Biology subjects

Chang, T.

Publications and source records attributed to Chang, T..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

United States PRRSV 1-4-4 L1C.5 isolate demonstrates similar pathogenicity to a historic Chinese highly pathogenic PRRSV

Porcine reproductive and respiratory syndrome virus (PRRSV) is a major economic and animal health burden on the United States swine industry due to morbidity- and mortality-associated losses affecting all stages of pig production. Currently, a large proportion of losses are attributed to a highly virulent PRRSV strain, PRRSV 1-4-4 L1C.5. To benchmark the virulence of PRRSV 1-4-4 L1C.5, a study was conducted to compare pathogenicity of this contemporary strain to a historical Chinese highly pathogenic PRRSV (HP-PRRSV) strain, JXwn06, that devastated the Chinese and other Asian swine industries since 2006, as well as a moderately virulent United States PRRSV strain, MN184, considered to be one of the most virulent PRRSV strains circulating in the United States in the early 2000s. Weaned pigs were inoculated with PRRSV strains L1C.5, JXwn06, MN184, or mock inoculum and necropsied at 2, 6, and 10 days post inoculation, or as needed due to severe disease. Clinical metrics, viral loads, cytokine concentrations, PRRSV-specific antibody concentrations, and pathology were compared between treatment groups to compare pathogenicity. Results indicate a high degree of similarity disease dynamics between L1C.5 and JXwn06 animals that diverged from MN184 and mock animals. Findings indicate L1C.5 and JXwn06 cause more severe morbidity and mortality in weaned pigs than MN184. Results may be applied to develop more effective strategies for mitigating PRRSV 1-4-4 L1C.5 outbreaks currently plaguing the United States swine industry.

microbiology↗

bioRxiv2025

Suite3D: Volumetric cell detection for two-photon microscopy

In two-photon imaging of neuronal activity it is increasingly common to acquire 3-dimensional volumes. However, these volumes are typically processed plane by plane, leading to uncorrected axial movement, duplicated cells across planes, reduced signal-to-noise ratio per cell, and missed cells. To overcome these limitations, we introduce Suite3D, a volumetric cell detection pipeline. Suite3D corrects for rigid and non-rigid 3D brain motion, both lateral and axial. It detects neurons using 3D correlation, improving detectability. Finally, it performs 3D segmentation, identifying cells across imaging planes. We validated Suite3D with data from conventional multi-plane microscopes and advanced volumetric microscopes, at multiple resolutions and in multiple brain regions, and with ground truth anatomical labelling. Suite3D successfully detected cells appearing on multiple imaging planes, improving cell detectability and signal quality, avoiding duplications, and running faster than a prior volumetric pipeline. Suite3D offers a powerful solution for analyzing volumetric two-photon data.

neuroscience↗

bioRxiv2025

Single-cell-guided identification of logic-gated antigen combinations for designing effective and safe CAR therapy

Chimeric antigen receptor (CAR) T-cell therapy has revolutionized the treatment of hematological malignancies. However, its application in solid tumors remains limited because single targets are unlikely to suffice due to tumor antigen heterogeneity and off-tumor toxicities. To overcome these obstacles, we developed LogiCAR designer, a computational approach that utilizes single-cell transcriptomics data from patient tumors to systematically identify the cancer-specific antigen circuits with logic gates ("AND," "OR," and "NOT") that target the majority of cancer cells in a tumor while sparing normal cells and tissues as much as possible. LogiCAR designer efficiently scales to higher-order antigen combinations involving up to five genes. Applied to a large-scale dataset encompassing approximately 2 million cells (including > 620k tumor cells) from 342 clinical patient samples across all major breast cancer subtypes, LogiCAR designer identified antigen circuits with enhanced tumor-targeting efficacy and improved safety profiles compared to both previously reported circuits and single-target therapies in clinical trials. However, even these optimized shared circuits still proved insufficient for some patients. We hence systematically studied LogiCAR designers ability to identify highly effective CAR circuits that are individualized to each patient. Remarkably, such personalized CAR circuits provide estimated tumor-targeting efficacy tantamount to complete response in 76% of patients and partial response for all patients. Taken together, this analysis is the first systematic quantification of the efficacy and safety of all possible CAR circuits, showing that: (a) the quality of existing solutions leaves much to be desired; (b) the ability of shared circuits optimized across many patients is moderate, and finally, (c) individually tailored circuits offer significantly higher tumor-targeting efficacies for patients. LogiCAR designer offers a rigorous, data-driven way to facilitate the rational design of safe and effective CAR-based immunotherapies for cancer. Statement of Significance Development of a computational approach that efficiently identifies logic-gated CAR target combinations, called circuits, from single-cell transcriptomics, addressing a critical unmet clinical need. Application to the largest ensemble of breast cancer datasets to date, comprising [~]2 million cells (> 620k tumor cells) from 17 clinical cohorts, to identify CAR circuits predicted to be effective. Comprehensive safety profiling of candidate circuits spanning major tissues at both RNA and protein levels. Logic-gated CAR circuits generated by our pipeline address tumor heterogeneity and achieve efficacy and safety scores that surpass clinical trial and previously computationally identified circuits. Individualized rational CAR design offers a transformative approach to deliver precision-engineered CAR therapies with unprecedented efficacy.

bioinformatics↗

bioRxiv2025

Lasting effect of psilocybin on sociability can be blocked by DNA methyltransferase inhibition

The recent renaissance in research on psychedelics such as psilocybin has highlighted their therapeutic potential including their lasting influences on brain function. Here we report that a single systemic administration of the serotonergic psychedelic psilocybin can durably promote social behaviour in the Cntnap2-knockout mouse model of autism. This effect can be blocked by pharmacological inhibition of DNA methyltransferase I, indicating an epigenetic mechanism underlying the long-lasting effect of psilocybin.

neuroscience↗

bioRxiv2024

Metabolic reprogramming tips vaccinia virus infection outcomes by stabilizing interferon-g induced IRF1

Interferon (IFN) induced activities are critical, early determinants of immune responses and infection outcomes. A key facet of IFN responses is the upregulation of hundreds of mRNAs termed interferon-stimulated genes (ISGs) that activate intrinsic and cell-mediated defenses. While primary interferon signaling is well-delineated, other layers of regulation are less explored but implied by aberrant ISG expression signatures in many diseases in the absence of infection. Consistently, our examination of tonic ISG levels across uninfected human tissues and individuals revealed three ISG subclasses. As tissue identity and many comorbidities with increased virus susceptibility are characterized by differences in metabolism, we characterized ISG responses in cells grown in media known to favor either aerobic glycolysis (glucose) or oxidative phosphorylation (galactose supplementation). While these conditions over time had a varying impact on the expression of ISG RNAs, the differences were typically greater between treatments than between glucose/galactose. Interestingly, extended interferon-priming led to divergent expression of two ISG proteins: upregulation of IRF1 in IFN-{gamma}/glucose and increased IFITM3 in galactose by IFN- and IFN-{gamma}. In agreement with a hardwired response, glucose/galactose regulation of interferon-{gamma} induced IRF1 is conserved in unrelated mouse and cat cell types. In galactose conditions, proteasome inhibition restored interferon-{gamma} induced IRF1 levels to that of glucose/interferon-{gamma}. Glucose/interferon-{gamma} decreased replication of the model poxvirus vaccinia at low MOI and high MOIs. Vaccinia replication was restored by IRF1 KO. In contrast, but consistent with differential regulation of IRF1 protein by glucose/galactose, WT and IRF1 KO cells in galactose media supported similar levels of vaccinia replication regardless of IFN-{gamma} priming. Also associated with glucose/galactose is a seemingly second block at a very late stage in viral replication which results in reductions in herpes- and poxvirus titers but not viral protein expression. Collectively, these data illustrate a novel layer of regulation for the key ISG protein, IRF1, mediated by glucose/galactose and imply unappreciated subprograms embedded in the interferon response. In principle, such cellular circuitry could rapidly adapt immune responses by sensing changing metabolite levels consumed during viral replication and cell proliferation.

microbiology↗

bioRxiv2024

δ-α cell-to-cell interactions modulate pancreatic islet Ca2+ oscillation modes

Glucose-induced pancreatic islet hormone release is tightly coupled with oscillations in cytoplasmic free Ca2+ concentration of islet cells, which is regulated by a complex interplay between intercellular and intracellular signaling. {delta} cells, which entangle with cells located at the islet periphery, are known to be important paracrine regulators. However, the role of {delta} cells in regulating Ca2+ oscillation pattern remains unclear. Here we show that {delta}- cell-to-cell interactions are the source of variability in glucose-induced Ca2+ oscillation pattern. Somatostatin secreted from {delta} cells prolonged the islets oscillation period in an cell mass-dependent manner. Pharmacological and optogenetic perturbations of {delta}- interactions led islets to switch between fast and slow Ca2+ oscillations. Continuous adjustment of {delta}- coupling strength caused the fast oscillating islets to transition to mixed and slow oscillations. We developed a mathematical model, demonstrating that the fast-mixed-slow oscillation transition is a Hopf bifurcation. Our findings provide a comprehensive understanding of how {delta} cells modulate islet Ca2+ dynamics and reveal the intrinsic heterogeneity of islets due to the structural composition of different cell types. HighlightsO_LISomatostatin slows down islet Ca2+ oscillations in an cell mass-dependent manner. C_LIO_LIPharmacological and optogenetic perturbations of {delta}- interaction cause islet Ca2+ oscillation mode switching. C_LIO_LIContinuous tuning of {delta}- interaction strength induces fast-mixed-slow oscillation transition successively. C_LIO_LIMathematical modeling shows the fast-mixed-slow oscillation transition as a Hopf bifurcation. C_LI

systems biology↗

bioRxiv2024

Alpine lakes harbor diverse, endemic and structurally unique RNA viruses

Alpine lakes, characterized by isolation, low temperatures, oligotrophic conditions, and intense ultraviolet radiation, remain a poorly explored ecosystem for RNA viruses. Here, we present the first comprehensive metatranscriptomic study of RNA viruses in Lake Nam Co, a high-altitude alkaline saline lake on the Tibetan Plateau. Using a combination of sequence- and structure-based homology searches, we identified 742 RNA virus species, including 383 novel genus-level groups and 84 novel family-level groups exclusively found in Lake Nam Co. These findings significantly expand the known diversity of the Orthornavirae, uncovering evolutionary adaptations such as permutated RNA-dependent RNA polymerase (RdRP) motifs and distinct RNA secondary structures. Notably, 14 previously unknown RNA virus families potentially infecting prokaryotes were predicted, broadening the known host range of RNA viruses and questioning the traditional assumption that RNA viruses predominantly target eukaryotes. The presence of auxiliary metabolic genes (AMGs) in viral genomes suggested that RNA viruses (families f.0102 and Nam-Co_family_51) exploit host energy production mechanisms in energy-limited alpine lakes. Low nucleotide diversity, SNP frequencies, and pN/pS ratios indicate strong purifying selection in Nam Co viral populations. Our findings offer insights into RNA virus evolution and ecology, highlighting the importance of extreme environments in uncovering hidden viral diversity, and further shed light into their potential ecological implications, particularly in the context of climate change. Significance StatementThis study unveils the hidden diversity and complexity of RNA viruses in the high-altitude ecosystem of Lake Nam Co, significantly expanding the known RNA virome. The discovery of novel viral clades, expanded potential host ranges, and unique evolutionary adaptations emphasizes the importance of exploring extreme environments to uncover viral diversity and evolutionary pathways. Our findings offer critical insights into viral evolution, host-virus interactions, and the ecological roles of RNA viruses, particularly in the context of climate change and environmental resilience.

microbiology↗

bioRxiv2024

PRISM: Multiplexed Profiling of RNA In-Situ through Single-round of Imaging in Three-Dimensional Tissue

Spatial RNA imaging has not been widely adopted because conventional fluorescence microscopy is limited to only a few channels, and the cyclic reactions needed to increase multiplexing in techniques such as sequential fluorescence in-situ hybridization (FISH) require sophisticated instrumentation. Here, we introduce Profiling of RNA In-situ through Single-round iMaging (PRISM), a method that expands coding capacity through color intensity grading. Using a radius vector filtering strategy to ensure the distinguishability of codewords in color space, PRISM achieves up to 64-plex color-barcoded RNA imaging in a single imaging round with conventional microscopes. We validate PRISMs versatility across various tissues by generating a 3D atlas of mouse embryonic development from E12.5 to E14.5, a quasi-3D tumor-normal transition landscape of human hepatocellular carcinoma (HCC), and a 3D cell atlas and subcellular RNA localization landscapes of mouse brain. Additionally, we show the critical role of cancer-associated fibroblasts (CAFs) in mediating immune infiltration and immune response heterogeneity within and between tumor microenvironments.

bioengineering↗

bioRxiv2024

Microenvironment Shapes Cell State, Plasticity, and Heterogeneity of Small Cell Lung Cancer

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intra-tumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the tumor microenvironment (TME) exhibits substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAF) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Together, our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLCs adaptable nature, opening possibilities for re-programming the intercellular communications that shape SCLC tumor states.

cancer biology↗

bioRxiv2023

Genetic, transcriptomic, histological, and biochemical analysis of progressive supranuclear palsy implicates glial activation and novel risk genes

Progressive supranuclear palsy (PSP) is a rare Parkinsonian disorder characterized by problems with movement, balance, cognition, and other symptoms. PSP differs from Alzheimers disease (AD) and other neurodegenerative diseases displaying abnormal forms of the microtubule-associated protein tau ("tauopathies") by the presence of pathology not only in neurons, but also in astrocytes and oligodendrocytes. Genetic contributors may mediate these differences, however much of PSP genetics remains unexplained. Here we conducted the largest genome-wide association study (GWAS) of PSP to date including 2,779 cases (2,595 neuropathologically-confirmed) and 5,584 controls and identified six independent PSP susceptibility loci with genome-wide significant (p < 5x10-8) associations including five known (MAPT, MOBP, STX6, RUNX2, SLCO1A2) and one novel locus (C4A). Integration with cell type-specific epigenomic annotations revealed a unique oligodendrocytic signature that distinguishes PSP from AD and Parkinsons disease. Candidate PSP risk gene prioritization using expression quantitative trait loci (eQTLs) identified oligodendrocyte-specific effects on gene expression in half of the genome-wide significant loci, as well as an association with elevated C4A expression in bulk brain tissue which may be driven by increased C4A copy number in PSP cases. Finally, histological studies demonstrated abnormal tau aggregates in oligodendrocytes that colocalize with C4 (complement) deposition. Integrating GWAS with functional studies including epigenomic and eQTL analyses, we identified potential causal roles for variation in MOBP, STX6, RUNX2, SLCO1A2, and C4A in the pathogenesis of PSP.

neuroscience↗

bioRxiv2023

Accurate prediction of RNA translation with a deep learning architecture

Accurate annotation of coding regions in RNAs is essential for understanding gene translation. We developed a deep neural network to directly predict and analyze translation initiation and termination sites from RNA sequences. Trained with human transcripts, our model learned hidden rules of translation control and achieved a near perfect prediction of canonical translation sites across entire human transcriptome. Surprisingly, this model revealed a new role of codon usage in regulating translation termination, which was experimentally validated. We also identified thousands of new open reading frames in mRNAs or lncRNAs, some of which were confirmed experimentally. The model trained with human mRNAs achieved high prediction accuracy of canonical translation sites in all eukaryotes and good prediction in polycistronic transcripts from prokaryotes or RNA viruses, suggesting a high degree of conservation in translation control. Collectively, we present a general and efficient deep learning model for RNA translation, generating new insights into the complexity of translation regulation.

molecular biology↗

bioRxiv2023

Spatiotemporal Mapping of brain cilia length and orientation reveals region-specific Oscillation

In this study, we conducted high-throughput spatiotemporal analysis of primary cilia length and orientation across 22 mouse brain regions. We developed automated image analysis algorithms, which enabled us to examine over 10 million individual cilia, generating the largest spatiotemporal atlas of cilia. We found that cilia length and orientation display substantial variations across different brain regions and exhibit fluctuations over a 24-hour period, with region-specific peaks during light-dark phases. Our analysis revealed unique orientation patterns of cilia at 45{degrees} intervals, suggesting that cilia orientation within the brain is not random but follows specific patterns. Using BioCycle, we identified circadian rhythms of cilia length in five brain regions: nucleus accumbens core, somatosensory cortex, and three hypothalamic nuclei. Our findings present novel insights into the complex relationship between cilia dynamics, circadian rhythms, and brain function, highlighting cilia crucial role in the brains response to environmental changes and regulation of time-dependent physiological processes. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/546950v3_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@153135corg.highwire.dtl.DTLVardef@11c1d7eorg.highwire.dtl.DTLVardef@d47014org.highwire.dtl.DTLVardef@10a65ca_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

Predicting tumor immune microenvironment and checkpoint therapy response of head & neck cancer patients from blood immune single-cell transcriptomics

The immune state of tumor microenvironment is crucial for determining immunotherapy response but is not readily accessible. Here we investigate if we can infer the tumor immune state from the blood and further predict immunotherapy response. First, we analyze a dataset of head and neck squamous cell carcinoma (HNSCC) patients with matched scRNA-Seq of peripheral blood mononuclear cells (PBMCs) and tumor tissues. We find that the tumor immune cell fractions of different immune cell types and many of the genes they express can be inferred from the matched PBMC scRNA-Seq. Second, analyzing another HNSCC dataset with PBMC scRNA-Seq and immunotherapy response, we find that the inferred ratio between tumor memory B and regulatory T cell fractions is predictive of immunotherapy response and is superior to the well-established cytolytic and exhausted T-cell signatures. Overall, these results showcase the potential of scRNA-Seq liquid biopsies in cancer immunotherapy, calling for their larger-scale testing. SignificanceThis head and neck cancer study demonstrates the potential of using blood single-cell transcriptomics to (1) infer the tumor immune status and (2) predict immunotherapy response from the tumor immune status inferred from blood. These results showcase the potential of single-cell transcriptomics liquid biopsies for further advancing personalized cancer immunotherapy.

bioinformatics↗

bioRxiv2022

Fraction of copy-number alterations significantly predicts survival following immunotherapy in a few cancers

Various studies have shown that high tumor mutation burden (TMB) may predict response to immune checkpoint therapy, at least in some cancer types 1,2. However, identifying patients with low TMB that are still likely to respond to cancer immunotherapy is an important open challenge. Recently, Spurr et al. 3 reported that the tumor aneuploidy score (AS), defined as the fraction of chromosome arms with arm-level copy number alterations in a sample, is predictive of survival following immunotherapy in low-TMB patients across multiple cancers. By re-analyzing the same data set by performing survival analysis in individual cancer types separately, we find that AS only significantly predicts survival in one single cancer indication. We further find that another metric conceptually related to the AS, the fraction of genome encompassed by copy number alterations (FGA), if called with a conventional copy number calling cutoff, has stronger predictive power than the AS proposed in 3, and that this observation holds even if the FGA and AS thresholds for presence/absence of copy number events are set comparably. However, with the current available data, even FGA can predict survival following immunotherapy in only a few cancer indications.

cancer biology↗

bioRxiv2022

Rapid and Signal Crowdedness-Robust In-Situ Sequencing through Hybrid Block Coding

Spatial transcriptomics technology has revolutionized our understanding of cell types and tissue organization, opening new possibilities for researchers to explore transcript distributions at subcellular levels. However, existing methods have limitations in resolution, sensitivity, or speed. To overcome these challenges, we introduce SPRINTseq (Spatially Resolved and signal-diluted Next-generation Targeted sequencing), an innovative in situ sequencing strategy that combines hybrid block coding and molecular dilution strategies. Our method enables fast and sensitive high-resolution data acquisition, as demonstrated by recovering over 142 million transcripts using a 108 gene panel from 453,843 cells from four mouse brain coronal slices in less than two days. Using this advanced technology, we uncover the cellular and subcellular molecular architecture of Alzheimers disease, providing additional information into abnormal cellular behaviors and their subcellular mRNA distribution. This improved spatial transcriptomics technology holds great promise for exploring complex biological processes and disease mechanisms.

genomics↗

bioRxiv2022

Genomic analyses identify key molecules and significant biological processes in LOC441461 treated gastric cancer cells

Gastric cancer (GC) remains one of the leading cancers globally with a high prevalence and high mortality rate. Currently, Long noncoding RNAs (lncRNAs) LOC441461 have been found to be related to cancer that regulates cell growth, apoptosis, and metastasis. However, the mechanisms of LOC441461 treated gastric cancer are still unknown. In this study, we aim to identify the key molecules and signaling pathways by analyzing the RNA-seq data. The GSE193700 was created by the Illumina NovaSeq 6000 (Homo sapiens). The KEGG and GO analyses indicated that Human papillomavirus infection and Epstein-Barr virus infection were the main biological processes during the knockdown of LOC441461 in gastric cancer. Moreover, we figured out several interactive genes including STAT1, IFIH1, ISG15, IRF7, IRF1, MX1, DDX58, IFIT1, RSAD2, and IFIT3. Our study may provide new knowledge on the treatment of gastric cancer.

bioinformatics↗

bioRxiv2022

Genomic analyses identify key molecules and significant signaling pathways in Sorafenib treated hepatocellular cancer cells

Sorafenib (Sfb) is a multikinase inhibitor that is significantly effective in killing liver cancer. However, the potential signaling pathways and mechanisms remain unknown. Here, we aim to identify the functional molecules and signaling pathways by analyzing the RNA-seq data. The GSE186280 was produced by the Illumina HiSeq 2000 (Homo sapiens). The KEGG and GO analyses indicated the MAPK signaling pathway and transcriptional misregulation in cancer are the major signaling pathways during the treatment of Sfb in liver cancer. Moreover, we identified ten key molecules including TP53, MYC, ACTB, CREBBP, HSP90AA1, JUN, UBB, SIRT1, CCNA2, RBX1. Therefore, this study provides novel knowledge of Sfb treated liver cancer.

bioinformatics↗

bioRxiv2022

Genomic analyses identify biological processes and functions between M1 and M2 macrophages

Macrophages can be induced by a variety of factors to change their phenotype and functions. M1 and M2 macrophages play converse roles during inflammation or other diseases. However, the mechanism and function of M1 and M2 macrophages are still not clear. This study aims to identify the different molecules and functions by analyzing the RNA-seq data. The GSE189354 was created by the Illumina HiSeq 4000 (Mus musculus). The KEGG and GO analyses indicated the Phagosome and Hematopoietic cell lineage are the major biological processes between M1 and M2 macrophages. Moreover, we further identified ten molecules including Il6, Il1b, Tlr2, Myc, Fn1, Itgax, Cxcl10, Ccl5, Cxcr4, and Pparg. Therefore, our study may provide novel knowledge of innate immunity.

bioinformatics↗