Biology subjects

Huang, J. Q.

Publications and source records attributed to Huang, J. Q..

3 recordsLinked to original sources

bioRxiv2025

Reproducible detection of antigen-specific T cells and Tregs via standardized and automated activation-induced marker assay workflows

Activation-induced marker (AIM) assays are a promising tool to track antigen-specific T cells, but methodological heterogeneity between research groups hinders their clinical utility. To evaluate AIM assay reproducibility, we conducted a multi-site study of SARS-CoV-2 and cytomegalovirus AIMs. We found inherent variability in AIM assays and optimized approaches to enhance reproducibility, including a standardized workflow to minimize technical variability and a generalizable Box-Cox transformation-based statistical method to optimize calculation of AIM stimulation responses. We further standardized AIM data analysis through development of automated flow cytometric gating software, which had superior reproducibility compared to manual analysis. We also characterized antigen-specific Tregs, finding that gating on a combination of CD134, CD137, FOXP3 and HELIOS optimally detects antigen-specific cells. The combined methodology results in a high degree of reproducibility within and between research groups and provides a comprehensive foundation from which standardized AIM assays can be implemented across diverse scientific and clinical settings. MOTIVATIONReliable detection of antigen-specific T cells is critical to understand immune responses to infection and vaccination, and has translational potential to monitor T cell responses across diverse clinical settings. Activation-induced marker (AIM) assays offer a variety of advantages over methods such as ELISPOT and tetramers, but are limited by methodological heterogeneity between research groups and a lack of standardized protocols. As such, the degree to which AIM assay results are reproducible is unknown. Key variables such as cell source, media, stimulation time, marker selection for CD4+ T cells, CD8+ T cells and regulatory T cells; as well as data analysis parameters such as flow cytometric gating strategies and mathematical correction for background AIM+ frequencies in unstimulated control samples, have not been rigorously studied. To address this, we comprehensively characterized variability in AIM assays, including within and between operators and across multiple research centres, and sought to optimize a standard AIM workflow to enhance reproducibility at both the experimental and analytical levels.

immunology↗

bioRxiv2025

Dynamic Proximal Interactomics and Chemical Genetic Screening Reveal CCR4-NOT Sequestration in Stress Granules as a Mechanism for Transcript Stabilization

Cells adapt to stress by rewiring their post-transcriptional gene regulation. Stress granules--biomolecular condensates composed of polyadenylated RNAs and RNA-binding proteins--are implicated in this process, yet their precise functional roles remain debated. To address this, we mapped the dynamic proteomic landscapes of stress granules formed under oxidative and hyperosmotic stress using multi-bait BioID proximity profiling coupled with quantitative mass spectrometry. This analysis revealed context-specific remodeling of proximal interaction networks and identified a conserved, stress-dependent shift in association with the CCR4-NOT deadenylase complex. A complementary genome-wide chemical genetic screen further implicated CCR4-NOT in stress granule biology, showing that reduced CCR4-NOT activity bypassed lipoamide-mediated inhibition of stress granule assembly. Microscopy showed sequestration of the CCR4-NOT complex into stress granules, and global transcriptomic analyses revealed that this relocalization promotes poly(A) tail lengthening and increased abundance of stress-induced survival transcripts. Together, integration of proteomics, chemical genetics, and transcriptomics uncovers a spatial mechanism by which stress granule assembly promotes cellular adaptation to stress through sequestration of CCR4-NOT from the cytosol and consequent remodeling of post-transcriptional regulation.

cell biology↗

bioRxiv2024

TSC22D, WNK and NRBP gene families exhibit functional buffering and evolved with Metazoa for macromolecular crowd sensing

The ability to sense and respond to osmotic fluctuations is critical for the maintenance of cellular integrity. Myriad redundancies have evolved across all facets of osmosensing in metazoans, including among water and ion transporters, regulators of cellular morphology, and macromolecular crowding sensors, hampering efforts to gain a clear understanding of how cells respond to rapid water loss. In this study, we harness the power of gene co-essentiality analysis and genome-scale CRISPR-Cas9 screening to identify an unappreciated relationship between TSC22D2, WNK1 and NRBP1 in regulating cell volume homeostasis. Each of these genes have paralogs and are functionally buffered for macromolecular crowd sensing and cell volume control. Within seconds of hyperosmotic stress, TSC22D, WNK and NRBP family members physically associate into cytoplasmic biocondensates, a process that is dependent on intrinsically disordered regions (IDRs). A close examination of these protein families across metazoans reveals that TSC22D genes evolved alongside a domain in NRBPs that specifically binds to TSC22D proteins, which we have termed NbrT (NRBP binding region with TSC22D), and this co-evolution is concomitant with rapid IDR length expansion in WNK family kinases. Our study identifies functions for unrecognized components of the cell volume sensing machinery and reveals that TSC22D, WNK and NRBP genes evolved as cytoplasmic crowding sensors in metazoans to co-regulate rapid cell volume changes in response to osmolarity.

cell biology↗