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Biology subjects

Sander, P.

Publications and source records attributed to Sander, P..

3 recordsLinked to original sources

c-Myc inhibits macrophage antimycobacterial response in Mycobacterium tuberculosis infection

Mycobacterium tuberculosis (MTB) is a major global cause of mortality worldwide, responsible for over a million deaths annually. Despite this burden, natural immunity prevents disease in more than 90% of exposed individuals. Previous studies have identified interferon-gamma (IFN-{gamma}) as a key regulator of innate immune defense against MTB. Here, we investigate the impact of IFN-{gamma} timing on macrophage-mediated control of MTB infection. We demonstrate that IFN-{gamma} exposure before infection enhances macrophage antibacterial activity, whereas post-infection exposure does not. Further investigation into this phenotype revealed a strong association between c-Myc signaling and macrophage function in MTB control, as identified using unbiased in vitro systems approaches. Given the challenge of perturbing c-Myc in primary cells, we developed a lentiviral system for c-Myc inhibition and overexpression. Using a tetracycline-inducible Omomyc system - a small peptide inhibitor of c-Myc - we show that c-Myc inhibition promotes a pro-inflammatory macrophage phenotype with enhanced antimycobacterial activity. Mechanistically, c-Myc inhibition induces metabolic reprogramming via increased mTORC1 activity, leading to upregulated inducible nitric oxide synthase and improved bacterial control. In vivo analyses, including murine models and human clinical histopathology, reveal a strong correlation between c-Myc expression and MTB persistence, as well as active tuberculosis (TB), suggesting a role for c-Myc in immune evasion. These findings reveal c-Myc as a potential mediator of immune privilege in MTB infection and highlight its role as a promising target for novel TB therapies aimed at enhancing macrophage function.

immunology↗

In-vivo detection of cyclic-di-AMP in Staphylococcus aureus

Cyclic-di-AMP (CDA) is a signaling molecule that controls various cellular functions including antibiotic tolerance and osmoregulation in Staphylococcus aureus. In this study, we developed a novel biosensor (bsuO P6-4) for in-vivo detection of CDA in S. aureus. Our study showed that bsuO P6-4 could detect a wide concentration range of CDA in both laboratory and clinical strains making it suitable for use in both basic and clinical research applications.

microbiology↗

Whole genome sequencing for drug resistance profile prediction in Mycobacterium tuberculosis

Whole genome sequencing allows rapid detection of drug-resistant M. tuberculosis isolates. However, high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data have thus far been lacking.\n\nWe determined drug resistance profiles of 176 genetically diverse clinical M. tuberculosis isolates from Democratic Republic of the Congo, Ivory Coast, Peru, Thailand and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD BACTEC MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared phenotypic drug susceptibility results with predicted drug resistance profiles inferred by whole genome sequencing.\n\nBoth phenotypic DST methods identically classified the strains into resistant/susceptible in 73-99% of the cases, depending on the drug. Changes in minimal inhibitory concentrations were readily explained by mutations identified by whole genome sequencing. Using the whole genome sequences we were able to predict quantitative drug resistance levels where wild type and mutant MIC distributions did not overlap. The utility of genome sequences to predict quantitative levels of drug resistance was partially limited due to incompletely understood mechanisms influencing the expression of phenotypic drug resistance. The overall sensitivity and specificity of whole genome-based DST were 86.8% and 94.5%, respectively.\n\nDespite some limitations, whole genome sequencing has high predictive power to infer resistance profiles without the need for time-consuming phenotypic methods.\n\nOne sentence summaryWhole genome sequencing of clinical M. tuberculosis isolates accurately predicts drug resistance profiles and may replace culture-based drug susceptibility testing in the future.

microbiology↗