Biology subjects

Tsang, J.

Publications and source records attributed to Tsang, J..

11 recordsLinked to original sources

bioRxiv2026

A starvation-remodeled pre-mRNA structure controls U1 recruitment and nutrient-stress adaptation in yeast

Recognition of 5' splice sites by the U1 small nuclear ribonucleoprotein commits pre-mRNAs to splicing, yet splice-site complementarity alone cannot predict productive U1 engagement. Whether dynamic pre-mRNA structure regulates this early spliceosome assembly step remains unclear. Here, we identify a 5'UTR-intron base-pairing interaction positioned near the 5' splice site that acts as an inducible structural gate for U1 engagement. In budding yeast, this element is enriched among introns required for adaptation to nutrient depletion, and in vivo DMS-MaPseq shows that starvation remodels its structure. Structure-guided disruption of pairing impairs adaptation, whereas compensatory mutations restoring pairing without restoring sequence rescue the phenotype, establishing RNA fold as the critical determinant. U1 association decreases when the gate is disrupted and recovers when pairing is restored, and increased Nam8 levels can compensate for gate disruption by stabilizing U1 engagement under stress. Thus, dynamic pre-mRNA folding gates U1 recognition, revealing how transcript architecture converts physiological state into selective splice-site choice.

molecular biology↗

bioRxiv2026

A surviving beta cell subpopulation enriched in patients with T1D

Type 1 diabetes (T1D) is characterized by the autoimmune destruction of pancreatic beta cells. While most beta cells are lost, a subset of beta cells persists years and even decades after disease onset. Studying these surviving cells is challenging, and thus how they escape immune killing remains poorly understood. Here, we applied a gene regulatory network inference-based clustering approach on existing islet scRNAseq data from cadaveric donors with T1D, autoantibody positive donors at risk for T1D, and non-diabetic donors to analyze beta cells from patients with established T1D. This approach identified a novel beta cell subtype enriched in T1D donors defined by the activity of several transcription factors which have well-characterized roles in beta cell survival, most notably IRF1. We found increased expression of immunomodulatory genes (e.g. SOCS1/3, HLA-E) as well as decreased expression of autoantigens and secretory genes, suggesting dedifferentiation. We identified inflammatory cytokines as a driver of this phenotype by reanalyzing public data from primary human beta cells stimulated with inflammatory cytokines in vitro. We additionally find a similar transcriptional program active in a subset of alpha cells, consistent with cell-extrinsic inflammatory cytokine signaling in vivo. Overall, we propose that this population represents a resilient beta cell phenotype, and that the transcriptional program active in these cells may identify targets for T1D prevention and reversal.

immunology↗

bioRxiv2025

The Connectome Interpreter Toolkit

Complete synaptic wiring diagrams, or connectomes, of whole brains open new opportunities for studying the structure-function relationship of neural circuits. However, the large number of nodes and edges in the graphs makes the analysis challenging. Here, we present the Connectome Interpreter, an open-source software toolkit for efficient graph exploration to find polysynaptic pathways, compute the effective connectivity and receptive fields for arbitrarily deep neurons, slice out subcircuits, and construct non-linear but differentiable circuit models, implemented using efficient approaches tailored to large connectomes with abundant divergent and convergent connections, such as that of the fruit fly Drosophila melanogaster. Our approach delivers results orders of magnitude faster than conventional methods on consumer hardware. We demonstrate the capabilities of our toolkit with select applications, including quantifying the density of polysynaptic connections in the whole adult fruit fly brain, exploring the necessity for non-linearities in circuit modeling, and combining known function of neurons with the connectome to aid in formulating hypotheses of circuit function.

neuroscience↗

bioRxiv2023

Glioblastoma Mesenchymal Transition and Invasion are Dependent on a NF-κB/BRD2 Chromatin Complex

Glioblastoma (GBM) represents the most aggressive subtype of glioma, noted for its profound invasiveness and molecular heterogeneity. The mesenchymal (MES) transcriptomic subtype is frequently associated with therapy resistance, rapid recurrence, and increased tumor-associated macrophages. Notably, activation of the NF-{kappa}B pathway and alterations in the PTEN gene are both associated with this malignant transition. Although PTEN aberrations have been shown to be associated with enhanced NF-{kappa}B signaling, the relationships between PTEN, NF-{kappa}B and MES transition are poorly understood in GBM. Here, we show that PTEN regulates the chromatin binding of bromodomain and extraterminal (BET) family proteins, BRD2 and BRD4, mediated by p65/RelA localization to the chromatin. By utilizing patient-derived glioblastoma stem cells and CRISPR gene editing of the RELA gene, we demonstrate a crucial role for RelA lysine 310 acetylation in recruiting BET proteins to chromatin for MES gene expression and GBM cell invasion upon PTEN loss. Remarkably, we found that BRD2 is dependent on chromatin associated acetylated RelA for its recruitment to MES gene promoters and their expression. Furthermore, loss of BRD2 results in the loss of MES signature, accompanied by an enrichment of proneural signature and enhanced therapy responsiveness. Finally, we demonstrate that disrupting the NF-{kappa}B/BRD2 interaction with a brain penetrant BET-BD2 inhibitor reduces mesenchymal gene expression, GBM invasion, and therapy resistance in GBM models. This study uncovers the role of hitherto unexplored PTEN-NF-{kappa}B-BRD2 pathway in promoting MES transition and suggests inhibiting this complex with BET-BD2 specific inhibitors as a therapeutic approach to target the MES phenotype in GBM.

cancer biology↗

bioRxiv2023

Characterizing the microbial metagenome of calcareous stromatolite formations in the San Felipe Creek in Anza Borrego Desert

Here we describe the metagenome composition, community functional annotation, and diversity of prokaryotic microbial species derived from calcareous stromatolite formations discovered in the dry stream bed of the open-canopy, ephemeral San Felipe Creek in the Anza Borrego Desert. In this environment, resident microbes must be able to adapt to the harsh conditions of extreme heat, high UV light, desiccation and fluctuating solubilization/precipitation and hydration/evaporation. Metagenomic analysis revealed a community capable of carrying out complete nitrogen fixation and assimilatory nitrate reduction, forming biofilms and quorum sensing, and potentially forming thick-walled akinetes as desiccation-resistant stages. Nitrogen cycling is likely to play a fundamental role in mediating both the structure of the stromatolite microbial community and the mineral precipitation/dissolution. The viruses present in the stromatolites, particularly Nodularia and Mycobacterium phages are also likely to impact community population dynamics and activity. Stromatolite community members possess different morphological and physiological strategies to cope with desiccation stress. Metagenomic signatures were found for scytonemin, carotenoids, synthesis of potential microsporine-like amino acids; genes involved in microalgal desiccation tolerance, including those encoding aquaporins, chaperones, antioxidants; and enzymes responsible for the synthesis of trehalose, sucrose, and polyamines. The stromatolite ecosystem provides a diverse array of microniches where different functional guilds can develop complex metabolite exchange with the substrate supporting their life in extreme conditions. Metagenome analyses revealed several genes that might enable a specialized and unique group of endolithic cyanobacteria including Chroococcidiopsis, Hyella, Myxosarcina, and Pleurocapsa to derive metals and important nutrients from rocks, being potentially destructive for the calcareous formations. Our study revealed environmental adaptations of freshwater microbial communities in desert stream stromatolites which may provide valuable insights into Precambrian paleoenvironments, which are little known.

genomics↗

bioRxiv2022

Transcriptional atlas of the human immune response to 13 vaccines reveals a common predictor of vaccine-induced antibody responses

Systems biology approaches have been used to define molecular signatures and mechanisms of immunity to vaccination. However, most such studies have been done with single vaccines, and comparative analysis of the response to different vaccines is lacking. We integrated temporal transcriptional data of over 3,000 samples, obtained from 820 healthy adults across 28 studies of 13 different vaccines and analyzed vaccination-induced signatures associated with the antibody response. Most vaccines induced similar kinetics of shared transcriptional signatures, including signatures of innate immunity occurring 1-3 days post-vaccination, as well as the canonical plasmablast and cell cycle signatures appearing 7 days post-vaccination. However, the yellow fever vaccine YF-17D uniquely induced an early transient signature of T and B cell activation at Day 1, followed by delayed antiviral/interferon and plasmablast signatures that peaked at Days 7 and 14-21, respectively. Thus, despite the shared transcriptional response to most vaccines, at any given time point there was no evidence for a "universal signature" that could be used to predict the antibody response to all vaccines. However, accounting for the asynchronous nature of responses led to the identification of a time-adjusted signature that improved prediction antibody of responses across vaccines. These results provide a transcriptional atlas of the human immune response to vaccination and define a common, time-adjusted signature of antibody responses to vaccination.

immunology↗

bioRxiv2021

The Immune Signatures Data Resource: A compendium of systems vaccinology datasets

Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines, including those targeting seasonal influenza, yellow fever, and hepatitis B. These data are made available to the broader scientific community through the ImmuneSpace data portal and analysis engine leveraging the NIH/NIAID ImmPort repository1,2. However, a barrier to progress in this area is that comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines and includes transcriptional profiles and antibody response measurements. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses. [Table 1]

systems biology↗

bioRxiv2021

An innate immune activation state prior to vaccination predicts responsiveness to multiple vaccines

Many factors determine whether an individual responding to vaccination will generate an immune response that can lead to protection. Several studies have shown that the pre-vaccination immune state is associated with the antibody response to vaccines. However, the generalizability and mechanisms that underlie this association remain poorly defined. Here, we sought to identify a common pre-vaccination signature and mechanisms that could predict the immune response across a wide variety of vaccines. We leveraged the "Immune Signatures Data Resource" created by the NIH Human Immunology Project Consortium (HIPC) to integrate data from 28 studies involving 13 different vaccines and associate the blood transcriptional status of 820 healthy young adults with their responses. An unsupervised analysis of blood transcriptional profiles across studies revealed three distinct pre-vaccination states, characterized by the differential expression of genes associated with a pro-inflammatory response, cell proliferation, and metabolism alterations downstream of NF{kappa}B and IRF7. Innate and adaptive immune cell subset-specific genes were also associated with the three pre-vaccination states. Importantly, individuals whose pre-vaccination state was enriched in pro-inflammatory response genes known to be downstream of NF{kappa}B tended to have higher serum antibody responses one month after vaccination. A supervised analysis of the same data resulted in a single classifier, also enriched for NF{kappa}B regulated genes, that predicted the antibody response across most of the vaccines. Projection into single-cell RNA-sequencing data suggested that this pre-vaccination state was attributable to the signature of activation of non-classical monocytes and myeloid dendritic cells. Transcriptional signatures of acute responses to bacterial and not viral infections were enriched in the high pro-inflammatory pre-vaccination state and also included NF{kappa}B regulated genes. The pro-inflammatory pre-vaccination state was highly reminiscent of the innate activation state triggered by TLR ligands or adjuvants. These results demonstrate that wide variations in the transcriptional state of the immune system in humans can be a key determinant of responsiveness to vaccination. They also define a transcriptional signature NF{kappa}B activation at baseline, that is associated with a greater magnitude of antibody response to multiple vaccines, and suggest that modulation of the innate immune system by next-generation adjuvants targeting NF{kappa}B before vaccine administration may improve vaccine responsiveness.

systems biology↗

bioRxiv2020

Combined Treatment with Dopamine Receptor Antagonists and Radiation Creates a Metabolic Vulnerability in Mouse Models of Glioblastoma

BackgroundGlioblastoma is the deadliest brain tumor in adults and the standard-of-care consists of surgery followed by radiation and treatment with temozolomide. Overall survival times for patients suffering from glioblastoma are unacceptably low indicating an unmet need for novel treatment options. MethodsUsing patient-derived glioblastoma lines and mouse models of glioblastoma we test the effect of radiation and the dopamine receptor antagonist on glioblastoma self-renewal in vitro and survival in vivo. A possible resistance mechanism is investigated using RNA-Sequencing. ResultsTreatment of glioma cells with the dopamine receptor antagonist quetiapine reduced glioma cell self-renewal in vitro and combined treatment of mice with quetiapine and radiation prolonged the survival of glioma-bearing animals. The combined treatment induced the expression of genes involved in cholesterol biosynthesis. This rendered the tumors vulnerable to simultaneous treatment with atorvastatin and further significantly prolonged the survival of the animals. ConclusionsOur results indicate high efficacy of a triple combination of quetiapine, atorvastatin and radiation against glioblastoma without increasing the toxicity of radiation. With both drugs readily available for clinical use our study could be rapidly translated into a clinical trial.

neuroscience↗

bioRxiv2019

A Modified Injector and Sample Acquisition Protocol Can Improve Data Quality and Reduce Inter-Instrument Variability of the Helios Mass Cytometer

Mass cytometry is a powerful tool for high dimensional single cell characterization. Since the introduction of the first commercial CyTOF mass cytometer by DVS Sciences in 2009, mass cytometry technology has matured and become more widely utilized, with sequential platform upgrades designed to address specific limitations and to expand the capabilities of the platform. Fluidigms 3rd-generation Helios mass cytometer introduced a number of upgrades over the previous CyTOF2. One of these new features is a modified narrow bore sample injector that generates smaller ion clouds, which is expected to improve sensitivity and throughput. However, following rigorous testing we find that the narrow-bore sample injector may have unintended negative consequences on data quality and result in lower median signal intensities and higher coefficients of variation in antibody expression. We describe an alternative Helios acquisition protocol using a wider bore injector, which largely mitigates these data quality issues. We directly compare these two protocols in a multi-site study of 10 Helios instruments across 7 institutions and show that the modified protocol improves data quality and reduces inter-instrument variability. These findings highlight and address an important source of technical variability in mass cytometry experiments that is of particular relevance in the setting of multi-center studies.

immunology↗

bioRxiv2018

ImmuneRegulation: A web-based tool for identifying human immune regulatory elements

Humans can vary considerably in their healthy immune phenotypes and in their immune responses to various stimuli. We have developed an interactive web-based tool, ImmuneRegulation, to enable discovery of human regulatory elements that drive some of the phenotypic differences observed in gene expression profiles. ImmuneRegulation currently provides the largest centrally integrated resource available in the literature on transcriptome regulation in whole blood and blood cell types, including genotype data from 23,040 individuals, with associated gene expression data from 30,562 experiments, that provide genetic variant-gene expression associations on [~]200 million eQTLs. In addition, it includes 14 million transcription factor (TF) binding region hits extracted from 1945 TF ChIP-seq peaks and the latest GWAS catalog of 67,230 published SNP-trait associations. Users can interactively explore ImmuneRegulation to visualize and discover associations between their gene(s) of interest and their regulators (genetic variants or transcription factors) across multiple cohorts and studies. These regulators can explain cohort or cell type dependent gene expression variations and may be critical in selecting the ideal cohorts or cell types for follow-up studies. Overall, ImmuneRegulation aims to contribute to our understanding of the effects of eQTLs and TFs on heterogeneous transcriptional responses reported in studies on the blood; in the development of molecular signatures of immune response; and facilitate their future application in patient management. ImmuneRegulation is freely available at http://icahn.mssm.edu/immuneregulation.

immunology↗