Biology subjects

Tandar, S. T.

Publications and source records attributed to Tandar, S. T..

4 recordsLinked to original sources

bioRxiv2025

Divergent spontaneous antibiotic-resistance evolution confers reciprocal and exploitable collateral sensitivity effects

The global rise of antibiotic-resistant pathogens has outpaced the development of new antibiotics, prompting the urgent need for alternative treatment strategies. One such approach is to leverage collateral sensitivity (CS), where resistance to one antibiotic increases susceptibility to another. However, the clinical implementation of CS-based therapies depends on the consistency of these responses, which is challenged by variable resistance mutations and the dynamics of resistant strains during infection. Here, we combined experiments and mathematical models to assess the consistency and consequences of CS responses in the Gram-positive pathogen Streptococcus pneumoniae following the de novo acquisition of resistance to five commonly used antibiotics. We found that many collateral responses were unpredictable and inconsistent between different resistance mutations. However, for two antibiotic pairs, we identified consistent unidirectional (RIF [->] FUS) and bidirectional (LNZ {leftrightarrow} FUS) CS interactions, despite the divergent evolutionary trajectories of resistant strains, as revealed by whole-genome sequencing. To evaluate if CS for these combinations can be exploited to design dosing strategies to eradicate S. pneumoniae infections while suppressing resistance, we developed a mathematical stochastic pharmacokinetic-pharmacodynamic (PK-PD) model, which integrated our experimentally derived PD parameters with existing clinical PK models. Our model-based analyses confirmed the superiority of these antibiotic combinations over monotherapy and showed that their efficacy depends on the presence of CS interactions between the administered antibiotics. In summary, our study demonstrates how consistent CS interactions can be leveraged to inform treatment strategies, laying the groundwork for CS-guided therapies to preserve antibiotic efficacy.

microbiology↗

bioRxiv2024

The endocannabinoid 2-arachidonoylglycerol is released and transported on demand via extracellular microvesicles

While it is known that endocannabinoids (eCB) modulate multiple neuronal functions, the molecular mechanism governing their release and transport remains elusive. Here, we propose an "on-demand release" model, wherein the formation of microvesicles, a specific group of extracellular vesicles (EVs) containing the eCB, 2-arachidonoylglycerol (2-AG), is the rate-limiting step. A co-culture model system that combines a reporter cell line expressing the fluorescent eCB sensor, GRABeCB2.0, and neuronal cells revealed that neurons release EVs containing 2-AG, but not anandamide, in a stimulus-dependent process regulated by PKC, DAGL, Arf6, and which was sensitive to inhibitors of eCB facilitated diffusion. A vesicle contained approximately 2000 2-AG molecules. Accordingly, hippocampal eCB-mediated synaptic plasticity was modulated by Arf6 and transport inhibitors. This "on demand release" model, supported by mathematical analysis, offers a cohesive framework for understanding eCB signaling at the molecular level and suggests that microvesicles carrying signaling lipids regulate neuronal functions in parallel to canonical synaptic vesicles.

neuroscience↗

bioRxiv2024

Interspecies interactions alter the antibiotic sensitivity of Pseudomonas aeruginosa

Polymicrobial infections are infections that are caused by multiple pathogens, and are common in patients with cystic fibrosis (CF). Although polymicrobial infections are associated with poor treatment responses in CF, the effects of the ecological interactions between co-infecting pathogens on antibiotic sensitivity and treatment outcome are poorly characterized. To this end, we systematically quantified the impact of these effects on the antibiotic sensitivity of Pseudomonas aeruginosa for nine antibiotics in the presence of thirteen secondary cystic fibrosis-associated bacterial and fungal pathogens through time-kill assays. We fitted pharmacodynamic models to these kill curves for each antibiotic-species combination and found that interspecies interactions changing the antibiotic sensitivity of P. aeruginosa are abundant. Interactions that lower antibiotic sensitivity are more common than those that increase it, with generally more substantial reductions than increases in sensitivity. For a selection of co-infecting species, we performed pharmacokinetic-pharmacodynamic modelling of P. aeruginosa treatment. We predicted that interspecies interactions can either improve or reduce treatment response to the extent that treatment is rendered ineffective from a previously effective antibiotic dosing schedule and vice versa. In summary, we show that quantifying the ecological interaction effects as pharmacodynamic parameters is necessary to determine the abundance and the extent to which these interactions affect antibiotic sensitivity in polymicrobial infections. ImportanceIn cystic fibrosis (CF) patients, chronic respiratory tract infections are often polymicrobial, involving multiple pathogens simultaneously. Polymicrobial infections are difficult to treat as they often respond unexpectedly to antibiotic treatment, which might possibly be explained because co-infecting pathogens can influence each others antibiotic sensitivity, but it is unknown to what extent such effects occur. To investigate this, we systematically quantified the impact of co-infecting species on antibiotic sensitivity, focusing on P. aeruginosa, a common CF pathogen. We studied for a large set co-infecting species and antibiotics whether changes in antibiotic response occur. Based on these experiments, we used mathematical modeling to simulate P. aeruginosas response to colistin and tobramycin treatment in the presence of multiple pathogens. This study offers comprehensive data on altered antibiotic sensitivity of P. aeruginosa in polymicrobial infections, serves as a foundation for optimizing treatment of such infections, and consolidates the importance of considering co-infecting pathogens.

pharmacology and toxicology↗

bioRxiv2020

Rapidemic, a versatile and label-free DNAzyme-based platform for visual nucleic acid detection

In the last three decades, there have been recurring outbreaks of infectious diseases, brought to light with the recent outbreak of coronavirus disease 2019 (COVID-19). Attempts to effectively contain the spread of infectious diseases have been hampered by the lack of rapidly adaptable, accurate, and accessible point-of-care diagnostic testing. In this study, we present a novel design of a label-free DNAzyme-based detection method called Rapidemic. This assay combines recombinase polymerase amplification (RPA) with linear strand-displacement amplification (LSDA) and guanine-quadruplex (GQ) DNAzyme-catalysed colour-changing reaction. The colorimetry basis of the signal readout omits the need for extensive instrumentation. Moreover, the primer-based sequence detection of RPA gives Rapidemic a potential to be rapidly adapted to target a new sequence. As a proof of concept, we developed the assay to detect isolated genomic DNA of Saccharomyces cerevisiae. The use of low-pH buffers and the optimization of the dilution rates from each preceding reaction to the next showed to be successful strategies to enable visible detection with this method. These findings demonstrate for the first time that a label-free DNAzyme-based detection method can be coupled to RPA and LSDA for nucleic acid detection.

molecular biology↗