Small Noncoding RNAs and Their Role in the Pathogenesis of Mycobacterium tuberculosis Infection

Transcriptome analysis and molecular characterization of novel small RNAs in Mycobacterium tuberculosis Lineage 1

Mycobacterium tuberculosis (Mtb), the tuberculosis-causing agent, exhibits diverse genetic lineages, with known links to virulence. While genomic and transcriptomic variations between modern and ancient Mtb lineages have been explored, the role of small non-coding RNA (sRNA) in post-translational gene regulation remains largely uncharted. In this study, Mtb Lineage 1 (L1) Sabahan strains (n = 3) underwent sRNA sequencing, revealing 351 sRNAs, including 23 known sRNAs and 328 novel ones identified using ANNOgesic. Thirteen sRNAs were selected based on the best average cut-off value of 300, with RT-qPCR revealing significant expression differences for sRNA 1 (p = 0.0132) and sRNA 29 (p = 0.0012) between Mtb L1 and other lineages (L2 and L4, n = 3) (p > 0.05). Further characterization using RACE (rapid amplification of cDNA ends), followed by target prediction with TargetRNA3 unveils that sRNA 1 (55 base pairs) targets Rv0506, Rv0697, and Rv3590c, and sRNA 29 (86 base pairs) targets Rv33859c, Rv3345c, Rv0755c, Rv0107c, Rv1817, Rv2950c, Rv1181, Rv3610c, and Rv3296. Functional characterization with Mycobrowser reveals these targets involved in regulating intermediary metabolism and respiration, cell wall and cell processes, lipid metabolism, information pathways, and PE/PPE. In summary, two novel sRNAs, sRNA 1 and sRNA 29, exhibited differential expression between L1 and other lineages, with predicted roles in essential Mtb functions. These findings offer insights into Mtb regulatory mechanisms, holding promise for the development of improved tuberculosis treatment strategies in the future.

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Mycobacterium tuberculosis (M. tb), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.

Mycobacterium tuberculosis complex molecular networks and their regulation: Implications of strain heterogeneity on epigenetic diversity and transcriptome regulation

Tuberculosis has been a public health crisis since the 1900, which has caused the highest mortalities due to a single bacterial infection worldwide, that was recently further complicated by the Coronavirus disease 2019 pandemic. The causative agent of Tuberculosis, Mycobacterium tuberculosis, belongs to a genetically well-characterized family of strains known as the Mycobacterium tuberculosis complex, which has complicated progress made towards eradicating Tuberculosis due to pathogen-specific phenotypic differences in the members of this complex. Mycobacterium tuberculosis complex strains are genetically diverse human- and animal-adapted pathogens belonging to 7 lineages (Indo-Oceanic, East-Asian, East-African Indian, Euro-American, M. africanum West Africa 1, M. africanum West Africa 2 and Ethopia), respectively and the recently identified Lineage 8 and M. africanum Lineage 9. Genomic studies have revealed that Mycobacterium tuberculosis complex members are ∼99 % similar, however, due to selective pressure and adaptation to human host, they are prone to mutations that have resulted in development of drug resistance and phenotypic heterogeneity that impact strain virulence. Furthermore, members of the Mycobacterium tuberculosis complex have preferred geographic locations and possess unique phenotypic characteristics that is linked to their pathogenicity. Due to the recent advances in development next generation sequencing platforms, several studies have revealed epigenetic changes in genomic regions combined with "unique" gene regulatory mechanisms through non-coding RNAs that are responsible for strain-specific behaviour on in vitro and in vivo infection models. The current review provides up to date epigenetic patterns, gene regulation through non-coding RNAs, together with implications of these mechanisms in down-stream proteome and metabolome, which may be responsible for "unique" responses to infection by members of the Mycobacterium tuberculosis complex. Understanding lineage-specific molecular mechanisms during infection may provide novel drug targets and disease control measures towards World Health organization END-TB strategy.

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Mycobacterium tuberculosis ( M. tb ), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.

Importance

Understanding mechanisms of resistance and tolerance in Mycobacterium tuberculosis ( M. tb ) can help us develop new treatments that capitalize on M. tb 's vulnerabilities. Here we used transcriptomics to study both the regulation of biofilm formation in clinical isolates as well as how those regulatory systems adapt to new environments. We find that closely related clinical populations have diverse strategies for growth under biofilm conditions, and that genetic background plays a large role in determining the trajectory of evolution. These results have implications for future treatment strategies that may be informed by our knowledge of the evolutionary constraints on strain(s) from an individual infection. This work provides new information about the mechanisms of biofilm formation in M. tb and outlines a framework for population level approaches for studying bacterial adaptation.

Advances in computational frameworks in the fight against TB: The way forward

Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its "End TB" strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for-early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.

A multi-omics investigation into the mechanisms of hyper-virulence in Mycobacterium tuberculosis

Clinical manifestations of tuberculosis range from asymptomatic infection to a life-threatening disease such as tuberculous meningitis (TBM). Recent studies showed that the spectrum of disease severity could be related to genetic diversity among clinical strains of Mycobacterium tuberculosis (Mtb). Certain strains are reported to preferentially invade the central nervous system, thus earning the label “hypervirulent strains”.However, specific genetic mutations that accounted for enhanced mycobacterial virulence are still unknown. We previously identified a set of 17 mutations in a hypervirulent Mtb strain that was from TBM patient and exhibited significantly better intracellular survivability. These mutations were also commonly shared by a cluster of globally circulating hyper-virulent strains. Here, we aimed to validate the impact of these hypervirulent-specific mutations on the dysregulation of gene networks associated with virulence in Mtb via multi-omic analysis. We surveyed transcriptomic and proteomic differences between the hyper-virulent and low-virulent strains using RNA-sequencing and label-free quantitative LC-MS/MS approach, respectively. We identified 25 genes consistently differentially expressed between the strains at both transcript and protein level, regardless the strains were growing in a nutrient-rich or a physiologically relevant multi-stress condition (acidic pH, limited nutrients, nitrosative stress, and hypoxia). Based on integrated genomic-transcriptomic and proteomic comparisons, the hypervirulent-specific mutations in FadE5 (g. 295,746 C >T), Rv0178 (p. asp150glu), higB (p. asp30glu), and pip (IS6110-insertion) were linked to deregulated expression of the respective genes and their functionally downstream regulons. The result validated the connections between mutations, gene expression, and mycobacterial pathogenicity, and identified new possible virulence-associated pathways in Mtb.

microRNAs associated with the pathogenesis and their role in regulating various signaling pathways during Mycobacterium tuberculosis infection

Despite more than a decade of active study, tuberculosis (TB) remains a serious health concern across the world, and it is still the biggest cause of mortality in the human population. Pathogenic bacteria recognize host-induced responses and adapt to those hostile circumstances. This high level of adaptability necessitates a strong regulation of bacterial metabolic characteristics. Furthermore, the immune reponse of the host virulence factors such as host invasion, colonization, and survival must be properly coordinated by the pathogen. This can only be accomplished by close synchronization of gene expression. Understanding the molecular characteristics of mycobacterial pathogenesis in order to discover therapies that prevent or resolve illness relies on the bacterial capacity to adjust its metabolism and replication in response to various environmental cues as necessary. An extensive literature details the transcriptional alterations of host in response to in vitro environmental stressors, macrophage infection, and human illness. Various studies have recently revealed the finding of several microRNAs (miRNAs) that are believed to play an important role in the regulatory networks responsible for adaptability and virulence in Mycobacterium tuberculosis. We highlighted the growing data on the existence and quantity of several forms of miRNAs in the pathogenesis of M. tuberculosis, considered their possible relevance to disease etiology, and discussed how the miRNA-based signaling pathways regulate bacterial virulence factors.

Close Related Drug-Resistance Beijing Isolates of Mycobacterium tuberculosis Reveal a Different Transcriptomic Signature in a Murine Disease Progression Model

Mycobacterium tuberculosis (MTB) lineage 2/Beijing is associated with high virulence and drug resistance worldwide. In Colombia, the Beijing genotype has circulated since 1997, predominantly on the pacific coast, with the Beijing-Like SIT-190 being more prevalent. This genotype conforms to a drug-resistant cluster and shows a fatal outcome in patients. To better understand virulence determinants, we performed a transcriptomic analysis with a Beijing-Like SIT-190 isolate (BL-323), and Beijing-Classic SIT-1 isolate (BC-391) in progressive tuberculosis (TB) murine model. Bacterial RNA was extracted from mice lungs on days 3, 14, 28, and 60. On average, 0.6% of the total reads mapped against MTB genomes and of those, 90% against coding genes. The strains were independently associated as determined by hierarchical cluster and multidimensional scaling analysis. Gene ontology showed that in strain BL-323 enriched functions were related to host immune response and hypoxia, while proteolysis and protein folding were enriched in the BC-391 strain. Altogether, our results suggested a differential bacterial transcriptional program when evaluating these two closely related strains. The data presented here could potentially impact the control of this emerging, highly virulent, and drug-resistant genotype.

Challenges in defining the functional, non-coding, expressed genome of members of the Mycobacterium tuberculosis complex

A definitive transcriptome atlas for the non-coding expressed elements of the members of the Mycobacterium tuberculosis complex (MTBC) does not exist. Incomplete lists of non-coding transcripts can be obtained for some of the reference genomes (e.g., M. tuberculosis H37Rv) but to what extent these transcripts have homologues in closely related species or even strains is not clear. This has implications for the analysis of transcriptomic data; non-coding parts of the transcriptome are often ignored in the absence of formal, reliable annotation. Here, we review the state of our knowledge of non-coding RNAs in pathogenic mycobacteria, emphasizing the disparities in the information included in commonly used databases. We then proceed to review ways of combining computational solutions for predicting the non-coding transcriptome with experiments that can help refine and confirm these predictions.

Small RNA Profiling in Mycobacterium Provides Insights Into Stress Adaptability

Mycobacteria encounter a number of environmental changes during infection and respond using different mechanisms. Small RNA (sRNA) is a post-transcriptionally regulatory system for gene functions and has been investigated in many other bacteria. This study used Mycobacterium tuberculosis and Mycobacterium bovis Bacillus Calmette-Guérin (BCG) infection models and sequenced whole bacterial RNAs before and after host cell infection. A comparison of differentially expressed sRNAs using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) and target prediction was carried out. Six pathogenically relevant stress conditions, growth rate, and morphology were used to screen and identify sRNAs. From these data, a subset of sRNAs was differentially expressed in multiple infection groups and stress conditions. Many were found associated with lipid metabolism. Among them, ncBCG427 was significantly downregulated when BCG entered into macrophages and was associated with increased biofilm formation. The reduction of virulence possibility depends on regulating lipid metabolism.

MTS1338 in Mycobacterium tuberculosis promotes detoxification of reactive oxygen species under oxidative stress

Diverse mechanisms exist in Mycobacterium tuberculosis for adaptation to stresses leading to its persistence in the hostile environment of macrophages. Small RNA (sRNA)-mediated regulatory mechanisms have been scarcely explored in M. tuberculosis. MTS1338, a sRNA present only in pathogenic mycobacteria, was discovered to be highly abundant during infection and significantly contributes to host-pathogen interaction. A variety of stresses have been implicated for its accumulation. Herein, we showed that MTS1338 is an oxidative stress induced sRNA, which promotes the detoxification of reactive oxygen species (ROS) under oxidative stress. Current study identified a new role of MTS1338 in M. tuberculosis under oxidative stress.

Small RNAs Asserting Big Roles in Mycobacteria

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb), with 10.4 million new cases per year reported in the human population. Recent studies on the Mtb transcriptome have revealed the abundance of noncoding RNAs expressed at various phases of mycobacteria growth, in culture, in infected mammalian cells, and in patients. Among these noncoding RNAs are both small RNAs (sRNAs) between 50 and 350 nts in length and smaller RNAs (sncRNA) < 50 nts. In this review, we provide an up-to-date synopsis of the identification, designation, and function of these Mtb-encoded sRNAs and sncRNAs. The methodological advances including RNA sequencing strategies, small RNA antagonists, and locked nucleic acid sequence-specific RNA probes advancing the studies on these small RNA are described. Initial insights into the regulation of the small RNA expression and putative processing enzymes required for their synthesis and function are discussed. There are many open questions remaining about the biological and pathogenic roles of these small non-coding RNAs, and potential research directions needed to define the role of these mycobacterial noncoding RNAs are summarized.

Small RNA F6 Provides Mycobacterium smegmatis Entry into Dormancy

Regulatory small non-coding RNAs play a significant role in bacterial adaptation to changing environmental conditions. Various stresses such as hypoxia and nutrient starvation cause a reduction in the metabolic activity of Mycobacterium smegmatis, leading to entry into dormancy. We investigated the functional role of F6, a small RNA of M. smegmatis, and constructed an F6 deletion strain of M. smegmatis. Using the RNA-seq approach, we demonstrated that gene expression changes that accompany F6 deletion contributed to bacterial resistance against oxidative stress. We also found that F6 directly interacted with 5'-UTR of MSMEG_4640 mRNA encoding RpfE2, a resuscitation-promoting factor, which led to the downregulation of RpfE2 expression. The F6 deletion strain was characterized by the reduced ability to enter into dormancy (non-culturability) in the potassium deficiency model compared to the wild-type strain, indicating that F6 significantly contributes to bacterial adaptation to non-optimal growth conditions.