Biology subjects

Yu, B.

Publications and source records attributed to Yu, B..

143 records · Page 8Linked to original sources

bioRxiv2020

Open syntaxin overcomes synaptic transmission defects in diverse C. elegans exocytosis mutants

Assembly of SNARE complexes that mediate neurotransmitter release requires opening of a closed conformation of UNC-64/syntaxin. Rescue of unc-13/Munc13 phenotypes by overexpressed open UNC-64/syntaxin suggested a specific function of UNC-13/Munc13 in opening UNC-64/ syntaxin. Here, we revisit the effects of open unc-64/syntaxin by generating knockin (KI) worms. The KI animals exhibited enhanced spontaneous and evoked exocytosis compared to wild-type animals. Unexpectedly, the open syntaxin KI partially suppressed exocytosis defects of various mutants, including snt-1/synaptotagmin, unc-2/P/Q/N-type Ca2+ channel alpha-subunit, and unc-31/CAPS in addition to unc-13/Munc13 and unc-10/RIM, and enhanced exocytosis in tom-1/Tomosyn mutants. However, open syntaxin aggravated the defects of unc-18/Munc18 mutants. Correspondingly, open syntaxin partially bypasses the requirement of Munc13 but not Munc18 for liposome fusion. Our results show that facilitating opening of syntaxin enhances exocytosis in a wide range of genetic backgrounds, and may provide a general means to enhance synaptic transmission in normal and disease states.

neuroscience↗

bioRxiv2020

Characterization of the Intestinal Absorption of Morroniside from Cornus officinalis Sieb. et Zucc via a Caco-2 Cell Monolayer Model

Morroniside is biologically active polyphenols found in Cornus officinalis Sieb. et Zucc (CO) which exhibits a broad spectrum of pharmacological activities, such as protecting nerves, preventing diabetic liver damageand renal damage. However, little data is available regarding its mechanism ofintestinal absorption. Here, ahuman intestinal epithelial cell model Caco-2 cell in vitro cultured was applied to study on the absorption and transport of morroniside, the effects of time, donor concentration,pH, temperature and inhibitors,the absorption and transport of morroniside were investigated.The bidirectional permeability of morroniside from the apical (AP) to the basolateral (BL) side and in the revese direction was studied. When administrated was setat three tested concentrations (5, 25 and 100M), the P app value in AP-to-BL direction was ranged from 1.59 to 2.66x10 -6 cm/s. Inthe reverse direction, BL-to-AP, the value was ranged from 2.67to 4.10 x10 -6 cm/s.The data indicated that morroniside transport was both pH- and temperature- dependent. The morronisides permeability process affected bytreatment with various inhibitors, such as the multidrug resistance protein inhibitors MK571 and benzbromarone, the breast cancer resistance protein inhibitor apigenin.It can be found that the mechanisms of intestinal absorption of morroniside may involve multiple transport pathways like passive diffusion as well as efflux protein-mediated active transportespecially the multidrug resistance protein2 and breast cancer resistance protein.After CO was added, P app AB increased significantly by about 125.26%, it can therefore be assumed that some ingredients in the crude material promote morronisides absorption in the small intestine.

pharmacology and toxicology↗

bioRxiv2019

An ALS-associated mutation in human FUS reduces neurotransmission from C. elegans motor neurons to muscles

Amytrophic lateral sclerosis (ALS) is a neurodegenerative disorder that has been associated with multiple genetic lesions, including mutations in the gene FUS (Fused in Sarcoma), an RNA/DNA-binding protein. Expression of the ALS-associated human FUS in C. elegans results in mislocalization and aggregation of FUS outside the nucleus, and leads to impaired neuromuscular behaviors. However, the mechanisms by which mutant FUS disrupts neuronal health and function remain partially understood. Here we investigated the impact of ALS-associated FUS on motor neuron health using correlative light and electron microscopy, electron tomography, and electrophysiology. Expression of ALS-associated FUS impairs synaptic vesicle docking at neuromuscular junctions, and leads to the emergence of a population of large and electron-dense filament-filled endosomes. Electrophysiological recording of neuromuscular transmission revealed reduced transmission from motor neurons to muscles. Together, these results suggest a potential direct or indirect role of human FUS in the organization of synaptic vesicles, and reduced transmission from motor neurons to muscles. Summary statementAn ALS-associated mutation in a trafficking protein disrupts the organization of the C. elegans neuromuscular junction.

neuroscience↗

bioRxiv2019

Single-cell analysis of Non-CpG methylation dynamics and gene expression in human oocyte maturation

Oocyte maturation is a coordinated process that is tightly linked to reproductive potential. A better understanding of gene regulation during human oocyte maturation will not only answer an important question in biology, but also facilitate the development of in vitro maturation technology as a fertility treatment. We generated single-cell transcriptome and use previously published single-cell methylome data from human oocytes at different maturation stages to investigate how genes are regulated during oocyte maturation, focusing on the potential regulatory role of non-CG methylation. DNMT3B, a gene encoding a key non-CG methylation enzyme, is one of the 1000 genes upregulated in mature oocytes, which may be at least partially responsible for the increased non-CG methylation as oocytes mature. Non-CG differentially methylated regions (DMRs) between mature and immature oocytes have multiple binding motifs for transcription factors, some of which bind with DNMT3B and may be important regulators of oocyte maturation through non-CG methylation. Over 98% of non-CG DMRs locate in transposable elements, and these DMRs are correlated with expression changes of the nearby genes. Taken together, this data indicates that global non-CG hypermethylation during oocyte maturation may play an active role in gene expression regulation, potentially through the interaction with transcription factors.

developmental biology↗

bioRxiv2019

Unraveling the functional role of the orphan solute carrier, SLC22A24 in the transport of steroid conjugates through metabolomic and genome-wide association studies

Variation in sex hormone levels has wide implications for health and disease. The genes encoding the proteins involved in steroid disposition represent key determinants of interindividual variation in steroid levels and ultimately, their effects. Beginning with metabolomic data from genome-wide association studies (GWAS), we observed that genetic variants in the orphan transporter, SLC22A24 were significantly associated with levels of androsterone glucuronide and etiocholanolone glucuronide (sentinel SNPs p-value <1x10-30). In cells over-expressing human or various mammalian orthologs of SLC22A24, we showed that steroid conjugates and bile acids were substrates of the transporter. Phylogenetic, genomic, and transcriptomic analyses suggested that SLC22A24 has a specialized role in the kidney and appears to function in the reabsorption of organic anions, and in particular, anionic steroids. Phenome-wide analysis showed that functional variants of SLC22A24 are associated with human disease such as cardiovascular diseases and acne, which have been linked to dysregulated steroid metabolism. Collectively, these functional genomic studies reveal a previously uncharacterized protein involved in steroid homeostasis, opening up new possibilities for SLC22A24 as a pharmacological target for regulating steroid levels.\n\nAuthor SummarySteroid hormones, ranging from sex steroids such as testosterone to glucocorticoids play key roles in human health and disease. Accordingly, the identification of the genes and proteins involved in their synthesis, disposition and elimination has been the subject of numerous genetic studies. We have been intrigued by recent studies demonstrating that genetic variants in or near a gene encoding SLC22A24 are strongly associated with steroid levels. SLC22A24 is an orphan transporter with no known ligands and no known biological functions. In this study, we use cellular and computational methods to show that SLC22A24 transports steroid conjugates, bile acids and other dicarboxylic acids. Based on the direction of association of a common stop codon in SLC22A24 with lower levels of steroids, our studies suggest that the transporter functions to reabsorb steroid conjugates in the kidney, a surprising finding, given that conjugation pathways generally function to polar molecules that are readily eliminated by the kidney. The absence of the transporter gene in many species and its presence in higher order primates suggest that SLC22A24 plays a specialized role in steroid homeostasis. Overall, our studies indicate that SLC22A24 functions in the reabsorption of conjugated steroids in the kidney.

pharmacology and toxicology↗

bioRxiv2019

dbMTS: a comprehensive database of putative human microRNA target site SNVs and their functional predictions

microRNAs (miRNAs) are short non-coding RNAs that can repress the expression of protein coding messenger RNAs (mRNAs) by binding to the 3UTR of the target. Genetic mutations such as single nucleotide variants (SNVs) in the 3UTR of the mRNAs can disrupt this regulatory effect. In this study, we presented dbMTS, the database for miRNA target site (MTS) SNVs, which includes all potential MTS SNVs in the 3UTR of human genome along with hundreds of functional annotations. This database can help studies easily identify putative SNVs that affect miRNA targeting and facilitate the prioritization of their functional importance. dbMTS is freely available at: https://sites.google.com/site/jpopgen/dbNSFP.

bioinformatics↗

bioRxiv2019

Mapping of transgenic alleles in plants using a Nanopore-based sequencing strategy

Transgenic technology was developed to introduce transgenes into various organisms to validate gene function and add genetic variation for the development of beneficial input or output trait over 40 years ago. However, the identification of the transgene insertion position in the genome, while doable, can be cumbersome in the organisms with complex genomes. Here, we report a Nanopore-based sequencing method to rapidly map transgenic alleles in the soybean genome. This strategy is high-throughput, convenient, reliable, and cost-efficient. The transgenic allele mapping protocol outlined herein can be easily translated to other higher eukaryotes with complex genomes.

plant biology↗

bioRxiv2018

Refining interaction search through signed iterative Random Forests

Advances in supervised learning have enabled accurate prediction in biological systems governed by complex interactions among biomolecules. However, state-of-the-art predictive algorithms are typically \"black-boxes,\" learning statistical interactions that are difficult to translate into testable hypotheses. The iterative Random Forest (iRF) algorithm took a step towards bridging this gap by providing a computationally tractable procedure to identify the stable, high-order feature interactions that drive the predictive accuracy of Random Forests (RF). Here we refine the interactions identified by iRF to explicitly map responses as a function of interacting features. Our method, signed iRF (s-iRF), describes \"subsets\" of rules that frequently occur on RF decision paths. We refer to these \"rule subsets\" as signed interactions. Signed interactions share not only the same set of interacting features but also exhibit similar thresholding behavior, and thus describe a consistent functional relationship between interacting features and responses. We describe stable and predictive importance metrics (SPIMs) to rank signed interactions in terms of their stability, predictive accuracy, and strength of interaction. For each SPIM, we define null importance metrics that characterize its expected behavior under known structure. We evaluate our proposed approach in biologically inspired simulations and two case studies: predicting enhancer activity and spatial gene expression patterns. In the case of enhancer activity, s-iRF recovers one of the few experimentally validated high-order interactions and suggests novel enhancer elements where this interaction may be active. In the case of spatial gene expression patterns, s-iRF recovers all 11 reported links in the gap gene network. By refining the process of interaction recovery, our approach has the potential to guide mechanistic inquiry into systems whose scale and complexity is beyond human comprehension.

genomics↗

bioRxiv2018

The DeepTune framework for modeling and characterizing neurons in visual cortex area V4

Deep neural network models have recently been shown to be effective in predicting single neuron responses in primate visual cortex areas V4. Despite their high predictive accuracy, these models are generally difficult to interpret. This limits their applicability in characterizing V4 neuron function. Here, we propose the DeepTune framework as a way to elicit interpretations of deep neural network-based models of single neurons in area V4. V4 is a midtier visual cortical area in the ventral visual pathway. Its functional role is not yet well understood. Using a dataset of recordings of 71 V4 neurons stimulated with thousands of static natural images, we build an ensemble of 18 neural network-based models per neuron that accurately predict its response given a stimulus image. To interpret and visualize these models, we use a stability criterion to form optimal stimuli (DeepTune images) by pooling the 18 models together. These DeepTune images not only confirm previous findings on the presence of diverse shape and texture tuning in area V4, but also provide rich, concrete and naturalistic characterization of receptive fields of individual V4 neurons. The population analysis of DeepTune images for 71 neurons reveals how different types of curvature tuning are distributed in V4. In addition, it also suggests strong suppressive tuning for nearly half of the V4 neurons. Though we focus exclusively on the area V4, the DeepTune framework could be applied more generally to enhance the understanding of other visual cortex areas.

neuroscience↗

bioRxiv2018

Experiments and simulations on short chain fatty acid production in a colonic bacterial community

Understanding how production of specific metabolites by gut microbes is modulated by interactions with surrounding species and by environmental nutrient availability is an important open challenge in microbiome research. As part of this endeavor, this work explores interactions between F. prausnitzii, a major butyrate producer, and B. thetaiotaomicron, an acetate producer, under three different in vitro media conditions in monoculture and coculture. In silico Genome-scale dynamic flux balance analysis (dFBA) models of metabolism in the system using COMETS (Computation of Microbial Ecosystems in Time and Space) are also tested for explanatory, predictive and inferential power. Experimental findings indicate enhancement of butyrate production in coculture relative to F. prausnitzii monoculture but defy a simple model of monotonic increases in butyrate production as a function of acetate availability in the medium. Simulations recapitulate biomass production curves for monocultures and accurately predict the growth curve of coculture total biomass, using parameters learned from monocultures, suggesting that the model captures some aspects of how the two bacteria interact. However, a comparison of data and simulations for environmental acetate and butyrate changes suggest that the organisms adopt one of many possible metabolic strategies equivalent in terms of growth efficiency. Furthermore, the model seems not to capture subsequent shifts in metabolic activities observed experimentally under low-nutrient regimes. Some discrepancies can be explained by the multiplicity of possible fermentative states for F. prausnitzii. In general, these results provide valuable guidelines for design of future experiments aimed at better determining the mechanisms leading to enhanced butyrate in this ecosystem.\n\nImportanceStudies associating butyrate levels with human colonic health have inspired research on therapeutic microbiota consortia that would optimize butyrate production if implanted in the human colon. Faecalibacterium prausnitzii is commonly observed in human fecal samples and produces butyrate as a product of fermentation. Previous studies indicate that Bacteroides thetaiotaomicron, also commonly found in human fecal samples, may enhance butyrate production in F. prausnitzi when the two species are co-localized. This possibility is investigated here under different environmental conditions using experimental methods paired with computer simulations of the whole metabolism of bacterial cells. Initial findings indicate that interactions between these two species result in enhanced butyrate production. However, results also paint a nuanced picture, suggesting the existence of a multiplicity of equivalently efficient metabolic strategies and complex interactions between acetate and butyrate production in these species that appear highly dependent on specific environmental conditions.

systems biology↗

bioRxiv2018

Plasma metabolomics and incidence of atrial fibrillation: the Atherosclerosis Risk in Communities (ARIC) Study

We have previously identified associations of two circulating secondary bile acids (glycocholenate and glycolithocolate sulfate) with atrial fibrillation (AF) risk among blacks. We aimed to replicate these findings in an independent sample including both whites and blacks, and performed a new metabolomic analysis in the combined sample. We studied 3,922 participants from the ARIC cohort followed between 1987 and 2013. Of these, 1,919 had been included in the prior analysis and 2,003 were new samples. Metabolomic profiling was done in baseline serum samples using gas and liquid chromatography mass spectrometry. AF was ascertained from electrocardiograms, hospitalizations, and death certificates. We used multivariable Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (95%CI) of AF by one standard deviation difference of metabolite levels. Over a mean follow-up of 20 years, 608 participants developed AF. Glycocholenate sulfate was associated with AF in the replication and combined samples (HR 1.10, 95%CI 1.00, 1.21 and HR 1.13, 95%CI 1.04, 1.22, respectively). Glycolithocolate sulfate was not related to AF risk in the replication sample (HR 1.02, 95%CI 0.92, 1.13). An analysis of 245 metabolites in the combined cohort identified three additional metabolites associated with AF after multiple-comparison correction: pseudouridine (HR 1.18, 95%CI 1.10, 1.28), uridine (HR 0.86, 95%CI 0.79, 0.93) and acisoga (HR 1.17, 95%CI 1.09, 1.26). To conclude, we replicated a prospective association between a previously identified secondary bile acid, glycocholenate sulfate, and AF incidence, and identified new metabolites involved in nucleoside and polyamine metabolism as markers of AF risk.

epidemiology↗

bioRxiv2018

CRISPR/Cas9 gene editing for the creation of an MGAT1 deficient CHO cell line to control HIV-1 vaccine glycosylation

Over the last decade multiple broadly neutralizing monoclonal antibodies (bN-mAbs) to the HIV-1 envelope protein, gp120, have been described. Surprisingly many of these recognize epitopes consisting of both amino acid and glycan residues. Moreover, the glycans required for binding of these bN-mAbs are early intermediates in the N-linked glycosylation pathway. This type of glycosylation substantially alters the mass and net charge of HIV envelope (Env) proteins compared to molecules with the same amino acid sequence but possessing mature, complex (sialic acid containing) carbohydrates. Since cell lines suitable for biopharmaceutical production that limit N-linked glycosylation to mannose-5 (Man5) or earlier intermediates are not readily available, the production of vaccine immunogens displaying these glycan dependent epitopes has been challenging. Here we report the development of a stable suspension adapted CHO cell line that limits glycosylation to Man5 and earlier intermediates. This cell line was created using the CRISPR/Cas9 gene editing system and contains a mutation that inactivates the gene encoding Mannosyl (Alpha-1,3-)-Glycoprotein Beta-1,2-N-Acetylglucosaminyltransferase (MGAT1). Monomeric gp120s produced in the MGAT1- CHO cell line exhibit improved binding to prototypic glycan dependent bN-mAbs directed to the V1/V2 domain (e.g. PG9) and the V3 stem (e.g. PGT128 and 10-1074) while preserving the structure of the important glycan independent epitopes (e.g. VRC01). The ability of the MGAT1-CHO cell line to limit glycosylation to early intermediates in the N-linked glycosylation pathway, without impairing the doubling time or ability to grow at high cell densities, suggest that it will be a useful substrate for the biopharmaceutical production of HIV-1 vaccine immunogens.

bioengineering↗

bioRxiv2018

A Framework for Predicting Design Failures in Engineered Genetic Codes

Extreme engineering of an organisms genetic code could impart true genetic incompatibility, even blocking effects of horizontal gene transfer and viral infection. Recent experiments exploring this possibility demonstrate that such radical genome engineering achievements are plausible. However, it is unclear when the modifications will compromise the fitness of an organism. Efforts to reformat an entire genome are difficult and expensive; computational methods predicting fruitful experimental trajectories could play a pivotal role in advancing such efforts. We present a framework for building in silico models to assist genome-scale engineering. Genetic code engineering requires choosing from many possible codon-usage schemes, to find a design that is viable and effective. We use machine learning to identify which alternative codon-usage schemes are likely to result in no observed viable cells. Our data-driven approach employs observations of how modifying codon usage in individual genes impacted observed viability in E. coli, revealing salient features for early identification of problematic genetic code designs. We achieved an average area under the receiver operating characteristic of 0.72 on out-ofsample data.\n\nAuthor SummaryAs machine learning and artificial intelligence play an increasingly central role in science and engineering, it will be important to establish standardized techniques that facilitate the dialogue between experimentation and modeling. Biological experimental techniques are concurrently evolving at a rapid pace, providing unique opportunities to collect high-quality, novel information that was previously unobtainable. This work navigates the landscape of this vast, new territory, identifies interesting landmarks for exploration and posits new approaches towards advancing our research efforts in these areas. In this work, we show that, using a small dataset of 47 observations and rigorous nested cross validation techniques, we can build a model that makes better-than-random predictions of how codon usage changes in essential genes influence viability in E. coli. These predictions can be used to inform experimental trajectories in both genetic code and codon optimization experiments. We discuss ways to improve this model, iteratively, by performing high value experiments that decrease uncertainty in predictions and extrapolation error. Finally, we present novel visualization methods to aid in developing intuitions for how re-coding impacts groups of genes. These methods are also useful tools in building important insights into how well machine learning algorithms can generalize to new data.

bioengineering↗

bioRxiv2018

MITA couples with PI3K to regulate actin reorganization during BCR activation

As an adaptor protein, MITA has been extensively studied in innate immunity. However, its role in adaptive immunity as well as its underlying mechanism are not completely understood. We used MITA KO mice to study the effect of MITA deficiency on B cell development and differentiation, BCR signaling during BCR activation and humoral immune response. We found that MITA deficiency promotes the differentiation of marginal zone B cells, which is linked to the lupus-like autoimmune disease that develops in MITA KO mice. MITA is involved in BCR activation and negatively regulates the activation of CD19 and Btk and positively regulates the activation of SHIP. Interestingly, we found that the activation of WASP and accumulation of F-actin is enhanced in MITA KO B cells upon stimulation. Mechanistically, we found that MITA uses PI3K mediated by the CD19-Btk axis as a central hub to control the actin remodeling that, in turn, offers feedback to BCR signaling. Overall, our study has provided a new mechanism on how MITA regulates BCR signaling via feedback from actin reorganization, which may contribute to the effects of MITA on the humoral immune response.

immunology↗

bioRxiv2018

Robotic selection for the rapid development of stable CHO cell lines for HIV vaccine for production

The production of envelope glycoproteins (Envs) for use as HIV vaccines is challenging. The yield of Envs expressed in stable Chinese Hamster Ovary (CHO) cell lines is typically 10-100 fold lower than other glycoproteins of pharmaceutical interest. Moreover, Envs produced in CHO cells are typically enriched for sialic acid containing glycans compared to virus associated Envs that possess mainly high-mannose carbohydrates. This difference alters the net charge and biophysical properties of Envs and impacts their antigenic structure. Here we employ a novel gene-edited CHO cell line (MGAT1- CHO) to address the problems of low expression, high sialic acid content, and poor antigenic structure. We demonstrate that stable cell lines expressing high levels of gp120, potentially suitable for biopharmaceutical production can be created using the MGAT1- CHO cell line. We also show that the efficiency of this process can be greatly improved with robotic selection. Finally, we describe a MGAT1- CHO cell line expressing A244-rgp120 that exhibits improved binding of three major families of bN-mAbs compared to Envs produced in normal CHO cells. The new strategy described has the potential to eliminate the bottleneck in HIV vaccine development that has limited the field for more than 25 years.

bioengineering↗

bioRxiv2017

iterative Random Forests to discover predictive and stable high order interactions

Genomics has revolutionized biology, enabling the interrogation of whole transcriptomes, genome-wide binding sites for proteins, and many other molecular processes. However, individual genomic assays measure elements that interact in vivo as components of larger molecular machines. Understanding how these high-order interactions drive gene expression presents a substantial statistical challenge. Building on Random Forests (RF), Random Intersection Trees (RITs), and through extensive, biologically inspired simulations, we developed the iterative Random Forest algorithm (iRF). iRF trains a feature-weighted ensemble of decision trees to detect stable, high-order interactions with same order of computational cost as RF. We demonstrate the utility of iRF for high-order interaction discovery in two prediction problems: enhancer activity in the early Drosophila embryo and alternative splicing of primary transcripts in human derived cell lines. In Drosophila, among the 20 pairwise transcription factor interactions iRF identifies as stable (returned in more than half of bootstrap replicates), 80% have been previously reported as physical interactions. Moreover, novel third-order interactions, e.g. between Zelda (Zld), Giant (Gt), and Twist (Twi), suggest high-order relationships that are candidates for follow-up experiments. In human-derived cells, iRF re-discovered a central role of H3K36me3 in chromatin-mediated splicing regulation, and identified novel 5th and 6th order interactions, indicative of multi-valent nucleosomes with specific roles in splicing regulation. By decoupling the order of interactions from the computational cost of identification, iRF opens new avenues of inquiry into the molecular mechanisms underlying genome biology.

genomics↗

bioRxiv2016

Mocap: Large-scale inference of transcription factor binding sites from chromatin accessibility

Differential binding of transcription factors (TFs) at cis-regulatory loci drives the differentiation and function of diverse cellular lineages. Understanding the regulatory interactions that underlie cell fate decisions requires characterizing TF binding sites (TFBS) across multiple cell types and conditions. Techniques, e.g. ChIP-Seq can reveal genome-wide patterns of TF binding, but typically requires laborious and costly experiments for each TF-cell-type (TFCT) condition of interest. Chromosomal accessibility assays can connect accessible chromatin in one cell type to many TFs through sequence motif mapping. Such methods, however, rarely take into account that the genomic context preferred by each factor differs from TF to TF, and from cell type to cell type. To address the differences in TF behaviors, we developed Mocap, a method that integrates chromatin accessibility, motif scores, TF footprints, CpG/GC content, evolutionary conservation and other factors in an ensemble of TFCT-specific classifiers. We show that integration of genomic features, such as CpG islands improves TFBS prediction in some TFCT. Further, we describe a method for mapping new TFCT, for which no ChIP-seq data exists, onto our ensemble of classifiers and show that our cross-sample TFBS prediction method outperforms several previously described methods.

bioinformatics↗