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Cai, G.

Publications and source records attributed to Cai, G..

At least 37 records · Page 2Linked to original sources

Pharmacologic Inhibition of Ferroptosis Attenuates Experimental Abdominal Aortic Aneurysm Formation

The pathogenesis of abdominal aortic aneurysm (AAA) formation involves vascular inflammation, thrombosis formation and programmed cell death leading to aortic remodeling. Recent studies have suggested that ferroptosis, an excessive iron-mediated cell death, can regulate cardiovascular diseases, including AAAs. However, the role of ferroptosis in immune cells, like macrophages, and ferroptosis-related genes in AAA formation remains to be deciphered. Single cell-RNA sequencing of human aortic tissue from AAA patients demonstrates significant differences in ferroptosis-related genes compared to control aortic tissue. Using two established murine models of AAA and aortic rupture in C57BL/6 (WT) mice, we observed that treatment with liproxstatin-1, a specific ferroptosis inhibitor, significantly attenuated aortic diameter, pro-inflammatory cytokine production, immune cell infiltration (neutrophils and macrophages), increased smooth muscle cell -actin expression and elastic fiber disruption compared to mice treated with inactivated elastase in both pre-treatment and treatment after a small AAA had already formed. Lipidomic analysis using mass spectrometry shows a significant increase in ceramides and a decrease in intact lipid species levels in murine tissue compared to controls in the chronic AAA model on day 28. Mechanistically, in vitro studies demonstrate that liproxstatin-1 treatment of macrophages mitigated the crosstalk with aortic smooth muscle cells (SMCs) by downregulating MMP2 secretion. Taken together, this study demonstrates that pharmacological inhibition by liproxstatin-1 mitigates macrophage-dependent ferroptosis contributing to inhibition of aortic inflammation and remodeling during AAA formation.

immunology↗

Lipoxin A4/FPR2 signaling mitigates ferroptosis of alveolar epithelial cells via NRF2-dependent pathway during lung ischemia-reperfusion injury

BACKGROUNDPost-lung transplantation (LTx) injury can involve sterile inflammation due to ischemia-reperfusion injury (IRI). We investigated the cell-specific role of ferroptosis (excessive iron-mediated cell death) in mediating lung IRI and determined if specialized pro-resolving mediators such as Lipoxin A4 (LxA4) can protect against ferroptosis in lung IRI. METHODSSingle-cell RNA sequencing of lung tissue from post-LTx patients was analyzed. Lung IRI was evaluated in C57BL/6 (WT), formyl peptide receptor 2 knockout (Fpr2-/-) and nuclear factor erythroid 2-related factor 2 knockout (Nrf2-/-) mice using a hilar-ligation model with or without LxA4 administration. Furthermore, the protective efficacy of LxA4 was evaluated employing a murine orthotopic LTx model and in vitro studies using alveolar type II epithelial (ATII) cells. RESULTSDifferential expression of ferroptosis-related genes was observed in post-LTx patient samples compared to healthy controls. A significant increase in the levels of oxidized lipids and reduction in the levels of intact lipids were observed in mice subjected to IRI compared to shams. Furthermore, pharmacological inhibition of ferroptosis with liproxstatin-1 mitigated lung IRI and lung dysfunction. Importantly, LxA4 treatment attenuated pulmonary dysfunction, ferroptosis and inflammation in WT mice subjected to lung IRI, but not in Fpr2-/- or Nrf2-/-mice, after IRI. In the murine LTx model, LxA4 treatment increased PaO2 levels and attenuated lung IRI. Mechanistically, LxA4-mediated protection involves increase in NRF2 activation and glutathione concentration as well as decrease in MDA levels in ATII cells. CONCLUSIONSLxA4/FPR2 signaling on ATII cells mitigates ferroptosis via NRF2 activation and protects against lung IRI.

immunology↗

Cellular mechanotransduction of human osteoblasts in microgravity

Astronauts experience significant and rapid bone loss as a result of an extended stay in space, making the International Space Station (ISS) the perfect laboratory for studying osteoporosis due to the accelerated nature of bone loss on the ISS. This prompts the question, how does the lack of load due to zero-gravity propagate to bone-forming cells, human fetal osteoblasts (hFOBs), altering their maturation to mineralization? Here, we aim to study the mechanotransduction mechanisms by which bone loss occurs in microgravity. Two automated experiments, 4 microfluidic chips capable of measuring single-cell mechanics of hFOBs via aspiration and cell spheroids incubated in pressure-controlled chambers, were each integrated into a CubeLab deployed to the ISS National Laboratory. For the first experiment, we report protrusion measurements of aspirated cells after exposure to microgravity at the ISS and compare these results to ground control conducted inside the CubeLab. Our analysis revealed slightly elongated protrusions for space samples compared to ground samples indicating softening of hFOB cells in microgravity. In the second experiment, we encapsulated osteoblast spheroids in collagen gel and incubated the samples in pressure-controlled chambers. We found that microgravity significantly reduced filamentous actin levels in the hFOB spheroids. When subjected to pressure, the spheroids exhibited increased pSMAD1/5/9 expression, regardless of the microgravity condition. Moreover, microgravity reduced YAP expression, while pressure increased YAP levels, thus restoring YAP expression for spheroids in microgravity. Our study provides insights into the influence of microgravity on the mechanical properties of bone cells and the impact of compressive pressure on cell behavior and signaling in space.

cell biology↗

MerTK-dependent efferocytosis by monocytic-MDSCs mediates resolution of post-lung transplant injury

ABSTRACTO_ST_ABSRationaleC_ST_ABSPatients with end stage lung diseases require lung transplantation (LTx) that can be impeded by ischemia-reperfusion injury (IRI) leading to subsequent chronic lung allograft dysfunction (CLAD) and inadequate outcomes. ObjectivesWe examined the undefined role of MerTK (receptor Mer tyrosine kinase) on monocytic myeloid-derived suppressor cells (M-MDSCs) in efferocytosis (phagocytosis of apoptotic cells) to facilitate resolution of lung IRI. MethodsSingle-cell RNA sequencing of lung tissue and BAL from post-LTx patients was analyzed. Murine lung hilar ligation and allogeneic orthotopic LTx models of IRI were used with Balb/c (WT), cebpb-/- (MDSC-deficient), Mertk-/- or MerTK-CR (cleavage resistant) mice. Lung function, IRI (inflammatory cytokine and myeloperoxidase expression, immunohistology for neutrophil infiltration), and flow cytometry of lung tissue for efferocytosis of apoptotic neutrophils were assessed in mice. Measurements and Main ResultsA significant downregulation in MerTK-related efferocytosis genes in M-MDSC populations of CLAD patients compared to healthy subjects was observed. In the murine IRI model, significant increase in M-MDSCs, MerTK expression and efferocytosis was observed in WT mice during resolution phase that was absent in cebpb-/- Land Mertk-/- mice. Adoptive transfer of M-MDSCs in cebpb-/- mice significantly attenuated lung dysfunction, and inflammation leading to resolution of IRI. Additionally, in a preclinical murine orthotopic LTx model, increases in M-MDSCs were associated with resolution of lung IRI in the transplant recipients. In vitro studies demonstrated the ability of M-MDSCs to efferocytose apoptotic neutrophils in a MerTK-dependent manner. ConclusionsOur results suggest that MerTK-dependent efferocytosis by M-MDSCs can significantly contribute to the resolution of post-LTx IRI.

immunology↗

Multi-omic characterization of allele-specific regulatory variation in hybrid pigs

Genetic variation in the regulation of gene expression contributes substantially to phenotypic variation. Understanding how variation in DNA sequences and epigentic modifications leads to gene expression variation remains a challenging task. In hybrid animals where cellular environments are homogeneous, differences between the expression of paternal and maternal alleles must be due to cis sequence or epigenic differences. Therefore, hybrid mapping is a powerful approach to efficiently identify and characterize genes under regulation through mechanisms in cis. In this study, using reciprocal crosses of the phenotypically divergent Duroc and Lulai pig breeds, we performed a comprehensive multi-omic characterization of regulatory variation across brain, liver, muscle, and placenta in four developmental stages. We produced one of the largest multi-omic datasets to date in pigs, including 16 whole genome sequenced genomes, 48 whole genome bisulfite sequencing, 168 ATAC-Seq and 168 RNA-Seq samples. We developed a novel read count-based method to reliably assess allele-specific methylation, chromatin accessibility, and RNA expression. We showed that tissue specificity was much stronger than developmental stage specificity in all of DNA methylation, chromatin accessibility, and gene expression. We identified 573 genes showing allele specific expression, including those influenced by parent-of-origin as well as allele genotype effects. By integrating methylation, chromatin accessibility, and gene expression data, many of these allele specific expression can be explained by allele specific methylation and/or chromatin accessibility. This study provides one of the most comprehensive characterizations of regulatory variation across multiple tissues and developmental stages in pigs and offers new opportunity of genetic improvement for this important food animal species.

developmental biology↗

Transcriptomic reprogramming screen identifies SRSF1 as rejuvenation factor

Aging is a complex process that manifests through the time-dependent functional decline of a biological system. Age-related changes in epigenetic and transcriptomic profiles have been successfully used to measure the aging process1,2. Moreover, modulating gene regulatory networks through interventions such as the induction of the Yamanaka factors has been shown to reverse aging signatures and improve cell function3,4. However, this intervention has safety and efficacy limitations for in vivo rejuvenation5,6, underscoring the need for identifying novel age reversal factors. Here, we discovered SRSF1 as a new rejuvenation factor that can improve cellular function in vitro and in vivo. Using a cDNA overexpression screen with a transcriptomic readout we identified that SRSF1 induction reprograms the cell transcriptome towards a younger state. Furthermore, we observed beneficial changes in senescence, proteasome function, collagen production, and ROS stress upon SRSF1 overexpression. Lastly, we showed that SRSF1 can improve wound healing in vitro and in vivo and is linked to organismal longevity. Our study provides a proof of concept for using transcriptomic reprogramming screens in the discovery of age reversal interventions and identifies SRSF1 as a promising target for cellular rejuvenation.

genomics↗

OSCAA: A Two-Dimensional Gaussian Mixture Model for Copy Number Variation Association Analysis

Copy number variants (CNVs) are prevalent in the human genome which provide profound effect on genomic organization and human diseases. Discovering disease associated CNVs is critical for understanding the pathogenesis of diseases and aiding their diagnosis and treatment. However, traditional methods for assessing the association between CNVs and disease risks adopt a two-stage strategy conducting quantitative CNV measurements first and then testing for association, which may lead to biased association estimation and low statistical power, serving as a major barrier in routine genome wide assessment of such variation. In this article, we developed OSCAA, a flexible algorithm to discover disease associated CNVs for both quantitative and qualitative traits. OSCAA employs a two-dimensional Gaussian mixture model that is built upon the principal components from copy number intensities, accounting for technical biases in CNV detection while simultaneously testing for their effect on outcome traits. In OSCAA, CNVs are identified and their associations with disease risk are evaluated simultaneously in a single step, taking into account the uncertainty of CNV identification in the statistical model. Our simulations demonstrated that OSCAA outperformed the existing one-stage method and traditional two-stage methods by yielding a more accurate estimate of the CNV-disease association, especially for short CNVs or CNVs with weak signal. In conclusion, OSCAA is a powerful and flexible approach for CNV association testing with high sensitivity and specificity, which can be easily applied to different traits and clinical risk predictions.

genomics↗

Enhanced neutralization of SARS-CoV-2 XBB sub-lineages and BA.2.86 by a tetravalent COVID-19 vaccine booster

As the SARS-CoV-2 virus continues to evolve, novel XBB sub-lineages such as XBB.1.5, XBB.1.16, EG.5, HK.3 (FLip), and XBB.2.3, as well as the most recent BA.2.86, have been identified and aroused global concern. Understanding the efficacy of current vaccines and the immune systems response to these emerging variants is critical for global public health. In this study, we evaluated the neutralization activities of sera from participants who received COVID-19 inactivated vaccines, or a booster vaccination of the recently approved tetravalent protein vaccine in China (SCTV01E), or had contracted a breakthrough infection with BA.5/BF.7/XBB virus. Comparative analysis of their neutralization profiles against a broad panel of 30 SARS-CoV-2 sub-lineage viruses revealed that strains such as BQ.1.1, CH.1.1, and all the XBB sub-lineages exhibited heightened resistance to neutralization than previous variants, however, despite the extra mutations carried by emerging XBB sub-lineages and BA.2.86, they did not demonstrate significantly increased resistance to neutralization compared to XBB.1.5. Encouragingly, the SCTV01E booster vaccination consistently induced robust and considerably higher neutralizing titers against all these variants than breakthrough infection did. Cellular immunity assays also showed that the SCTV01E booster vaccination elicited a higher frequency of virus-specific memory B cells but not IFN-{gamma} secreting T cells. Our findings underline the importance of developing novel multivalent vaccines to more effectively combat future viral variants.

immunology↗

Matrix stiffness modulates 3D spheroid sorting and burst-like collective migration

While it is known that cells with differential adhesion tend to segregate and preferentially sort, the physical forces governing sorting and invasion in heterogeneous tumors remain poorly understood. To investigate this, we tune matrix confinement, mimicking changes in the stiffness and confinement of the tumor microenvironment, to explore how physical confinement influences individual and collective cell migration in 3D spheroids. High levels of confinement lead to cell sorting while reducing matrix confinement triggers the collective fluidization of cell motion. Cell sorting, which depends on cell-cell adhesion, is crucial to this phenomenon. Burst-like migration does not occur for spheroids that have not undergone sorting, regardless of the degree of matrix confinement. Using computational Self-Propelled Voronoi modeling, we show that spheroid sorting and invasion into the matrix depend on the balance between cell-generated forces and matrix resistance. The findings support a model where matrix confinement modulates 3D spheroid sorting and unjamming in an adhesion-dependent manner, providing insights into the mechanisms of cell sorting and migration in the primary tumor and toward distant metastatic sites.

biophysics↗

Spatial pattern and differential expression analysis with spatial transcriptomic data

The emergence of spatial transcriptomic technologies has opened new avenues to investigate gene activities while preserving the spatial context of tissues. Utilizing data generated by such technologies, the identification of spatially variable (SV) genes is an essential step in investigating tissue landscapes and biological processes. Particularly in typical experimental designs such as case-control or longitudinal studies, identifying SV genes between groups is crucial for discovering significant biomarkers or developing targeted therapies for diseases. However, current methods available for analyzing spatial transcriptomic data are still in their infancy, and none of the existing methods are capable of identifying SV genes between groups. To overcome this challenge, we developed SPADE for spatial pattern and differential expression analysis to identify SV gene in spatial transcriptomic data. SPADE is based on a machine learning model of Gaussian process regression with a gene-specific Gaussian kernel, enabling the detection of SV genes both within and between groups. Through extensive simulations and real data analyses, we have demonstrated the superior performance of SPADE compared to existing methods in detecting SV genes within and between groups. The SPADE source code and documentation are publicly available at https://github.com/thecailab/SPADE.

bioinformatics↗

Considering Zeros in Single Cell Sequencing Data Correlation Analysis

Single-cell sequencing technology has enabled correlation analysis of genomic features at the cellular level. However, high levels of noise and sparsity in single-cell sequencing data make accurate assessment of correlations challenging. This study provides a toolkit, SCSC (https://github.com/thecailab/SCSC), for the estimation of correlation coefficients in single-cell sequencing data. It comprehensively assessed four strategies (classical, non-zero, dropout-weighted, imputation) and the impact of data features in various simulated scenarios. The study found that filtering zeros significantly improves estimation accuracy, and further improvement can be achieved by considering the drop-out probability. In addition, the study also identified data features including expression level, library size, and biological variations that affect correlation estimation.

bioinformatics↗

A statistical learning method for simultaneous copy number estimation and subclone clustering with single cell sequencing data

The availability of single cell sequencing (SCS) enables us to assess intra-tumor heterogeneity and identify cellular subclones without the confounding effect of mixed cells. Copy number aberrations (CNAs) have been commonly used to identify subclones in SCS data using various clustering methods, since cells comprising a subpopulation are found to share genetic profile. However, currently available methods may generate spurious results (e.g., falsely identified CNAs) in the procedure of CNA detection, hence diminishing the accuracy of subclone identification from a large complex cell population. In this study, we developed a CNA detection method based on a fused lasso model, referred to as FLCNA, which can simultaneously identify subclones in single cell DNA sequencing (scDNA-seq) data. Spike-in simulations were conducted to evaluate the clustering and CNA detection performance of FLCNA benchmarking to existing copy number estimation methods (SCOPE, HMMcopy) in combination with the existing and commonly used clustering methods. Interestingly, application of FLCNA to a real scDNA-seq dataset of breast cancer revealed remarkably different genomic variation patterns in neoadjuvant chemotherapy treated samples and pre-treated samples. We show that FLCNA is a practical and powerful method in subclone identification and CNA detection with scDNA-seq data.

genomics↗

Redefinition of archetypal phytoplankton-associated bacteria taxa based on globally distributed dinoflagellates and diatoms

Bacteria colonizing in the phycosphere formed by phytoplankton exudates play important roles in marine ecosystems, yet their taxonomy is poorly defined. Here, we customized the analytical approaches for the microalga-attached microbiotas from 110 diatom and 86 dinoflagellate samples to reveal key bacterial players and their ecological significance in the phycosphere. The results demonstrated a co-occurrence of host-specificity and conservation of phytoplankton-associated bacterial communities, defined 8 diatom- and 23 dinoflagellate-affiliated characteristic genera, as well as identifying 14 core genera prevalent with phytoplankton populations. Further classification of these 14 core genera into three tiers showed their distinct ecological features regarding occupancy, connectivity and community-stabilizing, whilst also matching their inherent metabolic properties. Our study redefines the archetypal phytoplankton-associated bacteria taxa more specifically up to the genus level, highlighting the significance of rarely noticed bacteria in the phycosphere, which is invaluable when selecting target bacteria for studying phytoplankton-bacteria interactions.

microbiology↗

Spanve: an Effective Statistical Method to Detect Spatially Variable Genes in Large-scale Spatial Transcriptomics Data

Depicting gene expression in a spatial context through spatial transcriptomics would be beneficial for inferring cell function mechanisms. The identification of spatially variable genes is a crucial step in leveraging the spatial transcriptome to understand intricate spatial dynamics. In this study, we developed Spanve, a nonparametric statistical method for detecting spatially variable genes in large-scale ST data by quantifying expression differences between spots and their spatial neighbours. This method offers a nonparametric approach to identifying spatial dependencies in gene expression without assuming specific distributions. Compared to traditional methods, Spanve decreases the number of false-positive outcomes, leading to more accurate identification of spatially variable genes. Furthermore, Spanve could facilitate downstream spatial transcriptomics analyses, including spatial domain detection and cell type deconvolution. These results show the broad applications of Spanve in advancing our understanding of spatial gene expression patterns within complex tissue microenvironments. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/527623v3_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@1574cfcorg.highwire.dtl.DTLVardef@7f3f56org.highwire.dtl.DTLVardef@1732a3org.highwire.dtl.DTLVardef@fdaafa_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

Neutralization of SARS-CoV-2 BQ.1.1 and XBB.1.5 by Breakthrough Infection Sera from Previous and Current Waves in China

SARS-CoV-2 is continuing to evolve and diversify, with an array of various Omicron sub-lineages, including BA.5, BA.2.75, BN.1, BF.7, BQ.1, BQ.1.1, XBB and XBB.1.5, now circulating globally at recent time. In this study, we evaluated the neutralization sensitivity of a comprehensive panel of Omicron subvariants to sera from different clinical cohorts, including individuals who received homologous or heterologous booster vaccinations, vaccinated people who had Delta or BA.2 breakthrough infection in previous waves, and patients who had BA.5 or BF.7 breakthrough infection in the current wave in China. All the Omicron subvariants exhibited substantial neutralization evasion, with BQ.1, BQ.1.1, XBB.1, and XBB.1.5 being the strongest escaped subvariants. Sera from Omicron breakthrough infection, especially the recent BA.5 or BF.7 breakthrough infection, exhibited higher neutralizing activity against all Omicron sub-lineages, indicating the chance of BA.5 and BF.7 being entirely replaced by BQ or XBB subvariants in China in a short-term might be low. We also demonstrated that the BQ and XBB subvariants were the most resistant viruses to monoclonal antibodies. Continuing to monitor the immune escape of SARS-CoV-2 emerging variants and developing novel broad-spectrum vaccines and antibodies are still crucial.

immunology↗

An Approach to Identify Expression Quantitative Super Enhancers Using Single-cell Multi-omic Data

Super enhancers (SEs) drive cell identity and disease related genes. However, current methods for studying associations between SE and gene expression are time consuming, costly and with poor scalability. This study formulated a computational approach for screening genome-wide SE-expression associations by analyzing single-cell multi-omic data of transcriptome and H3K27ac histone modification. A pipeline was also constructed for an easy workflow application. Further our application study identified expression correlated SEs (eSEs) in brain and found they mark cell types. Moreover, our analysis provided new insights into the functional role of SEs close to Kcnip4 and Nifb1 in frontal cortex neurons and CGE derived inhibitory neurons, linking to neuron development and neurological diseases. Collectively, this study provides a new tool for studying SE-expression associations and identifying significant expression associated SEs, which pave the way for understanding the regulatory role of SEs in gene expression and related cellular and disease development.

bioinformatics↗

MATTE: anti-noise module alignment for phenotype-gene-related analysis

PurposeAlthough many transcriptome analysis methods find fundamental interactions or markers of some phenotypes, preservation of module or network is still a challenge. MethodsThe study developed a method to directly compare the transcriptome data of phenotypes and present the differences modularly, called Module Alignment of TranscripTomE(MATTE). ResultsMATTE performs better under high noise than differential co-expression(DC) clustering in the simulation experiments but still detects differential expression(DE) and DC genes. After subsequent annotation of cell types in single-cell data, MATTE obtained the best scores in both supervised and unsupervised learning, i. e. MATTE found meaningful markers. Finally, we apply MATTE in analyzing the transcriptome of Breast Cancer(BRCA). We have found five BRCA subtypes, and the characteristic of one subtype is detected in the form of a module network. ConclusionMATTE can find meaningful genes and modules, thus facilitating the downstream analysis task to obtain insight into biology.

bioinformatics↗