Biology subjects

Pan, C.

Publications and source records attributed to Pan, C..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Genomic Regions and Variant Analysis Reveal Candidate Genes Associated with Age at First Service in Chinese Holstein Heifers

Understanding the genetic basis and identifying quantitative trait loci (QTL) for age at first service (AFS) is essential for improving reproductive efficiency and reducing economic costs in heifers rearing. We conducted a genome-wide association study (GWAS) for AFS using the genomic estimated breeding values (GEBVs) of 3,686 Chinese Holstein heifers, genotyped with 7,964,217 single nucleotide polymorphisms (SNPs) after quality control. Significant SNPs and candidate genes were identified and investigated through colocalization analysis of GWAS, expression QTL (eQTL), and splicing QTL (sQTL), and expression analysis in blood RNA sequencing (RNA-seq). The heritability estimate for AFS was moderate at 0.276 {+/-}0.025. Three QTL regions associated with AFS were identified: Region 1 on BTA6 (43688837-45007127 bp, 1.3 Mb with three 200kb windows), explaining 0.47% of genetic variance; Region 2 on BTA6 (62770788-62967316 bp) explaining 0.27% of the genetic variance; and Region 3 on BTA18 (6299721-6498934 bp) explaining 0.17% of the genetic variance. Combining GWAS and colocalization analysis, we identified ANAPC4, RBPJ, SEPSECS, SLC34A2, ZCCHC4, CCDC149, GNPDA2, GUF1, DHX15, SOD3, GUF1 and GNPDA2 as candidate genes. These genes are enriched in signaling pathways such as progesterone-mediated oocyte maturation, parathyroid hormone synthesis, secretion and action, and selenocompound metabolism. ANAPC4, DHX15, GUF1, SEPSECS, and SOD3 were also differently expressed genes (DEGs) in blood RNA-seq. Integrating the GWAS, colocalization, differential expression analysis, and existing literature, ANAPC4 and rs136363104 were highlighted as the putative causal gene and variant for puberty, respectively. In conclusion, our study identified three candidate regions and 12 candidate genes, confirming ANAPC4 as a putative causal gene influencing AFS. This research enhances the understanding of the genetic basis of AFS in Chinese Holstein heifers. The identified key genomic regions, candidate genes, and variants have the potential to improve reproductive efficiency and reduce economic costs in heifer rearing. Interpretative summaryThe economic burden of heifer-raising and reproductive inefficiency in dairy cattle is evident. The most important strategy for optimizing heifer-raising is selecting heifers with earlier puberty (sexual maturity) to shorten age at first service (AFS). In this study, we have identified key genomic regions and candidate genes on AFS in Chinese Holstein heifers by genome-wide association study, and validated them by colocalization and RNA-seq analysis. The findings have the potential to enhance the understanding of the genetic basis of reproductive traits, leading to more targeted breeding strategies for improved reproductive efficiency.

genetics↗

bioRxiv2025

Single-cell transcriptomics reveals targeted modulation of inflammatory repertoire by SOCE blockers

Store-operated calcium entry (SOCE) plays a critical role in regulating intracellular calcium signaling and is essential for immune cell functions. SOCE blockade with pyrazole derivative BTP2 has been explored as an anti-inflammatory strategy in preclinical models and Zegocractin (CM4620) is being investigated in Phase 2 clinical trials as an immunoregulatory agent. However, the mode of action and differential effects of SOCE blockade on diverse immune cell types remain largely unknown, limiting the precision of current therapeutic applications. Here, we used multiplexed single-cell RNA sequencing to investigate the effects of two prototypic SOCE blockers, BTP2 and CM4620, on polyclonally-stimulated, normal human peripheral blood mononuclear cells (PBMCs). The data revealed that SOCE blockade suppresses the expression of cytotoxicity-associated genes in CD8{square} effector T cells and natural killer (NK) cells, restoring them to levels comparable to those in unstimulated cells. Strikingly, SOCE blockade preserved activation-induced expression of anti-inflammatory genes in CD4{square} regulatory T cells, maintaining their tolerance phenotype even after SOCE blockade. These findings suggest that SOCE blockers modulate immune responses with greater selectivity than conventional immunosuppressants by reducing cytotoxicity while preserving tolerance-associated pathways, highlighting their potential for managing immune-mediated conditions, including organ transplantation. KEY POINTSO_LISOCE blockers BTP2 and CM4620 reduce cytotoxic gene expression in CD8{square} T cells and NK cells. C_LIO_LISOCE blockade preserves anti-inflammatory programs in CD4{square} Tregs, supporting selective immune modulation. C_LI

immunology↗

bioRxiv2025

Tryptophan metabolites as biomarkers to predict the severity and prognosis of acute ischemic stroke patients

BackgroundA growing body of evidence indicates alterations in metabolite levels and enzyme activities associated with the conversion of tryptophan (TRP) throughout the course of cerebral ischemia. In this study we aim to explore the potential relationship between TRP metabolism and clinical prognosis in acute ischemic stroke (AIS) patients of mainland China. MethodsBlood samples were obtained from a cohort of 304 patients diagnosed with AIS. The concentrations of ten TRP metabolites were quantified utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS). Stroke severity was evaluated upon admission using the National Institutes of Health Stroke Scale (NIHSS). A poor functional outcome was defined as modified Rankin scale (mRS) > 3, whereas a good functional outcome was defined by mRS [≤] 3 at 3 months post-stroke. LASSO regression and random forest algorithms were then employed to identify key TRP metabolism parameters associated with prognosis. ResultsFollowing the optimization of variable selection through Lasso regression, a prognostic risk model with 7-factors related to AIS was constructed, yielding an AUC of 0.917. Subsequently, a random forest analysis was conducted to establish an 11-factor prognostic risk model, which demonstrated an enhanced AUC of 1.000. Ultimately, three robust parameters related to TRP metabolism were identified. Multivariable logistic regression analysis, adjusted for covariates, revealed that TRP (odds ratio [OR] = 0.46, 95% confidence interval [CI]: 0.26 - 0.76, p = 0.004), the kynurenine (KYN)/TRP ratio (OR = 2.06, 95% CI: 1.23 - 3.60, p = 0.008), and the kynurenic acid (KYNA)/TRP ratio (OR = 2.15, 95% CI: 1.23 - 4.12, p = 0.014) were independently associated with poor functional prognosis. ConclusionsThe results of this study indicate that TRP metabolism is associated with the severity and prognosis of AIS. The TRP, KYN/TRP ratio and KYNA/TRP ratio may serve as potential biomarkers for 3-month prognostic evaluation.

neuroscience↗

bioRxiv2024

Modest functional diversity decline and pronounced composition shifts of microbial communities in a uranium-contaminated aquifer

BackgroundMicrobial taxonomic diversity declines with increased environmental stress. Yet, few studies have explored whether phylogenetic and functional diversities track taxonomic diversity along the stress gradient. Here, we investigated bacterial communities within an aquifer in Oak Ridge, Tennessee, USA, which is characterized by a broad spectrum of stressors, including extremely high levels of nitrate, heavy metals like cadmium and chromium, radionuclides such as uranium, and extremely low pH (<3). ResultsBoth taxonomic and phylogenetic -diversities were reduced in the most impacted wells, while the decline in functional -diversity was modest and statistically insignificant, indicating a more robust buffering capacity to environmental stress. Differences in functional gene composition (i.e., functional {beta}-diversity) were pronounced in highly contaminated wells, while convergent functional gene composition was observed in uncontaminated wells. The relative abundances of most carbon degradation genes were decreased in contaminated wells, but genes associated with denitrification, adenylylsulfate reduction, and sulfite reduction were increased. Compared to taxonomic and phylogenetic compositions, environmental variables played a more significant role in shaping functional gene composition, suggesting that niche selection could be more closely related to microbial functionality than taxonomy. ConclusionsOverall, we demonstrated that despite a reduced taxonomic -diversity, microbial communities under stress maintained functionality underpinned by environmental selection.

microbiology↗

bioRxiv2024

Dietary control of peripheral adipose storage capacity through membrane lipid remodelling

Complex genetic and dietary cues contribute to the development of obesity, but how these are integrated on a molecular level is incompletely understood. Here, we show that PPAR{gamma} supports hypertrophic expansion of adipose tissue via transcriptional control of LPCAT3, a membrane-bound O-acyltransferase that enriches diet-derived omega-6 (n-6) polyunsaturated fatty acids (PUFAs) in the phospholipidome. In high-fat diet-fed mice, lowering membrane n-6 PUFA levels by adipocyte-specific Lpcat3 knockout (Lpcat3AKO) or by dietary lipid manipulation leads to dysfunctional triglyceride (TG) storage, ectopic fat deposition and insulin resistance. Aberrant lipolysis of stored TGs in Lpcat3AKO adipose tissues instigates a non-canonical adaptive response that engages a futile lipid cycle to increase energy expenditure and limit further body weight gain. Mechanistically, we find that adipocyte LPCAT3 activity promotes TG storage by selectively enriching n-6 arachidonoyl-phosphatidylethanolamine at the ER-lipid droplet interface, which in turn favours the budding of large droplets that exhibit greater resistance to ATGL-dependent hydrolysis. Thus, our study highlights the PPAR{gamma}-LPCAT3 pathway as a molecular link between dietary n-6 PUFA intake, adipose expandability and systemic energy balance.

physiology↗

bioRxiv2024

Wheat stripe rust resistance gene Yr9, derived from rye, is a CC-NBS-LRR gene in a highly conserved NLR cluster

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a significant threat to global wheat production. Genetic resistance plays a crucial role in controlling this disease. Among wheat breeding innovations, the wheat-rye 1BL.1RS translocations are notable for introducing alien genetic diversity, partly due to the presence of the stripe rust resistance gene Yr9 on 1RS. To clone Yr9, we first identified four Pst-susceptible mutants from Lumai 15, which carries the 1BL.1RS translocation and Yr9. Using these mutants, we performed Sequencing Trait-Associated Mutations (STAM). A single candidate gene, YrChr1B, was identified within the Yr9 locus and later confirmed as Yr9 through genetic complementation and gene editing. The Yr9 gene encodes a coiled-coil nucleotide-binding site leucine-rich repeat (CC-NBS-LRR or NLR) protein and is part of a 14-member NLR gene cluster. This cluster is conserved among Triticeae species and is an ortholog of the barley Mla locus. Cloning Yr9 expands the genetic resources available for molecular wheat breeding aimed at durable and broad-spectrum disease resistance.

plant biology↗

bioRxiv2024

Absence of biofilm adhesin proteins changes surface attachment and cell strategy for Desulfovibrio vulgaris Hildenborough

Ubiquitous in nature, biofilms provide stability in a fluctuating environment and provide protection from stressors. Biofilms formed in industrial processes are exceedingly problematic and costly. While biofilms of sulfate-reducing bacteria in the environment are often beneficial because of their capacity to remove toxic metals from water, in industrial pipelines, these biofilms cause a major economic impact due to their involvement in metal and concrete corrosion. The mechanisms by which biofilms of sulfate-reducing bacteria form, however, is not well understood. Our previous work identified two proteins, named by their gene loci DVU1012 and DVU1545, as adhesins in the model sulfate-reducing bacterium, Desulfovibrio vulgaris Hildenborough. Both proteins are localized to the cell surface and the presence of at least one of the proteins, with either being sufficient, is necessary for biofilm formation to occur. In this study, differences in cell attachment and early biofilm formation in single deletion mutants of these adhesins were identified. Cells lacking DVU1012 had a different attachment strategy from wild-type and {Delta}DVU1545 cells, more often attaching as single cells than aggregates, which indicated that DVU1012 was more important for cell-to-cell attachment. {Delta}DVU1545 cells had increased cell attachment compared to wild-type cells when grown in static cultures. To date, comparisons of the D. vulgaris Hildenborough have been made to the large adhesion protein (Lap) system in environmental pseudomonads. Yet, we and others have shown distinct mechanistic differences in the systems. We propose to name these proteins in D. vulgaris Hildenborough biofilm formation system (Bfs) to facilitate comparisons. ImportanceBiofilms of sulfate-reducing bacteria contribute to biocorrosion, costing the U.S. hundreds of millions of dollars annually. In contrast, these biofilms can be used to bioremediate toxic heavy metals and to generate bioelectricity. As one of the most abundant groups of organisms on Earth, it is pertinent to better understand mechanistically how the biofilms of sulfate-reducing bacteria form so we may use this knowledge to help in efforts to mitigate biocorrosion, to promote bioremediation, and to produce clean energy. This study shows that the absence of either one of two biofilm adhesins impacts surface colonization by a sulfate-reducing bacterium, and that these two biofilm adhesins differ in their effect on cell attachment compared to other well-documented bacteria such as Pseudomonas species.

microbiology↗

bioRxiv2024

Deep Learning and 3D Imaging Reveal Whole-Body Alterations in Obesity

Many diseases, such as obesity, have systemic effects that impact multiple organ systems throughout the body. However, tools for comprehensive, high-resolution analysis of disease-associated changes at the whole-body scale have been lacking. Here, we developed a suite of deep learning-based image analysis algorithms (MouseMapper) and integrated it with tissue clearing and light-sheet microscopy to enable a comprehensive analysis of diseases impacting diverse systems across the mouse body. This approach enables the quantitative analysis of cellular and structural changes across the entire mouse body at unprecedented resolution and scale, including tracking nerves over several centimeters in whole animal bodies. To demonstrate its power, we applied MouseMapper to study nervous and immune systems in high-fat diet induced obesity. We uncovered widespread changes in both immune cell distribution and nerve structures, including alterations in the trigeminal nerve characterized by a reduced number of nerve endings in obese mice. These structural abnormalities were associated with functional deficits of whisker sensing and proteomic changes in the trigeminal ganglion, primarily affecting pathways related to axon growth and the complement system. Additionally, we found heterogeneity in obesity-induced whole-body inflammation across different tissues and organs. Our study demonstrates MouseMappers capability to discover and quantify pathological alterations at the whole-body level, offering a powerful approach for investigating the systemic impacts of various diseases. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=187 SRC="FIGDIR/small/608300v1_ufig1.gif" ALT="Figure 1"> View larger version (74K): org.highwire.dtl.DTLVardef@17d2601org.highwire.dtl.DTLVardef@14a2d3dorg.highwire.dtl.DTLVardef@e04114org.highwire.dtl.DTLVardef@d0b8b5_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIWe developed MouseMapper: AI-driven pipeline for whole-body structural analysis in mice C_LIO_LIMouseMapper revealed obesity-induced changes in nerves and immune cells across multiple organs C_LIO_LIMouseMapper identified facial nerve alterations in obesity linked to impaired whisker sensitivity C_LIO_LIMouseMapper has the potential for holistic 3D analysis of systemic diseases C_LI Supplementary Videos can be seen at: http://discotechnologies.org/MouseMapper/

systems biology↗

bioRxiv2024

Human Vascularized Macrophage-Islet Organoids to Model Immune-Mediated Pancreatic β cell Pyroptosis upon Viral Infection

There is a paucity of human models to study immune-mediated host damage. Here, we utilized the GeoMx spatial multi-omics platform to analyze immune cell changes in COVID-19 pancreatic autopsy samples, revealing an accumulation of proinflammatory macrophages. Single cell RNA-seq analysis of human islets exposed to SARS-CoV-2 or Coxsackievirus B4 (CVB4) viruses identified activation of proinflammatory macrophages and {beta} cell pyroptosis. To distinguish viral versus proinflammatory macrophage-mediated {beta} cell pyroptosis, we developed human pluripotent stem cell (hPSC)-derived vascularized macrophage-islet (VMI) organoids. VMI organoids exhibited enhanced marker expression and function in both {beta} cells and endothelial cells compared to separately cultured cells. Notably, proinflammatory macrophages within VMI organoids induced {beta} cell pyroptosis. Mechanistic investigations highlighted TNFSF12-TNFRSF12A involvement in proinflammatory macrophage-mediated {beta} cell pyroptosis. This study established hPSC- derived VMI organoids as a valuable tool for studying immune cell-mediated host damage and uncovered mechanism of {beta} cell damage during viral exposure.

developmental biology↗

bioRxiv2024

Contributions of genetic variation in astrocytes to cell and molecular mechanisms of risk and resilience to late onset Alzheimer's disease

Reactive astrocytes are associated with Alzheimers disease (AD), and several AD genetic risk variants are associated with genes highly expressed in astrocytes. However, the contribution of genetic risk within astrocytes to cellular processes relevant to the pathogenesis of AD remains ill-defined. Here we present a resource for studying AD genetic risk in astrocytes using a large collection of induced pluripotent stem cell (iPSC) lines from deeply phenotyped individuals with a range of neuropathological and cognitive outcomes. IPSC lines from forty-four individuals were differentiated into astrocytes followed by unbiased molecular profiling using RNA sequencing and tandem mass tag-mass spectrometry. We demonstrate the utility of this resource in examining gene- and pathway-level associations with clinical and neuropathological traits, as well as in analyzing genetic risk and resilience factors through parallel analyses of iPSC-astrocytes and brain tissue from the same individuals. Our analyses reveal that genes and pathways altered in iPSC-derived astrocytes from AD individuals are concordantly dysregulated in AD brain tissue. This includes increased prefoldin proteins, extracellular matrix factors, COPI-mediated trafficking components and reduced proteins involved in cellular respiration and fatty acid oxidation. Additionally, iPSC-derived astrocytes from individuals resilient to high AD neuropathology show elevated basal levels of interferon response proteins and increased secretion of interferon gamma. Correspondingly, higher polygenic risk scores for AD are associated with lower levels of interferon response proteins. This study establishes an experimental system that integrates genetic information with a heterogeneous set of iPSCs to identify genetic contributions to molecular pathways affecting AD risk and resilience.

neuroscience↗

bioRxiv2024

Nanopore Direct RNA Sequencing Reveals Virus-Induced Changes in the Transcriptional Landscape in Human Bronchial Epithelial Cells

Direct RNA nanopore sequencing data reveals changes in gene expression, polyadenylation, splicing, m6A methylation, and pseudouridylation in response to influenza virus exposure of primary human bronchial epithelial cells. This study focuses on the epitranscriptomic profile of genes in the host immune response. In addition to polyadenylated noncoding RNA, we purified and sequenced nonpolyadenylated noncoding RNA and observed changes in expression, N6-methyl-adenosine (m6A), and pseudouridylation ({Psi}) in these novel RNA. Two recently discovered lincRNA with roles in immune response, Chaserr and LEADR, are predicted in the analysis of the sequencing data to be highly methylated in response to influenza exposure. Several H/ACA type snoRNAs that guide pseudouridylation are decreased in expression in response to influenza, and there is a corresponding predicted decrease in the pseudouridylation of two novel lncRNA. Thus, novel epitranscriptomic changes revealed by direct RNA sequencing with nanopore technology provide unique insights into the host epitranscriptomic changes in epithelial gene networks that respond to influenza virus exposure.

bioinformatics↗

bioRxiv2024

Midline Assembloids Reveal Regulators of Human Axon Guidance

Organizers are specialized cell populations that orchestrate cell patterning and axon guidance in the developing nervous system. Although non-human models have led to fundamental discoveries about the organization of the nervous system midline by the floor plate, an experimental model of human floor plate would enable broader insights into regulation of human neurodevelopment and midline connectivity. Here, we have developed stem cell-derived organoids resembling human floor plate (hFpO) and assembled them with spinal cord organoids (hSpO) to generate midline assembloids (hMA). We demonstrate that hFpO promote Sonic hedgehog-dependent ventral patterning of human spinal progenitors and Netrin-dependent guidance of human commissural axons, paralleling non-human models. To investigate evolutionary-divergent midline regulators, we profiled the hFpO secretome and identified 27 evolutionarily divergent genes between human and mouse. Utilizing the hMA platform, we targeted these candidates in an arrayed CRISPR knockout screen and reveal that GALNT2, a gene involved in O-linked glycosylation, impairs floor plate-mediated guidance of commissural axons in humans. This novel platform extends prior axon guidance discoveries into human-specific neurobiology with implications for mechanisms of nervous system evolution and neurodevelopmental disorders.

neuroscience↗

bioRxiv2024

The Kv2.2 channel mediates the inhibition of Prostaglandin E2 on glucose-stimulated insulin secretion in pancreatic β/-cells

Prostaglandin E2 (PGE2) is an endogenous inhibitor of glucose-stimulated insulin secretion (GSIS) and plays an important role in pancreatic {beta}-cell dysfunction in type 2 diabetes mellitus (T2DM). This study aimed to explore the underlying mechanism by which PGE2 inhibits GSIS. Our results showed that PGE2 inhibited Kv2.2 channels via increasing PKA activity in HEK293T cells overexpressed with Kv2.2 channels. Point mutation analysis demonstrated that S448 residue was responsible for the PKA-dependent modulation of Kv2.2. Furthermore, the inhibitory effect of PGE2 on Kv2.2 was blocked by EP2/4 receptor antagonists, while mimicked by EP2/4 receptor agonists. The immune fluorescence results showed that EP1-EP4 receptors are expressed in both mouse and human {beta}-cells. In INS-1(832/13) {beta}-cells, PGE2 inhibited voltage-gated potassium currents and electrical activity through EP2/4 receptors and Kv2.2 channels. Knockdown of Kv2.2 reduced the action potential firing frequency and alleviated the inhibition of PGE2 on GSIS in INS-1(832/13) {beta}-cells. PGE2 impaired glucose tolerance in wild-type mice but did not alter glucose tolerance in Kv2.2 knockout mice. Knockout of Kv2.2 reduced electrical activity, GSIS and abrogated the inhibition of PGE2 on GSIS in mouse islets. In conclusion, we have demonstrated that PGE2 inhibits GSIS in pancreatic {beta}-cells through the EP2/4-Kv2.2 signaling pathway. The findings highlight the significant role of Kv2.2 channels in the regulation of {beta}-cell repetitive firing and insulin secretion, and contribute to the understanding of the molecular basis of {beta}-cell dysfunction in diabetes.

physiology↗

bioRxiv2024

Systems genetics approach uncovers associations between host amylase locus, gut microbiome and metabolic traits in hyperlipidemic mice

The molecular basis for how host genetic variation impacts gut microbial community and bacterial metabolic niches remain largely unknown. We leveraged 90 inbred hyperlipidemic mouse strains from the Hybrid Mouse Diversity Panel (HMDP), previously studied for a variety of cardio-metabolic traits. Metagenomic analysis of cecal DNA followed by genome-wide association analysis identified genomic loci that were associated with microbial enterotypes in the gut. Among these we detected a genetic locus surrounding multiple amylase genes that was associated with abundances of Firmicutes (Lachnospiraceae family) and Bacteroidetes (Muribaculaceae family) taxa encoding distinct starch and sugar metabolism functions. We also found that lower amylase gene number in the mouse genome was associated with higher gut Muribaculaceae levels. Previous work suggests that modulation of host amylase activity impacts the availability of carbohydrates to the host and potentially to gut bacteria. The genetic variants described above were associated with distinct gut microbial communities (enterotypes) with different predicted metabolic capacities for carbohydrate degradation. Mendelian randomization analysis revealed host phenotypes, including liver fibrosis and plasma HDL-cholesterol levels, that were associated with gut microbiome enterotypes. This work reveals novel relationships between host genetic variation, gut microbial enterotypes and host physiology/disease phenotypes in mice.

genetics↗

bioRxiv2024

Effects of different feeding methods on serum biochemical indexes, metabolic indexes, immune indexes, and intestinal microorganisms of Nanjiang yellow goats

The intestinal microbiota significantly influences the intake, storage, and absorption of nutrients in animals, thereby greatly impacting the growth and development of the animals. Factors such as diet, animal breed, growth stage, and feeding methods may affect variations in the composition of the intestinal microbiota. However, research on the variations in the intestinal microbiota and metabolites of Nanjiang Yellow goats under different feeding methods is still unclear. We measured various serum biochemical indicators and immune biochemical indicators and found that the triglyceride (TC) content in the grazing group (the FMMF) was significantly lower than in the barn-feeding group (the SSMF) (P<0.05). Serum levels of immunoglobulin A (IgA), immunoglobulin G (IgG), and immunoglobulin G (IgM) were higher in the FMMF group. At the phylum level, the most abundant bacteria were Firmicutes, Bacteroidota, and Verrucomicrobiota. At the genus level, the most abundant microbial groups were Christensenellaceae_R-7_group, UCG-005, and Rikenellaceae_RC9_gut_group. Differential metabolite enrichment analysis through KEGG pathways revealed that the most remarkably enriched pathway was "Metabolic pathways," including Steroid hormone biosynthesis and Arachidonic acid metabolism, among others. Analyzed by multi-omics association, we identified notably different microbial features correlated with immune indicators and metabolites after different feeding methods. We observed a significant negative correlation (P<0.05) between the concentrations of serum immune factors interleukin-2 (IL-2), interleukin-4 (IL-4), and g__probable_genus_10. The concentration of IgM in serum showed a highly significant positive correlation (P<0.01) with the relative abundance of g__Erysipelatoclostridium in the intestine. Interestingly, most differential metabolites were significantly associated with intestinal microbiota. This experiment indicates that different feeding methods may influence the diversity and relative abundance of the intestinal microbiota in Nanjiang Yellow goats. The intestinal microbiota is correlated with immune indicators and metabolism, and regulating the diversity and relative abundance of the intestinal microbiota can be a way to adjust metabolism, thereby promoting the healthy growth of the Nanjiang Yellow goats.

microbiology↗

bioRxiv2023

Interpretable Online Network Dictionary Learning for Inferring Long-Range Chromatin Interactions

Dictionary learning (DL), implemented via matrix factorization (MF), is commonly used in computational biology to tackle ubiquitous clustering problems. The method is favored due to its conceptual simplicity and relatively low computational complexity. However, DL algorithms produce results that lack interpretability in terms of real biological data. Additionally, they are not optimized for graph-structured data and hence often fail to handle them in a scalable manner. In order to address these limitations, we propose a novel DL algorithm called online convex network dictionary learning (online cvxNDL). Unlike classical DL algorithms, online cvxNDL is implemented via MF and designed to handle extremely large datasets by virtue of its online nature. Importantly, it enables the interpretation of dictionary elements, which serve as cluster representatives, through convex combinations of real measurements. Moreover, the algorithm can be applied to data with a network structure by incorporating specialized subnetwork sampling techniques. To demonstrate the utility of our approach, we apply cvxNDL on 3D-genome RNAPII ChIA-Drop data with the goal of identifying important long-range interaction patterns (long-range dictionary elements). ChIA-Drop probes higher-order interactions, and produces data in the form of hypergraphs whose nodes represent genomic fragments. The hyperedges represent observed physical contacts. Our hypergraph model analysis has the objective of creating an interpretable dictionary of long-range interaction patterns that accurately represent global chromatin physical contact maps. Through the use of dictionary information, one can also associate the contact maps with RNA transcripts and infer cellular functions. To accomplish the task at hand, we focus on RNAPII-enriched ChIA-Drop data from Drosophila Melanogaster S2 cell lines. Our results offer two key insights. First, we demonstrate that online cvxNDL retains the accuracy of classical DL (MF) methods while simultaneously ensuring unique interpretability and scalability. Second, we identify distinct collections of proximal and distal interaction patterns involving chromatin elements shared by related processes across different chromosomes, as well as patterns unique to specific chromosomes. To associate the dictionary elements with biological properties of the corresponding chromatin regions, we employ Gene Ontology (GO) enrichment analysis and perform multiple RNA coexpression studies. Availability and ImplementationThe code and test datasets are available at:\ https://github.com/rana95vishal/chromatin_DL/ Author summaryWe introduce a novel method for dictionary learning termed online convex Network Dictionary Learning (online cvxNDL). The method operates in an online manner and utilizes representative subnetworks of a network dataset as dictionary elements. A key feature of online cvxNDL is its ability to work with graph-structured data and generate dictionary elements that represent convex combinations of real data points, thus ensuring interpretability. Online cvxNDL is used to investigate long-range chromatin interactions in S2 cell lines of Drosophila Melanogaster obtained through RNAPII ChIA-Drop measurements represented as hypergraphs. The results show that dictionary elements can accurately and efficiently reconstruct the original interactions present in the data, even when subjected to convexity constraints. To shed light on the biological relevance of the identified dictionaries, we perform Gene Ontology enrichment and RNA-seq coexpression analyses. These studies uncover multiple long-range interaction patterns that are chromosome-specific. Furthermore, the findings affirm the significance of convex dictionaries in representing TADs cross-validated by imaging methods (such as 3-color FISH (fluorescence in situ hybridization)).

genomics↗

bioRxiv2023

An interactive web application for exploring human plasma and fibroblast metabolomics data from patients with inborn errors of metabolism

Metabolomic profiling is instrumental in understanding the systemic and cellular impact of inborn errors of metabolism (IEMs), monogenic disorders caused by pathogenic genomic variants in genes involved in metabolism. This study encompasses untargeted metabolomics analysis of plasma from 474 individuals and fibroblasts from 67 subjects, incorporating healthy controls, patients with 65 different monogenic diseases, and numerous undiagnosed cases. We introduce a web application designed for the in-depth exploration of this extensive metabolomics database. The application offers a user-friendly interface for data review, download, and detailed analysis of metabolic deviations linked to IEMs at the level of individual patients or groups of patients with the same diagnosis. It also provides interactive tools for investigating metabolic relationships and offers comparative analyses of plasma and fibroblast profiles. This tool emphasizes the metabolic interplay within and across biological matrices, enriching our understanding of metabolic regulation in health and disease. As a resource, the application provides broad utility in research, offering novel insights into metabolic pathways and their alterations in various disorders.

bioinformatics↗

bioRxiv2023

A Spatiotemporal and Machine-Learning Platform Accelerates the Manufacturing of hPSC-derived Esophageal Mucosa

Human pluripotent stem cell-derived tissue engineering offers great promise in designer cell-based personalized therapeutics. To harness such potential, a broader approach requires a deeper understanding of tissue-level interactions. We previously developed a manufacturing system for the ectoderm-derived skin epithelium for cell replacement therapy. However, it remains challenging to manufacture the endoderm-derived esophageal epithelium, despite both possessing similar stratified structure. Here we employ single cell and spatial technologies to generate a spatiotemporal multi-omics cell atlas for human esophageal development. We illuminate the cellular diversity, dynamics and signal communications for the developing esophageal epithelium and stroma. Using the machine-learning based Manatee, we prioritize the combinations of candidate human developmental signals for in vitro derivation of esophageal basal cells. Functional validation of the Manatee predictions leads to a clinically-compatible system for manufacturing human esophageal mucosa. Our approach creates a versatile platform to accelerate human tissue manufacturing for future cell replacement therapies to treat human genetic defects and wounds.

developmental biology↗