Biology subjects

Zheng, Y.

Publications and source records attributed to Zheng, Y..

At least 253 records · Page 14Linked to original sources

bioRxiv2023

Genome-wide SNP data reveal recent population structure of Huidobria fruticosa (Loasaceae), a paleo-endemic lineage from the Atacama Desert

The Atacama Desert is a biodiversity hotspot of neo-endemic radiation, where long-term aridity and complex physiographic processes create a unique environmental setting. Current species assemblages are mainly concentrated in highly patchy loma formations, and plant populations occurring in these are often geographically isolated from each other. Despite a general consensus on long-term aridity in the Atacama, climatological and geological evidence points to repeated climate change, making the Atacama Desert an ideal system for studying population genetic processes in highly unstable habitats. We are analyzing the genetic structure within and between populations of Huidobria fruticosa, a paleo-endemic lineage of the Atacama Desert, to shed new light on its biogeographic history and broaden our understanding of the evolution of life in extreme aridity, as well as plant evolution in response to a changing environment. To do this, we analyzed SNP data from genotyping-by-sequencing of 354 individuals from 21 populations. Our results suggest that, despite being an ancient lineage, the current population structure of Huidobria fruticosa only reflects changing abiotic conditions over the last 2 million years. We therefore conclude that the present distribution, together with the evolutionary processes documented here, is the result of climatic fluctuations and prolonged periods of hyperaridity during the Pleistocene. Building on this understanding, our findings contribute to a global narrative that highlights the complex interplay between climate change and evolutionary dynamics, and emphasize the importance of deserts as living laboratories for deciphering how species have historically adapted to some of the most extreme habitats on Earth.

evolutionary biology↗

bioRxiv2023

Predicting the dynamic interaction between intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) participate in various biological processes. Interactions involving IDPs are usually dynamic and affected by their inherent conformation fluctuations. Comprehensive characterization of these interactions based on current techniques is challenging. Here, we present GSALIDP, a GraphSAGE-LSTM Network to capture the dynamic nature of IDP-involved interactions and predict their behaviors. This framework models multiple conformations of IDP as a dynamic graph which can effectively describe the fluctuation of its flexible conformation. The dynamic interaction between IDPs is studied and the datasets of IDP conformations and their interactions are obtained through atomistic molecular dynamic (MD) simulations. Residues of IDP are encoded through a series of features, including their frustration. GSALIDP can effectively predict the interaction sites of IDP and the contact residue pairs between IDPs. Its performance in predicting IDP interaction is on par with or even better than the conventional models in predicting the interaction of structural proteins. To the best of our knowledge, this is the first model to extend the protein interaction prediction to IDP-involved interactions.

molecular biology↗

bioRxiv2023

Deletion of sulfate transporter SUL1 extends yeast replicative lifespan via reduced PKA signaling instead of decreased sulfate uptake

The regulation of cellular metabolism and growth in response to nutrient availability is crucial for cell survival and can significantly impact on lifespan. Central to this regulation is a class of transporters that sense and transport specific nutrients and transduce the signal downstream to control genes responsible for growth and survival. In this study, we identified SUL1, a plasma membrane transporter responsible for regulating the entry of extracellular sulfate in Saccharomyces cerevisiae, as a key gene for regulating lifespan. We conducted a systematic analysis to delineate the downstream mechanism underlying the lifespan extension by SUL1 deletion. Surprisingly, we found that the lifespan extending effect of SUL1 deletion is not due to decreased sulfate transport. The SUL1 deletion mutant exhibited decreased PKA signaling, resulting in a series of downstream effects, including increased stress-protective trehalose and glycogen, increased nuclear translocation of MSN2, elevated expression of general stress response genes, enhanced autophagy, and reduced expression of amino acid biosynthetic and ribosomal genes. We demonstrated that the observed increase in lifespan is dependent on MSN2 and autophagy pathways. Our findings exemplify the influence of nutrient signaling rather than the nutrient itself on lifespan regulation and further substantiate the pivotal role of the PKA pathway in this process.

molecular biology↗

bioRxiv2023

Integrated multi-omics single cell atlas of the human retina

Single-cell sequencing has revolutionized the scale and resolution of molecular profiling of tissues and organs. Here, we present an integrated multimodal reference atlas of the most accessible portion of the mammalian central nervous system, the retina. We compiled around 2.4 million cells from 55 donors, including 1.4 million unpublished data points, to create a comprehensive human retina cell atlas (HRCA) of transcriptome and chromatin accessibility, unveiling over 110 types. Engaging the retina community, we annotated each cluster, refined the Cell Ontology for the retina, identified distinct marker genes, and characterized cis-regulatory elements and gene regulatory networks (GRNs) for these cell types. Our analysis uncovered intriguing differences in transcriptome, chromatin, and GRNs across cell types. In addition, we modeled changes in gene expression and chromatin openness across gender and age. This integrated atlas also enabled the fine-mapping of GWAS and eQTL variants. Accessible through interactive browsers, this multimodal cross-donor and cross-lab HRCA, can facilitate a better understanding of retinal function and pathology.

molecular biology↗

bioRxiv2023

Thermo-sensitive condensation of SUF4 tunes flowering time in Arabidopsis thaliana

Intrinsically disordered proteins (IDP) lack stable tertiary structures, which allows them to change conformation and function under different physicochemical conditions. This may be highly advantageous for plants, which often use changes in their environment to elicit a variety of responses, including developmental events. For instance, some plants delay flowering in the fall and require exposure to winter temperatures as a cue to initiate flowering the following spring. Many of the genes involved in temperature-dependent flowering have been extensively studied in Arabidopsis, yet how plants coordinate their molecular states with seasonal temperature change is poorly understood. Here, we explore the role of temperature-sensitive phase separation of the IDP and flowering-time regulator, SUPPRESSOR OF FRIGIDA 4 (SUF4), in modulating flowering time. SUF4 has a well-defined role in regulating temperature-dependent flowering time by activating the master floral suppressor FLOWERING LOCUS C (FLC). We show that in plant nuclei, SUF4 is a temperature-sensitive protein that assembles into biomolecular condensates in warm temperatures (20{degrees}C). When temperatures cool (4{degrees}C), SUF4 nuclear condensates disassemble, causing SUF4 to disperse within the nucleoplasm. Additionally, we demonstrate that the number of SUF4 condensates quantitatively correlates with flowering time. Progressive alterations to the amino acid composition of SUF4s disordered region cause likewise progressive changes in temperature-dependent condensation both in vitro and in vivo, FLC transcription, and the onset of flowering. Lastly, we observe that SUF4 condensates coincide with the accumulation of other key flowering-time proteins (FRIGIDA and ELF7). These findings indicate that condensation of SUF4 likely plays a pivotal role in promoting flowering, possibly by concentrating and stabilizing regulatory factors needed for the transcriptional activation of FLC through temperature-dependent phase separation. This research suggests that in plants, IDPs can sense environmental cues and regulate critical developmental processes. One-Sentence SummaryEvidence suggest that Arabidopsis uses temperature-sensitive condensation to regulate FLC transcription and flowering time.

plant biology↗

bioRxiv2023

Graph attention-based fusion of pathology images and gene expression for prediction of cancer survival

Multimodal machine learning models are being developed to analyze pathology images and other modalities, such as gene expression, to gain clinical and biological in-sights. However, most frameworks for multimodal data fusion do not fully account for the interactions between different modalities. Here, we present an attention-based fusion architecture that integrates a graph representation of pathology images with gene expression data and concomitantly learns from the fused information to predict patient-specific survival. In our approach, pathology images are represented as undirected graphs, and their embeddings are combined with embeddings of gene expression signatures using an attention mechanism to stratify tumors by patient survival. We show that our framework improves the survival prediction of human non-small cell lung cancers, out-performing existing state-of-the-art approaches that lever-age multimodal data. Our framework can facilitate spatial molecular profiling to identify tumor heterogeneity using pathology images and gene expression data, complementing results obtained from more expensive spatial transcriptomic and proteomic technologies.

bioinformatics↗

bioRxiv2023

Prdm1 Positively Regulates Liver Type 1 ILCs Cancer Immune Surveillance and Preserves Functional Heterogeneity

Group 1 innate lymphoid cells (ILCs) comprise conventional natural killer (cNK) cells and type 1 innate lymphoid cells (ILC1s). The main functions of liver cNK cells and ILC1s not only include directly killing target cells but also regulating local immune microenvironment of the liver through the secretion of cytokines. Uncovering the intricate mechanisms by which transcriptional factors regulate and influence the functions of liver cNK cells and ILC1s, particularly within the context of liver tumors, presents a significant opportunity to amplify the effectiveness of immunotherapies against liver malignancies. Using Ncr1-drived conditional knockout mouse model, our study reveals the regulatory role of Prdm1 in shaping the composition and maturation of cNK cells. Although Prdm1 did not affect the killing function of cNK cells in an in vivo cytotoxicity model, a significant increase in cancer metastasis was observed in Prdm1 knockout mice. Interferon-gamma (IFN-{gamma}), granzyme B, and perforin secretion decreased significantly in Prdm1 deficient cNK cells and liver ILC1s. scRNA sequencing data also provided evidences that Prdm1 maintains functional subsets of cNK cells and liver ILC1s and facilitates communications between cNK cells, liver ILC1s and macrophages. The present study unveiled a novel regulatory mechanism of Prdm1 in cNK cells and liver ILC1s, showing promising potential for developing innovative immune therapy strategies against liver cancer. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/563222v4_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@194f9forg.highwire.dtl.DTLVardef@1ba5b0eorg.highwire.dtl.DTLVardef@1b02121org.highwire.dtl.DTLVardef@4f0385_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2023

Proteomic Stratification of Prognosis and Treatment Options for Small Cell Lung Cancer

Small cell lung cancer (SCLC) is a highly malignant and heterogeneous cancer with limited therapeutic options and prognosis prediction models. Here, we analyzed formalin-fixed, paraffin-embedded (FFPE) samples of surgical resections by proteomic profiling, and stratified SCLC into three proteomic subtypes (S-I, S-II, and S-III) with distinct clinical outcomes and chemotherapy responses. The proteomic subtyping was an independent prognostic factor and performed better than current TNM or Veterans Administration Lung Study Group (VALG) staging methods. The subtyping results could be further validated using FFPE biopsy samples from an independent center, extending the analysis to both surgical and biopsy samples. The signatures of the S-II subtype in particular suggest potential benefits from immunotherapy. Differentially overexpressed proteins in S-III, the worst prognostic subtype, allowed us to nominate potential therapeutic targets, indicating that patient selection may bring new hope for previously failed clinical trials. Finally, analysis of an independent cohort of SCLC patients who had received immunotherapy validated the prediction that the S-II patients had better Progression Free Survival (PFS) and Overall Survival (OS) after first-line immunotherapy. Collectively, our study provides the rationale for future clinical investigations to validate the current findings for more accurate prognosis prediction and precise treatments.

cancer biology↗

bioRxiv2023

LKB1 suppresses growth and promotes the internalization of EGFR through the PIKFYVE lipid kinase

The tumor suppressor LKB1 is a serine/threonine protein kinase that is frequently mutated in human lung adenocarcinoma (LUAD). LKB1 regulates a complex signaling network that is known to control cell polarity and metabolism; however, the pathways that mediate the tumor suppressive activity of LKB1 are incompletely defined. To identify mechanisms of LKB1- mediated growth suppression we developed a spheroid-based cell culture assay to study LKB1- dependent growth. Using this assay, along with genome-wide CRISPR screens and validation with orthogonal methods, we discovered that LKB1 suppresses growth, in part, by activating the PIKFYVE lipid kinase, which promotes the internalization of wild-type EGFR. Our findings reveal a new mechanism of regulation of EGFR, which may have implications for the treatment of LKB1-mutant LUAD.

cancer biology↗

bioRxiv2023

Graph perceiver network for lung tumor and premalignant lesion stratification from histopathology

Bronchial premalignant lesions (PMLs) precede the development of invasive lung squamous carcinoma (LUSC), posing a significant challenge in distinguishing those likely to advance to LUSC from those that might regress without intervention. In this context, we present a novel computational approach, the Graph Perceiver Network (GRAPE-Net), leveraging hematoxylin and eosin (H&E) stained whole slide images (WSIs) to stratify endobronchial biopsies of PMLs across a spectrum from normal to tumor lung tissues. GRAPE-Net outperforms existing frameworks in classification accuracy predicting LUSC, lung adenocarcinoma (LUAD), and non-tumor (normal) lung tissue on The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) datasets containing lung resection tissues while efficiently generating pathologist-aligned, class-specific heatmaps. The network was further tested using endobronchial biopsies from two data cohorts, containing normal to carcinoma in situ histology, and it demonstrated a unique capability to differentiate carcinoma in situ lung squamous PMLs based on their progression status to invasive carcinoma. The network may have utility in stratifying PMLs for chemoprevention trials or more aggressive follow-up.

pathology↗

bioRxiv2023

Single-cell bisulfite-free 5mC and 5hmC sequencing with high sensitivity and scalability

Existing single cell bisulfite-based DNA methylation analysis is limited by low DNA recovery, and the measurement of 5hmC at single-base resolution remains challenging. Here we present a bisulfite-free single-cell whole-genome 5mC and 5hmC profiling technique, named Cabernet, which can characterize 5mC and 5hmC at single-base resolution with high genomic coverage. Cabernet utilizes Tn5 transposome for DNA fragmentation, which enables the discrimination between different alleles for measuring hemi-methylation status. Using Cabernet, we revealed the 5mC, hemi-5mC and 5hmC dynamics during early mouse embryo development, uncovering genomic regions exclusively governed by active or passive demethylation. We show that hemi-methylation status can be used to distinguish between pre- and post-replication cells, enabling more efficient cell grouping when integrated with 5mC profile. The property of Tn5 naturally enables Cabernet to achieve high-throughput single-cell methylome profiling, where we probed mouse cortical neurons and embryonic day 7.5 (E7.5) embryos, and constructed the library for thousands of single cells at high efficiency, demonstrating its potential for analyzing complex tissues at substantially low cost. Together, we present a new way of high-throughput methylome and hydroxymethylome detection at single-cell resolution, enabling efficient analysis of epigenetic status of biological systems with complicated nature such as neurons and cancer cells. Significance StatementMost of current methylation profiling techniques rely on bisulfite treatment, which suffers low DNA recovery. The technique proposed in this study, named Cabernet, can be used to measure 5mC and 5hmC at single-base resolution with high genomic coverage. By using Tn5 transposome, hemi-methylation status can be measured and high-throughput methylome profiling can be achieved. Together, it provides an efficient way to analyze the epigenetic landscape of complicated biological systems.

genomics↗

bioRxiv2023

Digital profiling of cancer transcriptomes from histology images with grouped vision attention

Cancer is a heterogeneous disease that demands precise molecular profiling for better understanding and management. Recently, deep learning has demonstrated potentials for cost-efficient prediction of molecular alterations from histology images. While transformer-based deep learning architectures have enabled significant progress in non-medical domains, their application to histology images remains limited due to small dataset sizes coupled with the explosion of trainable parameters. Here, we develop SEQUOIA, a transformer model to predict cancer transcriptomes from whole-slide histology images. To enable the full potential of transformers, we first pre-train the model using data from 1,802 normal tissues. Then, we fine-tune and evaluate the model in 4,331 tumor samples across nine cancer types. The prediction performance is assessed at individual gene levels and pathway levels through Pearson correlation analysis and root mean square error. The generalization capacity is validated across two independent cohorts comprising 1,305 tumors. In predicting the expression levels of 25,749 genes, the highest performance is observed in cancers from breast, kidney and lung, where SEQUOIA accurately predicts the expression of 11,069, 10,086 and 8,759 genes, respectively. The accurately predicted genes are associated with the regulation of inflammatory response, cell cycles and metabolisms. While the model is trained at the tissue level, we showcase its potential in predicting spatial gene expression patterns using spatial transcriptomics datasets. Leveraging the prediction performance, we develop a digital gene expression signature that predicts the risk of recurrence in breast cancer. SEQUOIA deciphers clinically relevant gene expression patterns from histology images, opening avenues for improved cancer management and personalized therapies.

bioinformatics↗

bioRxiv2023

Estradiol propionate reduction of nuclear size in prostate cancer lines lacking DHRS7suggests DHRS7 absence as a biomarker for the effectiveness of estrogen therapy

Increased nuclear size correlates with lower survival rates for prostate cancer and is a hallmark of late-stage androgen-insensitive tumors. The short-chain dehydrogenase/reductase (SDR) family member DHRS7 was suggested as a marker for prostate cancer grading because it is lost in late-stage androgen-insensitive tumors. Here we find that loss of DHRS7 from the early-stage LNCaP prostate cancer cell line increases nuclear size, potentially explaining the nuclear size increase observed in higher-grade prostate tumors. Exogenous expression of DHRS7 in the late-stage PC3 prostate cancer cell line correspondingly decreases nuclear size. We separately tested 80 compounds from the Microsource Spectrum library for their ability to restore normal nuclear size to PC3 cells, finding estradiol propionate had the same effect as re-expression of DHRS7 in the PC3 cells. However, the drug had no effect on LNCaP cells or PC3 cells re-expressing DHRS7. We speculate that reported beneficial effects of estrogens in late-stage prostate cancer may target a pathway which is only active in cells lacking DHRS7 that have increased nuclear size and propose DHRS7 as a potential biomarker for the likely effectiveness of estrogen-based treatments.

cancer biology↗

bioRxiv2023

A novel MARV glycoprotein-specific antibody with potentials of broad-spectrum neutralization to filovirus

Marburg virus (MARV) is one of the filovirus species that cause deadly hemorrhagic fever in humans, with mortality rates up to 90%. Neutralizing antibodies represent ideal candidates to prevent or treat virus disease. However, no antibody has been approved for MARV treatment to date. In this study, we identified a novel human antibody named AF-03 that targeted MARV glycoprotein (GP). AF-03 possessed a high binding affinity to MARV GP and showed neutralizing and protective activities against the pseudotyped MARV in vitro and in vivo. Epitope identification, including molecular docking and experiment-based analysis of mutated species, revealed that AF-03 recognized the Niemann-Pick C1 (NPC1) binding domain within GP1. Interestingly, we found the neutralizing activity of AF-03 to pseudotyped Ebola viruses (EBOV, SUDV, and BDBV) harboring cleaved GP instead of full-length GP. Furthermore, NPC2-fused AF-03 exhibited neutralizing activity to several filovirus species and EBOV mutants via binding to CI-MPR. In conclusion, this work demonstrates that AF-03 represents a promising therapeutic cargo for filovirus-caused disease.

immunology↗

bioRxiv2023

Haplotype independence contributes to evolvability in the long-term absence of sex in a mite

Some unique asexual species persist over time and contradict the consensus that sex is a prerequisite for long-term evolutionary survival. How they escape the dead-end fate remains enigmatic. Here, we generated a haplotype-resolved genome assembly based on a single individual and collected genomic data from worldwide populations of the parthenogenetic diploid oribatid mite Platynothrus peltifer to identify signatures of persistence without sex. We found that haplotypes diverge independently since the transition to asexuality at least 20 my ago. Multiple lines of evidence indicate disparate evolutionary trajectories between haplotypic blocks. Our findings imply that such haplotypic independence can lead to non-canonical routes of evolvability, helping some species to adapt, diversify and persist for millions of years in the absence of sex. One-Sentence SummaryFunctionally different chromosome sets in an asexual mite species showcase a survival strategy spanning millions of years.

evolutionary biology↗

bioRxiv2023

The Diversity of NLRs in Brassica rapa Pan-genome

The species Brassica rapa is mainly cultivated as a vegetable crop with high economic value. But infectious diseases, such as soft rot disease and clubroot disease can cause severe yield losses. Introducing resistance genes through breeding is an efficient and sustainable way to reduce the susceptibility and improve the yield of crops. Nucleotide-Binding Leucine-Rich Repeat (NLR) genes are the main types of resistance genes. They can recognize pathogen effectors and initiate downstream immune response. However, the intraspecific diversity of NLR genes in Brassica rapa has remained unknown. Based on domain similarity search and machine learning pipeline, we identified 2188 NLRs in 17 accessions of Brassica rapa genomes, which constitute the species-wide pan-NLRome in Brassica rapa. The diversity of the four types of NLR genes are significantly different in the aspects of chromosome location, number stability, integrated domains (IDs), evolutionary trajectory, and positive selection sites. Phylogenetic analyses show TNL-type NLRs whose N terminus contain Toll/interleukin-1 receptor (TIR) domain experienced accession-specific expansion. Moreover, the expanded TNL-type NLRs carry more positively selected amino acid residues which are mainly located on the protein surface based on their 3D structures. These evidences might imply their important biological function in perceiving pathogen effectors. Taken together, our study provides better insights into the diversity and variation of NLR genes in Brassica rapa pangemone, which can facilitate the biofunction assigning, cloning, and subsequent application in breeding programs.

genomics↗

bioRxiv2023

Improved dual-color GRAB sensors for monitoring dopaminergic activity in vivo

Dopamine (DA) plays multiple roles in a wide range of physiological and pathological processes via a vast network of dopaminergic projections. To fully dissect the spatiotemporal dynamics of DA release in both dense and sparsely innervated brain regions, we developed a series of green and red fluorescent GPCR activation-based DA (GRABDA) sensors using a variety of DA receptor subtypes. These sensors have high sensitivity, selectivity, and signal-to-noise properties with subsecond response kinetics and the ability to detect a wide range of DA concentrations. We then used these sensors in freely moving mice to measure both optogenetically evoked and behaviorally relevant DA release while measuring neurochemical signaling in the nucleus accumbens, amygdala, and cortex. Using these sensors, we also detected spatially resolved heterogeneous cortical DA release in mice performing various behaviors. These next-generation GRABDA sensors provide a robust set of tools for imaging dopaminergic activity under a variety of physiological and pathological conditions.

neuroscience↗

bioRxiv2023

Distinguishing the roles of adaptation and demography in gene copy number changes in human populations

Genes with multiple copies are likely to be maintained by stabilizing selection that puts a bound to unlimited expansion of copy number. We designed a model where copy number variation is generated by unequal recombination, which fits well to a number of genes, surveyed in three human populations. Based on this theoretical model and on computer simulations, we were interested in answering the question whether gene copy number distribution in the derived European and Asian populations can be explained by a purely demographic scenario or whether shifts in the distribution are signatures of adaptation. Although copy number distribution in most of the analyzed gene clusters can be explained by a bottleneck as in the out of Africa expansion of homo sapiens 60-10kyrs ago, we identified several candidate genes, for instance AMY1A and PGA3, whose copy numbers are likely to be selected differently among African, Asian and European populations.

evolutionary biology↗