Biology subjects

Li, C.

Publications and source records attributed to Li, C..

At least 559 records · Page 31Linked to original sources

bioRxiv2023

Cardiac Molecular Analysis Reveals Aging-Associated Metabolic Alterations Promoting Glycosaminoglycans Accumulation Via Hexosamine Biosynthetic Pathway

Age is a prominent risk factor for cardiometabolic disease, and often leads to heart structural and functional changes. However, precise molecular mechanisms underlying cardiac remodeling and dysfunction resulting from physiological aging per se remain elusive. Understanding these mechanisms requires biological models with optimal translation to humans. Previous research demonstrated that baboons undergo age-related reduction in ejection fraction and increased heart sphericity, mirroring changes observed in humans. The goal of this study was to identify early cardiac molecular alterations that precede functional adaptations, shedding light on the regulation of age-associated changes. We performed unbiased transcriptomics of left ventricle (LV) samples from female baboons aged 7.5-22.1 years (human equivalent [~]30-88 years). Weighted-gene correlation network and pathway enrichment analyses were performed to identify potential age-associated mechanisms in LV, with histological validation. Myocardial modules of transcripts negatively associated with age were primarily enriched for cardiac metabolism, including oxidative phosphorylation, tricarboxylic acid cycle, glycolysis, and fatty-acid {beta}-oxidation. Transcripts positively correlated with age suggest upregulation of glucose uptake, pentose phosphate pathway, and hexosamine biosynthetic pathway (HBP), indicating a metabolic shift towards glucose-dependent anabolic pathways. Upregulation of HBP commonly results in increased glycosaminoglycan precursor synthesis. Transcripts involved in glycosaminoglycan synthesis, modification, and intermediate metabolism were also upregulated in older animals, while glycosaminoglycan degradation transcripts were downregulated with age. These alterations would promote glycosaminoglycan accumulation, which was verified histologically. Upregulation of extracellular matrix (ECM)-induced signaling pathways temporally coincided with glycosaminoglycan accumulation. We found a subsequent upregulation of cardiac hypertrophy-related pathways and an increase in cardiomyocyte width. Overall, our findings revealed a transcriptional shift in metabolism from catabolic to anabolic pathways that leads to ECM glycosaminoglycan accumulation through HBP prior to upregulation of transcripts of cardiac hypertrophy-related pathways. This study illuminates cellular mechanisms that precede development of cardiac hypertrophy, providing novel potential targets to remediate age-related cardiac diseases.

molecular biology↗

bioRxiv2023

FFCM-MRF: An accurate and generalizable cerebrovascular segmentation pipeline for humans and rhesus monkeys based on TOF-MRA

PurposeCerebrovascular segmentation and quantification of vascular morphological features on humans and rhesus monkeys are essential for prevention, diagnosis, and treatment of brain diseases. However, current automated whole-brain vessel segmentation methods are often not generalizable to independent datasets, limiting their usefulness in real-world environments with their heterogeneity in participants, scanners, and species. Materials and MethodsIn this study, we proposed an automated, accurate and generalizable segmentation method for magnetic resonance angiography images called FFCM-MRF. This method integrates fast fuzzy c-means clustering and Markov random field optimization using blood vessel shape priors and spatial constraints. We used a total of 123 human and 44 macaque MRA images scanned at 1.5 T, 3 T, and 7 T MRI from 9 datasets to develop and validate the method. ResultsThe average Dice score coefficients for multiple independent datasets were 69.16-89.63%, with the improvements in FFCM-MRF ranged from 0.16-16.14% compared with state-of-the-art machine learning methods. Quantitative analysis showed that FFCM-MRF can accurately segment major arteries in the Circle of Willis at the base of the brain and smaller distal pial arteries while effectively suppressing noise. Test-retest analysis showed that the model yielded high vascular volume and diameter reliability. ConclusionsOur results demonstrate that the proposed method is highly accurate and reliable and largely independent of variations in field strength, scanner platforms, acquisition parameters, and species. The macaque MRA data and user-friendly open-source toolbox are freely available at OpenNeuro and GitHub to facilitate studies of imaging biomarkers for cerebrovascular and neurodegenerative diseases.

neuroscience↗

bioRxiv2023

Study on genetic differentiation of Schistosome japonicum intermediate hosts Oncomelania hupensis robertsoni in hilly regions of China: using the complete mitochondrial genome

ObjectiveOncomelania hupensis robertsoni is the only intermediate host of Schistosoma japonicum in western China, its genetic differentiation directly impacts the susceptibility of Schistosoma japonicum. This study aimed to sequence the complete mitochondrial genome of Oncomelania hupensis robertsoni Yunnan strain and analyze the genetic differentiation of Oncomelania hupensis robertsoni in hilly regions of China. MethodsSamples were from 14 administrative villages in Yunnan Province of China, with 30 Oncomelania hupensis per village, and the complete mitochondrial genome was sequenced. Additional, we retrieved 14 other region Oncomelania hupensis of complete mitochondrial sequences from GenBank, and a comprehensive analysis of the genetic differentiation of Oncomelania hupensis robertsoni was conducted by constructing phylogenetic trees, calculating genetic distances, and analyzing homogeneity. ResultsA total of 26 complete mitochondrial sequences were determined. The length of genome ranged from 15,181 to 15,187 bp, and the base composition of the genome was A+T (67.5%) and G+C content (32.5%). This genome encoded 37 genes, including 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes and a non-coding region rich in A+T. Using the Philippines genotypes as outgroup, the phylogenetic trees and homology analysis confirmed the existence of two distinct phylogroups, Oncomelania hupensis robertsoni and the remaining 9 provincial genotypes. Oncomelania hupensis robertsoni is subdivided into Oncomelania hupensis robertsoni Yunnan strain and Sichuan strain, with a genetic distance of 0.0834. Oncomelania hupensis robertsoni Yunnan strain is subdivided into two subbranches, "Yunnan North" and "Yunnan South", with a genetic distance of 0.0216, and the samples exhibited over 97% homology. ConclusionOncomelania hupensis robertsoni Yunnan strain exhibits a higher level of genetic homology and clear north-south differentiation, the distribution characteristics were closely associated with watershed distribution. This work reported the first mitochondrial genome of Oncomelania hupensis robertsoni Yunnan strain, which could be used as an important reference genome for Oncomelania hupensis, and also provide a theoretical basis for explaining the distribution pattern of Oncomelania hupensis robertsoni and control of schistosomiasis. Author SummaryOncomelania hupensis (O. hupensis) is the only intermediate host of Schistosoma japonicum (S. japonicum), O. hupensis residing in different geographical regions display morphological differences and genetic variations, along with varying susceptibility to S. japonicum. In this study, we sequenced 26 complete mitochondrial genome of O. hupensis robertsoni Yunnan strain (O. h. r. Yunnan strain), the length of genome ranged from 15,181 to 15,187 bp, and the base composition of the genome was A+T (67.5%) and G+C content (32.5%). This genome encoded 37 genes, including 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes and a non-coding region rich in A+T. Additional, we retrieved 14 other region O. hupensis of complete mitochondrial sequences from GenBank. The phylogenetic trees and homology analysis confirmed that O. hupensis robertsoni is subdivided into Yunnan strain and Sichuan strain, and O. h. r. Yunnan strain is subdivided into two subbranches, "Yunnan North" and "Yunnan South", the samples exhibited over 97% homology. This work reported the first mitochondrial genome of O. h. r. Yunnan strain, which could be used as an important reference genome for O. hupensis, and also provide a molecular biology-based theoretical foundation for understanding the genetic differentiation of O. hupensis.

genomics↗

bioRxiv2023

LEAFY interacts with WHEAT ORTHOLOG OF APO1 to regulate spikelet number per spike in wheat

In wheat, the transition of the inflorescence meristem to a terminal spikelet (IM[->]TS) determines the spikelet number per spike (SNS), an important yield component. In this study, we demonstrate that the plant-specific transcription factor LEAFY (LFY) physically and genetically interacts with WHEAT ORTHOLOG OF APO1 (WAPO1) to regulate SNS and floret development. Loss-of-function mutations in either or both genes result in significant and similar reductions in SNS, as a result of a reduction in the rate of spikelet meristems formation per day. SNS is also modulated by significant genetic interactions between LFY and SQUAMOSA MADS-box genes VRN1 and FUL2, which promote the IM[->]TS transition. Single-molecule fluorescence in-situ hybridization revealed a down-regulation of LFY and up-regulation of the SQUAMOSA MADS-box genes in the distal part of the developing spike during the IM[->]TS transition, supporting their opposite roles in the regulation of SNS in wheat. Concurrently, the overlap of LFY and WAPO1 transcription domains in the developing spikelets contributes to normal floret development. Understanding the genetic network regulating SNS is a necessary first step to engineer this important agronomic trait. SUMMARY STATEMENTThe plant specific transcription factor LEAFY plays an important role in the regulation of the number of spikelets per spike in wheat.

plant biology↗

bioRxiv2023

Molecular Connectomics Reveals a Glucagon-Like Peptide 1 Sensitive Neural Circuit for Satiety

Liraglutide and other agonists of the glucagon-like peptide 1 receptor (GLP-1RAs) are effective weight loss drugs, but how they suppress appetite remains unclear. One potential mechanism is by activating neurons which inhibit hunger-promoting Agouti-related peptide (AgRP) neurons of the arcuate hypothalamus (Arc). To identify these afferents, we developed a method combining rabies-based connectomics with single-nuclei transcriptomics. Applying this method to AgRP neurons predicted at least 21 afferent subtypes in the mouse mediobasal and paraventricular hypothalamus. Among these are Trh+ Arc neurons (TrhArc), inhibitory neurons which express the Glp1r gene and are activated by the GLP-1RA liraglutide. Activating TrhArc neurons inhibits AgRP neurons and feeding in an AgRP neuron-dependent manner. Silencing TrhArc neurons causes over-eating and weight gain and attenuates liraglutides effect on body weight. Our results demonstrate a widely applicable method for molecular connectomics, comprehensively identify local inputs to AgRP neurons, and reveal a circuit through which GLP-1RAs suppress appetite.

neuroscience↗

bioRxiv2023

A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits (low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides) in 61,861 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered new associations with lipid traits missed by single-trait analysis, including rare variants within an enhancer of NIPSNAP3A and an intergenic region on chromosome 1.

genetics↗

bioRxiv2023

Legionella pneumophila exploits the endo-lysosomal network for phagosome biogenesis by co-opting SUMOylated Rab7

L. pneumophila strains harboring wild-type rpsL such as Lp02rpsLWT cannot replicate in mouse bone marrow-derived macrophages (BMDMs) due to induction of extensive lysosome damage and apoptosis. The mechanism of this unique infection-induced cell death remains unknown. Using a genome-wide CRISPR/Cas9 screening, we identified Hmg20a and Nol9 as host factors important for restricting strain Lp02rpsLWT in BMDMs. Depletion of Hmg20a protects macrophages from infection-induced lysosomal damage and apoptosis, allowing productive bacterial replication. The restriction imposed by Hmg20a was mediated by repressing the expression of several endo-lysosomal proteins, including the small GTPase Rab7. We found that SUMOylated Rab7 is recruited to the bacterial phagosome via SulF, a Dot/Icm effector that harbors a SUMO-interacting motif (SIM). Moreover, overexpression of Rab7 rescues intracellular growth of strain Lp02rpsLWT in BMDMs. Our results establish that L. pneumophila exploits the lysosomal network for the biogenesis of its phagosome in BMDMs.

microbiology↗

bioRxiv2023

Investigating the neural effects of typicality and predictability for face and object stimuli

The brain calibrates itself based on the past stimulus diet, which makes frequently observed stimuli appear as typical (as opposed to uncommon stimuli, which appear as distinctive). Based on predictive processing theory, the brain should be more "prepared" for typical exemplars, because these contain information that has been encountered frequently, and allow to economically represent items of that category. Thus, one could ask whether predictability and typicality of visual stimuli interact, or rather act in an additive manner. We adapted the design by Egner and colleagues (2010), who used cues to induce expectations about stimulus category (face vs. chair) occurrence during an orthogonal inversion detection task. We measured BOLD responses with fMRI in 35 participants. First, distinctive stimuli always elicited stronger responses than typical ones in all ROIs, and our whole-brain directional contrasts for the effects of typicality and distinctiveness converge with previous findings. Second and importantly, we could not replicate the interaction between category and predictability reported by Egner et al. (2010), which casts doubt on whether cueing designs are ideal to elicit reliable predictability effects. Third, likely as a consequence of the lack of predictability effects, we found no interaction between predictability and typicality in any of the four tested regions (bilateral fusiform face areas, lateral occipital complexes) when considering both categories, nor in the whole brain. We discuss the issue of replicability in neuroscience and sketch an agenda for how future studies might address the same question.

neuroscience↗

bioRxiv2023

GRAMD2+ alveolar type I cell plasticity facilitates cell state transitions in organoid culture

Alveolar epithelial regeneration is critical for normal lung function and becomes dysregulated in disease. While alveolar type 2 (AT2) and club cells are known distal lung epithelial progenitors, determining if alveolar epithelial type 1 (AT1) cells also contribute to alveolar regeneration has been hampered by lack of highly specific mouse models labeling AT1 cells. To address this, the Gramd2CreERT2 transgenic strain was generated and crossed to RosamTmG mice. Extensive cellular characterization, including distal lung immunofluorescence and cytospin staining, confirmed that GRAMD2+ AT1 cells are highly enriched for green fluorescent protein (GFP). Interestingly, Gramd2CreERT2 GFP+ cells were able to form organoids in organoid co-culture with Mlg fibroblasts. Temporal scRNAseq revealed that Gramd2+ AT1 cells transition through numerous intermediate lung epithelial cell states including basal, secretory and AT2 cell in organoids while acquiring proliferative capacity. Our results indicate that Gramd2+ AT1 cells are highly plastic suggesting they may contribute to alveolar regeneration.

cell biology↗

bioRxiv2023

Regulated Cleavage and Relocation of FERONIA Control Immunity in Arabidopsis Roots

Plant roots exhibit localized immunity (LI) specifically in the root cap and transition/elongation zone (TZ/EZ). Such immunity relies on receptor-like kinases localized at the plasma membrane (PM), which are essential for plant response to bacteria in the rhizosphere. Here, we identified a new mechanism of action for receptor kinase FERONIA (FER) in LI. In the absence of bacterial stimuli, FER is localized to the PM, maintaining plant growth. When confronted with bacterial colonization, RALF23 peptide hyper-accumulates in TZ/EZ cells and activates a metalloproteinase that cleaves FER and transfer the cytosolic kinase domain into the nucleus. The nucleus-localized kinase domain of FER contributes to LI by reducing bacterial abundance at TZ/EZ. Thus, this work uncovered a unique mechanism by which a single receptor kinase acts in two molecular forms and two distinct subcellular locations to balance growth and immunity. One Sentence SummaryBacteria induces the cleavage of FER via At2-MMP to trigger a localized immunity around TZ and EZ of Arabidopsis roots.

plant biology↗

bioRxiv2023

An interface-based molecular generative framework for protein-protein interaction inhibitors

Protein-protein interactions (PPIs) play a crucial role in numerous biochemical and biological processes. Although several structure-based molecular generative models have been developed, PPI interfaces and compounds targeting PPIs exhibit distinct physicochemical properties compared to traditional binding pockets and small-molecule drugs. As a result, generating compounds that effectively target PPIs, particularly by considering PPI complexes or interface hotspot residues, remains a significant challenge. In this work, we constructed a comprehensive dataset of PPI interfaces with active and inactive compound pairs. Based on this, we propose a novel molecular generative framework tailored to PPI interfaces, named GENiPPI. Our evaluation demonstrates that GENiPPI captures the implicit relationships between the PPI interfaces and the active molecules, and can generate novel compounds that target these interfaces. Moreover, GENiPPI can generate structurally diverse novel compounds with limited PPI interface modulators. To the best of our knowledge, this is the first exploration of a structure-based molecular generative model focused on PPI interfaces, which could facilitate the design of PPI modulators. The PPI interface-based molecular generative model enriches the existing landscape of structure-based (pocket/interface) molecular generative model.

bioinformatics↗

bioRxiv2023

G6PD Maintains Redox Homeostasis and Biosynthesis in LKB1-Deficient KRAS-Driven Lung Cancer

Cancer cells depend on nicotinamide adenine dinucleotide phosphate (NADPH) to combat oxidative stress and support reductive biosynthesis. One major NAPDH production route is the oxidative pentose phosphate pathway (committed step: glucose-6-phosphate dehydrogenase, G6PD). Alternatives exist and can compensate in some tumors. Here, using genetically-engineered lung cancer model, we show that ablation of G6PD significantly suppresses KrasG12D/+;Lkb1-/-(KL) but not KrasG12D/+;p53-/- (KP) lung tumorigenesis. In vivo isotope tracing and metabolomics revealed that G6PD ablation significantly impaired NADPH generation, redox balance and de novo lipogenesis in KL but not KP lung tumors. Mechanistically, in KL tumors, G6PD ablation caused p53 activation that suppressed tumor growth. As tumor progressed, G6PD-deficient KL tumors increased an alternative NADPH source, serine-driven one carbon metabolism, rendering associated tumor-derived cell lines sensitive to serine/glycine depletion. Thus, oncogenic driver mutations determine lung cancer dependence on G6PD, whose targeting is a potential therapeutic strategy for tumors harboring KRAS and LKB1 co-mutations.

cancer biology↗

bioRxiv2023

In silico MS/MS prediction for peptidoglycan profiling uncovers novel anti-inflammatory peptidoglycan fragments of the gut microbiota

Peptidoglycan is an essential exoskeletal polymer present across all bacteria. The gut microbiota-derived peptidoglycan fragments (PGNs) are increasingly recognized as key effector molecules that impact host biology, offering attractive yet untapped potential to combat microbiome-associated diseases in humans. Unfortunately, comprehensive peptidoglycan profiling of gut bacteria has been hampered by the lack of a robust and automated analysis workflow. Currently, PGN identification still relies on manual deconvolutions of acquired tandem mass spectrometry (MS/MS) data, which are highly laborious and inconsistent. Recognizing the unique sugar and amino acid makeup of bacterial peptidoglycan and guided by the experimental MS/MS fragmentation patterns of known PGNs, we developed a computational tool PGN_MS2 that reliably simulates MS/MS spectra of PGNs. Integrating PGN_MS2 into the customizable in silico PGN database, we built an open-access PGN MS library of predicted MS/MS spectra for all molecules in the user-defined in silico PGN search space. With this library, automated searching and spectral matching can be used to identify PGN. We then performed comprehensive peptidoglycan profiling for several gut bacteria species, revealing distinct PGN structural features that may be implicated in microbiota-host crosstalk. Strikingly, the probiotic Bifidobacterium spp. has an exceedingly high proportion of anhydro-PGNs, which exhibit anti-inflammatory effects in vitro. We further identified MltG and RfpB homologs in Bifidobacterium as lytic transglycosylases (LTs), which demonstrate distinct substrate preferences to produce anhydro-PGNs. Overall, our novel PGN_MS2 prediction tool contributes to the robust and automated peptidoglycan analysis workflow, advancing efforts to elucidate the structures and functions of gut microbiota-derived PGNs in the host.

microbiology↗

bioRxiv2023

SC-Track: a robust cell tracking algorithm for generating accurate single cell linages from diverse cell segmentations

Computational analysis of fluorescent timelapse microscopy images at the single-cell level is a powerful approach to study cellular changes that dictate important cell fate decisions. Core to this approach is the need to generate reliable cell segmentations and classifications necessary for accurate quantitative analysis. Deep learning-based convolutional neural networks (CNNs) have emerged as a promising solution to these challenges. However, current CNNs are prone to produce noisy cell segmentations and classifications, which is a significant barrier to constructing accurate single-cell lineages. To address this, we developed a novel algorithm called Single Cell Track (SC-Track), which employs a hierarchical probabilistic cache cascade model based on biological observations of cell division and movement dynamics. Our results show that SC-Track performs better than a panel of publicly available cell trackers on a diverse set of cell segmentation types. This cell-tracking performance was achieved without any parameter adjustments, making SC-Track an excellent generalised algorithm that can maintain robust cell-tracking performance in varying cell segmentation qualities, cell morphological appearances and imaging conditions. Furthermore, SC-Track is equipped with a cell class correction function to improve the accuracy of cell classifications in multi-class cell segmentation time series. These features together make SC-Track a robust cell-tracking algorithm that works well with noisy cell instance segmentation and classification predictions from CNNs to generate accurate single-cell lineages and classifications.

bioinformatics↗

bioRxiv2023

Association of leaf spectral variation with functional genetic variants

The application of in-field and aerial spectroscopy to assess functional and phylogenetic variation in plants has led to novel ecological insights and supports global assessments of plant biodiversity. Understanding how plant genetic variation influences reflectance spectra will help harness this potential for biodiversity monitoring and improve understanding of why plants differ in functional responses to environmental change. Here, we use a well-resolved genetic mapping population derived from Multi-parent Advanced Generation Inter-cross (MAGIC) lines of Nicotiana attenuata to associate genetic differences with differences in leaf spectra between plants in a field experiment in their natural environment. We analyzed the leaf reflectance spectra using a hand-held spectroradiometer (350-2500 nm) on 616 fully genotyped plants of N. attenuata grown in a randomized block design. We tested three approaches to conducting Genome-Wide Association Studies on spectral variants. We introduce a new Hierarchical Spectral Clustering with Parallel Analysis (HSC-PA) method. This method efficiently captured the variation in our high-dimensional dataset and allowed us to discover a novel association, between a locus on chromosome 1 and the 734-1143 nm spectral range, spanning the red-edge and near-infrared regions that are sensitive to leaf structure and photosynthetic activity. This locus contains a candidate gene annotated as carbonic anhydrase, an enzyme involved in CO2 hydration and regulation of photosynthetic efficiency, suggesting a physiological link between variation in leaf optical properties and carbon assimilation. In contrast, an approach treating single wavelengths as phenotypes identified the same associations as HSC-PA, but without the statistical power to pinpoint significant associations. An index-based approach, which reduces complex spectra to a few dimensionless variables, detected two significant associations for ARDSI_Cw (a water-content-related index) with loci on chromosome 1 near genes annotated as a Zeta toxin domain-containing protein, and an Exocyst subunit Exo70 family protein. While these findings are biologically plausible, they represent a very narrow subset of the spectral variation captured by HSC-PA. The HSC-PA approach supports a comprehensive understanding of the genetic determinants of leaf spectral variation which is data-driven but human-interpretable, and lays a robust foundation for future research in linking plant genetics with biodiversity monitoring, large-scale ecological assessment and remote-sensing applications.

ecology↗

bioRxiv2023

Comparative single-cell analysis reveals IFN-γ as a driver of respiratory sequelae post COVID-19

Post-acute sequelae of SARS-CoV-2 infection (PASC) represents an urgent public health challenge, with its impact resonating in over 60 million individuals globally. While a growing body of evidence suggests that dysregulated immune reactions may be linked with PASC symptoms, most investigations have primarily centered around blood studies, with few focusing on samples derived from post-COVID affected tissues. Further, clinical studies alone often provide correlative insights rather than causal relationships. Thus, it is essential to compare clinical samples with relevant animal models and conduct functional experiments to truly understand the etiology of PASC. In this study, we have made comprehensive comparisons between bronchoalveolar lavage fluid (BAL) single-cell RNA sequencing (scRNAseq) data derived from clinical PASC samples and relevant PASC mouse models. This revealed a strong pro-fibrotic monocyte-derived macrophage response in respiratory PASC (R-PASC) in both humans and mice, and abnormal interactions between pulmonary macrophages and respiratory resident T cells. IFN-{gamma} emerged as a key node mediating the immune anomalies in R-PASC. Strikingly, neutralizing IFN-{gamma} post the resolution of acute infection reduced lung inflammation, tissue fibrosis, and improved pulmonary gas-exchange function in two mouse models of R-PASC. Our study underscores the importance of performing comparative analysis to understand the root cause of PASC for developing effective therapies.

immunology↗

bioRxiv2023

Inhibiting endothelial cell Mst1 attenuates acute lung injury in mice

BackgroundLung endothelium plays a pivotal role in the orchestration of inflammatory and injury responses to acute pulmonary insults. Mammalian sterile 20-like kinase 1 (Mst1), a mammalian homolog of Hippo, is a serine/threonine kinase that is ubiquitously expressed in many tissues and has been shown to play an important role in the regulation of apoptosis, inflammation, stress responses, and organ growth. While Mst1 exhibits high expression in the lung, its involvement in the endothelial response to pulmonary insults remains largely unexplored. MethodsMst1 activity was assessed in lung endothelium by western blot. Mst1 endothelial specific knockout mice and a pharmacological inhibitor were employed to assess the effects of Mst1 on homeostatic and lipopolysaccharide (LPS)-induced endothelial responses. Readouts for these studies included various assays, including NF-{kappa}B activation and levels of various inflammatory cytokines and adhesion molecules. The role of Mst1 in lung injury was evaluated in a LPS-induced murine model of acute lung injury (ALI). ResultsMst1 phosphorylation was significantly increased in lung endothelial cells after exposure to tumor necrosis factor (TNF)-alpha (TNF-) and mouse lung tissues after LPS exposure. Overexpression of full length Mst1 or its kinase domain promoted nuclear factor kappaB (NF-{kappa}B) activation through promoting JNK and p38 activation, whereas dominant negative forms of Mst1 (DN-Mst1) attenuated endothelial responses to TNF- and interleukin-1{beta}. Consistent with this, targeted deletion of Mst1 in lung endothelium reduced lung injury to LPS in mice. Similarly, wild-type mice were protected from LPS-induced lung injury following treatment with a pharmacological inhibitor of Mst1/2. ConclusionsOur findings identified Mst1 kinase as a key regulator in the control of lung EC activation and suggest that therapeutic strategies aimed at inhibiting Mst1 activation might be effective in the prevention and treatment of lung injury to inflammatory insults.

physiology↗

bioRxiv2023

RCoV19: A One-stop Hub for SARS-CoV-2 Genome Data Integration, Variants Monitoring, and Risk Pre-warning

The Resource for Coronavirus 2019 (RCoV19, https://ngdc.cncb.ac.cn/ncov/) is an open-access information resource dedicated to providing valuable data on the genomes, mutations, and variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this updated implementation of RCoV19, we have made significant improvements and advancements over the previous version. Firstly, we have implemented a highly refined genome data curation model. This model now features an automated integration pipeline and optimized curation rules, enabling efficient daily updates of data in RCoV19. Secondly, we have developed a global and regional lineage evolution monitoring platform, alongside an outbreak risk pre-warning system. These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns, enabling better preparedness and response strategies. Thirdly, we have developed a powerful interactive mutation spectrum comparison module. This module allows users to compare and analyze mutation patterns, assisting in the detection of potential new lineages. Furthermore, we have incorporated a comprehensive knowledgebase on mutation effects. This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations. In summary, RCoV19 serves as a vital scientific resource, providing access to valuable data, relevant information, and technical support in the global fight against COVID-19.

bioinformatics↗