Biology subjects

Qi, T.

Publications and source records attributed to Qi, T..

30 records · Page 2Linked to original sources

bioRxiv2022

Longitudinally modeling anti-neoantigen immunity under paradigms of immunodominance

Predator-prey theory is commonly used to approximately describe tumor growth in the presence of selective pressure from the adaptive immune system. These interactions are mediated by the tumor immunopeptidome (what the tumor "shows" the body) and the T-cell receptor (TCR) repertoire (how well the body "sees" cancer cells). Importantly, both tumor and T cell populations are dynamic and in competition with each other and their fraternal lineages. In particular, the immunopeptidome comprises neoantigens which can be gained and lost throughout tumorigenesis and treatment. Heterogeneity in the immunopeptidome is predictive of poorer survival and response to T-cell dependent immunotherapy in some tumor types, suggesting the TCR repertoire is unable to support a fully polyclonal response against every neoantigen. Whether between-lineage competition among T cells plays a role, and in what contexts, is unknown; moreover, longitudinal TCR profiling studies are expensive and logistically complex to conduct. In silico models may offer an inexpensive way to interrogate these phenomena ex ante and deepen our understanding of the tumor-immune axis. Here, we construct and calibrate a predator-prey-like model to preclinical and clinical data to describe tumor growth and immunopeptidome diversification. Simultaneously, we model the expansion of neoantigen-specific T cell lineages and their consumption of both lineage-specific and shared, lineage-agnostic resources. This predator-prey-like framework accurately described clinically observed immunopeptidomes as well as correlates and consequences of response to immunotherapy, including immunoediting. The model was also suitable for exploring treatment of tumors with varying growth and mutation rates.

cancer biology↗

bioRxiv2021

Targeting interactions between the Galectin-3 intrinsically disordered and structured domains based on long time-scale accelerated molecular dynamics

Intrinsically disordered regions (IDRs) are common and important functional domains in many proteins. However, IDRs are difficult to target for drug development due to the lack of defined structures which would facilitate the identification of possible drug-binding pockets. Galectin-3 is a carbohydrate-binding protein of which overexpression has been implicated in a wide variety of disorders including cancer and inflammation. Apart from its carbohydrate recognition/binding domain (CRD), Galectin-3 also contains a functionally important disordered N-terminal domain (NTD) that contacts the C-terminal domain (CTD) and could be a target for drug development. To overcome challenges involved in inhibitor design due to lack of structure and the highly dynamic nature of the NTD, we used a novel protocol combining nuclear magnetic resonance data from recombinant Galectin-3 with accelerated molecular dynamics (MD) simulations. This approach identified a pocket in the CTD with which the NTD makes frequent contact. In accordance with this model, mutation of residues L131 and L203 in this pocket caused loss of Galectin-3 agglutination ability, signifying the functional relevance of the cavity. In-silico screening was used to design candidate inhibitory peptides targeting the newly discovered cavity and experimental testing of only 3 of these yielded one peptide that inhibits the agglutination promoted by wild type Galectin-3. NMR experiments further confirmed that this peptide indeed binds to a cavity in the CTD not within the actual CRD. Our results show that it is possible to apply a combination of MD simulations and NMR experiments to precisely predict the binding interface of a disordered domain with a structured domain, and furthermore use this predicted interface for designing inhibitors. This procedure can be potentially extended to many other targets in which similar IDR interactions play a vital functional role.

biochemistry↗

bioRxiv2021

BEdeepoff: an in silico tool for off-target prediction of ABE and CBE base editors

Base editors, including adenine base editors (ABEs) and cytosine base editors (CBEs), are valuable tools for introducing point mutations, but they frequently induce unwanted off-target mutations. Here, we performed a high-throughput gRNA-target library screening to measure editing efficiencies at integrated genomic off-targets and obtained datasets of 48,632 and 52,429 off-targets for ABE and CBE, respectively. We used the datasets to train deep learning models, resulting in ABEdeepoff and CBEdeepoff which can predict editing efficiencies at off-targets. These tools are freely accessible via online web server http://www.deephf.com/#/bedeep.

bioinformatics↗

bioRxiv2021

BEdeepon: an in silico tool for prediction of base editor efficiencies and outcomes

Base editors enable direct conversion of one target base into another in a programmable manner, but conversion efficiencies vary dramatically among different targets. Here, we performed a high-throughput gRNA-target library screening to measure conversion efficiencies and outcome product frequencies at integrated genomic targets and obtained datasets of 60,615 and 73,303 targets for ABE and CBE, respectively. We used the datasets to train deep learning models, resulting in ABEdeepon and CBEdeepon which can predict on-target efficiencies and outcome sequence frequencies. The software is freely accessible via online web server http://www.deephf.com/#/bedeep/bedeepon.

bioinformatics↗

bioRxiv2021

Evolutionary selection on synonymous codons in RNA G-quadruplex structural region

In addition to the amino acid sequence information, synonymous codons can encode multiple regulatory and structural signals in protein coding region. In this study, we investigated how synonymous codons have been adapted to the formation of RNA G-quadruplex (rG4) structure. We found a universal selective pressure acting on synonymous codons to facilitate rG4 formation in five eukaryotic organisms. While G-rich codons are preferred in rG4 structural region, C-rich codons are selectively unpreferred for rG4 structures. Genes codon usage bias, nucleotide composition and evolutionary rate can account for the selective variations on synonymous codons among rG4 structures within a species. Moreover, rG4 structures in translational initiation region showed significantly higher selective pressures than those in translational elongation region. These results bring us another dimension of evolutionary selection on synonymous codons for proper RNA structure and function.

bioinformatics↗

bioRxiv2020

Structure of the activated Roq1 resistosome directly recognizing the pathogen effector XopQ

Plants and animals detect pathogen infection via intracellular nucleotide-binding leucine-rich repeat receptors (NLRs) that directly or indirectly recognize pathogen effectors and activate an immune response. How effector sensing triggers NLR activation remains poorly understood. Here we describe the 3.8 [A] resolution cryo-electron microscopy structure of the activated Roq1, an NLR native to Nicotiana benthamiana with a Toll-like interleukin-1 receptor (TIR) domain, bound to the Xanthomonas effector XopQ. Roq1 directly binds to both the predicted active site and surface residues of XopQ while forming a tetrameric resistosome that brings together the TIR domains for downstream immune signaling. Our results suggest a mechanism for the direct recognition of effectors by NLRs leading to the oligomerization-dependent activation of a plant resistosome and signaling by the TIR domain. One Sentence SummaryVisualization of an activated plant immune receptor that triggers the immune response upon pathogen recognition.

plant biology↗

bioRxiv2019

A resource-efficient tool for mixed model association analysis of large-scale data

The genome-wide association study (GWAS) has been widely used as an experimental design to detect associations between genetic variants and a phenotype. Two major confounding factors, population stratification and relatedness, could potentially lead to inflated GWAS test-statistics and thereby spurious associations. Mixed linear model (MLM)-based approaches can be used to account for sample structure. However, genome-wide association (GWA) analyses in biobank samples such as the UK Biobank (UKB) often exceed the capability of most existing MLM-based tools especially if the number of traits is large. Here, we developed an MLM-based tool (called fastGWA) that controls for population stratification by principal components and relatedness by a sparse genetic relationship matrix for GWA analyses of biobank-scale data. We demonstrated by extensive simulations that fastGWA is reliable, robust and highly resource-efficient. We then applied fastGWA to 2,173 traits on 456,422 array-genotyped and imputed individuals and 2,048 traits on 46,191 whole-exome-sequenced individuals in the UKB.

genetics↗

bioRxiv2019

Conditional GWAS analysis identifies putative disorder-specific SNPs for psychiatric disorders

Substantial genetic liability is shared across psychiatric disorders but less is known about risk variants that are specific to a given disorder. We used multi-trait conditional and joint analysis (mtCOJO) to adjust GWAS summary statistics of one disorder for the effects of genetically correlated traits to identify putative disorder-specific SNP associations. We applied mtCOJO to summary statistics for five psychiatric disorders from the Psychiatric Genomics Consortium - schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit hyperactivity disorder (ADHD) and autism (AUT). Most genom-wide significant variants for these disorders had evidence of pleiotropy (i.e., impact on multiple psychiatric disorders) and hence have reduced mtCOJO conditional effect sizes. However, subsets of genome-wide significant variants had larger conditional effect sizes consistent with disorder-specific effects: 15 of 130 genome-wide significant variants for schizophrenia, 5 of 40 for major depression, 3 of 11 for ADHD and 1 of 2 for autism. In addition, we identified a number of variants that approached genome-wide significance in the original GWAS and have larger conditional effect sizes after conditioning on the other disorders. We show that decreased expression of VPS29 in the brain may increase risk to SCZ only and increased expression of CSE1L is associated with SCZ and MD, but not with BIP. Likewise, decreased expression of PCDHA7 in the brain is linked to increased risk of MD but decreased risk of SCZ and BIP.

genetics↗

bioRxiv2019

Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data

Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are not scalable to large cohorts. Here, we present an analytical approach that uses summary-level data from cohort-based DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood (n=1,980), we predicted 34,797 PAIs which showed strong overlap with the chromatin contacts identified by previous experimental assays. The promoter-interacting DNAm sites were enriched in enhancers or near expression QTLs. Genes whose promoters were involved in PAIs were more actively expressed, and gene pairs with promoter-promoter interactions were enriched for co-expression. Integration of the predicted PAIs with GWAS data highlighted interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provides insights into the role of PAIs in complex trait variation.

genetics↗

bioRxiv2018

ADS-J1 Disaggregates Semen-derived Amyloid Fibrils

Semen-derived amyloid fibrils, composing SEVI (semen-derived enhancer of viral infection) fibrils and SEM1 fibrils, could remarkably enhance HIV-1 sexual transmission and thus, are potential targets for the development of an effective microbicide. Previously, we found that ADS-J1, apart from being an HIV-1 entry inhibitor, could also potently inhibit seminal amyloid fibrillization and block fibril-mediated enhancement of viral infection. However, the remodeling effects of ADS-J1 on mature seminal fibrils were unexplored. Herein, we investigated the capacity of ADS-J1 to disassemble seminal fibrils and the potential mode of action by applying several biophysical and biochemical measurements, combined with molecular dynamic (MD) simulations. We found that ADS-J1 effectively remodeled SEVI, SEM186-107 fibrils and endogenous seminal fibrils. Unlike epi-gallocatechin gallate (EGCG), a universal amyloid fibril breaker, ADS-J1 disaggregated SEVI fibrils into monomeric peptides, which was independent of oxidation reaction. MD simulations revealed that ADS-J1 displayed strong binding potency to the full-length PAP248-286 via electrostatic interactions, hydrophobic interactions and hydrogen bonds. ADS-J1 might initially bind to the fibrillar surface and then occupy the amyloid core, which eventually lead to fibril disassembly. Furthermore, the binding of ADS-J1 with PAP248-286 might induce conformational changes of PAP248-286. Disassembled PAP248-286 might not be favor to re-aggregate into fibrils. ADS-J1 also exerts abilities to remodel a panel of amyloid fibrils, including A{beta}1-42, hIAPP1-37 and EP2 fibrils. ADS-J1 displays promising potential to be a combination microbicide and an effective lead-product to treat amyloidogenic diseases.

pharmacology and toxicology↗

bioRxiv2018

NRG1 is required for the function of the TIR-NLR immune receptors Roq1 and RPP1 in Nicotiana benthamiana

The plant immune system involves a large family of nucleotide-binding leucine-rich repeat (NLR) intracellular immune receptors. These immune receptors often function to directly or indirectly mediate the perception of specific pathogen effector proteins secreted into the cell. Activation of these immune receptors typically results in activation of the immune system and subsequent suppression of pathogen proliferation. Although many examples of NLR receptors are known, a mechanistic understanding of how receptor activation ultimately leads to an immune response is not well understood. A subset of the NLR proteins contain a TIR domain at their N terminus (TNL). One such TNL, the N gene, was previously shown to depend on a non-TIR NLR protein, N requirement gene 1 (NRG1) for immune function. We tested additional NLR proteins in Nicotiana benthamiana for dependency on NRG1. We found that two additional TIR-NLR proteins, Roq1 and RPP1, also require NRG1 but that two coiled-coil NLR proteins, Bs2 and Rps2, do not. This finding suggests that NRG1 may be a conserved component of TNL signaling pathways.

plant biology↗

bioRxiv2018

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes associated with brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top associated cis-expression (cis-eQTLs or cis-mQTLs) between brain and blood for genes expressed (or CpG sites methylated) in both tissues, while accounting for errors in their estimated effects (rb). Using publicly available data (n = 72 to l,366), we find that the genetic effects of cis-eQTLs (PeQTL < 5x10-8) or mQTLs (PmQTL < 1x10-10) are highly correlated between independent brain and blood samples ([Formula] with SE = 0.015 for cis-eQTL and [Formula] with SE = 0.006 for cis-mQTLs). Using meta-analyzed brain eQTL/mQTL data (n = 526 to 1,194), we identify 61 genes and 167 DNA methylation (DNAm) sites associated with 4 brain-related traits and disorders. Most of these associations are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = l,980 to 14,115). We further find that cis-eQTLs with tissue-specific effects are approximately uniformly distributed across all the functional annotation categories, and that mean difference in gene expression level between brain and blood is almost independent of the difference in the corresponding cis-eQTL effect. Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL or cis-mQTL data with large sample sizes.

genetics↗