Biology subjects

Barge, N. S.

Publications and source records attributed to Barge, N. S..

3 recordsLinked to original sources

bioRxiv2026

Dissolution-Controlled Nanocrystalline Rifapentine Formulation for Tuberculosis Treatment

Current tuberculosis (TB) treatment suffers from drawbacks such as long regimens, high pill burden and side effects leading to non-adherence and poor treatment outcomes. Dissolution-controlled drug depot formulation with high drug loading is a clinically successful drug delivery strategy. Such depots reduce the dosing frequency for treatments requiring daily administration, thereby improving treatment adherence and compliance. However, dissolution-controlled depots for first-line TB drugs have not been demonstrated due to their high solubility and high dose requirements. In this study, we overcame this challenge by developing injectable, extended-release, dissolution-controlled depots of nanocrystalline rifapentine (NCRPT), microcrystalline rifapentine (MCRPT) and amorphous rifapentine microparticles (ARPT) with more than 75% loading. Crystalline formulations resulted in much slower depot dissolution compared to amorphous formulations. A single intramuscular (IM) injection of NCRPT in mice resulted in therapeutic serum concentrations for over a week. We then demonstrated the efficacy of NCRPT in both pre-exposure prophylaxis and therapeutic models of mice TB. NCRPT administered at 60 mg/kg once every two weeks demonstrated excellent efficacy in a mouse model of TB infection. In each case, a [~] 4-log-fold reduction in lung bacterial load compared to untreated mice was observed. These results open new avenues for developing LAI formulations of TB drugs and could improve patient compliance and TB management.

bioengineering↗

bioRxiv2026

Bacteriophage utilize pseudolysogeny to target non-replicating bacteria and CRISPR-resistant phages eliminate recalcitrant implant infections

A key driver of bacterial infection treatment failure and relapse is the persistence of non-replicating bacterial subpopulations that emerge under stressors like nutrient starvation and immune pressure. These dormant cells evade antibiotics, fuelling recurrence and resistance. Bacteriophage therapy is a promising alternative, but its efficacy against non-replicating bacteria is poorly understood. Improving our understanding of bacteria-phage interactions under non-replicating conditions could greatly enhance phage therapeutic outcomes in clinics. By utilising various bacterial (Mycobacterium smegmatis, Mycobacterium tuberculosis, and Pseudomonas aeruginosa) and phage species, this study quantitatively demonstrates that lytic phages can infect non-replicating bacteria (under nutrient starvation, acidic pH or antibiotic pressure), persisting in a state of pseudolysogeny and resuming lysis upon bacterial regrowth. We find that the pseudolysogeny window is phage- and host-dependent, with degradation of extrachromosomal phage DNA leading to loss of pseudolysogeny. We find that Pseudomonas CRISPR defence plays a crucial role in phage DNA degradation even under non-replicating conditions, underscoring the need for its consideration in phage therapy design. We also demonstrated the in vivo relevance of pseudolysogeny and CRISPR-resistant bacteriophages in eliminating implant-associated and antibiotic-persistent Pseudomonas infections in mice. These findings highlight the need to consider phage-host dynamics and bacterial defences when designing phage-based strategies to target non-replicating bacteria and persistent infections.

microbiology↗

bioRxiv2023

Analysis of the genome-scale metabolic model of Bacillus subtilis to design novel in-silico strategies for native and recombinant L-asparaginase overproduction

L-asparaginase is an enzyme with widescale use in the food and medicine industry. It is used as a chemotherapeutic drug in the treatment of acute lymphoblastic leukemia. Limitations of side effects associated with commercially available L-asparaginase necessitate the search for alternative sources. Bacillus subtilis is an emerging host for the production of chemicals and therapeutic products. This study deals with L-asparaginase production in Bacillus subtilis using systems metabolic engineering approach. System biology offers a detailed understanding of organism metabolism at the network level unlike the conventional molecular approach of metabolic engineering allowing one to study the effects of metabolite production on growth. Metabolism of Bacillus subtilis is studied using genome-scale metabolic model iYO844 which consists of relationships between the genes and proteins present in Bacillus subtilis. Also, the model contains information about all the metabolic reactions and pathways allowing convenient metabolic engineering methods. Computational methods like flux balance analysis, flux variability analysis, robustness analysis, etc. are carried out to study the metabolic capabilities of Bacillus subtilis. The model predicted a specific growth rate of 0.6242 h-1, which was comparable to the experimental value. Further, the model is used to simulate recombinant L-asparaginase production generating a maximum production rate of 0.4028 mmol gDW-1 h-1. Flux scanning based on enforced objective flux and OptKnock design strategies are used for strain development of Bacillus subtilis for higher production of both native and recombinant L-asparaginase.

systems biology↗