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Yang, Y.

Publications and source records attributed to Yang, Y..

At least 955 records · Page 53Linked to original sources
bioRxiv2022

Allelic variation in the Arabidopsis TNL CHS3/CSA1 immune receptor pair reveals two functional regulatory modes

Some plant NLR immune receptors are encoded in head-to-head pairs that function together. Alleles of the NLR pair CHS3/CSA1 form three clades. The clade 1 sensor CHS3 contains an integrated domain (ID) with homology to regulatory domains, which is lacking in clades 2 and 3. We defined two regulatory modes for CHS3/CSA1 pairs. One is likely mediated by effector binding to the clade 1 ID of CHS3 and the other relies on CHS3/CSA1 pairs from all clades detecting effector modification of an associated pattern recognition receptor. We suggest that an ancestral Arabidopsis CHS3/CSA1 pair gained a second recognition specificity and regulatory mechanism through ID acquisition, while retaining its original specificity as a Guard against perturbation of pattern recognition receptor targeting by a pathogen effector. This likely comes with a cost, since both ID and non-ID alleles of the pair persist in diverse Arabidopsis populations through balancing selection. SummaryWe dissect a novel case where two regulatory modes emerged across three clades of the co-evolved CHS3/CSA1 plant immune receptor pairs, which features recruitment of an integrated domain (ID) into the clade 1 CHS3 alleles. Pre- and post-ID integration alleles maintain functionality; balancing selection maintains both in the Arabidopsis pan-genome.

plant biology↗
bioRxiv2022

Soil nitrogen impacts the rhizosphere microbial community owing to microbial hitchhiking

Microbial hitchhiking demonstrates that some nonmotile microbes utilize trans-species motility to traverse their environment; however, whether driving forces, such as plants and nitrogen, affect microbial hitchhiking is not clear. In our study, we explored the effects of plants and nitrogen fertilizer on Bacillus-hitchhiking by setting filter membranes and different nitrogen fertilizer concentration gradients. In the experimental treatment, we added a filter membrane to the soil to prevent hitchhiking. In the absence of plants, nitrogen alone had little influence on motile bacteria and hitchhiking. However, Bacillus contents were significantly impacted by the nitrogen concentration when the plants were rooted, leading to a great variation in cell motility function according to the functional analysis in the soil microbial community. After applying the filter membrane, there were no significant differences in Bacillus contents, microbial community structure or cell motility functional abundance, which illustrated that hitchhiking impacted the microbial community. Our analysis of co-occurrence between bulk soil motile bacteria (Bacillus) and rhizosphere bacteria also confirmed this. The correlation between bulk soil motile bacteria and the rhizosphere microbial community was strong in the groups with suitable nitrogen concentrations without filter membranes and was weak at all nitrogen levels in the no-membrane treatments. Thus, we concluded that plants and different nitrogen doses synergistically altered the soil microbiome by hitchhiking, whose effect depends on nitrogen.

microbiology↗
bioRxiv2022

Airway Basal Cells Show Regionally Distinct Potential to Undergo Metaplastic Differentiation

Basal cells are multipotent stem cells of a variety of organs, and in the lung are known as crucial components of the airway epithelium. However, it remains unclear how diverse basal cells are and whether distinct subpopulations respond differently to airway challenges. Using single cell RNA-sequencing and functional approaches, we report a significant and previously underappreciated degree of heterogeneity in the basal cell pool, leading to identification of six subpopulations in the murine trachea. Among these we found two major subpopulations comprising the most stem-like progenitor compartment, but with distinct signatures and ability to self-renew and differentiate. Notably, these occupy distinct ventral and dorsal tracheal niches and differ in their ability to initiate an aberrant program of differentiation in response to environmental perturbations in primary cultures and in injury mouse models in vivo. We found that such heterogeneity is acquired prenatally, when the basal cell pool and local niches are being established, and depends on the integrity of these niches, as supported by the altered basal cell phenotype of cartilage-deficient mouse mutants. Lastly, we show that key features that distinguish these progenitor subpopulations in murine airways are conserved in humans. Together, the data provide critical insights into the origin and impact of basal cell heterogeneity on the establishment of regionally distinct responses of the airway epithelium during injury-repair and in disease conditions.

developmental biology↗
bioRxiv2022

MCIBox: A Toolkit for Single-molecule Multi-way Chromatin Interaction Visualization and Micro-Domains Identification

The emerging ligation-free three-dimensional (3D) genome mapping technologies can identify multiplex chromatin interactions with single-molecule precision. These technologies offer new insight into high-dimensional chromatin organization and gene regulation, but also introduce new challenges in data visualization and analysis. To overcome these challenges, we developed MCIBox, a toolkit for Multi-way Chromatin Interaction (MCI) analysis, including a visualization tool and a platform for identifying micro-domains with clustered single-molecule chromatin complexes. MCIBox is based on various clustering algorithms integrated with dimensionality reduction methods that can display multiplex chromatin interactions at single-molecule level, allowing users to explore chromatin extrusion patterns and super-enhancers regulation modes in transcription, and to identify single-molecule chromatin complexes that are clustered into micro-domains. Furthermore, MCIBox incorporates a two-dimensional kernel density estimation algorithm to identify micro-domains boundaries automatically. These micro-domains were stratified with distinctive signatures of transcription activity and contained different cell cycle associated genes. MCIBox could potentially distinguish the specificity of single-molecule chromatin interaction patterns in various phases of a cell cycle or cell types.

genomics↗
bioRxiv2022

Reversible and gain modulation of neuronal responses and sensorimotor behavior by mid-infrared stimulation

Neuromodulation serves as a cornerstone for brain sciences and clinical applications. Mid-infrared stimulation (MIRS) has been recently reported to cause non-thermal modulation of brain functions. However little knowledge of mechanisms hampers its application. Here we bridge across ion channels, neuronal signals, and behavioral performances associated with sensorimotor transformation to provide evidence of how the alternation of neuronal activity by MIRS guides the change of behavioral performance in awake-behaving pigeons. We compared effects on visually-guided eye movements by applying MIRS and electrical stimulation (ES) in the pretectal nucleus lentiformis mesencephali (nLM). Distinct from ES, we found a specific gain modulation of MIRS to alter behavior in a manner of the strength of visual inputs. Our simultaneous extracellular recordings showed that MIRS can excite and inhibit the neuronal activity in the same pretectal neuron based on its ongoing sensory responsiveness levels in awake-behaving animals. We further applied computational simulations and found that MIRS can modulate the carbonyl group (-C=O) enriched on the potassium channel to resonate, and could affect action potential generation, alter neuronal responses to sensory inputs and then guide behavior. Our findings suggest that MIRS could be a promising approach for brain researches and neurological diseases, with gene free manipulation.

neuroscience↗
bioRxiv2022

Metformin decreases Cyp26a1 to prevent hepatocarcinogenesis through down- regulating CD8+ T cells

Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer, which limits the selectivity of prevention and treatment. Preclinical and clinical studies suggested that in patients with diabetes, prolonged use of metformin, the AMPK activator, was associated with a reduction of HCC incidence. This association promotes us to investigate the possible functions and mechanisms of metformin in HCC without diabetes backgrounds. Here, we found that several unique pathways that changed during chronic liver injury of Fah-/- mice, including glucose metabolic process and retinol metabolism. Further, metformin suppressed the tumor formation in chronic liver injury of Fah-/- mice. RNA sequencing, in vivo and in vitro experiments showed that metformin suppressed Cyp26a1 gene expression of hepatocyte. Moreover, the down-regulation of Cyp26a1 leads to the increased level of all-trans-retinoic acid (atRA), which could suppress the tumor formation in our model. On the other hand, flow multicolor analysis showed that the cell number and proportion of cancer promoting (pro-tumor) CD8+ T cells increased significantly during chronic liver injury in Fah-/- mice, and both metformin and atRA treatment could reduce the number and proportion of pro-tumor CD8+ T cells. We also found metformin decreased the Cyp26a1 expression through the AMPK/JNK/c-Jun pathway. In short, the association between the metformin and atRA may explain the commonness of their anti-tumor activities. Our findings highlight the importance of targeting the precancerous microenvironment for the prognosis, prevention and treatment of HCC.

cancer biology↗
bioRxiv2022

A Comparison of Dimension Reduction Methods for Cytometry by Time-of-Flight Data

While experimental and informatic techniques around single cell sequencing (scRNA-seq) are advanced, research around mass cytometry (CyTOF) data analysis has severely lagged behind. CyTOF data are dramatically different from scRNA-seq data in many aspects. This calls for the evaluation and development of computational methods specific for CyTOF data. Dimension reduction (DR) is one of the critical steps of single cell data analysis. Here, we benchmark the performances of 21 DR methods on 110 real and 425 synthetic CyTOF samples. We find that less well-known methods like SAUCIE, SQuaD-MDS, and scvis are the overall best performers. In particular, SAUCIE and scvis are well balanced, SQuaD-MDS excels at structure preservation, whereas UMAP has great downstream analysis performance. We also find that t- SNE (along with SQuad-MDS/t-SNE Hybrid) possesses the best local structure preservation. Nevertheless, there is a high level of complementarity between these tools, so the choice of method should depend on the underlying data structure and the analytical needs.

bioinformatics↗
bioRxiv2022

Mutually exclusive spectral biclustering and its applications in cancer subtyping

Many soft biclustering algorithms have been developed and applied to various biological and biomedical data analyses. However, until now, few mutually exclusive (hard) biclustering algorithms have been proposed although they can be extremely useful for identify disease or molecular subtypes based on genomic or transcriptomic data. We considered the biclustering problem of expression matrices as a bipartite graph partitioning problem and developed a novel biclustering algorithm, MESBC, based on Dhillons spectral method to detect mutually exclusive biclusters. MESBC simultaneously detects relevant features (genes) and corresponding subgroups, and therefore automatically uses the signature features for each subtype to perform the clustering, improving the clustering performance. MESBC could accurately detect the pre-specified biclusters in simulations, and the identified biclusters were highly consistent with the true labels. Particularly, in setting with high noise, MESBC outperformed existing NMF and Dhillons method and provided markedly better accuracy. Analysis of two TCGA datasets (LUAD and BRAC cohorts) revealed that MESBC provided similar or more accurate prognostication (i.e., smaller p value) for overall survival in patients with breast and lung cancer, respectively, compared to the existing, gold-standard subtypes for breast (PAM50) and lung cancer (integrative clustering). In the TCGA lung cancer patients, MESBC detected two clinically relevant, rare subtypes that other biclustering or integrative clustering algorithms could not detect. These findings validated our hypothesis that MESBC could improve molecular subtyping in cancer patients and potentially facilitate better individual patient management, risk stratification, patient selection, therapeutic assignments, as well as better understanding gene signatures and molecular pathways for development of novel therapeutic agents.

bioinformatics↗
bioRxiv2022

CONCERT: Genome-wide prediction of sequence elements that modulate DNA replication timing

Proper control of replication timing (RT) is of vital importance to maintain genome and epigenome integrity. However, the genome-wide sequence determinants regulating RT remain unclear. Here, we develop a new machine learning method, named CO_SCPLOWONCERTC_SCPLOW, to simultaneously predict RT from sequence features and identify RT-modulating sequence elements in a genome-wide manner. CO_SCPLOWONCERTC_SCPLOW integrates two functionally cooperative modules, a selector, which performs importance estimationbased sampling to detect predictive sequence elements, and a predictor, which incorporates bidirectional recurrent neural networks and self-attention mechanism to achieve selective learning of longrange spatial dependencies across genomic loci. We apply CO_SCPLOWONCERTC_SCPLOW to predict RT in mouse embryonic stem cells and multiple human cell types with high accuracy. The identified RT-modulating sequence elements show novel connections with genomic and epigenomic features such as 3D chromatin interactions. In particular, CO_SCPLOWONCERTC_SCPLOW reveals a class of RT-modulating elements that are not transcriptional regulatory elements but are enriched with specific repetitive sequences. As a generic interpretable machine learning framework for predicting large-scale functional genomic profiles based on sequence features, CO_SCPLOWONCERTC_SCPLOW provides new insights into the potential sequence determinants of RT.

bioinformatics↗
bioRxiv2022

Prefusion-Stabilized Lassa Virus Trimer Identifies Neutralizing Nanobodies and Reveals an Apex-Situated Site of Vulnerability

Lassa virus (LASV) is responsible for 100,000-300,000 zoonotic infections annually and poses a threat to public health. Development of antibody-based therapeutics or vaccines has been challenging because neutralizing antibodies - even among Lassa hemorrhagic fever survivors - are generally of low titer, and the target of neutralizing antibodies, the trimeric glycoprotein complex (GPC), a type 1-fusion machine with GP1 and GP2 subunits, has been difficult to produce. Here, we use structure-based design to obtain a soluble LASV GPC by engineering an inter-protomer disulfide (R207GCGP1-L326CGP2) and appending the T4-fibritin trimerization domain. We verified the antigenicity of this prefusion-stabilized LASV GPC against a panel of human antibodies and used electron microscopy (EM) to confirm its trimeric association. We panned the prefusion-stabilized LASV GPC against single domain nanobody libraries and identified one of camel origin, which we named D5, which bound GPC with 27 nM affinity and neutralized the Josiah strain of LASV with an IC50 of 12 {micro}g/ml when formatted into a bivalent IgG2a context. The cryo-EM structure of a ternary complex of the D5 nanobody, the antigen-binding fragment of human antibody 8.11G, and LASV GPC revealed D5 to recognize a site-of-vulnerability at the trimer apex. The recognized site appeared to be specific to GPC lacking cleavage of between GP1 and GP2 subunits. Collectively, our findings suggest that GPC-cleavage intermediates may be targets for LASV neutralization and define an apex-situated site of vulnerability for vaccine development. SignificanceLassa virus (LASV) infection is expanding outside its traditionally endemic areas in West Africa, posing a biothreat to the world. LASV-neutralizing antibodies, moreover, have proven difficult to elicit. To gain insight into requirements for antibody-mediated neutralization of LASV, we developed a prefusion-stabilized LASV glycoprotein trimer (GPC), panned it against phage libraries comprised single-domain antibodies or nanobodies from shark and camel, and identified one, D5, which - when placed into bivalent IgG2a context - could neutralize LASV. Cryo-EM analysis revealed D5 to recognize a cleavage-dependent site-of-vulnerability at the trimer apex. We propose this apex-situated site to be an attractive target for LASV vaccine and therapeutic development.

immunology↗
bioRxiv2022

Polio Virotherapy of Malignant Glioma Engages the Tumor Myeloid Infiltrate and Induces Diffuse Microglia Activation

Malignant gliomas commandeer abundant inflammatory infiltrates with glioma-associated macrophages and microglia (GAMM) actively promoting tumor progression. Like all cells in the mononuclear phagocytic system, macrophages and microglia constitutively express the poliovirus receptor, CD155. Besides myeloid cells, CD155 is widely upregulated ectopically in the neoplastic compartment of malignant gliomas (and solid cancers in general). Intratumor treatment with the highly attenuated rhino:poliovirus chimera, PVSRIPO, yielded long-term survival with durable radiographic responses in patients with recurrent glioblastoma (Desjardins et al. New England Journal of Medicine, 2018). Here, we studied mechanisms of PVSRIPO immunotherapy in mouse brain tumor models to decipher contributions of myeloid vs. malignant cells to antitumor efficacy. PVSRIPO treatment caused intense engagement of the GAMM infiltrate associated with substantial, but transient tumor regression. This was accompanied by diffuse microglia activation and proliferation in the normal central nervous system (CNS) surrounding the tumor, extending to the ipsilateral and even the contralateral hemispheres. PVSRIPO-instigated microglia activation occurred against a backdrop of sustained innate antiviral inflammation, associated with induction of the PD-L1 immune checkpoint on GAMM. Combining PVSRIPO with PD1/PD-L1 blockade led to durable remissions. Our work implicates GAMM as active drivers of PVSRIPO-induced antitumor inflammation and reveals profound and widespread neuroinflammatory activation of the CNS-resident myeloid compartment by PVSRIPO.

cancer biology↗
bioRxiv2022

CPGL: Prediction of compound-protein interaction by integrating graph attention network with long short-term memory neural network

Recent advancements of artificial intelligence based on deep learning algorithms have made it possible to computationally predict compound-protein interaction (CPI) without conducting laboratory experiments. In this manuscript, we integrated a graph attention network (GAT) for compounds and a long short-term memory neural network (LSTM) for proteins, used end-to-end representation learning for both compounds and proteins, and proposed a deep learning algorithm, CPGL (CPI with GAT and LSTM) to optimize the feature extraction from compounds and proteins and to improve the model robustness and generalizability. CPGL demonstrated an excellent predictive performance and outperforms recently reported deep learning models. Based on 3 public CPI datasets, C.elegans, Human and BindingDB, CPGL represented 1 - 5% improvement compared to existing deep-learning models. Our method also achieves excellent results on datasets with imbalanced positive and negative proportions constructed based on the above two datasets. More importantly, using 2 label reversal datasets, GPCR and Kinase, CPGL showed superior performance compared to other existing deep learning models. The AUC were substantially improved by 15% to 50% on the Kinase dataset, indicative of the robustness and generalizability of CPGL.

bioinformatics↗
bioRxiv2022

Shell Microelectrode Arrays (MEAs) for brain organoids

Brain organoids are important models for mimicking some three-dimensional (3D) cytoarchitectural and functional aspects of the brain. Multielectrode arrays (MEAs) that enable recording and stimulation of activity from electrogenic cells are widely utilized in biomedical engineering. However, conventional MEAs, initially designed for monolayer cultures, offer limited recording contact area restricted to the bottom of the 3D organoids. Inspired by the shape of electroencephalography (EEG) caps, we developed miniaturized chip-integrated MEA caps for organoids. The optically transparent shells are composed of self-folding polymer leaflets with conductive polymer-coated metal electrodes. Tunable folding of the minicaps polymer leaflets guided by mechanics simulations enables versatile recording from organoids of different sizes and we validate the feasibility of electrophysiology recording from 400-600 {micro}m sized organoids for up to four weeks and in response to glutamate stimulation. Our studies suggest that 3D shell MEAs offer significant potential for high signal-to-noise and 3D spatiotemporal brain organoid recording.

bioengineering↗
bioRxiv2022

Broadly neutralizing and protective nanobodies against diverse sarbecoviruses

As SARS-CoV-2 Omicron and other variants of concern continue spreading around the world, development of antibodies and vaccines to confer broad and protective activity is a global priority. Here, we report on the identification of a special group of nanobodies from immunized alpaca with exceptional breadth and potency against diverse sarbecoviruses including SARS-CoV-1, Omicron BA.1, and BA.2. Crystal structure analysis of one representative nanobody, 3-2A2-4, revealed a highly conserved epitope between the cryptic and the outer face of the receptor binding domain (RBD). The epitope is readily accessible regardless of RBD in "up" or "down" conformation and distinctive from the receptor ACE2 binding site. Passive delivery of 3-2A2-4 protected K18-hACE2 mice from infection of authentic SARS-CoV-2 Delta and Omicron. This group of nanobodies and the epitope identified should provide invaluable reference for the development of next generation antibody therapies and vaccines against wide varieties of SARS-CoV-2 infection and beyond.

immunology↗
bioRxiv2022

Profiling the size-dependent heterogeneity of membrane proteins in a mixed population of small extracellular vesicle for potential cancer diagnosis

The heterogeneity in small extracellular vesicles (small EVs) introduces an extra level of complexity in small EV-based liquid biopsy for cancer diagnosis. Heterogeneous membrane protein expression is correlated with sizes of small EVs, but accessing this correlative information is limited by the precise isolation of size-dependent subpopulations. Herein, we present a single EV enumeration (SEVEN) approach to profile protein heterogeneity in size-dependent subpopulations, and demonstrate its potential in improving the accuracy of cancer diagnosis. The interferometric plasmonic microscopy (iPM) capable of imaging single biological nanoparticles with the diameter down to 30 nm is employed to detect small EVs at the single-particle level. Small EVs population with mixed sizes are directly imaged, individually sized and digitally counted during their binding onto different aptamer-coated iPM sensor surfaces. The protein expression levels and binding kinetics of three size-dependent subpopulations are analyzed, forming a multidimensional data matrix for cancer diagnosis. Using small EVs derived from different cancer cell lines, highly heterogeneous protein profiles are recorded in the three subpopulations. We further demonstrate that the cancer classification accuracy could be greatly improved by including the subpopulation level heterogeneous protein profiles as compared with conventional ensemble measurement.

biochemistry↗
bioRxiv2022

In Silico Improvement of Highly Protective Anti-Malarial Antibodies

Antibody CIS43 binds Plasmodium falciparum circumsporozoite protein (PfCSP) and protects against malaria, as recently demonstrated clinically. To improve the efficacy of CIS43, we developed an in silico pipeline to optimize the interaction energy of CIS43 to its junctional epitope (peptide 21: PfCSP residues 101-115). Starting from two improved CIS43 variants, recently elicited from a CIS43-germline knock-in mice, single and double amino acid substitutions in the peptide 21-proximal heavy (VH) and light (VL) variable regions were introduced. CIS43-variants, selected on the basis of improved in silico interface and stability energies, showed increased affinity to peptide 21 and superior malaria-protective efficacy. The best designed variant, antibody P3-43, was significantly more protective than its template antibody m43.151, with greater liver-burden protection than the current best-in-class (antibody iGL-CIS43.D3). Crystal structures of improved antibodies revealed atomic-level interactions explaining gains in binding affinity. The reported pipeline provides a powerful in silico approach to improve antibody functionality.

immunology↗
bioRxiv2022

A Novel Prognosis Model based on Comprehensive Analysis of Pyroptosis-Related Genes in Breast Cancer

BackgroundPyroptosis plays a dual role in cancer. It can not only induce chronic tumor necrosis, but also stimulate acute inflammation to enhance immune response. However, the study of cell pyroptosis in Breast Cancer (BC) is still limited. MethodsA total of 26 pyroptosis-related differential genes were obtained, and PPI network and correlation analysis were demonstrated as well. Besides, 3 pyroptosis-related prognostic genes were collected by the univariate COX analysis. Through these 3 genes, patients were clustered into 2 sub-types by the Consensus clustering, then the EM and XMeans were also carried out to recheck the result. Furthermore, the significant prognosis-related genes were obtained by the Random Forest and LASSO analysis. Based on the above, the corresponding weights were calculated through the univariate and multivariate Cox analysis, and the prognostic model was constructed. In addition, the ROC curve, risk curve, PCA, t-SNE, COX, GO, KEGG and ssGSEA were analyzed, respectively. ResultsThrough the verification of 3 different clustering algorithms, 2 sub-types of BC were obtained. Furthermore, ELOVL2, IGLV6-57, FGBP1, HLA-DPB2 with weights of -0.183, -0.101, -0.227 and -0.254 were employed to establish the prognostic model. Validation shows that our model has good effect and the Go KEGG and Immune microenvironment analysis showed the enrichment of the differential genes. ConclusionOur study identified 4 genes that are closely correlated with the overall survival of BC patients, and the prognostic model can effectively divide patients into high- and low-risk groups, which may have certain guiding significance for prognosis.

bioinformatics↗