Biology subjects

Hoch, A.

Publications and source records attributed to Hoch, A..

6 recordsLinked to original sources

bioRxiv2025

Development of AI-designed protein binders for detection and targeting of cancer cell surface proteins

Artificial intelligence (AI)-based protein design opens new avenues for the rapid generation of new research tools and therapeutics, but experimental validation lags behind the computational design throughput. Here, we present a scalable workflow for the discovery and validation of AI-designed protein binders. Leveraging the RFdiffusion protein design pipeline with a custom filter for stable alpha-helical bundle folds, we construct libraries of thousands of AI-binders against cancer-associated surface proteins. Mammalian cell-surface and phage display screening yield multiple high-affinity PD-L1 binders but fewer hits for CD276 (B7-H3) and VTCN1 (B7-H4), reflecting the target-dependent efficiency of RFdiffusion in generating high-quality designs. Using our experimentally validated AI-designed binder libraries, we benchmark freely available structure prediction models. We find that interface predicted template modelling (ipTM) scores by Chai-1 with ESM embedding correlate well with experimental success and even predict deleterious effects of binding interface mutations. To demonstrate the versatility of AI-binders as research tools, we deploy them in CAR-T cells and also assemble them with fluorophore-labeled streptavidin into tetravalent quattrobinders, which achieve antibody-comparable staining of endogenous PD-L1 by flow cytometry. With high production yields and accessible structural models, AI-designed quattrobinders are versatile and cost-effective research tools amenable to community-driven validation and optimization.

bioengineering↗

bioRxiv2025

Transposon-Display of AI-designed binders enables manipulation of the proteome in human cells

Transposon-Display is a highly scalable screening method that links proteins to their encoding DNA during expression in E. coli via a mutant transposase. Leveraging this system, we identified AI-designed binders targeting four intracellular human proteins, saturation-mutagenized top candidates, and charge-balanced variants to improve compatibility with the intracellular environment while preserving target binding. The resulting neutral binders can be fused to EGFP allowing antibody-free intracellular staining. Expressing neutral binders in human cells as fusions with functional domains can drive small molecule-controlled protein aggregation and trigger proteasomal degradation of endogenous target proteins in living cells. Manipulating the proteome of living cells using libraries of AI-designed binders may provide a new avenue to screen for disease-relevant protein functions and large-scale functional data may help to refine protein design algorithms.

bioengineering↗

bioRxiv2025

Identification of a multi-omics factor predictive of long COVID in the IMPACC study

Following SARS-CoV-2 infection, [~]10-35% of COVID-19 patients experience long COVID (LC), in which often debilitating symptoms persist for at least three months. Elucidating the biologic underpinnings of LC could identify therapeutic opportunities. We utilized machine learning methods on biologic analytes and patient reported outcome surveys provided over 12 months after hospital discharge from >500 hospitalized COVID-19 patients in the IMPACC cohort to identify a multi-omics "recovery factor". IMPACC participants who experienced LC had lower recovery factor scores compared to participants without LC. Biologic characterization revealed increased levels of plasma proteins associated with inflammation, elevated transcriptional signatures of heme metabolism, and decreased androgenic steroids in LC patients. The recovery factor was also associated with altered circulating immune cell frequencies. Notably, recovery factor scores were predictive of LC occurrence in patients as early as hospital admission, irrespective of acute disease severity. Thus, the recovery factor identifies patients at risk of LC early after SARS-CoV-2 infection and reveals LC biomarkers and potential treatment targets.

systems biology↗

bioRxiv2024

Unraveling SARS-CoV-2 Host-Response Heterogeneity through Longitudinal Molecular Subtyping

Hospitalized COVID-19 patients exhibit diverse immune responses during acute infection, which are associated with a wide range of clinical outcomes. However, understanding these immune heterogeneities and their links to various clinical complications, especially long COVID, remains a challenge. In this study, we performed unsupervised subtyping of longitudinal multi-omics immunophenotyping in over 1,000 hospitalized patients, identifying two critical subtypes linked to mortality or mechanical ventilation with prolonged hospital stay and three severe subtypes associated with timely acute recovery. We confirmed that unresolved systemic inflammation and T-cell dysfunctions were hallmarks of increased severity and further distinguished patients with similar acute respiratory severity by their distinct immune profiles, which correlated with differences in demographic and clinical complications. Notably, one critical subtype (SubF) was uniquely characterized by early excessive inflammation, insufficient anticoagulation, and fatty acid dysregulation, alongside higher incidences of hematologic, cardiac, and renal complications, and an elevated risk of long COVID. Among the severe subtypes, significant differences in viral clearance and early antiviral responses were observed, with one subtype (SubC) showing strong early T-cell cytotoxicity but a poor humoral response, slower viral clearance, and greater risks of chronic organ dysfunction and long COVID. These findings provide crucial insights into the complex and context-dependent nature of COVID-19 immune responses, highlighting the importance of personalized therapeutic strategies to improve both acute and long-term outcomes.

immunology↗

bioRxiv2024

Sensing endogenous RNA in living human cells using a CRISPR-activated protease

Most techniques used to detect specific mRNAs in eukaryotic cells require to extract nucleic acids and thereby kill the cells. A programmable sensor for monitoring endogenous transcripts in living cells, in contrast, would enable to enrich living cells based on a specific transcription or splicing event, and studying these cells by live microscopy or sequencing methods requiring intact cells. We have engineered CRISPR-READ, a live cell RNA detector based on the CRISPR-associated Lon protease CalpL and a cA4-producing Type III CRISPR system. Upon RNA-programmable RNA sensing, CRISPR-READ produces an orthogonal second messenger, which leads to the cleavage of a dual FRET / localization reporter compatible with FACS sorting and live microscopy. Using this genetically encoded sensing circuit as a readout for a genome-wide CRISPR perturbation screen, we identified an extended Type-I interferon signaling cascade; RNA-Seq on sensor-sorted cells enabled unbiased identification of correlated stochasticity in gene expression across single cells.

bioengineering↗

bioRxiv2023

Integrated longitudinal multi-omics study identifies immune programs associated with COVID-19 severity and mortality in 1152 hospitalized participants

Hospitalized COVID-19 patients exhibit diverse clinical outcomes, with some individuals diverging over time even though their initial disease severity appears similar. A systematic evaluation of molecular and cellular profiles over the full disease course can link immune programs and their coordination with progression heterogeneity. In this study, we carried out deep immunophenotyping and conducted longitudinal multi-omics modeling integrating ten distinct assays on a total of 1,152 IMPACC participants and identified several immune cascades that were significant drivers of differential clinical outcomes. Increasing disease severity was driven by a temporal pattern that began with the early upregulation of immunosuppressive metabolites and then elevated levels of inflammatory cytokines, signatures of coagulation, NETosis, and T-cell functional dysregulation. A second immune cascade, predictive of 28-day mortality among critically ill patients, was characterized by reduced total plasma immunoglobulins and B cells, as well as dysregulated IFN responsiveness. We demonstrated that the balance disruption between IFN-stimulated genes and IFN inhibitors is a crucial biomarker of COVID-19 mortality, potentially contributing to the failure of viral clearance in patients with fatal illness. Our longitudinal multi-omics profiling study revealed novel temporal coordination across diverse omics that potentially explain disease progression, providing insights that inform the targeted development of therapies for hospitalized COVID-19 patients, especially those critically ill.

immunology↗