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

A comprehensive review on the emerging role of long non-coding RNAs in the regulation of NF-κB signaling in inflammatory lung diseases

Public health globally faces significant risks from conditions like acute respiratory distress syndrome (ARDS), chronic obstructive pulmonary disease (COPD), and various inflammatory lung disorders. The NF-κB signaling system partially controls lung inflammation, immunological responses, and remodeling. Non-coding RNAs (lncRNAs) are crucial in regulating gene expression. They are increasingly recognized for their involvement in NF-κB signaling and the development of inflammatory lung diseases. Disruption of lncRNA-NF-κB interactions is a potential cause and resolution factor for inflammatory respiratory conditions. This study explores the therapeutic potential of targeting lncRNAs and NF-κB signaling to alleviate inflammation and restore lung function. Understanding the intricate relationship between lncRNAs and NF-κB signaling could offer novel insights into disease mechanisms and identify therapeutic targets. Regulation of lncRNAs and NF-κB signaling holds promise as an effective approach for managing inflammatory lung disorders. This review aims to comprehensively analyze the interaction between lncRNAs and the NF-κB signaling pathway in the context of inflammatory lung diseases. It investigates the functional roles of lncRNAs in modulating NF-κB activity and the resulting inflammatory responses in lung cells, focusing on molecular mechanisms involving upstream regulators, inhibitory proteins, and downstream effectors.

Using a whole genome co-expression network to inform the functional characterisation of predicted genomic elements from Mycobacterium tuberculosis transcriptomic data

A whole genome co-expression network was created using Mycobacterium tuberculosis transcriptomic data from publicly available RNA-sequencing experiments covering a wide variety of experimental conditions. The network includes expressed regions with no formal annotation, including putative short RNAs and untranslated regions of expressed transcripts, along with the protein-coding genes. These unannotated expressed transcripts were among the best-connected members of the module sub-networks, making up more than half of the 'hub' elements in modules that include protein-coding genes known to be part of regulatory systems involved in stress response and host adaptation. This data set provides a valuable resource for investigating the role of non-coding RNA, and conserved hypothetical proteins, in transcriptomic remodelling. Based on their connections to genes with known functional groupings and correlations with replicated host conditions, predicted expressed transcripts can be screened as suitable candidates for further experimental validation.

Mycobacterium tuberculosis transcriptome in intraocular tuberculosis

Introduction. Intraocular tuberculosis (IOTB) is a significant cause of visual morbidity in tuberculosis (TB)-endemic countries. Although Mycobacterium tuberculosis (M. tb) has been detected in both the retinal pigment epithelial (RPE) cells and in the intraocular fluid (IOF) in some cases, IOTB is paucibacillary in the vast majority of patients. As a result, M. tb pathogenesis in the ocular compartment is poorly defined.Hypothesis. The transcriptional profile of M. tb in the ocular compartment will differ from those of M. tb in environments that represent earlier stages of infection.Aim. Our aim is to shed light on the pathogenesis of M. tb in a clinically relevant but challenging environment to study.Methodology. Whole-genome microarray analysis was performed on M. tb grown in an IOF model (artificial IOF; AIOF) over 6 days against reference log phase bacteria grown in 7H9. Results were compared to published M. tb transcriptomes in other physiologically relevant environments, e.g. RPE cell line.Results. M. tb replicates slowly in AIOF. Genes involved in active replication and aerobic respiration as well as lipid metabolism were either downregulated or not differentially expressed. Yet, M. tb in AIOF downregulated genes of the DosR regulon, indicating the suppression of dormancy, similar to M. tb in RPE cells. This transcriptional profile is distinct from the active and virulent transcriptomes of M. tb in alveolar epithelial cells and blood.Conclusion. M. tb likely acquires a non-invasive and quiescent phenotype, between active infection and dormancy, upon reaching an extrapulmonary niche, i.e. the ocular environment.

RNA Preparation and RNA-Seq Bioinformatics for Comparative Transcriptomics

The principal transcriptome analysis is the determination of differentially expressed genes across experimental conditions. For this, the next-generation sequencing of RNA (RNA-seq) has several advantages over other techniques, such as the capability of detecting all the transcripts in one assay over RT-qPCR, such as its higher accuracy and broader dynamic range over microarrays or the ability to detect novel transcripts, including non-coding RNA molecules, at nucleotide-level resolution over both techniques. Despite these advantages, many microbiology laboratories have not yet applied RNA-seq analyses to their investigations. The high cost of the equipment for next-generation sequencing is no longer an issue since this intermediate part of the analysis can be provided by commercial or central services. Here, we detail a protocol for the first part of the analysis, the RNA extraction and an introductory protocol to the bioinformatics analysis of the sequencing data to generate the differential expression results.

Non-Coding RNAs in Tuberculosis Epidemiology: Platforms and Approaches for Investigating the Genome's Dark Matter

A growing amount of information about the different types, functions, and roles played by non-coding RNAs (ncRNAs) is becoming available, as more and more research is done. ncRNAs have been identified as potential therapeutic targets in the treatment of tuberculosis (TB), because they may be essential regulators of the gene network. ncRNA profiling and sequencing has recently revealed significant dysregulation in tuberculosis, primarily due to aberrant processes of ncRNA synthesis, including amplification, deletion, improper epigenetic regulation, or abnormal transcription. Despite the fact that ncRNAs may have a role in TB characteristics, the detailed mechanisms behind these occurrences are still unknown. The dark matter of the genome can only be explored through the development of cutting-edge bioinformatics and molecular technologies. In this review, ncRNAs' synthesis and functions are discussed in detail, with an emphasis on the potential role of ncRNAs in tuberculosis. We also focus on current platforms, experimental strategies, and computational analyses to explore ncRNAs in TB. Finally, a viewpoint is presented on the key challenges and novel techniques for the future and for a wide-ranging therapeutic application of ncRNAs.