Biology subjects

Yu, F.

Publications and source records attributed to Yu, F..

At least 145 records · Page 8Linked to original sources

bioRxiv2021

Cannabinoids differentially modulate behavioral and developmental responses to ethanol in Drosophila

Prolonged prenatal or adult exposure to ethanol is detrimental to mental and physical well-being, resulting in developmental abnormalities, progressive addiction and ultimate death. A growing number of studies have shown the therapeutic potential of cannabinoids in ethanol-related behaviors in mammals. However, the potential pharmacological actions of cannabinoids in ethanol responses have not been examined in the model organism Drosophila melanogaster. Here, we systematically investigated the effects of various cannabinoids on ethanol preference, ethanol sensitivity and tolerance, and ethanol-induced developmental defect in Drosophila. We showed that treatment with the phytocannabinoid cannabidiol (CBD) displayed a significant decrease in preference for consuming ethanol in adult flies. Interestingly, cannabinoids exhibited differential roles in short- and long-term ethanol tolerance in flies. Although cannabinoids had no detectable effects on short-term ethanol tolerance, CBD and the endocannabinoid anandamide (AEA) suppressed long-term tolerance to ethanol. Moreover, ethanol exposure delayed larval-to-pupal development and increased larval/pupal size. Unexpectedly, treatment with CBD or endocannabinoids did not attenuate ethanol-induced developmental delay, instead, exacerbated its detrimental effect. Thus, our systematical study reveals, for the first time, a differential role of the cannabinoids in the modulation of ethanol-related responses in Drosophila.

pharmacology and toxicology↗

bioRxiv2021

Phosphorylation of STIM1 at ERK/CDK sites is dispensable for cell migration and ER partitioning in mitosis

Store-operated Ca2+ entry (SOCE) is a ubiquitous Ca2+ influx required for multiple physiological functions including cell motility. SOCE is activated in response to depletion of intracellular Ca2+ stores following the activation of endoplasmic reticulum (ER) Ca2+ sensor STIM1 which recruits the plasma membrane (PM) Ca2+ channel Orai1 at ER-PM junctions to induce Ca2+ influx. STIM1 is phosphorylated dynamically and this phosphorylation has been implicated in several processes including SOCE inactivation during M-phase, maximal SOCE activation, ER segregation during mitosis, and cell migration. Human STIM1 has 10 Ser/Thr residues in its cytosolic domain that match the ERK/CDK consensus phosphorylation. We recently generated a mouse knock-in line where wild-type STIM1 was replaced by a non-phosphorylatable STIM1 with all 10 S/T mutated to Ala (STIM1-10A). Here, we generate mouse embryonic fibroblasts (MEF) the STIM1-10A mouse line and a control MEF line (WT) that express wild-type STIM1 from a congenic mouse strain. These lines offer a unique model to address the role of STIM1 phosphorylation at endogenous expression and modulation levels in contrast to previous studies that relied mostly on overexpression. We show that STIM1 phosphorylation at ERK/CDK sites is not required for SOCE activation, cell migration, or ER partitioning during mitosis. These results rule out STIM1 phosphorylation as a regulator of SOCE, migration and ER distribution in mitosis.

cell biology↗

bioRxiv2021

Systematic dissection of a complex gut bacterial community

Efforts to model the gut microbiome have yielded important insights into the mechanisms of interspecies interactions, the impact of priority effects on ecosystem dynamics, and the role of diet and nutrient availability in determining community composition. However, the model communities studied to date have been defined or complex but not both, limiting their utility. Here, we construct a defined community of 104 bacterial strains composed of the most common taxa from the human gut microbiota. By propagating this community in growth media missing one amino acid at a time, we show that branched-chain amino acids have an outsize impact on community structure and identify a pathway in Clostridium sporogenes for generating ATP from arginine. We constructed and propagated the complete set of single-strain dropout communities, revealing a sparse network of strain-strain interactions including a novel interaction between C. sporogenes and Lactococcus lactis driven by metabolism. This work forms a foundation for studying strain-strain and strain-nutrient interactions in highly complex defined communities, and it provides a starting point for interrogating the rules of synthetic ecology at the 100+ strain scale.

microbiology↗

bioRxiv2021

ROS-Degradable Polythioketal Urethane Foam Dressings to Promote Porcine Skin Wound Repair

Impaired skin healing and progression into chronic wounds is a prevalent and growing medical problem. Porous, resorbable biomaterials can be used as temporary substrates placed into skin defects to support cell infiltration, neo-tissue formation, and remodeling of nonhealing wounds. Naturally-derived biomaterials have promising healing benefits, but their low mechanical properties and exuberant costs limit their performance and use. Synthetic materials can be affordably manufactured and tuned across a broader range of physiochemical properties, but opportunities remain for tailoring them for ideal host immune and regenerative responses. Polyesters are the most clinically-tested class of synthetic biomaterials, but their hydrolysis releases acidic degradation products that can cause autocatalytic degradation processes that are poorly controlled and are not tied to cellular or other biologic activities. Here, we systemically explored a series of ROS-degradable polythioketal (PTK) urethane (UR) foams with varied hydrophilicity as an alternative class of synthetic biomaterials for wound healing. It was found that the most hydrophilic PTK- UR variant, which had 7 ethylene glycol (EG7) repeats flanking each side of each thioketal bond, had the highest ROS reactivity of the PTK-URs tested. In an in vivo porcine excisional skin wound healing model, hydrophilic EG7 PTK-UR foams more effectively promoted tissue integration, ECM deposition, and re- epithelialization of full-thickness skin wound compared to more hydrophobic PTK-UR variants. Resolution of type 1 inflammation and lower foreign body response to scaffold remnants was also observed for EG7 versus more hydrophobic PTK-UR scaffolds. Finally, porcine wound healing studies showed that EG7 PTK-UR foams had similar wound healing response to a collagen-based clinical gold standard product, Integra Bilayer Wound Matrix (BWM), while outperforming polyester UR foam-based NovoSorb Biodegradable Temporizing Matrix (BTM) with respect to increased ECM production, vascularization, and biomaterial-associated immune phenotype. In sum, PTK-UR foams warrant further development toward a new class of synthetic biomaterial foams for skin wound healing applications.

bioengineering↗

bioRxiv2021

Inferring the timing and strength of natural selection and gene migration in the evolution of chicken from ancient DNA data

With the rapid growth of the number of sequenced ancient genomes, there has been increasing interest in using this new information to study past and present adaptation. Such an additional temporal component has the promise of providing improved power for the estimation of natural selection. Over the last decade, statistical approaches for detection and quantification of natural selection from ancient DNA (aDNA) data have been developed. However, most of the existing methods do not allow us to estimate the timing of natural selection along with its strength, which is key to understanding the evolution and persistence of organismal diversity. Additionally, most methods ignore the fact that natural populations are almost always structured, which can result in overestimation of the effect of natural selection. To address these issues, we introduce a novel Bayesian framework for the inference of natural selection and gene migration from aDNA data with Markov chain Monte Carlo techniques, co-estimating both timing and strength of natural selection and gene migration. Such an advance enables us to infer drivers of natural selection and gene migration by correlating genetic evolution with potential causes such as the changes in the ecological context in which an organism has evolved. The performance of our procedure is evaluated through extensive simulations, with its utility shown with an application to ancient chicken samples.

genetics↗

bioRxiv2021

Uncovering the modified immunopeptidome reveals insights into principles of PTM-driven antigenicity

Antigen processing and presentation are critical for modulating tumor-host interactions. While post-translational modifications (PTMs) can alter the binding and recognition of antigens, their identification remains challenging. Here we uncover the role PTMs may play in antigen presentation and recognition in human cancers by profiling 29 different PTM combinations in immunopeptidomics data from multiple clinical samples and cell lines. We established and validated an antigen discovery pipeline and showed that newly identified modified antigens from a murine cancer model are cancer-specific and can elicit T cell killing. Systematic analysis of PTMs across multiple cohorts defined new haplotype preferences and binding motifs in association with specific PTM types. By expanding the antigenic landscape with modifications, we uncover disease-specific targets, including thousands of novel cancer-specific antigens and reveal insight into PTM-driven antigenicity. Collectively, our findings highlight an immunomodulatory role for modified peptides presented on HLA I, which may have broad implications for T-cell mediated therapies in cancer and beyond. SignificanceMajor efforts are underway to identify cancer-specific antigens for personalized immunotherapy. Here, we enrich the immunopeptidome landscape by uncovering thousands of novel putative antigens that are post-translationally modified. We define unique preferences for PTM-driven alterations affecting HLA binding and TCR recognition, which in turn alter tumor-immune interactions. Conflict of interest statementAuthors declare no conflicts of interest.

cancer biology↗

bioRxiv2021

High sensitivity dia-PASEF proteomics with DIA-NN and FragPipe

The dia-PASEF technology exploits ion mobility separation for high-sensitivity analysis of complex proteomes. Here, we demonstrate neural network-based processing of the ion mobility data, which we implement in the DIA-NN software suite. Using spectral libraries generated with the MSFragger-based FragPipe computational platform, the DIA-NN analysis of dia-PASEF raw data increases the proteomic depth by up to 69% compared to the originally published dia-PASEF workflow. For example, we quantify over 5200 proteins from 10ng of HeLa peptides separated with a 95-minute nanoflow gradient, and over 5000 proteins from 200ng using a 4.8-minute separation with an Evosep One system. In complex samples, featuring a mix of human and yeast lysates, the workflow detects over 11700 proteins in single runs acquired with a 100-minute nanoflow gradient, while demonstrating quantitative precision. Hence, the combination of FragPipe and DIA-NN provides a simple-to-use software platform for dia-PASEF data analysis, yielding significant gains in high-sensitivity proteomics.

bioinformatics↗

bioRxiv2021

Spike mutations in SARS-CoV-2 variants confer resistance to antibody neutralization

New SARS-CoV-2 variants continue to emerge from the current global pandemic, some of which can replicate faster and with greater transmissibility and pathogenicity. In particular, UK501Y.V1 identified in UK, SA501Y.V2 in South Africa, and BR501Y.V3 in Brazil are raising serious concerns as they spread quickly and contain spike protein mutations that may facilitate escape from current antibody therapies and vaccine protection. Here, we constructed a panel of 28 SARS-CoV-2 pseudoviruses bearing single or combined mutations found in the spike protein of these three variants, as well as additional nine mutations that within or close by the major antigenic sites in the spike protein identified in the GISAID database. These pseudoviruses were tested against a panel of monoclonal antibodies (mAbs), including some approved for emergency use to treat SARS-CoV-2 infection, and convalescent patient plasma collected early in the pandemic. SA501Y.V2 pseudovirus was the most resistant, in magnitude and breadth, against mAbs and convalescent plasma, followed by BR501Y.V3, and then UK501Y.V1. This resistance hierarchy corresponds with Y144del and 242-244del mutations in the N-terminal domain as well as K417N/T, E484K and N501Y mutations in the receptor binding domain (RBD). Crystal structural analysis of RBD carrying triple K417N-E484K-N501Y mutations found in SA501Y.V2 bound with mAb P2C-1F11 revealed a molecular basis for antibody neutralization and escape. SA501Y.V2 and BR501Y.V3 also acquired substantial ability to use mouse and mink ACE2 for entry. Taken together, our results clearly demonstrate major antigenic shifts and potentially broadening the host range of SA501Y.V2 and BR501Y.V3, which pose serious challenges to our current antibody therapies and vaccine protection.

immunology↗

bioRxiv2021

Intrinsically disordered protein biosensor tracks the physical-chemical effects of osmotic stress on cells

Cell homeostasis is perturbed when dramatic shifts in the external environment cause the physical-chemical properties inside the cell to change. Methods that dynamically monitor these intracellular effects are currently lacking. Here, we leveraged the environmental sensitivity and structural plasticity of intrinsically disordered regions (IDRs) to develop a FRET biosensor capable of monitoring rapid intracellular changes caused by osmotic stress. The biosensor, named SED1, utilizes the Arabidopsis intrinsically disordered AtLEA4-5 protein expressed in plants under water deficit. Computational modeling and in vitro studies reveal that SED1 is highly sensitive to macromolecular crowding. SED1 exhibits large and near-linear osmolarity-dependent changes in FRET inside living bacteria, yeast, plant, and human cells, demonstrating the broad utility of this tool for studying water-associated stress. This study demonstrates the remarkable ability of IDRs to sense the cellular environment across the tree of life and provides a blueprint for their use in environmentally-responsive molecular tools.

cell biology↗

bioRxiv2021

CUT&RUNTools 2.0: A pipeline for single-cell and bulk-level CUT&RUN and CUT&Tag data analysis

Genome-wide profiling of transcription factor binding and chromatin states is a widely-used approach for mechanistic understanding of gene regulation. Recent technology development has enabled such profiling at single-cell resolution. However, an end-to-end computational pipeline for analyzing such data is still lacking. To fill this gap, we have developed a flexible pipeline for analysis and visualization of single-cell CUT&RUN and CUT&Tag data, which provides functions for sequence alignment, quality control, dimensionality reduction, cell clustering, data aggregation, and visualization. Furthermore, it is also seamlessly integrated with the functions in original CUT&RUNTools for population-level analyses. As such, this provides a valuable toolbox for the community.

bioinformatics↗

bioRxiv2021

MAESTRO affords 'breadth and depth' for mutation testing

The ability to assay large numbers of low-abundance mutations is crucial in biomedicine. Yet, the technical hurdles of sequencing multiple mutations at extremely high depth and accuracy remain daunting. For sequencing low-level mutations, its either depth or breadth but not both. Here, we report a simple and powerful approach to accurately track thousands of distinct mutations with minimal reads. Our technique called MAESTRO (minor allele enriched sequencing through recognition oligonucleotides) employs massively-parallel mutation enrichment to empower duplex sequencing--one of the most accurate methods--to track up to 10,000 low-frequency mutations with up to 100-fold less sequencing. In example use cases, we show that MAESTRO could enable mutation validation from cancer genome sequencing studies. We also show that it could track thousands of mutations from a patients tumor in cell-free DNA, which may improve detection of minimal residual disease from liquid biopsies. In all, MAESTRO improves the breadth, depth, accuracy, and efficiency of mutation testing.

molecular biology↗

bioRxiv2021

Moment-based approximations for the Wright-Fisher model of population dynamics under natural selection at two linked loci

Properly modelling genetic recombination and local linkage has been shown to bring significant improvement to the inference of natural selection from time series data of allele frequencies under a Wright-Fisher model. Existing approaches that can account for genetic recombination and local linkage are built on either the diffusion approximation or a moment-based approximation of the Wright-Fisher model. However, methods based on the diffusion approximation are likely to require much higher computational cost, whereas moment-based approximations may suffer from the distribution support issue: for example, the normal approximation can seriously affect computational accuracy. In the present work, we introduce two novel moment-based approximations of the Wright-Fisher model on a pair of linked loci, both subject to natural selection. Our key innovation is to extend existing methods to account for both the mean and (co)variance of the two-locus Wright-Fisher model with selection. We devise two approximation schemes, using a logistic normal distribution and a hierarchical beta distribution, respectively, by matching the first two moments of the Wright-Fisher model and the approximating model. As compared with the diffusion approximation, our approximations enable the approximate computation of the transition probabilities of the Wright-Fisher model at a far smaller computational cost. We can also avoid the distribution support issue found in the normal approximation.

genetics↗

bioRxiv2020

Analysis of Intermolt and Postmolt Transcriptomes Provides Insight into Molecular Mechanisms of the Red Swamp Crayfish, Procambarus Clarkii Molting

In the present study, we explored expression changes in the transcriptomes of two molting stages (post-molt (M) and Intermolt (NM)) of the red swamp crayfish. A total of 307608398 clean reads, with an average length of 145bp were obtained. Further clustering and assembly of the transcripts generated 139100 unigenes. The results were searched against the NCBI, NR, KEGG, Swissprot, and KOG databases, in order to annotate gene descriptions, associate them with gene ontology terms, and assign them to pathways. Several genes and other factors involved in a number of molecular events critical for molting, such as energy requirements, hormonal regulation, immune response, and exoskeleton formation were identified, evaluated, and characterized. The information presented here provides a basic understanding of the molecular mechanisms underlying the crayfish molting process, with respect to energy requirements, hormonal regulation, immune response, and skeletal related activities during post-molt stage and the intermolt stage.

genomics↗

bioRxiv2020

Cannabinoids modulate food preference and consumption in Drosophila melanogaster

Cannabinoids have an important role in regulating feeding behaviors via cannabinoid receptors in mammals. Cannabinoids also exhibit potential therapeutic functions in Drosophila melanogaster, or fruit fly that lacks cannabinoid receptors. However, it remains unclear whether cannabinoids affect food consumption and metabolism in a cannabinoid receptors-independent manner in flies. In this study, we systematically investigated pharmacological functions of various cannabinoids in modulating food preference and consumption in flies. We show that flies display preferences for consuming cannabinoids, independent of their sensory functions. Interestingly, phyto- and endo- cannabinoids exhibit an inhibitory effect on food intake. Unexpectedly, the non-selective CB1 receptor antagonist AM251 attenuates the suppression of food intake by endocannabinoids. Moreover, the endocannabinoid anandamide (AEA) and its metabolite inhibit food intake and promote resistance to starvation, possibly through reduced lipid metabolism. Thus, this study has provided insights into a pharmacological role of cannabinoids in feeding behaviors using an adult Drosophila model.

animal behavior and cognition↗

bioRxiv2020

Label-free quantification with FDR-controlled match-between-runs

Missing values weaken the power of label-free quantitative proteomic experiments to uncover true quantitative differences between biological samples or experimental conditions. Match-between-runs (MBR) has become a common approach to mitigate the missing value problem, where peptides identified by tandem mass spectra in one run are transferred to another by inference based on m/z, charge state, retention time, and ion mobility when applicable. Though tolerances are used to ensure such transferred identifications are reasonably located and meet certain quality thresholds, little work has been done to evaluate the statistical confidence of MBR. Here, we present a mixture model-based approach to estimate the false discovery rate (FDR) of peptide and protein identification transfer, which we implement in the label-free quantification tool IonQuant. Using several benchmarking datasets generated on both Orbitrap and timsTOF mass spectrometers, we demonstrate superior performance of IonQuant with FDR-controlled MBR compared to MaxQuant (19-38 times faster; 6-18% more proteins quantified and with comparable or better accuracy). We further illustrate the performance of IonQuant, and highlight the need for FDR-controlled MBR, in two single-cell proteomics experiments, including one acquired with the help of high-field asymmetric ion mobility spectrometry (FAIMS) separation. Fully integrated in FragPipe computational environment, IonQuant with FDR-controlled MBR enables fast and accurate peptide and protein quantification in label-free proteomics experiments.

bioinformatics↗

bioRxiv2020

Genome sequencing sheds light on the contribution of structural variants to Brassica oleracea diversification

Brassica oleracea includes several morphologically diverse, economically important vegetable crops. Here we present high-quality chromosome-scale genome assemblies for two B. oleracea morphotypes, cauliflower and cabbage. Direct comparison of these two assemblies identifies ~120 K high-confidence structural variants (SVs). Population analysis of 271 B. oleracea accessions using these SVs clearly separates different morphotypes, suggesting the association of SVs with B. oleracea intraspecific divergence. Genes affected by SVs selected between cauliflower and cabbage are enriched with functions related to response to stress and stimulus and meristem and flower development. Furthermore, genes affected by selected SVs and involved in the switch from vegetative to generative growth that defines curd initiation, inflorescence meristem proliferation for curd formation, maintenance and enlargement, are identified, providing insights into the regulatory network of curd development. This study reveals the important roles of SVs in diversification of different morphotypes of B. oleracea, and the newly assembled genomes and the SVs provide rich resources for future research and breeding.

plant biology↗

bioRxiv2020

Combining epiGBS markers with long read transcriptome sequencing to assess differentiation associated with habitat in Reynoutria (aka Fallopia)

Despite the limitations of genetic bottlenecks, several invasive species appear to thrive in non-native ranges with extremely low levels of sequence-based genetic variation. We previously demonstrated differentiation of DNA methylation to habitat types of the highly clonal, genetically depauperate Japanese knotweeds using anonymous markers, but the functional relevance of this DNA methylation variation is unknown. Here, we sequenced the full transcriptome combined with a reduced representation bisulfite sequencing approach, epigenotyping by sequencing (epiGBS), to characterize the association among DNA methylation, functional transcripts and the diverse habitat types occupied by the invasive Reynoutria species. We identified 50,435 putative transcripts overall, of which 48,866 were annotated with the NCBI NR database. Of these 17,872 (35%) and 16,122 (32%) transcripts shared sequence identity with Arabidopsis thaliana and Beta vulgaris, respectively. We found genetic differentiation by habitat type suggesting the action of selection and a marginal pattern of differentiation of DNA methylation among habitats, which appears to be associated with sequence differences. However, we found no individual methylation loci associated with habitat, limiting our ability to make functional interpretations. Regardless of the source of variation in DNA methylation, these changes may represent an important component of the response to environmental conditions, particularly in highly clonal plants, but more fine scale genomics analysis is required to test if DNA methylation variation in this system is responsible for functional divergence.

plant biology↗

bioRxiv2020

Medium-chain acyl-CoA dehydrogenase, a gatekeeper of mitochondrial function in glioblastoma multiforme

Glioblastoma (GBM) is among the deadliest of human cancers. Despite extensive efforts, it has proven to be highly resistant to chemo- and immune-based therapeutic strategies, and little headway has been made with targeted inhibitors. Like many cancers, metabolism is dysregulated in GBM. Thus, to identify new vulnerabilities and drug targets in GBM, we conducted genetic screens using pooled RNAi libraries targeting metabolic enzymes. We screened multiple glioma stem cell-derived (GSC) xenograft models, which revealed that several enzymes involved in the mitochondrial metabolism of fatty acids were required for tumor cell proliferation. From among these, we focused on medium-chain acyl-CoA dehydrogenase (MCAD), which oxidizes medium-chain fatty acids, due to its consistently high score across all of our screens, as well as its high expression level in multiple GSC models and its upregulation in GBM compared to normal brain. In this manuscript, we describe the dependence of GBM on sustained fatty acid metabolism to actively catabolize lipid species that would otherwise damage the mitochondrial structure. The uptake of mediumchain fatty acids lacks negative feedback regulation; therefore, in the absence of MCAD, medium-chain fatty acids accumulate to toxic levels, inducing reactive oxygen species (ROS), mitochondrial damage and failure, and apoptosis. Taken together, our findings uncover a previously unappreciated protective role exerted by MCAD in GBM cells, making it a unique and therapeutically exploitable vulnerability.

cancer biology↗