Biology subjects

Ma, R.

Publications and source records attributed to Ma, R..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Basal EFNA3 Facilitates Luminal-Driving Mammary Epithelial Migration and Cancer Metastasis by Promoting OXPHOS

Collective migration is essential for tissue development, repair, and cancer metastasis. However, the mechanisms by which different cell types coordinate to facilitate cohesive movement remain poorly understood. Here, we report distinct migratory behaviors in luminal and basal cells during collective migration of the mammary epithelium. We show that luminal cells are leaders of directional migration. However, basal cells also play a central role in promoting collective migration by producing EFNA3, which targets luminal cells and enhances oxidative phosphorylation and energy production. This promotion of epithelial migration and branching morphogenesis is confirmed in vivo. Importantly, EFNA3 is a prognostic marker for breast cancer metastasis, with high expression correlating with increased metastasis. Conversely, inhibition of EFNA3 significantly slows metastasis. These findings reveal a novel mechanism of epithelial migration that is critical for organogenesis and identify EFNA3 as a potential therapeutic target for cancer metastasis.

developmental biology↗

bioRxiv2024

Mammary Epithelial Migration is EMT-Independent

Epithelial tissues are traditionally considered immobile, requiring epithelial-to-mesenchymal transition (EMT) for individual or collective cell migration as mesenchymal cells. However, recent studies indicate that the mammary epithelium migrates via mechanisms distinct from mesenchymal collectives. Here, we demonstrate that mammary epithelium does not undergo EMT before migration, as evidenced by cellular and molecular characteristics, including EMT marker expression at the mRNA, protein, localization, and transcriptomic levels. Contrary to established models, cell-cell adhesion is not diminished but is required for epithelial migration. Furthermore, Snail1 does not repress cell-cell adhesion but instead plays a pivotal role in directing epithelial migration by regulating processes such as the directional movement of individual cells via Cdc42ep5. Our findings reveal the existence of both stationary and migratory states within the epithelium, providing new insights into how epithelial tissues transition between these states, with broad implications for organogenesis and cancer biology.

cell biology↗

bioRxiv2024

A T6SS DNase effector induces nuclear DNA Damage to trigger apoptosis via activation of the cGAS-STING-TNF axis

In the relentless battle for survival, bacteria have evolved sophisticated weaponry like the Type VI secretion system (T6SS) to not only outcompete rivals but also manipulate host cell processes to their advantage. Apoptosis, a controlled form of programmed cell death without triggering inflammatory responses, is often exploited by pathogens. While many bacterial pathogens are known to induce apoptosis, the role of T6SS effectors in this process remains unexplored. In this study, we discovered that Yersinia pseudotuberculosis (Yptb) utilizes its T6SS to secrete a DNase effector, TkeA, which induces apoptosis in host cells. Mechanistically, the translocation of TkeA into host cells causes nuclear DNA damage, leading to the release of fragmented DNA into the cytoplasm. This, in turn, activates the DNA-sensing cyclic GMP-AMP synthase (cGAS)/stimulator of interferon genes (STING) pathway. The activation of the cGAS-STING pathway by TkeA subsequently triggers apoptosis in host cells via extrinsic pathways, with tumor necrosis factor (TNF) signaling playing a critical role. Additionally, TkeA also mediates interbacterial competition, promoting the colonization of Yptb in mices gut. Our findings reveal that the T6SS-secreted DNase effector TkeA acts as a trans-kingdom effector, enhancing interbacterial competition and inducing apoptosis in host cells by activating the cGAS-STING-TNF axis. This discovery adds a new dimension to the mechanisms employed by bacterial pathogens to manipulate host cell death pathways by using their secretion systems. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/613802v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@1bfd70org.highwire.dtl.DTLVardef@19bfc89org.highwire.dtl.DTLVardef@1e0bf9dorg.highwire.dtl.DTLVardef@4412b9_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTS* Yptb T6SS secretes a trans-kingdom DNase effector TkeA * TkeA degrades bacterial DNA to mediate interbacterial competition * TkeA causes nuclear DNA damage in host cells to induce apoptosis * TkeA induces apoptosis via the cGAS-STING-TNF axis

microbiology↗

bioRxiv2024

Track-A-Worm 2.0: A Software Suite for Quantifying Properties of C. elegans Locomotion, Bending, Sleep, and Action Potentials

Comparative analyses of locomotor behavior and cellular electrical properties between wild-type and mutant C. elegans are crucial for exploring the gene basis of behaviors and the underlying cellular mechanisms. Although many tools have been developed by research labs and companies, their application is often hindered by implementation difficulties or lack of features specifically suited for C. elegans. Track-A-Worm 2.0 addresses these challenges with three key components: WormTracker, SleepTracker, and Action Potential (AP) Analyzer. WormTracker accurately quantifies a comprehensive set of locomotor and body bending metrics, reliably distinguish between the ventral and dorsal sides, continuously tracks the animal using a motorized stage, and seamlessly integrates external devices, such as a light source for optogenetic stimulation. SleepTracker detects and quantifies sleep-like behavior in freely moving animals. AP Analyzer assesses the resting membrane potential, afterhyperpolarization level, and various AP properties, including threshold, amplitude, mid-peak width, rise and decay times, and maximum and minimum slopes. Importantly, it addresses the challenge of AP threshold quantification posed by the absence of a pre-upstroke inflection point. Track-A-Worm 2.0 is potentially a valuable tool for many C. elegans research labs due to its powerful functionality and ease of implementation.

neuroscience↗

bioRxiv2024

P(all-atom) Is Unlocking New Path For Protein Design

We introduce Pallatom, an innovative protein generation model capable of producing protein structures with all-atom coordinates. Pallatom directly learns and models the joint distribution P(structure, seq) by focusing on P(all-atom), effectively addressing the interdependence between sequence and structure in protein generation. To achieve this, we propose a novel network architecture specifically designed for all-atom protein generation. Our model employs a dual-track framework that tokenizes proteins into residue-level and atomic-level representations, integrating them through a multi-layer decoding process with "traversing" representations and recycling mechanism. We also introduce the atom14 representation method, which unifies the description of unknown side-chain coordinates, ensuring high fidelity between the generated all-atom conformation and its physical structure. Experimental results demonstrate that Pallatom excels in key metrics of protein design, including designability, diversity, and novelty, showing significant improvements across the board. Our model not only enhances the accuracy of protein generation but also exhibits excellent sampling efficiency, paving the way for future applications in larger and more complex systems.

bioinformatics↗

bioRxiv2024

Vesiculation pathways in clathrin-mediated endocytosis

During clathrin-mediated endocytosis, a patch of flat plasma membrane is internalized to form a vesicle. In mammalian cells, how the clathrin coat deforms the membrane into a vesicle remains unclear and two main hypotheses have been debated. The "constant area" hypothesis assumes that clathrin molecules initially form a flat lattice on the membrane and deform the membrane by changing its intrinsic curvature while keeping the coating area constant. The alternative "constant curvature" hypothesis assumes that the intrinsic curvature of the clathrin lattice remains constant during the formation of a vesicle while the surface area it covers increases. Previous experimental studies were unable to unambiguously determine which hypothesis is correct. In this paper, we show that these two hypotheses are only two extreme cases of a continuum spectrum if we account for the free energies associated with clathrin assembly and curvature generation. By tracing the negative gradient of the free energy, we define vesiculation pathways in the phase space of the coating area and the intrinsic curvature of clathrin coat. Our results show that, overall, the differences in measurable membrane morphology between the different models are not as big as expected, and the main differences are most salient at the early stage of endocytosis. Furthermore, the best fitting pathway to experimental data is not compatible with the constant-curvature model and resembles a constant-area-like pathway where the coating area initially expands with minor changes in the intrinsic curvature, later followed by a dramatic increase in the intrinsic curvature and minor change in the coating area. Our results also suggest that experimental measurement of the tip radius and the projected area of the clathrin coat will be the key to distinguish between models.

cell biology↗

bioRxiv2024

An Automated High-throughput Affinity Capture-Mass Spectrometry Platform with Data-Independent Acquisition

Affinity capture (AC) combined with mass spectrometry (MS)-based proteomics is highly utilized throughout the drug discovery pipeline to determine small molecule target selectivity and engagement. However, the tedious sample preparation steps and time-consuming MS acquisition process has limited its use in high-throughput format. Here, we report an automated workflow employing biotinylated probes and streptavidin magnetic beads for small molecule target enrichment in 96-well plate format, ending with direct sampling from EvoSep Solid Phase Extraction tips for liquid chromatography (LC)-tandem mass spectrometry (MS/MS) analysis. The streamlined process significantly reduced both overall and hands-on time needed for sample preparation. Additionally, we developed a data-independent acquisition-mass spectrometry (DIA-MS) method to establish an efficient label-free quantitative chemical proteomic kinome profiling workflow. DIA-MS yielded coverage of [~]380 kinases, a >60% increase compared to using a data-dependent acquisition (DDA)-MS method and provided reproducible target profiling of the kinase inhibitor dasatinib. We further showcased the applicability of this AC-MS workflow for assessing the selectivity of two clinical-stage CDK9 inhibitors against [~]250 probe-enriched kinases. Our study here provides a roadmap for efficient target engagement and selectivity profiling in native cell or tissue lysates using AC-MS.

biochemistry↗

bioRxiv2024

Direcred Micro-Ecology Application System: On-site One-step Fermentation Facilitating Microbial Application through Theoretical and Equipment Innovation

Functional microbial agents play a crucial role in various fields such as agriculture, feed fermentation, aquaculture, and environmental protection. However, traditional microbial agents were confronted with critical challenges such as limited shelf-life, reduced activity, and inconsistent efficacy. In this case, we innovatively proposed the concept of Directed Micro-Ecology (DME) and developed its application system, including a core module named DME intelligent fermentor (DME25). Over 40 functional strains, including bacterial strains and fungus strains, were successfully cultured to 10[~]50 x108 CFU/mL within 20[~]48 h and maintained a relatively low contamination rate (<2.5%). Finally, the stability and effectiveness of these DME-fermented strains were validated in different application areas, all of which exhibited perfect functional characteristics. Firstly, the bacillus strains inhibited the progression of wilt disease and significantly improved the growth of tomatoes. Secondly, all tested lactobacillus strains improved the nutrition and quality of fermented feed, complying with feed industry standards. Lastly, the ammonia nitrogen concentration, nitrite concentration of aquaculture water and phosphate concentration, COD of aquaculture tail water were significantly reduced within 1[~]4 d. The successful application of the DME intelligent fermentor in different fields marks a pivotal breakthrough in technological innovation of microbial agents on-site one-step fermentation. This technological advancement opens new avenues for enhancing the stability and effectiveness of microbial agents, infusing powerful impetus to the development of microbial application.

microbiology↗

bioRxiv2024

Screening and assessment of functional variants by regulatory features from epigenomic data in livestock species

BackgroundUnderstanding the functional impact of genetic variants is essential for advancing animal genomics and improving livestock breeding. Variants that disrupt transcription factor (TF) motifs provide a means to assess functional potential, but the lack of TF ChIP-seq data for farm animals presents a challenge. ResultsTo address this, we curated nearly 900 epigenomic datasets from 10 farm animal species and annotated eight regulatory regions to assess how variants affect TF motifs. Over 127 million candidate functional variants were classified into five functional confidence categories across the species. Variants with high confidence were enriched in eQTLs and trait-associated SNPs, showing greater potential to affect gene expression and phenotypes. Incorporating these functional variants into genomic prediction models improved the accuracy of Estimated Breeding Values (EBVs). Active variants also revealed trait-related tissues, and single-cell RNA sequencing (scRNA-seq) identified the cell types most associated with production traits. To facilitate research, we developed the Integrated Functional Mutation (IFmut) platform, enabling users to explore variant functions easily. Our study provides a flexible platform and resource for studying genomic variation in farm animals, setting a new standard for research and breeding strategies. ConclusionThe results indicated that evaluating functional potential by annotating and categorizing variants that interfere with transcription factor motifs can help elucidate changes in gene expression and phenotype. By focusing on high-confidence variants enriched in eQTL and trait-associated SNPs, it improves the accuracy of genomic predictions in research and breeding strategies.

genomics↗

bioRxiv2024

The T-cell niche tunes immune function through modulation of the cytoskeleton and TCR-antigen forces

Obesity is a major public health crisis given its rampant growth and association with an increased risk for cancer. Interestingly, patients with obesity tend to have an increased tumor burden and decreased T-cell function. It remains unclear how obesity compromises T-cell mediated immunity. To address this question, we modeled the adipocyte niche using the secretome released from adipocytes as well as the niche of stromal cells and investigated how these factors modulated T-cell function. We found that the secretomes altered antigen-specific T-cell receptor (TCR) triggering and activation. RNA-sequencing analysis identified thousands of gene targets modulated by the secretome including those associated with cytoskeletal regulation and actin polymerization. We next used molecular force probes to show that T-cells exposed to the adipocyte niche display dampened force transmission to the TCR-antigen complex and conversely, stromal cell secreted factors lead to significantly enhanced TCR forces. These results were then validated in diet-induced obese mice. Importantly, secretome-mediated TCR force modulation mirrored the changes in T-cell functional responses in human T-cells using the FDA-approved immunotherapy, blinatumomab. Thus, this work shows that the adipocyte niche contributes to T-cell dysfunction through cytoskeletal modulation and reduces TCR triggering by dampening TCR forces consistent with the mechanosensor model of T-cell activation.

bioengineering↗

bioRxiv2024

SPRITE: improving spatial gene expression imputation with gene and cell networks

Spatially resolved single-cell transcriptomics have provided unprecedented insights into gene expression in situ, particularly in the context of cell interactions or organization of tissues. However, current technologies for profiling spatial gene expression at single-cell resolution are generally limited to the measurement of a small number of genes. To address this limitation, several algorithms have been developed to impute or predict the expression of additional genes that were not present in the measured gene panel. Current algorithms do not leverage the rich spatial and gene relational information in spatial transcriptomics. To improve spatial gene expression predictions, we introduce SPRITE (Spatial Propagation and Reinforcement of Imputed Transcript Expression) as a meta-algorithm that processes predictions obtained from existing methods by propagating information across gene correlation networks and spatial neighborhood graphs. SPRITE improves spatial gene expression predictions across multiple spatial transcriptomics datasets. Furthermore, SPRITE predicted spatial gene expression leads to improved clustering, visualization, and classification of cells. SPRITE is available as a software package and can be used in spatial transcriptomics data analysis to improve inferences based on predicted gene expression.

bioinformatics↗

bioRxiv2023

Metabolite Fingerprinting for Phenotypic Screening by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry

The adoption of mass spectrometry for high-throughput screening in drug discovery has become increasingly prevalent and has enabled label-free screening against diverse targets. Cellular assays for phenotypic screening, however, are primarily conducted by microscopy as there remain many challenges associated with conducting phenotypic screens via ultra-high throughput mass spectrometry. Following a simple on-plate extraction, infrared matrix assisted laser desorption electrospray ionization (IR-MALDESI) was employed to directly sample the cell lysate at a speed of one second per sample. A549 cells were treated with compounds identified as hits in literature including a recently reported glutaminase cellular screen. Among the test compounds, there were confirmed glutaminase inhibitors, proposed nuisance compounds, and cell-active but enzyme-inactive compounds. Filtered data were further processed in R for dimensionality reduction and unsupervised clustering. Though it was observed that all compounds affected the intracellular conversion of glutamine to glutamate, there were clear metabolic differences between the biochemically active compounds and the off-target hits. Moreover, two nuisance compounds were observed to cluster separately from the confirmed glutaminase inhibitors in the observed metabolite fingerprints. This proof-of-concept work establishes a complete workflow that enables highthroughput mass spectrometry-based phenotypic screening. The methods proposed herein, at the throughput enabled by IR-MALDESI, could offer a new avenue for discovery of novel drugs.

cell biology↗

bioRxiv2023

A time-resolved multi-omics atlas of transcriptional regulation in response to high-altitude hypoxia across whole-body tissues

High-altitude hypoxia acclimatization requires whole-body physiological regulation in highland immigrants, but the underlying genetic mechanism has not been clarified. Here we used sheep as an animal model for plain-to-plateau transplantation. We generated multi-omics data including time-resolved bulk RNA-Seq, ATAC-Seq and single-cell RNA-Seq from multiple tissues as well as phenotypic data from 20 bio-indicators. We characterized transcriptional changes of all genes in each tissue, and examined multi-tissue temporal dynamics and transcriptional interactions among genes. In particular, we identified critical functional genes regulating the short response to hypoxia in each tissue (e.g., PARG in the cerebellum and HMOX1 in the colon). We further identified TAD-constrained cis-regulatory elements, which suppressed the transcriptional activity of most genes under hypoxia. Phenotypic and transcriptional evidence indicated that antenatal hypoxia could improve hypoxia tolerance in offspring. Furthermore, we provided time-series expression data of candidate genes associated with human mountain sickness (e.g., BMPR2) and high-altitude adaptation (e.g., HIF1A). Our study provides valuable resources and insights for future hypoxia-related studies in mammals.

genetics↗

bioRxiv2023

High-throughput single-nucleus hybrid sequencing reveals genome-transcriptome correlations in cancer

To deepen our understanding of cancer heterogeneity and uncover the dynamic interactions of tumor and host cells, we introduce hybrid BAG-seq: a high-throughput, multi-omic method that simultaneously captures DNA and RNA from tens of thousands of individual single nuclei. This method provides dual molecular layer information: DNA to distinguish tumor from stroma, identify tumor subclones, and detect mutant stromal sub-populations; and RNA to characterize distinct cell types, cell states, and signatures of aberrant expression. Additionally, we developed a suite of analysis tools to illuminate cluster phylogeny and connections between DNA identity and RNA expression. We applied this hybrid protocol to 65,499 single nuclei from samples of five uterine cancer patients, and validated the clustering using RNA-only and DNA-only protocols on 34,651 and 21,432 nuclei, respectively, from the same tissues. Multiple tumor genome or expression clusters were often present within a patient, with different tumor clones projecting into distinct or shared expression states, demonstrating nearly all possible genome-transcriptome correlations across the cohort. While tumor expression profiles were highly unique to each patient, the stromal cell types generally recurred across samples, but certain patients and tissues exhibited unique stromal sub-types characterized by aberrant expression. Moreover, we identified mutant stroma in various cell types from several patients with a significant loss of the X-chromosome. This study reveals the complex landscape of genome and transcriptome interactions at the resolution of single nuclei, providing new insights into mutant stroma and tumor heterogeneity.

genomics↗

bioRxiv2023

Force-induced site-specific enzymatic cleavage probes reveal that serial mechanical engagement boosts T cell activation

The surface of T cells is studded with T cell receptors (TCRs) that are used to scan target cells to identify peptide-major histo-compatibility complexes (pMHCs) signatures of viral infection or cancerous mutation. It is now established that the TCR-pMHC complex is highly transient and experiences mechanical forces that augment the fidelity of T cell activation. An important question in this area pertains to the role of force duration in immune activation. Herein, we report the development of force probes that autonomously terminate tension within a time window following mechanical triggering. Force-induced site-specific enzymatic cleavage (FUSE) probes tune tension duration by controlling the rate of a force-triggered endonuclease hydrolysis reaction. This new capability provides a method to study how accumulated force duration contributes to T cell activation. We screened DNA sequences and identified FUSE probes that disrupt mechanical interactions with F >7.1 piconewtons (pN) between TCRs and pMHCs. Force lifetimes ({tau}F) are tunable from tens of min down to 1.9 min. T cells challenged with FUSE probes presenting cognate antigens with {tau}F of 1.9 min demonstrated dampened markers of early activation, thus demonstrating that repeated mechanical sampling boosts TCR activation. Repeated mechanical sampling F >7.1 pN was found to be particularly critical at lower pMHC antigen densities, wherein the T cell activation declined by 23% with {tau}F of 1.9 min. FUSE probes with F >17.0 pN response showed weaker influence on T cell triggering further showing that TCR-pMHC with F >17.0 pN are less frequent compared to F >7.1 pN. Taken together, FUSE probes allow a new strategy to investigate the role of force dynamics in mechanotransduction broadly and specifically suggest a model of serial mechanical engagement in antigen recognition.

biophysics↗

bioRxiv2023

Is your data alignable? Principled and interpretable alignability testing and integration of single-cell data

Single-cell data integration can provide a comprehensive molecular view of cells, and many algorithms have been developed to remove unwanted technical or biological variations and integrate heterogeneous single-cell datasets. Despite their wide usage, existing methods suffer from several fundamental limitations. In particular, we lack a rigorous statistical test for whether two high-dimensional single-cell datasets are alignable (and therefore should even be aligned). Moreover, popular methods can substantially distort the data during alignment, making the aligned data and downstream analysis difficult to interpret. To overcome these limitations, we present a spectral manifold alignment and inference (SMAI) framework, which enables principled and interpretable alignability testing and structure-preserving integration of single-cell data. SMAI provides a statistical test to robustly determine the alignability between datasets to avoid misleading inference, and is justified by high-dimensional statistical theory. On a diverse range of real and simulated benchmark datasets, it outperforms commonly used alignment methods. Moreover, we show that SMAI improves various downstream analyses such as identification of differentially expressed genes and imputation of single-cell spatial transcriptomics, providing further biological insights. SMAIs interpretability also enables quantification and a deeper understanding of the sources of technical confounders in single-cell data.

bioinformatics↗

bioRxiv2023

Tandemly duplicated MYB genes specifically in the Phaseoleae lineage are functionally diverged in the regulation of anthocyanin biosynthesis

Gene duplications have long been recognized as a driving force in the evolution of genes, giving rise to novel functions. The soybean genome is characterized by a large extent of duplicated genes. However, the extent and mechanisms of functional divergence among these duplicated genes in soybean remain poorly understood. In this study, we revealed that tandem duplication of MYB genes, which occurred specifically in the Phaseoleae lineage, exhibited a stronger purifying selection in soybean compared to common bean. To gain insights into the diverse functions of these MYB genes in anthocyanin biosynthesis, we examined the expression, transcriptional activity, metabolite, and evolutionary history of four MYB genes (GmMYBA5, GmMYBA2, GmMYBA1 and Glyma.09g235000), which were presumably generated by tandem duplication in soybean. Our data revealed that Glyma.09g235000 had become a pseudogene, while the remaining three MYB genes exhibited strong transcriptional activation activity and promoted anthocyanin biosynthesis in different soybean tissues. Furthermore, GmMYBA5 produced distinct compounds in Nicotiana benthamiana leaves compared to GmMYBA2 and GmMYBA1 due to variations in their DNA binding domains. The lower expression of anthocyanin related genes in GmMYBA5 resulted in lower levels of anthocyanins compared to GmMYBA2 and GmMYBA1. Metabolomics analysis further demonstrated the diverse and differential downstream metabolites, suggesting their functional divergence in metabolites following gene duplication. Together, our data provided evidence of functional divergence within the MYB gene cluster following tandem duplication, which shed light on the potential evolutionary direction of gene duplications during legume evolution.

evolutionary biology↗

bioRxiv2023

Distinct Neurodevelopmental Patterns and Intermediate Integration-Based Predictive Modeling in Autism Spectral Disorder

Autism Spectrum Disorder (ASD) is known to exhibit a more rapid expansion in brain structure during the early years of life compared to typically developing children (TD). This is of utmost importance in understanding atypical brain development and forecasting the onset of ASD. However, the precise age-related cortical changes (trajectories) that could pinpoint atypical brain development in ASD remain largely unknown. In this study, we characterize the distinct developmental patterns of cortical morphology in individuals with ASD, investigate the important neural biomarkers for ASD diagnostics, and propose a deep-learning workflow that combined graph convolutional networks with low-rank multi-model tensor fusion (LMFGCN) for ASD prediction. Our findings reveal that the constituents of gray matter volume (GV), cortical thickness (CT), and surface area (SA) exhibit separable developmental trajectories in ASD. Furthermore, we identify regional differences in CT and SA that underscore the separable brain developmental trajectories, both of which contribute to changes in GV. Our study also demonstrates that LMFGCN, an end-to-end deep-learning model with intermediate integrative approach, outperforms early and late integration methods and other state-of-the-art models in ASD classification. Overall, our results highlight the importance of distinguishing between cortical SA and CT for understanding ASD pathobiology, particularly during the early brain overgrowth period, and demonstrate the potential utility of LMFGCN in ASD classification.

neuroscience↗