Biology subjects

Cohen, R.

Publications and source records attributed to Cohen, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Predicting VHH-Fc Developability from Large-Scale IgG Data

The VHH-Fc antibody scaffold is an emerging therapeutic modality. No public large-scale, standardized developability VHH-Fc dataset exists. Filling that gap, we introduce GDPa5, a 160-member VHH-Fc library profiled across 10 biophysical assays on the PROPHET-Ab platform. Cross format models trained on the developability properties of 559 IgGs outperformed intra-format models trained on GDPa5 alone, which is an advantage driven by the larger scale of standardized IgG data rather than by format. The most accurately predicted properties were heparin binding (HAC, Spearman {rho}=0.82), hydrophobicity (HIC, {rho}=0.63), and self-association (AC-SINS, {rho}=0.62), all of which are largely governed by antibody surface properties. Tabular neural networks (TabICLv2, TabPFN v2.5), applied here for the first time to antibody developability prediction, outperformed conventional modeling approaches. Adding experimental HIC and HAC measurements as model inputs improved prediction of the more complex polyreactivity liability (PR-CHO, {Delta}{rho} = +0.10), supporting a tiered assay strategy that extends predictive performance while limiting experimental burden. We demonstrate through this work that IgG-trained models are a practical, data-efficient starting point for VHH-Fc developability prediction.

biophysics↗

bioRxiv2026

Quantifying the mechanisms of vaccine-induced serotype replacement in Streptococcus pneumoniae using genome-informed modelling

Streptococcus pneumoniae is a colonizer of the childs nasopharynx and a leading cause of invasive pneumococcal disease (IPD). Despite widespread use of pneumococcal conjugate vaccines, recent rebounds in IPD incidence have coincided with serotype replacement. Whether this phenomenon is driven by the replacement of serotypes within lineages or the replacement of the lineages themselves is unclear. Here, we quantified the relative contribution of these two mechanisms to serotype replacement in carriage and their consequences for IPD. We combined nationwide longitudinal surveillance of carriage and IPD in children from 2002 to 2023 with whole-genome sequencing. Observed lineage-specific carriage rates across PCV-related periods were fitted with polynomial logistic regression and compared with two counterfactual scenarios, each isolating one mechanism with: (i) fixed serotype composition within varying lineages and (ii) serotype shifts within fixed lineage carriage rates over time. Carriage dynamics were consistent with an 82% contribution of serotype shifts within persistent lineages. Estimates of serotype-specific IPD incidence derived from this predominant scenario correlated with observed IPD trends. These findings quantify the dominant role of serotype replacement within persistent lineages, disentangling the vaccine-driven adaptive history of S. pneumoniae.

microbiology↗

bioRxiv2026

Decoding Bispecific Antibody Developability: Design Rules and Predictive Models from a 160-Member Library

Bispecific antibodies deliver functional outcomes that monospecific antibodies cannot, yet emergent self-association, polyreactivity, and aggregation often degrade their developability relative to their parental arms. Whether bispecific developability inherits from the parents or is driven by the format has not been tested at scale. We characterized 160 bispecific antibodies and their 65 parental arms on a uniform knobs-into-holes CrossMab IgG1 scaffold across 10 assays on the PROPHET-Ab high-throughput platform. Bispecific developability separates into three classes of inheritance. Hydrophobicity and surface charge inherit cleanly from the parents (Spearman {rho} {approx} 0.85 to 0.95), so parental-level screening predicts bispecific fate. Self-association and polyreactivity inherit partially ({rho} {approx} 0.60 to 0.88), with mechanistically interpretable emergent outliers driven in part by Fv-Fv charge complementarity and a parental biophysical ceiling on the hydrophobicity (HIC) by surface-charge (HAC) plane. Thermostability is poorly predicted from parental antibodies ({rho} < 0.4), so it requires bispecific-level testing. The class framework yields actionable selection rules: triage hydrophobicity and charge at the parental level, avoid pairing two high-HIC x high-HAC arms, pair opposite-sign Fv charges to suppress self-association but re-validate at the formulation buffer, and measure thermostability on the bispecific itself. This work charts a tractable path from monospecific sequence to bispecific developability prediction. SignificanceBispecific antibodies are a fast-growing therapeutic class, yet the rational design of well-behaving bispecific antibodies from validated monospecific antibody building blocks remains challenging. A key bottleneck is the lack of comprehensive, high-quality public datasets linking parental antibody developability properties to corresponding bispecific antibody developability properties. We address this gap by releasing a dataset comprising 160 bispecific antibodies and the 65 parental monospecific antibodies profiled in 10 developability assays. The data show that bispecific antibody developability is complex. Some properties are easily predictable from the parents, whereas others emerge in the bispecific format or from the bispecific format itself. The factors that govern each property can be identified empirically and used to make practical selection decisions. The mechanistic explanations and predictive models reported here establish a compact set of actionable rules. Together, they define a framework for using computational pipelines to convert monospecific antibodies into bispecific antibodies with drug-like developability properties, enabling faster and more effective generation of high-quality bispecific antibodies for diverse therapeutic applications.

biophysics↗

bioRxiv2026

Dependencies in heterogeneous, lineage plastic patient-derived prostate cancer organoids revealed through integrated single-cell multiomics and CRISPR screening

Lineage plasticity and tumor heterogeneity limit the effectiveness of targeted therapies, yet the functional dependencies used to nominate therapeutic targets are often derived from homogeneous systems that fail to capture this complexity. Here, we establish a framework to resolve state-specific genetic vulnerabilities by integrating single-cell multiomics (RNA and ATAC) with pooled CRISPR-Cas9 screening across a large panel of patient-derived organoids (PDOs) from castrate-resistant prostate cancer (CRPC) and neuroendocrine prostate cancer (NEPC). We generate a single-cell multiome atlas spanning >190,000 cells across 22 PDOs, defining seven lineage states--including intermediate and plastic populations not resolved by bulk profiling--and demonstrate that these lineage programs robustly classify independent transcriptomic datasets from prostate cancer patient tumors. By systematically coupling this atlas to subtype-resolved CRISPR screens, we construct a functional dependency map linking cell state in heterogeneous 3D human tumor models. We show that intratumoral heterogeneity fundamentally reshapes the interpretation of gene essentiality, whereby gene-level depletion reflects the composite behavior of co-existing subpopulations, and identify a general principle in which resistant "limiting" populations disproportionately determine aggregate fitness effects. This framework reveals both canonical and previously unrecognized lineage-restricted dependencies within highly plastic tumor and NEPC states, including a therapeutically targetable dependency on the aryl hydrocarbon receptor (AHR) in a novel hybrid stem-like/ASCL1 population. Together, these data establish an extensive multi-dimensional prostate cancer resource, identify novel lineage-resolved biology, and provide a generalizable strategy for interpreting functional genomics in heterogeneous human tumors.

cancer biology↗

bioRxiv2026

The MBW complex regulates volatiles in petunia flowers: EOBV interacts with AN1 to suppress biosynthesis of phenylpropenes

Pigment production in petunia is regulated by the bHLH AN1 and the WDR protein AN11, which together with interchangeable MYBs form the MYB-bHLH-WDR (MBW) complex. Pigments and scent are interlinked flower traits, produced via the phenylpropanoid pathway. However, involvement of the MBW complex in regulating floral scent has not been demonstrated. TRV-based suppression of either AN1 or AN11 led to an increase in volatile emission, indicating that they are involved in negative regulation of this trait. Yeast two-hybrid and in-planta pairwise and three-way protein-protein interaction assays revealed that EMISSION OF BENZENOIDS V (EOBV) is a component of the MBW complex. Headspace and internal pool analyses of flowers from eobv-knockout lines, generated using a viral-based CRISPR/Cas9 system, revealed that EOBV fine-tunes volatile production: phenylpropene levels increased while those of benzenoids and phenylpropanoid-related compounds decreased. Accordingly, transcript levels of C4H, directing carbon flux to phenylpropenes, and ADT3 were significantly elevated in eobv flowers, along with decreases in PAAS and BSMT. EOBV is heat-responsive and under a high-temperature regime, in addition to its involvement in scent production, it affected flower development by mitigating reduction of flower size. EOBVs participation in the MBW complex that regulates volatiles and anthocyanins reveals an intriguing molecular link between these showy traits and flower development.

plant biology↗

bioRxiv2025

Identification and optimization of trans-species reactive TfR1-binding VHH as tools for drug delivery across the blood brain barrier

The blood-brain barrier (BBB) is a major obstacle for delivering therapeutic agents to the central nervous system (CNS), posing significant challenges for treating neurological disorders. Among current strategies to improve brain drug exposure, hijacking physiological pathways involved in receptor-mediated transcytosis (RMT) has emerged as a promising strategy. While targeting transferrin receptor 1 (TfR1) is widely explored, many TfR1-antibodies lack cross-species reactivity, limiting translational development. In the present study, we identified and characterized camelid-derived single-domain antibodies (VHHs) with robust cross-reactivity to rodent, rhesus monkey, and human TfR1. Epitope mapping of the VHH revealed a novel binding site at the interface of the TfR1 dimer. When fused to a human IgG1 Fc domain, these VHHs, as monomers or homodimers, were efficiently internalized by engineered CHO cells and brain endothelial cells expressing TfR1 from different species. Systemic administration of VHH-Fc constructs in mice demonstrated significantly improved brain uptake compared to irrelevant controls. Functional delivery was confirmed using neurotensin (NT)-induced hypothermia, and we established correlations between in vivo effects and TfR1 VHH binding properties determined by surface plasmon resonance. Notably, efficient BBB transcytosis was associated with intermediate affinity and rapid dissociation rates. Engineered variants maintained favorable cross-species binding, including similar affinities to human and non-human primate TfR1, facilitating translational studies. The cross-reactive anti-TfR1 VHHs we developed offer a versatile and modular platform for CNS drug delivery and hold promise as molecular shuttles for transporting therapeutic agents across the BBB. Our work establishes a robust foundation for developing next-generation brain-targeted biotherapeutics, including peptides, enzyme replacement therapies, antibody-based treatments for neurodegenerative diseases, and oligonucleotide delivery for CNS disorders, enabling seamless translation from preclinical to clinical applications.

neuroscience↗

bioRxiv2025

A high-throughput platform for biophysical antibody developability assessment to enable AI/ML model training

Antibodies must bind their targets with high affinity and specificity to achieve useful therapeutic activity. They must also possess suitable developability properties (e.g., thermostability, solubility, viscosity, polyreactivity) to ensure favorable manufacturing, formulation, and in vivo performance. Both binding and developability properties are inherent to a given antibody amino acid sequence. Identification or selection of antibodies possessing suitable binding characteristics is now routine, and de novo computational design models, trained on extensive complementarity-determining region sequence and structural data, are rapidly improving. Developability properties, however, remain difficult to predict largely due to insufficient training data, with empirical testing being heavily used to avoid challenges in late-stage antibody development. To fill this gap, we built a high-throughput antibody developability assay platform designed to generate the large datasets needed to train improved machine learning (ML) models. We optimized and automated known developability assays [Jain et al., 2017], and developed a robust integrated data analytics pipeline. Here we report data on 246 antibodies--representing 106 approved, 135 clinical-stage, and 5 preregistration/withdrawn molecules--across a panel of 10 developability assays, in a "tidy data" format suitable for AI/ML modeling. We used these data to develop an XGBoost [Chen et al., 2016] ML model that better predicts similarity to approved antibodies compared to conventional use of developability warning thresholds. Additionally, we confirm that preliminary predictive models do improve with more training data. Our high-throughput PROPHET-Ab platform enables data generation at the scale needed to develop improved ML models to predict antibody developability. SignificanceSuccessful antibody drugs exhibit important "developability" properties, beyond tight and specific binding to their target, including high expressibility, high stability and solubility, low aggregation propensity, low viscosity, low polyreactivity, and long in vivo half-life. Collectively, developability properties predict favorable manufacturing, storage, administration, and safety, and deficiencies in these properties increase risk for clinical failure. Despite progress in developing machine learning models to predict structure and binding, antibody developability models lag, largely due to a lack of sufficiently large training datasets. We have built a high-throughput platform, PROPHET-Ab, that enables data generation at the scale needed to train improved AI/ML models to predict antibody developability.

biophysics↗

bioRxiv2024

The Fat4 intracellular domain controls turnover of Fat4/Dchs1 planar polarity membrane complexes

The Fat/Dachsous (Ft/Ds) pathway is a highly conserved pathway regulating planar cell polarity (PCP) across different animal species. Proteins from the Ft and Ds family are large transmembrane protocadherins that form heterophilic complexes on the boundaries between cells. Fat4 and Dchs1, the main mammalian homologues of this pathway, have been implicated in PCP in various epithelial tissues and were shown to form extremely stable complexes at the boundaries between cells. It is unclear however, what are the dynamics controlling such stable boundary complexes, and how the formation and turnover of these complexes is regulated. Here, we use quantitative live imaging to elucidate the role of the intracellular domains (ICD) of Fat4 and Dchs1 in regulating Fat4/Dchs1 complex dynamics. We show that removing the ICD of Fat4 results in a reduction of both Trans-endocytosis (TEC) of Dchs1 into the Fat4 cells and boundary accumulation, but does not affect the diffusion of the complexes at the boundary. We further show that the ICD of Fat4 controls the turnover rate of Fat4/Dchs1 complexes. Finally, we find that while actin polymerization is required for maintaining the boundary accumulation of Fat4/Dchs1 complexes, we do not identify correlations between Fat4/Dchs1 complexes and local actin accumulation. Overall, we suggest that the Fat4 ICD is important for the turnover and plasticity of the highly stable Fat4/Dchs1 complexes associated with PCP. Statement of SignificanceThe purpose of this study is to elucidate the dynamics leading to the formation and maintenance of Fat4/Dchs1 complexes at the cell boundary and how it is affected by the ICD of Fat4 in mammals. The insights from this work are important for obtaining a mechanistic molecular framework for understanding formation of planar cell polarity as well as for highlighting how cell boundary membrane complexes are regulated.

cell biology↗

bioRxiv2023

Fecal microbiomes of laboratory beagles receiving antiparasitic formulations in an experimental setting

Here we describe the fecal microbiome of laboratory beagles in a non-invasive and humane experiment designed to contrast in vivo versus invitro bioequivalence in response to antiparasitic drug administration. The experiment provided a unique opportunity to describe the fecal microbiota of dogs in an experimental setting prior to their adoption. These data are contributed as a resource for the scientific community by the Center for Veterinary Medicine (CVM) of the U.S. Food and Drug Administration (FDA).

microbiology↗

bioRxiv2023

Transgene-Free Ex Utero Derivation of A Human Post-Implantation Embryo Model Solely from Genetically Unmodified Naive PSCs

Our ability to study early human post-implantation development remains highly limited due to the ethical and technical challenges associated with intrauterine development of the human embryo after implantation. Despite the great progress made on human gastruloids, axioloids and in vitro cultured blastoids, such elegant models do not constitute an integrated Stem cell-derived Embryo Models (SEMs) that includes all the key extra-embryonic tissues of the early post-implantation human conceptus (e.g., hypoblast, yolk-sac, trophoblasts, amnion, and extraembryonic mesoderm), and thus, do not recapitulate post-implantation epiblast development within the context of these extra-embryonic compartments. Mouse naive pluripotent stem cells (PSCs) have recently been shown to give rise to embryonic and extra-embryonic stem cells capable of self-assembling into post-gastrulation mouse SEMs, while bypassing the blastocyst-like stage, and eventually initiating organogenesis ex utero. Here, we implement critical adaptations to extend these finding to humans, while using only genetically unmodified human naive PSCs, thus circumventing the need for ectopic expression of lineage promoting transgenes. Such integrated human SEMs recapitulate the organization of all known compartments of early post-implantation stage human embryos, including epiblast, hypoblast, extra-embryonic mesoderm, and trophoblast surrounding the latter layers. The organized human SEMs recapitulate key hallmarks of post-implantation stage embryogenesis up to 13-14 days post-fertilization (dpf, Carnegie stage 6a), such as bilaminar disk formation, epiblast lumenogenesis, amniogenesis, anterior-posterior symmetry breaking, PGC specification, primary and secondary yolk sac formation, and extra-embryonic mesoderm expansion that defines a chorionic cavity and a connective stalk. This new platform constitutes a tractable stem cell-based model for experimentally interrogating previously inaccessible windows of human peri- and early post-implantation development.

developmental biology↗

bioRxiv2022

Melon pan-genome and multi-parental framework for high-resolution trait dissection

Linking between genotype and phenotype is a fundamental goal in biology and requires robust data for both layers. The prominent increase in plant genome sequencing and comparisons of multiple related individuals, exposed the abundance of structural genomic variation and suggest that a single reference genome cannot represent the complete sequence diversity of a crop species, leading to the expansion of the pan-genome concept. For high-resolution forward genetics, this unprecedented access to genomic variation should be paralleled by availability and phenotypic characterization of genetic diversity, and effective integration between these layers. Here, we describe a multi-parental framework for trait dissection in melon, leveraging a novel pan-genome constructed for this crop. Melon (Cucumis melo L.) is an important crop from the Cucurbitaceae family, which display extensive phenotypic variation available for breeding. A diverse core set of 25 founder lines (MelonCore25) was sequenced using a combination of short and long-read technologies and their genomes were assembled de novo. The construction of a melon pan-genome exposed substantial variation in genome size and structure, including detection of ~300,000 structural variants and ~9 million SNPs. A half-diallel derived set of 300 F2 populations representing all possible MelonCore25 parental combinations was constructed as framework for trait dissection through integration with the pan-genome. We demonstrate the potential of this unified framework for genetic analysis of various melon traits, including rind color and mottling pattern, fruit sugar content and resistance to fungal diseases. We anticipate that utilization of this integrated resource will enhance genetic dissection of important traits and accelerate melon breeding. Significance statementPan-genomes aim to address the abundance of genome structural variation within species for improved genomic analyses. New pan-genome, constructed from de novo genome assemblies of 25 diverse melon (Cucumis melo L.) accessions is integrated with a half-diallel derived set of 300 F2 populations representing all possible parental combinations. The potential of this unified multi-parental trait dissection framework for melon genetics and breeding is presented.

genetics↗

bioRxiv2022

Mechano-signaling feedback underlies precise inner hair cell patterning in the organ of Corti

The mammalian hearing organ, the organ of Corti, is one of the most organized tissues in the mammalian body plan. It contains precisely positioned array of alternating sensory hair cells (HC) and non-sensory supporting cells that emerge during embryonic development from an initially disordered pro-sensory domain. While much is known on the genetics and biochemistry underlying this process, it is still unclear how such precise alternating patterns emerge during embryonic development. Here, we combine live imaging of mouse inner ear explants with hybrid mechano-regulatory models to elucidate the mechanisms underlying the formation of a single row of inner HC (IHC). We show that a narrow strip of initially disordered salt-and-pepper pattern, generated by Notch-mediated lateral inhibition, is dynamically refined by coordinated intercalations, delaminations, and differential adhesion. We identify a new morphological transition, termed hopping intercalation, that allows nascent IHC to hop under the apical plane into their final position. We further show that IHC patterning is associated with boundary localization of the cell adhesion molecules, Nectin-3 and Nectin-1. Our experimental results and modeling support a mechanism for precise patterning based on a feedback between Notch-mediated differentiation and mechanically driven cellular reorganization that is likely relevant for many developmental processes.

developmental biology↗

bioRxiv2021

A nesprin-4/kinesin-1 cargo model for nucleus positioning in cochlear outer hair cells

Nuclear positioning is important for the functionality of many cell types and is mediated by interactions of cytoskeletal elements and nucleoskeleton proteins. Nesprin proteins, part of the linker of nucleoskeleton and cytoskeleton (LINC) complex, have been shown to participate in nuclear positioning in multiple cell types. Outer hair cells (OHCs) in the inner ear are specialized sensory epithelial cells that utilize somatic electromotility to amplify auditory signals in the cochlea. Recently, nesprin-4 (encoded by Syne4) was shown to play a crucial role in nuclear positioning in OHCs. Syne4 deficiency in humans and mice leads to mislocalization of the OHC nuclei and cell death resulting in deafness. However, it is unknown how nesprin-4 mediates the position of the nucleus, and which other molecular components are involved in this process. Here, we show that the interaction of nesprin-4 and the microtubule motor kinesin-1 is mediated by a conserved 4 amino-acid motif. Using in-vivo AAV gene delivery, we show that this interaction is critical for nuclear positioning and hearing in mice. Nuclear mislocalization and cell death of OHCs coincide with the onset of hearing and electromotility and are solely restricted to outer, but not inner, hair cells. Likewise, the C. elegans functional homolog of nesprin-4, UNC-83, uses a similar motif to mediate interactions between migrating nuclei and kinesin-1. Overall, our results suggest that OHCs require unique cellular machinery for proper nuclear positioning at the onset of electromotility. This machinery relies on the interaction between nesprin-4 and kinesin-1 motors supporting a microtubule cargo model for nuclear positioning.

cell biology↗

bioRxiv2021

A cell-penetrant peptide blocking C9ORF72-repeat RNA nuclear export suppresses neurodegeneration

Hexanucleotide repeat expansions in C9ORF72 are the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), a spectrum of incurable debilitating neurodegenerative diseases. Here, we report a novel ALS/FTD drug concept with in vivo and in vitro therapeutic activity in preclinical models of C9ORF72-ALS/FTD. Our data demonstrate that supplementation or oral administration of a cell-penetrant peptide, which competes with the SRSF1:NXF1 interaction, confers neuroprotection by inhibiting the nuclear export of pathological C9ORF72-repeat transcripts in various models of disease including primary neurons, patient-derived motor neurons and Drosophila. Our drug-like rationale for disrupting the nuclear export of microsatellite repeat transcripts in neurological disorders provides a promising alternative to conventional small molecule inhibitors often limited by poor blood-brain barrier penetrance.

molecular biology↗

bioRxiv2019

Shear forces drive precise patterning of hair cells in the mammalian inner ear

Precise cellular organizations are required for the function of many organs and tissues. It is often unclear, however, how such precise patterns emerge during development. The mammalian hearing organ, the organ of Corti, consists of a remarkably organized pattern of four rows of hair cells (HCs) interspersed by non-sensory supporting cells (SCs). This checkerboard-like pattern of HCs and SCs emerges from a disordered epithelium over several days, yet the transition to an ordered cellular pattern is not well understood. Using a combination of quantitative morphological analysis and time-lapse imaging of mouse cochlear explants, we show here that patterning of the organ of Corti involves dynamic reorganizations that include lateral shear motion, cell intercalations, and delaminations. A mathematical model, where tissue morphology is described in terms of the mechanical forces that act on cells and cellular junctions, suggests that global shear on HCs and local repulsion between HCs are sufficient to drive the tissue into the final checkerboard-like pattern. Our findings suggest that precise patterns can emerge during development from reorganization processes, driven by a combination of global and local forces in a process analogous to shear-induced crystallization.

developmental biology↗

bioRxiv2018

Model-Aware Deep Learning Based Strategies for Clutter Suppression in Contrast Enhanced Ultrasound

Contrast enhanced ultrasound is a radiation-free imaging modality which uses encapsulated gas microbubbles for improved visualization of the vascular bed deep within the tissue. It has recently been used to enable imaging with unprecedented subwavelength spatial resolution by relying on super-resolution techniques. A typical preprocessing step in super-resolution ultrasound is to separate the microbubble signal from the cluttering tissue signal. This step has a crucial impact on the final image quality. Here, we propose a new approach to clutter removal based on robust principle component analysis (PCA) and deep learning. We begin by modeling the acquired contrast enhanced ultrasound signal as a combination of a low rank and sparse components. This model is used in robust PCA and was previously suggested in the context of ultrasound Doppler processing and dynamic magnetic resonance imaging. We then illustrate that an iterative algorithm based on this model exhibits improved separation of microbubble signal from the tissue signal over commonly practiced methods. Next, we apply the concept of deep unfolding to suggest a deep network architecture tailored to our clutter filtering problem which exhibits improved convergence speed and accuracy with respect to its iterative counterpart. We compare the performance of the suggested deep network on both simulations and in-vivo rat brain scans, with a commonly practiced deep-network architecture and the fast iterative shrinkage algorithm, and show that our architecture exhibits better image quality and contrast.

bioengineering↗

bioRxiv2018

LINGO3 interacts with Trefoil factor 2 to enforce mucosal barrier integrity and drive tissue repair during colitis

Mucosal epithelia are constantly exposed to damaging stimuli from mechanical, chemical, or biologic entities, and depend on rapid repair mechanisms to maintain tissue homeostasis and immunological quiescence. The reparative cytokine Trefoil factor 2 (TFF2) serves to enforce mucosal barrier integrity, but whether TFF2 receptor(s) exist is controversial. Herein, we demonstrate leucine rich repeat and immunoglobulin like domain containing nogo receptor interacting protein 3 (LINGO3) is a necessary transmembrane component for TFF2-mediated ERK signaling, proliferation, and recovery of trans-epithelial resistance of primary epithelia during wound healing. Human respiratory and intestinal epithelia express LINGO3 and mice lacking Lingo3 have impaired intestinal barrier function and fail to recover from DSS-induced colitis. Compared to wild-type controls, LINGO3 deficiency impairs both crypt regeneration and expression of the intestinal stem cell marker Lgr5. Importantly, Lingo3-/- mice display a phenotype similar to that previously reported for Tff2 deficiency, with increased paracellular permeability, and significant accumulation of mucosal CD4+ TH1 cells expressing IFN{gamma}+ TNF+ even under steady-state conditions. Combined, these data reveal a previously unrecognized role for LINGO3 as a putative TFF2 receptor that regulates mucosal barrier integrity and GI inflammation.\n\nSignificanceIntestinal epithelial cells (IEC) are necessary for maintenance of homeostasis, resistance to infectious organisms, and overall organismal health. When injured the IEC and the underlying stroma and progenitor cell pool undergo restitutive and regenerative processes driven by the reparative cytokine Trefoil factor 2 (TFF2). This report identifies a novel receptor component for TFF2 signaling expressed on both human and mouse epithelial cells that is necessary for barrier integrity at the steady state and during colitic disease. The discovery of a novel TFF2-LINGO3 axis sheds new light on the processes controlling tissue repair, restitution, and regeneration at the mucosal interface.

cell biology↗

bioRxiv2018

Digital therapeutics for distributed response to global pandemics

Despite advances in the development of drugs and vaccines, the spread of infectious diseases remains an imminent threat to our global health, in extreme cases potentially having detrimental consequences. At present our response to this threat is based on physically distributing therapeutic material, which utilizes the same transportation networks that support the spread of the infectious agent itself. Such competition is at risk of failure in the face of a rapidly spreading pathogen, especially given the inevitable delay from the initial outbreak to the development and execution of our response. Moreover, based on our existing transportation networks, we show that such physical distribution is intrinsically inefficient, leading to an uneven concentration of the therapeutic within a small fraction of destinations, while leaving the majority of the population deprived. This suggests that outrunning a virulent epidemic can only be achieved if we develop a mitigation strategy that bypasses the existing distribution networks of biological and chemical material. Here we propose such a response, utilizing digitizable therapeutics, which can be distributed as digital sequence files and synthesized on location, exposing an extremely efficient mitigation scheme that systematically outperforms physical distribution. Our proposed strategy, based for example on nucleic acid therapeutics, is plausibly the only viable mitigation plan, based on current technology, that can face a violently spreading pathogen. Complementing the current paradigm, which ranks drugs based on efficacy, our analysis demonstrates the importance of balancing efficacy with distributability, finding that in some cases the latter plays the dominant role in the overall mitigation efficiency.

bioinformatics↗