Biology subjects

Lynch, D.

Publications and source records attributed to Lynch, D..

9 recordsLinked to original sources

bioRxiv2026

Time-Resolved Single-Cell Atlas Reveals Early Endothelial Activation and Stage-Dependent Immune-Stromal Communication in HFpEF

BackgroundHeart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome associated with metabolic stress, hypertension, systemic inflammation, and microvascular dysfunction. Early cell-type-specific events and intercellular communication programs that accompany disease onset and progression remain poorly defined. MethodsWe performed a longitudinal study of HFpEF progression in high-fat diet (HFD)+L-NAME mice at control/baseline (0 weeks, 0w/Ctrl), early (1w), intermediate (4w), and established (8w) stages. Metabolic, hemodynamic, exercise, echocardiographic, and single-cardiomyocyte function were assessed. Cardiac non-cardiomyocytes (non-CMs) were profiled by single-cell RNA sequencing (scRNA-seq), with bulk RNA-seq for tissue-level comparison. Endothelial remodeling was assessed in an L-NAME-independent HFD plus mild transverse aortic constriction model (HFD+mTAC) and a published human HFpEF single-nucleus RNA-seq cohort. An endothelial-macrophage adhesion assay tested whether HFpEF-mimic stress promotes endothelial activation and macrophage adhesion. ResultsIn the HFD+L-NAME model, metabolic dysfunction, hypertension, reduced exercise tolerance, abnormal diastolic filling with preserved ejection fraction, and altered cardiomyocyte calcium handling were detected by 1w and persisted through 8w. Bulk RNA-seq showed progressive remodeling, with limited change between 8w and 12w, guiding scRNA-seq timepoint selection. scRNA-seq of 94,848 cardiac non-CMs identified nine major populations with stage-dependent remodeling. Endothelial cells (ECs) were recovered in high proportion and showed an early, pronounced transcriptional response, with inflammatory, adhesion, interferon-response, migratory, and vascular-remodeling programs emerging by 1w. Related EC activation signatures were observed in HFD+mTAC and human HFpEF data. Functionally, HFpEF-mimic stress increased adhesion and chemokine expression in human ECs and enhanced macrophage adhesion. Fibroblast matrix remodeling occurred at later stages, while macrophages progressively shifted toward inflammatory states. CellChat suggested stage-dependent communication remodeling from early endothelial-immune interactions toward later macrophage-fibroblast crosstalk. ConclusionTime-resolved scRNA-seq reveals coordinated, stage-dependent remodeling of the cardiac microvascular and interstitial microenvironment during HFpEF progression. Early endothelial activation emerges before later fibroblast matrix remodeling and inflammatory macrophage remodeling, identifying candidate cell states and signaling pathways for future mechanistic investigation. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSO_LIThis study provides a time-resolved single-cell atlas of the cardiac non-cardiomyocyte compartment across baseline, early, intermediate, and established stages of HFpEF progression, rather than a single late-stage snapshot. C_LIO_LIEndothelial cells exhibit early inflammatory, adhesion, interferon-response, and vascular-remodeling programs within the first week of disease, preceding the later predominance of fibroblast matrix remodeling and inflammatory macrophage remodeling. C_LIO_LIThis endothelial activation signature is supported across two mechanistically distinct HFpEF mouse models and aligns with endothelial inflammatory and vascular-remodeling programs in human HFpEF myocardium, supporting its translational relevance. C_LI What Are the Clinical Implications?O_LIEarly endothelial activation may represent a targetable stage of HFpEF pathogenesis that arises before more established structural and fibrotic remodeling. C_LIO_LITherapeutic strategies aimed at limiting endothelial inflammatory activation or endothelial-immune interactions may help attenuate downstream vascular, immune, and stromal remodeling in HFpEF. C_LIO_LIThese findings provide a preclinical foundation for future longitudinal human studies testing whether early endothelial activation can serve as a biomarker, therapeutic target, or disease-staging feature in HFpEF. C_LI

cell biology↗

bioRxiv2026

Large language model inference of macromolecular complex composition via model consensus and experimental data integration

Large language models (LLMs) are poised to reshape how biologists retrieve specialized knowledge at scale. Yet their performance on deep, domain-specific queries is poorly defined because much biological information resides in structured databases or large experimental datasets rather than in a free text format. One such gap in cellular biology lies in identifying major macromolecular complexes, conserved biological units essential to many cellular processes. Cataloging large complexes, such as the ribosome or RNA polymerase, along with their constituent genes, presents a significant challenge for LLMs because of their tendency to hallucinate and to produce incomplete or inconsistent lists of components. Here, we systematically evaluate six state-of-the-art LLMs on the task of retrieving the gene components of 91 protein complexes and develop an integrative framework that combines LLM output consensus with experimental multi-omics data to reconcile and filter model responses. We found that two extensions of a basic single-LLM baseline, (i) aggregating LLM outputs into a consensus and (ii) integrating LLM predictions with the experimental data, each improved retrieval accuracy. Furthermore, a consensus of LLM outputs integrated with the incomplete experimental data using a graph-theoretic approach achieved the highest accuracy (F1 score of 82.5%), compared to the best stand-alone singe LLM (F1 score of 76.4%). These results show that optimized integration of predictions from multiple LLMs and high-throughput experimental data can support scalable, semi-automated curation of specialized biological resources, providing a general template for benchmarking and deploying LLMs for the structured knowledge retrieval tasks in molecular biology.

bioinformatics↗

bioRxiv2026

Human serum triglycerides promote Staphylococcus aureus biofilm formation and antibiotic tolerance

Biofilm formation and antibiotic tolerance are major contributors to the persistence of Staphylococcus aureus infections, yet how the host environment affects these phenotypes remains poorly understood. Here, we show that incubation in human serum primes S. aureus to form robust biofilms and tolerate vancomycin and daptomycin, last resort antibiotics for the treatment of antibiotic-resistant staphylococcal infections. Mechanistically, we demonstrate that the staphylococcal Geh lipase is essential for serum-induced biofilm formation by liberating glycerol from host lipids, which is then used to promote increased synthesis of D-alanylated wall teichoic acids, driving biofilm development. Inhibition of the Geh lipase or wall teichoic acid synthesis markedly reduces biofilm formation and restores antibiotic susceptibility, highlighting clinically achievable strategies to inhibit host-induced biofilm formation and prevent the associated antibiotic tolerance. Together, our findings reveal a host-driven mechanism of biofilm-associated antibiotic tolerance in S. aureus and provide rational targets for therapeutic intervention.

microbiology↗

bioRxiv2025

Automation of high-throughput arrayed mammalian cell line cultivation

Cell culture automation has traditionally been limited to basic tasks at low throughput, which are insufficient for passaging rapidly proliferating cell lines or for generating stable clonal lines. To address unmet needs, this study implemented a Biomek i7 Hybrid automated workstation, integrated with peripheral instruments and coordinated by SAMI EX software, to enable automated, high throughput mammalian cell culture workflows. The workflows support cell density monitoring, arrayed passaging, sample cherry-picking, plate reformatting, cell density normalization, and cryopreservation in 96-well plates. Integration with the CloneSelect imager allows rapid confluency monitoring and monoclonality assessment (<100 sec per plate). Cell passaging and density normalization require 32 minutes for one plate and 61 minutes for two plates. Workflow consistency was demonstrated across multiple cell lines and biological replicates, with wells showing comparable confluency within three standard deviations, lower coefficient of variation, and substantially narrower interquartile ranges after a single cell passage and density normalization. Four automation pipelines, including monoclonality screening, cell passaging and cherry-picking, density normalization, and cryopreservation, collectively enable clonal line establishment. Depending on scale, one to eight 384-well plates were processed in 69 to 355 minutes, yielding an average of 35 clonal lines per plate suitable for downstream genomic DNA sequence confirmation.

cell biology↗

bioRxiv2025

Detection of a Unique Unfolded p53 Conformation (U-p53AZ) in Tissue of Alzheimers Disease Patients

INTRODUCTIONAlzheimers Disease (AD) is a major public health challenge. An AD-specific unfolded form of the p53 protein was identified (U-p53AZ) and data from animal studies suggests it colocalizes with pTau, in neurofibrillary tangles (NFT) METHODSBrain samples of patients with AD, cognitively unimpaired non-AD, and with fronto-temporal dementia (FTD) are being tested, comparing the pattern of U-p53AZ accumulation (using the antibody 2D3A8, developed by Diadem SpA) with accumulation of pTau, beta-amyloid, and TDP-43. RESULTSU-p53AZ accumulates in brain samples from AD, colocalizes with pTau in the NFT, with a small degree of accumulation in neuritic plaques (NP). The intensity of staining correlates with the pTau staining and Braak staging. No staining is observed in samples from cognitively unimpaired non-AD and FTD. DISCUSSIONThis study provides further support to the hypothesis that U-p53AZ is a player in AD pathology, in link with pTau accumulation and Braak staging.

molecular biology↗

bioRxiv2025

Machine learning of molecular dynamics simulations provides insights into modulation of viral capsid assembly

An effective approach in the development of novel antivirals is to target the assembly of viral capsids using capsid assembly modulators (CAMs). CAMs targeting hepatitis B virus (HBV) have two major modes of function: they can either accelerate nucleocapsid assembly, retaining its structure, or misdirect it into non-capsid-like particles. Previous molecular dynamics (MD) simulations of early capsid-assembly intermediates showed differences in protein conformations for apo and bound states. Here, we have developed and tested several classification machine learning (ML) models to better distinguish between apo-tetramer intermediates and those bound to accelerating or misdirecting CAMs. Models based on tertiary structural properties of the Cp149 tetramers and their inter-dimer orientation, as well as models based on direct and inverse contact distances between protein residues, were tested. All models distinguished the apo states and the two CAM-bound states with high accuracy. Furthermore, tertiary structure models and residue-distance models highlighted different tetramer regions as important for classification. Both models can be used to better understand structural transitions that govern the assembly of nucleocapsids and to assist the development of more potent CAMs. Finally, we demonstrate the utility of classification ML methods in comparing MD trajectories and describe our ML approaches, which can be extended to other systems of interest. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/637202v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@b2a910org.highwire.dtl.DTLVardef@1798a02org.highwire.dtl.DTLVardef@539b80org.highwire.dtl.DTLVardef@105f0aa_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2024

The First Comprehensive Description of the Platelet Single Cell Transcriptome

Platelets are derived from megakaryocytes, either in peripheral or pulmonic circulation. The transcriptome of megakaryocytes has been studied, while the platelet transcriptome is thought to be a reflection of their parent cells; it has not yet been investigated. Although platelets lack nuclei, they inherit RNA from their parent megakaryocytes, while only about 10% of them are believed to contain enough RNA for meaningful analysis. This study explores the potential of single-cell RNA sequencing to analyze the platelet transcriptome, aiming to expand our understanding of platelets beyond their traditional role in coagulation. Using acridine orange staining and antibody-based sequencing, we successfully sequenced RNA from seven healthy donors. Results revealed significant heterogeneity in gene expression, with common platelet markers, such as ITGA2B and GP1B, being less abundant than expected. Interestingly, immune markers associated with lung megakaryocytes were not strongly represented in peripheral platelets. Comparison with current algorithms for cell identification suggests that platelets are often misclassified as other blood cell types, highlighting limitations of existing pipelines in platelet annotation. This misclassification may have led to misrepresentation of platelet transcriptomics in previous studies. These findings underscore the need for tailored sequencing methods to accurately profile platelets and set the foundation for further exploration of platelet biology and immune function, potentially opening avenues for therapeutic interventions in immune modulation, drug delivery, and the use of platelets as disease biomarkers in cancer and other conditions. Key PointsPlatelet single cell sequencing can be implemented with appropriate technical refinements to ensure optimal isolation without exogenous activation. In comparison to bulk sequencing techniques, single cell analysis affords the ability to exclude contaminating cells enabling examination of the authentic platelet transcriptome. This is critically important as contaminating cells contain far more RNA ultimately skewing results of transcriptomic analysis. Most platelets do not contain significant levels of commonly expected transcripts such as ITGA2B, GP1B, TREML1. In the context of recent data, our single cell transcriptomic data supports the intradividual and interindividual heterogeneity of the platelet transcriptome. The lung megakaryocyte signature is not disguisable in peripheral platelets. Further studies are needed to understand sources of RNA within platelets and the impact of the platelet microenvironment. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=145 SRC="FIGDIR/small/618506v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@556339org.highwire.dtl.DTLVardef@1e543c4org.highwire.dtl.DTLVardef@c41cb5org.highwire.dtl.DTLVardef@138d779_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOVisual abstractC_FLOATNO C_FIG

bioinformatics↗

bioRxiv2021

SARS-CoV-2 spike opening dynamics and energetics reveal the individual roles of glycans and their collective impact

The trimeric spike (S) glycoprotein, which protrudes from the SARS-CoV-2 viral envelope, binds to human ACE2, initiated by at least one protomers receptor binding domain (RBD) switching from a "down" (closed) to an "up" (open) state. Here, we used large-scale molecular dynamics simulations and two-dimensional replica exchange umbrella sampling calculations with more than a thousand windows and an aggregate total of 160 {micro}s of simulation to investigate this transition with and without glycans. We find that the glycosylated spike has a higher barrier to opening and also energetically favors the down state over the up state. Analysis of the S-protein opening pathway reveals that glycans at N165 and N122 interfere with hydrogen bonds between the RBD and the N-terminal domain in the up state, while glycans at N165 and N343 can stabilize both the down and up states. Finally we estimate how epitope exposure for several known antibodies changes along the opening path. We find that the BD-368-2 antibodys epitope is continuously exposed, explaining its high efficacy.

biophysics↗

bioRxiv2021

ACE2 glycans preferentially interact with the RBD of SARS-CoV-2 over SARS-CoV

We report a distinct difference in the interactions of the glycans of the host-cell receptor, ACE2, with SARS-CoV-2 and SARS-CoV S-protein receptor-binding domains (RBDs). Our analysis demonstrates that the ACE2 glycan at N90 may offer protection against infections of both coronaviruses, while the ACE2 glycan at N322 enhances interactions with the SARS-CoV-2 RBD. The interactions of the ACE2 glycan at N322 with SARS-CoV RBD are blocked by the presence of the RBD glycan at N357 of the SARS-CoV RBD. The absence of this glycosylation site on SARS-CoV-2 RBD may enhance its binding with ACE2.

biophysics↗