Biology subjects

Yue, T.

Publications and source records attributed to Yue, T..

7 recordsLinked to original sources

bioRxiv2026

A lifespan-scale single-cell atlas defines an early-childhood immunometabolic transition linked to age-referenced immune states

Childhood represents a critical period with rapid metabolic and immune remodeling, during which perturbations may have lasting consequences for health. We integrated single-cell RNA sequencing (scRNA-seq) profiles of peripheral blood mononuclear cells (PBMCs) from 2,008 healthy individuals aged 0-100 years. Age-resolved modeling highlighted an early-childhood transition centered at age 6, characterized by coordinated remodeling of metabolism-related transcriptional programs, particularly in monocyte and B-lineage cells. Matched serum metabolomics and lipidomics in a pediatric subcohort detected a temporally concordant wave of metabolite and lipid changes around ages 6-8 and extensive metabolite/lipid-transcript associations, prominently involving steroid and phospholipid species. Building on these findings, we developed an immunometabolic transition score and age-specific reference chart, which were evaluated in an independent healthy cohort and applied to quantify deviations in pediatric immune disorders. These findings highlight a coordinated immunometabolic transition in early childhood and provide an age-referenced framework for distinguishing atypical immune-state variation from healthy age-associated variation.

immunology↗

bioRxiv2025

Decrypting cellular engagement and recruitment from spatially resolved transcriptomics

The recruitment of the various types of cells into the tissue microenvironment and how these cells engage with other cells in the tissue sites play critical biological roles. However, it is difficult to study these processes on a genome-wide scale using traditional low-throughput experiments. To address this gap, we developed a fully interpretable multi-instance deep learner, coined "spacer". Spacer digests the transcriptomics and spatial modalities of spatially resolved transcriptomics (SRT) data in alignment with the biological principles of the tissue spatial architecture. We deployed spacer to a panel of 17 high definition and 20 low definition SRT datasets, for studying how stromal and immune cells were recruited into tumors and heart during myocarditis. Spacer discovered novel biological insights not affordable by prior spatial data analysis tools, which were validated by orthogonal immuno-peptidomics, spatial T cell receptor (TCR) sequencing, and single cell sequencing experiments. We discovered genes that encode more immunogenic peptides and that are involved in developmental pathways are more potent in recruiting T cells to local tumor sites, while the recruitment of B cells and macrophages is stipulated by a different molecular program. On the other hand, expression of mucins in the tumor cells was found to repel T cell localization. For the engaging cell side, we also uncovered T cell-intrinsic features that determine their localization, validated by spatial-TCR-seq data. Spacer also unexpectedly revealed that CD4+ T cells, though fewer in numbers, are more responsive than CD8+ T cells in the heart during myocarditis. Collectively, this study establishes a new spatially resolved paradigm for studying cellular localization mechanisms in situ and shifts the paradigm from descriptive mapping to mechanistic discovery.

bioinformatics↗

bioRxiv2025

VISTA-induced tumor suppression by a four amino acid intracellular motif

VISTA is a key immune checkpoint receptor under investigation for cancer immunotherapy; however, its signaling mechanisms remain unclear. Here we identify a conserved four amino acid (NPGF) intracellular motif in VISTA that suppresses cell proliferation by constraining cell-intrinsic growth receptor signaling. The NPGF motif binds to the adapter protein NUMB and recruits Rab11 endosomal recycling machinery. We identify and characterize a class of triple-negative breast cancers with high VISTA expression and low proliferative index. In tumor cells with high VISTA levels, the NPGF motif sequesters NUMB at endosomes, which interferes with epidermal growth factor receptor (EGFR) trafficking and signaling to suppress tumor growth. These effects do not require canonical VISTA ligands, nor a functioning immune system. As a consequence of VISTA expression, EGFR receptor remains abnormally phosphorylated and cannot propagate ligand-induced signaling. Mutation of the VISTA NPGF domain reverts VISTA-induced growth suppression in multiple breast cancer mouse models. These results define a mechanism by which VISTA represses NUMB to control malignant epithelial cell growth and signaling. They also define distinct intracellular residues that are critical for VISTA-induced cell-intrinsic signaling that could be exploited to improve immunotherapy.

cancer biology↗

bioRxiv2024

Puzzle Hi-C: an accurate scaffolding software

High-quality, chromosome-scale genomes are essential for genomic analyses. Analyses, including 3D genomics, epigenetics, and comparative genomics rely on a high-quality genome assembly, which is often accomplished with the assistance of Hi-C data. Current Hi-C-assisted assembling algorithms either generate ordering and orientation errors or fail to assemble high-quality chromosome-level scaffolds. Here, we offer the software Puzzle Hi-C, which uses Hi-C reads to accurately assign contigs or scaffolds to chromosomes. Puzzle Hi-C uses the triangle region instead of the square region to count interactions in a Hi-C heatmap. This strategy dramatically diminishes scaffolding interference caused by long-range interactions. This software also introduces a dynamic, triangle window strategy during assembly. Initially small, the window expands with interactions to produce more effective clustering. Puzzle Hi-C outperforms available scaffolding tools.

bioinformatics↗

bioRxiv2023

Sex-biased regulatory changes in the placenta of native highlanders contribute to adaptive fetal development

Compared with lowlander migrants, native Tibetans have a higher reproductive success at high altitude though the underlying mechanism remains unclear. Here, we compared the transcriptome and histology of full-term placentas between native Tibetans and Han migrants. We found that the placental trophoblast shows the largest expression divergence between Tibetans and Han, and Tibetans show decreased immune response and endoplasmic reticulum stress. Remarkably, we detected a sex-biased expression divergence, where the male-infant placentas show a greater between-population difference than the female-infant placentas. The umbilical cord plays a key role in the sex-biased expression divergence, which is associated with the higher birth weight of the male newborns of Tibetans. We also identified adaptive histological changes in the male-infant placentas of Tibetans, including larger umbilical artery wall and umbilical artery intima and media, and fewer syncytial knots. These findings provide valuable insights into the sex-biased adaptation of human populations, with significant implications for medical and genetic studies of human reproduction.

evolutionary biology↗

bioRxiv2023

Integrated analysis and annotation for T-cell receptor sequences using TCRosetta

BackgroundT cells and T cell receptors (TCRs) are essential components of the adaptive immune system. TCRs, on the surface of T cells, are responsible for recognizing and binding antigen peptide-MHC complex and play vital roles in T-cell immunology. Characterization of TCR repertoire offers a promising and high informative source for understanding the functions of T cells in immune responses and immunotherapies. Many researchers are now interested in TCR repertoire study; however, there are rare online servers for TCR analysis, especially no servers for TCR annotation and advanced analyses. ResultsWe developed TCRosetta, a comprehensive online server integrating the analytical methods for TCR repertoire/sequences analysis and visualization. TCRosetta combines general features analysis, large-scale sequence clustering, network construction, TCR-peptide binding prediction, generation probability calculation, and k-mer motif analysis for robust TCR sequence analysis, making TCR data analysis as simple as possible and allowing users to concentrate on research rather than coding. In addition, TCRosetta could annotate disease information for TRB CDR3 sequences by batch searching similar sequences in manually curated disease-related TCR database. The TCRosetta server accepts multiple input data formats and can analyze [~]20000 TCR sequences in less than three minutes. ConclusionsTCRosetta is the most comprehensive web server to date for TCR sequences/repertoires analysis and it is freely available at http://bioinfo.life.hust.edu.cn/TCRosetta/. It can be applied to help discover novel biomarkers for disease diagnosis and identify cancer-associated TCR sequences. WHAT IS ALERADY KNOWN ON THIS TOPICT cell receptor repertoires are largely untapped resource than can be used for predicting immune responses to different exposures including viral infections and tumor neoantigens. The downstream analysis of TCR repertoire is often performed by different tools requiring diverse operating environments and expertise. There is no webserver for comprehensive TCR repertoire analysis including general and advanced analysis. WHAT THIS STUDY ADDSWe developed TCRosetta, a comprehensive platform for analyzing T-cell repertoire which combines nearly all TCR analysis methods. It supports different kinds of the format of input including most mainstream TCR extraction tools or amino acid sequences. It could analyze the features of TCR repertoire and display them in interactive graphs and is the first platform with a batch search and TCR annotation function. HOW THIS STUDY MIGHT AFFECT RESEARCH, PACTICE OR POLICYTCRosetta can be applied to discover novel biomarkers to predict response in immunotherapy such TCR repertoire diversity and clonality. It also can identify cancer-associated TCR sequences by clustering biochemically similar CDR3 sequences. It can make TCR repertoire analysis as effortless as possible and help users focus on research instead of coding.

bioinformatics↗

bioRxiv2020

Candidate Explorer: a tool for discovery, evaluation, and display of mutations causing significant immune phenotypes

When applied to immunity, forward genetic studies use meiotic mapping to provide strong statistical evidence that a particular mutation is causative of a particular immune phenotype. Notwithstanding this, co-segregation of multiple mutations, occasional unawareness of mutations, and paucity of homozygotes may lead to erroneous declarations of cause and effect. We sought to improve the selection of authentic causative mutations using a machine learning software tool, Candidate Explorer (CE), which integrates 65 data features into a single numeric score, mathematically convertible to the likelihood of verification of any putative mutation-phenotype association. CE has identified most genes within which mutations can be causative of flow cytometric phenovariation in Mus musculus. The majority of these genes were not previously known to support immune function or homeostasis. Mouse geneticists will find CE data informative in identifying causative mutations within quantitative trait loci, while clinical geneticists may use CE to help connect causative variants with rare heritable diseases of immunity, even in the absence of linkage information. CE displays integrated mutation, phenotype, and linkage data, and is freely available for query online.

genetics↗