SummaryMycobacteria encode putative class II polyphosphate kinases (PPKs). We report that recombinant PPK2 of Mycobacterium tuberculosis catalyses the synthesis of GTP from GDP using polyphosphate rather than ATP as phosphate donor. Unlike that of PPK1, this is the favoured reaction of PPK2. The sites of autophosphorylation, H115 and H247, as well as G74 were critical for GTP-synthesizing activity. Compromised survival of a ppk2 knockout (PPK2-KO) of Mycobacterium smegmatis under heat or acid stress or hypoxia, and the ability of ppk2 of M. tuberculosis to complement this, confirmed that PPK2 plays a role in mycobacterial survival under stress. Intracellular ATP : GTP ratio was higher in PPK2-KO compared with the wildtype M. smegmatis, bringing to light a role of PPK2 in regulating the intracellular nucleotide pool. We present evidence that PPK2 does so by interacting with nucleoside diphosphate kinase (Ndk). Pull-down assays and analysis by surface plasmon resonance demonstrated that the interaction requires G74 of PPK2 MTB and 109 LET 111 of NdkMTB. In summary, we unravel a novel mechanism of regulation of nucleotide pools in mycobacteria. Downregulation of ppk2 impairs survival of M. tuberculosis in macrophages, suggesting that PPK2 plays an important role in the physiology of the bacteria residing within macrophages.

Polyphosphate (poly P) metabolism regulates the stress response in mycobacteria. Here we describe the regulatory architecture of a signal transduction system involving the two-component system (TCS) SenX3-RegX3, the extracytoplasmic function sigma factor sigma E (SigE) and the poly P-synthesizing enzyme polyphosphate kinase 1 (PPK1). The ppk1 promoter of Mycobacterium tuberculosis is activated under phosphate starvation. This is attenuated upon deletion of an imperfect palindrome likely representing a binding site for the response regulator RegX3, a component of the two-component system SenX3-RegX3 that responds to phosphate starvation. Binding of phosphorylated RegX3 to this site was confirmed by electrophoretic mobility shift assay. The activity of the ppk1 promoter was abrogated upon deletion of a putative SigE binding site. Pull-down of SigE from M. tuberculosis lysates of phosphate-starved cells with a biotinylated DNA harbouring the SigE binding site confirmed the likely binding of SigE to the ppk1 promoter. In vitro transcription corroborated the involvement of SigE in ppk1 transcription. Finally, the overexpression of RseA (anti-SigE) attenuated ppk1 expression under phosphate starvation, supporting the role of SigE in ppk1 transcription. The regulatory elements identified in ppk1 transcription in this study, combined with our earlier observation that PPK1 is itself capable of regulating sigE expression via the MprAB TCS, suggest the presence of multiple positivefeedback loops in this signalling circuit. In combination with the sequestering effect of RseA, we hypothesize that this architecture could be linked to bistability in the system that, in turn, could be a key element of persistence in M. tuberculosis.

BackgroundThe Mycobacterium tuberculosis genome encodes two peptide transporters encoded by Rv3665c-Rv3662c and Rv1280c-Rv1283c. Both belong to the family of ABC transporters containing two nucleotide-binding subunits, two integral membrane proteins and one substrate-binding polypeptide. However, little is known about their functions in M. tuberculosis. Here we report functional characterization of the Rv1280c-Rv1283c-encoded transporter and its substrate-binding polypeptide OppAMTB.Methodology/Principal FindingsOppAMTB was capable of binding the tripeptide glutathione and the nonapeptide bradykinin, indicative of a somewhat broad substrate specificity. Amino acid residues G109, N110, N230, D494 and F496, situated at the interface between domains I and III of OppA, were required for optimal peptide binding. Complementaton of an oppA knockout mutant of M. smegmatis with OppAMTB confirmed the role of this transporter in importing glutathione and the importance of the aforesaid amino acid residues in peptide transport. Interestingly, this transporter regulated the ability of M. tuberculosis to lower glutathione levels in infected compared to uninfected macrophages. This ability was partly offset by inactivation of oppD. Concomitantly, inactivation of oppD was associated with lowered levels of methyl glyoxal in infected macrophages and reduced apoptosis-inducing ability of the mutant. The ability to induce the production of the cytokines IL-1β, IL-6 and TNF-α was also compromised after inactivation of oppD.ConclusionsTaken together, these studies uncover the novel observations that this peptide transporter modulates the innate immune response of macrophages infected with M. tuberculosis.

An experimental study of five isolates of Aeromonas jandaei and 12 of A. trota was carried out to examine if they produced an enterotoxic substance, and if so, to characterise that factor and to see if it caused any mucosal damage. Only two of the A. trota strains caused fluid accumulation in the initial rabbit ileal loop (RIL) tests. The remaining strains did so only after one to five sequential passages through RILs and once they caused a secretory response they showed a gradual enhancement of fluid outpouring after each subsequent passage. Inocula of approximately 1 x 10(5) viable cells and 0.25 ml of culture filtrate caused fluid accumulations comparable to those of toxigenic V. cholerae 569B. The enterotoxic factors of both organisms were inactivated when held at 56 degrees C for 20 min or 65 degrees C for 10 min and showed biological activity over a wide range of pH. The only histopathological change observed in the ileal loop was depletion of mucus from the goblet cells. These data thus indicate that strains of A. jandaei and A. trota may produce a heat-labile and pH-stable diarrhoeagenic substance that causes little or no damage to the intestinal mucosa, like that of other known heat-labile enterotoxins.

Breast cancer is considered as a leading cause of cancer related death worldwide. The development of chemotherapeutic resistance and the production of undesirable side effects steer the search for new potential candidates with therapeutic implications. Lantana camara has been reported to cure a number of ailments, with few studies showing its cytotoxic effect on breast cancer cell lines. However, the impact of Lantana camara on triple negative breast cancer cells is largely obscure to date. The present study investigated the effect of ethanolic extract of Lantana camara leaves on the triple negative breast cancer cell line, MDA-MB-231. We found that Lantana camara leaf extract induced cytomorphological changes and exhibited a growth inhibitory effect on MDA-MB-231 cells in a dose-dependent manner. The extract was observed to induce G0/G1 cell cycle arrest. Nuclear staining of the cells exposed to Lantana camara leaf extract suggested the presence of condensed nuclei and the result of flow cytometry analysis confirmed cell death by apoptosis. Lantana camara leaf extract also reduced the migration of MDA-MB-231 cells as evidenced by the wound healing assay results. In summary, this study demonstrates the efficacy of the extract to produce growth-inhibitory and anti-migratory effects on MDA-MB-231 cells. Our results thus suggest that Lantana camara leaf extract can be considered a potent source of chemotherapeutic agents for triple-negative breast cancer treatment.

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Model Predictive Control (MPC) is a state-of-theart (SOTA) control technique which requires solving hard constrained optimization problems iteratively. For uncertain dynamics, analytical model based robust MPC imposes additional constraints, increasing the hardness of the problem. The problem exacerbates in performance-critical applications, when more compute is required in lesser time. Data-driven regression methods such as Neural Networks have been proposed in the past to approximate system dynamics. However, such models rely on high volumes of labeled data, in the absence of symbolic analytical priors. This incurs non-trivial training overheads. Physics-informed Neural Networks (PINNs) have gained traction for approximating non-linear system of ordinary differential equations (ODEs), with reasonable accuracy. In this work, we propose a Robust Adaptive MPC framework via PINNs (RAMP-Net), which uses a neural network trained partly from simple ODEs and partly from data. A physics loss is used to learn simple ODEs representing ideal dynamics. Having access to analytical functions inside the loss function acts as a regularizer, enforcing robust behavior for parametric uncertainties. On the other hand, a regular data loss is used for adapting to residual disturbances (non-parametric uncertainties), unaccounted during mathematical modelling. Experiments are performed in a simulated environment for trajectory tracking of a quadrotor. We report 7.8% to 43.2% and 8.04% to 61.5% reduction in tracking errors for speeds ranging from 0.5 to 1.75 m/s compared to two SOTA regression based MPC methods.

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