Circulating Monocyte-Like Myeloid Derived Suppressor Cells and CD16 Positive Monocytes Correlate With Immunological Responsiveness of Tuberculosis Patients.

Alterations of myeloid cell populations have been reported in patients with tuberculosis (TB). In this work, we studied the relationship between myeloid-derived suppressor cells (MDSC) and monocytes subsets with the immunological responsiveness of TB patients. Individuals with active TB were classified as low responders (LR-TB) or high responders (HR-TB) according to their T cell responses against a cell lysate of Mycobacterium tuberculosis (Mtb-Ag). Thus, LR-TB, individuals with severe disease, display a weaker immune response to Mtb compare to HR-TB, subjects with strong immunity against the bacteria. We observed that LR-TB presented higher percentages of CD16 positive monocytes as compared to HR-TB and healthy donors. Moreover, monocyte-like (M-MDSC) and polymorphonuclear-like (PMN-MDSC) MDSC were increased in patients and the proportion of M-MDSC inversely correlated with IFN-γ levels released after Mtb-Ag stimulation in HR-TB. We also found that LR-TB displayed the highest percentages of circulating M-MDSC. These results demonstrate that CD16 positive monocytes and M-MDSC frequencies could be used as another immunological classification parameter. Interestingly, in LR-TB, frequencies of CD16 positive monocytes and M-MDSC were restored after only three weeks of anti-TB treatment. Together, our findings show a link between the immunological status of TB patients and the levels of different circulating myeloid cell populations.

Identification of Potential Kinase Inhibitors within the PI3K/AKT Pathway of Leishmania Species.

Leishmaniasis is a public health disease that requires the development of more effective treatments and the identification of novel molecular targets. Since blocking the PI3K/AKT pathway has been successfully studied as an effective anticancer strategy for decades, we examined whether the same approach would also be feasible in Leishmania due to their high amount and diverse set of annotated proteins. Here, we used a best reciprocal hits protocol to identify potential protein kinase homologues in an annotated human PI3K/AKT pathway. We calculated their ligandibility based on available bioactivity data of the reported homologues and modelled their 3D structures to estimate the druggability of their binding pockets. The models were used to run a virtual screening method with molecular docking. We found and studied five protein kinases in five different Leishmania species, which are AKT, CDK, AMPK, mTOR and GSK3 homologues from the studied pathways. The compounds found for different enzymes and species were analysed and suggested as starting point scaffolds for the design of inhibitors. We studied the kinases' participation in protein-protein interaction networks, and the potential deleterious effects, if inhibited, were supported with the literature. In the case of Leishmania GSK3, an inhibitor of its human counterpart, prioritized by our method, was validated in vitro to test its anti-Leishmania activity and indirectly infer the presence of the enzyme in the parasite. The analysis contributes to improving the knowledge about the presence of similar signalling pathways in Leishmania, as well as the discovery of compounds acting against any of these kinases as potential molecular targets in the parasite.

From Genome to Drugs: New Approaches in Antimicrobial Discovery.

Decades of successful use of antibiotics is currently challenged by the emergence of increasingly resistant bacterial strains. Novel drugs are urgently required but, in a scenario where private investment in the development of new antimicrobials is declining, efforts to combat drug-resistant infections become a worldwide public health problem. Reasons behind unsuccessful new antimicrobial development projects range from inadequate selection of the molecular targets to a lack of innovation. In this context, increasingly available omics data for multiple pathogens has created new drug discovery and development opportunities to fight infectious diseases. Identification of an appropriate molecular target is currently accepted as a critical step of the drug discovery process. Here, we review how diverse layers of multi-omics data in conjunction with structural/functional analysis and systems biology can be used to prioritize the best candidate proteins. Once the target is selected, virtual screening can be used as a robust methodology to explore molecular scaffolds that could act as inhibitors, guiding the development of new drug lead compounds. This review focuses on how the advent of omics and the development and application of bioinformatics strategies conduct a "big-data era" that improves target selection and lead compound identification in a cost-effective and shortened timeline.

IFN-γ and IgG responses to Mycobacterium tuberculosis latency antigen Rv2626c differentiate remote from recent tuberculosis infection.

Tuberculin skin test (TST) and IFN-γ release assays are currently used to detect Mycobacterium tuberculosis (Mtb) infection but none of them differentiate active from latent infection (LTBI). Since improved tests to diagnose Mtb infection are required, we studied the immune response to Mtb latency antigen Rv2626c in individuals exposed to the bacteria during different periods. Tuberculosis patients (TB), TB close contacts (CC: subjects exposed to Mtb for less than three months) and healthcare workers (HW: individuals exposed to Mtb at least two years) were recruited and QuantiFERON (QFT) assay, TST and IFN-γ secretion to Rv2626c were analyzed. Twenty-two percent of the individuals assessed had discordant results between QFT and TST tests. Furthermore, QFT negative and QFT positive individuals produced differential levels of IFN-γ against Rv2626c, in direct association with their exposure period to Mtb. Actually, 91% of CC QFT negative subjects secreted low levels of IFN-γ to Rv2626c, whereas 43% of HW QFT negative people produced elevated IFN-γ amounts against Rv2626c. Conversely, 69% of CC QFT positive subjects didn´t produce IFN-γ to Rv2626c. Interestingly, a similar pattern of IgG anti-Rv2626c plasma levels was observed. Therefore, determination of IFN-γ and IgG levels against the dormancy antigen Rv2626c allows to identify established LTBI.

The IFNG rs1861494 Single Nucleotide Polymorphism Is Associated with Protection against Tuberculosis Disease in Argentina.

Interferon gamma (IFNG) plays a key role during Mycobacterium tuberculosis (Mtb) infection, and several polymorphisms located in its gene are associated with risk of tuberculosis in diverse populations. Nevertheless, the genetic resistance/susceptibility to tuberculosis in Argentina is unknown. The IFNG rs1861494 polymorphism (G→A) was reported to alter the binding of transcription factors to this region, influencing IFNG production. Using a case-control study, we found an association between the AA and AG genotypes and tuberculosis resistance (AA vs. GG: odds ratio (OR) = 0.235, p-value = 0.012; AG vs. GG: OR = 0.303, p-value = 0.044; AA vs. AG: OR = 0.776, p-value = 0.427; AA + AG vs. GG: OR = 0.270, p-value = 0.022). Moreover, Mtb-antigen stimulated peripheral blood mononuclear cells (PBMCs) from healthy donors and AA carriers secreted the highest amounts of IFNG in culture supernatants (p-value = 0.034) and presented the greatest percentage of CD4⁺IFNG⁺ lymphocytes (p-value = 0.035), in comparison with GG carriers. No association between the polymorphism and clinical parameters of tuberculosis severity was detected. However, our findings indicate that the rs1861494 single nucleotide polymorphism (SNP) could be considered as a biomarker of tuberculosis resistance in the Argentinean population.