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      The Mycobacterium tuberculosis transcriptional landscape under genotoxic stress

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          Abstract

          Background

          As an intracellular human pathogen, Mycobacterium tuberculosis (Mtb) is facing multiple stressful stimuli inside the macrophage and the granuloma. Understanding Mtb responses to stress is essential to identify new virulence factors and pathways that play a role in the survival of the tubercle bacillus. The main goal of this study was to map the regulatory networks of differentially expressed (DE) transcripts in Mtb upon various forms of genotoxic stress. We exposed Mtb cells to oxidative (H 2O 2 or paraquat), nitrosative (DETA/NO), or alkylation (MNNG) stress or mitomycin C, inducing double-strand breaks in the DNA. Total RNA was isolated from treated and untreated cells and subjected to high-throughput deep sequencing. The data generated was analysed to identify DE genes encoding mRNAs, non-coding RNAs (ncRNAs), and the genes potentially targeted by ncRNAs.

          Results

          The most significant transcriptomic alteration with more than 700 DE genes was seen under nitrosative stress. In addition to genes that belong to the replication, recombination and repair (3R) group, mainly found under mitomycin C stress, we identified DE genes important for bacterial virulence and survival, such as genes of the type VII secretion system (T7SS) and the proline-glutamic acid/proline-proline-glutamic acid (PE/PPE) family. By predicting the structures of hypothetical proteins (HPs) encoded by DE genes, we found that some of these HPs might be involved in mycobacterial genome maintenance. We also applied a state-of-the-art method to predict potential target genes of the identified ncRNAs and found that some of these could regulate several genes that might be directly involved in the response to genotoxic stress.

          Conclusions

          Our study reflects the complexity of the response of Mtb in handling genotoxic stress. In addition to genes involved in genome maintenance, other potential key players, such as the members of the T7SS and PE/PPE gene family, were identified. This plethora of responses is detected not only at the level of DE genes encoding mRNAs but also at the level of ncRNAs and their potential targets.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-016-3132-1) contains supplementary material, which is available to authorized users.

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          Most cited references60

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          Bacterial iron homeostasis.

          Iron is essential to virtually all organisms, but poses problems of toxicity and poor solubility. Bacteria have evolved various mechanisms to counter the problems imposed by their iron dependence, allowing them to achieve effective iron homeostasis under a range of iron regimes. Highly efficient iron acquisition systems are used to scavenge iron from the environment under iron-restricted conditions. In many cases, this involves the secretion and internalisation of extracellular ferric chelators called siderophores. Ferrous iron can also be directly imported by the G protein-like transporter, FeoB. For pathogens, host-iron complexes (transferrin, lactoferrin, haem, haemoglobin) are directly used as iron sources. Bacterial iron storage proteins (ferritin, bacterioferritin) provide intracellular iron reserves for use when external supplies are restricted, and iron detoxification proteins (Dps) are employed to protect the chromosome from iron-induced free radical damage. There is evidence that bacteria control their iron requirements in response to iron availability by down-regulating the expression of iron proteins during iron-restricted growth. And finally, the expression of the iron homeostatic machinery is subject to iron-dependent global control ensuring that iron acquisition, storage and consumption are geared to iron availability and that intracellular levels of free iron do not reach toxic levels.
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            Genes required for mycobacterial growth defined by high density mutagenesis.

            Despite over a century of research, tuberculosis remains a leading cause of infectious death worldwide. Faced with increasing rates of drug resistance, the identification of genes that are required for the growth of this organism should provide new targets for the design of antimycobacterial agents. Here, we describe the use of transposon site hybridization (TraSH) to comprehensively identify the genes required by the causative agent, Mycobacterium tuberculosis, for optimal growth. These genes include those that can be assigned to essential pathways as well as many of unknown function. The genes important for the growth of M. tuberculosis are largely conserved in the degenerate genome of the leprosy bacillus, Mycobacterium leprae, indicating that non-essential functions have been selectively lost since this bacterium diverged from other mycobacteria. In contrast, a surprisingly high proportion of these genes lack identifiable orthologues in other bacteria, suggesting that the minimal gene set required for survival varies greatly between organisms with different evolutionary histories.
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              Regulatory RNAs in bacteria.

              Bacteria possess numerous and diverse means of gene regulation using RNA molecules, including mRNA leaders that affect expression in cis, small RNAs that bind to proteins or base pair with target RNAs, and CRISPR RNAs that inhibit the uptake of foreign DNA. Although examples of RNA regulators have been known for decades in bacteria, we are only now coming to a full appreciation of their importance and prevalence. Here, we review the known mechanisms and roles of regulatory RNAs, highlight emerging themes, and discuss remaining questions.
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                Author and article information

                Contributors
                sbala@rr-research.no
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                10 October 2016
                10 October 2016
                2016
                : 17
                : 791
                Affiliations
                [1 ]Department of Microbiology, Oslo University Hospital, Postboks 4950, NO-0424 Oslo, Norway
                [2 ]Department of Microbiology, University of Oslo, Oslo, Norway
                [3 ]Department of Informatics, University of Oslo, Oslo, Norway
                [4 ]Current address: Department of Nutrition, University of Oslo, Oslo, Norway
                Article
                3132
                10.1186/s12864-016-3132-1
                5057432
                27724857
                89093a3e-293e-4067-a58a-a0e893a39cf1
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 29 April 2016
                : 27 September 2016
                Funding
                Funded by: Research Council of Norway GLOBVAC
                Award ID: 234506
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100005366, Universitetet i Oslo;
                Award ID: UNIFOR
                Award Recipient :
                Funded by: Research Council of Norway, FRIMED
                Award ID: 204747
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Genetics
                mycobacterium tuberculosis,transcriptomics,genotoxic stress,rna deep-sequencing,non-coding rna (ncrna)

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