Biology subjects

Fu, A.

Publications and source records attributed to Fu, A..

11 recordsLinked to original sources

bioRxiv2026

Interpretable machine learning coupled to gene regulatory networks uncovers subcircuits underlying cell fate decisions

Gene regulatory networks (GRNs) model causal linkages that control cell fate decisions and differentiation transitions. Prioritizing regulatory subnetworks underlying cell state differences is of critical importance, but current methods including those reliant on topological metrics introduce circularity as the metrics prioritizing TFs are computed from the same networks whose assumptions they inherit. Separately, interpretable machine learning methods can identify latent factors (LFs) that discriminate cellular states with formal statistical guarantees but do not model regulatory linkages. Here, we present FOCAL (Factor-Outcome Coupling for Assessment of Linkages), a paradigm to prioritize regulatory subnetworks by coupling state-specific and dynamic GRNs with outcome-supervised LFs learned using interpretable machine learning without reference to network topology. This shifts GRN focus from macroscopic TF nodes to state-specific and dynamic TF-gene linkages. In B and T cells, FOCAL identified GIFs (GRNs coupled to Interpretable latent Factors), prioritized regulatory subnetworks underlying established states as well as transient regulatory episodes preceding them. By coupling LFs learnt from perturbation experiments of lineage-defining TFs, FOCAL identified transcriptional predisposition to alternative fates within progenitor cell populations before overt differentiation. This uncovered a novel NFATC2-IRF8 interplay in activated B cells, that was validated by in-vitro and in-vivo genetic perturbations. The two transcription factors act cooperatively to restrain extrafollicular plasmablast differentiation and promote germinal center B cell fate.

systems biology↗

bioRxiv2024

Proteome asymmetry in mouse and human embryos before fate specification

Pre-patterning of the embryo, driven by spatially localized factors, is a common feature across several non-mammalian species1-4. However, mammals display regulative development and thus it was thought that blastomeres of the embryo do not show such pre-patterning, contributing randomly to the three lineages of the blastocyst: the epiblast, primitive endoderm and trophectoderm that will generate the new organism, the yolk sac and placenta respectively 4-6. Unexpectedly, early blastomeres of mouse and human embryos have been reported to have distinct developmental fates, potential and heterogeneous abundance of certain transcripts7-12. Nevertheless, the extent of the earliest intra-embryo differences remains unclear and controversial. Here, by utilizing multiplexed and label-free single-cell proteomics by mass-spectrometry13, we show that 2-cell mouse and human embryos contain an alpha and a beta blastomere as defined by differential abundance of hundreds of proteins exhibiting strong functional enrichment for protein synthesis, transport, and degradation. Such asymmetrically distributed proteins include Gps1 and Nedd8, depletion or overexpression of which in one blastomere of the 2-cell embryo impacts lineage segregation. These protein asymmetries increase at 4-cell stage. Intriguingly, halved mouse zygotes display asymmetric protein abundance that resembles alpha and beta blastomeres, suggesting differential proteome localization already within zygotes. We find that beta blastomeres give rise to a blastocyst with a higher proportion of epiblast cells than alpha blastomeres and that vegetal blastomeres, which are known to have a reduced developmental potential, are more likely to be alpha. Human 2-cell blastomeres also partition into two clusters sharing strong concordance with clusters found in mouse, in terms of differentially abundant proteins and functional enrichment. To our knowledge, this is the first demonstration of intra-zygotic and inter-blastomere proteomic asymmetry in mammals that has a role in lineage segregation.

developmental biology↗

bioRxiv2024

Cancer radiomic feature variations due to reconstruction kernel choice and integral tube current.

PurposeRadiological cancer imaging features, or radiomics features, can be derived to diagnose disease or predict treatment response. However, variability between vendors, scanners, protocols, and even reconstruction software versions is an obstacle to the clinical use of radiomics features. This study aimed to characterize the impact of kernel reconstruction differences and integral tube current settings on radiomic features extracted from computed tomography (CT) scans. MethodsRadiomic features were extracted from CT scans of a 3D-printed phantom with five imprinted tumors using the CERR software system, resulting in 282 features. Batch effects were assessed via principal component analysis (PCA) and correlation measures. Robustness was measured using the concordance correlation coefficient (CCC) and Pearson correlation coefficient. Statistical analysis was performed using R software. ResultsPCA identified two clusters comprised of Standard, ASIRs, ASIRV, and soft kernels in one, and Lung and Bone Kernels in the other. Features displayed a gradient from ASIR10 to ASIR50 and ASIRV1 to ASIRV5 in terms of nearness to Standard Kernel feature values. Feature correlation matrices revealed little change in ASIRs, ASIRVs, and the Standard Kernel, but showed significant changes in Bone and Lung Kernel results. Combat-algorithm correction improved robustness, particularly in first-order statistic features, and mitigated batch effects due to the ASIRs and the standard kernel. Forty (40) out of 282 features were identified as robust. However, Combat-based correction performed poorly in harmonizing Bone and Lung reconstruction kernels. ConclusionsThe robustness of means and median radiomic features across kernel reconstruction choices, in contrast to the lack of robustness in many other radiomic features, suggests that kernel reconstruction effects are not well-addressed by current harmonization methods.

bioinformatics↗

bioRxiv2024

Systematic Identification of UBE2C As a Prognostic Biomarker and Correlated with Immunosuppression and Invasiveness in Glioma

Glioma is one of the common tumors of the central nervous system, which presents difficulties in clinical diagnosis and treatment due to its characteristics of immunosuppression and cell invasion phenotypes. If the condition and prognosis of glioma can be predicted during the process of diagnosis and treatment, it will be more conducive to timely intervention or evaluation of glioma. Therefore, we still need to search for more valuable tumor markers. The differential/risk genes and enrichment analysis based on glioma samples (The Cancer Genome Atlas, TCGA). Target gene UBE2C were obtained by the expression correlation and differential expression analysis for the enrichment results. UBE2C were evaluated by clinical grading, survival prognosis and cell experiments. The correlation of UBE2C with immune invasion, immune checkpoint, network analysis and cell invasiveness of gliomas was analyzed by TCGA-glioma data and STRING, respectively. The results suggests that the high expression and risk of UBE2C in gliomas may be a factor that promotes malignant phenotype of tumor cells. The immune phenotype shows that IL6 and IL10 may be the key nodes affecting the immunosuppressive phenotype of glioma. Further, the tumor cells aggressive genes from the MMP family can be correlated with immunosuppressive phenotypes via UBE2C-IL6/IL10 axis, especially displayed by MMP2/MMP9. The UBE2C may systemic effects the malignant phenotype, immunosuppression and cell invasiveness of tumors systematically, which reflects UBE2C as a potential biomarker of glioma and therapeutic target for this tumor.

cancer biology↗

bioRxiv2023

Adaptive Functions of Structural Variants in Human Brain Development

Quantifying the structural variants (SVs) in nonhuman primates could provide a niche to clarify the genetic backgrounds underlying human-specific traits, but such resource is largely lacking. Here, we report an accurate SV atlas in a population of 562 rhesus macaques, verified by two public SV benchmarks, an inhouse benchmark of eight macaque genomes with long-read sequencing and another inhouse benchmark of one macaque genome with whole-genome assembly. This accurate, quantitative SV map indicates stronger purifying selection on inversions, one type of poorly-clarified SVs to date, especially for those located on regulatory regions, suggesting a strategy for prioritizing inversions with the most important functions. Based on the distribution and the evolutionary features of these inversions in macaque population, we then identified 75 human-specific inversions, clarified their functional effects and prioritized them. Notably, the top-ranked inversions have substantially shaped the human transcriptome, through their dual-effects of reconfiguring the ancestral genomic architecture and introducing regional mutation hotspots at the inverted regions. As a proof-of-concept, we linked APCDD1, located on one of these inversions with the highest rank score and downregulated in human brains, to neuronal maturation. The accumulation of human-specific mutations on its promoter region, accelerated by the formation of the inversion, contributed to the decreased expression in humans. Notably, the overexpression of APCDD1 could accelerate the neuronal maturation, while its depletion in mice delays the neuronal maturation. This study thus highlights the contribution of SVs, especially the inversions, to the distinct features in human brain development.

evolutionary biology↗

bioRxiv2022

Targeting the Immune-Fibrosis Axis in Myocardial Infarction and Heart Failure

Cardiac fibrosis is causally linked to heart failure pathogenesis and adverse clinical outcomes. However, the precise fibroblast populations that drive fibrosis in the human heart and the mechanisms that govern their emergence remain incompletely defined. Here, we performed Cellular Indexing of Transcriptomes and Epitomes by sequencing (CITE-seq) in 22 explanted human hearts from healthy donors, acute myocardial infarction (MI), and chronic ischemic and non-ischemic cardiomyopathy patients. We identified a fibroblast trajectory marked by fibroblast activator protein (FAP) and periostin (POSTN) expression that was independent of myofibroblasts, peaked early after MI, remained elevated in chronic heart failure, and displayed a transcriptional signature consistent with fibrotic activity. We assessed the applicability of cardiac fibrosis models and demonstrated that mouse MI, angiotensin II/phenylephrine infusion, and pressure overload models were superior compared to cultured human heart and dermal fibroblasts in recapitulating cardiac fibroblast diversity including pathogenic cell states. Ligand-receptor analysis and spatial transcriptomics predicted interactions between macrophages, T cells, and fibroblasts within spatially defined niches. CCR2+ monocyte and macrophage states were the dominant source of ligands targeting fibroblasts. Inhibition of IL-1{beta} signaling to cardiac fibroblasts was sufficient to suppress fibrosis, emergence, and maturation of FAP+POSTN+ fibroblasts. Herein, we identify a human fibroblast trajectory marked by FAP and POSTN expression that is associated with cardiac fibrosis and identify macrophage-fibroblast crosstalk mediated by IL-1{beta} signaling as a key regulator of pathologic fibroblast differentiation and fibrosis.

immunology↗

bioRxiv2022

Persistent Hypersomnia Following Repetitive Mild Experimental Traumatic Brain Injury: Roles of Chronic Stress and Sex Differences

Traumatic brain injury (TBI) is often more complicated than a single head injury. An extreme example of this point may be military service members who experience a spectrum of exposures over a prolonged period under stressful conditions. Understanding the effects of complex exposures can support proper evaluation and care for patients experiencing persistent symptoms. We designed a longitudinal series of non-invasive procedures in adult mice to evaluate the effects of prolonged mild exposures. We assessed anxiety, depression, and sleep-wake dysfunction as symptoms that can impact long term outcomes after mild TBI. Unpredictable chronic mild stress (UCMS) was generated from a variable sequence of environmental stressors distributed within each of 21 days. Subsequently, mice received a mild blast combined with closed-head mild TBI on five days at 24-hour intervals. TBI components were either five linear force impacts, or a novel alternating repetitive mild TBI (Ar-mTBI) model of linear and rotational (CHIMERA) impacts over five days to produce diffuse pathology. In males and females, UCMS induced anxiety without depressive behavior. Persistent hypersomnia, specifically increased sleep during the active dark period, was found through 6-12 month time points in male mice receiving UCMS with repetitive blast plus TBI events, or surprisingly after UCMS alone. Sleep-wake dysfunction was not found with TBI events alone and was not found in females under any conditions. These results identify prolonged stress and sex differences as important considerations for sleep-wake dysfunction. Furthermore, this reproducible hypersomnia is similar to excessive daytime sleepiness reported in patients, which may inform treatments.

neuroscience↗

bioRxiv2021

Target Enrichment Enhances the Sensitivity of Sanger Sequencing for BRAF V600 Mutation Detection

BRAF is a serine/threonine protein kinase whose mutations lead to unregulated cell growth and cause different types of cancers. Since V600E is a major BRAF mutation and V600E detection as a companion diagnostic test (CDx) is stipulated in the labeling of the BRAF V600 inhibitors. Traditional Sanger sequencing cannot accurately detect mutations lower than 15% variant allele frequency (VAF) due to its limited sensitivity. Here we applied our patented XNA molecular clamping technology to modify Sanger sequencing template preparation by enriching the mutation population. We found that the use of our mutation-enriched template enhanced the analytical sensitivity of Sanger sequencing to 0.04% VAF. The method is verified to detect V600E, V600K, and V600R mutants and is validated for the known BRAF mutation status in clinical samples. Our streamlined protocol can be used for easy validation of the highly sensitive target-enrichment method for detecting BRAF V600 mutations using Sanger sequencing in clinical labs. In addition to BRAF V600 mutations, this method can be extended to the detection of other clinically important actionable mutations for cancer diagnostics.

molecular biology↗

bioRxiv2021

Irx3 Promotes Gap Junction Communication Between Uterine Stromal Cells to Regulate Vascularization during Embryo Implantation

Spontaneous abortions have been reported to affect up to 43% of parous women, with over 20% occurring before pregnancy is clinically diagnosed. Establishment of pregnancy is critically dependent on proper embryo-uterine interactions at the time of implantation. Besides oocyte abnormalities, implantation failure is a major contributor to early pregnancy loss. Previously, we demonstrated that two members of the Iroquois homeobox transcription factor family, IRX3 and IRX5, exhibited distinct and dynamic expression profiles in the developing ovary to promote oocyte and follicle survival. Elimination of each gene independently caused subfertility, but with different breeding pattern outcomes. Irx3 KO (Irx3LacZ/LacZ) females produced fewer pups throughout their reproductive lifespan which could only be partially explained by poor oocyte quality. Thus, we hypothesized that IRX3 is also expressed in the uterus where it acts to establish functional embryo-uterine interactions to support pregnancy. To test this hypothesis, we harvested pregnant uteri from control and Irx3 KO females to evaluate IRX3 expression profiles and the integrity of embryo implantation sites. Our results indicate that IRX3 is expressed in the endometrial stromal cells of the pregnant uterus. Notably, of the days evaluated, IRX3 expression expanded into the endometrial stroma starting at day 4 of pregnancy (D4) with peak expression at D5-6, and then greatly diminished by D7. This pattern corresponds to the critical window for implantation and remodeling of the vasculature network in mice. Further, histology and immunohistochemistry at D7 showed that while embryos were able to attach to the uterus, implantation sites in Irx3 KO pregnant mice exhibited impaired vascularization. In addition, our results showed significantly diminished expression of decidualization markers and disruptions in GJA1 organization in the decidual bed. These data, taken together with previous reports focused on the ovary, suggest that IRX3 promotes fertility via at least two different mechanisms: 1) promoting competent oocytes and 2) facilitating functional embryo-uterine interactions during implantation. Future research aims to tease apart the roles for IRX3 in the oocyte versus the uterus and the mechanisms by which it promotes early embryo survival and a successful pregnancy outcome.

physiology↗

bioRxiv2018

Identification of pathogens in culture-negative infective endocarditis with metagenomic analysis

Pathogens identification is critical for the proper diagnosis and precise treatment of infective endocarditis. Although blood and valve cultures are the gold standard for IE pathogens detection, many cases are culture-negative, especially in patients who had received long-term antibiotic treatment, and precise diagnosis has therefore become a major challenge in the clinic. Metagenomic sequencing can provide both information on the pathogenic strain and the antibiotic susceptibility profile of patient samples without culturing, offering a powerful method to deal with culture-negative cases. In this work, we assessed the feasibility of a metagenomic approach to detect the causative pathogens in resected valves from IE patients.\n\nUsing our in-house developed bioinformatics pipeline, we analyzed the sequencing results generated from both next-generation sequencing and Oxford Nanopore Technologies MinION nanopore sequencing for the direct identification of pathogens from the resected valves of seven clinically culture-negative IE patients according to the modified Duke criteria. Moreover, we were able to simultaneously characterize respective antimicrobial resistance features. This provides clinicians with valuable information to diagnose and treat IE patients after valve replacement surgery.

microbiology↗

bioRxiv2017

Inferring Relevant Cell Types For Complex Traits Using Single-Cell Gene Expression

Previous studies have prioritized trait-relevant cell types by looking for an enrichment of GWAS signal within functional regions. However, these studies are limited in cell resolution by the lack of functional annotations from difficult-to-characterize or rare cell populations. Measurement of single-cell gene expression has become a popular method for characterizing novel cell types, and yet, hardly any work exists linking single-cell RNA-seq to phenotypes of interest. To address this deficiency, we present RolyPoly, a regression-based polygenic model that can prioritize trait-relevant cell types and genes from GWAS summary statistics and single-cell RNA-seq. We demonstrate RolyPolys accuracy through simulation and validate previously known tissue-trait associations. We discover a significant association between microglia and late-onset Alzheimers disease, and an association between oligodendrocytes and replicating fetal cortical cells with schizophrenia. Additionally, RolyPoly computes a trait-relevance score for each gene which reflects the importance of expression specific to a cell type. We found that differentially expressed genes in the prefrontal cortex of Alzheimers patients were significantly enriched for highly ranked genes by RolyPoly gene scores. Overall, our method represents a powerful framework for understanding the effect of common variants on cell types contributing to complex traits.

genomics↗