Biology subjects

Sur, S.

Publications and source records attributed to Sur, S..

At least 19 recordsLinked to original sources

bioRxiv2026

A Reproducible Pre-Transplant γδ T-cell Effector Signature Reveals Immune-Metabolic Programs Associated with Kidney Allograft Rejection

Despite optimized immunosuppression, acute kidney transplant rejection affects 10-20% of recipients within the first year, and no reliable pre-transplant molecular test exists to identify patients at high risk, independent of the donor HLA matching. Across three independent cohorts of kidney transplant recipients, profiled by bulk RNA-sequencing with T-cell receptor repertoire analysis, flow cytometry, CyTOF with paired metabolomics, we identified a reproducible depletion of {gamma}{delta} T cells associated with rejection: an elevated {beta}/{gamma}{delta} T cell ratio in two post-transplant, biopsy-matched cohorts, and depletion of specific {gamma}{delta} T effector clusters in a third, longitudinally sampled cohort. In this third cohort, {gamma}{delta} T cell depletion was already present at the pre-transplant baseline in patients who subsequently developed rejection and remained detectable across the transplant course, indicating that it reflects recipient baseline immune biology rather than a consequence of graft injury. Longitudinal metabolomic profiling in this cohort identified time-dependent metabolic changes, including in amino acid metabolism that co-occur with the {gamma}{delta} signature and converge with it upon multi-omics integration. At the pre-transplant baseline, {gamma}{delta} T-cell marker expression alone showed exploratory discriminatory value for rejection risk (AUC = 0.69), improving marginally when integrated with metabolomic features (AUC = 0.71); larger prospective studies will be needed before clinical translation.

immunology↗

bioRxiv2026

Physical Basis Of pKa Shift For Ionizable Lipids In An LNP-like Environment

Lipid nanoparticles (LNPs) are a leading drug delivery platform for mRNA or other nucleic acid-based therapeutics. LNP platforms are typically composed of ionizable aminolipids, phospholipids, sterols, and lipids tagged with polyethylene glycol. The ionizable aminolipids are typically cationic at low pH, allowing them to encapsulate negatively charged mRNA. The pH at which the ionizable head groups change charge states, the apparent pKa, is crucial to understand the characteristics and formulation of LNP. However, this is difficult to measure as the apparent pKa differs from the pKa of the aminolipids in bulk solution due to the complex chemical and charge environment. In this study, we use molecular dynamics (MD) simulations with alchemical free energy perturbation to calculate the pKa shift as a function of lipid composition, treating LNP-like and vesicle-like environments. Our results show that the pH-dependent structure of the systems affects the trends in pKa shifts in complex ways, driven by factors including surface electrostatics and lipid internalization. Our all-atom simulation protocol allows us to efficiently estimate the apparent pKa of LNP-like models formed with novel ionizable aminolipids and estimate how it will change with composition.

biophysics↗

bioRxiv2026

Spatial Regulation of CAR Signaling Enables Logic-Gated Activity

Chimeric antigen receptors (CARs) can induce T cells to kill cancer cells but also to kill normal cells that express the same antigens1. Designing CARs to recognize combinations of antigens, via Boolean logic, can simultaneously expand the scope of targetable antigens and make CAR T cells more specific to cancer2. For example, one antigen may be expressed on cancer cells and normal bone marrow cells, while a second antigen may be present on the same cancer cells but only in normal lungs. If recognition of both antigens is required for T cell activation, only the cancer cells will be killed. Creating such AND-gated CAR T cells has been challenging given the need to engineer non-natural signaling mechanisms that integrate two ligand binding events into a single T cell activation stimulus3-6. Here, we design a fundamentally new AND-gated receptor called Multi-ANtigen Triggered Immune Synapse (MANTIS), which leverages differences in extracellular receptor dimensions to regulate CAR signaling. MANTIS initially prevents CAR activity by steric blocking with a bulky extracellular domain. Upon engagement of the first antigen, MANTIS sheds this blocking domain, releasing a free CAR that can bind a second antigen and activate the T cell in an AND-gated manner. This work demonstrates how differences in extracellular receptor size can be leveraged to spatially regulate intracellular signaling pathways in response to antigen patterns, paving the way for new applications in synthetic biology and cell engineering. One sentence summaryDifferences in extracellular size can be leveraged to regulate CAR T cell activity for precise recognition of antigen patterns.

synthetic biology↗

bioRxiv2026

Theoretical estimate of the effective pKa of titratable lipids using continuum electrostatics

The apparent pKa of ionizable lipids in lipid nanoparticles (LNPs) is a key determinant of RNA encapsulation during formulation and endosomal release after cellular uptake. However, it is difficult to predict the effective pKa of a given ionizable lipid solely from its solution pKa, because it is sensitive to the membranes composition, as well as solution conditions such as the salt concentration. We developed a simple continuum electrostatics model, based on Gouy-Chapman theory, to predict the shift in effective pKa for ionizable lipids in lipid bilayers as a function of salt concentration and membrane composition. We derive equations for the surface potential and fraction of lipids charged, which are solved self-consistently as a function of solution pH to extract the titration curve and effective pKa. The model shows that the shift in effective pKa is largest when the concentration of titratable lipid is high, and the effect is diminished by increasing salt concentration. We provide a python implementation of the model and an interactive notebook that will allow users to further easily explore the predicted pKa shifts as a function of formulation variables.

biophysics↗

bioRxiv2025

Integrative Transcriptomics and Phytochemical Screening Reveal Pratenol B, Eriodictyol, Losbanine, and Isookanin, as Potential EGFR and HRAS Inhibitors in Indian Oral Squamous Cell Carcinoma Patients

Oral squamous cell carcinoma (OSCC) is the most common head and neck cancer, with India contributing nearly one-third of the global cases. Management of OSCC remains difficult due to increasing risk factors, limited therapeutic options, severe side effects, and rising drug resistance. Therefore, novel and safer treatment strategies are urgently needed. This study explores the potential of phytochemicals as targeted inhibitors of key dysregulated biomarkers in Indian OSCC patients. RNA sequencing and pathway analysis revealed significant alterations in the MAPK signaling pathway, highlighting EGFR and HRAS as crucial therapeutic targets. Given the limited clinical success of existing EGFR-targeted therapies and the scarcity of HRAS inhibitors, a natural product-based approach was adopted. Molecular docking of 17,000 phytochemicals identified Pratenol B, Eriodictyol, Losbanine, and Isookanin as promising inhibitors, with Pratenol B showing dual inhibition of EGFR and HRAS. These compounds exhibited strong binding affinities, favorable pharmacokinetic profiles, high bioavailability, and low toxicity. Molecular dynamics simulations confirmed the stability of Pratenol B with both target proteins, surpassing reference inhibitors. Utilizing vast medicinal plant diversity presents a cost-effective and low-toxicity avenue for OSCC therapy. Further in vitro, in vivo, and clinical studies are warranted to validate these phytochemicals as potential therapeutics.

cancer biology↗

bioRxiv2025

Upregulation of a novel lncRNA KLHDC7B-DT in Head and Neck Cancers: Implications for Prognosis and Molecular Mechanisms

Head and neck cancer (HNC), the seventh most frequent malignancy globally, is a serious health concern. Despite advancements in treatment, the overall survival rate for HNC remains around 50%, with even poorer outcomes in metastatic cases. This highlights the urgent need to explore the molecular mechanisms underlying HNC for improved diagnostics and therapies. The importance of non-coding RNAs, especially long non-coding RNAs (lncRNAs), in a variety of malignancies, including HNC, has been highlighted in recent researches. Although lncRNAs and mRNA are very similar, lncRNAs do not encode proteins and they are longer than 200 nucleotides. While studies have implicated lncRNAs in several cancers, including HNC, their exact role in HNC remains unclear, and there are currently no clinically established lncRNA biomarkers for diagnosis or therapy. Thus, this study aims to identify novel lncRNAs and investigate their significance in HNC. For this, we looked over recent research and discovered a new lncRNA called KLHDC7B-DT. The KLHDC7B-DT is significantly upregulated in HNC patient samples, and this result is corroborated by TCGA HNC data and cell lines. Further investigation suggests that KLHDC7B-DT may be linked with cancer stage, grade, age, and worse patient survival. We identified potential miRNAs that interact with KLHDC7B-DT and presented mRNA targets of these miRNAs, along with their possible functions. We propose that KLHDC7B-DT may regulate IL-6 expression in HNC, either through miRNAs or alternative mechanisms. Additionally, we found a significant positive correlation between the neighboring protein-coding gene KLHDC7B and the KLHDC7B-DT in HNC, both of which are significantly upregulated in HNC. In conclusion, KLHDC7B-DT is upregulated in HNC and holds promise as a prognostic and therapeutic biomarker. This study marks the first report highlighting the significance of KLHDC7B-DT in HNC.

cancer biology↗

bioRxiv2024

Unveiling theranostic potential: Insights into cell-free microRNA-protein interactions

MicroRNAs (miRNAs) belong to a short endogenous class of non-coding RNAs which have been well studied for their crucial role in regulating cellular homeostasis. Their role in modulation of diverse biological pathways by intracellular or extracellular communication and interaction with DNA, RNA or protein, projects them or their targets as promising biomarkers and therapeutic agents. However, studying specific interactions in the extracellular or cell-free environment for drug discovery or biomarker establishment is resource-intensive. In this study, we derive a computational approach based on available experimental data to decipher patterns in miRNA-protein interactions in the cell-free milieu. We characterized the miRNA-protein interactome (miRPin, https://www.mirna.in/miRPin) and identified consensus sequences governing these interactions. The study establishes the role of multiple miRNAs and protein interactions present in cell-free environments leading to pathological conditions, viz., role of proteins like METTL3 and AGO2 etc. and miRNAs like hsa-miR-484 and hsa-miR-30 families, hsa-mir-126-5p etc. in association with multiple miRNAs in different cancer types, cardiovascular diseases, and neurological disorders. The findings outlined in the study may facilitate new avenues of therapeutic discovery leading to the understanding of cellular mechanisms underlying therapy relapse and drug resistance. By addressing these interactions in an extracellular environment may further gain insight into regulating disease initiation and progression, overcoming challenges related to drug efficacy and drug delivery in the presence of bilayer membranes with drug efflux pumps.

bioinformatics↗

bioRxiv2024

Essential Considerations for Free Energy Calculations of RNA-Small Molecule Complexes: Lessons from Theophylline-Binding RNA Aptamer

Alchemical free energy calculations are widely used to predict the binding affinity of small molecule ligands to protein targets; however, the application of these methods to RNA targets has not been deeply explored. We systematically investigated how modeling decisions affect the performance of absolute binding free energy calculations for a relatively simple RNA model system: theophylline-binding RNA aptamer with theophylline and five analogs. The goal of this investigation was twofold: (1) understanding the performance levels we can expect from absolute free energy calculations for a simple RNA complex and (2) learning about practical modeling considerations that impact the success of RNA binding predictions, which may be different than the best practices established for protein targets. We learned that magnesium ion (Mg2+) placement is a critical decision that impacts affinity predictions. When information regarding Mg2+ positions is lacking, implementing RNA backbone restraints is an alternative way of stabilizing RNA structure that recapitulates prediction accuracy. Since mistakes in Mg2+ placement can be detrimental, omitting magnesium ions entirely and using RNA backbone restraints is attractive as a risk-mitigating approach. We found that predictions are sensitive to modeling experimental buffer conditions correctly, including salt type and ionic strength. We explored the effects of sampling in the alchemical protocol, choice of the ligand force field (GAFF2/OpenFF Sage), and water model (TIP3P/OPC) on predictions, which allowed us to give practical advice for the application of free energy methods to RNA targets. By capturing experimental buffer conditions and implementing RNA backbone restraints, we were able to compute binding affinities accurately (MAE = 2.2 kcal/mol, Pearsons correlation coefficient = 0.9, Kendalls tau = 0.7). We believe there is much to learn about how to apply free energy calculations for RNA targets and how to enhance their performance in prospective predictions. This study is an important first step for learning best practices and special considerations for RNA-ligand free energy calculations. Future studies will consider increasingly complicated ligands and diverse RNA systems and help the development of general protocols for therapeutically relevant RNA targets.

biophysics↗

bioRxiv2024

Allosteric inhibition of CXCR1 and CXCR2 abrogates Th2/Th17-associated Allergic Lung Inflammation in Mice

BackgroundIL4, IL5, IL13, and IL17-producing CD4 T helper 2 (Th2)-cells and IL17-producing CD4 T helper 17 (Th17)-cells contribute to chronic eosinophilic and neutrophilic airway inflammation in asthma and allergic airway inflammation. Chemokines and their receptors are upregulated in Th2/Th17-mediated inflammation. However, the ability of CXCR1 and CXCR2 modulate Th2 and Th17-cell-mediated allergic lung inflammation has not been reported. MethodsMice sensitized and challenged with cat dander extract (CDE) mount a vigorous Th2-Th17-mediated allergic lung inflammation. Allosteric inhibitor of CXCR1 and CXCR2, ladarixin was orally administered in this model. The ability of ladarixin to modulate allergen-challenge induced recruitment of CXCR1 and CXCR2-expressing Th2 and Th17-cells and allergic lung inflammation were examined. ResultsAllergen challenge in sensitized mice increased mRNA expression levels of Il4, Il5, Il13, Il6, Il1{beta}, Tgf{beta}1, Il17, Il23, Gata3, and Rorc, and induced allergic lung inflammation characterized by recruitment of CXCR1- and CXCR2-expressing Th2-cells, Th17-cells, neutrophils, and eosinophils. Allosteric inhibition of CXCR1 and CXCR2 vigorously blocked each of these pro-inflammatory effects of allergen challenge. CXCL chemokines induced a CXCR1 and CXCR2-dependent proliferation of IL4, IL5, IL13, and IL17 expressing T-cells. ConclusionAllosteric inhibition of CXCR1 and CXCR2 abrogates blocks recruitment of CXCR1- and CXCR2-expressing Th2-cells, Th17-cells, neutrophils, and eosinophils in this mouse model of allergic lung inflammation. We suggest that the ability of allosteric inhibition of CXCR1 and CXCR2 to abrogate Th2 and Th17-mediated allergic inflammation should be investigated in humans.

immunology↗

bioRxiv2024

Dirichlet distribution parameter estimation with application in microbiome analyses

Microbiomes are of vital importance for understanding human and environmental health. However, quantifying microbial composition remains challenging and relies on statistical modeling of either the raw taxonomic counts or the relative abundances. Relative abundance measures are commonly preferred over the absolute counts to analyze and interpret microbiome (as the sampling fraction are unknown in sequence data) but currently there is no ideal distribution for carrying out this modeling . In this work, the Dirichlet distribution is proposed to model the relative abundances of taxa directly without the use of any further transformation. In a comprehensive simulation study, we compared biases and standard errors of two Methods of Moments Estimators (MMEs) and Maximum Likelihood Estimator (MLE) of the Dirichlet distribution. Comparison of each estimator is done over three different cases of differing sample size and dimension: (i) small dimension and small sample size; (ii) small dimension and large sample size; (iii) large dimension with both large and small sample size. We demonstrate the Dirichlet modeling methodology with four real world microbiome datasets and show how the results of the Dirichlet model differ from those obtained by a commonly used method, namely Bayesian Dirichlet-Multinomial estimation (BDME). We find that the results of parameter estimation can be dependent upon the sequencing depth and sequencing technique used to produce a given microbiome dataset. However, for all datasets, the Dirichlet MLE (DMLE) results are comparable to the BDME results while requiring less computational time in each case.

bioinformatics↗

bioRxiv2023

Identification of nonsense-mediated decay inhibitors that alter the tumor immune landscape

Despite exciting developments in cancer immunotherapy, its broad application is limited by the paucity of targetable antigens on the tumor cell surface. As an intrinsic cellular pathway, nonsense-mediated decay (NMD) conceals neoantigens through the destruction of the RNA products from genes harboring truncating mutations. We developed and conducted a high throughput screen, based on the ratiometric analysis of transcripts, to identify critical mediators of NMD. This screen implicated disruption of kinase SMG1s phosphorylation of UPF1 as a potential disruptor of NMD. This led us to design a novel SMG1 inhibitor, KVS0001, that elevates the expression of transcripts and proteins resulting from truncating mutations in vivo and in vitro. Most importantly, KVS0001 concomitantly increased the presentation of immune-targetable HLA class I-associated peptides from NMD-downregulated proteins on the surface of cancer cells. KVS0001 provides new opportunities for studying NMD and the diseases in which NMD plays a role, including cancer and inherited diseases. One Sentence SummaryDisruption of the nonsense-mediated decay pathway with a newly developed SMG1 inhibitor with in-vivo activity increases the expression of T-cell targetable cancer neoantigens resulting from truncating mutations.

cancer biology↗

bioRxiv2023

ME3BP-7 is a targeted cytotoxic agent that rapidly kills pancreatic cancer cells expressing high levels of monocarboxylate transporter MCT1

Nearly 30% of Pancreatic ductal adenocarcinoma (PDAC)s exhibit a marked overexpression of Monocarboxylate Transporter 1 (MCT1) offering a unique opportunity for therapy. However, biochemical inhibitors of MCT1 have proven unsuccessful in clinical trials. In this study we present an alternative approach using 3-Bromopyruvate (3BP) to target MCT1 overexpressing PDACs. 3BP is a cytotoxic agent that is known to be transported into cells via MCT1, but its clinical usefulness has been hampered by difficulties in delivering the drug systemically. We describe here a novel microencapsulated formulation of 3BP (ME3BP-7), that is effective against a variety of PDAC cells in vitro and remains stable in serum. Furthermore, systemically administered ME3BP-7 significantly reduces pancreatic cancer growth and metastatic spread in multiple orthotopic models of pancreatic cancer with manageable toxicity. ME3BP-7 is, therefore, a prototype of a promising new drug, in which the targeting moiety and the cytotoxic moiety are both contained within the same single small molecule. One Sentence SummaryME3BP-7 is a novel formulation of 3BP that resists serum degradation and rapidly kills pancreatic cancer cells expressing high levels of MCT1 with tolerable toxicity in mice.

cancer biology↗

bioRxiv2023

Application of nanopore sequencing for accurate identification of bacterial colonies

Culture based detection remains to be one of the most reliable and acceptable techniques to detect extremely low quantity pathogens present in a sample. The process typically involves inoculating the sample on an agar plate to allow growth of the microorganisms to form colonies, followed by the identification of the individual colonies, commonly by DNA sequencing of a PCR-amplified targeted gene. Sanger method is often the default choice of sequencing as it offers affordable and accurate results for a single species. However, the technique could pose limitations in certain situations such as identification of multi-species microbial colonies. In this work, we compared the performance of Sanger sequencing with MinION nanopore sequencing in identifying bacterial colonies derived from bioaerosol samples. We conducted Sanger and nanopore sequencing of full-length 16S rRNA genes from seven bacterial colonies derived from bioaerosol samples and compared the outcome by alignment against NCBI 16S reference database. We found that for five out of seven colonies both techniques indicated the presence of the same bacterial genus. For one of the remaining colonies, a noisy Sanger electropherogram failed to generate a meaningful sequence, but nanopore sequencing identified it to be a mix of two bacterial genera Alkalihalobacillus and Kocuria. For the other remaining colony, the Sanger sequencing suggested Micrococcus with a clean electropherogram, however, the nanopore sequencing suggested the presence of an additional genus Paraburkholderia. Further corroborating these findings with mock multispecies colonies from pure bacterial DNA samples, we confirm that nanopore sequencing is comparable to the Sanger method in identifying colonies with single bacterial species but is the superior method in classifying individual bacterial components with their relative abundances in multispecies colonies. Our results suggest that nanopore sequencing could be advantageous over Sanger sequencing for colony identification in culture-based analysis of environmental samples such as bioaerosol where direct inoculation of the sample to culture plate might lead to formation of multispecies colonies.

microbiology↗

bioRxiv2022

Plasma Proteome Perturbation for CMV DNAemia in Kidney Transplantation

BackgroundCytomegalovirus (CMV) infection, either de novo or as reactivation after allotransplantation and chronic immunosuppression, is recognized to cause detrimental alloimmune effects, inclusive of higher susceptibility to graft rejection and substantive impact on chronic graft injury and reduced transplant survival. To obtain further insights into the evolution and pathogenesis of CMV infection in an immunocompromised host we evaluated changes in the circulating host proteome serially, before and after transplantation, and during and after CMV DNA replication (DNAemia), as measured by quantitative polymerase chain reaction (QPCR). MethodsLC-MS-based proteomics was conducted on 168 serially banked plasma samples, from 62 propensity score-matched kidney transplant recipients. Patients were stratified by CMV replication status into 31 with CMV DNAemia and 31 without CMV DNAemia. Patients had blood samples drawn at protocol times of 3- and 12-months post-transplant. Additionally, blood samples were also drawn before and 1 week and 1 month after detection of CMV DNAemia. Plasma proteins were analyzed using an LCMS 8060 triple quadrupole mass spectrometer. Further, public transcriptomic data on time matched PBMCs samples from the same patients was utilized to evaluate integrative pathways. Data analysis was conducted using R and Limma. ResultsSamples were segregated based on their proteomic profiles with respect to their CMV Dnaemia status. A subset of 17 plasma proteins was observed to predict the onset of CMV at 3 months post-transplant enriching platelet degranulation (FDR, 4.83E-06), acute inflammatory response (FDR, 0.0018), blood coagulation (FDR, 0.0018) pathways. An increase in many immune complex proteins were observed at CMV infection. Prior to DNAemia the plasma proteome showed changes in the anti-inflammatory adipokine vaspin (SERPINA12), copper binding protein ceruloplasmin (CP), complement activation (FDR=0.03), and proteins enriched in the humoral (FDR=0.01) and innate immune responses (FDR=0.01). ConclusionPlasma proteomic and transcriptional perturbations impacting humoral and innate immune pathways are observed during CMV infection and provide biomarkers for CMV disease prediction and resolution. Further studies to understand the clinical impact of these pathways can help in the formulation of different types and duration of anti-viral therapies for management of CMV infection in the immunocompromised host.

immunology↗

bioRxiv2022

Implications of Spike Protein Interactions with Zn-bound form of ACE2: A Computational Structural Study

The COVID-19 pandemic has generated a major interest in designing inhibitors to prevent SARS-CoV-2 binding on host cells to protect against infection. One promising approach to such research utilizes molecular dynamics (MD) to identify potential inhibitors that can prevent the interaction between spike (S) protein on the virus and angiotensin converting enzyme 2 (ACE2) receptor on the host cells. In these studies, many groups have chosen to exclude a zinc (Zn) ion bound to the ACE2 molecule which is critical for enzymatic activity. While the relatively distant location of Zn ion from the S protein binding site (S1 domain), combined with the difficulties in modeling this ion have motivated the decision of exclusion, Zn can potentially contribute to the structural stability of the entire protein, and thus, may have implications on spike protein interaction. In this study, we explored the effects of excluding Zn on the structural stability and binding free energy of the ACE2-S1 protein complex. We generated two versions of an experimentally-derived structure of the ACE2-S1 protein complex: one with Zn and one without. Examining the differences between these two complexes during MD simulation, we found that the Zn-bound complex exhibited greater instability at nearly all residues except for the interacting residues, which were more stable in the Zn-bound complex. Additionally, the Zn-bound complex had a stronger binding free energy at all internal dielectric constants greater than one. Since binding free energy is often used to score inhibitors performances, excluding Zn could potentially have implications on inhibitor selection and performance, both in the ACE2-S1 protein system and other protein complexes that include the Zn ion.

biophysics↗

bioRxiv2022

Perturbation of ATP6V0A1 as a Driver and Druggable Target for Renal Proximal Tubular Cellular Injury in Nephropathic Cystinosis

Understanding the unique susceptibility of the human kidney to pH dysfunction and injury in cystinosis is paramount to developing new therapies to preserve renal function. Renal proximal tubular epithelial cells (RPTECs) and fibroblasts isolated from patients with cystinosis were transcriptionally profiled. Lysosomal fractionation, immunoblotting, confocal microscopy, intracellular pH, TEM, mitochondrial stress test, and membrane integrity assays were performed for validation. CRISPR, CTNS -/- RPTECs were generated. Alterations in cell stress, pH, autophagic turnover, and mitochondrial energetics highlighted key changes in the vacuolar (V)-ATPases in patient-derived and CTNS-/- RPTECs. ATP6V0A1 was significantly downregulated in cystinosis and highly co-regulated with loss of CTNS. Correction of ATP6V0A1 rescued cell stress and mitochondrial function. Treatment of CTNS -/- RPTECs with antioxidants astaxanthin (ATX) induced ATP6V0A1 expression and improved autophagosome turnover and mitochondrial integrity. In conclusion, our exploratory transcriptional and in vitro cellular and functional studies confirm that loss of cystinosin in RPTECs, results in a reduction in ATP6V0A1 expression, with changes in intracellular pH, mitochondrial integrity, mitochondrial function, and autophagosome-lysosome clearance. The novel findings are ATP6V0A1s role in cystinosis-associated renal pathology and among other antioxidants, ATX specifically upregulated ATP6V0A1, improved autophagosome turnover or reduced autophagy and mitochondrial integrity. This is a pilot study highlighting a novel mechanism of tubular injury in cystinosis and requires further study in animal models to clarify its utility in clinical settings.

cell biology↗

bioRxiv2022

Circulatory exosomes from COVID-19 patients trigger NLRP3 inflammasome in endothelial cells

SARS-CoV-2 infection induces inflammatory response, cytokine storm, venous thromboembolism, coagulopathy, and multiple organ damage. Resting endothelial cells prevent coagulation, control blood flow and inhibit inflammation. However, it remains unknown how SARS-CoV-2 induces strong molecular signals in distant cells for immunopathogenesis. In this study, we examined the consequence of human endothelial cells (microvascular endothelial cells (HMEC-1) and liver endothelial cells (TMNK-1)) to exosomes from plasma of severe COVID-19 patients. We observed a significant induction of NLRP3, caspase-1 and IL-1{beta} mRNA expression in the endothelial cells following exposure to exosomes from plasma of COVID-19 patients as compared to that of healthy donors. Activation of caspase-1 was noted in the endothelial cell culture medium following exposure to the COVID-19 exosomes. Further, COVID-19 exosomes significantly induced mature IL-1{beta} secretion in the endothelial cell culture medium. Thus, our results demonstrated for the first time that exosomes from COVID-19 plasma trigger NLRP3 inflammasome in endothelial cells of distant organs.

immunology↗

bioRxiv2021

Effects of Cholesterol on the mechanism of fengycin, a biofungicide

Fengycins are a class of antifungal lipopeptides synthesized by the bacteria Bacillus subtilis, commercially available as the primary component of the agricultural fungicide Serenade(R). They are toxic to fungi, but far less to mammalian cells. One key difference between mammalian and fungal cell membranes is the presence of cholesterol only in the former; recent experimental work showed that the presence of cholesterol reduces fengycin-induced membrane leakage. (1) Since our previous all-atom and coarse-grained simulations (2, 3) suggested that aggregation of membrane-bound fengycin is central to its ability to disrupt membranes, we hypothesized that cholesterol might reduce fengycin aggregation. Here, we test this hypothesis using coarse-grained molecular dynamics simulations, with sampling enhanced via the weighted ensemble method. The results indicate that cholesterol subtly alters the size distribution for fengycin aggregates, limits the lateral range of their membrane disordering, and reduces the ability of aggregates to bend the membrane. Taken together, these phenomena may account for cholesterols affects on fengycin activity.

biophysics↗