Biology subjects

Yin, M.

Publications and source records attributed to Yin, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Ophiostomatalean fungi associated with bark beetles infesting Pinus koraiensis, including the description of Ceratocystiopsis fushunensis sp. nov. in China

Fungi of Ophiostomatales (Sordariomycetes, Ascomycota) always have a symbiotic relationship with bark beetles (Coleoptera: Scolytinae). In this study, we investigated the fungi associated with Cryphalus piceae and Hylastes sp in Fushun. Based on the four gene fragments of TUB, ITS, LSU, and TEF and morphological characteristics, 206 strains of Ophiostomatales were identified to be distributed in 21 taxa; these included an undescribed taxon. Here, we described it as Ceratocystiopsis fushunensis sp. nov. The results of this study provided valuable information on the relationship between fungi and bark beetles.

microbiology↗

bioRxiv2024

Two new species of Graphium (Microascales, Ascomycota) associated with pine-infesting bark beetles in China

Graphium is a genus of fungi that falls under the order Microascales of Ascomycota. Some species in this genus can establish a unique symbiotic relationship with the pine-infesting bark beetles, while others are typically found in wood or soil habitats. To comprehensively investigate the diversity of species of these fungi, recent field trips were conducted in seven provinces (Fujian, Guangdong, Guizhou, Guangxi, Liaoning, Shaanxi, and Shandong) in China. 96 pure isolates of Graphium were obtained by sequences from 361 samples. Nineteen representative strains were carefully selected to generate sequencing data from four gene regions (ITS, LSU, EF1A and TUBB), then used to construct phylogenetic trees for the genus. The results revealed the discovery of two new species, namely G. armandii sp. nov. and G. massoniana sp. nov., and G. pseudoumiticum was the most common species in various pine hosts.

microbiology↗

bioRxiv2024

An in vivo screen identifies NAT10 as a master regulator of brain metastasis

Metastasis is the major cause of cancer-related deaths. Emerging evidence has shown that epigenetic regulation plays a fundamental role in cancer metastasis. To better understand the epigenetic regulation of metastasis, we conducted an in vivo shRNA screen for vulnerabilities of brain metastasis and identified N-acetyltransferase 10 (NAT10) as a driver of brain metastasis. Knockdown of NAT10 significantly restrains cancer cell proliferation and migration in vitro, and tumor growth and brain metastasis in vivo. Structure-function analysis of NAT10 showed that its poorly characterized RNA helicase domain is critical for breast cancer cell growth in vitro, while its N-acetyltransferase domain is essential for primary tumor growth and brain metastasis in vivo. Integrative transcriptomic and proteomic analyses revealed key downstream effectors of NAT10, including PHGDH and PSAT1, two catalyzing enzymes for serine biosynthesis implicated in brain metastasis, and HSPA5, known to promote metastasis. We found that distant metastases of breast cancer, especially brain metastases express higher levels of NAT10, PHGDH, PSAT1, and HSPA5. Silencing PHGDH/PSAT1 or HSPA5 in metastatic breast cancer cells inhibits their ability to grow in the serine/glycine-limited condition or migrate, respectively, phenocopying the effects of NAT10 depletion. Moreover, NAT10 promotes the expression of PHGDH, PSAT1, and HSPA5 in its RNA helicase-dependent manner. These findings establish NAT10 as a master regulator of brain metastasis and shed light on the biological functions of its RNA helicase domain, nominating NAT10 as a target for treating metastatic diseases.

cancer biology↗

bioRxiv2024

Multi-Modal CLIP-Informed Protein Editing

AO_SCPLOWBSTRACTC_SCPLOWProteins govern most biological functions essential for life, but achieving controllable protein discovery and optimization remains challenging. Recently, machine learning-assisted protein editing (MLPE) has shown promise in accelerating optimization cycles and reducing experimental workloads. However, current methods struggle with the vast combinatorial space of potential protein edits and cannot explicitly conduct protein editing using biotext instructions, limiting their interactivity with human feedback. To fill these gaps, we propose a novel method called ProtET for efficient CLIP-informed protein editing through multi-modality learning. Our approach comprises two stages: in the pretraining stage, contrastive learning aligns protein-biotext representations encoded by two large language models (LLMs), respectively. Subsequently, during the protein editing stage, the fused features from editing instruction texts and original protein sequences serve as the final editing condition for generating target protein sequences. Comprehensive experiments demonstrated the superiority of ProtET in editing proteins to enhance human-expected functionality across multiple attribute domains, including enzyme catalytic activity, protein stability and antibody specific binding ability. And ProtET improves the state-of-the-art results by a large margin, leading to significant stability improvements of 16.67% and 16.90%. This capability positions ProtET to advance real-world artificial protein editing, potentially addressing unmet academic, industrial, and clinical needs.

bioinformatics↗

bioRxiv2024

Capturing gait parameters during asymmetric overground walking using ultra-wideband radars: A preliminary study

This study investigates the deployability of commercially available impulse-radio ultra-wideband radar (UWB) sensors, in accurately detecting and analysing gait patterns during asymmetric overground locomotion. An adjustable knee brace was fitted on the right knee of 10 able-bodied participants, in five different confinement angles, during a 6-meter walking task to simulate asymmetric walking patterns. A computationally efficient signal processing framework extracts seven spatiotemporal gait parameters from six UWB radar signals, based on their joint Range-Doppler-Time representation. Gait asymmetry was quantified using primarily the symmetry ratio metric of step times. Validated against the gold standard motion capture system, radar-based gait parameters were estimated with 88.2-98.8% accuracy for all settings. By capturing step time symmetry ratios with 95.6{+/-}2.8% accuracy, the radar system can effectively distinguish between different gait impairment levels.

bioengineering↗

bioRxiv2024

Dissecting the cis-regulatory syntax of transcription initiation with deep learning

Despite extensive characterization of mammalian Pol II transcription, the DNA sequence determinants of transcription initiation at a third of human promoters and most enhancers remain poorly understood. We trained and interpreted a neural network called ProCapNet that accurately models base-resolution initiation profiles from PRO-cap experiments using local DNA sequence. ProCapNet learns sequence motifs with distinct effects on initiation rates and TSS positioning and uncovers context-specific cryptic initiator elements intertwined within other TF motifs. ProCapNet annotates predictive motifs in nearly all actively transcribed regulatory elements across multiple cell-lines, revealing a shared cis-regulatory logic across promoters and enhancers and a highly epistatic sequence syntax of cooperative and competitive motif interactions. ProCapNet models of steady-state RAMPAGE profiles distill initiation signals on par with models trained directly on PRO-cap profiles. ProCapNet learns a largely cell-type-agnostic cis-regulatory code of initiation complementing sequence drivers of cell-type-specific chromatin state critical for accurate prediction of cell-type-specific transcription initiation.

genomics↗

bioRxiv2024

TRAPT: A multi-stage fused deep learning framework for transcriptional regulators prediction via integrating large-scale epigenomic data

It is a challenging task to identify functional transcriptional regulators, which control expression of gene sets via regulatory elements and epigenomic signals, involving context-specific studies such as development and diseases. Integrating large-scale multi-omics epigenomic data enables the elucidation of the complex epigenomic control patterns of regulatory elements and regulators. Here, we propose TRAPT, a multi-modality deep learning framework that predicts functional transcriptional regulators from a queried gene set by integrating large-scale multi-omics epigenomic data, including histone modifications, ATAC-seq and TR-ChIP-seq. We design two-stage self-knowledge distillation model to learn nonlinear embedded representation of upstream and downstream regulatory element activity, and merge multi-modality epigenomic features from TR and the queried gene sets for inferring regulator activity. Experimental results on 1072 TR-related datasets demonstrate that TRAPT outperforms current state-of-the-art methods in predicting transcriptional regulators, especially in the prediction of transcription co-factors and chromatin regulators. Additionally, we have successfully identified key transcriptional regulators associated with the disease, genetic variation, cell fate decisions, and tissues. Our method provides an innovative perspective for integrating epigenomic data and has the potential to significantly assist researchers in deepening their understanding of gene expression regulation mechanisms.

bioinformatics↗

bioRxiv2024

Force-Enhanced Sensitive Detection of New DNA-Interactive Agents from Microorganisms at the Single-Molecule Level

The discovery of microbial-derived DNA-interacting agents, which hold broad therapeutic potential, is inherently challenging due to the limited sensitivity and specificity of conventional methodologies. Our study introduces a pioneering application of single-molecule stretching assay (SMSA) in natural product chemistry to identify DNA-intercalating agents directly from microbial cultures or extracts. We demonstrate that mechanical force can enhance sensitivity by increasing both the binding affinity Ka and the quantity of ligands bound. The changes induced by intercalators in the counter length and overstretching transition of dsDNA yield a distinctive and highly specific signature indicative of DNA intercalative binding, thereby enabling straightforward detection of DNA intercalators even in trace amounts from microbial cultures. This methodology eliminates the need for extensive large-scale fermentation and purification processes, thus offering a more streamlined approach to DNA-intercalating natural product discovery. By applying SMSA to 17 microorganisms, we identified two DNA intercalator-producing strains: Streptomyces tanashiensis and Talaromyces funiculosus. Subsequently, three DNA intercalators, namely medermycin, kalafungin, and ligustrone B, were isolated and characterized. Among them, medermycin and kalafungin showed significant inhibitory effects against HCT-116 cancer cells, with IC50 values of 52 {+/-} 6 nM and 70 {+/-} 7 nM, respectively.

biophysics↗

bioRxiv2024

A large-scale cancer-specific protein-DNA interaction network

Cancer development and progression are generally associated with dysregulation of gene expression, often resulting from changes in transcription factor (TF) sequence or expression. Identifying key TFs involved in cancer gene regulation provides a framework for potential new therapeutics. This study presents a large-scale cancer gene TF-DNA interaction network as well as an extensive promoter clone resource for future studies. Most highly connected TFs do not show a preference for binding to promoters of genes associated with either good or poor cancer prognosis, suggesting that emerging strategies aimed at shifting gene expression balance between these two prognostic groups may be inherently complex. However, we identified potential for oncogene targeted therapeutics, with half of the tested oncogenes being potentially repressed by influencing specific activator or bifunctional TFs. Finally, we investigate the role of intrinsically disordered regions within the key cancer-related TF estrogen receptor [a] (ESR1) on DNA binding and transcriptional activity, and found that these regions can have complex trade-offs in TF function. Altogether, our study not only broadens our knowledge of TFs involved in the cancer gene regulatory network but also provides a valuable resource for future studies, laying a foundation for potential therapeutic strategies targeting TFs in cancer.

systems biology↗

bioRxiv2024

Defining cell type-specific immune responses in a mouse model of allergic contact dermatitis by single-cell transcriptomics

Allergic contact dermatitis (ACD), a prevalent inflammatory skin disease, is elicited upon repeated skin contact with protein-reactive chemicals through a complex and poorly characterized cellular network between immune cells and skin resident cells. Here, single-cell transcriptomic analysis of the murine hapten-elicited model of ACD reveals that upon elicitation of ACD, infiltrated CD4+ or CD8+ lymphocytes were primarily the IFN{gamma}-producing type 1 central memory phenotype. In contrast, type 2 cytokines (IL4 and IL13) were dominantly expressed by basophils, IL17A was primarily expressed by {delta}{gamma} T cells, and IL1{beta} was identified as the primary cytokine expressed by activated neutrophils/monocytes and macrophages. Furthermore, analysis of skin resident cells identified a sub-cluster of dermal fibroblasts with preadipocyte signature as a prominent target for IFN{gamma}+ lymphocytes and dermal source for key T cell chemokines CXCL9/10. IFN{gamma} treatment shifted dermal fibroblasts from collagen-producing to CXCL9/10-producing, which promoted T cell polarization toward the type-1 phenotype through a CXCR3-dependent mechanism. Furthermore, targeted deletion of Ifngr1 in dermal fibroblasts in mice reduced Cxcl9/10 expression, dermal infiltration of CD8+ T cell, and alleviated ACD inflammation in mice. Finally, we showed that IFN{gamma}+ CD8+ T cells and CXCL10-producing dermal fibroblasts co-enriched in the dermis of human ACD skin. Together, our results define the cell type-specific immune responses in ACD, and recognize an indispensable role of dermal fibroblasts in shaping the development of type-1 skin inflammation through the IFNGR-CXCR3 signaling circuit during ACD pathogenesis.

immunology↗

bioRxiv2024

Structural Insights into the DNA-Binding Mechanism of BCL11A: The Integral Role of ZnF6

The transcription factor BCL11A is a critical regulator of the switch from fetal hemoglobin (HbF: 2{gamma}2) to adult hemoglobin (HbA: 2{beta}2) during development. BCL11A binds at a cognate recognition site (TGACCA) in the {gamma}-globin gene promoter and represses its expression. DNA-binding is mediated by a triple zinc finger domain, designated ZnF456. Here, we report comprehensive investigation of ZnF456, leveraging X-ray crystallography and NMR to determine the structures in both the presence and absence of DNA. We delve into the dynamics and mode of interaction with DNA. Moreover, we discovered that the last zinc finger of BCL11A (ZnF6) plays a special role in DNA binding and {gamma}-globin gene repression. Our findings help account for some rare {gamma}-globin gene promoter mutations that perturb BCL11A binding and lead to increased HbF in adults (hereditary persistence of fetal hemoglobin). Comprehending the DNA binding mechanism of BCL11A opens avenues for the strategic, structure-based design of novel therapeutics targeting sickle cell disease and {beta}-thalassemia.

molecular biology↗

bioRxiv2023

Liver Protects Cytoarchitecture, Neuron Viability and Electrocortical Activity in Post-Cardiac Arrest Brain Injury

BACKGROUNDBrain injury is the major reason for patient deaths in victims who survive after cardiac arrest. Clinical studies have shown that the presence of hypoxic hepatitis and pre-cardiac arrest liver disease is associated with increased mortality and inferior neurological recovery. However, how the liver might impact the pathogenesis of post-cardiac arrest is still unknown. METHODSAn in vivo global cerebral ischemia model was established to assess how simultaneous liver ischemia affected the recovery of brain ischemic injury. In addition, an ex vivo brain normothermic machine perfusion (NMP) model was established to evaluate how addition of a functioning liver might impact the circulation, cytoarchitecture, neuron viability and electrocortical activity of the reperfused brain post-cardiac arrest. RESULTSIn the in vivo model, we observed a larger infarct area in the frontal lobe, elevated tissue injury scores in the CA1 region, as well as increased intravascular immune cell adhesion in the reperfused brains with hepatic ischemia, compared to those without simultaneous hepatic ischemia. The results of the ex vivo model demonstrated that the addition of a functioning liver to the brain NMP circuit significantly reduced post-cardiac arrest brain injury, increased neuronal viability and improved electrocortical activity. Furthermore, we observed significant alterations in gene expressions and metabolites in the presence or absence of hepatic ischemia. CONCLUSIONSOur research highlights the crucial role of the liver in the pathogenesis of post-cardiac arrest brain injury. These findings shed lights on a cardio-pulmonary-hepatic brain resuscitation strategy for patients with cardiac arrest.

neuroscience↗

bioRxiv2023

Chemotherapeutic regulation of the ROS/MondoA-dependent TXNIP/GDF15 axis; and derivation of a new organoid metric as a predictive biomarker

Chemotherapy, the standard of care treatment for cancer patients with advanced disease, has been increasingly recognised to activate host immune responses to produce durable outcomes. Here, in colorectal adenocarcinoma (CRC) we identify chemotherapy-induced Thioredoxin Interacting Protein (TXNIP), a MondoA-dependent tumor suppressor gene, as a negative regulator of Growth/Differentiation Factor 15 (GDF15). GDF15 is a negative prognostic factor in CRC and promotes the differentiation of regulatory T cells (Tregs), through CD48 ligation. Intriguingly, multiple models including patient-derived tumor organoids demonstrate that loss of TXNIP/GDF15 axis functionality is associated with advanced disease or chemotherapeutic resistance, with transcriptomic or proteomic GDF15/TXNIP ratios showing potential as a prognostic biomarker. These findings illustrate a potentially common pathway where chemotherapy-induced epithelial stress drives local immune remodelling for patient benefit, with disruption of this pathway seen in refractory or advanced cases.

cancer biology↗

bioRxiv2023

Network-based molecular subtyping of acral melanoma

Acral melanoma is more biologically aggressive with a worse prognosis compared with other melanoma subtypes. However, the molecular basis underlying the biological and clinical behavior of this cancer is still unclear. Here, using the combination of multi-omics data analysis and network-based disease gene prediction algorithm, we first demonstrate the existence of two acral melanoma subtypes which greatly differed in clinical performance, cellular and molecular mechanisms, and discovered a biomarker panel (EREG, VSIG4, FCGR3A, RAB20) that accurately distinguished these two subtypes with the AUC of 0.946, which has been verified by clinical samples. Subtype I has thinner Breslow with a better prognosis. On the contrary, subtype II is a high-risk subtype that is easier to invade the dermis. We further analyzes the intrinsic biological mechanism of the two subtypes from the cellular level, and reveals the important role of macrophages subgroups in the molecular typing of acral melanoma. Feature genes of subtype I are enriched in FCN1+ macrophages that promote inflammatory and immune responses. In contrast, feature genes of subtype II are enriched in SPP1+ macrophages which ha the greatest impact on tumor cells. The identification of the two subtypes opens up important biological and clinical perspectives for acral melanoma.

bioinformatics↗

bioRxiv2022

Not just with the natives, but phylogenetic relationship between stages of the invasion process determines invasion success of alien plant species

Darwin proposed two alternate hypotheses on the invasion success of alien plant species based on their close or distant phylogenetic relationship with the natives. Here we tested these hypotheses along the invasion process at large spatio-temporal scale. Using two abundance-based phylogenetic metrics for the native and alien flora of China, our study showed that invasion success of alien plant species is influenced by the phylogenetic relationship with native and alien species of different invasion stages. Phylogenetic similarity with the native species helps the alien ones to introduce and naturalize, but phylogenetic dissimilarity with the natives facilitates invasion success. The co-occurrence of invasive and naturalized aliens also formed more clustered assemblages, showed specialized responses to environmental stress, and provided temporal stability to the phylogenetic measures. The native-alien phylogenetic relationship is dynamic across spatial, environmental, and taxonomic scales. Therefore, assessing Darwins naturalization conundrum at different gradients of community assembly process is important.

ecology↗

bioRxiv2022

Widespread perturbation of ETS factor binding sites in cancer

Although >90% of somatic mutations reside in non-coding regions, few have been reported as cancer drivers. To predict driver non-coding variants (NCVs), we present a novel transcription factor (TF)-aware burden test (TFA-BT) based on a model of coherent TF function in promoters. We applied our TFA-BT to NCVs from the Pan-Cancer Analysis of Whole Genomes cohort and predicted 2,555 driver NCVs in the promoters of 813 genes across 20 cancer-types. These genes are enriched in cancer-related gene ontologies, essential genes, and genes associated with cancer prognosis. We found that 765 candidate driver NCVs alter transcriptional activity, 510 lead to differential binding of TF-cofactor regulatory complexes, and that they primarily impact the binding of ETS factors. Finally, we show that different NCVs within a promoter often affect transcriptional activity through shared mechanisms. Our integrated computational and experimental approach shows that cancer NCVs are widespread and that ETS factors are commonly disrupted.

cancer biology↗

bioRxiv2022

Why is Babesia not killed by artemisinin like Plasmodium?

Babesia spp. are intraerythrocytic apicomplexan organisms digesting hemoglobin similar to intraerythrocytic Plasmodium spp. However, unlike Plasmodium spp., Babesia spp. are not sensitive to artemisinin, The difference between Babesia genomes and Plasmodium genomes revealed that smaller Babesia genomes lack numerous genes, especially haem synthesis-related genes. Single-cell sequencing analysis showed that different groups of B. microti with expressed pentose phosphate pathway (PPP)-related, DNA replication-related, antioxidation-related, glycolysis-related, and glutathione-related genes were not as sensitive to artemether as P. yoelii 17XNL. Especially, PPP-related, DNA replication-related, and glutathione-related genes were inactively expressed compared with P. yoelii 17XNL. Adding iron supply in vivo can promote the reproduction of B. microti. These results suggest that Babesia spp. lack a similar mechanism to that in malaria parasites, by which haem or iron in hemoglobin is utilized, but it likely leads to their insensitivity to artemisinin in turn. Author summaryBabesia and Plasmodium are similar in many ways, from morphology to life history. In particular, both ingest and break down hemoglobin. However, compared with Plasmodium, Babesia cannot form hemozoin with less pathogenicity and insensitivity to artemisinin. Recent studies suggest that artemisinin can kill malaria parasites through free-radical and iron-capture effects, indicating that iron and haem play a key role in the sensitivity of malaria parasites to artemisinin. The Babesia genome is smaller and does not contain haem synthesis-related genes, indicating low requirements and utilization of haem and iron (HI). Moreover, we found that the expression of PPP-related and DNA replication-related genes is not active, distinctly different from malaria parasites. However, adding iron supply in vivo can increase the infection rate of B. microti. Therefore, we hypothesized that Babesia lacks mechanisms for the efficient utilization of HI, resulting in low requirements for HI, and therefore insensitivity to artemisinin.

evolutionary biology↗

bioRxiv2022

Analysis of the mechanism of castor tolerance to Cd metal based on proteomics and metabolomics

The pollution of soil with heavy metals is an increasingly serious worldwide problem, and cadmium (Cd) has attracted attention because of its high toxicity to almost all plants. Since castor tolerates the accumulation of heavy metals, it has the potential for heavy metal soil remediation. We studied the mechanism of the tolerance of castor to Cd stress treatments at three doses: 300 mg/L, 700 mg/L, and 1,000 mg/L. Our research provides new ideas for revealing the defense and detoxification mechanisms of Cd-stressed castor. By combining the results of physiology, differential proteomics and comparative metabolomics, we conducted a comprehensive analysis of the networks that regulate the response of castor to Cd stress. The physiological results mainly emphasize the super-sensitive responses of castor plant roots to Cd stress and the effects of Cd stress on plants antioxidant system, ATP synthesis and ion homeostasis. We confirmed these results at the protein and metabolite levels. At the same time, proteomics and metabolomics show that castor plants mainly block the root systems absorption of Cd2+ by enhancing the strength of the cell wall, and inducing programmed cell death in response to the three different doses of Cd stress. In addition, the plasma membrane ATPase encoding gene (RcHA4), which was significantly upregulated in our differential proteomics and RT-qPCR studies, was transgenically overexpressed in wild type Arabidopsis thaliana for functional verification. The results indicated that this gene plays an important role in improving plant Cd tolerance.

molecular biology↗