Biology subjects

Panda, S.

Publications and source records attributed to Panda, S..

At least 19 recordsLinked to original sources

bioRxiv2026

RNA trans-splicing treatment for Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is a fatal disorder caused by dystrophin mutations, leading to progressive muscle degeneration and cardiac failure. Although AAV-based DMD therapies with innovative designs to overcome the cargo limits of the virus are effective in animal models, these current systems may face clinical translation challenges related to efficiency, off-target effects, and immunogenicity. We developed a multi-vector RNA End Joining (REJ) system to split large genes into multiple co-delivered AAVs that engage the cell's intrinsic spliceosome to precisely reassemble RNA segments that encode very large scar-free proteins. We show the system is efficient and has negligible off-target interactions. In vivo, REJ vectors expressing the adenine base editor Abe8e, mini-dystrophin Dp253, or native full-length dystrophin Dp427 each prevented muscle degeneration. Machine-learning histopathology of more than 120,000 myofibers revealed robust reductions in nuclear infiltration, improved centronucleation, and normalized hypertrophy, supported by functional, transcriptomic, and behavioral analyses. These findings establish REJ as a clinically viable AAV-based strategy for DMD that enables expression of large therapeutic proteins while avoiding potentially antigenic bacterial protein- or DNA-recombinases.

molecular biology↗

bioRxiv2026

The circadian system is affected by Alzheimers disease independently from amyloid beta deposits

Circadian disruption, notably sleep disturbances, serves as an early indicator of Alzheimers disease (AD), preceding cognitive symptoms like memory loss. The suprachiasmatic nucleus (SCN) governs biological rhythms and receives direct retinal input via melanopsin-expressing retinal ganglion cells (mRGCs) to synchronize with environmental light cycles. The anatomical and functional basis for circadian disruption in AD remains unclear. Here, we explored the multi-level relationships between gene expression, the SCN connectome, and regulations of sleep and circadian rhythms in the APP/PS1 mouse model. The sleep architecture of APP/PS1 mice displayed significantly reduced rapid eye movement sleep (REM), associated with a reduced daily core body temperature amplitude and locomotor hyperactivity. Lastly, APP/PS1 mice showed an impaired response to acute light pulse stimulation and present hyperactivity of mRGCs at a young age and hypoactivity of these cells at older ages. These physiological functions are known to be, at least in part, regulated by the SCN, the main target of mRGCs. We noted several modifications in SCN connectomics using serial blockface electron microscopy (SBEM), including a reduction of the dendro-dendritic chemical synapse (DDCS) network that receives a large part of the retinal input and is thought to be crucial for synchronicity between SCN neurons. In addition, we observed multiple signs of dystrophy, including modifications of the shape of dendrites and cell soma, accumulation of aggregated lysosomes, and swelling of axons. At the same time, we investigated the changes in gene expression using spatial transcriptomics. The SCN presents changes in the expression of genes associated with synapse formation, cell adhesion, and neurite growth. These results suggest that, despite the absence of amyloid plaques in the ventral hypothalamus, the SCN of APP/PS1 mice still undergo profound gene expression changes, impacting connectomics and physiological functions. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC="FIGDIR/small/744599v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@ceedb0org.highwire.dtl.DTLVardef@156cfaaorg.highwire.dtl.DTLVardef@5bc262org.highwire.dtl.DTLVardef@36df4d_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Combining 3D-multispectral and hyperspectral imaging to identify environmental stress treatments imposed during plant growth

Non-invasive, high-throughput phenotyping tools are needed that can identify environmental effects on plant structure and function to diagnose factors responsible for reduced growth in commercial and non-commercial settings. In this study, we explored whether the integration of 3D-multispectral (3D) and 2D-hyperspectral imaging (HSI), aided by machine learning (ML), could be used to identify environmental stress treatments imposed during plant growth. Controlled environment-grown Nicotiana Benthamiana plants were subjected to a range of abiotic treatments - including different growth irradiances, heat treatment and drought stress - with the treatments resulting in differences in shoot height, biomass, leaf area and spectral reflectance. ML models were trained to identify these treatments using morphological and spectral traits measured at 27, 29, 31, and 34 days after sowing (DAS). A 3D-multispectral scanner was used to obtain information on plant height, biomass, and leaf area. A visible and near-infrared (VNIR) HSI camera provided detailed spectral information for deriving spectral indices including the Normalised Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI) and Normalized Difference Red Edge (NDRE). Manual measurements provided baseline comparative data. The 3D-multispectral scanner reliably estimated above-ground traits, with high correlations between manual and scanner-derived measurements. The ML models accurately differentiated among environmental stress treatments, with the fused 3D+HSI model achieving the best overall predictive performance across all evaluated metrics compared with models based on either imaging modality alone. Results demonstrated the effectiveness of combining 3D-multispectral and 2D-HSI data with ML analyses for non-destructive, high-throughput phenotyping. The integration of these techniques enabled non-destructive, high-throughput identification of environmental stress treatments imposed during plant growth.

plant biology↗

bioRxiv2026

Evidence-constrained mechanistic synthesis for drug discovery

Biomedical evidence can become mechanistically informative before it becomes sufficiently commensurate to calibrate one system model. We developed evidence-constrained mechanistic synthesis (ECMS), a pre-calibration framework that converts only the mathematical information supported by each finding into constraints on a possibility space of executable mechanistic worlds. We reconstructed historical ECMS systems for alopecia areata (AA) and chronic spontaneous urticaria (CSU) using knowledge available by 31 December 2023, froze molecule/regimen inputs, observation semantics and finite ensembles before outcome reveal, and evaluated later studies at prespecified information-property resolution rather than as calibrated clinical predictions. Among 41 registered atomic properties, ECMS committed to 34 executable propositions: 29 were empirically concordant, one was clearly contradicted, and four could not be fully assessed because intermediate reporting or intervention isolation was insufficient; seven additional properties were prespecified abstentions and were not counted as empirical successes. An evidence-lineage audit further separated nine direct historical analogues from 16 near transfers, four mechanistic transfers and four cross-stream syntheses. Baricitinib withdrawal in AA was a cross-stream synthesis: no pre-cutoff baricitinib-withdrawal result was used, yet the frozen system reproduced early persistence followed by progressive loss. Selective MRGPRX2 antagonism in CSU transferred from pre-cutoff route-separation evidence, whereas patient-level clinical efficacy was withheld. A later baricitinib trajectory contradicted the frozen week-36-to-52 monotonicity property, preserving falsifiability. These results show that heterogeneous pre-calibration evidence can be made executable and externally challenged without being converted into unsupported coefficients,posterior biological probabilities or patient-response models.

systems biology↗

bioRxiv2026

Excitatory Dysfunction and Phenotypic Rescue in a Human Neuronal Model of SCN2A-Related Disorders

SCN2A-related disorders result from pathogenic variants in the gene encoding for the voltage-gated sodium channel Nav1.2. Collectively, these disorders result in variable age of onset epilepsy, autism spectrum disorder, and epileptic encephalopathies. While the mechanisms of haploinsufficiency resulting in autism spectrum disorder have been explored in detail, few studies report the impact of pathogenic missense variants in human neurons. In this work, we combined conventional electrophysiology and high-throughput all-optical electrophysiology assays to analyze the SCN2A p.M1879T pathogenic variant associated with early-onset epilepsy and developmental delay. In both platforms, iPSC-derived excitatory neurons expressing the disease variant showed greater firing at higher stimuli compared to the isogenic control neurons (corrected by CRISPR/Cas9), as well as changes to action potential shape (steeper slope and larger amplitude) with evoked firing. We used machine learning techniques on the optical physiology dataset to classify the two genotypes, finding that sodium channel blocking anti-seizure drugs could restore an isogenic phenotype. This work demonstrates proof of sodium channel blocker efficacy in a human neuronal model of SCN2A-related epilepsy and highlights the power of leveraging high-throughput all-optical electrophysiology for testing drug efficacy.

neuroscience↗

bioRxiv2026

Time Restricted Feeding Mitigates High-Fat-Diet Induced Sleep Disruption and Amplifies NREM Substates

The effects of diet quality and timing on sleep quality remain poorly understood, particularly at the level of sleep microarchitecture. Traditional visual scoring captures only coarse sleep stages, overlooking the marked heterogeneity of electroencephalographic (EEG) patterns in non-rapid eye movement (NREM) sleep of mice. Here, we apply a pipeline that combines EEG feature extraction with unsupervised machine-learning-based clustering to resolve discrete NREM substates and ask how a high-fat diet (HFD) and time- restricted feeding (TRF) affect sleep microarchitectures. HFD increases sleep latency and sleep fragmentation; both abnormalities were ameliorated by active phase TRF. Clustering of 10s epochs identified two high-amplitude NREM substates sensitive to TRF: Cluster 1, enriched in low-delta power and peaking early in the light phase (ZT 0-6), consistent with canonical slow-wave sleep, and Cluster 6, characterized by elevated alpha, sigma, and beta power and peaking in the latter half of the light phase (ZT6-12). TRF increases the frequency of both NREM substates, particularly within longer uninterrupted sleep episodes during the light phases. These findings introduce an objective framework for quantifying murine sleep microarchitecture and show that aligning caloric intake with the circadian active window mitigates HFD-induced macro-level sleep disruption while selectively enhancing two physiologically distinct NREM substates. Significance StatementTime-restricted eating - targeting food intake to a defined window during the circadian active phase - confers well-established metabolic benefits, but its impact on sleep is largely underexplored. Using continuous EEG/EMG recordings, we show that an active- phase eating window mitigates high-fat-diet-induced sleep disruption in mice. We employed a novel machine-learning pipeline, further revealing that timed eating selectively increases distinct NREM substates, demonstrating that "when we eat" fine-tunes the macro- and microarchitecture of sleep. These insights lay the foundation for future translational studies and clinical trials aimed at harnessing timed eating to enhance both metabolic and sleep health.

animal behavior and cognition↗

bioRxiv2026

Early Blood Metabolome Remodeling Reveals Metabolic Signatures of Hypoxic-Ischemic Encephalopathy

Hypoxic-ischemic encephalopathy (HIE) is a neonatal brain injury in which a definitive diagnosis within the first 6 hours of life is essential for initiating therapeutic hypothermia and improving neurological outcomes. However, early clinical evaluation and currently available biomarkers lack quantitative specificity during this narrow therapeutic window. We are providing insights into how rapid disturbances in systemic metabolites that regulate cerebral energy metabolism, neurotransmitter cycling, redox balance, and membrane integrity generate a definitive biochemical signature of HIE immediately after birth. We performed quantitative blood-based 1H NMR metabolomics on collected blood samples within [~]1 hour of birth from 81 neonates (HIE, n = 42; non-HIE, n = 39), under optimized handling conditions to preserve metabolic integrity. Metabolite analysis revealed a distinct HIE-associated profile characterized by elevated lactate, alanine, succinate, glutamate, taurine, glycine, choline, and pyroglutamate, alongside significant depletion of glucose and glutamine compared with non-HIE controls (p < 0.05). These coordinated metabolic shifts reflect impaired mitochondrial respiration, enhanced anaerobic glycolysis, excitotoxic amino acid accumulation, altered membrane phospholipid turnover, and oxidative stress. Multivariate analysis demonstrated clear separation between groups (PLS-DA accuracy = 0.83, R{superscript 2}Y = 0.46, Q{superscript 2} = 0.82), with glutamine, lactate, glutamate, and pyroglutamate as key discriminators. Pathway enrichment highlighted perturbations in glycolysis, the glucose-alanine cycle, glutamate-glutamine metabolism, Warburg effect like metabolic reprogramming, and redox homeostasis. Integration into supervised machine-learning models (Random Forest, XGBoost, SVM, KNN) achieved strong diagnostic performance (AUC = 0.97 {+/-} 0.03; sensitivity {approx} 87%). Collectively, this minimally invasive NMR-to-machine-learning framework enables early, mechanistically grounded risk stratification of neonatal HIE within the therapeutic window.

neuroscience↗

bioRxiv2026

Urbanisation Reshapes Freshwater Microbiomes: A Systematic Review of Ecological Patterns and Functional Shifts

Rapid urbanisation has profoundly shaped microbial diversity across different ecosystems. Freshwater microbiomes are particularly affected by urbanisation activities, such as eutrophication, pollution, runoff, and sewage. This is of significant concern as marginalised communities often depend on waterbodies for their livelihood. Freshwater bodies play a crucial role in maintaining both human and ecological health at population level. Currently, we lack a systematic understanding of the global impacts of urbanisation on freshwater microbiomes in relation to human health, ecosystem functioning, and sustainability. We identified 90 eligible papers from the last 25 years after screening based on the inclusion exclusion criteria. We extracted data that examined changes in the functional traits such as antimicrobial resistance (AMR), nutrient cycling of the microbiome in urban waterbodies and several other factors. Data were extracted by a thematic analysis followed by a narrative synthesis on specific functional traits. This systematic review presents a comprehensive analysis on the changes and challenges brought about by urbanisation on freshwater bodies. Our results indicate that urbanisation leads to reduced bacterial diversity of urban waterbodies, with a striking increase in reporting of Proteobacteria, Cyanobacteria and Coliform bacteria. These insights will help inform public health strategies and sustainable urban planning. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/715732v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@1198ae7org.highwire.dtl.DTLVardef@1ee7db3org.highwire.dtl.DTLVardef@7e959corg.highwire.dtl.DTLVardef@90653b_HPS_FORMAT_FIGEXP M_FIG C_FIG Waterbodies in urban areas function as convergence platforms for anthropogenic and environmental microbiomes. Runoffs, wastewater and effluents contain antimicrobial resistance genes and other pathogens that survive in water due to inadequate treatment. Disposal, use, and overflow of wastewater cause restructuration of microbial communities, proliferation of opportunistic microorganisms, and spread of antimicrobial resistance in aquatic ecosystems.

genomics↗

bioRxiv2026

AI-designed nuclease performs robust knock out, base editing and prime editing in plants

Genome-editing applications in biological organisms rely on a limited set of naturally occurring enzymes. Artificial intelligence (AI) is transforming protein design. Here, building on the AI-designed nuclease OpenCRISPR-1, we establish the plant-optimized AI-designed editors (PAiD) as a versatile genome-editing platform in plants. PAiD supports NHEJ-mediated indel generation, adenine and cytosine base editing, and prime editing, with robust performance across multiple loci comparable to SpCas9. These results highlight the translational potential of AI-designed nucleases for plant genome engineering.

plant biology↗

bioRxiv2026

K27-linked ubiquitination restrains the NOD2-RIP2 signaling pathway

Nucleotide-binding oligomerization domain 2 (NOD2) signaling is a critical arm of host defense and immune homeostasis but requires strict regulation to prevent self-injury. Central to this regulation is the polyubiquitination of the adaptor protein RIP2, yet the precise ubiquitin linkages and their dynamic control remain incompletely understood. Here, we identify K27-linked polyubiquitination of RIP2 by the E3 ligase XIAP as a novel inhibitory signal that attenuates RIP2 complex assembly and downstream NF-{kappa}B activation, thereby fine-tuning NOD2-induced inflammatory signaling. We show that XIAP-mediated K63-linked ubiquitination promotes NOD2-RIP2 activation, whereas K27-linked ubiquitination impairs the recruitment of TAK1 and NEMO to the NOD2-RIP2 complex, dampening downstream signaling and cytokine production. We further demonstrate that this regulation is counterbalanced by the deubiquitinase MYSM1, which selectively removes K27-, K63-. and M1-polyubiquitin chains via its SWIRM-MPN domains to restore balanced signaling. Together, these findings define a dynamic XIAP-RIP2-MYSM1 axis in which opposing ubiquitin linkages fine-tune NOD2 responses, establishing a molecular rheostat for immune signaling with implications for inflammatory disease pathogenesis and opportunities for targeted therapeutic intervention.

immunology↗

bioRxiv2026

Prime editing of an evolutionarily informed PEPC residue enhances photosynthesis and grain nutrition in C₃ rice

C4 photosynthesis evolved through adaptive changes in key metabolic enzymes that enhance carbon fixation efficiency, yet transferring such traits into C3 crops has met limited success. Using precision prime editing, we introduced an evolutionarily conserved single amino acid substitution (Arg[->]Gly) into phosphoenolpyruvate carboxylase (PEPC) in rice. Edited plants exhibited enhanced PEPC activity in the presence of the feedback inhibitor malate, increased chlorophyll content, elevated photosynthetic rates under ambient CO2, and increased seed size and weight. Remarkably, seeds from the edited lines showed simultaneous enrichment of zinc (Zn), iron (Fe), and protein, hereafter referred to as ZiP rice. This work demonstrates that a single, evolutionarily guided residue change can reprogram core carbon metabolism in a C3 crop, enabling concurrent improvements in photosynthesis and grain nutritional quality.

plant biology↗

bioRxiv2025

Activation of the Spx redox sensor counters cysteine-driven Fe(II) depletion under disulfide stress

In many low G+C Gram-positive bacteria, the global regulator Spx helps maintain thiol homeostasis during disulfide stress, when protein thiols form aberrant disulfide bonds that can lead to misfolding and oxidative damage. Spx-dependent gene expression is triggered when an intramolecular disulfide bond forms between two cysteines in its redox switch. Surprisingly, some Spx functions persist even in the absence of an active redox switch, highlighting the need to better understand the physiological significance of maintaining this regulatory feature. Here, we utilize a spxC10A mutant that encodes a redox-insensitive Spx variant to study the role of the Spx redox switch in Staphylococcus aureus. We show that the spxC10A mutant is hypersensitive to diamide-induced disulfide stress and exhibits widespread transcriptional dysregulation of genes that contribute to thiol maintenance and disulfide repair. Remarkably, the spxC10A mutant rapidly adapts to disulfide stress by increasing its intracellular pool of L-cysteine (L-Cys) through enhanced uptake, which helps restore a reduced intracellular environment. However, during this process increased L-Cys inadvertently depletes cytosolic Fe(II), leading to growth inhibition of the spxC10A mutant. Finally, we show that the Spx-dependent control of intracellular L-Cys is critical for S. aureus survival when it encounters human neutrophils. Overall, these findings suggest that staphylococcal adaptation to disulfide stress through intracellular L-Cys accumulation imposes significant fitness costs that S. aureus overcomes by rapid regulatory control of thiol homeostasis through a functional Spx redox switch. SignificanceAll cells have a pool of low molecular weight thiols, such as cysteine, glutathione, bacillithiol, and coenzyme A, to maintain redox balance under oxidative and disulfide stress. Among these, cysteine is a very effective thiol but is highly reactive, and its intracellular concentration must be tightly regulated. In S. aureus, we found that cysteine accumulates intracellularly during disulfide stress and if left unchecked, can inadvertently deplete cytosolic Fe(II), leading to growth inhibition. To prevent cysteine toxicity, S. aureus activates the global regulator Spx, which rapidly induces genes that restore thiol homeostasis and limits cysteine accumulation.

microbiology↗

bioRxiv2025

Fingerprint-Based Explainable Machine Learning for Predicting Blood--Brain Barrier Permeability

Predicting blood-brain barrier (BBB) permeability is essential for early central nervous system (CNS) drug discovery, yet reliable computational screening remains challenging. This study presents a gradient-boosted ensemble framework trained on precomputed molecular fingerprints to classify compounds as BBB-permeable (BBB+) or non-permeable (BBB-). The 2048-bit fingerprints encode substructural information relevant to passive diffusion without requiring explicit physicochemical descriptors. The model, trained on experimentally annotated BBB datasets using Extreme Gradient Boosting (XGBoost) with Synthetic Minority Oversampling (SMOTE) to address class imbalance, achieved strong predictive performance (cross-validated ROC- AUC = 0.897 {+/-} 0.019; validation ROC-AUC = 0.932). External testing on literature-reported CNS-active compounds (Caffeine, Diazepam, Dopamine, and Levodopa) confirmed biological consistency: highly lipophilic drugs were predicted as BBB+, while polar molecules dependent on carrier-mediated transport were predicted as BBB-. The fingerprint-based model thus captures underlying permeability mechanisms through data-driven substructure learning. This approach eliminates the need for handcrafted descriptors while preserving interpretability through feature-importance analysis, establishing a reproducible, efficient, and explainable baseline for virtual BBB permeability screening in CNS drug development.

neuroscience↗

bioRxiv2025

Time-Restricted Feeding Attenuates Kidney Damage and Preserves Renal Function in Mouse Model of Chronic Kidney Disease

Chronic kidney disease (CKD) is a highly disabling and potentially deadly condition for which there is no cure. With renal damage risk factors such as hypertension, metabolic syndrome and type 2 diabetes on the rise, the prevalence of CKD is increasing worldwide. New therapeutic approaches to CKD management are thus warranted. Time-restricted feeding, a dietary intervention in which daily food intake is limited to a consistent time window, has shown benefits in the context of metabolic disease management. Boolean implication network model of human CKD gene expression data and data from mouse TRF kidney implied TRF could attenuate kidney injury from CKD. We tested the effect of TRF in mouse models of kidney damage under high-fat high-sucrose feeding to induce a metabolic-disease prone environment. Using gold standard pre-clinical models of renal fibrosis, we discovered that TRF protected from kidney damage and clinical features of CKD. At the molecular level, the effects of TRF were pleiotropic with benefits in pathways involved in renal inflammation, fibrosis, and ER stress. Importantly, our results also suggest that TRF can confer early protection from metabolic alterations implicated in kidney damage.

pathology↗

bioRxiv2025

Mechanism-aware inference of response to targeted cancer therapies

Targeted therapies like small-molecule inhibitors often work by blocking proteins that cancer cells rely on for survival. Omics based modeling of drug sensitivity alone lack mechanistic grounding. We propose FORGE (Factorization Of Response and Gene Essentiality) a simple yet powerful joint matrix factorization framework that co-models drug response and target gene essentiality, enabling the stratification of promising treatment groups for targeted therapy consideration. FORGE also provides Benefit Score -- a predictive score that estimates treatment efficacy from basal gene expression profiles. We validated the predictive performance of FORGE across multiple targeted therapies, including Erlotinib (EGFR inhibitor) and Daporinad (NAMPT inhibitor). Our meta-analysis of large scale in-vitro studies underscores FORGEs ability to identify common determinants of drug vulnerabilities and target gene essentiality. Such convergences were not observed when treatment vulnerabilities and gene essentialities were modeled independently. We also demonstrated the universality of Erlotinib Benefit Scores by transferring transformations learned from high-throughput drug response studies across other published datasets, including the TAHOE-100M single-cell perturbation atlas and patient-derived xenograft studies. FORGE successfully identified key regulators within the molecular pathways targeted by these therapies, reinforcing its potential for mechanistically grounded treatment stratification.

cancer biology↗

bioRxiv2025

A D-alanine aminotransferase S180F substitution confers resistance to β-chloro-D-alanine in Staphylococcus aureus via antibiotic inactivation

Alanine transport and metabolism impact MRSA pathophysiology by dictating the availability of D-alanine for cell wall synthesis, the target of {beta}-lactam antibiotics. Furthermore cycA-dependent alanine transport controls MRSA {beta}-lactam susceptibility in chemically defined medium (CDM) in a glucose-dependent manner. Here we report that S. aureus was auxotrophic for L-alanine in CDM, and that this growth defect was rescued by glucose (or compensatory mutations), but only when the alanine racemase (alr1) and D-alanine aminotransferase (dat) genes were functional. No role was observed for the alanine dehydrogenase 1 (ald1) and ald2 genes. As previously reported, alr1 and, to a lesser extent, cycA mutations increased susceptibility to D-cycloserine (DCS). In contrast, only alr1 mutation increased susceptibility to {beta}-chloro-D-alanine (BCDA), suggesting distinct targets for these alanine analogue antibiotics, which act synergistically against MRSA. Genome sequencing of a BCDA-resistant mutant identified a C539T mutation in dat, predicted to result in a S180F substitution. Expression of the datC539T operon in wild-type increased BCDA resistance. alr1/dat::Em and alr1/datC539T double mutants were auxotrophic for D-alanine, indicating that Dat-S180F transaminase activity is impaired, a conclusion supported by in vitro enzyme assays. Structural modeling revealed an active-site loop shift in Dat-S180F that altered PLP co-factor binding. Molecular docking showed that the S180F substitution promotes BCDA-PLP adduct dissociation by releasing inactivated BCDA, thereby conferring resistance. These data reveal essential roles for Alr1 and Dat during growth under nutrient-limiting conditions and the potential of combination therapy separately targeting both enzymes with DCS and BCDA to extend the treatment options for MRSA infections.

microbiology↗

bioRxiv2025

Minimal immune cell subset differences in a cohort of close contacts of tuberculosis index cases

Understanding the perturbations in immune response across the spectrum of TB infection is still unclear. In this study, we followed a cohort of close contacts of pulmonary TB patients with serial QFT testing at 0, 3, 6, and 12 months, and stratified them into six subgroups: QFT-increasing (low/high), QFT converters (QFT- to QFT+), QFT+ stable, and QFT- individuals. Despite these distinct QFT trajectories, we observed minimal differences in immune cell frequencies, activation profiles, and T helper subset distributions among the QFT subgroups, suggesting limited immunological stratification based on QFT dynamics alone. Ex vivo immune phenotyping, including analysis of CD4, CD8, and NKT cell frequencies, memory T cell subsets, and activated T cells (HLA-DRCD38), failed to distinguish between QFT subgroups. Antigen-specific CD4 T cell responses assessed by the activation-induced marker (AIM) assay were elevated in QFT+ compared to QFT- individuals. These findings suggest that blood-based immune profiling may not capture subtle immunological transitions among QFT converters or individuals with increasing QFT responses. In contrast, individuals with active TB (ATB) showed clear immune perturbations. ATB patients at diagnosis exhibited significantly elevated frequencies of antigen-specific CD4 T cells, increased activated T cells, and higher frequencies of intermediate monocytes and NK cells compared to QFT+/QFT- contacts. Many of these immune features declined with treatment, indicating therapy-associated immune resolution. Additionally, shifts in T helper subsets and effector memory populations were observed over the course of treatment. These results suggest that while ex vivo immune profiling can robustly distinguish active TB from non-diseased states, it lacks the resolution to differentiate QFT subgroups based on QFT dynamics alone. This could reflect either immunological similarity among close contacts regardless of QFT status or limitations of blood-based phenotyping in detecting early or subclinical immune shifts. Our study highlights the challenge of immunologically distinguishing QFT-defined subgroups within close contacts using conventional ex vivo profiling approaches.

immunology↗

bioRxiv2025

Ketone body driven lipid remodeling supports thermogenic adaptation to fasting

Metabolic adaptation to fasting may have conferred survival advantage to early humans and predicts weight gain caused by overnutrition in modern societies. Fasting suppresses brown adipose tissue (BAT) thermogenesis; however, it is unclear how BAT rewires cellular metabolism to balance between energy conservation and heat generation. Here, we report that BAT in mice under fasting and cold challenge consumed ketone bodies, specifically acetoacetate (AcAc). Ablating liver ketogenesis decreased, while enhancing hepatic AcAc output defended, body temperature in mice facing the dual challenge. Using stable isotope tracing in brown adipocytes in vitro combined with quantitative analysis of metabolic fluxes and lipidomics in BAT from genetic mouse models, we disentangled the two metabolic fates of AcAc - terminal oxidation in the mitochondria and lipid biosynthesis in the cytosol. Notably, AcAc-sourced carbon preferentially supported polyunsaturated fatty acid synthesis in BAT, linking to the positive impact of intermittent fasting on lipid profiles in both mice and humans. Therefore, ketone body utilization by thermogenic adipocytes contributes to metabolic resilience of mammals and can be targeted to optimize benefits of dietary regimens.

physiology↗