Biology subjects

Yang, W.

Publications and source records attributed to Yang, W..

At least 235 records · Page 13Linked to original sources

bioRxiv2022

ID1 and CEBPA Coordinate Epidermal Progenitor Cell Differentiation

The regulatory circuits that coordinate epidermal differentiation during development are still not fully understood. Here we report that the transcriptional regulator ID1 is enriched in basal epidermal progenitor cells and find ID1 expression to be diminished upon differentiation. In utero silencing of Id1 impairs progenitor cell proliferation, leads to precocious delamination of targeted progenitor cells and enables differentiated keratinocytes to retain progenitor markers and characteristics. Transcriptional profiling suggests ID1 acts by mediating adhesion to the basement membrane while inhibiting spinous layer differentiation. Co-immunoprecipitation reveals ID1 binding to transcriptional regulators of the class I bHLH family. We localize bHLH Tcf3, Tcf4 and Tcf12 to epidermal progenitor cells during epidermal stratification and established TCF3 as a downstream effector of ID1-mediated epidermal proliferation. Finally, we identify crosstalk between CEBPA, a known mediator of epidermal differentiation, and Id1 and demonstrate that CEBPA antagonizes BMP-induced activation of Id1. Our work establishes ID1 as a key coordinator of epidermal development, acting to balance progenitor proliferation with differentiation and unveils how functional crosstalk between CEBPA and Id1 orchestrates epidermal lineage progression.

developmental biology↗

bioRxiv2022

Phenethylamine-producing gut bacteria induces diarrhea-predominant irritable bowel syndrome by increasing serotonin biosynthesis

Despite the strong association between gut microbial dysbiosis, serotonin (5-HT) dysregulation and diarrhea-predominant irritable bowel syndrome (IBS-D), the mechanism by which changes in the gut microbiota contribute to the pathogenesis of IBS-D, particularly the role of dysregulated 5-HT production, remains unclear. The present study identified Ruminococcus gnavus in the human gut microbiota as a key risk factor of IBS-D. R. gnavus was significantly enriched in IBS-D patients and exhibited positive correlation with serum 5- HT level and severity of diarrhea symptoms. We showed that R. gnavus induced diarrhea-like symptoms in mice by promoting microbial shunting of essential aromatic amino acids to aromatic trace amines including phenethylamine and tryptamine, thereby stimulating the biosynthesis of peripheral 5-HT, a potent stimulator for gastrointestinal transit. This study identify gut-microbial metabolism of dietary amino acids as a cause of IBS-D and lays a foundation for developing novel therapeutic target for the treatment of IBS-D. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/483096v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@48400aorg.highwire.dtl.DTLVardef@1645aedorg.highwire.dtl.DTLVardef@18d878dorg.highwire.dtl.DTLVardef@be4b30_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2022

Structure of IgG-Fc hexamer reveals a mutual lock-and-key mode of Fc-Fc interaction

IgG exists mainly as monomer, but recent studies suggest that IgG forms hexamer to mediate antibody functions. Although many structures of IgG monomer and its fragments are determined, there is no IgG hexamer structure at atomic level due to the weak Fc-Fc interactions. Here we engineered a hexameric IgG with IgM tailpiece fusion and determined the structure by cryo-EM. IgG-Fc hexamer forms hexagon symmetry with the six Fcs lie in a plane with Fc-Fc interaction in a mutual lock-and-key mode. This structure provides structural insights into Fc-Fc interaction of IgG and reveals molecular basis for its function.

biophysics↗

bioRxiv2022

Reduced Hippocampal-Cortical Connectivity During Memory Suppression Predicts the Ability to Forget Unwanted Memories

The ability to suppress unwelcome memories is important for productivity and well-being. Successful memory suppression is associated with hippocampal deactivations and a concomitant disruption of this regions functionality. Much of the previous neuroimaging literature exploring such suppression-related hippocampal modulations has focused on the regions negative coupling with the prefrontal cortex. In contrast, task-based changes in functional connectivity between the hippocampus and other brain regions have remained relatively underexplored. Here, we utilize psychophysiological interactions and seed connectome-based predictive modeling (seed-CPM) to investigate the relationship between the hippocampus and the rest of the brain as 134 participants attempted to suppress unwanted memories during the Think/No-Think task. The results show that during retrieval suppression, the right hippocampus exhibited decreased functional connectivity with visual cortical areas (bilateral intracalcarine cortex, right cuneal cortex, left lingual gyrus, right supracalcarine cortex, right occipital pole), left nucleus accumbens and the brain-stem that predicted superior forgetting of unwanted memories on later memory tests. Validation tests verified that prediction performance was not an artifact of head motion or prediction method and that the negative features remained consistent across different brain parcellations. These findings suggest that systemic memory suppression involves more than the modulation of hippocampal activity--it alters functional connectivity patterns between the hippocampus and visual cortex, leading to successful forgetting.

neuroscience↗

bioRxiv2022

Reward contingency gates selective cholinergic suppression of amygdala neurons

Basal forebrain cholinergic neurons modulate how organisms process and respond to environmental stimuli through impacts on arousal, attention, and memory. It is unknown, however, whether basal forebrain cholinergic neurons are directly involved in conditioned behavior, independent of secondary roles in the processing of external stimuli. Using fluorescent imaging, we found that cholinergic neurons are active during behavioral responding for a reward - even in prior to reward delivery and in the absence of discrete stimuli. Photostimulation of basal forebrain cholinergic neurons, or their terminals in the basolateral amygdala (BLA), selectively promoted conditioned responding (licking), but not unconditioned behavior nor innate motor outputs. In vivo electrophysiological recordings during cholinergic photostimulation revealed reward-contingency-dependent suppression of BLA neural activity, but not prefrontal cortex (PFC). Finally, ex vivo experiments demonstrated that photostimulation of cholinergic terminals suppressed BLA projection neuron activity via monosynaptic muscarinic-receptor-signaling, while also facilitating firing in GABAergic interneurons. Taken together, we show that the neural and behavioral effects of basal forebrain cholinergic activation are modulated by reward contingency in a target-specific manner.

neuroscience↗

bioRxiv2022

A metric and its derived protein similarity network to analyze function-oriented ortholog

Orthology prediction is challenging yet rewarding. Orthologs are the cornerstone of almost all comparative genomics studies. Dozens of ortholog resources have been available and broadly used over the past decades. However, the inconsistency between these resources has drawn growing concerns, especially when more proteomes are available and ortholog databases expand. It is no longer easy to decide which ortholog database to use, and it becomes necessary to compare conclusions based on different resources. We are presenting here a metric to assess ortholog functional consistency. Using this metric, we built a network connecting proteins based on their functional similarity. We then detected network communities as ortholog groups, and each protein in our ortholog group inherited the network degree centrality. By benchmarking Quest for Orthologs (QfO) and some representative ortholog resources, we concluded the degree centrality could serve as the index for the reliability of functional consistency. The numerical nature of degree centrality could also open a door for quantitative study in pan-genome and other comparative genomics studies.

bioinformatics↗

bioRxiv2022

Multiplexed imaging mass cytometry reveals distincttumor-immune microenvironments linked to immunotherapyresponses in melanoma

Single-cell technologies have enabled extensive analysis of complex immune composition, phenotype and interactions within tumor, which is crucial in understanding the mechanisms behind cancer progression and treatment resistance. Unfortunately, the knowledge on cell phenotypes and their spatial interactions at present has only limited utilization in guiding pathological stratification on patients based on their immune microenvironments for better clinical decisions. Here we used imaging mass cytometry (IMC) to simultaneously quantify 35 proteins in a spatially resolved manner on tumor tissues from melanoma patients receiving anti-programmed cell death-1 (anti-PD-1) therapy. Unbiased single-cell analysis revealed highly dynamic tumor-immune microenvironments that are characterized with variable tumor and immune cell phenotypes and their organizations across and within melanomas, and identified distinct archetypes of melanoma microenvironments that are associated with benefit from anti-PD-1 therapy based on high-dimensional multicellular features. Our results demonstrate the utility of multiplex proteomic imaging technologies in studying complex molecular events in a spatially resolved manner for the development of new strategies for patient stratification and treatment outcome prediction.

immunology↗

bioRxiv2022

ISSAAC-seq enables sensitive and flexible multimodal profiling of chromatin accessibility and gene expression in single cells

Joint profiling of chromatin accessibility and gene expression from the same single cell/nucleus provides critical information about cell types in a tissue and cell states during a dynamic process. These emerging multi-omics techniques help the investigation of cell-type resolved gene regulatory mechanisms1-7. However, many methods are currently limited by low sensitivity, low throughput or complex workflow. Here, we developed in situ SHERRY after ATAC-seq (ISSAAC-seq), a highly sensitive and flexible single cell multi-omics method to interrogate chromatin accessibility and gene expression from the same single nucleus. We demonstrated that ISSAAC-seq is sensitive and provides high quality data with orders of magnitude more features than existing methods. Using the joint profiles from over 10,000 nuclei from the mouse cerebral cortex, we uncovered major and rare cell types and cell-type specific regulatory elements and identified heterogeneity at the chromatin level within established cell types defined by gene expression. Finally, we revealed distinct dynamics and relationships of gene expression and chromatin accessibility during an oligodendrocyte maturation trajectory.

genomics↗

bioRxiv2022

Structural and functional impact by SARS-CoV-2 Omicron spike mutations

The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), bearing an unusually high number of mutations, has become a dominant strain in many countries within several weeks. We report here structural, functional and antigenic properties of its full-length spike (S) protein with a native sequence in comparison with those of previously prevalent variants. Omicron S requires a substantially higher level of host receptor ACE2 for efficient membrane fusion than other variants, possibly explaining its unexpected cellular tropism. Mutations not only remodel the antigenic structure of the N-terminal domain of the S protein, but also alter the surface of the receptor-binding domain in a way not seen in other variants, consistent with its remarkable resistance to neutralizing antibodies. These results suggest that Omicron S has acquired an extraordinary ability to evade host immunity by excessive mutations, which also compromise its fusogenic capability.

biochemistry↗

bioRxiv2022

Epac1 regulates cellular SUMOylation by promoting the formation of SUMO-activating nuclear condensates

Protein SUMOylation plays an essential role in maintaining cellular homeostasis when cells are under stress. However, precisely how SUMOylation is regulated, and a molecular mechanism linking cellular stress to SUMOylation remains elusive. Herein, we report that cAMP, a major stress-response second messenger, acts through Epac1 as a regulator of cellular SUMOylation. The Epac1-associated proteome is highly enriched with components of the SUMOylation pathway. Activation of Epac1 by intracellular cAMP triggers phase separation and the formation of nuclear condensates containing Epac1 and general components of the SUMOylation machinery to promote cellular SUMOylation. Furthermore, genetic knockout of Epac1 obliterates oxidized low-density lipoprotein induced cellular SUMOylation in macrophages, leading to suppression of foam cell formation. These results provide a direct nexus connecting two major cellular stress responses to define a molecular mechanism in which cAMP regulates the dynamics of cellular condensates to modulate protein SUMOylation.

cell biology↗

bioRxiv2021

An ultrapotent RBD-targeted biparatopic nanobody neutralizes broad SARS-CoV-2 variants

The wide transmission and host adaptation of SARS-CoV-2 have led to the rapid accumulation of mutations, posing significant challenges to the effectiveness of vaccines and therapeutic antibodies. Although several neutralizing antibodies were authorized for emergency clinical use, convalescent patients derived natural antibodies are vulnerable to SARS-CoV-2 Spike mutation. Here, we describe the screen of a panel of SARS-CoV-2 receptor-binding domain (RBD) targeted nanobodies (Nbs) from a synthetic library and the design of a biparatopic Nb, named Nb1-Nb2, with tight affinity and super wide neutralization breadth against multiple SARS-CoV-2 variants of concern. Deep-mutational scanning experiments identify the potential binding epitopes of the Nbs on the RBD and demonstrate that biparatopic Nb1-Nb2 has a strong escape resistant feature against more than 60 tested RBD amino acid substitutions. Using pseudovirion-based and trans-complementation SARS-CoV-2 tools, we determine that the Nb1-Nb2 broadly neutralizes multiple SARS-CoV-2 variants, including Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), Lambda (C.37), Kappa (B.1.617.1) and Mu (B.1.621). Furthermore, a heavy chain antibody is constructed by fusing the human IgG1 Fc to Nb1-Nb2 (designated as Nb1-Nb2-Fc) to improve its neutralization potency, yield, stability and potential half-life extension. For the new Omicron variant (B.1.1.529) that harbors unprecedented multiple RBD mutations, Nb1-Nb2-Fc keeps a firm affinity (KD < 1.0x10-12 M) and strong neutralizing activity (IC50 = 0.0017 nM). Together, we developed a tetravalent biparatopic human heavy chain antibody with ultrapotent and broad-spectrum SARS-CoV-2 neutralization activity which highlights the potential clinical applications.

microbiology↗

bioRxiv2021

Two distinct binding modes provide the RNA binding protein RbFox with extraordinary sequence specificity

The specificity of RNA-binding proteins for their target sequences varies considerably. Yet, it is not understood how certain proteins achieve markedly higher sequence specificity than most others. Here we show that the RNA Recognition Motif of RbFox accomplishes extraordinary sequence specificity by employing functionally and structurally distinct binding modes. Affinity measurements of RbFox for all binding site variants reveal the existence of two different binding modes. The first exclusively binds the cognate and a closely related RNA variant with high affinity. The second mode accommodates all other RNAs with greatly reduced affinity, thereby imposing large thermodynamic penalties on even near-cognate sequences. NMR studies indicate marked structural differences between the two binding modes, including large conformational rearrangements distant from the RNA binding site. Distinct binding modes by a single RNA binding module explain extraordinary sequence selectivity and reveal an unknown layer of functional diversity, cross talk and regulation for RNA-protein interactions.

biochemistry↗

bioRxiv2021

A slow dynamic switch regulates processing of microRNA-21

The microRNAs are non-coding RNAs which post-transcriptionally regulate the expression of a majority of eukaryotic genes, and whose dysregulation is a driver of many human diseases. Here we report the discovery of a very slow (0.1 sec) conformational rearrangement at the Dicer cleavage site of pre-miR-21 which regulates the relative concentration of readily processed and inefficiently processed structural states. We show this dynamic switch is affected by single nucleotide mutations and can be biased by small molecule and peptide ligands, which can direct the microRNA to occupy the inefficiently processed state and reduce processing efficiency. This result reveals a new mechanism of RNA regulation and suggests a chemical approach to suppressing or activating pathogenic microRNAs by selective stabilization of the unprocessed or processed state.

biochemistry↗

bioRxiv2021

A high-density lineage tree reveals dynamics of expression differences accumulation in nondifferentiating clonal expansion

Differences in gene expression levels among genetically identical cells naturally accumulate during cellular proliferation, forming the basis of expression noise or differentiation. Nevertheless, how transcriptome-wide noise accumulation is constrained to maintain homeostasis during continuous cell divisions has remained largely unresolved. We developed a novel method named "single-cell transcriptome and dense tree" (STADT) to simultaneously determines the transcriptomes and lineage tree of >50% single cells in a single-cell-seeded colony. This lineage tree revealed gradual accumulation of transcriptome differences that became saturated upon four cell divisions, reduced expression noise for sub-tree/sub-colonies closer to inferred expression boundaries, and transcriptionally modulated co-fluctuations among genes. These results collectively showed, for the first time, constrained dynamics of expression noise in the context of cell division.

cell biology↗

bioRxiv2021

Identification, analysis, and confirmation of seed storability-related loci in Dongxiang wild rice (Oryza rufipogon Griff.)

Dongxiang wild rice (Oryza rufipogon Griff.) (DXWR) has strong seed storability and identifying its elite gene resources may facilitate genetic improvements in rice seed storability. In this study, we developed two backcross inbred lines (BILs) populations, with DXWR as a common donor parent and two rice varieties (F6 and R974) as recipient parents. Bulked segregant analysis via whole genome sequencing (BSA-seq) was used to identify seed storability-related loci in the DXWR and F6 population. Two main genomic regions containing 18,550,000-20,870,000 bp on chromosome 4 and 7,860,000-9,780,000 bp on chromosome 9 were identified as candidate loci of DXWR seed storability; these overlapped partially with seed storability-related quantitative trait loci (QTLs) discovered in previous studies, suggesting that these loci may provide important regions for isolating the responsible genes. In total, 448 annotated genes were predicted within the identified regions, of which 274 and 82 had nonsynonymous and frameshift mutations, respectively. We detected extensive metabolic activities and cellular processes during seed storability and confirmed the effects of the seed storability-related candidate loci using four BILs from DXWR and R974. These results may facilitate the cloning of DXWR seed storability-related genes, thereby elucidating rice seed storability and its improvement potential.

genomics↗

bioRxiv2021

4DPhenoMVS: A Low-Cost 3D Tomato Phenotyping Pipeline Using a 3D Reconstruction Point Cloud Based on Multiview Images

Manual phenotyping of tomato plants is time consuming and labor intensive. Due to the lack of low-cost and open-access 3D phenotyping tools, the dynamic 3D growth of tomato plants during all growth stages has not been fully explored. In this study, based on the 3D structural data points generated by employing structures from motion algorithms on multiple-view images, we proposed a dynamic 3D phenotyping pipeline, 4DPhenoMVS, to calculate and analyze 14 phenotypic traits of tomato plants covering the whole life cycle. The results showed that the R2 values between the phenotypic traits and the manual measurements stem length, plant height, and internode length were more than 0.8. In addition, to investigate the environmental influence on tomato plant growth and yield in the greenhouse, eight tomato plants were chosen and phenotyped during 7 growth stages according to different light intensities, temperatures, and humidities. The results showed that stronger light intensity and moderate temperature and humidity contribute to a higher growth rate and higher yield. In conclusion, we developed a low-cost and open-access 3D phenotyping pipeline for tomato plants, which will benefit tomato breeding, cultivation research, and functional genomics in the future. HighlightsBased on the 3D structural data points generated by employing structures from motion algorithms on multiple-view images, we developed a low-cost and open-access 3D phenotyping tool for tomato plants during all growth stages.

plant biology↗

bioRxiv2021

Deep learning methods for designing proteins scaffolding functional sites

Current approaches to de novo design of proteins harboring a desired binding or catalytic motif require pre-specification of an overall fold or secondary structure composition, and hence considerable trial and error can be required to identify protein structures capable of scaffolding an arbitrary functional site. Here we describe two complementary approaches to the general functional site design problem that employ the RosettaFold and AlphaFold neural networks which map input sequences to predicted structures. In the first "constrained hallucination" approach, we carry out gradient descent in sequence space to optimize a loss function which simultaneously rewards recapitulation of the desired functional site and the ideality of the surrounding scaffold, supplemented with problem-specific interaction terms, to design candidate immunogens presenting epitopes recognized by neutralizing antibodies, receptor traps for escape-resistant viral inhibition, metalloproteins and enzymes, and target binding proteins with designed interfaces expanding around known binding motifs. In the second "missing information recovery" approach, we start from the desired functional site and jointly fill in the missing sequence and structure information needed to complete the protein in a single forward pass through an updated RoseTTAFold trained to recover sequence from structure in addition to structure from sequence. We show that the two approaches have considerable synergy, and AlphaFold2 structure prediction calculations suggest that the approaches can accurately generate proteins containing a very wide array of functional sites.

biochemistry↗

bioRxiv2021

Fast anther dehiscence state recognition system establishing by deep learning to screen heat tolerant cotton

Cotton is one of the most economically important crops in the world. The fertility of male reproductive organs is a key determinant of cotton yield. The anther dehiscence or indehiscence directly determine the probability of fertilization in cotton. Thus, the rapid and accurate identification of cotton anther dehiscence status is important for judging anther growth status and promoting genetic breeding research. The development of computer vision technology and the advent of big data have prompted the application of deep learning techniques to agricultural phenotype research. Therefore, two deep learning models (Faster R-CNN and YOLOv5) were proposed to detect the number and dehiscence status of anthers. The single-stage model based on YOLOv5 has higher recognition efficiency and the ability to deploy to the mobile end. Breeding researchers can apply this model to terminals to achieve a more intuitive understanding of cotton anther dehiscence status. Moreover, three improvement strategies of Faster R-CNN model were proposed, the improved model has higher detection accuracy than YOLOv5 model. In addition, the percentage of dehiscent anther of randomly selected 30 cotton varieties were observed from cotton population under normal temperature and high temperature (HT) conditions through the integrated Faster R-CNN model and manual observation. The result showed HT varying decreased the percentage of dehiscent anther in different cotton lines, consistent with the manual method. Thus, this system can help us to rapid and accurate identification of HT-tolerant cotton. One sentence summaryThe deep learning technique was applied to identify the anther dehiscence state for the first time to quickly screen heat tolerant cotton varieties and help to explore key genetic improvement genes.

bioengineering↗