Biology subjects

Leong, J.

Publications and source records attributed to Leong, J..

6 recordsLinked to original sources

bioRxiv2026

Live high-content imaging with automated analysis reveals mitochondrial changes during vascular calcification

Mitochondrial dysfunction is implicated in a wide range of disorders, including cancer, neurodegeneration, and cardiovascular diseases. Conventional assays typically assess mitochondrial function by measuring bulk respiration rates across thousands of cells. While informative, these approaches cannot resolve the behavior of individual mitochondria, may overlook rare mitochondrial events, and often lack sensitivity to subtle changes. Fluorescence microscopy provides single-organelle resolution but is usually low throughput; for example, imaging 1000 cells can require from 20 minutes to an entire day depending on imaging mode. Additionally, analysis of fluorescence images frequently relies on manually selected thresholds, introducing potential bias and variability due to differences in signal-to-background ratios across cells. Here, we present a High-throughput Mitochondrial Imaging Platform (H-MIP) combined with a deep learning segmentation model, enabling rapid imaging and automated characterization of mitochondrial morphology in millions of mitochondria from tens of thousands of cells. We demonstrate the utility of H-MIP by assessing mitochondrial morphology following treatment with Mdivi-1, an inhibitor of mitochondrial division. Furthermore, we employ an in vitro disease model (vascular calcification) to show that mitochondria become elongated in vascular smooth muscle cells undergoing pathological calcification. Overall, H-MIP provides a scalable and robust tool for investigating mitochondrial structure, with the potential to accelerate therapeutic discovery targeting mitochondrial health. HighlightsO_LIH-MIP enables high-throughput imaging of mitochondrial morphology and automated single-mitochondrion analysis at scale. C_LIO_LIH-MIP links mitochondrial morphology to an established disease model, with exciting implications for drug discovery. C_LI

cell biology↗

bioRxiv2024

Histone acetyltransferase HAF2 associates with PDC to control H3K14ac and H3K23ac in ethylene response

Ethylene plays its essential roles in plant development, growth, and defense responses by controlling the transcriptional reprogramming, in which EIN2-C-directed regulation of histone acetylation is the first key-step for chromatin to perceive ethylene signaling. However, the histone acetyltransferase in this process remains unknown. Here, we identified histone acetyltransferase HAF2, and mutations in HAF2 confer plants with ethylene insensitivity. Furthermore, we found that HAF2 interacts with EIN2-C in response to ethylene. Biochemical assays demonstrated that the bromodomain of HAF2 binds to H3K14ac and H3K23ac peptides with a distinct affinity for H3K14ac; the HAT domain possesses acetyltransferase catalytic activity for H3K14 and H3K23 acetylation, with a preference for H3K14. ChIP-seq results provide additional evidence supporting the role of HAF2 in regulating H3K14ac and H3K23ac levels in response to ethylene. Finally, our findings revealed that HAF2 co-functions with pyruvate dehydrogenase complex (PDC) to regulate H3K14ac and H3K23ac in response to ethylene in an EIN2 dependent manner. Overall, this research reveals that HAF2 as a histone acetyltransferase that forms a complex with EIN2-C and PDC, collectively governing histone acetylation of H3H14ac and H3K23ac, preferentially for H3K14 in response to ethylene.

plant biology↗

bioRxiv2021

Lack of blocking activity in anti-CTLA-4 antibodies reduces toxicity, but not anti-tumor efficacy

Anti-CTLA-4 antibodies such as ipilimumab were among the first immune-oncology agents to show significantly improved outcomes for patients. However, existing anti-CTLA-4 therapies fail to induce a response in a majority of patients and can induce severe, immune-related adverse events. It has been assumed that checkpoint inhibition, i.e., blocking the interaction between CTLA-4 and its ligands, is the primary mechanism of action for ipilimumab. In this study we present evidence that checkpoint inhibition is not a primary mechanism of action for efficacy of anti-CTLA-4 antibodies. Instead, the primary mechanism for efficacy is FcR-mediated Treg depletion in the tumor microenvironment. First, we identified a monoclonal antibody (mAb) that binds to CTLA-4 at an epitope that differs from ipilimumabs by only a few amino acids, yet has limited checkpoint inhibitor activity. Surprisingly, the weak checkpoint inhibitor has superior anti-tumor activity compared to ipilimumab in a murine model. The weak checkpoint inhibitor also induces less Treg proliferation and has increased ability to induce in vitro FcR signaling and in vivo depletion of intratumoral Tregs. Further experiments showed that the enhanced FcR activity of the weak checkpoint inhibitor likely contributes to its enhanced anti-tumor activity. Importantly, we also showed that weak checkpoint inhibition was associated with lower toxicity in murine models. Our work suggests that new anti-CTLA-4 drugs should be optimized for Treg depletion rather than checkpoint inhibition.

immunology↗

bioRxiv2020

Capturing and Recreating Diverse Antibody Repertoires as Multivalent Recombinant Polyclonal Antibody Drugs

Plasma-derived polyclonal antibodies are polyvalent drugs used for many important clinical indications that require modulation of multiple drug targets simultaneously, including emerging infectious disease and transplantation. However, plasma-derived drugs suffer many problems, including low potency, impurities, constraints on supply, and batch-to-batch variation. In this study, we demonstrated proofs-of-concept for a technology that uses microfluidics and molecular genomics to capture diverse mammalian antibody repertoires as multivalent recombinant drugs. These "recombinant hyperimmune" drugs comprised thousands to tens of thousands of antibodies and were derived from convalescent human donors, or vaccinated human donors or immunized mice. Here we used our technology to build a highly potent recombinant hyperimmune for Severe Acute Respiratory Syndrome Coronavirus-2 (SARS CoV-2) in less than three months. We also validated a recombinant hyperimmune for Zika virus disease that abrogates antibody-dependent enhancement (ADE) through Fc engineering. For patients with primary immune deficiency (PID), we built high potency polyvalent recombinant hyperimmunes against pathogens that commonly cause serious lung infections. Finally, to address the limitations of rabbit-derived anti-thymocyte globulin (ATG), we generated a recombinant human version and demonstrated in vivo function against graft-versus-host disease (GVHD). Recombinant hyperimmunes are a novel class of drugs that could be used to target a wide variety of other clinical applications, including cancer and autoimmunity.

immunology↗

bioRxiv2020

Curation of over 10,000 transcriptomic studies to enable data reuse

Vast amounts of transcriptomic data reside in public repositories, but effective reuse remains challenging. Issues include unstructured dataset metadata, inconsistent data processing and quality control, and inconsistent probe-gene mappings across microarray technologies. Thus, extensive curation and data reprocessing is necessary prior to any reuse. The Gemma bioinformatics system was created to help address these issues. Gemma consists of a database of curated transcriptomic datasets, analytical software, a web interface, and web services. Here we present an update on Gemmas holdings, data processing and analysis pipelines, our curation guidelines, and software features. As of June 2020, Gemma contains 10,811 manually curated datasets (primarily human, mouse, and rat), over 395,000 samples and hundreds of curated transcriptomic platforms (both microarray and RNA-sequencing). Dataset topics were represented with 10,215 distinct terms from 12 ontologies, for a total of 54,316 topic annotations (mean topics/dataset = 5.2). While Gemma has broad coverage of conditions and tissues, it captures a large majority of available brain-related datasets, accounting for 34% of its holdings. Users can access the curated data and differential expression analyses through the Gemma website, RESTful service, and an R package. Database URL: https://gemma.msl.ubc.ca/home.html

bioinformatics↗

bioRxiv2018

Convergence in form and function overcomes non-parallel evolutionary histories in Arctic charr

Understanding the extent to which evolution is predictable under multifarious selection is a longstanding question in evolutionary biology. However, the interplay of stochastic and contingent factors influencing the extent of parallelism in nature is not well understood. To test the predictability of evolution, we studied a natural experiment on different organismal levels across lakes and evolutionary lineages of a freshwater salmonid fish, Arctic charr (Salvelinus alpinus). We identified significant phenotypic parallelism between Arctic charr ecotype pairs within a continuum of parallel evolution and highly parallel adaptive morphological traits. Variability in phenotypic predictability was explained by complex demographic histories, differing genomic backgrounds and genomic responses to selection, variable genetic associations with ecotype, and environmental variation. Remarkably, gene expression was highly similar across ecotype replicates, and explained the observed parallelism continuum. Our findings suggest that parallel evolution by non-parallel evolutionary routes is possible when the regulatory molecular phenotype compensates for divergent histories.

evolutionary biology↗