Biology subjects

Rui, X.

Publications and source records attributed to Rui, X..

6 recordsLinked to original sources

bioRxiv2023

B cell directed CAR-T cell therapy results in activation of CD8+ cytotoxic CAR-negative bystander T cells in both non-human primates and patients

There is growing appreciation for the emergence of CARneg bystander T cells after CAR-T cell infusion. However, their phenotypic and transcriptomic hallmarks and mechanisms of activation remain uncertain. We performed single-cell RNA-Seq (scRNA-Seq) on non-human primate (NHP) and patient-derived T cells to interrogate CARneg T cells following B cell targeted CAR-T cell therapy. In a NHP model, we observed a distinct population of activated CD8+ CARneg T cells emerging during CAR-T cell expansion. These bystander CD8+ CARneg T cells exhibited a unique transcriptional signature with upregulation of NK-cell markers (KIR3DL2, CD160, KLRD1), chemokines and chemokine receptors (CCL5, XCL1, CCR9), and downregulation of naive T cell-associated genes (SELL, CD28). A transcriptionally similar population was identified in patients following Tisangelecleucel infusion. Mechanistic studies revealed that IL-2 and IL-15 exposure induced bystander-like CD8+ T cells. These T cells efficiently killed leukemic cells through a TCR-independent mechanism. Together, these data identify bystander CD8+ T cells as a novel mechanism by which CAR-T cell infusion can induce further anti-leukemic activity, measurable in both NHP and in patients. Statement of SignificanceWe have deeply interrogated CARneg bystander CD8+ T cells during CAR-T cell expansion in non{-}human primates and patients receiving Tisangelecleucel to identify the unique transcriptomic signature defining these cells, and to determine that IL-2-and IL-15-induced cytotoxic bystander T cells are capable of killing in a TCR-independent manner. These data highlight the potential of bystander T cells for leukemia control and provide a critical foundation for their future analysis.

immunology↗

bioRxiv2023

Imputation Efficacy Across Global Human Populations

Genotype imputation is now fundamental for genome-wide association studies but lacks fairness due to the underrepresentation of populations with non-European ancestries. The state-of-the-art imputation reference panel released by the Trans-Omics for Precision Medicine (TOPMed) initiative contains a substantial number of admixed African-ancestry and Hispanic/Latino samples to impute these populations with nearly the same accuracy as European-ancestry cohorts. However, imputation for populations primarily residing outside of North America may still fall short in performance due to persisting underrepresentation. To illustrate this point, we curated genome-wide array data from 23 publications published between 2008 to 2021. In total, we imputed over 43k individuals across 123 populations around the world. We identified a number of populations where imputation accuracy paled in comparison to that of European-ancestry populations. For instance, the mean imputation r-squared (Rsq) for 1-5% alleles in Saudi Arabians (N=1061), Vietnamese (N=1264), Thai (N=2435), and Papua New Guineans (N=776) were 0.79, 0.78, 0.76, and 0.62, respectively. In contrast, the mean Rsq ranged from 0.90 to 0.93 for comparable European populations matched in sample size and SNP content. Outside of Africa and Latin America, Rsq appeared to decrease as genetic distances to European reference increased, as predicted. Further analysis using sequencing data as ground truth suggested that imputation software may over-estimate imputation accuracy for non-European populations than European populations, suggesting further disparity between populations. Using 1496 whole genome sequenced individuals from Taiwan Biobank as a reference, we also assessed a strategy to improve imputation for non-European populations with meta-imputation, which can combine results from TOPMed with smaller population-specific reference panels. We found that meta-imputation in this design did not improve Rsq genome-wide. Taken together, our analysis suggests that with the current size of alternative reference panels, meta-imputation alone cannot improve imputation efficacy for underrepresented cohorts and we must ultimately strive to increase diversity and size to promote equity within genetics research.

genetics↗

bioRxiv2023

Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics

The heritability explained by local ancestry markers in an admixed population [Formula] provides crucial insight into the genetic architecture of a complex disease or trait. Estimation of [Formula] can be susceptible to biases due to population structure in ancestral populations. Here, we present a novel approach, Heritability estimation from Admixture Mapping Summary STAtistics (HAMSTA), which uses summary statistics from admixture mapping to infer heritability explained by local ancestry while adjusting for biases due to ancestral stratification. Through extensive simulations, we demonstrate that HAMSTA [Formula] estimates are approximately unbiased and are robust to ancestral stratification compared to existing approaches. In the presence of ancestral stratification, we show a HAMSTA-derived sampling scheme provides a calibrated family-wise error rate (FWER) of [~]5% for admixture mapping, unlike existing FWER estimation approaches. We apply HAMSTA to 20 quantitative phenotypes of up to 15,988 self-reported African American individuals in the Population Architecture using Genomics and Epidemiology (PAGE) study. We observe [Formula] in the 20 phenotypes range from 0.0025 to 0.033 (mean [Formula]), which translates to [Formula] ranging from 0.062 to 0.85 (mean [Formula]). Across these phenotypes we find little evidence of inflation due to ancestral population stratification in current admixture mapping studies (mean inflation factor of 0.99 +/-0.001). Overall, HAMSTA provides a fast and powerful approach to estimate genome-wide heritability and evaluate biases in test statistics of admixture mapping studies.

genetics↗

bioRxiv2022

Molecular insights into intrinsic transducer-coupling bias in the CXCR4-CXCR7 system

Chemokine receptors constitute an important subfamily of G protein-coupled receptors (GPCRs), and they are critically involved in a broad range of immune response mechanisms. Ligand promiscuity among these receptors makes them an interesting target to explore novel aspects of biased agonism. Here, we comprehensively characterize two chemokine receptors namely, CXCR4 and CXCR7, which share a common chemokine agonist (CXCL12), in terms of their G-protein coupling, {beta}-arrestin ({beta}arr) recruitment, contribution of GRKs, and ERK1/2 MAP kinase activation. We observe that CXCR7 lacks G-protein coupling while maintaining robust {beta}arr recruitment with a major contribution of GRK5/6. On the other hand, CXCR4 displays robust G-protein activation as expected, however, it exhibits significantly reduced {beta}arr-coupling compared to CXCR7 in response to their shared natural agonist, CXCL12. These two receptors induce distinct {beta}arr conformations even when activated by the same agonist, and CXCR7, unlike CXCR4, fails to activate ERK1/2 MAP kinase. We further determine the crystal structure of {beta}arr2 in complex with a carboxyl-terminal phosphopeptide derived from CXCR7, which reveals a smaller interdomain rotation than observed previously for activated {beta}arrs. Importantly, structure-guided cellular experiments reveal a key contribution of a single phosphorylation site in CXCR7 on {beta}arr recruitment and endosomal trafficking. Taken together, our study provides molecular insights into intrinsic bias encoded in the CXCR4-CXCR7 system, and it has broad implications for therapeutically important framework of biased agonism.

biochemistry↗

bioRxiv2022

Evolutionarily conserved effects of Notch signaling drive intestinal graft-versus-host disease in mice and non-human primates

Notch signaling promotes T-cell pathogenicity and graft-versus-host disease (GVHD) after allogeneic hematopoietic cell transplantation (allo-HCT) in mice, with a dominant role for the Delta-like ligand DLL4. To assess if Notchs effects are evolutionarily conserved and identify key mechanisms, we studied antibody-mediated DLL4 blockade in a non-human primate model similar to human allo-HCT. Short-term DLL4 blockade improved post-transplant survival with striking, durable protection from gastrointestinal GVHD, out of proportion to other disease sites. Unlike prior immunosuppressive strategies, anti-DLL4 interfered with a T-cell transcriptional program associated with intestinal infiltration. In cross-species investigations, Notch inhibition decreased surface abundance of the gut-homing integrin a4b7 in conventional T-cells via b1 competition for a4 binding, while preserving a4b7 in regulatory T-cells. Thereby, DLL4/Notch blockade decreased effector T-cell infiltration into the gut, with increased regulatory to conventional T-cell ratios early after allo-HCT. Our results identify a conserved, biologically unique and targetable role of DLL4/Notch signaling in GVHD. One Sentence SummaryNotch signaling promotes pathogenic effector T cell infiltration of the intestine during acute graft-versus-host disease.

immunology↗

bioRxiv2021

Identification and tracking of alloreactive T cell clones in Rhesus Macaques through the RM-scTCR-Seq platform.

T cell receptor clonotype tracking is a powerful tool for interrogating T cell mediated immune processes. New methods to pair a single cells transcriptional program with its T cell receptor (TCR) identity allow monitoring of T cell clonotype-specific transcriptional dynamics. While these technologies have been available for human and mouse T cells studies, they have not been developed for Rhesus Macaques, a critical translational organism for autoimmune diseases, vaccine development and transplantation. We describe a new pipeline, RM-scTCR-Seq, which, for the first time, enables RM specific single cell TCR amplification, reconstitution and pairing of RM TCRs with their transcriptional profiles. We apply this method to a RM model of GVHD, and identify and track in vitro detected alloreactive clonotypes in GVHD target organs and explore their GVHD driven cytotoxic T cell signature. This novel, state-of-the-art platform fundamentally advances the utility of RM to study protective and pathogenic T cell responses.

immunology↗