Biology subjects

Tsui, H.

Publications and source records attributed to Tsui, H..

5 recordsLinked to original sources

bioRxiv2026

Productive Mayaro Virus Infection Requires Host Fatty Acid Synthase for nsP1 S-palmitoylation

To date, twenty-seven pathogenic human viruses require host-catalyzed de novo fatty acid biosynthesis for replication. This pathway is driven by fatty acid synthase (FASN), which produces palmitate. Palmitate is a precursor for various functions during viral infection, including lipid droplet formation for assembly, beta-oxidation for ATP generation, and post-translational modification of proteins. Whether Mayaro virus (MAYV), an emerging alphavirus that causes debilitating arthritogenic disease, required FASN for infection was unknown. Using genetic and pharmacological approaches in a human cell line and primary cell model, we found that MAYV requires FASN-dependent palmitate synthesis for virion production. To determine how palmitate contributes to infection, we pharmacologically inhibited pathways downstream of FASN and found that only 2-bromopalmitate (2-BP), a protein palmitoylation inhibitor, led to a 94% reduction in MAYV infection. S-palmitoylation is a post-translational modification in which palmitate is attached to sulfur atoms in cysteine residues. In chikungunya virus, a related alphavirus, FASN-dependent palmitoylation of nonstructural protein 1 (nsP1) is essential for membrane association and replication. Consequently, we hypothesized that MAYV nsP1 is palmitoylated in a FASN-dependent manner. Using an alkyne acetate analog, Alk-4, metabolized by FASN into alkyne palmitate, we observed specific labeling of wild-type nsP1 at conserved cysteine residues (C417-419), but not of a cysteine-to-alanine triple mutant. Treatment with TVB-2640 or 2-BP abrogated Alk-4 labeling of wild-type nsP1 during active infection, reinforcing that MAYV protein palmitoylation is a FASN-dependent process. Our findings reveal a conserved mechanism of FASN-dependent protein palmitoylation in alphaviruses and highlight FASN as a potential anti-viral target. ImportanceMayaro virus (MAYV) is a neglected, mosquito-borne tropical virus that causes debilitating pathologies, such as chronic joint pain that can last from months to years. Currently, MAYV transmissions are endemic in sylvatic and peri-urban regions in Central and South America and the Caribbean. However, MAYV has been detected in urban-adapted mosquitos like Aedes aegypti (Ae. aegypti) and is a concern for potential global spread. Consequently, investigating the mechanisms of MAYV infection is critical to uncover opportunities for antiviral drug development. In this study, we report that MAYV infection requires host fatty acid synthase (FASN) derived palmitate for palmitoylation of the viral non-structural protein 1 (nsP1). In addition, we report that inhibiting FASN with the clinically advanced small molecule TVB-2640 significantly reduced MAYV infection and nsP1 palmitoylation. This study highlights FASN as an essential host factor for MAYV replication and establishes it as a promising therapeutic target for MAYV and related alphaviruses.

microbiology↗

bioRxiv2026

ClumPyCells resolves spatial aggregation in complex tissues overcoming size biases

The spatial arrangement of cells within a tissue microenvironment shapes their interactions and cell states, which are essential for tissue development, homeostasis, and disease. Spatial -omics technologies can precisely map the location of each cell within complex tissue structures, while also profiling their protein content and transcriptional diversity. Various approaches have been developed to analyze spatial patterns of cell aggregation, repulsion, or random distribution within tissues. However, differences in cell morphology within a tissue can introduce significant bias. Cell size in particular is not accounted for and introduces challenges when quantifying the aggregation of cells or their molecular features. To overcome such limitations, we present ClumPyCells: a statistical framework that measures cell and marker aggregation within tissue while correcting for size morphology. ClumPyCells enables interpretation of cell aggregation, bypassing interfering cell types or tissue regions unrelated to the desired spatial correlation. We demonstrate the capabilities of ClumPyCells across several tumor types, including melanoma and colorectal cancer, and spatial -omics technologies such as spatial transcriptomics and proteomics, while benchmarking how cell-size differences contribute to misinterpretations. By correcting for disruptive cell types within a region of interest, ClumPyCells will determine new tissue patterns and structures without morphological interference.

bioinformatics↗

bioRxiv2025

Aberrant splicing of MBD1 reshapes the epigenome to drive convergent myeloerythroid defects in MDS

Myelodysplastic neoplasms (MDS) feature hematopoietic deficits driven in part by transcript splicing abnormalities. Thus far, such disease-driving transcripts have been identified in association with specific splicing factor mutations. However, it remains unclear whether there also exists a set of disease-wide conserved pathological transcripts, which drive MDS independently of mutational status. Here, we characterize an MDS-associated long isoform of MBD1 (MBD1-L) as the first described member of this class of transcripts. Overexpression of MBD1-L in healthy human HSPCs recapitulates archetypal defects of MDS including deficits in erythroid differentiation and reconstitution capacity. These defects arise from an isoform-specific switching of MBD1s binding behavior, refocusing its heterochromatin-promoting activity from methylated to unmethylated CpGs and enacting broad downregulation of CpG-rich promoters as well as secondary epigenetic effects mediated by its downstream target BCOR. Remarkably, we also find that directly reversing abnormal MBD1 splicing in primary human MDS using nanoparticle-encapsulated ASOs enhances erythroid differentiation. Key pointsO_LIGlobal mis-splicing of MBD1 represents a novel gain-of-function epigenetic axis driving erythropoietic and proliferative defects in MDS. C_LIO_LIASO based depletion of pathogenic MBD1 transcripts restores erythroid differentiation, advancing RNA-based therapies for MDS. C_LI

cancer biology↗

bioRxiv2025

PKP2 orchestrates OXPHOS expression in cardiomyocytes via a PGC1α-dependent mechanism

Arrhythmogenic cardiomyopathy (ACM) is an inherited cardiac disease where the majority of ACM patients carry a (likely) pathogenic variant in desmosomal genes, predominantly in plakophilin-2 (PKP2). While the genetic cause of the disease is well studied, the molecular disease-driving mechanisms and how exercise can drive disease progression remain poorly understood. In this study, we identified the oxidative phosphorylation (OXPHOS) pathway to be downregulated in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and human explanted hearts carrying pathogenic PKP2 variants. The reduced expression of OXPHOS related genes was a result of lower PPARGC1A expression which led to decreased mitochondrial spare capacity in PKP2 mutant hiPSC-CMs. Induction of PPARGC1A expression partially restored the expression of OXPHOS components and improved contractility in PKP2 mutant cells. These results suggest that improving oxidative capacity through modulation of PPARGC1A in cardiomyocytes could be considered as a new therapeutic target for ACM patients in the future.

molecular biology↗

bioRxiv2022

General stain deconvolution of histopathology images with physics-guided deep learning

Advances have been made in the use of deep learning to extract quantitative and predictive information from digital pathology slides, yet many barriers remain before clinical translation and deployment. In particular, models need to be generalizable despite the wide variations in image characteristics due to inter-scanner variability and differences in slide preparation protocols. This has led to an interest in stain deconvolution methods that could correct for the variability in image appearances. However, most existing stain deconvolution methods were developed and validated on specific datasets and perform poorly on unseen data. We developed Physics-Guided Deep Image Prior network for Stain deconvolution (PGDIPS), a method that combines a novel optical physics model and a self-supervised deep neural network to perform deconvolution for various classes and any number of stains, without the need of training data. PGDIPS outperformed state-of-the-art approaches for the deconvolution of conventional stain combinations, enabled analysis of previously unsupported special stains, and provided superior interpretability by explicitly encoding representations for stain properties and the light transmittance/absorbance process. PGDIPS is publicly available as an end-to-end off-the-shelf tool that does not require data curation, domain knowledge or high computation power.

bioinformatics↗