B.), the National Institutes of Health (grants GM121498 to W.R.H. and AI123146 to A.D.B.), the Japan Agency for Medical Research (AMED; project 17fk0108116h0401 to F.M.), and Kakenhi (grants 18K19674 and 16H05501 to F.M.).
Publisher Copyright:
Copyright © 2019 Minato et al.
Keywords
- Comparative genomics
- Metabolic modeling
- Metabolism
- Tn-seq
- Tuberculosis
PubMed: MeSH publication types
- Journal Article
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TnSeq of Himar1 transposon library of Mycobacterium tuberculosis H37Rv grown in vitro (on Mtb YM rich or Mtb minimal).
Minato, Y. & Baughn, A., Data Repository for the University of Minnesota, 2019
DOI: 10.13020/c37f-nv41, http://hdl.handle.net/11299/203632
Dataset