Biology subjects

Wang, M. X.

Publications and source records attributed to Wang, M. X..

7 recordsLinked to original sources

bioRxiv2025

Seqwin: Ultrafast Identification of Signature Sequences in Microbial Genomes

MotivationPolymerase chain reaction (PCR) enables rapid, cost-effective diagnostics but requires prior identification of genomic regions that allow sensitive and specific detection of target microbial groups, herein referred to as microbial signature sequences. We introduce Seqwin, an open-source framework designed to automate microbial genome signature discovery. Tens of thousands of microbial genomes are now available for a single species, limiting the application of existing manual and automated approaches for identifying signatures. Modern approaches that are capable of leveraging all available microbial genomes will ensure sensitive and accurate DNA signature identification and enable robust pathogen detection for clinical, environmental, and public health applications. ResultsSeqwin builds weighted pan-genome minimizer graphs and uses a traversal algorithm to identify signature sequences that occur frequently in target genomes but remain rare in non-targets. Unlike earlier tools that depend on strict presence or absence of sequences, Seqwin accommodates natural sequence variation and scales to very large genome collections. When applied to genomes from C. difficile, M. tuberculosis, and S. enterica, Seqwin recovered more high-quality signatures than alternative methods with lower computational burden. Seqwins analysis of nearly 15,000 S. enterica genomes yielded over 200 candidate signatures in 5 minutes. Seqwin provides an open-source solution for the long-standing need for scalable microbial signature discovery and diagnostic assay design. Availability and ImplementationSeqwin is freely available for academic use (https://github.com/treangenlab/Seqwin) and can be installed via Bioconda. Benchmarking datasets, outputs, and scripts are available on Zenodo https://doi.org/10.5281/zenodo.19176444. Contacttreangen@rice.edu, xw66@rice.edu Supplementary MaterialsProvided as separate PDF and data files.

bioinformatics↗

bioRxiv2025

DFFB suppresses interferon to enable cancer persister cell regrowth

Oncogene targeted cancer therapies can provide deep responses but frequently suffer from acquired resistance.1 Therapeutic approaches to treat tumours which have acquired drug resistance are complicated by continual tumour evolution and multiple co-occurring resistance mechanisms.2,3 Rather than treating resistance after it emerges, it may possible to prevent it by inhibiting the adaptive processes which initiate resistance but these are poorly understood.4 Here we report that residual cancer persister cells that survive oncogene targeted therapy are growth arrested by drug stress-induced intrinsic Type I interferon (IFN) signaling. To escape growth arrest, persister cells leverage apoptotic machinery to transcriptionally suppress interferon-stimulated genes (ISGs). Mechanistically, persister cells sublethally engage apoptotic caspases to activate DNA endonuclease DNA Fragmentation Factor B (DFFB, also known as Caspase-Activated DNase (CAD)) which induces DNA damage, mutagenesis, and stress response factor Activating Transcription Factor 3 (ATF3). ATF3 limits Activator Protein-1 (AP1)-mediated ISG expression sufficiently to allow persister cell regrowth. Persister cells deficient in DFFB or ATF3 exhibit high ISG expression and are consequently unable to regrow. Therefore, sublethal apoptotic stress paradoxically promotes regrowth of residual cancer cells that survive drug treatment.

cancer biology↗

bioRxiv2025

Antigenic cancer persister cells survive direct T cell attack

Drug-tolerant persister cancer cells were first reported fifteen years ago as a quiescent, reversible cell state which tolerates unattenuated cytotoxic drug stress. It remains unknown whether a similar phenomenon contributes to immune evasion. Here we report a persister state which survives weeks of direct cytotoxic T lymphocyte (CTL) attack. In contrast to previously known immune evasion mechanisms that avoid immune attack, antigenic persister cells robustly activate CTLs which deliver Granzyme B, secrete IFN{gamma}, and induce tryptophan starvation resulting in apoptosis initiation. Instead of dying, persister cells paradoxically leverage apoptotic caspase activity to avoid inflammatory death. Furthermore, persister cells acquire mutations and epigenetic changes which enable outgrowth of CTL-resistant cells. Persister cell features are enriched in inflamed tumors which regressed during immunotherapy in vivo and in surgically resected human melanoma tissue under immune stress ex vivo. These findings reveal a persister cell state which is a barrier to immune-mediated tumor clearance. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/643359v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1ca8905org.highwire.dtl.DTLVardef@1e9b584org.highwire.dtl.DTLVardef@8bf43eorg.highwire.dtl.DTLVardef@504918_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2023

Olivar: fully automated and variant aware primer design for multiplex tiled amplicon sequencing of pathogen genomes

Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 2 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly. Here we present Olivar, a first step towards a fully automated, variant-aware design of tiled amplicons for pathogen genomes. Olivar converts each nucleotide of the target genome into a numeric risk score, capturing undesired sequence features that should be avoided. In a direct comparison with PrimalScheme, we show that Olivar has fewer SNPs overlapping with primers and predicted PCR byproducts. We also compared Olivar head-to-head with ARTIC v4.1, the most widely used primer set for SARS-CoV-2 sequencing, and show Olivar yields similar read mapping rates ([~]90%) and better coverage to the manually designed ARTIC v4.1 amplicons. We also evaluated Olivar on real wastewater samples and found that Olivar had up to 3-fold higher mapping rates while retaining similar coverage. In summary, Olivar automates and accelerates the generation of tiled amplicons, even in situations of high mutation frequency and/or density. Olivar is available as a web application at https://olivar.rice.edu. Olivar can also be installed locally as a command line tool with Bioconda. Source code, installation guide and usage are available at https://github.com/treangenlab/Olivar.

bioinformatics↗

bioRxiv2021

Experimental Confirmation of Multiple Co-Existent DNA Secondary Structures using Low-Yield Bisulfite Sequencing

Predicting DNA secondary structures is critical to a broad range of applications involving single-stranded DNA (ssDNA), yet remains an open problem. Existing prediction models are limited by insufficient experimental data, due to a lack of high-throughput methods to study DNA structures, in contrast to RNA structures. Here, we present a method for profiling DNA secondary structures using multiplexed low-yield bisulfite sequencing (MLB-seq), which examines the chemical accessibility of cytosines in thousands of different oligonucleotides. By establishing a probability-based model to evaluate the consensus probability between MLB-seq data and structures proposed using NUPACK software, we identified the secondary structures of individual ssDNA molecules and estimated the distribution of multiple secondary structures in solution. We studied the structures of 1,057 human genome subsequences and experimentally confirmed that 84% adopted two or more structures. MLB-seq thus enables high-throughput ssDNA structure profiling and will benefit the design of probes, primers, aptamers, and genetic regulators.

molecular biology↗

bioRxiv2020

Rare coding variants in 35 genes associate with circulating lipid levels: a multi-ancestry analysis of 170,000 exomes

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency<1%) predicted damaging coding variation using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels. Ten of these: ALB, SRSF2, JAK2, CREB3L3, TMEM136, VARS, NR1H3, PLA2G12A, PPARG and STAB1 have not been implicated for lipid levels using rare coding variation in population-based samples. We prioritize 32 genes identified in array-based genome-wide association study (GWAS) loci based on gene-based associations, of which three: EVI5, SH2B3, and PLIN1, had no prior evidence of rare coding variant associations. Most of the associated genes showed evidence of association in multiple ancestries. Also, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes, and for genes closest to GWAS index single nucleotide polymorphisms (SNP). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

genetics↗

bioRxiv2020

Varying perivascular astroglial endfoot dimensions along the vascular tree maintain perivascular-interstitial flux through the cortical mantle

The glymphatic system is a recently defined brain-wide network of perivascular spaces along which cerebrospinal fluid (CSF) and interstitial solutes exchange. Astrocyte endfeet encircling the perivascular space form a physical barrier in between these two compartments, and fluid and solutes that are not taken up by astrocytes move out of the perivascular space through the junctions in between astrocyte endfeet. However, little is known about the anatomical structure and the physiological roles of the astrocyte endfeet in regulating the local perivascular exchange. Here, visualizing astrocyte endfoot-endfoot junctions with immunofluorescent labeling against the protein megalencephalic leukoencephalopathy with subcortical cysts-1 (MLC1), we characterized endfoot dimensions along the mouse cerebrovascular tree. We observed marked heterogeneity in endfoot dimensions along vessels of different sizes, and of different types. Specifically, endfoot size was positively correlated with the vessel diameters, with large vessel segments surrounded by large endfeet and small vessel segments surrounded by small endfeet. This association was most pronounced along arterial, rather than venous segments. Computational modeling simulating vascular trees with uniform or varying endfeet dimensions demonstrates that varying endfoot dimensions maintain near constant perivascular-interstitial flux despite correspondingly declining perivascular pressures along the cerebrovascular tree through the cortical depth. These results describe a novel anatomical feature of perivascular astroglial endfeet and suggest that endfoot heterogeneity may be an evolutionary adaptation to maintain perivascular CSF-interstitial fluid exchange through deep brain structures.

neuroscience↗