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Cai, P.

Publications and source records attributed to Cai, P..

30 records · Page 2Linked to original sources

DESpace: spatially variable gene detection via differential expression testing of spatial clusters

MotivationSpatially resolved transcriptomics (SRT) enables scientists to investigate spatial context of mRNA abundance, including identifying spatially variable genes (SVGs), i.e., genes whose expression varies across the tissue. Although several methods have been proposed for this task, native SVG tools cannot jointly model biological replicates, or identify the key areas of the tissue affected by spatial variability. ResultsHere, we introduce DESpace, a framework, based on an original application of existing methods, to discover SVGs. In particular, our approach inputs all types of SRT data, summarizes spatial information via spatial clusters, and identifies spatially variable genes by performing differential gene expression testing between clusters. Furthermore, our framework can identify (and test) the main cluster of the tissue affected by spatial variability; this allows scientists to investigate spatial expression changes in specific areas of interest. Additionally, DESpace enables joint modelling of multiple samples (i.e., biological replicates); compared to inference based on individual samples, this approach increases statistical power, and targets SVGs with consistent spatial patterns across replicates. Overall, in our benchmarks, DESpace displays good true positive rates, controls for false positive and false discovery rates, and is computationally efficient. Availability and implementationDESpace is freely distributed as a Bioconductor R package.

bioinformatics↗

Ipsilateral restriction of chromosome movement along a centrosome, and apical-basal axis during the cell cycle

Little is known about how distance between homologous chromosomes are controlled during the cell cycle. Here, we show that the distribution of centromere components display two discrete clusters placed to either side of the centrosome and apical/basal axis from prophase to G1 interphase. 4-Dimensional live cell imaging analysis of centromere and centrosome tracking reveals that centromeres oscillate largely within one cluster, but do not cross over to the other cluster. We propose a model of an axis-dependent ipsilateral restriction of chromosome oscillations throughout mitosis.

cell biology↗

A systematic investigation of lactic acid bacteria-derived biosynthetic gene clusters reveals diverse antagonistic bacteriocins in the human microbiome

Lactic acid bacteria (LAB) produce various bioactive secondary metabolites (SMs), which endow LAB with a protective role for the host. However, the biosynthetic potentials of LAB-derived SMs remain elusive, particularly in their diversity, abundance, and distribution in the human microbiome. To gain an insight into the biosynthetic capacity of LAB, we analyzed the biosynthetic gene clusters (BGCs) from 31,977 LAB genomes and 748 human microbiome metagenomes, identifying 130,051 BGCs. The found BGCs were clustered into 2,849 gene cluster families (GCFs), most of which are species-specific, niche-specific, and uncharacterized yet. We found that most LAB BGCs encoded bacteriocins with pervasive antagonistic activities predicted by machine learning models, potentially playing protective roles in the human microbiome. Class II bacteriocins, the most abundant LAB SMs, are particularly enriched and predominant in vaginal microbiomes. Together with experimental validation, our metagenomic and metatranscriptomic analysis showed that class II bacteriocins with antagonistic potential might regulate microbial communities in the vagina, thereby contributing to homeostasis. These discoveries of the diverse and prevalent antagonistic SMs are expected to stimulate the mechanism study of LABs protective roles in the host and highlight the potential of LAB as a new source of antibacterial SMs.

bioinformatics↗

Peripheral NOD-like receptor deficient inflammatory macrophages trigger neutrophil infiltration disrupting daytime locomotion

Inflammation is known to disrupt normal behavior, yet the underlying neuroimmune interactions remain elusive. Here, we investigated whether inappropriate macrophage-evoked inflammation alters CNS control of daily-life animal locomotion using a set of zebrafish mutants selected for specific macrophage dysfunction and microglia deficiency. Large-scale genetic and computational analyses revealed that NOD-like receptor nlrc3l mutants are capable of normal motility and visuomotor response, but preferentially swim less in the daytime, suggesting low motivation rather than physical impairment. Examining their brain activities and structures implicate impaired dopaminergic descending circuits, where neutrophils abnormally infiltrate. Furthermore, neutrophil depletion recovered daytime locomotion. Restoring wild-type macrophages reversed behavioral and neutrophil aberrations, while three other microglia-lacking mutants failed to phenocopy nlrc3l mutants. Overall, we reveal how peripheral inflammatory macrophages with elevated pro-inflammatory cues (including il1b, tnfa, cxcl8a) in the absence of microglia co-opt neutrophils to infiltrate the brain, thereby enabling local modulation of neural circuits affecting spontaneous locomotion.

immunology↗

The noncoding RNA PRANCR regulates splicing of Fibronectin-1 to control keratinocyte proliferation and migration

Most human genes undergo alternative splicing (AS), but the regulation and functional consequences of most splicing events remain unknown. Long noncoding RNAs (lncRNAs) have recently been discovered to have novel roles in the regulation of AS. Here we investigate whether PRANCR, a lncRNA recently identified to be essential for epidermis formation, functions by controlling AS of cell fate genes. Using transcriptome-wide analysis, we identified 238 exonic splicing events regulated by PRANCR. Among these is alternative splicing of an exon containing the extra domain A (EDA) in the gene fibronectin-1 (FN1). Expression of the FN1-EDA+ isoform is enriched in proliferating keratinocytes. We find that PRANCR regulates EDA inclusion by controlling expression of the serine/arginine-rich splicing factors (SRSFs) 1 and 7. Depletion of PRANCR or FN1-EDA resulted in decreased proliferation, increased CDKN1A/p21, and inhibition of keratinocyte migration. We find that these cellular phenotypes can be explained by reduced phosphorylation of focal adhesion kinase (FAK). Collectively, these results identify a lncRNA regulating skin function through alternative splicing of a cell fate gene.

cell biology↗

Large-scale single-cell analysis reveals critical immune characteristics of COVID-19 patients

Dysfunctional immune response in the COVID-19 patients is a recurrent theme impacting symptoms and mortality, yet the detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 205 COVID-19 patients and controls to create a comprehensive immune landscape. Lymphopenia and active T and B cell responses were found to coexist and associated with age, sex and their interactions with COVID-19. Diverse epithelial and immune cell types were observed to be virus-positive and showed dramatic transcriptomic changes. Elevation of ANXA1 and S100A9 in virus-positive squamous epithelial cells may enable the initiation of neutrophil and macrophage responses via the ANXA1-FPR1 and S100A8/9-TLR4 axes. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis and designing effective therapeutic strategies for COVID-19. HIGHLIGHTSO_LILarge-scale scRNA-seq analysis depicts the immune landscape of COVID-19 C_LIO_LILymphopenia and active T and B cell responses coexist and are shaped by age and sex C_LIO_LISARS-CoV-2 infects diverse epithelial and immune cells, inducing distinct responses C_LIO_LICytokine storms with systemic S100A8/A9 are associated with COVID-19 severity C_LI

genomics↗

Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, creates an urgent need for identifying molecular mechanisms that mediate viral entry, propagation, and tissue pathology. Cell membrane bound angiotensin-converting enzyme 2 (ACE2) and associated proteases, transmembrane protease serine 2 (TMPRSS2) and Cathepsin L (CTSL), were previously identified as mediators of SARS-CoV2 cellular entry. Here, we assess the cell type-specific RNA expression of ACE2, TMPRSS2, and CTSL through an integrated analysis of 107 single-cell and single-nucleus RNA-Seq studies, including 22 lung and airways datasets (16 unpublished), and 85 datasets from other diverse organs. Joint expression of ACE2 and the accessory proteases identifies specific subsets of respiratory epithelial cells as putative targets of viral infection in the nasal passages, airways, and alveoli. Cells that co-express ACE2 and proteases are also identified in cells from other organs, some of which have been associated with COVID-19 transmission or pathology, including gut enterocytes, corneal epithelial cells, cardiomyocytes, heart pericytes, olfactory sustentacular cells, and renal epithelial cells. Performing the first meta-analyses of scRNA-seq studies, we analyzed 1,176,683 cells from 282 nasal, airway, and lung parenchyma samples from 164 donors spanning fetal, childhood, adult, and elderly age groups, associate increased levels of ACE2, TMPRSS2, and CTSL in specific cell types with increasing age, male gender, and smoking, all of which are epidemiologically linked to COVID-19 susceptibility and outcomes. Notably, there was a particularly low expression of ACE2 in the few young pediatric samples in the analysis. Further analysis reveals a gene expression program shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues, including genes that may mediate viral entry, subtend key immune functions, and mediate epithelial-macrophage cross-talk. Amongst these are IL6, its receptor and co-receptor, IL1R, TNF response pathways, and complement genes. Cell type specificity in the lung and airways and smoking effects were conserved in mice. Our analyses suggest that differences in the cell type-specific expression of mediators of SARS-CoV-2 viral entry may be responsible for aspects of COVID-19 epidemiology and clinical course, and point to putative molecular pathways involved in disease susceptibility and pathogenesis.

bioinformatics↗

Tocilizumab treatment in severe COVID-19 patients attenuates the inflammatory storm incited by monocyte centric immune interactions revealed by single-cell analysis

ABSTRACTDespite the current devastation of the COVID-19 pandemic, several recent studies have suggested that the immunosuppressive drug Tocilizumab can powerfully treating inflammatory responses that occur in this disease. Here, by employing single-cell analysis of the immune cell composition of severe-stage COVID-19 patients and these same patients in post Tocilizumab-treatment remission, we have identified a monocyte subpopulation specific to severe disease that contributes to inflammatory storms in COVID-19 patients. Although Tocilizumab treatment attenuated the strong inflammatory immune response, we found that immune cells including plasma B cells and CD8+ T cells still exhibited an intense humoral and cell-mediated anti-virus immune response in COVID-19 patients after Tocilizumab treatment. Thus, in addition to providing a rich, very high-resolution data resource about the immune cell distribution at multiple stages of the COVID-19 disease, our work both helps explain Tocilizumab’s powerful therapeutic effects and defines a large number of potential new drug targets related to inflammatory storms.Competing Interest StatementJingwen Fang is the executive officer of HanGen BiotechView Full Text

genomics↗

WEDGE: recovery of gene expression values for sparse single-cell RNA-seq datasets using matrix decomposition

The low capture rate of expressed RNAs from single-cell sequencing technology is one of the major obstacles to downstream functional genomics analyses. Recently, a number of imputation methods have emerged for single-cell transcriptome data, however, recovering missing values in very sparse expression matrices remains a substantial challenge. Here, we propose a new algorithm, WEDGE (WEighted Decomposition of Gene Expression), to impute gene expression matrices by using a biased low-rank matrix decomposition method (bLRMD). WEDGE successfully recovered expression matrices, reproduced the cell-wise and gene-wise correlations, and improved the clustering of cells, performing impressively for applications with multiple cell type datasets with high dropout rates. Overall, this study demonstrates a potent approach for imputing sparse expression matrix data, and our WEDGE algorithm should help many researchers to more profitably explore the biological meanings embedded in their scRNA-seq datasets.

bioinformatics↗

Functional classification of noncoding RNAs associated with distinct histone modifications by PIRCh-seq

Many long noncoding RNAs (lncRNAs) regulate gene transcription through binding to histone modification complexes. Therefore, a comprehensive study of nuclear RNAs in a histone modification-specific manner is critical to understand their regulatory mechanisms. Here we develop a method named Profiling Interacting RNAs on Chromatin by deep sequencing (PIRCh-seq), in which we profile chromatin-associated transcriptome in 5 different cell types using antibodies recognizing histone H3 and 6 distinct histone modifications associated with active or repressive chromatin states. PIRCh-seq identified chromatin-associated RNAs with substantially less contamination by nascent transcripts, as compared to existing methods. We classified chromatin-enriched lncRNAs into 6 functional groups based on the patterns of their association with specific histone modifications. LncRNAs were enriched with different chromatin modifications in different cell types, suggesting lncRNAs regulation may also be cell type-specific. By integrating profiles of RNA secondary structure and RNA m6A modification, we found that RNA bases which bind to chromatin tend to be more single stranded. We discovered hundreds of allele-specific RNA-chromatin interactions, nominating specific single nucleotide variants that alter RNA association with chromatin. These results provide a unique resource to globally study the functions of chromatin-associated lncRNAs and elucidate the basic mechanisms of chromatin-RNA interaction.

cell biology↗

APEC: An accesson-based method for single-cell chromatin accessibility analysis

The development of sequencing technologies has promoted the survey of genome-wide chromatin accessibility at single-cell resolution; however, comprehensive analysis of single-cell epigenomic profiles remains a challenge. Here, we introduce an accessibility pattern-based epigenomic clustering (APEC) method, which classifies each individual cell by groups of accessible regions with synergistic signal patterns termed "accessons". By integrating with other analytical tools, this python-based APEC package greatly improves the accuracy of unsupervised single-cell clustering for many different public data sets. APEC also predicts gene expressions, identifies significant differential enriched motifs, discovers super enhancers, and projects pseudotime trajectories. Furthermore, we adopted a fluorescent tagmentation-based single-cell ATAC-seq technique (ftATAC-seq) to investigated the per cell regulome dynamics of mouse thymocytes. Associated with ftATAC-seq, APEC revealed a detailed epigenomic heterogeneity of thymocytes, characterized the developmental trajectory and predicted the regulators that control the stages of maturation process. Overall, this work illustrates a powerful approach to study single-cell epigenomic heterogeneity and regulome dynamics.

bioinformatics↗

Co-culture of soil biofilm isolates enables the discovery of novel antibiotics

Bacterial natural products (NPs) are considered to be a promising source of drug discovery. However, the biosynthesis gene clusters (BGCs) of NP are not often expressed, making it difficult to identify them. Recently, the study of biofilm community showed bacteria may gain competitive advantages by the secretion of antibiotics, implying a possible way to screen antibiotic by evaluating the social behavior of bacteria. In this study, we have described an efficient workflow for novel antibiotic discovery by employing the bacterial social interaction strategy with biofilm cultivation, co-culture, transcriptomic and genomic methods. We showed that a biofilm dominant species, i.e. Pseudomonas sp. G7, which was isolated from cultivated soil biofilm community, was highly competitive in four-species biofilm communities, as the synergistic combinations preferred to exclude this strain while the antagonistic combinations did not. Through the analysis of transcriptomic changes in four-species co-culture and the complete genome of Pseudomonas sp. G7, we finally discovered two novel non-ribosomal polypeptide synthetic (NRPS) BGCs, whose products were predicted to have seven and six amino acid components, respectively. Furthermore, we provide evidence showing that only when Pseudomonas sp. G7 was co-cultivated with at least two or three other bacterial species can these BGC genes be induced, suggesting that the co-culture of the soil biofilm isolates is critical to the discovery of novel antibiotics. As a conclusion, we set a model of applying microbial interaction to the discovery of new antibiotics.

microbiology↗