Biology subjects

Jung, W.

Publications and source records attributed to Jung, W..

At least 19 recordsLinked to original sources

bioRxiv2026

COGNITIVE HETEROGENEITY AND AGING: AN AGE-INDEPENDENT CILIARY GENE PROGRAM TRACKS COGNITIVE RESILIENCE IN MICE

Cognitive decline with age is often viewed as inevitable, yet older animals show striking heterogeneity in functional trajectories, with many preserving cognitive integrity despite physiological decline. The biological basis of this resilience remains poorly understood, partly due to insensitive behavioral testing paradigms. Using an automated home-cage platform and hippocampal RNA sequencing, we integrated behavioral phenotyping with transcriptomic profiling to disentangle molecular programs linked to cognitive performance from chronological age. Behavioral data from 906 C57BL/6 mice across 129 standardized studies, trajectory-based modeling, variance-partitioned correlation, and stability-driven gene prioritization identified a transcriptional signature (271 genes) linked to cognitive state independent of age. Preserved cognition was associated with higher expression of genes governing ciliary structure and motility, neurite organization, and synaptic architecture, while impairment was associated with neuroimmune and metabolic-stress programs. A 38-gene cilia structural module score remained associated with resilience after controlling for age (partial rho = -0.81), with consistent effects across leave-one-out resampling. Because the constituent genes were selected on this same outcome, the module-level magnitude is not an unbiased effect-size estimate; recalibration against a null that reapplies the full selection procedure gave an empirical p of 0.026. This divergence emerged among genetically identical mice, indicating non-genetic, discrete hippocampal molecular signatures underlying individual differences. Cell-type attribution against the Allen Brain Cell Atlas localized the module predominantly to ependymal cells, with 27 of 38 genes ependymal-restricted (median detection 90.2% in ependymal cells versus 1.1% in CA1 glutamatergic neurons) and three genes (Dnah9, Dnai4, Kif9) also detected in CA1. The association was not attributable to ependymal tissue content: the module score was unrelated to Foxj1 expression (rho = -0.016) and the partial correlation was unchanged after adjustment for ependymal and choroid plexus marker panels, indicating that the module reflects how strongly the ciliary program is expressed rather than how many ependymal cells each sample contained. These findings support a conceptual shift: cognitive trajectories appear shaped by intrinsic molecular set points rather than by chronological age, with expression of a motile ciliary program at the cerebrospinal fluid interface, rather than the abundance of the cells carrying it, emerging as a candidate correlate of resilience. This approach offers a generalizable strategy for dissecting functional heterogeneity from aging and identifying pathways for hypothesis-driven tests of resilience across the lifespan.

animal behavior and cognition↗

bioRxiv2026

Antibody Correlates of Resilience to Staphylococcus aureus Disease and Recurrence in Children

Staphylococcus aureus remains a major global pathogen with no licensed vaccine and high recurrent infection burden, yet correlates of protection remain undefined. In a prospective pediatric cohort, we profiled 319 children spanning non-carriers, asymptomatic carriers, those with skin and soft tissue infection (SSTI), or invasive disease. We interrogated 182,149 antibody features, generating the most comprehensive S. aureus immune profiling dataset to date. Antibody responses increased with age, marked by expansion of IgG subclasses and Fc-receptor engagement. Asymptomatic carriage was associated with functional antibody profiles targeting conserved surface antigens and select toxins. Multivariate modeling robustly distinguished clinical phenotypes and identified high-value antigens associated with disease resilience. Protection from recurrent disease converged on enhanced Fc{gamma}R binding and antibody effector function. These findings nominate key antigen targets, and highlight anti-Hla neutralizing antibodies and functional antibodies to additional surface antigens that can be recapitulated through Fc engineering, informing next-generation vaccine and monoclonal antibody strategies.

immunology↗

bioRxiv2026

CA19-9 induces microenvironment remodeling in pancreatic ductal adenocarcinoma

Durable therapeutic efficacy remains a major barrier to improving outcomes for patients with pancreatic ductal adenocarcinoma (PDAC). An immunosuppressive tumor microenvironment (TME) is a hallmark of PDAC and has been demonstrated to be a dominant driver of therapeutic resistance. The aberrant glycan CA19-9 is prevalent in PDAC and drives tumor progression, but the paracrine mechanisms by which it contributes to TME remodeling are unknown. To address this, we mapped TME changes and performed functional analyses using a genetically engineered mouse model (GEMM) harboring KrasG12D mutation and inducible CA19-9 expression. Elevation of CA19-9 led to expansion of antigen-presenting cancer associated fibroblasts (apCAFs) and regulatory T cells (Tregs), which can drive immunosuppression. Antibody blockade of CA19 -9 resulted in significant restoration of normal histology and decreased apCAF and Treg populations. We dissected the paracrine signaling mechanisms that drive this TME remodeling in vitro using mouse and human organoid mono- and co-culture models as well as in vivo using GEMMs and syngeneic orthotopic transplantation models. CA19-9 induced IL1a and TGFb expression, reprogramming pancreatic mesothelial cells into apCAFs in vitro, which in turn directly ligated naive Cd4+ T cells resulting in Treg differentiation in co-cultures. Antibody blockade of IL1a and TGFb in mice led to reduced apCAF and Treg differentiation. We previously reported that CA19-9 modification of the secreted Fbln3 protein increased Egfr engagement and now find that the induction of IL1a and TGFb expression by CA19-9 is dependent on Fbln3 hyperactivation of EGFR signaling. Genetic depletion of Fbln3 led to reduced tumor progression and increased Cd8+ T cell infiltration in mice. Together these findings identify a previously unknown signaling axis driving immunosuppressive phenotypes in PDAC, uncovering multiple potential nodes to relieve the immunosuppressive pressures within the PDAC TME.

cancer biology↗

bioRxiv2026

Metabolic Salvage and Acyl-chain Remodeling Support Glycosphingolipid Synthesis with the PDAC Tumor Microenvironment

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy where metabolic homeostasis is maintained by tumor and stromal cells within the tumor microenvironment (TME). To better assess pathways supporting macromolecule biosynthesis in PDAC tumors, we apply 13C metabolic flux analysis (MFA) to slice cultures of treatment-naive human tumors and mouse models that retain the native TME. Glycans, lipid headgroups, and very long-chain fatty acids are the most dynamic metabolic pools, while long chain fatty acids, purines, and pyrimidines are predominantly salvaged locally in situ. We use targeted pharmacological modulators to highlight the importance of recycling pathways and metabolic redundancies which mitigate changes in lipid abundances. Finally, we leverage targeted lipid fluxomics and the distinct ganglioside and globoside profiles of tumor and stromal cells, respectively, to demonstrate the role of the lipid kinase PIKfyve in supporting ganglioside homeostasis via sialic acid and ceramide salvage. These data establish application of MFA to slice cultures of PDAC tumors as an effective approach for assessing metabolic mechanisms and therapeutic responses within an intact TME.

cancer biology↗

bioRxiv2026

Rejuvenation of the Aged Cerebrovascular System via Protein Corona-Guided Fusogenic Liposome Delivery

Brain vascular aging is increasingly recognized as a critical therapeutic target for age-related cognitive decline. Oxidative stress, bioenergetic dysfunction, and molecular damage play central roles in the progression of vascular aging, contributing to cerebrovascular dysfunction and impaired cognitive function. While naturally occurring polyphenols such as resveratrol (RSV) have demonstrated potential in mitigating aging-related pathologies, their poor bioavailability and limited brain targeting efficiency significantly constrain their therapeutic impact. As a result, high doses or advanced drug delivery strategies are necessary to achieve meaningful physiological effects. We introduce a novel nanocarrier system designed to enhance RSV delivery to the cerebral endothelium by leveraging the natural formation of an apolipoprotein E (ApoE)-enriched protein corona around fusogenic liposomes (FL) in vivo. These nanoparticles directly fuse with cytoplasmic cell membranes and thus evade endocytosis. We found that once in the circulation FL spontaneously acquire a protein corona, which is highly enriched in ApoE, a key ligand for brain endothelial low-density lipoprotein receptors (LDLR). Based on this observation, we engineered an ApoE-functionalized protein corona around FL (ApoE-FL) to systematically evaluate whether this mechanism could be exploited for targeted brain delivery. Following optimization and physicochemical characterization, the RSV-loaded liposomes were evaluated in vitro using human cerebral microvascular endothelial cells and in vivo C57BL/6 aged mice to assess their therapeutic potential. Both FL and engineered ApoE-FL liposomal delivery systems exhibited a strong affinity for endothelial cell membranes in vitro. The knockdown of the ApoE receptor, low-density lipoprotein receptor-related protein 1 (LRP1), significantly reduced liposomal docking. Microscopy analysis revealed that both ApoE-FL and non-functionalized FL directly fused with endothelial plasma membranes, thus bypassing intracellular organelles and minimizing lysosomal degradation. This suggests that the naturally formed ApoE corona in vivo may contribute to efficient cerebrovascular targeting, a property successfully replicated by the engineered ApoE corona strategy. In vivo biodistribution and kinetic studies demonstrated that especially ApoE-FL achieved enhanced brain-targeting efficiency, prolonged cerebrovascular retention, and extended targeting distance along the arteriovenous axis. This emphasizes that fusogenic liposomes effectively engage almost the entire microvascular network, including capillaries and post-capillary venules. Functionally, fusogenic liposome-delivered RSV improved blood-brain barrier (BBB) integrity, enhanced neurovascular coupling (NVC) responses, and promoted brain vascularization in aged mice. Single-cell RNA sequencing (scRNA-seq) revealed enhanced endothelial angiogenesis and barrier protective transcriptional profiles in cerebrovascular cells treated with ApoE-FL/RSV, suggesting a molecular basis for the observed vascular benefits. Liposomal RSV delivery achieved near-complete cerebrovascular and cognitive rejuvenation in aged mice applying a 2000-fold lower RSV dose than oral administration used as control sample. Thus, ApoE-FL liposomes exhibited exceptionally high delivery efficiency in deeper brain regions, further expanding their therapeutic potential. These findings underscore the importance of targeted drug delivery in optimizing therapeutic outcomes and establish ApoE-functionalized fusogenic liposomes as a promising strategy for mitigating brain vascular aging and cognitive decline. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/709925v1_ufig1.gif" ALT="Figure 1000"> View larger version (52K): org.highwire.dtl.DTLVardef@acad5borg.highwire.dtl.DTLVardef@a96e3borg.highwire.dtl.DTLVardef@18405aeorg.highwire.dtl.DTLVardef@90e349_HPS_FORMAT_FIGEXP M_FIG C_FIG

animal behavior and cognition↗

bioRxiv2026

Model-Driven Hybrid AI Framework for End-to-End Autonomous Decision-Making in Drug Development

Decision-making in drug development spans heterogeneous stages from molecular design to clinical optimization, yet computer-aided workflows across stages remain fragmented, limiting traceability from evidence-derived clinical questions to simulation scenarios and decision endpoints. We present a model-driven hybrid AI framework for end-to-end decision support that treats PICO (Participants, Intervention, Comparison, Outcome) as a machine-actionable specification to define scenarios and align endpoints across modules. Given a PICO-defined clinical question and a drug SMILES, the framework infers PBPK-ready parameters from structure, generates exposure via mechanistic PBPK simulation, and links exposure outputs to clinic-facing therapeutic drug monitoring (TDM) decision support using an open-source NLME-based Clinical Pharmacokinetic Consultant Service (CPCS). We additionally implement an LLM-based PICO extraction layer to structure clinical abstracts into P/I/C/O elements for systematic evidence ingestion. Results include backbone verification for DTI-guided intrinsic clearance prediction under fold-error bounds and PBPK trajectory plausibility, and external validation of the hybrid AI-PBPK pipeline showing substantial dispersion for several endpoints. An input-controlled comparison between PhysioSim and PK-Sim on N = 9 drugs yields similarly degraded accuracy under identical AI-predicted inputs, suggesting upstream parameter quality as a dominant constraint. For evidence ingestion, prompting-only PICO extraction achieves F1 of 0.687 on EBM-NLP and 0.552 on TB-PICO. For clinical utility, CPCS improves TDM performance over a PKS baseline on phenobarbital and vancomycin, reducing MAPE by approximately 26-60% depending on configuration. Overall, the framework provides a modular, traceable blueprint linking evidence-defined questions to exposure simulation and TDM decision support while preserving mechanistic interpretability. Future work will integrate outcome-aligned time-to-event modeling and federated learning to close the PICO-to-outcome loop and improve parameter inference under multi-site governance.

pharmacology and toxicology↗

bioRxiv2026

Real world data based evaluation of a novel target-mediated drug disposition approximation model

Target-mediated drug disposition (TMDD) models have been widely used to describe nonlinear pharmacokinetic profiles driven by high-affinity, low-capacity drug-target binding. A pTMDD model, derived by applying the Pade approximation of the quasi-steady-state (QSS) model (qTMDD) was previously proposed. Although pTMDD model showed a comparable estimation accuracy while maintaining computational efficiency, further validation in realistic clinical scenarios and comprehensive performance evaluations have been needed to assess its practical applicability. Here, we evaluated the pTMDD model using five clinical datasets and extended the previous study that focused on simulations. Using the full TMDD as a reference, the approximation models were compared in terms of the parameter estimation results (parameter estimates, relative standard error values and model diagnostics) and computational efficiency (estimation and bootstrap runtimes). The pTMDD model, previously validated in simulation settings, also preserved the estimation accuracy while reducing the computation time of the clinical data. Both pTMDD and qTMDD remained close to the full TMDD model, whereas Michaelis-Menten TMDD (mTMDD) model showed substantial discrepancies especially at low doses, including biased estimates for key TMDD-related parameters (e.g., kdeg, kint, krec, and kup) and higher objective function values. Moreover, pTMDD was faster than qTMDD in four of the five cases compared to the full TMDD. The time savings were particularly pronounced for larger datasets, supporting the computational efficiency of pTMDD. Q2PCONV, an R Shiny application that converts NONMEM code from qTMDD to pTMDD, was also developed, thereby making this new approximation more accessible to researchers. The findings support pTMDD as a practical alternative to existing TMDD approximation models. Author SummaryTarget-mediated drug disposition (TMDD) models describe a high-affinity, low-capacity binding between drug and its target. To avoid overparameterization, approximation models have been used. The two primary models are Michaelis-Menten model (mTMDD), which is accurate only at high doses, and Quasi-steady-state (qTMDD), which is accurate in wider ranges but requires longer runtime. We have proposed a new approximation model named pTMDD. Here, we evaluated pTMDD using five real clinical trial datasets to assess its practical usefulness. pTMDD produced parameter estimates closer to those from the full TMDD model and showed lower uncertainty than both the full TMDD and mTMDD models. In terms of computational efficiency, pTMDD reduced estimation time by an average of 11% and bootstrap time by an average of 6% relative to qTMDD across cases. In addition, we also developed an R shiny application to help researchers apply pTMDD in practice. Our work supports pTMDD as a practical and efficient tool for TMDD modeling in drug development.

pharmacology and toxicology↗

bioRxiv2025

A painless nerve growth factor variant uncouples nociceptive and neurotrophic TrkA signaling

Nerve growth factor (NGF) binding to the receptor tyrosine kinase, TrkA, drives neurotrophic signaling essential for neuronal development and survival. This interaction simultaneously drives peripheral pain, making this pathway an attractive but complicated therapeutic target for chronic pain. By integrating single-molecule microscopy, structural and electrophysiology analyses, with a human NGF variant, NGFpainless, which retains neurotrophic effects but abolishes pain, we delineate the molecular mechanisms that bias TrkA signaling towards neurotrophic functions without triggering nociception. We show that, unlike wild-type NGF, NGFpainless fails to sensitize TRPV1 channels to capsaicin, thus disengaging TrkA from the nociceptive pathway. We further show that this selective loss of nociceptive TrkA signaling by NGFpainless results from its reduced ability to activate PLC{gamma}1 and trigger calcium release compared to NGF, while still preserving the ERK and AKT signaling essential for neurotrophic functions. This biased signaling arises from reduced electrostatic complementarity at the TrkA:NGFpainless complex interface, which shortens the lifetime of this functional complex on native membranes. Mutations in TrkA that restore the electrostatic complementarity at the TrkA:NGFpainless interface eliminate biased signaling. This mechanistic understanding of TrkA binding by NGFpainless, and how it differs from NGF, will spur the development of two therapeutic classes of molecules - one that selectively suppresses nociceptive signaling while preserving neurotrophic functions in chronic pain, and another that enhances neurotrophic activity without evoking peripheral pain in neurodegenerative conditions.

neuroscience↗

bioRxiv2025

An integrated in silico-in vitro workflow for discovering high-affinity, selective antibodies to the KRAS(G12D)-MHC I complex

Antibodies that recognize peptide-loaded class I major histocompatibility complex (pMHC I) molecules could enable therapeutic targeting of intracellular oncogenic proteins, yet their discovery has been hampered by the small size of peptide antigens and allele-specificity. We describe an integrated in silico-in vitro workflow for generating high-affinity, selective antibodies to KRAS(G12D)10 presented by HLA-C*08:02, a clinically validated cancer neoantigen. In silico, multiple human antibody-derived variable fragments (Fvs) plausibly docked to the target pMHC were generated, followed by limited complementarity-determining region (CDR) sequence design. In vitro, CDR diversity was introduced at 3-4 positions per Fv to construct yeast surface display library for iterative selections. This workflow yielded antibodies with exclusive binding to KRAS(G12D)10/HLA-C*08:02 without cross-reactivity. Affinity maturation achieved nanomolar dissociation constants, and incorporation into chimeric antigen receptor T cells enabled specific activation against target-positive cells. This study establishes a practical design-to-function pipeline for TCR-like antibody discovery, and demonstrates the feasibility of therapeutic targeting against KRAS(G12D)-driven malignancies.

biochemistry↗

bioRxiv2025

Distinct antibody-based signatures and functionality distinguish latent and active pediatric tuberculosis

BackgroundTuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is among the leading causes of death from an infectious agent among children worldwide. Children represent a particularly vulnerable population due to the greater challenges in diagnosis and the higher risk of progression to severe forms of the disease. However, whether different pediatric outcomes relate to distinct immunologic responses remains incompletely understood. Emerging data suggest that Mtb-specific humoral immune responses represent a correlate of protection against Mtb both following natural infection and vaccination. MethodsTo determine if immune profiles can distinguish children across the spectrum from Mtb infection to TB disease, as well as children with TB from non-TB lower respiratory tract infection, we mapped the humoral immune response across a panel of 4 dozen Mtb antigens across children presenting with symptoms of active TB (ATB), children with evidence of latent TB infection (LTBI) and children exhibiting non-TB lower respiratory tract infection (non-TB LRTI). Using a custom Luminex assay, Mtb-specific antibody subclass/isotype, Fc receptor (FcR) binding profiles, and functions were profiled across the pediatric groups. FindingsA robust humoral immune response was observed in children with active TB compared to non-TB LRTI, marked by a strong IgA response, that exhibited high FcR binding. Conversely, children with LTBI uniquely elicited Mtb-specific antibodies with enhanced opsinophagocytic Fc{gamma}R2A binding, as well as a higher capacity to activate NK cells and neutrophils. InterpretationThere are significant differences in humoral immune profiles across the landscape of pediatric TB, potentially contributing to differential mycobacterial control, and highlighting biomarkers that could guide both diagnostic and therapeutic approaches. FundingUS National Institutes of Health.

immunology↗

bioRxiv2025

H2O2-induced astrocytic collagen triggers neuronal death via fucosylation-dependent glial barrier formation upon ischemic stroke

The cascade of molecular and cellular events leading to neuronal death after a focal ischemic stroke remains enigmatic. Although astrocytes form glial barriers that may protect surrounding tissue, how barriers develop and contribute to neuronal death is unclear. Here, we show that H2O2 induces astrocytic type I collagen (COL1)-production via miR-29-mediated post-transcriptional and fucosylation-dependent post-translational regulations, leading to integrin activation and neuronal death. In photothrombosis (PT)-induced cortical stroke model, PT triggered H2O2-surge, astrogliosis, glial barrier formation, COL1 expression, fibrotic scarring, altered N-glycosylation, neuronal loss, and neurological deficits. Remarkably, these effects were reversed by astrocyte-specific COL1 or FUT8 gene-silencing or treatment with KDS12025, an H2O2-decomposing peroxidase enhancer. KDS12025s neuroprotective effects were also recapitulated in non-human primate stroke model. These findings delineate a previously unrecognized astrocyte-driven mechanism in which oxidative stress induces COL1 production, promoting neuronal death, and position H2O2 and astrocytic COL1 and FUT8 as promising therapeutic targets for ischemic stroke.

neuroscience↗

bioRxiv2025

Long-term innovative potential of genetic research and its suppression

Long-term innovation depends not only on discovering new elements but also on facilitating new recombination at the time of their co-availability. This notion of combinatorial innovation raises the question about whether scientific exploration and industry research persist over similar time horizons to meet innovative opportunities. Here, we analyze about 20 million papers and US, Chinese, and European patents to compare the courses of scientific and industrial activities in genetic research, a domain of far-reaching societal importance. We observe that research on new genes has declined since the early 2000s, but the exploration of novel gene combinations remains active for biotechnology innovation. Yet, fields of highly practical or commercial focus are less likely to test novel gene combinations. Furthermore, industry R&D on each gene tends to decline earlier than scientific interest in that gene. After this decline of the industrial momentum, continuous scientific research still sustains exploratory and innovative opportunities, involving novel gene combinations, clinical trials, and technologically-impactful work. Based on a hypothetical scenario of over-aligned science and industry, we estimate that up to 42.2-74.4% of the combinational opportunities would be unexplored if scientific research becomes hindered due to industrys retreat. This study suggests the potential complementary roles of scientific and industrial research with different temporal modes in innovation cycles, calling for balanced policies to foster innovation ecosystems.

scientific communication and education↗

bioRxiv2024

Acute infectious mononucleosis generates persistent, functional EBNA-1 antibodies with high cross-reactivity to alpha crystalline beta

Epstein-Barr Virus (EBV) infects over 95% of the worlds population and is the most common cause of infectious mononucleosis (IM). Epidemiologic studies have linked EBV with certain cancers or autoimmune conditions, including multiple sclerosis (MS). Recent studies suggest that molecular mimicry between EBV proteins, particularly EBV nuclear antigen 1 (EBNA-1), and self-proteins is a plausible mechanism through which EBV infection may contribute to the development of autoimmune disorders. We used a systems immunology approach to investigate the magnitude, specificity, and functional properties of EBNA-1 specific antibodies in a cohort of 97 young adults with IM from presentation through 1-year post-primary infection compared to a control cohort of EBV-seropositive individuals. Levels of EBNA-1 specific IgG1 and IgG3 binding antibodies increased over the course of infection. EBNA-1 antibodies capable of mediating antibody-dependent cellular phagocytosis (ADCP) and antibody-dependent complement deposition (ADCD) were detected at or after 6 months. Binding and ADCP- and ADCD-leveraged antibodies primarily targeted a region of EBNA-1 known to elicit cross-reactive antibodies to several self-peptides in individuals with MS. Significantly higher binding and ADCD-active antibodies targeting EBNA-1 were observed in individuals with at least one HLA-DRB1*15:01 allele, a known genetic risk factor for MS; Importantly, high levels of antibodies capable of binding alpha crystalline beta (CRYAB) and mediating complement deposition were detected at 6 months and 1-year following IM; CRYAB antibodies were resistant to denaturing forces, indicating an affinity matured response. Blocking experiments confirmed that CRYAB antibodies were cross-reactive with EBNA-1. Altogether, these results demonstrate that high levels of functional antibodies targeting EBNA-1 are generated in early EBV infection, some of which are cross-reactive with CRYAB. Further investigation is warranted to determine how these antibody responses may contribute to the subsequent development of MS.

immunology↗

bioRxiv2024

Back-to-the-future motion analysis using machine intelligence predicts the potential risk of mood disorders

Motion encodes emotional value. Decoding the hidden information within the complexity and randomness of motion may aid in the early diagnosis and prevention of mood disorders. In this study, we utilized machine intelligence to predict the risk of mood disorders by analyzing random motion patterns in mice. The support vector machine, trained on motion data collected before chronic social defeat stress (CSDS), predicted a significant correlation between these data and the degree of CSDS-induced social avoidance. Unsupervised clustering revealed key motion biomarkers of stress susceptibility, accounting for approximately 70% of the onset of social avoidance in a new group of mice before exposure to CSDS. These findings suggest that motion analysis using machine intelligence could provide a non-invasive approach for predicting the risk of mood disorders.

animal behavior and cognition↗

bioRxiv2024

Limited O-specific polysaccharide (OSP)-specific functional antibody responses in young children with Shigella infection in Bangladesh

Shigellosis is the second leading cause of diarrheal death in children younger than five years of age globally. At present, there is no broadly licensed vaccine against shigella infection. Previous vaccine candidates have failed at providing protection for young children in endemic settings. Improved understanding of correlates of protection against Shigella infection and severe shigellosis in young children living in endemic settings is needed. Here, we applied a functional antibody profiling approach to define Shigella-specific antibody responses in young children versus older individuals with culture-confirmed shigellosis in Bangladesh, a Shigella endemic area. We analyzed Shigella-specific antibody isotypes, FcR binding and antibody-mediated innate immune cell activation in longitudinal serum samples collected at clinical presentation and up to 1 year later. We found that higher initial Shigella O-specific polysaccharide (OSP)-specific and protein-specific IgG and Fc{gamma}R binding levels correlated with less severe disease regardless of patient age, but that individuals under 5 years of age developed a less prominent class switched, FcR-binding, functional and durable antibody response against both OSP and protein Shigella antigens than older individuals. Focusing on the largest cohort, we found that functional S. flexneri 2a OSP-specific responses were significantly induced only in individuals over age 5 years, and that these responses promoted monocyte phagocytosis and activation. Our findings suggest that in a Shigella endemic region, young children with shigellosis harbor a functional antibody response that fails to maximally activate monocytes; such a response may be important in facilitating subsequent innate cell clearance of Shigella, especially via recruitment and activation of polymorphonuclear cells capable of directly killing Shigella.

immunology↗

bioRxiv2024

Compartment-Specific Antibody Correlates of Protection to SARS-CoV-2 Omicron in Macaques

Antibodies represent a primary mediator of protection against respiratory viruses such as SARS-CoV-2. Serum neutralizing antibodies (NAbs) are often considered a primary correlate of protection. However, detailed antibody profiles including characterization of antibody functions in different anatomic compartments are not well understood. Here we show that antibody correlates of protection against SARS-CoV-2 challenge are different in systemic versus mucosal compartments in rhesus macaques. In serum, neutralizing antibodies were the strongest correlate of protection and were linked to Spike-specific binding antibodies and other extra-neutralizing antibody functions that create a larger protective network. In contrast, in bronchiolar lavage (BAL), antibody-dependent cellular phagocytosis (ADCP) proved the strongest correlate of protection rather than NAbs. Within BAL, ADCP was linked to mucosal Spike-specific IgG, IgA/secretory IgA, and Fc{gamma}-receptor binding antibodies. Our results support a model in which antibodies with different functions mediate protection at different anatomic sites. The correlation of ADCP and other Fc functional antibody responses with protection in BAL suggests that these antibody responses may be critical for protection against SARS-CoV-2 Omicron challenge in mucosa.

immunology↗

bioRxiv2023

A "through-DNA" mechanism for metal uptake-vs.-efflux regulation

Transition metals like Zn are essential for all organisms including bacteria, but fluctuations of their concentrations in the cell can be lethal. Organisms have thus evolved complex mechanisms for cellular metal homeostasis. One mechanistic paradigm involves pairs of transcription regulators sensing intracellular metal concentrations to regulate metal uptake and efflux. Here we report that Zur and ZntR, a prototypical pair of regulators for Zn uptake and efflux in E. coli, respectively, can coordinate their regulation through DNA, besides sensing cellular Zn2+ concentrations. Using a combination of live-cell single-molecule tracking and in vitro single-molecule FRET measurements, we show that unmetallated ZntR can enhance the unbinding kinetics of Zur from DNA by directly acting on Zur-DNA complexes, possibly through forming heteromeric ternary and quaternary complexes that involve both protein-DNA and protein-protein interactions. This through-DNA mechanism may functionally facilitate the switching in Zn uptake regulation when bacteria encounter changing Zn environments; it could also be relevant for regulating the uptake-vs.-efflux of various metals across different bacterial species and yeast.

biophysics↗

bioRxiv2023

A molecularly defined and spatially resolved cell atlas of the whole mouse brain

In mammalian brains, tens of millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells in the brain have so far hindered our understanding of the molecular and cellular basis of its functions. Recent advances in spatially resolved single-cell transcriptomics have allowed systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1-3. However, these approaches have only been applied to a few brain regions1-11 and a comprehensive cell atlas of the whole brain is still missing. Here, we imaged a panel of >1,100 genes in [~]8 million cells across the entire adult mouse brain using multiplexed error-robust fluorescence in situ hybridization (MERFISH)12 and performed spatially resolved, single-cell expression profiling at the whole-transcriptome scale by integrating MERFISH and single-cell RNA-sequencing (scRNA-seq) data. Using this approach, we generated a comprehensive cell atlas of >5,000 transcriptionally distinct cell clusters, belonging to [~]300 major cell types, in the whole mouse brain with high molecular and spatial resolution. Registration of the MERFISH images to the common coordinate framework (CCF) of the mouse brain further allowed systematic quantifications of the cell composition and organization in individual brain regions defined in the CCF. We further identified spatial modules characterized by distinct cell-type compositions and spatial gradients featuring gradual changes in the gene-expression profiles of cells. Finally, this high-resolution spatial map of cells, with a transcriptome-wide expression profile associated with each cell, allowed us to infer cell-type-specific interactions between several hundred pairs of molecularly defined cell types and predict potential molecular (ligand-receptor) basis and functional implications of these cell-cell interactions. These results provide rich insights into the molecular and cellular architecture of the brain and a valuable resource for future functional investigations of neural circuits and their dysfunction in diseases.

neuroscience↗