Biology subjects

Sridhar, V.

Publications and source records attributed to Sridhar, V..

6 recordsLinked to original sources

bioRxiv2025

Quorum sensing antiactivators constrain Pseudomonas aeruginosa RhlR activity

Pseudomonas aeruginosa, an opportunistic pathogen, uses a cell-cell communication system called quorum sensing (QS) to regulate gene expression in response to population density. P. aeruginosa QS involves, in part, two transcription factors, LasR and RhlR, that respond to N-acyl homoserine lactone (AHL) signals. Two proteins known as "antiactivators," QteE and QslA, attenuate QS by inhibiting LasR, RhlR, or both. While initial characterization of antiactivation has revealed the considerable influence these factors may have on dampening QS, details regarding the individual impacts of these antiactivators on P. aeruginosa QS activity remain scant. Additionally, the effects of antiactivators on RhlR QS activity and in QS systems in isolates or strain lacking LasR have yet to be explored. To investigate how QteE and QslA each modulate LasR or RhlR independently, we combined gene deletion and over-expression analysis of each antiactivator in wild-type P. aeruginosa (PAO1) and two strains with rhl-dominated QS: clinical isolate E90 and PAO {Delta}lasR {Delta}mexT. As measured with a transcriptional reporter, over-expression of qteE or qslA notably reduced RhlR activity in PAO1 and PAO {Delta}lasR {Delta}mexT, but only expression of qteE had a marked effect on RhlR activity in E90. Expression analysis indicates LasR and RhlR repress QteE transcription, but not QslA. By over-expressing qslA in the absence of QteE and vice versa, we demonstrate that QslA activity and corresponding effects on QS phenotypes can be QteE-dependent in some scenarios. Our results reveal a nuanced role for individual antiactivator proteins in affecting the layered P. aeruginosa QS circuitry. ImportanceQuorum sensing (QS) is a cell signaling mechanism that enables populations of Pseudomonas aeruginosa to coordinate group behaviors such as biofilm formation, virulence factor production, and antibiotic tolerance once a critical cell-density threshold is reached. P. aeruginosa employs two "antiactivator" proteins that attenuate QS at low cell densities, dampening QS activation. The specific effects of individual antiactivators on the complex and hierarchically-arranged P. aeruginosa QS systems remain undefined. Here, we use two strains with rewired QS circuits to independently assess the effects of QS antiactivators on each QS circuit. We find that while one antiactivator selectively targets one QS circuit, the other can broadly target both with strong effects on QS activity. This work reveals an additional layer of complexity to counter-regulation of QS signalling and further defines antiactivation as a mechanism P. aeruginosa uses to finely tune QS responses.

microbiology↗

bioRxiv2025

Pathogenic tau inhibits synaptic plasticity by blocking eIF4B-mediated local protein synthesis

Activity-dependent modulation of synaptic strength is critical for encoding memories and it is inhibited in tauopathies including Alzheimers disease (AD) and Frontotemporal lobar degeneration with tau inclusions (FTLD-tau). Pathogenic tau accumulates in neurons where it obstructs synaptic plasticity. How tau blocks synaptic plasticity leading to memory loss is unclear. Here, we show that FTLD-tau inhibits plasticity by blocking activity-dependent protein synthesis in dendrites. In the plasticity-associated translatome, we identified a subset of downregulated translated mRNAs in FTLD-tau neurons that encode postsynaptic plasticity regulators. Protein synthesis was blocked by FTLD-tau binding to eIF4B which caused eIF4B dissociation from the translation initiation complex and reduced dendritic eIF4B levels. Inhibiting the tau-eIF4B interaction or enhancing eIF4B levels in FTLD-tau neurons restored local protein synthesis and synaptic plasticity. Together, this suggests that pathogenic tau binding to eIF4B disables the local synthesis of plasticity-related proteins that drive synapse strengthening and memory formation.

neuroscience↗

bioRxiv2025

From sequence to signature: Uncovering multiscale AMR features across bacterial pathogens with supervised machine learning

Since the clinical introduction of antibiotics in the 1940s, antimicrobial resistance (AMR) has become an increasingly dire threat to global public health. Pathogens acquire AMR much faster than we discover new drugs (antibiotics), warranting innovative methods to better understand its molecular underpinnings. Traditional approaches for detecting AMR in novel bacterial strains are time-consuming and labor-intensive. However, advances in sequencing technology offer a plethora of bacterial genome data, and computational approaches like machine learning (ML) provide an optimistic scope for in silico AMR prediction. Here, we introduce a comprehensive multiscale ML approach to predict AMR phenotypes and identify AMR molecular features associated with a single drug or drug family, stratified by time and geographical locations. As a case study, we focus on a subset of the World Health Organizations Bacterial Priority Pathogens, the frequently drug-resistant and nosocomial ESKAPE pathogens: Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species. We started with sequenced genomes with lab-derived AMR phenotypes, constructed pangenomes, clustered gene and protein sequences, and extracted protein domains to generate pangenomic features across molecular scales. To uncover the molecular mechanisms behind drug-/drug class-specific resistance, we trained logistic regression ML models on our datasets. These yielded ranked lists of AMR-associated genes, proteins, and domains. In addition to recapitulating known AMR features, our models identified novel candidates for experimental validation. The models were performant across molecular scales, data types, and drugs while achieving a median normalized Matthews correlation coefficient of 0.89. Prediction performance showed resilience even when evaluated on geographical and temporal holdouts. We also evaluated model generalizability and cross-resistance across the drug-/drug class-specific models cross-tested on other available drug-/drug class genomes. Finally, we uncovered multiple drug class resistance features using multiclass and multilabel models. Our holistic approach promises reliable prediction of existing and developing resistance in newly sequenced pathogen genomes, while pinpointing the mechanistic molecular contributors of AMR. All our models and results are available at our interactive web app, https://jravilab.org/amr.

bioinformatics↗

bioRxiv2025

Characterizing mixed single chain amphiphile-based coacervates as a robust protocell system

Prebiotic soup would have been a dilute pool of various constituent chemicals that would have reacted with each other to form biologically relevant precursors during lifes origin. In this milieu, compartments formed by liquid-liquid phase separation (LLPS) are thought to have facilitated concentration of chemicals, thereby catalyzing their reactions. Towards this, various LLPS-based systems have been studied as model protocells. Relevantly, fatty acid-based (decanoic acid) coacervates have recently been explored as model protocells. As far as protocell research is concerned, fatty acids have been studied much more extensively in the context of vesicle-forming entities when compared to them resulting in coacervate systems. Furthermore, exogenous delivery and endogenous synthesis of fatty acids suggest the prevalence of single chain amphiphiles (SCAs) on the early Earth, with a greater abundance of the shorter chain length moieties. In this backdrop, we set out to fabricate robust coacervate-based protocells using SCAs that would have been readily present in a chemically heterogeneous prebiotic soup, and which could thrive under various prebiotically relevant selection pressures. Towards this, we characterized a mixed amphiphile-based coacervate system composed of nonanoic acid (NA), nonanol (NOH) and tyramine (Tyra), which could form coacervates over a broad range of pHs, temperatures, and salt concentrations. This is noteworthy as compositionally heterogenous vesicles have also been shown to have advantages over pure fatty acid vesicles. Additionally, we also demonstrate RNA sequestration in these coacervates that gets enhanced upon addition of cationic amino acids, emphasizing the importance of co-solute interactions in the prebiotic soup. Lastly, we also demonstrate nonenzymatic template-directed primer extension in these coacervates, suggesting the potential functional role of these compartments during lifes origin.

biochemistry↗

bioRxiv2025

Hoi1 targets the yeast BLTP2 protein to ER-PM contact sites to regulate lipid homeostasis

Membrane contact sites between organelles are important for maintaining cellular lipid homeostasis. Members of the recently identified family of bridge-like lipid transfer proteins (BLTPs) span opposing membranes at these contact sites to enable the rapid transfer of bulk lipids between organelles. While the VPS13 and ATG2 family members use organelle-specific adaptors for membrane targeting, the mechanisms that regulate other bridge-like transporters remain unknown. Here, we identify the conserved protein Ybl086c, which we name Hoi1 (Hob interactor 1), as an adaptor that targets the yeast BLTP2-like proteins Fmp27/Hob1 and Hob2 to ER-PM contact sites. Two separate Hoi1 domains interface with alpha-helical projections that decorate the central hydrophobic channel on Fmp27, and loss of these interactions disrupts cellular sterol homeostasis. The mutant phenotypes of BLTP2 and HOI1 orthologs indicate these proteins act in a shared pathway in worms and flies. Together, this suggests that Hoi1-mediated recruitment of BLTP2-like proteins represents an evolutionarily conserved mechanism for regulating lipid transport at membrane contact sites.

cell biology↗

bioRxiv2024

Taking stock of selective logging in the Andaman Islands, India: recent & legacy effects of timber extraction, assisted natural regeneration and a revamped working plan

Forest management is an evolving balance between biodiversity conservation and economic needs. A shift in Andaman Islands Working Plan mandate in 2000s reflects this evolution. Our study independently assesses the impact of said policy change on post-logging recovery of forests in Baratang and Middle Andaman. In 2017-18, we placed seventy-six 0.49ha plots across evergreen and deciduous patches and compared large-tree ([≥]180cm girth) density and diversity across forests that were logged after 2005 focussing on sustainability, logged in 1990s focussing on timber, logged twice in 1990s and after 2005, and unlogged forests. We assessed forest regeneration in thirty 0.01ha plots along a coupe road within forests logged after 2005. Forests logged after 2005 had similar density of large trees as forests logged in 1990s (despite having 1/3rd the recovery time), indicating reduced offtake or better recruitment. Along the unlogged--once-logged--twice-logged gradient, the dominance of Pterocarpus dalbergioides in deciduous patches decreased while the dominance of Diptercarpus sp. in evergreen patches increased. Compared to natural regeneration, proportionately more deciduous saplings were planted in both evergreen and deciduous patches. The new working plan maintains timber stock but not diversity. We make six simple recommendations to better align practice with the Working Plan mandate. SynthesisPost-2005 timber extraction policy in the Andaman Islands is partially successful but long-term forest health, in line with the working plan mandate, requires (1) lower timber offtake from deciduous patches and (2) targeted assisted regeneration of non-timber tree species.

ecology↗