Biology subjects

Wan, Y.-W.

Publications and source records attributed to Wan, Y.-W..

15 recordsLinked to original sources

bioRxiv2026

Evaluation of Oxford Nanopore Sequencing for Antimicrobial Resistance Surveillance in Salmonella: Comparison with Phenotypic Antimicrobial Susceptibility in a Large-Scale Study

Salmonella is a major zoonotic foodborne pathogen, and antimicrobial resistance (AMR) in Salmonella presents a significant public health challenge. Whole-genome sequencing (WGS) offers a more rapid and comprehensive method for AMR characterization compared to conventional antimicrobial susceptibility testing (AST), supporting antimicrobial therapy and surveillance efforts. In this study, Oxford Nanopore Technology (ONT)-based WGS was performed on 1,490 Salmonella isolates collected through nationwide surveillance in Taiwan in 2025. Genotypic resistance inferred from WGS data was compared with phenotypic AST results to assess the performance of ONT-WGS. Overall, WGS-inferred resistance showed high concordance with phenotypic resistance for most antimicrobials. However, major genotype- phenotype discordance was observed, attributed to four categories: (i) breakpoint-dependent classification, (ii) reduced or absent phenotypic expression of resistance genes, (iii) MIC modulation by ramAp, and (iv) absence of known AMR determinants. Notable discrepancies included tigecycline resistance without known genetic determinants, nalidixic acid resistance linked to ramAp-mediated MIC elevation, and a high prevalence of colistin resistance (35.4%) in S. Enteritidis without identifiable AMR determinants. Additionally, a significant proportion of ESBL- and AmpC-producing isolates were classified as susceptible or intermediate to cefotaxime and ceftazidime under CLSI criteria, highlighting the potential for misclassification and treatment failure. These findings demonstrate that ONT-WGS enables accurate, comprehensive AMR characterization, offering direct identification of AMR determinants and minimizing misclassification due to breakpoint-based AST interpretations. When interpreted appropriately, WGS can support better antimicrobial selection and serve as a valuable alternative to conventional susceptibility testing.

microbiology↗

bioRxiv2024

Multi-omics delineate growth factor network underlying exercise effects in an Alzheimer's mouse model

Physical exercise represents a primary defense against age-related cognitive decline and neurodegenerative disorders like Alzheimers disease (AD). To impartially investigate the underlying mechanisms, we conducted single-nucleus transcriptomic and chromatin accessibility analyses (snRNA-seq and ATAC-seq) on the hippocampus of mice carrying AD-linked NL-G-F mutations in the amyloid precursor protein gene (APPNL-G-F) following prolonged voluntary wheel-running exercise. Our study reveals that exercise mitigates amyloid-induced changes in both transcriptomic expression and chromatin accessibility through cell type-specific transcriptional regulatory networks. These networks converge on the activation of growth factor signaling pathways, particularly the epidermal growth factor receptor (EGFR) and insulin signaling, correlating with an increased proportion of immature dentate granule cells and oligodendrocytes. Notably, the beneficial effects of exercise on neurocognitive functions can be blocked by pharmacological inhibition of EGFR and the downstream phosphoinositide 3-kinases (PI3K). Furthermore, exercise leads to elevated levels of heparin-binding EGF (HB-EGF) in the blood, and intranasal administration of HB-EGF enhances memory function in sedentary APPNL-G-F mice. These findings offer a panoramic delineation of cell type-specific hippocampal transcriptional networks activated by exercise and suggest EGF-related growth factor signaling as a druggable contributor to exercise-induced memory enhancement, thereby suggesting therapeutic avenues for combatting AD-related cognitive decline.

animal behavior and cognition↗

bioRxiv2023

Differential effects of MATR3 variants on its cryptic splicing repression function

MATR3 is an RNA-binding protein implicated in neurodegenerative and neurodevelopmental diseases. However, little is known regarding the role of MATR3 in cryptic splicing within the context of functional genes and how disease-associated variants impact this function. We show that loss of MATR3 leads to cryptic exon inclusion in many transcripts. We reveal that ALS-linked S85C pathogenic variant reduces MATR3 solubility but does not impair RNA binding. In parallel, we report a novel neurodevelopmental disease-associated M548T variant, located in the RRM2 domain, which reduces protein solubility and impairs RNA binding and cryptic splicing repression functions of MATR3. Altogether, our research identifies cryptic events within functional genes and demonstrates how disease-associated variants impact MATR3 cryptic splicing repression function.

molecular biology↗

bioRxiv2022

Discovery of gene-gene co-perturbation through big data

Millions of RNA sequencing samples have been deposited into public databases, providing a rich resource for biological research. These datasets encompass tens of thousands of experiments and offer comprehensive insights into human cellular regulation. However, a major challenge is how to integrate these experiments that acquired at different conditions. We propose a new statistical tool based on beta-binomial distributions that can construct robust gene co-regulation network (CoRegNet) across tens of thousands of experiments. Our analysis of over 12,000 experiments involving human tissues and cells shows that CoRegNet significantly outperforms existing gene co-expression-based methods. Although the majority of the genes are linearly co-regulated, we did discover an interesting set of genes that are non-linearly co-regulated; half of the time they change in the same direction and the other half they change in the opposite direction. Additionally, we identified a set of gene pairs that follows the Simpsons paradox. By utilizing public domain data, CoRegNet offers a powerful approach for identifying functionally related gene pairs, thereby revealing new biological insights.

bioinformatics↗

bioRxiv2022

MeCP2 regulates Gdf11, a dosage-sensitive gene critical for neurological function

Loss- and gain-of-function of MeCP2 causes Rett syndrome (RTT) and MECP2 duplication syndrome (MDS), respectively. MeCP2 binds methyl-cytosines to finely tune gene expression in the brain, though identifying genes robustly regulated by MeCP2 has been difficult. By integrating multiple transcriptomics datasets, we identified that MeCP2 finely regulates Growth differentiation factor 11 (Gdf11). Gdf11 is down-regulated in RTT mouse models and is inversely up-regulated in MDS mouse models. Strikingly, genetically normalizing Gdf11 dosage levels improved several behavioral deficits in a mouse model of MDS. Next, we discovered that losing one copy of Gdf11 alone was sufficient to cause multiple neurobehavioral deficits in mice, most notably hyperactivity and decreased learning and memory. This decrease in learning and memory was not due to changes in proliferation or numbers of progenitor cells in the hippocampus. Lastly, loss of one copy of Gdf11 decreased longevity and survival in mice, corroborating its putative role in aging. Our data demonstrate that Gdf11 dosage is important for brain function.

neuroscience↗

bioRxiv2022

Most High Throughput Expression Data Sets are Underpowered

Researchers handicap their high-throughput sequencing experiments when they do not perform enough biological replicates. Given that biological tissues can be highly variable, too few replicates will lead to false negatives, false positives, irreproducibility, and failure to detect real biological signatures. We propose that at least six biological replicates per condition becomes the standard for high-throughput expression datasets.

bioinformatics↗

bioRxiv2021

MECP2pedia: A Comprehensive Transcriptome Portal for MECP2 Disease Research

Mutations in MeCP2 result in a crippling neurological disease, but we lack a lucid picture of MeCP2s molecular role. Focusing on individual transcriptomic studies yields inconsistent differentially expressed genes. We have aggregated and homogeneously processed modern public MeCP2 transcriptome data, which we present in a web portal. With this big data, we discovered a commonly perturbed core set of genes that transcends the limitations of any individual study. We then found distinct consistently up and downregulated subsets within these genes. We observe enrichment for this mouse core in other species MeCP2 models and see overlap between this core and ASD models. Analysis of signal to noise finds that many studies lack enough biological replicates. By integrating and examining transcriptomic data at scale, we have generated a valuable resource and insight on MeCP2 function.

bioinformatics↗

bioRxiv2021

Synergy of chemotherapy and macrophage depletion leads to T cell memory activation and durable triple negative breast cancer regression

Immunosuppressive elements within the tumor microenvironment such as Tumor Associated Macrophages (TAMs) can present a barrier to successful anti-tumor responses by cytolytic T cells. We employed preclinical syngeneic p53 null mouse models of triple negative breast cancer (TNBC) to develop a treatment regimen that harnessed the immunostimulatory effects of low-dose cyclophosphamide coupled with the pharmacologic inhibition of TAMs using either a small molecule CSF1R inhibitor or an anti-CSF1R antibody. This therapeutic combination was used to successfully treat several highly aggressive TNBC murine mammary tumors and lung metastasis. Using this regimen and single cell RNA sequencing we characterized tumor infiltrating lymphocytes (TILs) including helper T cells and antigen-presenting B cells that were highly enriched in good responders to combination therapy. Using high dimensional imaging techniques, we identified the close spatial localization of B220+ CD86+ activated B cells and CD4+ T cells in tertiary lymphoid structures that were present up to 6 weeks post-treatment in one model that also exhibited long-term tumor regression post-treatment. We also characterized the transcriptional and metabolic heterogeneity of TAMS in these two closely related claudin-low/mesenchymal subtype tumor models with differential treatment responses. A murine TAM signature derived from the T12 model is highly expressed and conserved in human claudin-low breast cancers, and high expression of the T12 signature correlated with reduced overall survival. This T12 tumor TAM signature may help identify human claudin-low breast cancer patients that will benefit from the combination of cyclophosphamide and anti-CSF1R therapy. These studies illustrate the complexity of the tumor immune microenvironment and highlight different immune responses that result from rationale combinations of immunotherapy. SignificanceA treatment regimen that harnessed the immunostimulatory effects of cyclophosphamide coupled with the inhibition of CSF1R was used to successfully treat several highly aggressive claudin-low TNBC murine mammary tumors and lung metastasis.

cancer biology↗

bioRxiv2020

The bone microenvironment invigorates metastatic seeds for further dissemination

Metastasis has been considered as the terminal step of tumor progression. However, recent clinical studies suggest that many metastases are seeded from other metastases, rather than primary tumors. Thus, some metastases can further spread, but the corresponding pre-clinical models are lacking. By using several approaches including parabiosis and an evolving barcode system, we demonstrated that the bone microenvironment facilitates breast and prostate cancer cells to further metastasize and establish multi-organ secondary metastases. Importantly, dissemination from the bone microenvironment appears to be more aggressive compared to that from mammary tumors and lung metastases. We further uncovered that this metastasis-promoting effect is independent from genetic selection, as single cell-derived cancer cell populations (SCPs) exhibited enhanced metastasis capacity after being extracted from the bone microenvironment. Taken together, our work revealed a previously unappreciated effect of the bone microenvironment on metastasis evolution, and suggested a stable reprogramming process that engenders cancer cells more metastatic.

cancer biology↗

bioRxiv2020

Phenotypic plasticity of ER+ breast cancer in the bone microenvironment

ER+ breast cancer exhibits a strong bone-tropism in metastasis. How the bone microenvironment impacts the ER signaling and endocrine therapies remains poorly understood. Here, we discover that the osteogenic niche transiently reduces ER expression and activities specifically in bone micrometastases (BMMs), leading to endocrine resistance. This is mediated by gap junctions and paracrine FGF/PDGF signaling, which together generate a stable "memory": cancer cells extracted from bone remain resistant to endocrine therapies for several generations. Using single cell-derived populations (SCPs), we demonstrated that this process is independent of clonal selection, and represents an EZH2-mediated epigenomic reprogramming. EZH2 drives ER+ BMMs toward a basal and stem-like state. EZH2 inhibition reverses endocrine resistance. Our data demonstrates how epigenomic adaptation to the bone microenvironment drives phenotypic plasticity of metastatic seeds and alters their therapeutic responses together with clonal selection, and provides insights into the clinical enigma of ER+ metastatic recurrences despite endocrine therapies.

cancer biology↗

bioRxiv2020

Modulating glial genes involved in synaptic function mitigates pathogenesis and behavioral deficits in a Drosophila model of Huntington's Disease

Most research on neurodegenerative diseases has focused on neurons, yet glia help form and maintain the synapses whose loss is so prominent in these conditions. To investigate the contributions of glia to Huntingtons disease (HD), we studied transcriptomic changes in HD human, HD mice, and Drosophila expressing human mutant Huntingtin (mHTT) in either glia, neurons or both. A large portion of conserved genes are concordantly dysregulated across the three species; we tested these genes in a high-throughput behavioral assay and found that downregulation of genes involved in synapse assembly mitigated pathogenesis and behavioral deficits. To our surprise, mitigating glial pathogenesis by dNRXN3 knockdown was sufficient to improve the phenotype of flies expressing mHTT in neurons, suggesting that mHTTs toxic effects in glia ramify throughout the brain. This supports a model in which dampening synaptic function is protective because it attenuates the excitotoxicity that characterizes HD.

systems biology↗

bioRxiv2019

Loss of Dnmt3a dependent methylation in inhibitory neurons impairs neural function through a mechanism that impacts Rett syndrome

Methylated cytosine is an effector of epigenetic gene regulation. In the mammalian brain, the DNA methyltransferase, Dnmt3a, is the sole \"writer\" of atypical non-CpG methylation (mCH), and methyl CpG binding protein 2 (MeCP2) is the only known \"reader\" for mCH. We set out to determine if MeCP2 is the sole reader for Dnmt3a dependent methylation by comparing mice lacking either Dnmt3a or MeCP2 in GABAergic inhibitory neurons. Loss of either the writer or the reader causes overlapping and distinct features from the behavioral to the molecular level. Loss of Dnmt3a results in global loss of mCH and a small subset of mCG sites resulting in more widespread transcriptional alterations and severe neurological dysfunction than seen upon MeCP2 loss. These data indicate that MeCP2 is responsible for reading part of the Dnmt3a dependent methylation in the brain. Importantly, the impact of MeCP2 on genes differentially expressed in both cKO models shows a strong dependence on mCH, but not Dnmt3a dependent mCG, consistent with mCH playing a central role in the pathogenesis of Rett Syndrome.

neuroscience↗

bioRxiv2019

Molecular profiling predicts meningioma recurrence and reveals loss of DREAM complex repression in aggressive tumors

Meningiomas account for one-third of all primary brain tumors. Although typically benign, about 20% of meningiomas are aggressive, and despite the rigor of the current histopathological classification system, there remains considerable uncertainty in predicting tumor behavior. Here, we analyzed 160 tumors from all three WHO grades (I-III) using clinical, gene expression and sequencing data. Unsupervised clustering analysis identified three molecular types (A, B, and C) that reliably predicted recurrence. These groups did not directly correlate with the WHO grading system, which would classify more than half of the tumors in the most aggressive molecular type as benign. Transcriptional and biochemical analyses revealed that aggressive meningiomas involve loss of the repressor function of the DREAM complex, which results in cell cycle activation; only tumors in this category tend to recur after full resection. These findings should improve our ability to predict recurrence and develop targeted treatments for these clinically challenging tumors.\n\nSignificance StatementMeningiomas are the most common primary brain tumors. Although most of these tumors are benign, one-fifth will recur despite apparently complete resection. Several studies have demonstrated that genomic approaches can yield important insights into the biology of these tumors. We performed RNA sequencing and whole-exome sequencing of 160 tumors from 140 patients, which identified three distinct groups of meningioma that correlate with recurrence better than the current WHO grading system. Our analysis also revealed that the most aggressive type was characterized by loss of the repressive DREAM complex. These findings should improve prognostication for patients and lead to viable therapeutic targets.

cancer biology↗

bioRxiv2019

Functional dissection of Alzheimer’s disease brain gene expression signatures in humans and mouse models

Human brain transcriptomes can highlight biological pathways associated with Alzheimers disease (AD); however, challenges remain to link expression changes with causal triggers. We have examined 30 AD-associated, gene coexpression modules from human brains for overlap with 251 differentially-expressed gene sets from mouse brain RNA-sequencing experiments, including from models of AD and other neurodegenerative disorders. Human-mouse overlaps highlight responses to amyloid versus neurofibrillary tangle pathology and further reveal age- and sex-dependent expression signatures for AD progression. Human coexpression modules enriched for neuronal and/or microglial genes overlap broadly with signatures from mouse models of AD, Huntingtons disease, Amyotrophic Lateral Sclerosis, and also aging. Several human AD coexpression modules, including those implicated in the unfolded protein response and oxidative phosphorylation, were not activated in AD models, but instead were detected following other, unexpected mouse genetic manipulations. Our results comprise a powerful, cross-species resource and pinpoint experimental models for diverse features of AD pathophysiology from human brain transcriptomes.

systems biology↗

bioRxiv2017

Bias toward long gene misregulation in synaptic disorders can be an artefact of amplification-based methods

Several recent studies have suggested that genes that are longer than 100 kilobases are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in Mecp2-mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, the statistical significance of these results needs to be re-evaluated. Here, we show that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-Sequencing datasets, particularly in genes with low fold-changes, disappeared after accounting for baseline variability estimated from randomized control samples. As we found no similar bias with NanoString technology, this long-gene bias seems to be particular to PCR amplification-based platforms. In contrast, authentic long gene effects, such as those caused by topoisomerase inhibition, can be detected even after adjustment for baseline variability. Accurate detection of length-dependent trends requires establishing a baseline from randomized control samples.\n\nHIGHLIGHTSO_LILength-dependent gene misregulation is not intrinsic to Mecp2 disruption.\nC_LIO_LITopoisomerase inhibition produces an authentic long gene bias.\nC_LIO_LIPCR amplification-based high-throughput datasets are biased toward long genes.\nC_LI

neuroscience↗