Biology subjects

Chen, M.

Publications and source records attributed to Chen, M..

At least 235 records · Page 13Linked to original sources

bioRxiv2024

Cholecystokinin modulates age-dependent Thalamocortical Neuroplasticity

The thalamocortical pathways exhibit neuroplasticity not only during the critical period but also in adulthood. In this study, we investigated how cholecystokinin (CCK) modulates age-dependent thalamocortical plasticity. Our findings demonstrated that CCK is expressed in thalamocortical neurons and that high-frequency stimulation (HFS) of the thalamocortical pathway triggers the release of CCK in auditory cortex (ACx), as detected by a CCK sensor. HFS of the medial geniculate body (MGB) induced thalamocortical long-term potentiation (LTP) in wild-type young adult mice. However, knockdown of Cck expression in MGB neurons or blockade of the CCK-B receptor (CCKBR) in the ACx abolished HFS-induced LTP. Interestingly, this LTP could not be elicited in juvenile (3-week-old) or aged mice (over 18-month-old) due to distinct mechanisms: the absence of CCKBR in juveniles and the inability to release CCK in aged mice. Notably, exogenous administration of CCK into the ACx rescued LTP in aged mice and significantly improved frequency discrimination. These findings highlight the potential of CCK as a therapeutic intervention for ameliorating neuroplasticity deficits associated with thalamocortical connectivity.

neuroscience↗

bioRxiv2024

Genetic diversity analysis of main agronomic traits and ISSR markers in 35 ornamental rape germplasm resources

Rape (Brassica napus L.) is a major oil crop in our country, valued for its oil and ornamental uses. This study analyzed 35 ornamental rape germplasm resources from different origins to examine differences in agronomic traits and molecular markers. Nine agronomic traits were assessed in the field for variability, correlation, principal component analysis, and cluster analysis. Genetic diversity was analyzed using microsatellite (ISSR) markers and the unweighted pair group method with arithmetic mean (UPGMA). Our findings revealed a notable average coefficient of variation of 22.59% across the nine agronomic traits, with flower color exhibiting the highest variability and corolla width the least. The observed range of variation spanned from 9.24% to 83.38%, the correlation among these traits was generally low, with a mere 13.9% demonstrating significant correlations. The four principal components accounted for an impressive 84.62% of the cumulative contribution rate, while the genetic similarity, as gauged by eight ISSR primers, varied from 0.675 to 0.980. Most strikingly, we observed that plants from the same geographical region displayed molecular-level differences, underscoring the rich genetic diversity inherent in the 35 ornamental rape resources under study. Employing UPGMA cluster analysis on the primary agronomic traits and ISSR molecular markers, the 35 ornamental rape resources were categorized into seven and four distinct groups, respectively. Although the clustering outcomes from these two methodologies did not align perfectly, they served to complement each other. Collectively, these insights offer a theoretical framework for the innovation of ornamental rape germplasm resources and the cultivation of novel varieties.

genetics↗

bioRxiv2024

An Omni-Mesoscope for multiscale high-throughput quantitative phase imaging of cellular dynamics and high-content molecular characterization

The mesoscope has emerged as a powerful imaging tool in biomedical research, yet its high cost and low resolution have limited its broader application. Here, we introduce the Omni-Mesoscope, a cost-effective high-spatial-temporal, multimodal, and multiplex mesoscopic imaging platform built from cost-efficient off-the-shelf components. This system uniquely merges the capabilities of quantitative phase microscopy to capture live-cell dynamics over a large cell population with highly multiplexed fluorescence imaging for comprehensive molecular characterization. This integration facilitates simultaneous tracking of live-cell morphodynamics across thousands of cells, alongside high-content molecular analysis at the single-cell level. Furthermore, the Omni-Mesoscope offers a mesoscale field of view of approximately 5 mm2 with a high spatial resolution down to 700 nm, enabling the capture of information-rich images with detailed sub-cellular features. We demonstrate such capability in delineating molecular characteristics underlying rare dynamic cellular phenomena, such as cancer cell responses to chemotherapy and the emergence of polyploidy in drug-resistant cells. Moreover, the cost-effectiveness and the simplicity of our Omni-Mesoscope democratizes mesoscopic imaging, making it accessible across diverse biomedical research fields. To further demonstrate its versatility, we integrate expansion microscopy to enhance 3D volumetric super-resolution imaging of thicker tissues, opening new avenues for biological exploration at unprecedented scales and resolutions.

cell biology↗

bioRxiv2024

BOOST: a robust ten-fold expansion method on hour-scale

Expansion microscopy (ExM) enhances the microscopy resolution by physically expanding biological specimens and improves the visualization of structural and molecular details. Numerous ExM techniques and labeling methods have been developed and refined over the past decade to cater to specific research needs. Nonetheless, a shared limitation among current protocols is the extensive time required for sample processing, particularly for challenging-to-expand biological specimens (e.g., formalin-fixed paraffin-embedded (FFPE) sections and large three-dimensional specimens). Here, we have developed a rapid and robust ExM workflow named BOOST, which leverages a series of novel microwave (MW)-accelerated ExM chemistry, resulting in a single-step linear expansion of [~]10x. Specifically, BOOST facilitates a [~]10-fold expansion of cultured cells, tissue sections, and even the challenging-to-expand FFPE sections under merely 90 minutes with heat and surfactant-based protein denaturation. Furthermore, BOOST employs microwave-assisted proteomic staining and immunostaining to facilitate high-resolution visualization of structural and molecular details with significantly enhanced throughput. Noteworthily, BOOST has pioneered a [~]10-fold expansion of large millimeter-sized three-dimensional specimens in approximately three hours. BOOST offers an easily adaptable workflow based on stable and common reagents, thus boosting the potential adoption of ExM methods in biological investigations.

bioengineering↗

bioRxiv2024

YTHDF2 upregulation and relocation dictate CD8 T cell polyfunctionality in tumor immunity

Epigenetic traits impact the antitumor function of CD8 T cells, yet whether and how RNA methylation programs engage in T cell immunity is poorly understood. Here we show that the N6-methyladenosine (m6A) RNA reader YTHDF2 is highly expressed in early effector or effector-like CD8 T cells and is partially distributed in the nucleus. YTHDF2 loss in T cells exacerbates tumor progression and confers unresponsiveness to PD-1 blockade in mice and humans. In addition to initiating RNA decay for mitochondrial fitness, YTHDF2 can orchestrate chromatin regulation to promote T cell polyfunctionality. YTHDF2-mediatd preservation of gene transcription arises from the interaction of YTHDF2 with IKZF1/3. Accordingly, immunotherapy-induced efficacy could be largely restored in YTHDF2-deficient T cells through combinational use of lenalidomide. Moreover, m6A recognition is fundamental for YTHDF2 translocation to the nucleus and autoregulation at the RNA level. Thus, YTHDF2 coordinates epitranscriptional and transcriptional networks to potentiate T cell immunity. HighlightsO_LIYTHDF2 expression and distribution underpin the threshold for bona fide CD8 T cell effector response C_LIO_LICanonical YTHDF2-mRNA decay pathway alleviates mitochondrial stress and CD8 T cell exhaustion C_LIO_LINuclear YTHDF2 sequesters IKZF1/3-mediated transcriptional repression to safeguard CD8 T cell polyfunctionality C_LIO_LIThe tumoricidal activity of YTHDF2-deficient CD8 T cells could be repaired through the synergy of anti-PD-1 and lenalidomide C_LI

immunology↗

bioRxiv2024

Structure of human PIEZO1 and its slow inactivating channelopathy mutants

PIEZO channels transmit mechanical force signals to cells, allowing them to make critical decisions during development and in pathophysiological conditions. Their fast/slow inactivation modes have been implicated in mechanopathologies, but remain poorly understood. Here, we report several near-atomic resolution cryo-EM structures of fast-inactivating wild-type human PIEZO1 (hPIEZO1) and its slow-inactivating channelopathy mutants with or without its auxiliary subunit MDFIC. Our results suggest that hPIEZO1 has a more flattened and extended architecture than curved mouse PIEZO1 (mPIEZO1). The multi-lipidated MDFIC subunits insert laterally into the hPIEZO1 pore module like mPIEZO1, resulting in a more curved and extended state. Interestingly, the high-resolution structures suggest that the pore lipids, which directly seal the central hydrophobic pore, may be involved in the rapid inactivation of hPIEZO1. While the severe hereditary erythrocytosis mutant R2456H significantly slows down the inactivation of hPIEZO1, the hPIEZO1-R2456H-MDFIC complex shows a more curved and contracted structure with an inner helix twist due to the broken link between the pore lipid and R2456H. These results suggest that the pore lipids may be involved in the mechanopathological rapid inactivation mechanism of PIEZO channels.

biochemistry↗

bioRxiv2024

Reinforcement learning guides single-cell sequencing in decoding lineage and cell fate decisions

The rapid development of single-cell sequencing offers an unparalleled opportunity to delineate the heterogeneity of individual cells. However, current methods struggle to pinpoint the states of cell fate decisions. In this study, we introduce a novel approach called Single-cell Reinforcement Learning (scRL), which integrates reinforcement learning into single-cell data analysis using an actor-critic architecture. Among existing dimensionality reduction methods, we identified one with the best interpretability. Based on this latent space and combined with our scRL algorithm, we assessed the intensity of fate decisions at the single-cell level. Extensive evaluations demonstrate that scRL outperforms existing techniques, as well as their variants and alternative approaches, in assessing cell fate decisions. Moreover, scRL offers an alternative method for evaluating the intensity of cell lineage differentiation which shows competitive interpretability as well. The superiority of scRL in assessing fate decisions is confirmed across several types of single-cell datasets.

bioinformatics↗

bioRxiv2024

Regulation of the poly(A) Polymerase Star-PAP by a Nuclear Phosphoinositide Signalosome

Star-PAP is a noncanonical poly(A) polymerase that controls gene expression. Star-PAP was previously reported to bind the phosphatidylinositol 4-phosphate 5-kinase PIPKI and its product phosphatidylinositol 4,5-bisphosphate, which regulate Star-PAP poly(A) polymerase activity and expression of specific genes. Recent studies have revealed a nuclear PI signaling pathway in which the PI transfer proteins PITP/{beta}, PI kinases and phosphatases bind p53 to sequentially modify protein-linked phosphatidylinositol phosphates and regulate its function. Here we demonstrate that multiple phosphoinositides, including phosphatidylinositol 4-monophosphate and phosphatidylinositol 3,4,5-trisphosphate are also coupled to Star-PAP in response to stress. This is initiated by PITP/{beta} binding to Star-PAP, while the Star-PAP-linked phosphoinositides are modified by PI4KII, PIPKI, IPMK, and PTEN recruited to Star- PAP. The phosphoinositide coupling enhances the association of the small heat shock proteins HSP27/B-crystallin with Star-PAP. Knockdown of the PITPs, kinases, or HSP27 reduce the expression of Star-PAP targets. Our results demonstrate that the PITPs generate Star-PAP-PIPn complexes that are then modified by PI kinases/phosphatases and small heat shock proteins that regulate the linked phosphoinositide phosphorylation and Star-PAP activity in response to stress.

cell biology↗

bioRxiv2024

Informing grassland ecosystem modeling with in-situ and remote sensing observations

Historical grassland aboveground plant productivity (ANPP) was simulated by the DayCent-UV ecosystem model across the midwestern and western conterminous United States. For this study we developed a novel method for informing the DayCent-UV model and validating its plant productivity estimates for grasslands of the midwestern and western conterminous USA by utilizing a wide range of data sources at multiple scales, from field observations to remotely sensed satellite data. The model phenology was informed by the MODIS MCD12Q2 product, which showed good agreement with in-situ observations of growing season commencement and duration across different grassland ecosystems, and with observed historical trends. Model results from each simulated grid cell were compared to a remote-sensing ANPP modified version offered by the Analysis Rangeland Platform (RAP). This modified RAP ANPP calculation incorporated total annual precipitation, instead of mean annual temperature, as the control factor for the fraction of carbon allocated to roots. Strong temporal correlations were obtained between RAP and DayCent-UV, especially across the Great Plains. Good agreement was also found when the model results were compared with ANPP observations at the site and county level. The data produced by this study will serve as a valuable resource for validation or calibration of various models that aim to capture accurate productivity dynamics across diverse grassland ecosystems. Plain Language SummaryThis research used a computer model called DayCent-UV to simulate daily grassland growth across the central and western regions of the contiguous United States. To improve the agreement between the simulations and real-world conditions, we incorporated data from local field measurements and satellite imagery. This data helped determine the start and end dates of the growing season at each location. The simulated annual growth showed good agreement with satellite estimates from the Rangeland Analysis Platform (RAP), another computer application that monitors rangeland vegetation, and with local observations based on harvesting and weighing vegetation, particularly across the Great Plains. These results are valuable for validating and refining other computer models that aim to accurately simulate plant growth in grassland ecosystems; the predictions of these models are crucial for understanding the balance of carbon between plants, soils, and the atmosphere as the climate changes. Key PointsO_LIThe DayCent-UV model was used to simulate historical aboveground net primary productivity (ANPP) for different grassland ecosystems across the midwestern and western United States. C_LIO_LIMODIS MCD12Q2 was used to provide the phenology for the model. C_LIO_LIThe Rangeland Analysis Platform (RAP) fraction of biomass production allocated to roots calculation was modified, resulting in a stronger agreement between its ANPP estimates and those from the DayCent-UV model. C_LIO_LISite- and county-level ANPP observations were used to validate the model. C_LI

ecology↗

bioRxiv2024

Deficiency in a special dynein DNAH12 causes male infertility by impairing DNAH1 and DNALI1 recruitment in humans and mice

Asthenoteratozoospermia, a prevalent cause of male infertility, lacks a well-defined etiology. DNAH12 is a special dynein featured by the absence of a microtubule-binding domain, however, its functions in spermatogenesis remain largely unknown. Through comprehensive genetic analyses involving whole-exome sequencing and subsequent Sanger sequencing on infertile patients and fertile controls from six distinct families, we unveiled six biallelic mutations in DNAH12 that co-segregate recessively with male infertility in the studied families. Transmission electron microscopy (TEM) revealed pronounced axonemal abnormalities, including inner dynein arms (IDAs) impairment and central pair (CP) loss in sperm flagella of the patients. Mouse models (Dnah12-/- and Dnah12mut/mut) were generated and recapitulated the reproductive defects in the patients. Noteworthy, DNAH12 deficiency did not show effects on cilium organization and function. Mechanistically, DNAH12 was confirmed to interact with two other IDA components DNALI1 and DNAH1, while disruption of DNAH12 leads to failed recruitment of DNALI1 and DNAH1 to IDAs and compromised sperm development. Furthermore, DNAH12 also interacts with radial spoke head proteins RSPH1, RSPH9, and DNAJB13 to regulate CP stability. Moreover, the infertility of Dnah12-/- mice could be overcome by intracytoplasmic sperm injection (ICSI) treatment. Collectively, DNAH12 plays a crucial role in the proper organization of axoneme in sperm flagella, but not cilia, by recruiting DNAH1 and DNALI1 in both humans and mice. These findings expand our comprehension of dynein component assembly in flagella and cilia and provide a valuable marker for genetic counseling and diagnosis of asthenoteratozoospermia in clinical practice.

genetics↗

bioRxiv2024

Latrophilin-2 mediates fluid shear stress mechanotransduction at endothelial junctions

Endothelial cell responses to fluid shear stress from blood flow are crucial for vascular development, function and disease. A complex of PECAM-1, VE-cadherin, VEGF receptors (VEGFRs) and PlexinD1 located at cell-cell junctions mediates many of these events. But available evidence suggests that another mechanosensor upstream of PECAM-1 initiates signaling. Hypothesizing that GPCR and G proteins may serve this role, we performed siRNA screening of G subunits and found that Gi2 and Gq/11 are required for activation of the junctional complex. We then developed a new activation assay, which showed that these G proteins are activated by flow. We next mapped the G residues required for activation and developed an affinity purification method that used this information to identify latrophilin-2 (Lphn-2/ADGRL2) as the upstream GPCR. Latrophilin-2 is required for all PECAM-1 downstream events tested. In both mice and zebrafish, latrophilin-2 is required for flow-dependent angiogenesis and artery remodeling. Furthermore, endothelial specific knockout demonstrates that latrophilin plays a role in flow-dependent artery remodeling. Human genetic data reveal a correlation between the latrophilin-2-encoding Adgrl2 gene and cardiovascular disease. Together, these results define a pathway that connects latrophilin-dependent G protein activation to subsequent endothelial signaling, vascular physiology and disease.

molecular biology↗

bioRxiv2024

Selective inflammation of the tumor microenvironment and invigorated T cell-mediated tumor control upon induced systemic inactivation of TREX1

Therapeutic innate immune stimulation within the tumor microenvironment can potentiate endogenous antitumor T cell immunity. DNase 3-repair exonuclease 1 (TREX1) is essential for cellular DNA disposal which prevents autoimmunity ensuing from cGAS/STING activation by endogenous DNA. Optimal strategies to therapeutically leverage cGAS/STING signalling for cancer therapy are highly sought after. TREX1-deficient tumor cells elicit enhanced protective immunity in syngeneic models. Here we show that induced inactivation of the Trex1 gene in (non-malignant) host cells is well tolerated and yields improved type I IFN- and T cell-dependent control of established TREX1-competent tumors with selective immune cell infiltration of tumor, but not other tissues. Intra-tumoral T cell proliferation and numbers of effector and effector-like exhausted cells massively increased, enabling complete rejection in synergy with checkpoint inhibition. We conclude that systemic TREX1 inhibition is a promising approach to boost anti-tumor immunity, that can overcome immune evasion by cancer cell- intrinsic cGAS/STING inactivation.

immunology↗

bioRxiv2024

ApoE ϵ4-dependent alteration of CXCR3+CD127+ CD4+ T cells is associated with elevated plasma neurofilament light chain in Alzheimer's disease

Recent findings indicate a correlation between the peripheral adaptive immune system and neuroinflammation in Alzheimers disease (AD). To characterize the composition of adaptive immune cells in the peripheral blood of AD patients, we utilized single-cell mass cytometry (CyTOF) to profile peripheral blood mononuclear cells (PBMCs). Concurrently, we assessed the concentration of proteins associated with AD and neuroinflammation in the plasma of the same subjects. We found that the abundance of proinflammatory CXCR3+CD127+ Type 1 T helper (Th1) cells in AD patients was negatively correlated with the abundance of neurofilament light chain (NfL) protein. This correlation is apolipoprotein E (ApoE) {varepsilon}4-dependent. Analyzing public single-cell RNA-sequencing (scRNA-seq) data, we found that, contrary to the scenario in the peripheral blood, the cell frequency of CXCR3+CD127+ Th1 cells in the cerebrospinal fluid (CSF) of AD patients was increased compared to healthy controls (HCs). Moreover, the proinflammatory capacity of CXCR3+CD127+ Th1 cells in the CSF of AD patients was further increased compared to HCs. These results reveal an association of a peripheral T-cell change with neuroinflammation in AD and suggest that dysregulation of peripheral adaptive immune responses, particularly involving CXCR3+CD127+ Th1 cells, may potentially be mediated by factors such as ApoE {varepsilon}4 genotype. One sentence summaryAn apolipoprotein E (ApoE) {varepsilon}4-dependent alteration of CD4 T cell subpopulation in peripheral blood is associated with neuroinflammation in patients with Alzheimers disease.

immunology↗

bioRxiv2024

Beyond variability: a novel gene expression stability metric to unveil homeostasis and regulation

The concept of gene expression stability within a homeostatic cell is explored through the gene homeostasis Z-index, a measure that highlights genes under active regulation in response to internal and external stimuli. This index reveals distinct regulatory activities and patterns in different organs, such as enhanced synaptic transmission in pancreatic islets. The research indicates that traditional mean-based methods may miss these nuances, underlining the significance of new metrics in identifying gene regulation specifics in cellular adaptation.

bioinformatics↗

bioRxiv2024

The curses of performing differential expression analysis using single-cell data

Differential expression analysis is pivotal in single-cell transcriptomics for unraveling cell-type- specific responses to stimuli. While numerous methods are available to identify differentially expressed genes in single-cell data, recent evaluations of both single-cell-specific methods and methods adapted from bulk studies have revealed significant shortcomings in performance. In this paper, we dissect the four major challenges in single-cell DE analysis: normalization, excessive zeros, donor effects, and cumulative biases. These "curses" underscore the limitations and conceptual pitfalls in existing workflows. In response, we introduce a novel paradigm addressing several of these issues.

bioinformatics↗

bioRxiv2024

RBET guides case-specific choice of batch correction methods for single-cell transcriptomic data with overcorrection awareness and large batch effect robustness

Integrating single-cell RNA-sequencing datasets from different sources is a common practice to empower in-depth interrogation for biological insights, where batch effect correction (BEC) is of vital importance. However, an inappropriate BEC may lead to overcorrection and report misleading results on downstream analyses including cell annotation, trajectory inference and cell-cell communication. Hence, we develop the Reference-based Batch Effect Testing (RBET), a novel statistical framework for evaluating the performance of different BEC methods by leveraging housekeeping-gene inspired reference genes and MAC statistics for distribution comparison. Comparing with existing methods, RBET is more powerful on detecting batch effect, overcorrection sensitive, computationally efficient, and robust to large batch effect sizes. Furthermore, extensive multi-scenario real examples show that RBET selects optimal BEC tools for consistent downstream analysis results, which confirm prior biological knowledge. This comprehensive BEC decision-making tool is available as an R package.

bioinformatics↗

bioRxiv2024

An in vivo 'turning model' reveals new RanBP9 interactions in lung macrophages.

The biological functions of the scaffold protein Ran Binding Protein 9 (RanBP9) remain elusive in macrophages or any other cell type where this protein is expressed together with its CTLH (C-terminal to LisH) complex partners. We have engineered a new mouse model, named RanBP9-TurnX, where RanBP9 fused to three copies of the HA tag (RanBP9-3xHA) can be turned into RanBP9-V5 tagged upon Cre-mediated recombination. We created this model to enable stringent biochemical studies at cell type specific level throughout the entire organism. Here, we have used this tool crossed with LysM-Cre transgenic mice to identify RanBP9 interactions in lung macrophages. We show that RanBP9-V5 and RanBP9-3xHA can be both co-immunoprecipitated with the known members of the CTLH complex from the same whole lung lysates. However, more than ninety percent of the proteins pulled down by RanBP9-V5 differ from those pulled-down by RanBP9-HA. The lung RanBP9-V5 associated proteome includes previously unknown interactions with macrophage-specific proteins as well as with players of the innate immune response, DNA damage response, metabolism, and mitochondrial function. This work provides the first lung specific RanBP9-associated interactome in physiological conditions and reveals that RanBP9 and the CTLH complex could be key regulators of macrophage bioenergetics and immune functions.

cell biology↗

bioRxiv2024

iSeq: An integrated tool to fetch public sequencing data

High-throughput sequencing technologies (Next Generation Sequencing; NGS) are increasingly utilized by researchers to tackle a diverse array of biological inquiries. Leveraging the remarkable scale and efficiency of modern sequencing, significant advancements are made across various fields, spanning from genome analysis to the intricate dynamics of protein-nucleic acid interactions. Recognizing that NGS data harbors rich biological information, the International Nucleotide Sequence Database Collaboration (INSDC) was established nearly 40 years ago to collect and disseminate public nucleotide sequence data and associated metadata. The National Genomics Data Center (NGDC) has also provided open access to vast amounts of raw sequence data. These databases have greatly enhanced the capacity for reanalyzing NGS data. In recent years, amid the rise of large language models, biological sequences and data have emerged as inputs for training models to address biological challenges. However, methods for programmatically accessing this public sequencing data remain limited. To address this gap, we have developed iSeq, an integrated tool that allows for quick and straightforward retrieval of metadata and NGS data via the command-line interface. iSeq is currently the only tool that supports simultaneous retrieval from multiple databases (GSA, SRA, ENA, DDBJ, and GEO). Additionally, iSeq supports a wide range of accession formats as input and features parallel downloads, multi-threaded processes, and FASTQ file merging. It is freely available on Bioconda (https://anaconda.org/bioconda/iseq) and GitHub (https://github.com/BioOmics/iSeq). HighlightsO_LIiSeq supports multiple databases for accessing a wide range of raw sequencing data and metadata. C_LIO_LIiSeq supports at least 25 different accession formats as input. C_LIO_LIiSeq supports parallel downloads, multi-threaded processes, FASTQ file merging, and integrity verification. C_LI

bioinformatics↗