Biology subjects

Xiao, G.

Publications and source records attributed to Xiao, G..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

A Generalized Supervised Contrastive Learning Framework for Integrative Multi-omics Prediction Models

Recent technological advances have highlighted the significant impact of the human microbiome and metabolites on physiological conditions. Integrating microbiome and metabolite data has shown promise in predictive capabilities. We developed a new supervised contrastive learning framework, MB-SupCon-cont, that (1) proposes a general contrastive learning framework for continuous outcomes and (2) improves prediction accuracy over models using single omics data. Simulation studies confirmed the improved performance of MB-SupCon-cont, and applied scenarios in type 2 diabetes and high-fat diet studies also showed improved prediction performance. Overall, MB-SupCon-cont is a versatile research tool for multi-omics prediction models.

bioinformatics↗

bioRxiv2023

Mapping Cell-to-cell Interactions from Spatially Resolved Transcriptomics Data

Cell-cell communication (CCC) is essential to how life forms and functions. However, accurate, high-throughput mapping of how expression of all genes in one cell affects expression of all genes in another cell is made possible only recently, through the introduction of spatially resolved transcriptomics technologies (SRTs), especially those that achieve single cell resolution. However, significant challenges remain to analyze such highly complex data properly. Here, we introduce a Bayesian multi-instance learning framework, spacia, to detect CCCs from data generated by SRTs, by uniquely exploiting their spatial modality. We highlight spacias power to overcome fundamental limitations of popular analytical tools for inference of CCCs, including losing single-cell resolution, limited to ligand-receptor relationships and prior interaction databases, high false positive rates, and most importantly the lack of consideration of the multiple-sender-to-one-receiver paradigm. We evaluated the fitness of spacia for all three commercialized single cell resolution ST technologies: MERSCOPE/Vizgen, CosMx/Nanostring, and Xenium/10X. Spacia unveiled how endothelial cells, fibroblasts and B cells in the tumor microenvironment contribute to Epithelial-Mesenchymal Transition and lineage plasticity in prostate cancer cells. We deployed spacia in a set of pan-cancer datasets and showed that B cells also participate in PDL1/PD1 signaling in tumors. We demonstrated that a CD8+ T cell/PDL1 effectiveness signature derived from spacia analyses is associated with patient survival and response to immune checkpoint inhibitor treatments in 3,354 patients. We revealed differential spatial interaction patterns between {gamma}{delta} T cells and liver hepatocytes in healthy and cancerous contexts. Overall, spacia represents a notable step in advancing quantitative theories of cellular communications.

bioinformatics↗

bioRxiv2023

NanoPDLIM2 enhanced efficacy of PD-1 blockade and chemotherapy in mouse lung cancers

BackgroundImmune checkpoint inhibitors (ICIs) and their combination with other therapies such as chemotherapy, fail in most cancer patients. We previously identified the PDZ-LIM domain-containing protein 2 (PDLIM2) as a bona fide tumor suppressor that is repressed in lung cancer to drive cancer and its chemo and immunotherapy resistance, suggesting a new target for lung cancer therapy improvement. MethodsHuman clinical samples and data were used to investigate PDLIM2 genetic and epigenetic changes in lung cancer. Using an endogenous mouse lung cancer model faithfully recapitulating refractory human lung cancer and a clinically feasible nano-delivery system, we investigated the therapeutic efficacy, action mechanism, and safety of systemically administrated PDLIM2 expression plasmids encapsulated in nanoparticles (nanoPDLIM2) and its combination with PD-1 antibody and chemotherapeutic drugs. ResultsPDLIM2 repression in human lung cancer involves both genetic deletion and epigenetic alteration. NanoPDLIM2 showed low toxicity, high tumor specificity, antitumor activity, and greatly improved the efficacy of anti-PD-1 and chemotherapeutic drugs, with complete tumor remission in most mice and substantial tumor reduction in the remaining mice by their triple combination. Mechanistically, nanoPDLIM2 increased major histocompatibility complex class I (MHC-I) expression, suppressed multi-drug resistance 1 (MDR1) induction and survival genes and other tumor-related genes expression in tumor cells, and enhanced lymphocyte tumor infiltration, turning the cold tumors hot and sensitive to ICIs and rendering them vulnerable to chemotherapeutic drugs and activated tumor-infiltrating lymphocytes (TILs) including those unleashed by ICIs. ConclusionsThese studies established a clinically applicable PDLIM2-based combination therapy with great efficacy for lung cancer and possibly other cold cancers.

cancer biology↗

bioRxiv2023

ScopeViewer: A Browser-Based Solution for Visualizing Spatial Transcriptomics Data

MotivationSpatial transcriptomics (ST) enables a high-resolution interrogation of molecular characteristics within specific spatial contexts and tissue morphology. Despite its potential, visualization of ST data is a challenging task due to the complexities in handling, sharing and visualizing large image datasets together with molecular information. ResultsWe introduce ScopeViewer, a browser-based software designed to overcome these challenges. ScopeViewer offers the following functionalities: (1) It visualizes large image data and associated annotations at various zoom levels, allowing for intricate exploration of the data; (2) It enables dual interactive viewing of the original images along with their annotations, providing a comprehensive understanding of the context; (3) It displays spatial molecular features with optimized bandwidth, ensuring a smooth user experience; and (4) It bolsters data security by circumventing data transfers. AvailabilityScopeViewer is available at: https://datacommons.swmed.edu/scopeviewer ContactXiaowei.Zhan@UTSouthwestern.edu, Guanghua.Xiao@UTSouthwestern.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2023

Patient-derived tumor organoids with p53 mutations, and not wild-type p53, are sensitive to synergistic combination PARP inhibitor treatment

Poly (ADP-ribose) polymerase inhibitors (PARPi) are used for patients with BRCA1/2 mutations, but patients with other mutations may benefit from PARPi treatment. Another mutation that is present in more cancers than BRCA1/2 is mutation to the TP53 gene. In 2D breast cancer cell lines, mutant p53 (mtp53) proteins tightly associate with replicating DNA and Poly (ADP-ribose) polymerase (PARP) protein. Combination drug treatment with the alkylating agent temozolomide and the PARPi talazoparib kills mtp53 expressing 2D grown breast cancer cell lines. We evaluated the sensitivity to the combination of temozolomide plus PARPi talazoparib treatment to breast and lung cancer patient-derived tumor organoids (PDTOs). The combination of the two drugs was synergistic for a cytotoxic response in PDTOs with mtp53 but not for PDTOs with wtp53. The combination of talazoparib and temozolomide induced more DNA double-strand breaks in mtp53 expressing organoids than in wild-type p53 expressing organoids as shown by increased {psi}-H2AX protein expression. Moreover, breast cancer tissue microarrays (TMAs) showed a positive correlation between stable p53 and high PARP1 expression in sub-groups of breast cancers, which may indicate sub-classes of breast cancers sensitive to PARPi therapy. These results suggest that mtp53 could be a biomarker to predict response to the combination of PARPi talazoparib-temozolomide treatment.

cancer biology↗

bioRxiv2023

Integrating Image and Molecular Profiles for Spatial Transcriptomics Analysis

The spatially resolved transcriptomics (SRT) field has revolutionized our ability to comprehensively leverage image and molecular profiles to elucidate spatial organization of cellular microenvironments. Current clustering analysis of SRT data primarily relies on molecular information and fails to fully exploit the morphological features present in histology images, leading to compromised accuracy and interpretability. To overcome these limitations, we have developed a multi-stage statistical method called iIMPACT. It includes a finite mixture model to identify and define histology-based spatial domains based on AI-reconstructed histology images and spatial context of gene expression measurements, and a negative binomial regression model to detect domain-specific spatially variable genes. Through multiple case studies, we demonstrate iIMPACT outperformed existing methods, confirmed by ground truth biological knowledge. These findings underscore the accuracy and interpretability of iIMPACT as a new clustering approach, providing valuable insights into the cellular spatial organization and landscape of functional genes within spatial transcriptomics data.

bioinformatics↗

bioRxiv2023

Developmental exposure to polychlorinated biphenyls prevents recovery from noise-induced hearing loss and disrupts the functional organization of the inferior colliculus

Exposure to combinations of environmental toxins is growing in prevalence, and therefore understanding their interactions is of increasing societal importance. Here, we examined the mechanisms by which two environmental toxins - polychlorinated biphenyls (PCBs) and high-amplitude acoustic noise - interact to produce dysfunction in central auditory processing. PCBs are well-established to impose negative developmental impacts on hearing. However, it is not known if developmental exposure to this ototoxin alters the sensitivity to other ototoxic exposures later in life. Here, male mice were exposed to PCBs in utero, and later as adults were exposed to 45 minutes of high-intensity noise. We then examined the impacts of the two exposures on hearing and the organization of the auditory midbrain using two-photon imaging and analysis of the expression of mediators of oxidative stress. We observed that developmental exposure to PCBs blocked hearing recovery from acoustic trauma. In vivo two-photon imaging of the inferior colliculus revealed that this lack of recovery was associated with disruption of the tonotopic organization and reduction of inhibition in the auditory midbrain. In addition, expression analysis in the inferior colliculus revealed that reduced GABAergic inhibition was more prominent in animals with a lower capacity to mitigate oxidative stress. These data suggest that combined PCBs and noise exposure act nonlinearly to damage hearing and that this damage is associated with synaptic reorganization, and reduced capacity to limit oxidative stress. In addition, this work provides a new paradigm by which to understand nonlinear interactions between combinations of environmental toxins. Significance statementExposure to common environmental toxins is a large and growing problem in the population. This work provides a new mechanistic understanding of how the pre-and postnatal developmental changes induced by polychlorinated biphenyls could negatively impact the resilience of the brain to noise-induced hearing loss later in adulthood. The use of state-of-the-art tools, including in vivo multiphoton microscopy of the midbrain helped in identifying the long-term central changes in the auditory system after the peripheral hearing damage induced by such environmental toxins. In addition, the novel combination of methods employed in this study will lead to additional advances in our understanding of mechanisms of central hearing loss in other contexts.

neuroscience↗

bioRxiv2023

Targeted engagement of β-catenin-Ikaros complexes in refractory B-cell malignancies

In most cell types, nuclear {beta}-catenin functions as prominent oncogenic driver and pairs with TCF7-family factors for transcriptional activation of MYC. Surprisingly, B-lymphoid malignancies not only lacked expression and activating lesions of {beta}-catenin but critically depended on GSK3{beta} for effective {beta}-catenin degradation. Our interactome studies in B-lymphoid tumors revealed that {beta}-catenin formed repressive complexes with lymphoid-specific Ikaros factors at the expense of TCF7. Instead of MYC-activation, {beta}-catenin was essential to enable Ikaros-mediated recruitment of nucleosome remodeling and deacetylation (NuRD) complexes for transcriptional repression of MYC. To leverage this previously unrecognized vulnerability of B-cell-specific repressive {beta}-catenin-Ikaros-complexes in refractory B-cell malignancies, we examined GSK3{beta} small molecule inhibitors to subvert {beta}-catenin degradation. Clinically approved GSK3{beta}-inhibitors that achieved favorable safety prof les at micromolar concentrations in clinical trials for neurological disorders and solid tumors were effective at low nanomolar concentrations in B-cell malignancies, induced massive accumulation of {beta}-catenin, repression of MYC and acute cell death. Preclinical in vivo treatment experiments in patient-derived xenografts validated small molecule GSK3{beta}-inhibitors for targeted engagement of lymphoid-specific {beta}-catenin-Ikaros complexes as a novel strategy to overcome conventional mechanisms of drug-resistance in refractory malignancies. HIGHLIGHTSO_LIUnlike other cell lineages, B-cells express nuclear {beta}-catenin protein at low baseline levels and depend on GSK3{beta} for its degradation. C_LIO_LIIn B-cells, {beta}-catenin forms unique complexes with lymphoid-specific Ikaros factors and is required for Ikaros-mediated tumor suppression and assembly of repressive NuRD complexes. C_LIO_LICRISPR-based knockin mutation of a single Ikaros-binding motif in a lymphoid MYC superenhancer region reversed {beta}-catenin-dependent Myc repression and induction of cell death. C_LIO_LIThe discovery of GSK3{beta}-dependent degradation of {beta}-catenin as unique B-lymphoid vulnerability provides a rationale to repurpose clinically approved GSK3{beta}-inhibitors for the treatment of refractory B-cell malignancies. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/532152v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@1b70e4dorg.highwire.dtl.DTLVardef@10bfcc8org.highwire.dtl.DTLVardef@b10eorg.highwire.dtl.DTLVardef@1683a3e_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIAbundant nuclear {beta}-catenin C_LIO_LI{beta}-catenin pairs with TCF7 factors for transcriptional activation of MYC C_LIO_LIB-cells rely on efficient degradation of {beta}-catenin by GSK3{beta} C_LIO_LIB-cell-specific expression of Ikaros factors C_LI Unique vulnerability in B-cell tumors: O_LIGSK3{beta}-inhibitors induce nuclear accumulation of {beta}-catenin. C_LIO_LI{beta}-catenin pairs with B-cell-specific Ikaros factors for transcriptional repression of MYC C_LI

cancer biology↗

bioRxiv2023

Spatial Transcriptomics Arena (STAr): an Integrated Platform for Spatial Transcriptomics Methodology Research

The emerging field of spatially resolved transcriptomics (SRT) has revolutionized biomedical research. SRT quantifies expression levels at different spatial locations, providing a new and powerful tool to interrogate novel biological insights. An essential question in the analysis of SRT data is to identify spatially variable (SV) genes; the expression levels of such genes have spatial variation across different tissues. SV genes usually play an important role in underlying biological mechanisms and tissue heterogeneity. Currently, several computational methods have been developed to detect such genes; however, there is a lack of unbiased assessment of these approaches to guide researchers in selecting the appropriate methods for their specific biomedical applications. In addition, it is difficult for researchers to implement different existing methods for either biological study or methodology development. Furthermore, currently available public SRT datasets are scattered across different websites and preprocessed in different ways, posing additional obstacles for quantitative researchers developing computational methods for SRT data analysis. To address these challenges, we designed Spatial Transcriptomics Arena (STAr), an open platform comprising 193 curated datasets from seven technologies, seven statistical methods, and analysis results. This resource allows users to retrieve high-quality datasets, apply or develop spatial gene detection methods, as well as browse and compare spatial gene analysis results. It also enables researchers to comprehensively evaluate SRT methodology research in both simulated and real datasets. Altogether, STAr is an integrated research resource intended to promote reproducible research and accelerate rigorous methodology development, which can eventually lead to an improved understanding of biological processes and diseases. STAr can be accessed at https://lce.biohpc.swmed.edu/star/.

genomics↗

bioRxiv2022

A Deep Learning Approach for Histology-Based Nuclei Segmentation and Tumor Microenvironment Characterization

Microscopic examination of pathology slides is essential to disease diagnosis and biomedical research; however, traditional manual examination of tissue slides is laborious and subjective. Tumor whole-slide image (WSI) scanning is becoming part of routine clinical procedure and produces massive data that capture tumor histological details at high resolution. Furthermore, the rapid development of deep learning algorithms has significantly increased the efficiency and accuracy of pathology image analysis. In light of this progress, digital pathology is fast becoming a powerful tool to assist pathologists. Studying tumor tissue and its surrounding microenvironment provides critical insight into tumor initiation, progression, metastasis, and potential therapeutic targets. Nuclei segmentation and classification are critical to pathology image analysis, especially in characterizing and quantifying the tumor microenvironment (TME). Computational algorithms have been developed for nuclei segmentation and TME quantification within image patches; however, existing algorithms are computationally intensive and time-consuming for WSI analysis. In this study, we present Histology-based Detection using Yolo (HD-Yolo), a new method that significantly accelerates nuclei segmentation and TME quantification. We demonstrate that HD-Yolo outperforms existing methods for WSI analysis in nuclei detection and classification accuracy, as well as computation time.

pathology↗

bioRxiv2022

Bulk and Mosaic Deletions of Egfr Reveal Regionally Defined Gliogenesis in the Developing Mouse Forebrain

The Epidermal growth factor receptor (EGFR) plays a role in cell proliferation and differentiation during healthy development and tumor growth, however its requirement for brain development remains unclear. Here we used a conditional mouse allele for Egfr to examine its contributions to perinatal forebrain development at the tissue level. Subtractive bulk ventral and dorsal forebrain deletions of Egfr uncovered significant and permanent decreases in oligodendrogenesis and myelination in the cortex and corpus callosum. Additionally, an increase in astrogenesis or reactive astrocytes in effected regions was evident in response to cortical scarring. Sparse deletion using Mosaic Analysis with Double Markers (MADM) surprisingly revealed a regional requirement for EGFR in rostrodorsal, but not ventrocaudal glial lineages including both astrocytes and oligodendrocytes. The EGFR-independent ventral glial progenitors may compensate for the missing EGFR-dependent dorsal glia in the bulk Egfr-deleted forebrain, potentially exposing a regenerative population of gliogenic progenitors in the mouse forebrain.

neuroscience↗

bioRxiv2022

A comparative study of neuroendocrine heterogeneity in SCLC and NBL

Lineage plasticity has long been documented in both small cell lung cancer (SCLC) and neuroblastoma (NBL), two clinically distinct neuroendocrine (NE) cancers. In this study, we quantified the NE features of cancer as NE scores and performed a systematic comparison of SCLC and NBL. We found NBL and SCLC cell lines have highly similar molecular profiles and shared therapeutic sensitivity. In addition, NE heterogeneity was observed at both the inter- and intra-cell line levels. Surprisingly, we did not find a significant association between NE scores and overall survival in SCLC or NBL. We described many shared and unique NE score-associated features between SCLC and NBL, including dysregulation of Myc oncogenes, alterations in protein expression, metabolism, drug resistance, and selective gene dependencies. Our work establishes a reference for molecular changes and vulnerabilities associated with NE to non-NE transdifferentiation through mutual validation of SCLC and NBL samples.

bioinformatics↗

bioRxiv2022

Focal adhesion protein vinculin inhibits Mef2c-driven sclerostin expression in osteocytes to promote bone formation in mice

The focal adhesion (FA) is the structural basis of the cell-extracellular matrix crosstalk and plays important roles in control of organ formation and function. Here we show that expression of FA protein vinculin is dramatically reduced in osteocytes in patients with aging-related osteoporosis. Deleting vinculin using the mouse 10-kb Dmp1-Cre transgenic mice causes a severe osteopenia in both young and aged mice by impairing osteoblast function without affecting bone resorption. Vinculin loss impairs the anabolic response of skeleton to mechanical loading in mice. At the molecular level, vinculin knockdown increases, while vinculin overexpression decreases, sclerostin expression in osteocytes without impacting expression of Mef2c, a major transcriptional regulator of the Sost gene, which encodes sclerostin. Vinculin interacts with Mef2c and vinculin loss enhances Mef2c nuclear translocation and binding to the Sost enhancer ECR5 to promote sclerostin production in osteocytes. Deleting Sost expression reverses the osteopenic phenotypes caused by vinculin loss in mice. We demonstrate that estrogen is a major regulator of vinculin expression in osteocytes and that more importantly vinculin loss mediates estrogen deficiency induction of bone loss in mice. Thus, we demonstrate a novel mechanism through which vinculin inhibits the Mef2c-driven sclerostin expression in osteocytes to promote bone formation.

developmental biology↗

bioRxiv2022

Microprism-based two-photon imaging of the lateral cortex of the mouse inferior colliculus reveals novel organizational principles of the auditory midbrain

To navigate real-world listening conditions, the auditory system relies on the integration of multiple sources of information. However, to avoid inappropriate cross-talk between inputs, highly connected neural systems need to strike a balance between integration and segregation. Here, we develop a novel approach to examine how repeated neurochemical modules in the mouse inferior colliculus lateral cortex (LC) allow controlled integration of its multimodal inputs. The LC had been impossible to study via imaging because it is buried in a sulcus. Therefore we coupled two-photon microscopy with the use of a microprism to reveal the first-ever sagittal views of the LC to examine neuronal responses with respect to its neurochemical motifs under anesthetized and awake conditions. This approach revealed marked differences in the acoustic response properties of LC and neighboring nonlemniscal portions of the inferior colliculus. In addition, we observed that the module and matrix cellular motifs of the LC displayed distinct somatosensory and auditory responses. Specifically, neurons in modules demonstrated primarily offset responses to acoustic stimuli with enhancement in responses to bimodal stimuli, whereas matrix neurons showed onset response to acoustic stimuli and suppressed responses to bimodal stimulation. Thus, this new approach revealed that the repeated structural motifs of the LC permit functional integration of multimodal inputs while retaining distinct response properties.

neuroscience↗

bioRxiv2022

A pan-cancer PDX histology image repository with genomic and pathological annotations for deep learning analysis

Patient-derived xenografts (PDXs) model human intra-tumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histological imaging via hematoxylin and eosin (H&E) staining is performed on PDX samples for routine assessment and, in principle, captures the complex interplay between tumor and stromal cells. Deep learning (DL)-based analysis of large human H&E image repositories has extracted inter-cellular and morphological signals correlated with disease phenotype and therapeutic response. Here, we present an extensive, pan-cancer repository of nearly 1,000 PDX and paired human progenitor H&E images. These images, curated from the PDXNet consortium, are associated with genomic and transcriptomic data, clinical metadata, pathological assessment of cell composition, and, in several cases, detailed pathological annotation of tumor, stroma, and necrotic regions. We demonstrate that DL can be applied to these images to classify tumor regions and to predict xenograft-transplant lymphoproliferative disorder, the unintended outgrowth of human lymphocytes at the transplantation site. This repository enables PDX-specific, investigations of cancer biology through histopathological analysis and contributes important model system data that expand on existing human histology repositories. We expect the PDXNet Image Repository to be valuable for controlled digital pathology analysis, both for the evaluation of technical issues such as stain normalization and for development of novel computational methods based on spatial behaviors within cancer tissues.

bioinformatics↗

bioRxiv2022

Image-based quantification of histological features as a function of spatial location using the Tissue Positioning System

Tissues such as the liver lobule, kidney nephron, and intestinal gland exhibit intricate patterns of zonated gene expression corresponding to distinct cell types and functions. To quantitatively understand zonation, it would be important to measure cellular or genetic features as a function of position along a zonal axis. While it is possible to manually count, characterize, and locate features in relation to the zonal axis, it is very difficult to do this for more than a few hundred instances. We addressed this challenge by developing a deep-learning-based quantification method called the "Tissue Positioning System" (TPS), which can automatically analyze zonation in the liver lobule as a model system. By using algorithms that identified vessels, classified vessels, and segmented zones based on the relative position along the portal vein to central vein axis, TPS was able to spatially quantify gene expression in mice with zone specific reporters. TPS could discern expression differences between zonal reporter strains, ages, and disease states. TPS could also reveal the zonal distribution of cells previously thought to be randomly distributed. The design principles of TPS could be generalized to other tissues to explore the biology of zonation. The software is available at https://github.com/yunguan-wang/Tissue_positioning_system.

bioinformatics↗

bioRxiv2022

The Piks allele of the NLR immune receptor Pik breaks the recognition of AvrPik effectors of the rice blast fungus

Arms race co-evolution of plant-pathogen interactions evolved sophisticated recognition mechanisms between host immune receptors and pathogen effectors. Different allelic haplotypes of an immune receptor in host mount distinct recognition against sequence or non-sequence related effectors in pathogens. We report the molecular characterization of the Piks allele of the rice immune receptor Pik against rice blast pathogen, which requires two head-to-head arrayed nucleotide binding site and leucine-rich repeat proteins. Like other Pik genes, both Piks-1 and Piks-2 are necessary and sufficient for Piks-mediated resistance. However, unlike other Pik alleles, Piks does not recognize any known AvrPik variants of M. oryzae. Sequence analysis of the genome of an avirulent isolate V86010 further revealed that its cognate avirulence (Avr) gene most likely has no significant sequence similarity to known AvrPik variants. We conclude that Piks breaks the canonical Pik/AvrPik recognition pattern. Piks-1 and Pikm-1 have only two amino acid differences within the integrated heavy metal-associated (HMA) domain. Pikm-1-HMA interact with AvrPik-A, -D and -E in vitro and in vivo, whereas Piks-1-HMA does not bind any AvrPik variants. Reciprocal exchanges of single amino acid residues between Piks-1 and Pikm-1 further reveal a dynamic recognition mechanism between Piks/Pikm alleles and their respective effectors. Piks-1E229Q/Pikm-1V261A can only activate immunity to AvrPik-D but not to other effectors, indicating that the amino acid change of E to Q at position 229 leads to its gain of a partial recognition spectrum of Pikm. By contrast, Piks-1A261V/Pikm-1Q229E confers immunity to the Piks cognate effector, indicating that the amino acid change of Q to E at position 229 leads to its shifts of the recognition from Pikm to Piks. Intriguingly, binding activities in both Y2H and analytical gel filtration assays are illustrated between Piks-1A261V/Pikm-1Q229E and AvrPik-D. However, it is unable to mount immunity against AvrPik-D, suggesting that biochemical activities based on in vitro and in vivo assays could be insufficient for sustaining biological function of receptor and effector pairs.

plant biology↗

bioRxiv2022

Kindlin-2 inhibits TNF/NF-kB-caspase 8 pathway in hepatocytes to maintain liver development and function

Inflammatory liver diseases are a major cause of morbidity and mortality worldwide; however, underlying mechanisms are incompletely understood. Here we show that deleting the focal adhesion protein Kindlin-2 in hepatocytes using the Alb-Cre transgenic mice causes a severe inflammation, resulting in premature death. Kindlin-2 loss accelerates hepatocyte apoptosis with subsequent compensatory cell proliferation and accumulation of the collagenous extracellular matrix, leading to massive liver fibrosis and dysfunction. Mechanistically, Kindlin-2 loss abnormally activates the tumor necrosis factor (TNF) pathway. Blocking activation of the TNF signaling pathway by deleting TNF receptor or deletion of caspase 8 expression in hepatocytes essentially restores liver function and prevents premature death caused by Kindlin-2 loss.Finally, of translational significance, adeno-associated virus mediated overexpression of Kindlin-2 in hepatocytes attenuates the D-galactosamine and lipopolysaccharide-induced liver injury and death in mice. Collectively, we establish that Kindlin-2 acts as a novel intrinsic inhibitor of the TNF pathway to maintain liver homeostasis and may define a useful therapeutic target for liver diseases.

cell biology↗