Protein-protein interaction of Rv0148 with Htdy and its predicted role towards drug resistance in Mycobacterium tuberculosis

Deciphering the structure of a multi-drug resistant Acinetobacter baumannii short-chain dehydrogenase reductase

The rapidly increasing threat of multi-drug-resistant Acinetobacter baumannii infections globally, encompassing a range of clinical manifestations from skin and soft tissue infections to life-threatening conditions like meningitis and pneumonia, underscores an urgent need for novel therapeutic strategies. These infections, prevalent in both hospital and community settings, present a formidable challenge to the healthcare system due to the bacterium's widespread nature and dwindling effective treatment options. Against this backdrop, the exploration of bacterial short-chain dehydrogenase reductases (SDRs) emerges as a promising avenue. These enzymes play pivotal roles in various critical bacterial processes, including fatty acid synthesis, homeostasis, metabolism, and contributing to drug resistance mechanisms. In this study, we present the first examination of the X-ray crystallographic structure of an uncharacterized SDR enzyme from A. baumannii. The tertiary structure of this SDR is distinguished by a central parallel β-sheet, consisting of seven strands, which is flanked by eight α-helices. This configuration exhibits structural parallels with other enzymes in the SDR family, underscoring a conserved architectural theme within this enzyme class. Despite the current ambiguity regarding the enzyme's natural substrate, the importance of many SDR enzymes as targets in anti-bacterial agent design is well-established. Therefore, the detailed structural insights provided in this study open new pathways for the in-silico design of therapeutic agents. By offering a structural blueprint, our findings may provide a platform for future research aimed at developing targeted treatments against this and other multi-drug-resistant infections.

Rv0687 a Putative Short-Chain Dehydrogenase is indispensable for pathogenesis of Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb), a successful human pathogen, resides in host sentinel cells and combats the stressful intracellular environment induced by reactive oxygen and nitrogen species during infection. Mtb employs several evasion mechanisms in the face of the host as a survival strategy, including detoxifying enzymes as short-chain dehydrogenases/ reductases (SDRs) to withstand host-generated insults. In this study, using specialized transduction we have generated a Rv0687 deletion mutant and its complemented strain and investigated the functional role of Rv0687, a member of SDRs family genes in Mtb pathogenesis. Wildtype (WT) and mutant Mtb strain lacking Rv0687 (RvΔ0687) were tested for in-vitro stress response and in-vivo survival in macrophages and mice models of infection. The study demonstrates that Rv0687 is crucial for sustaining bacterial growth in nutrition-limited conditions. The deletion of Rv0687 elevated the sensitivity of Mtb to oxidative and nitrosative stress-inducing agents. Furthermore, the lack of Rv0687 compromised the survival of Mtb in primary bone marrow macrophages and led to an increase in the levels of the secreted proinflammatory cytokines TNF-α, and MIP-1α. Interestingly, the growth of WT and RvΔ0687 was similar in the lungs of infected immunocompromised mice however, a significant reduction in RvΔ0687 growth was observed in the spleen of immunocompromised Rag -/- mice at 4 weeks post-infection. Moreover Rag -/- mice infected with RvΔ0687 survived longer compared to WT Mtb strain. Additionally, we observed significant reduction in bacterial burden in spleens and lungs of immunocompetent C57BL/6 mice infected with RvΔ0687 compared to complemented and WT Mtb strains. Collectively, this study reveals that Rv0687 plays a role in Mtb pathogenesis.

Clustering minimal inhibitory concentration data through Bayesian mixture models: An application to detect Mycobacterium tuberculosis resistance mutations

Antimicrobial resistance is becoming a major threat to public health throughout the world. Researchers are attempting to contrast it by developing both new antibiotics and patient-specific treatments. In the second case, whole-genome sequencing has had a huge impact in two ways: first, it is becoming cheaper and faster to perform whole-genome sequencing, and this makes it competitive with respect to standard phenotypic tests; second, it is possible to statistically associate the phenotypic patterns of resistance to specific mutations in the genome. Therefore, it is now possible to develop catalogues of genomic variants associated with resistance to specific antibiotics, in order to improve prediction of resistance and suggest treatments. It is essential to have robust methods for identifying mutations associated to resistance and continuously updating the available catalogues. This work proposes a general method to study minimal inhibitory concentration distributions and to identify clusters of strains showing different levels of resistance to antimicrobials. Once the clusters are identified and strains allocated to each of them, it is possible to perform regression method to identify with high statistical power the mutations associated with resistance. The method is applied to a new 96-well microtiter plate used for testing Mycobacterium tuberculosis.

Role of a Putative Alkylhydroperoxidase Rv2159c in the Oxidative Stress Response and Virulence of Mycobacterium tuberculosis

Mycobacterium tuberculosis, which causes tuberculosis, is one of the leading infectious agents worldwide with a high rate of mortality. Following aerosol inhalation, M. tuberculosis primarily infects the alveolar macrophages, which results in a host immune response that gradually activates various antimicrobial mechanisms, including the production of reactive oxygen species (ROS), within the phagocytes to neutralize the bacteria. OxyR is the master regulator of oxidative stress response in several bacterial species. However, due to the absence of a functional oxyR locus in M. tuberculosis, the peroxidase stress is controlled by alkylhydroperoxidases. M. tuberculosis expresses alkylhydroperoxide reductase to counteract the toxic effects of ROS. In the current study, we report the functional characterization of an orthologue of alkylhydroperoxidase family member, Rv2159c, a conserved protein with putative peroxidase activity, during stress response and virulence of M. tuberculosis. We generated a gene knockout mutant of M. tuberculosis Rv2159c (MtbΔ2159) by specialized transduction. The MtbΔ2159 was sensitive to oxidative stress and exposure to toxic transition metals. In a human monocyte (THP-1) cell infection model, MtbΔ2159 showed reduced uptake and intracellular survival and increased expression of pro-inflammatory molecules, including IL-1β, IP-10, and MIP-1α, compared to the wild type M. tuberculosis and Rv2159c-complemented MtbΔ2159 strains. Similarly, in a guinea pig model of pulmonary infection, MtbΔ2159 displayed growth attenuation in the lungs, compared to the wild type M. tuberculosis and Rv2159c-complemented MtbΔ2159 strains. Our study suggests that Rv2159c has a significant role in maintaining the cellular homeostasis during stress and virulence of M. tuberculosis.

Protein–Protein Interaction (PPI) Network of Zebrafish Oestrogen Receptors: A Bioinformatics Workflow

Protein–protein interaction (PPI) is involved in every biological process that occurs within an organism. The understanding of PPI is essential for deciphering the cellular behaviours in a particular organism. The experimental data from PPI methods have been used in constructing the PPI network. PPI network has been widely applied in biomedical research to understand the pathobiology of human diseases. It has also been used to understand the plant physiology that relates to crop improvement. However, the application of the PPI network in aquaculture is limited as compared to humans and plants. This review aims to demonstrate the workflow and step-by-step instructions for constructing a PPI network using bioinformatics tools and PPI databases that can help to predict potential interaction between proteins. We used zebrafish proteins, the oestrogen receptors (ERs) to build and analyse the PPI network. Thus, serving as a guide for future steps in exploring potential mechanisms on the organismal physiology of interest that ultimately benefit aquaculture research.