Biology subjects

Li, R.

Publications and source records attributed to Li, R..

At least 343 records · Page 19Linked to original sources

bioRxiv2023

Regulated bacterial interaction networks: A mathematical framework to describe competitive growth under inclusion of metabolite cross-feeding

When bacterial species with the same resource preferences share the same growth environment, it is commonly believed that direct competition will arise. A large variety of competition and more general interaction models have been formulated, but what is currently lacking are models that link mono-culture growth kinetics and community growth under inclusion of emerging biological interactions, such as metabolite cross-feeding. In order to understand and mathematically describe the nature of potential cross-feeding interactions, we design experiments where two bacterial species Pseudomonas putida and Pseudomonas veronii grow in liquid medium either in mono- or as co-culture in a resource-limited environment. We measure population growth under single substrate competition or with double species-specific substrates (substrate indifference), and starting from varying cell ratios of either species. Using experimental data as input, we first consider a mean-field model of resource-based competition, which captures well the empirically observed growth rates for mono-cultures, but fails to correctly predict growth rates in co-culture mixtures, in particular for skewed starting species ratios. Based on this, we extend the model by cross-feeding interactions where the consumption of substrate by one consumer produces metabolites that in turn are resources for the other consumer, thus leading to positive feedback loops in the species system. Two different cross-feeding options were considered, which either lead to constant metabolite cross-feeding, or to a regulated form, where metabolite utilization is activated with rates according to either a threshold or a Hill function, dependent on metabolite concentration. Both mathematical proof and experimental data indicate regulated cross-feeding to be the preferred model over constant metabolite utilization, with best co-culture growth predictions in case of high Hill coefficients, close to binary (on/off) activation states. This suggests that species use the appearing metabolite concentrations only when they are becoming high enough; possibly as a consequence of their lower energetic content than the primary substrate. Metabolite sharing was particularly relevant at unbalanced starting cell ratios, causing the minority partner to proliferate more than expected from the competitive substrate because of metabolite release from the majority partner. This effect thus likely quells immediate substrate competition and may be important in natural communities with typical very skewed relative taxa abundances and slower-growing taxa. In conclusion, the regulated bacterial interaction network correctly describes species substrate growth reactions in mixtures with few kinetic parameters that can be obtained from mono-culture growth experiments. 1 Author summaryCorrectly predicting growth of communities of diverse bacterial taxa remains a challenge, because of the very different growth properties of individual members and their myriads of interactions that can influence growth. Here we tried to improve and empirically validate mathematical models that combine theory of bacterial growth kinetics (i.e., Monod models) with mathematical definition of interaction parameters. We focused in particular on common cases of shared primary substrates (i.e., competition) and independent substrates (i.e., indifference) in an experimental system consisting of one fast-growing and one slower growing Pseudomonas species. Growth kinetic parameters derived from mono-culture experiments included in a Monod-type consumer-resource model explained some 75% of biomass formation of either species in co-culture, but underestimated the observed growth improvement when either of the species started as a minority compared to the other. This suggested an in important role of cross-feeding, whereby released metabolites from one of the partners is utilized by the other. Inclusion of cross-feeding feedback in the two-species Monod growth model largely explained empirical data at all species-starting ratios, in particular when cross-feeding is activated in almost binary manner as a function of metabolite concentration. Our results also indicate the importance of cross-feeding for minority taxa, which can explain their survival despite being poorly competitive.

microbiology↗

bioRxiv2023

Single-cell RNA sequencing reveals dysregulated fibroblast subclusters in prurigo nodularis

Prurigo nodularis (PN) is an intensely pruritic, chronic inflammatory skin disease that disproportionately affects black patients. However, the pathogenesis of PN is poorly understood. We performed single-cell transcriptomic profiling, ligand receptor analysis and cell trajectory analysis of 28,695 lesional and non-lesional PN skin cells to uncover disease-identifying cell compositions and genetic characteristics. We uncovered a dysregulated role for fibroblasts (FBs) and myofibroblasts as a key pathogenic element in PN, which were significantly increased in PN lesional skin. We defined seven unique subclusters of FBs in PN skin and observed a shift of PN lesional FBs towards a cancer-associated fibroblast (CAF)-like phenotype, with WNT5A+ CAFs increased in the skin of PN patients and similarly so in squamous cell carcinoma (SCC). A multi-center PN cohort study subsequently revealed an increased risk of SCC as well as additional CAF-associated malignancies in PN patients, including breast and colorectal cancers. Systemic fibroproliferative diseases were also upregulated in PN patients, including renal sclerosis and idiopathic pulmonary fibrosis. Ligand receptor analyses demonstrated increased FB1-derived WNT5A and periostin interactions with neuronal receptors MCAM and ITGAV, suggesting a fibroblast-neuronal axis in PN. Type I IFN responses in immune cells and increased angiogenesis/permeability in endothelial cells were also observed. As compared to atopic dermatitis (AD) and psoriasis (PSO) patients, increased mesenchymal dysregulation is unique to PN with an intermediate Th2/Th17 phenotype between atopic dermatitis and psoriasis. These findings identify a pathogenic role for CAFs in PN, including a novel targetable WNT5A+ fibroblast subpopulation and CAF-associated malignancies in PN patients.

bioinformatics↗

bioRxiv2023

Dopamine promotes Klebsiella quasivariicola proliferation and inflammatory response in the presence of macrophages

Klebsiella quasivariicola was a novel strain of Klebsiella species and had potential pathogenicity. Our previously studies showed dopamine, one of the most commonly used rescue drugs for critically ill patients, had clear effects on the growth of K. quasivariicola in culture medium, however, its effects on host immune system were ignored. Therefore, in consideration of the host immunity, the interactions of K. quasivariicola, dopamine and macrophages were explored. In this study, RAW264.7 cells and C57/BL6 mice were infected with K. quasivariicola, and the bacterial growth in macrophage, the production of inflammatory cytokines and the pathological changes of mice lung were detected, in the absence or presence of dopamine. Our results showed dopamine inhibited the K. quasivariicola growth in medium, but promoted the bacterial growth when K. quasivariicola was co-cultured with macrophages; The expression of proinflammatory cytokines in K. quasivariicola infected RAW 264.7 were increased, while a sharp rise was observed with the addition of dopamine; Infection of K. quasivariicola to mice induced an inflammatory response and lung injury, which were exacerbated by dopamine administration. It can be concluded that dopamine administration resulted in a significantly increase of K. quasivariicola burdens in the presence of macrophage, consequently, aggravated the inflammatory response and inflammatory injury. ImportanceDopamine is one of the most commonly used rescue drugs for critically ill patients. Here we indicated K. quasivariicola was a potential pathogen of pulmonary infection, and dopamine significantly increased the proliferation of K. quasivariicola when exposed to macrophage, subsequently result in severe inflammatory response and inflammatory injury. We also proposed an in vitro model of microbes-drugs-host immune cells that could better mimic in vivo environment and more suitable for the studies of inhibitor screening. This fundamental work had contributed to the present understanding of the crosstalk between pathogen, dopamine and host immune cells. Furthermore, our data showed dopamine was one of the risk factors for patients with K. quasivariicola infection, which provided a basis for clinical precision medicine.

microbiology↗

bioRxiv2023

A defined clathrin-mediated trafficking pathway regulates sFLT1/VEGFR1 secretion from endothelial cells

FLT1/VEGFR1 negatively regulates VEGF-A signaling and is required for proper vessel morphogenesis during vascular development and vessel homeostasis. Although a soluble isoform, sFLT1, is often mis-regulated in disease and aging, how sFLT1 is trafficked and secreted from endothelial cells is not well understood. Here we define requirements for constitutive sFLT1 trafficking and secretion in endothelial cells from the Golgi to the plasma membrane, and we show that sFLT1 secretion requires clathrin at or near the Golgi. Perturbations that affect sFLT1 trafficking blunted endothelial cell secretion and promoted intracellular mis-localization in cells and zebrafish embryos. siRNA-mediated depletion of specific trafficking components revealed requirements for RAB27A, VAMP3, and STX3 for post-Golgi vesicle trafficking and sFLT1 secretion, while STX6, ARF1, and AP1 were required at the Golgi. Depletion of STX6 altered vessel sprouting in a 3D angiogenesis model, indicating that endothelial cell sFLT1 secretion is important for proper vessel sprouting. Thus, specific trafficking components provide a secretory path from the Golgi to the plasma membrane for sFLT1 in endothelial cells that utilizes a specialized clathrin-dependent intermediate, suggesting novel therapeutic targets.

cell biology↗

bioRxiv2023

Automated quantitative trait locus analysis (AutoQTL)

BackgroundQuantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture significant levels of phenotypic variance in complex traits. However, effort and time are required to select the best methods and optimize parameters and pre-processing steps. Although machine learning approaches have been shown to greatly assist in optimization and data processing, applying them to QTL analysis and GWAS is challenging due to the complexity of large, heterogenous datasets. Here, we describe proof-of-concept for an automated machine learning approach, AutoQTL, with the ability to automate many complex decisions related to analysis of complex traits and generate diverse solutions to describe relationships that exist in genetic data. ResultsUsing a dataset of 18 putative QTL from a large-scale GWAS of body mass index in the laboratory rat, Rattus norvegicus, AutoQTL captures the phenotypic variance explained under a standard additive model while also providing evidence of non-additive effects including deviations from additivity and 2-way epistatic interactions from simulated data via multiple optimal solutions. Additionally, feature importance metrics provide different insights into the inheritance models and predictive power of multiple GWAS-derived putative QTL. ConclusionsThis proof-of-concept illustrates that automated machine learning techniques can be applied to genetic data and has the potential to detect both additive and non-additive effects via various optimal solutions and feature importance metrics. In the future, we aim to expand AutoQTL to accommodate omics-level datasets with intelligent feature selection strategies.

genetics↗

bioRxiv2023

Construction of Model Animals to Explore Intestinal Microbiome for Detection of Breast Cancer

Breast cancer ranks first among female cancers and has become a major public health problem in the current society. More studies indicated that these cancers are related to the change in the gut microbiome that can cause metabolic and immune system disorders in the body. However, there are few studies on the changes in gut microbiome caused by the onset of breast cancer, and the relationship between breast cancer and gut microbiome needs to be further clarified. In this study, we inoculated 4T1 breast cancer cells to induce breast cancer tumorigenesis in mice and collected their feces samples at different stages during this process. These intestinal florae were analyzed using 16S rRNA gene amplicon sequencing, and the results showed that at the phylum level, the ratio of Firmicutes/Bacteroidetes decreased with the development of the tumor; at the family level, the intestinal microbiome had obvious variations of Lachnospiraceae, Bacteroidaceae, Erysipelotrichaceae, etc. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and COG annotation demonstrated that decreased abundance of cancer related signaling pathways. This study elucidated the relationship between breast cancer and intestinal microbiome, and the research results can be used as an important biomarker for the diagnosis of breast cancer.

cancer biology↗

bioRxiv2023

Molecular Mechanocytometry Using Tension-activated Cell Tagging (TaCT)

Flow cytometry is routinely used to measure single-cell gene expression by staining cells with fluorescent antibodies and nucleic acids. Here we present Tension-activated Cell Tagging (TaCT) to fluorescently label cells based on the magnitude of molecular force transmitted through cell adhesion receptors. As a proof-of-concept, we analyzed fibroblasts and mouse platelets after TaCT using conventional flow cytometry.

bioengineering↗

bioRxiv2023

HPC-Atlas: Computationally Constructing A Comprehensive Atlas of Human Protein Complexes

A fundamental principle of biology is that proteins tend to form complexes to play significant roles in the core functions of cells. For a complete understanding of human cellular functions, it is crucial to have a comprehensive atlas of human protein complexes. Unfortunately, we still lack such a comprehensive atlas of experimentally validated protein complexes, which prevents us from gaining a complete understanding of the compositions and functions of human protein complexes and biological mechanisms. To fill this gap, we built HPC-Atlas, as far as we know, the most accurate and comprehensive atlas of human protein complexes available to date. We integrated two latest protein interaction networks, and developed a novel computational method to identify nearly 9000 protein complexes, including many previously uncharacterized complexes. Compared with the existing works, our method achieves outstanding performance on both test and independent sets. Furthermore, with HPC-Atlas we identified 751 SARS-CoV-2 affected human protein complexes, and 456 multifunctional proteins that contain many potential moonlighting proteins. These results suggest that HPC-Atlas can serve as not only a computing framework to effectively identify biologically meaningful protein complexes by integrating multiple protein data sources, but also a valuable resource for exploring new biological findings. The HPC-Atlas webserver is freely available at http://www.yulpan.top/HPC-Atlas.

bioinformatics↗

bioRxiv2022

Cataloguing and profiling of the gut virome in Chinese populations uncover extensive viral signatures across common diseases

The gut viral community has been linked to human physiology and health, but our knowledge of its genetic and functional contents and disease dependence is far from complete. Here, we collected 11,327 bulk or viral metagenomes from fecal samples from large-scale Chinese populations to establish a Chinese gut virus catalogue (cnGVC) comprising 67,096 nonredundant viral genomes. This catalogue included [~]70% of novel viruses that are not represented in existing gut viral databases, and allowed us to characterize the functional diversity and specificity of the gut virome. Using cnGVC, we 1) profiled the gut virome in large-scale populations and evaluated their sex- and age-related variations, 2) investigated the diversity and compositional patterns of the gut virome across common diseases by analyzing 6,314 bulk metagenomes spanning 28 disease or unhealthy statuses, and 3) identified a large number of universal viral signatures of diseases and validated their predictive ability for health status. Overall, our resources and results would contribute to the grand effort of expanding the knowledge of the human gut virome and addressing a full picture of the associations between viruses and common diseases.

microbiology↗

bioRxiv2022

IIIandMe: An Algorithm for Chromosome-scale Haplotype Determination Using Genome-wide Variants of Three Haploid Reproductive Cells

Our recent algorithm, Hapi, infers chromosome-scale haplotypes using genomic data of a small number of single gametes. Its advanced version, IIIandMe, is proposed here to achieve comparable phasing accuracy with as few as three gametes, pushing the analysis to its limit. The new method is validated with simulation and a citrus gamete dataset. The rapid advances in genotyping technologies promise a broad application of IIIandMe in disclosing important genetic information.

bioinformatics↗

bioRxiv2022

Accurate de novo detection of somatic mutations in high-throughput single-cell profiling data sets

Characterization of somatic mutations at single-cell resolution is essential to study cancer evolution, clonal mosaicism, and cell plasticity. However, detection of mutations in single cells remains technically challenging. Here, we describe SComatic, an algorithm designed for the detection of somatic mutations in single-cell transcriptomic and ATAC-seq data sets without requiring matched bulk or single-cell DNA sequencing data. Using >1.5M single cells from 383 single-cell RNAseq and single-cell ATAC-seq data sets spanning cancer and non-neoplastic samples, we show that SComatic detects mutations in single cells, even in differentiated cells from polyclonal tissues not amenable to mutation detection using existing methods. In addition, SComatic permits the estimation of mutational burdens and de novo mutational signature analysis at single-cell and cell-type resolution. Notably, using matched exome and single-cell RNAseq data, we show that SComatic achieves a 20 to 40-fold increase in precision as compared to existing algorithms for somatic SNV calling without compromising sensitivity. Overall, SComatic opens the possibility to study somatic mutagenesis at unprecedented scale and resolution using high-throughput single-cell profiling data sets.

genomics↗

bioRxiv2022

Investigations into hydrogen sulfide-induced suppression of neuronal activity in vivo and calcium dysregulation in vitro

Acute exposure to high concentrations of hydrogen sulfide (H2S) leads to sudden death and, if survived, lingering neurological disorders. Clinical signs include seizures, loss of consciousness, and dyspnea. The proximate mechanisms underlying H2S-induced acute toxicity and death have not been clearly elucidated. We investigated electrocerebral, cardiac and respiratory activity during H2S exposure using EEG, EKG and plethysmography. H2S suppressed electrocerebral activity and disrupted breathing. Cardiac activity was comparatively less affected. To test whether Ca2+ dysregulation contributes to H2S-induced EEG suppression, we developed an in vitro real-time rapid throughput assay measuring patterns of spontaneous synchronized Ca2+ oscillations in cultured primary cortical neuronal (PCN) networks loaded with the indicator Fluo-4 using the fluorescent imaging plate reader (FLIPR-Tetra(R)). Sulfide >5 ppm dysregulated SCO patterns in a dose-dependent manner. Inhibitors of NMDA and AMPA receptors magnified H2S-induced SCO suppression. Inhibitors of L-type voltage gated Ca2+ channels (VGCC) and transient receptor potential (TRP) channels prevented H2S-induced SCO suppression. Inhibitors of T-type VGCC, ryanodine receptors, and sodium channels had no measurable influence on H2S-induced SCO suppression. Exposures to >5 ppm sulfide also suppressed neuronal electrical activity in PCN measured by multi-electrode array (MEA), an effect alleviated by pretreatment with the nonselective TRP inhibitor 2-APB. The TRP inhibitor also reduced PCN cell death from sulfide exposure. These results improve our understanding of the role of different Ca2+ channels in acute H2S-induced neurotoxicity and identify TRP channel modulators as novel structures with potential therapeutic benefits.

pharmacology and toxicology↗

bioRxiv2022

The effect of wheat genotype on its microbiome is more evident in roots than rhizosphere and is strongly influenced by time

Crop breeding has traditionally ignored the plant-associated microbial communities. Consideration of the interactions between plant genotype and associated microbiota is of value since different genotypes of the same crop often harbor distinct microbial communities which can influence the plant phenotype. However, recent studies have reported contrasting results, which led us to hypothesize that the effect of genotype is constrained by time (growth stage, year) and space (plant compartment). To test this hypothesis, we sampled bulk soil, rhizosphere soil and roots of 10 wheat genotypes, twice per year, for 4 years. DNA was extracted and regions of the bacterial 16S rRNA and CPN60 genes and the fungal ITS region were amplified and sequenced. The effect of genotype was highly contingent on the time of sampling and on the plant compartment sampled. Only for a few sampling dates, were the microbial communities significantly different across genotypes. The effect of genotype was most often significant for root microbial communities. The three marker genes used provided a highly coherent picture of the effect of genotype. Taken together, our results confirm that microbial communities in the plant environment strongly vary temporally and spatially and that this can mask the effect of genotype.

microbiology↗

bioRxiv2022

XIST ribonucleoproteins promote female sex-biased autoimmunity

Autoimmune diseases disproportionately affect females more than males. The XX sex chromosome complement is strongly associated with susceptibility to autoimmunity. Xist long noncoding RNA (lncRNA) is expressed only in females to randomly inactivate one of the two X chromosomes to achieve gene dosage compensation. Here, we show that the Xist ribonucleoprotein (RNP) complex, comprised of numerous autoantigenic components, is an important driver of sex-biased autoimmunity. Inducible transgenic expression of a non-silencing form of Xist in male mice introduced Xist RNP complexes and sufficed to produce autoantibodies. Male SJL/J mice expressing transgenic Xist developed more severe multiorgan pathology in pristane-induced model of lupus than wild-type males. Xist expression in males reprogrammed T and B cell population and chromatin states to more resemble wild type females. Human patients with autoimmune diseases displayed significant autoantibodies to multiple components of XIST RNP. Thus, a sex-specific lncRNA scaffolds ubiquitous RNP components to drive sex-biased immunity. HIGHLIGHTSO_LITransgenic mouse models inducibly express Xist in male animals. C_LIO_LIXist expression in males induce autoantibodies and autoimmune pathology. C_LIO_LIXist in males reprograms T and B cell populations to female-like patterns. C_LIO_LIAutoantibodies to Xist RNP characterize female-biased autoimmune diseases. C_LI

molecular biology↗

bioRxiv2022

Discovery of aphid-transmitted Rice tiller inhibition virus from native plants through metagenomic sequencing

A major threat to rice production is the disease epidemics caused by insect-borne viruses that emerge and re-emerge with undefined origins. It is well known that some human viruses have zoonotic origins from wild animals. However, it remains unknown whether native plants host new endemic viruses with spillover potential to rice (Oryza sativa) as emerging pathogens. Here, we discovered rice tiller inhibition virus (RTIV), a novel RNA virus species, from colonies of Asian wild rice (O. rufipogon) in a genetic reserve by metagenomic sequencing. We identified the specific aphid vector to transmit RTIV and found RTIV would cause low-tillering disease in rice cultivar after transmission. We further demonstrated that an infectious molecular clone of RTIV initiated systemic infection and causes low-tillering disease in an elite rice variety after Agrobacterium-mediated inoculation or stable plant transformation, and RTIV can also be transmitted from transgenic rice plant through its aphid vector to cause disease. Finally, global transcriptome analysis indicated that RTIV may disturb defense and tillering pathway to cause low tillering disease in rice cultivar. Thus, our results show that new rice viral pathogens can emerge from native habitats, and RTIV, a rare aphid-transmitted rice viral pathogen from native wild rice, can threaten the production of rice cultivar after spillover.

pathology↗

bioRxiv2022

Mechano-Cas12a Assisted Tension Sensor (MCATS) for Massively Amplified Cell Traction Force Measurements

Cells transmit piconewton forces to mediate essential biological processes such as coagulation. One challenge is that cell-generated forces are infrequent, transient, and difficult to detect. Here, we report the development of Mechano-Cas12a Assisted Tension Sensor (MCATS) that utilizes CRISPR-Cas12a to transduce and amplify the molecular forces generated by cells. We demonstrate the power of MCATS by detecting the forces generated by as few as ~103 human platelets in a high-throughput manner. Platelet forces are significantly inhibited when blood samples are treated with FDA-approved drugs such as aspirin, eptifibatide(integrilin(R)), 7E3(Reopro(R)), and ticagrelor (Brelinta(R)). Because MCATS requires <5uL of blood/measurement, a single blood draw can generate a personalized dose-response curve and IC50 for this panel of drugs. Platelet activity and force-generation are tightly associated, and hence MCATS was used to quantify platelet dysfunction following cardiopulmonary bypass (CPB) in a pilot study of 7 cardiac patients. We found that MCATS detected platelet dysfunction which strongly correlated with the need for platelet transfusion to limit bleeding. These results indicate MCATS may be a useful assay for clinical applications.

biophysics↗

bioRxiv2022

Ratio-based quantitative multiomics profiling using universal reference materials empowers data integration

Multiomics profiling is a powerful tool to characterize the same samples with complementary features orchestrating the genome, epigenome, transcriptome, proteome, and metabolome. However, the lack of ground truth hampers the objective assessment of and subsequent choice from a plethora of measurement and computational methods aiming to integrate diverse and often enigmatically incomparable omics datasets. Here we establish and characterize the first suites of publicly available multiomics reference materials of matched DNA, RNA, proteins, and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters, providing built-in truth defined by family relationship and the central dogma. We demonstrate that the "ratio"-based omics profiling data, i.e., by scaling the absolute feature values of a study sample relative to those of a concurrently measured universal reference sample, were inherently much more reproducible and comparable across batches, labs, platforms, and omics types, thus empower the horizontal (within-omics) and vertical (cross-omics) data integration in multiomics studies. Our study identifies "absolute" feature quantitation as the root cause of irreproducibility in multiomics measurement and data integration, and urges a paradigm shift from "absolute" to "ratio"-based multiomics profiling with universal reference materials.

systems biology↗

bioRxiv2022

Metabolic acids impact bone mineral maturation

Bone mineral has a complex 3D architecture that is essential to its mechanical properties. It is a complex calcium phosphate phase related to hydroxyapatite that also contains significant quantities of cell respiration metabolites, in particular: carbonate, citrate and lactate. An as-yet unanswered question is what, if any, role do these metabolites collectively play in determining the 3D architecture of bone mineral? Here we synthesize apatitic materials by transformation from precursor mineral phases containing citrate, lactate or carbonate so that the synthesis environment mimics the densely-packed ionic environment within which bone mineral forms in vivo, and so that we can understand the mineral factors that may direct bone mineral 3D architecture. We show that incorporating citrate and lactate leads to complex mineral architectures reminiscent of those in bone mineral, including curvature of the mineral crystals. Our results suggest that metabolic acids may assist the moulding of bone mineral to restricted spaces available for mineral in in vivo bone. We find that the incorporation of lactate creates a softer material and inhibits the transformation towards apatitic structures, which may help to explain why foetal bone - necessarily soft - contains considerable quantities of lactate. High levels of plasma citrate have been previously found to correlate with high bone mineral density. Here we find that citrate incorporation leads to mineral crystal curvature modelling that in in vivo bone mineral suggesting its importance in mineral morphology. We conclude that metabolic anions may play an important role in controlling bone mineral physicochemical properties and 3D architecture.

biophysics↗