Developmental transcriptome of resting cell formation in Mycobacterium smegmatis

Wu, Mu Lu; Gengenbacher, Martin; Chung, Jade C. S.; Chen, Swaine L.; Mollenkopf, Hans-Joachim; Kaufmann, Stefan H. E.; Dick, Thomas

doi:10.1186/s12864-016-3190-4

Cited by 21 publications

(12 citation statements)

References 41 publications

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“…In mc 2 155, Shell et al ( 2015 ) revealed a high abundance of leaderless mRNAs and small proteins by the combination of RNA-seq and ribosome profiling data. Other studies mainly focused on the identification of DEGs in different conditions (Petridis et al, 2015 ; Li et al, 2016 ; Wu et al, 2016 ; Hillion et al, 2017 ). However, no comprehensive insights have been achieved regarding M. smegmatis yet.…”

Section: Introductionmentioning

confidence: 99%

Transcriptome Landscape of Mycobacterium smegmatis

Li¹,

Han²,

Chen³

et al. 2017

Front. Microbiol.

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The non-pathogenic bacterium Mycobacterium smegmatis mc2155 has been widely used as a model organism in mycobacterial research, yet a detailed study about its transcription landscape remains to be established. Here we report the transcriptome, expression profiles and transcriptional structures through growth-phase-dependent RNA sequencing (RNA-seq) as well as other related experiments. We found: (1) 2,139 transcriptional start sites (TSSs) in the genome-wide scale, of which eight samples were randomly selected and further verified by 5′-RACE; (2) 2,233 independent monocistronic or polycistronic mRNAs in the transcriptome within the operon/sub-operon structures which are classified into five groups; (3) 47.50% (1016/2139) genes were transcribed into leaderless mRNAs, with the TSSs of 41.3% (883/2139) mRNAs overlapping with the first base of the annotated start codon. Initial amino acids of MSMEG_4921 and MSMEG_6422 proteins were identified by Edman degradation, indicating the presence of distinctive widespread leaderless features in M. smegmatis mc2155. (4) 150 genes with potentially wrong structural annotation, of which 124 proposed genes have been corrected; (5) eight highly active promoters, with their activities further determined by β-galactosidase assays. These data integrated the transcriptional landscape to genome information of model organism mc2155 and lay a solid foundation for further works in Mycobacterium.

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Section: Introductionmentioning

confidence: 99%

Transcriptome Landscape of Mycobacterium smegmatis

Li¹,

Han²,

Chen³

et al. 2017

Front. Microbiol.

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“…For mycobacteria treated with antibiotics, which disrupt formation of the cell wall (such as Cycloserine, ethambutol, and isoniazid), elevated transcription of the transcriptional regulator whiB2 was shown [ 38 , 39 ]. Mycobacterium smegmatis also overexpresses whiB2 during the transition to uncultivated forms [ 40 ]. In our study, we detected the increased expression of MSMEG_1831/whiB2 upon Olivomycin treatment.…”

Section: Resultsmentioning

confidence: 99%

Aureolic Acid Group of Agents as Potential Antituberculosis Drugs

et al. 2020

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Mycobacterium tuberculosis is one of the most dangerous pathogens. Bacterial resistance to antituberculosis drugs grows each year, but searching for new drugs is a long process. Testing for available drugs to find active against mycobacteria may be a good alternative. In this work, antibiotics of the aureolic acid group were tested on a model organism Mycobacterium smegmatis. We presumed that antibiotics of this group may be potential G4 ligands. However, this was not confirmed in our analyses. We determined the antimicrobial activity of these drugs and revealed morphological changes in the cell structure upon treatment. Transcriptomic analysis documented increased expression of MSMEG_3743/soj and MSMEG_4228/ftsW, involved in cell division. Therefore, drugs may affect cell division, possibly disrupting the function of the Z-ring and the formation of a septum. Additionally, a decrease in the transcription level of several indispensable genes, such as nitrate reductase subunits (MSMEG_5137/narI and MSMEG_5139/narX) and MSMEG_3205/hisD was shown. We concluded that the mechanism of action of aureolic acid and its related compounds may be similar to that bedaquiline and disturb the NAD+/NADH balance in the cell. All of this allowed us to conclude that aureolic acid derivatives can be considered as potential antituberculosis drugs.

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“…Ftsw , ftsz , and pbp3 -encoded proteins can form a ternary complex to potentially regulate peptidoglycan biogenesis. Roda glycosyltransferase is also involved in peptidoglycan synthesis ( Wu et al, 2016 ). Figure 6C shows that Subnet 2 contains 13 ESX-1 secretory system-related genes.…”

Section: Resultsmentioning

confidence: 99%

High-Throughput Screen for Cell Wall Synthesis Network Module in Mycobacterium tuberculosis Based on Integrated Bioinformatics Strategy

Luo

Pan

Meng

et al. 2020

Front. Bioeng. Biotechnol.

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Background: Mycobacterium tuberculosis is one of the deadliest pathogens in humans. Co-infection of M. tuberculosis with HIV and the emergence of multi-drugresistant tuberculosis (TB) constitute a serious global threat. However, no effective anti-TB drugs are available, with the exception of first-line drugs such as isoniazid. The cell wall of M. tuberculosis, which is primarily responsible for the lack of effective anti-TB drugs and the escape of the bacteria from host immunity, is an important drug target. The core components of the cell wall of M. tuberculosis are peptidoglycan, arabinogalactan, and mycotic acid. However, the functional genome and metabolic regulation pathways for the M. tuberculosis cell wall are still unknown. In this study, we used the biclustering algorithm integrated into cMonkey, sequence alignment, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and other bioinformatics methods to scan the whole genome of M. tuberculosis as well as to identify and statistically analyze the genes related to the synthesis of the M. tuberculosis cell wall. Method: We performed high-throughput genome-wide screening for M. tuberculosis using Biocarta, KEGG, National Cancer Institute Pathway Interaction Database (NCI-PID), HumanCyc, and Reactome. We then used the Database of Origin and Registration (DOOR) established in our laboratory to classify the collection of operons for M. tuberculosis cell wall synthetic genes. We used the cMonkey double clustering algorithm to perform clustering analysis on the gene expression profile of M. tuberculosis for cell wall synthesis. Finally, we visualized the results using Cytoscape. Result and Conclusion: Through bioinformatics and statistical analyses, we identified 893 M. tuberculosis H37Rv cell wall synthesis genes, distributed in 20 pathways, involved in 46 different functions related to cell wall synthesis, and clustered in 386 modules. We identified important pivotal genes and proteins in the cell wall synthesis

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Developmental transcriptome of resting cell formation in Mycobacterium smegmatis

Cited by 21 publications

References 41 publications

Transcriptome Landscape of Mycobacterium smegmatis

Transcriptome Landscape of Mycobacterium smegmatis

Aureolic Acid Group of Agents as Potential Antituberculosis Drugs

High-Throughput Screen for Cell Wall Synthesis Network Module in Mycobacterium tuberculosis Based on Integrated Bioinformatics Strategy

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