Biology subjects

Lu, A.

Publications and source records attributed to Lu, A..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

Proliferating cell nuclear antigen involves in temperature stress tolerance of Ulva prolifera

Ulva prolifera is the dominant species of "green tide", and has higher tolerance to environmental stresses such as temperature. However, the molecular mechanisms are still unclear. Here, transcriptome analysis, Western blot and RT-qPCR analysis of U. prolifera suggested that, under temperature stresses (4{degrees}C, 36{degrees}C), the expression of PCNA and CyclinA was promoted, and the MAPK signaling was activated. Besides, the results showed that PCNA interacted with CyclinA. Interestingly, the expression of miR-2916, which was predicted to bind PCNA at -552[~]-772, was negatively correlated with the expression of PCNA under temperature stresses (4{degrees}C, 36{degrees}C). In addition, the results showed that low temperature (4{degrees}C) had no obvious effect on the survival, the formation of cell walls, and the division of protoplasts. However, high temperature (36{degrees}C) had obvious effect on them. PCNA inhibitors increased the sensitivity of the protoplasts under temperature stresses. Together, our results suggested PCNA regulating the proliferation in response to the temperature stress of U. prolifera was associated with miR-2916/PCNA/CyclinA/MAPK pathway. In conclusion, the study preliminarily illuminates the molecular mechanism in response to temperature stress of U. prolifera, and may provide a new insight for prevention of green tide.

cell biology↗

bioRxiv2023

Tissue-specific sex difference in mouse eye and brain metabolome under fed and fasted states

PurposeVisual physiology and various ocular diseases demonstrate sexual dimorphisms; however, how sex influences metabolism in different eye tissues remains undetermined. This study aims to address common and tissue-specific sex differences in metabolism in the retina, retinal pigment epithelium (RPE), lens and brain under fed and fasted conditions. MethodsAfter ad libitum fed or deprived of food for 18 hours, mouse eye tissues (retina, RPE/choroid, and lens), brain, and plasma were harvested for targeted metabolomics. The data were analyzed with both Partial least squares-discriminant analysis (PLS-DA) and Volcano Plot analysis. ResultsAmong 133 metabolites that cover major metabolic pathways, we found 9-45 metabolites that are sex-different in different tissues under the fed state and 6-18 metabolites under the fasted state. Among these sex-different metabolites, 33 were changed in two or more tissues, and 64 were tissue-specific. Pantothenic acid, hypotaurine and 4-hydroxyproline were the top commonly changed metabolites. Lens and retina had the most tissue-specific sex-different metabolites enriched in the metabolism of amino acid, nucleotide, lipids and TCA cycle. Lens and brain had more similar sex-different metabolites than other occular tissues. Female RPE and female brain were more sensitive to fasting with more reduced metabolites in amino acid metabolism, TCA cycle and glycolysis. The plasma had the least sex-different metabolites with very few overlapping changes with tissues. ConclusionSex has a strong influence on eye and brain metabolism in tissue-specific and metabolic state-specific manners. Our findings may implicate the sexual dimorphisms in eye physiology and susceptibility to ocular diseases.

biochemistry↗

bioRxiv2022

Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer.

Glucose and glutamine are major carbon and energy sources that promote the fast proliferation of cancer cells. Metabolic shifs observed on cell line or mouse models may not reflect the general metabolic shifts in real human cancer tissue. In this study, we conducted a computational characterization of the flux distribution and variations of the central energy metabolism and key branches in a pan-cancer analysis, including glycolytic pathway, production of lactate, TCA cycle, nucleic acids synthesis, glutaminolysis, glutaminate, glutamine and glutathione metabolism, amino acids synthesis, in 11 cancer subtypes and 9 matched adjacent normal tissue types, by using TCGA tissue transcriptomics data. Our analysis confirms the increased influx in glucose uptake and glycolysis and decreased upper part of TCA cycle, i.e., Warbug effect in the analyzed cancer types. However, consistently increased lactate production and second half of TCA cycle were only seen in certain cancer types. More interestingly, we did not see cancer tissues have highly shifted glutaminolysis compared to their adjacent normal controls. A systems biology model of metabolic shifts in through cancer and tissue types is further developed and analyzed. We observed that (1) normal tissues have distinct metabolic phenotypes, (2) cancer types have drastically different metabolic shifts compared to their adjacent normal controls, and (3) the different shifts happened to tissue specific metabolic phenotypes result in a converged metabolic phenotype through cancer types and cancer progression. This study strongly suggests the possibility to have a unified framework for studies of cancer-inducing stressors, adaptive metabolic reprogramming, and cancerous behaviors.

bioinformatics↗

bioRxiv2022

Structural journey of an insecticidal pore-forming protein targeting western corn rootworm

Broad adoption of transgenic crops has revolutionized agriculture. However, resistance to insecticidal proteins by agricultural pests poses a continuous challenge to maintaining crop productivity and new proteins are urgently needed to replace existing transgenic traits. We identified an insecticidal membrane attack complex/perforin (MACPF) protein, Mpf2Ba1, with strong activity against western corn rootworm larvae and a novel site of action. By integrating X-ray crystallography, cryo-EM, and modelling, we determined monomeric, pre-pore and pore structures, revealing changes between structural states at atomic resolution. We discovered a monomer inhibition mechanism, a molecular "switch" associated with pre-pore activation/oligomerization upon gut fluid incubation and solved the highest resolution MACPF pore structure to-date. Our findings provide a mechanistic basis for Mpf2Ba1 effectiveness as an insecticidal protein with potential for biotechnology development. One-Sentence SummaryThe molecular mechanism of an insecticidal protein is revealed through 3D structures of the three main pore formation states

molecular biology↗

bioRxiv2022

Exploring high-quality microbial genomes by assembly of linked-reads with high barcode specificity using deep learning

Despite long-read sequencing enables to generate complete genomes of unculturable microbes, its high cost hinders its widespread application in large cohorts. An alternative method is to assemble short-reads with long-range connectivity, which can be a cost-effective way to generate high-quality microbial genomes. We developed Pangaea to improve metagenome assembly using short-reads with physical or virtual barcodes. It adopts a deep-learning-based binning algorithm to assemble the co-barcoded reads with similar sequence contexts and abundances to improve assemblies of high- and medium-abundance microbes. Pangaea also leverages a multi-thresholding reassembly strategy to refine assembly for low-abundance microbes. We benchmarked Pangaea with linked-reads and a combination of short- and long-reads from mock communities and human gut metagenomes. Pangaea achieved significantly higher contig continuity as well as more near-complete metagenome-assembled genomes (NCMAGs) than the existing assemblers. Pangaea was also observed to generate three complete and circular NCMAGs on the human gut microbiomes.

genomics↗

bioRxiv2022

scFLUX: a web server for metabolic flux and variation prediction using transcriptomics data

Quantitative assessment of single cell fluxome is critical for understanding the metabolic heterogeneity in diseases. Unfortunately, single cell fluxomics using laboratory approaches is currently infeasible, and none of the current flux estimation tools could achieve single cell resolution. In light of the natural associations between transcriptomic and metabolomic profiles, it remains both a feasible and urgent task to use the available single cell transcriptomics data for prediction of single cell fluxome. We present scFLUX here, which provides an online platform for prediction of metabolic fluxome and variations using transcriptomics data, on individual cell or sample level. This is in contrast to other flux estimation methods that are only able to model the fluxes for cells of pre-defined groups. The scFLUX webserver implements our in-house single cell flux estimation model, namely scFEA, which integrates a novel graph neural network architecture with a factor graph derived from the complex human metabolic network. To the best of our knowledge, scFLUX is the first and only web-based tool dedicated to predicting individual sample-/cell-metabolic fluxome and variations of metabolites using transcriptomics data. scFLUX is available at http://scflux.org/. The stand-alone tools for using scFLUX locally are available at https://github.com/changwn/scFEA.

bioinformatics↗

bioRxiv2022

Biological age is increased by stress and restored upon recovery

Aging is classically conceptualized as an ever-increasing trajectory of damage accumulation and loss of function, leading to increases in morbidity and mortality. However, recent in vitro studies have raised the possibility of age reversal. Here, we report that biological age is fluid and exhibits rapid changes in both directions. By applying advanced epigenetic aging clocks, we find that the biological age of young mice is increased by heterochronic parabiosis and restored following surgical detachment of animals. We also identify transient changes in biological age during major surgery, pregnancy, and severe COVID-19 in humans and/or mice. Together, these data show that biological age undergoes a rapid increase in response to diverse forms of stress, which is reversed following recovery from stress. Our study uncovers a new layer of aging dynamics that should be considered in future studies. Elevation of biological age by stress may be a quantifiable and actionable target for future interventions.

systems biology↗

bioRxiv2022

Viruses inhibit TIR gcADPR signaling to overcome bacterial defense

The Toll/interleukin-1 receptor (TIR) domain is a key component of immune receptors that identify pathogen invasion in bacteria, plants, and animals. In the bacterial antiphage system Thoeris, as well as in plants, recognition of infection stimulates TIR domains to produce an immune signaling molecule whose molecular structure remained elusive. This molecule binds and activates the Thoeris immune effector, which then executes the immune function. We identified a large family of phage-encoded proteins, denoted here Thoeris anti-defense 1 (Tad1), that inhibit Thoeris immunity. We found that Tad1 proteins are "sponges" that bind and sequester the immune signaling molecule produced by TIR-domain proteins, thus decoupling phage sensing from immune effector activation and rendering Thoeris inactive. A high-resolution crystal structure of Tad1 bound to the signaling molecule revealed that its chemical structure is 1'-2' glycocyclic ADPR (gcADPR), a unique molecule not previously described in other biological systems. Our results define the chemical structure of a central immune signaling molecule, and reveal a new mode of action by which pathogens can suppress host immunity.

microbiology↗

bioRxiv2022

ReDisX: a Continuous Max Flow-based framework to redefine the diagnosis of diseases based on identified patterns of genomic signatures

Diseases originate at the molecular-genetic layer, manifest through altered biochemical homeostasis, and develop symptoms later. Hence symptomatic diagnosis is inadequate to explain the underlying molecular-genetic abnormality and individual genomic disparities. The current trends include molecular-genetic information relying on algorithms to recognize the disease subtypes through gene expressions. Despite their disposition toward disease-specific heterogeneity and cross-disease homogeneity, a gap still exists to describe the extent of homogeneity within the heterogeneous subpopulation of different diseases. They are limited to obtaining the holistic sense of the whole genome-based diagnosis resulting in inaccurate diagnosis and subsequent management. To fill those gaps, we proposed ReDisX framework, a scalable machine learning algorithm that uniquely classifies patients based on their genomic signatures. It was deployed to re-categorizes the patients with rheumatoid arthritis and coronary artery disease. It reveals heterogeneous subpopulations within a disease and homogenous subpopulations across different diseases. Besides, it identifies GZMB as a subpopulation-differentiation marker that plausibly serves as a prominent indicator for GZMB-targeted drug repurposing. The ReDisX framework offers a novel strategy to redefine disease diagnosis through characterizing personalized genomic signatures. It may rejuvenate the landscape of precision and personalized diagnosis, and a clue to drug repurposing.

bioinformatics↗

bioRxiv2021

Lateralization of autonomic activity in response to limb-specific threat

In times of stress or danger, the autonomic nervous system (ANS) signals the fight or flight response. A canonical function of ANS activity is to globally mobilize metabolic resources, preparing the organism to respond to threat. Yet a body of research has demonstrated that, rather than displaying a homogenous pattern across the body, autonomic responses to arousing events -- as measured through changes in electrodermal activity (EDA) -- can differ between right and left body locations. Surprisingly, the metabolic function of such ANS asymmetry has not been investigated. In the current study, we investigated whether asymmetric autonomic responses could be induced through limb-specific aversive stimulation. Participants were given mild electric stimulation to either the left or right arm while EDA was monitored bilaterally. Across participants, a strong ipsilateral EDA response bias was observed, with increased EDA response in the hand adjacent to the stimulation. This effect was observable in over 50% of individual subjects. These results demonstrate that autonomic output is more complex than canonical interpretations suggest. We suggest that, in stressful situations, autonomic outputs can prepare either the whole-body fight or flight response, or a simply a limb-localized flick, which can effectively neutralize the threat while minimizing global resource consumption. These findings provide insight into the evolutionary pathway of neural systems processing general arousal by linking observed asymmetry in the peripheral arousal response to a historical leveraging of neural structures organized to mediate responses to localized threat.

neuroscience↗

bioRxiv2021

Maternal effects on early-life gut microbiome maturation in a wild nonhuman primate

Early-life gut microbial colonization is an important process shaping host physiology, immunity and long-term health outcomes in humans and other animals. However, our understanding of this dynamic process remains poorly investigated in wild animals, where developmental mechanisms can be better understood within ecological and evolutionary relevant contexts. Using 16s rRNA amplicon sequencing on 525 fecal samples from a large cohort of infant and juvenile geladas (Theropithecus gelada), we characterized gut microbiome maturation during the first three years of life and assessed the role of maternal effects in shaping offspring microbiome assembly. Microbial diversity increased rapidly in the first months of life, followed by more gradual changes until weaning. As expected, changes in gut microbiome composition and function with increasing age reflected progressive dietary transitions: in early infancy when infants rely heavily on their mothers milk, microbes that facilitate milk glycans and lactose utilization dominated, while later in development as graminoids are progressively introduced into the diet, microbes that metabolize plant complex polysaccharides became dominant. Furthermore, the microbial community of nursing infants born to first-time (primiparous) mothers was more "milk-oriented" compared to similarly-aged infants born to experienced (multiparous) mothers. Comparisons of matched mother-offspring fecal samples to random dyads did not support vertical transmission as a conduit for these maternal effects, which instead could be explained by slower phenotypic development (and associated slower gut microbiome maturation) in infants born to first-time mothers. Together, our findings highlight the dynamic nature of gut colonization in early life and the role of maternal effects in modulating this trajectory in a wild primate.

microbiology↗

bioRxiv2021

A systematic evaluation of 41 DNA methylation predictors across 101 data preprocessing and normalization strategies highlights considerable variation in algorithm performance

BackgroundDNA methylation (DNAm) based predictors hold great promise to serve as clinical tools for health interventions and disease management. While these algorithms often have high prediction accuracy and are associated with many disease-related phenotypes, the reliability of their performance remains to be determined. We therefore conducted a systematic evaluation across 101 different data processing strategies that preprocess and normalize DNAm data and assessed how each analytical strategy affects the reliability and prediction accuracy of 41 DNAm-based predictors. ResultsOur analyses were conducted in a large EPIC DNAm sample of the Jackson Heart Study (N=2,053) that included 146 pairs of technical replicate samples. By estimating the average absolute agreement between replicate pairs, we show that 32 out of 41 predictors (78%) demonstrate excellent test-retest reliability when appropriate data processing and normalization steps are implemented. Across all pairs of predictors, we find a moderate correlation in performance across analytical strategies (mean rho=0.40, SD=0.27), highlighting significant heterogeneity in performance across algorithms within a choice of an analytical pipeline. (Un)successful removal of technical variation furthermore significantly impacts downstream phenotypic association analysis, such as all-cause mortality risk associations. ConclusionsWe show that DNAm-based algorithms are sensitive to technical variation. The right choice of data processing and normalization pipeline is important to achieve reproducible estimates and improve prediction accuracy in downstream phenotypic association analyses. For each of the 41 DNAm predictors, we report its test-retest reliability and provide the best performing analytical strategy as a guideline for the research community. As DNAm-based predictors become more and more widely used, both for research purposes as well as for clinic applications, our work helps improve their performance and standardize their implementation.

genomics↗

bioRxiv2021

Multi-context genetic modeling of transcriptional regulation resolves novel disease loci

A majority of the variants identified in genome-wide association studies fall in non-coding regions of the genome, indicating their mechanism of impact is mediated via gene expression. Leveraging this hypothesis, transcriptome-wide association studies (TWAS) have assisted in both the interpretation and discovery of additional genes associated with complex traits. However, existing methods for conducting TWAS do not take full advantage of the intra-individual correlation inherently present in multi-context expression studies and do not properly adjust for multiple testing across contexts. We developed CONTENT-- a computationally efficient method with proper cross-context false discovery correction that leverages correlation structure across contexts to improve power and generate context-specific and context-shared components of expression. We applied CONTENT to bulk multi-tissue and single-cell RNA-seq data sets and show that CONTENT leads to a 42% (bulk) and 110% (single cell) increase in the number of genetically predicted genes relative to previous approaches. Interestingly, we find the context-specific component of expression comprises 30% of heritability in tissue-level bulk data and 75% in single-cell data, consistent with cell type heterogeneity in bulk tissue. In the context of TWAS, CONTENT increased the number of gene-phenotype associations discovered by over 47% relative to previous methods across 22 complex traits.

genomics↗

bioRxiv2021

High-altitude adaptation and incipient speciation in geladas

Survival at high altitude requires adapting to extreme conditions such as environmental hypoxia. To understand high-altitude adaptations in a primate, we assembled the genome of the gelada (Theropithecus gelada), an endemic Ethiopian monkey, and complemented it with population resequencing, hematological, and morphometric data. Unexpectedly, we identified a novel karyotype that may contribute to reproductive isolation between gelada populations. We also identified genomic elements including protein-coding sequences and gene families that exhibit accelerated changes in geladas and may contribute to high-altitude adaptation. Our findings lend insight into mechanisms of speciation and adaptation while providing promising avenues for functional hypoxia research.

genomics↗

bioRxiv2021

Physicochemical and Pharmacokinetic Properties Determining Drug Detection in Skin

Chemicals, including some systemically administered xenobiotics and their biotransformations, can be detected noninvasively using skin swabs and untargeted metabolomics analysis. We sought to understand the principal drivers that determine whether a drug taken orally or systemically is likely to be observed on the epidermis by using a random forest classifier to predict which drugs would be detected on the skin. A variety of molecular descriptors describing calculated properties of drugs, such as measures of volume, electronegativity, bond energy, and electrotopology, were used to train the classifier. The mean area under the ROC curve was 0.71 for predicting drug detection on the epidermis, and the SHapley Additive exPlanations model interpretation technique was used to determine the most relevant molecular descriptors. Based on the analysis of 2,561 FDA approved drugs, we predict that therapeutic drug classes such as nervous system drugs are more likely to be detected on the skin. Detecting drugs and other chemicals noninvasively on the skin using untargeted metabolomics could be a useful clinical advancement in therapeutic drug monitoring, adherence, and health status.

bioinformatics↗

bioRxiv2021

Myeloid-to-mesenchymal NGF-p75 signaling coordinates skeletal cell migration during repair

Bone regeneration following injury is initiated by inflammatory signals and occurs in association with infiltration by sensory nerve fibers. Together, these events are believed to coordinate angiogenesis and tissue reprogramming, but the mechanism of coupling immune signals to re-innervation and osteogenesis is unknown. Here, we found that NGF is expressed following cranial bone injury and signals via p75 in resident mesenchymal osteogenic precursors to impact their migration into the damaged tissue. Mice lacking Ngf in myeloid cells demonstrated reduced migration of osteogenic precursors to the injury site with consequently delayed bone healing. These features were phenocopied by mice lacking p75 in Pdgfra+ osteoblast precursors. Single-cell transcriptomics identified mesenchymal subpopulations with potential roles in cell migration and immune response, altered in the context of p75 deletion. Together, these results identify the role of p75 signaling pathway in coordinating skeletal cell migration during early bone repair.

cell biology↗

bioRxiv2021

Genetic Analyses of Epigenetic Predictors that Estimate Aging, Metabolic Traits, and Lifespan

Changes in DNA methylation (DNAm) are linked to aging. Here, we profile highly conserved CpGs in 339 predominantly female mice belonging to the BXD family for which we have deep longevity and genomic data. We use a pan-mammalian microarray that provides a common platform for assaying the methylome across mammalian clades. We computed epigenetic clocks and tested associations with DNAm entropy, diet, weight, metabolic traits, and genetic variation. We describe the multifactorial variance of methylation at these CpGs, and show that high fat diet augments the age-associated changes. Entropy increases with age. The progression to disorder, particularly at CpGs that gain methylation over time, was predictive of genotype-dependent life expectancy. The longer-lived BXD strains had comparatively lower entropy at a given age. We identified two genetic loci that modulate rates of epigenetic age acceleration (EAA): one on chromosome (Chr) 11 that encompasses the Erbb2/Her2 oncogenic region, and a second on Chr19 that contains a cytochrome P450 cluster. Both loci harbor genes associated with EAA in humans including STXBP4, NKX2-3, and CUTC. Transcriptome and proteome analyses revealed associations with oxidation-reduction, metabolic, and immune response pathways. Our results highlight concordant loci for EAA in humans and mice, and demonstrate a tight coupling between the metabolic state and epigenetic aging.

genomics↗

bioRxiv2021

Fast and powerful statistical method for context-specific QTL mapping in multi-context genomic studies

Context-specific eQTLs mediate genetic risk for complex diseases. However, limitations in current methods for identifying these eQTLs have hindered their comprehensive characterization and downstream interpretation of disease-associated variants. Here, we introduce FastGxC, a method to efficiently and powerfully map context-specific eQTLs by leveraging the correlation structure in genomic studies with repeated sampling, e.g., single-cell RNA-seq studies. Using simulations, we demonstrate that FastGxC is up to nine times more powerful and 106 times faster than existing approaches, reducing computation time from years to minutes. We applied FastGxC to bulk multi-tissue (N=698) and single-cell PBMC (N=1,218) RNA-seq datasets, generating comprehensive tissue- and cell-type-specific eQTL maps. These eQTLs exhibited up to four-fold enrichment in open chromatin regions from matched contexts and were twice as enriched as standard context-specific eQTLs, highlighting their biological relevance. Furthermore, we examined the relationship between context-specific eQTLs and complex human traits and diseases. FastGxC improved precision in identifying relevant contexts for each trait by three-fold and expanded candidate causal genes by 25% in cell types and 6% in tissues compared to standard eQTLs. In summary, FastGxC provides a powerful framework for mapping context-specific eQTLs, advancing our understanding of gene regulatory mechanisms underlying complex human traits and diseases.

genomics↗