Exploring the transcription start sites and other genomic features facilitates the accurate identification and annotation of small RNAs across multiple stress conditions in Mycobacterium tuberculosis.

Mycobacterium tuberculosis (MTB) is a pathogen that is known for its ability to persist in harsh environments and cause chronic infections. Understanding the regulatory networks of MTB is crucial for developing effective treatments. Small regulatory RNAs (sRNAs) play important roles in gene expression regulation in all kingdoms of life, and their classification based solely on genomic location can be imprecise due to the computational-based prediction of protein-coding genes in bacteria, which often neglects segments of mRNA such as 5'UTRs, 3'UTRs, and intercistronic regions of operons. To address this issue, our study simultaneously discovered genomic features such as TSSs, UTRs, and operons together with sRNAs in the M. tuberculosis H37Rv strain (ATCC 27294) across multiple stress conditions. Our analysis identified 1,376 sRNA candidates and 8,173 TSSs in MTB, providing valuable insights into its complex regulatory landscape. TSS mapping enabled us to classify these sRNAs into more specific categories, including promoter-associated sRNAs, 5'UTR-derived sRNAs, 3'UTR-derived sRNAs, true intergenic sRNAs, and antisense sRNAs. Three of these sRNA candidates were experimentally validated using 3'-RACE-PCR: predictedRNA_0240, predictedRNA_0325, and predictedRNA_0578. Future characterization and validation are necessary to fully elucidate the functions and roles of these sRNAs in MTB. Our study is the first to simultaneously unravel TSSs and sRNAs in MTB and demonstrate that the identification of other genomic features, such as TSSs, UTRs, and operons, allows for more accurate and specific classification of sRNAs.

Bacterial regulatory RNAs: complexity, function, and putative drug targeting.

Over the past decade, RNA-deep sequencing has uncovered copious non-protein coding RNAs (npcRNAs) in bacteria. Many of them are key players in the regulation of gene expression, taking part in various regulatory circuits, such as metabolic responses to different environmental stresses, virulence, antibiotic resistance, and host-pathogen interactions. This has contributed to the high adaptability of bacteria to changing or even hostile environments. Their mechanisms include the regulation of transcriptional termination, modulation of translation, and alteration of messenger RNA (mRNA) stability, as well as protein sequestration. Here, the mechanisms of gene expression by regulatory bacterial npcRNAs are comprehensively reviewed and supplemented with well-characterized examples. This class of molecules and their mechanisms of action might be useful targets for the development of novel antibiotics.

RNomic identification and evaluation of npcTB_6715, a non-protein-coding RNA gene as a potential biomarker for the detection of Mycobacterium tuberculosis.

Technological advances in RNA biology greatly improved transcriptome profiling during the last two decades. Besides the discovery of many small RNAs (sRNA) that are involved in the physiological and pathophysiological regulation of various cellular circuits, it becomes evident that the corresponding RNA genes might also serve as potential biomarkers to monitor the progression of disease and treatment. sRNA gene candidate npcTB_6715 was previously identified via experimental RNomic (unpublished data), and we report its application as potential biomarker for the detection of Mycobacterium tuberculosis (MTB) in patient samples. For proof of principle, we developed a multiplex PCR assay and report its validation with 500 clinical cultures, positive for Mycobacteria. The analysis revealed 98.9% sensitivity, 96.1% specificity, positive and negative predictive values of 98.6% and 96.8%, respectively. These results underscore the diagnostic value of the sRNA gene as diagnostic marker for the specific detection of MTB in clinical samples. Its successful application and the general ease of PCR-based detection compared to standard bacterial culture techniques might be the first step towards 'point-of-care' diagnostics of Mycobacteria. To the best of our knowledge, this is the first time for the design of diagnostic applications based on sRNA genes, in Mycobacteria.

Lipase-Secreting Bacillus Species in an Oil-Contaminated Habitat: Promising Strains to Alleviate Oil Pollution.

Lipases are of great interest for different industrial applications due to their diversity and versatility. Among different lipases, microbial lipases are preferable due to their broad substrate specificity, and higher stability with lower production costs compared to the lipases from plants and animals. In the past, a vast number of bacterial species have been reported as potential lipases producers. In this study, the lipases-producing bacterial species were isolated from an oil spillage area in the conventional night market. Isolated species were identified as Bacillus species by biochemical tests which indicate their predominant establishment, and further screened on the agar solid surfaces using lipid and gelatin as the substrates. Out of the ten strains tested, four potential strains were subjected to comparison analysis of the lipolytic versus proteolytic activities. Strain 10 exhibited the highest lipolytic and proteolytic activity. In all the strains, the proteolytic activity is higher than the lipolytic activity except for strain 8, suggesting the possibility for substrate-based extracellular gene induction. The simultaneous secretion of both the lipase and protease is a mean of survival. The isolated bacterial species which harbour both lipase and protease enzymes could render potential industrial-based applications and solve environmental issues.

Non-protein coding RNA genes as the novel diagnostic markers for the discrimination of Salmonella species using PCR.

Salmonellosis, a communicable disease caused by members of the Salmonella species, transmitted to humans through contaminated food or water. It is of paramount importance, to generate accurate detection methods for discriminating the various Salmonella species that cause severe infection in humans, including S. Typhi and S. Paratyphi A. Here, we formulated a strategy of detection and differentiation of salmonellosis by a multiplex polymerase chain reaction assay using S. Typhi non-protein coding RNA (sRNA) genes. With the designed sequences that specifically detect sRNA genes from S. Typhi and S. Paratyphi A, a detection limit of up to 10 pg was achieved. Moreover, in a stool-seeding experiment with S. Typhi and S. Paratyphi A, we have attained a respective detection limit of 15 and 1.5 CFU/mL. The designed strategy using sRNA genes shown here is comparatively sensitive and specific, suitable for clinical diagnosis and disease surveillance, and sRNAs represent an excellent molecular target for infectious disease.