Biology subjects

Tian, L.

Publications and source records attributed to Tian, L..

At least 163 records · Page 9Linked to original sources

bioRxiv2020

St. Jude Cloud a Pediatric Cancer Genomic Data Sharing Ecosystem

Effective data sharing is key to accelerating research that will improve the precision of diagnoses, efficacy of treatments and long-term survival of pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data sharing ecosystem developed via collaboration between St. Jude Childrens Research Hospital, DNAnexus, and Microsoft, for accessing, analyzing and visualizing genomic data from >10,000 pediatric cancer patients, long-term survivors of pediatric cancer and >800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabyes on St. Jude Cloud include 12,104 whole genomes, 7,697 whole exomes and 2,202 transcriptomes, which are freely available to researchers worldwide. The resource is expanding rapidly with regular data uploads from St. Judes prospective clinical genomics programs, providing public access as soon as possible rather than holding data back until publication. Three interconnected apps within the St. Jude Cloud ecosystem--Genomics Platform, Pediatric Cancer Knowledgebase (PeCan) and Visualization Community--provide a unique experience for simultaneously performing advanced data analysis in the cloud and enhancing the pediatric cancer knowledgebase. We demonstrate the value of the St. Jude Cloud ecosystem through use cases that classify 48 pediatric cancer subtypes by gene expression profiling and map mutational signatures across 35 subtypes of pediatric cancer.

cancer biology↗

bioRxiv2020

Anatomical modeling of brain vasculature in two-photon microscopy by generalizable deep learning

Objective and Impact StatementSegmentation of blood vessels from two-photon microscopy (2PM) angiograms of brains has important applications in hemodynamic analysis and disease diagnosis. Here we develop a generalizable deep learning technique for accurate 2PM vascular segmentation of sizable regions in mouse brains acquired from multiple 2PM setups. The technique is computationally efficient, thus ideal for large-scale neurovascular analysis. IntroductionVascular segmentation from 2PM angiograms is an important first step in hemodynamic modeling of brain vasculature. Existing segmentation methods based on deep learning either lack the ability to generalize to data from different imaging systems, or are computationally infeasible for large-scale angiograms. In this work, we overcome both these limitations by a method that is generalizable to various imaging systems, and is able to segment large-scale angiograms. MethodsWe employ a computationally efficient deep learning framework with a loss function that incorporates a balanced binary-cross-entropy loss and a total variation regularization on the networks output. Its effectiveness is demonstrated on experimentally acquired in-vivo angiograms from mouse brains of dimensions up to 808x808x702 m. ResultsTo demonstrate the superior generalizability of our framework, we train on data from only one 2PM microscope, and demonstrate high-quality segmentation on data from a different microscope without any network tuning. Overall, our method demonstrates 10x faster computation in terms of voxels-segmented-per-second and 3x larger depth compared to the state-of-the-art. ConclusionOur work provides a generalizable and computationally efficient anatomical modeling framework for brain vasculature, which consists of deep learning based vascular segmentation followed by graphing. It paves the way for future modeling and analysis of hemodynamic response at much greater scales that were inaccessible before.

neuroscience↗

bioRxiv2020

Comprehensive characterization of single cell full-length isoforms in human and mouse with long-read sequencing

Alternative splicing shapes the phenotype of cells in development and disease. Long-read RNA-sequencing recovers full-length transcripts but has limited throughput at the single-cell level. Here we developed single-cell full-length transcript sequencing by sampling (FLT-seq), together with the computational pipeline FLAMES to overcome these issues and perform isoform discovery and quantification, splicing analysis and mutation detection in single cells. With FLT-seq and FLAMES, we performed the first comprehensive characterization of the full-length isoform landscape in single cells of different types and species and identified thousands of unannotated isoforms. We found conserved functional modules that were enriched for alternative transcript usage in different cell populations, including ribosome biogenesis and mRNA splicing. Analysis at the transcript-level allowed data integration with scATAC-seq on individual promoters, improved correlation with protein expression data and linked mutations known to confer drug resistance to transcriptome heterogeneity. Our methods reveal previously unseen isoform complexity and provide a better framework for multi-omics data integration.

genomics↗

bioRxiv2020

Single-cell cytometry via multiplexed fluorescence prediction by label-free reflectance microscopy

Traditional imaging cytometry uses fluorescence markers to identify specific structures, but is limited in throughput by the labeling process. Here we develop a label-free technique that alleviates the physical staining and provides highly multiplexed readouts via a deep learning-augmented digital labeling method. We leverage the rich structural information and superior sensitivity in reflectance microscopy and show that digital labeling predicts highly accurate subcellular features after training on immunofluorescence images. We demonstrate up to 3x improvement in the prediction accuracy over the state-of-the-art. Beyond fluorescence prediction, we demonstrate that single-cell level structural phenotypes of cell cycles are correctly reproduced by the digital multiplexed images, including Golgi twins, Golgi haze during mitosis and DNA synthesis. We further show that the multiplexed readouts enable accurate multi-parametric single-cell profiling across a large cell population. Our method can dramatically improve the throughput for imaging cytometry toward applications for phenotyping, pathology, and high-content screening.

bioengineering↗

bioRxiv2020

Endocardial/endothelial angiocrines regulate cardiomyocyte development and maturation and induce features of ventricular non-compaction

Non-compaction cardiomyopathy is a devastating genetic disease caused by insufficient consolidation of ventricular wall muscle that can result in inadequate cardiac performance. Despite being the third most common cardiomyopathy, the mechanisms underlying the disease, including the cell types involved, are poorly understood. We have previously shown that endothelial cell-specific deletion of the chromatin remodeler gene Ino80 results in defective coronary vessel development that leads to ventricular noncompaction in embryonic mouse hearts. Here, we used single-cell RNA-sequencing to characterize endothelial and endocardial defects in Ino80-deficient hearts. We observed a pathological endocardial cell population in the non-compacted hearts, and identified multiple dysregulated angiocrine factors that dramatically affected cardiomyocyte behavior. We identified Col15A1 as a coronary vessel-secreted angiocrine factor, downregulated by Ino80-deficiency, that functioned to promote cardiomyocyte proliferation. Furthermore, mutant endocardial and endothelial cells (ECs) upregulated expression of secreted factors, such as Tgfbi, Igfbp3, Isg15, and Adm, which decreased cardiomyocyte proliferation and increased maturation. These findings support a model where coronary ECs normally promote myocardial compaction through secreted factors, but that endocardial and ECs can secrete factors that contribute to non-compaction under pathological conditions.

developmental biology↗

bioRxiv2020

Inter-determination of blood metabolite levels and gut microbiome supported by Mendelian randomization

The gut microbiome has been implicated in a variety of physiological states, but controversy over causality remains unresolved. Here, we performed bidirectional Mendelian randomization (MR) analyses on 3,432 Chinese individuals with whole genome, whole metagenome, anthropometric, and blood metabolic trait data. We identified 58 causal relationships between the gut microbiome and blood metabolites, and replicated 43 of them. Increased relative abundances of fecal Oscillibacter and Alistipes were causally linked to decreased triglyceride concentration. Conversely, blood metabolites such as glutamic acid appeared to decrease fecal Oxalobacter, and members of Proteobacteria were influenced by metabolites such as 5-methyltetrahydrofolic acid, alanine, glutamate, and selenium. Two-sample MR with data from Biobank Japan partly corroborated results with triglyceride and with uric acid, and also provided causal support for published fecal bacterial markers for cancer and cardiovascular diseases. This study illustrates the value of human genetic information to help prioritize gut microbial features for mechanistic and clinical studies.

genetics↗

bioRxiv2020

The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read tools

Application of Oxford Nanopore Technologies long-read sequencing platform to transcriptomic analysis is increasing in popularity. However, such analysis can be challenging due to small library sizes and high sequence error, which decreases quantification accuracy and reduces power for statistical testing. Here, we report the analysis of two nanopore sequencing RNA-seq datasets with the goal of obtaining gene-level and isoform-level differential expression information. A dataset of synthetic, spliced, spike-in RNAs ("sequins") as well as a mouse neural stem cell dataset from samples with a null mutation of the epigenetic regulator Smchd1 were analysed using a mix of long-read specific tools for preprocessing together with established short-read RNA-seq methods. We used limma-voom to perform differential gene expression analysis, and the novel FLAMES pipeline to perform isoform identification and quantification, followed by DRIMSeq and limma-diffSplice (with stageR) to perform differential transcript usage analysis. We compared results from the sequins dataset to the ground truth, and results of the mouse dataset to a previous short-read study on equivalent samples. Overall, our work shows that transcriptomic analysis of long-read nanopore data using short-read software and methods that are already in wide use can yield meaningful results.

bioinformatics↗

bioRxiv2020

Cell cycle checkpoints cooperate to suppress DNA and RNA associated molecular pattern recognition and anti-tumor immune responses

The DNA dependent pattern recognition receptor, cGAS mediates communication between genotoxic stress and the immune system. Mitotic chromosome missegregation is an established stimulator of cGAS activity, however, it is unclear if progression through mitosis is required for cancer cell intrinsic activation of immune mediated anti-tumor responses. Moreover, it is unknown if disruption of cell cycle checkpoints can restore responses in cancer cells that are recalcitrant to DNA damage induced inflammation. Here we demonstrate that prolonged cell cycle arrest at the G2-mitosis boundary from either CDK1 inhibition or excessive DNA damage prevents inflammatory stimulated gene expression and immune mediated destruction of distal tumors. Remarkably, DNA damage induced inflammatory signaling is restored in a cGAS-and RIG-I-dependent manner upon concomitant disruption of p53 and the G2 checkpoint. These findings link aberrant cell progression and p53 loss to an expanded spectrum of damage associated molecular pattern recognition and have implications for the design of rational approaches to augment antitumor immune responses.

cell biology↗

bioRxiv2020

Personalized vagino-cervical microbiome dynamics after oral probiotics

The vaginal microbiota is presumably much simpler than the gut microbiome, and oral probiotics appear as a promising means to modulate its homeostasis in the general population. Here, 60 women were followed for over a year before, during and after a probiotic containing Lactobacillus rhamnosus GR-1 and L. reuteri RC-14. Shotgun metagenomic data of 1334 samples from multiple body sites did not support colonization of the probiotics to the vagino-cervical microbiome, yet the microbiome was stable in those dominated by Lactobacilli and some individuals have likely benefited from this medication-free intervention.

microbiology↗

bioRxiv2020

The clonal and molecular aetiology of emergency dendritic cell development

Extrinsic regulation of single haematopoietic stem and progenitor cell (HSPC) fate is crucial for immune cell development. Here, we examine the aetiology of Flt3 ligand (Flt3L)-mediated emergency development of type 1 conventional dendritic cells (cDC1s), which results in enhanced immunity against infections and cancer. Using cellular barcoding, we demonstrate a predominant role of enhanced clonal expansion and moderate contribution via recruitment of additional cDC1-generating HSPCs. The selective cDC1 expansion occurs primarily via multi-/oligo-potent clones, without compromising output to other lineages. To understand the molecular hallmarks early during a Flt3L response, we develop Divi-Seq to simultaneously profile cell division history, surface phenotype and transcriptional state of single HSPCs. We discover that Flt3L-responsive HSPCs maintain a proliferative early progenitor-like state, which leads to selective emergence of CD11c+cKit+ transitional precursors with high cellular output to cDC1s. These findings inform the mechanistic action of Flt3L in natural immunity and immunotherapy at a clonal level.

immunology↗

bioRxiv2020

Tyrosine kinase inhibitors induce mitochondrial dysfunction during cardiomyocyte differentiation through alteration of GATA4-mediated networks

Maternal drug exposure during pregnancy increases the risks of developmental cardiotoxicity, leading to congenital heart defects (CHDs). In this study, we used human stem cells as an in-vitro system to interrogate the mechanisms underlying drug-induced toxicity during cardiomyocyte differentiation, including anticancer tyrosine kinase inhibitor (TKI) drugs (imatinib, sunitinib, and vandetanib). H1-ESCs were treated with these drugs at sublethal levels during cardiomyocyte differentiation. We found that early exposure to TKIs during differentiation induced obvious toxic effects in differentiated cardiomyocytes, including disarranged sarcomere structure, interrupted Ca2+-handling, and impaired mitochondrial function. As sunitinib exposure showed the most significant developmental cardiotoxicity of all TKIs, we further examine its effect with in-vivo experiments. Maternal sunitinib exposure caused fetal death, bioaccumulation, and histopathologic changes in the neonatal mice. Integrative analysis of both transcriptomic and chromatin accessibility landscapes revealed that TKI-exposure altered GATA4-mediated regulatory network, which included key mitochondrial genes. Overexpression of GATA4 with CRISPR-activation restored morphologies, contraction, and mitochondria function in cardiomyocytes upon TKI exposure early during differentiation. Altogether, our study identified a novel crosstalk mechanism between GATA4 activity and mitochondrial function during cardiomyocyte differentiation, and revealed potential therapeutic approaches for reducing TKI-induced developmental cardiotoxicity for human health. HighlightsO_LIEarly-stage exposure to TKIs induced cardiotoxicity and mitochondrial dysfunction C_LIO_LIGATA4 transcriptional activity is inhibited by TKIs C_LIO_LINetwork analysis reveals interactions between GATA4 and mitochondrial genes C_LIO_LIGATA4-overexpression rescues cardiomyocytes and mitochondria from TKI exposure C_LI

systems biology↗

bioRxiv2020

Induced Pluripotent Stem Cell-derived CAR-Macrophage Cells with Antigen-dependent Anti-Cancer Cell Functions for Liquid and Solid Tumors

The Chimera antigen receptor (CAR)-T cell therapy has gained great success in the clinic. However, there are still major challenges for its wider applications in a variety of cancer types including lack of effectiveness due to the highly complex tumor microenvironment, and the forbiddingly high cost due to personalized manufacturing procedures. In order to overcome these hurdles, numerous efforts have been spent focusing on optimizing Chimera Antigen Receptors, engineering and improving T cell capacity, exploiting features of subsets of T cell or NK cells, or making off-the-shelf universal T cells. Here, we developed induced pluripotent stem cells (iPSCs)-derived, CAR-expressing macrophage cells (CAR-iMac). These cells showed antigen-dependent macrophage functions such as expression and secretion of cytokines, polarization toward the pro-inflammatory/anti-tumor state, and phagocytosis of tumor cells, as well as some in vivo anti-cancer cell activity for both liquid and solid tumors. This technology platform for the first time provides an unlimited source of iPSC-derived engineered CAR-macrophage cells which could be utilized to eliminate cancer cells or modulate the tumor microenvironment in liquid and solid tumor immunotherapy. One sentence summaryWe developed CAR-expressing iPSC-induced macrophage cells that have antigen-dependent phagocytosis and pro-inflammatory functions and anti-cancer cell activity for both liquid and solid tumor cells.

cell biology↗

bioRxiv2019

Cell-type specific asynchronous modulation of PKA by dopamine during reward based learning

Canonical reinforcement learning models postulate that dopamine neurons encode reward prediction error (RPE) and provide a teaching signal to striatal spiny projection neurons (SPNs) in the form of dopamine (DA) release. DA is thought to guide learning via dynamic modulation of protein kinase A (PKA) in SPNs. However, this fundamental assumption remains untested in behaving animals. Here we utilized multi-channel fiber photometry and fluorescence lifetime photometry (FLiP) to monitor the activity of DA neurons, extracellular DA levels, and net PKA activity in SPNs in the nucleus accumbens during learning. We found dynamic encoding of RPE in the activity of DA neurons, which is both necessary and sufficient to explain striatal DA levels and SPN PKA activity. The modulation of PKA in SPNs that express type-1 (D1R-SPNs) and type-2 (D2R-SPNs) DA receptors was dichotomous such that in each cell class it is selectively sensitive to increases and decreases in DA, respectively, and occur at and support different phases of learning. Thus, PKA-dependent pathways in D1R- and D2R-SPNs are asynchronously engaged by RPE-encoding DA signals to promote different aspects of reinforcement learning: the former responsible for the initial association between action and outcome and the latter responsible for refining the learned association.

neuroscience↗

bioRxiv2019

Over 50000 metagenomically assembled draft genomes for the human oral microbiome reveal new taxa

The oral cavity of each person is home for hundreds of bacterial species. While taxa for oral diseases have been well studied using culture-based as well as amplicon sequencing methods, metagenomic and genomic information remain scarce compared to the fecal microbiome. Here we provide metagenomic shotgun data for 3346 oral metagenomics samples, and together with 808 published samples, assemble 56,213 metagenome-assembled genomes (MAGs). 64% of the 3,589 species-level genome bins contained no publicly available genomes, others with only a handful. The resulting genome collection is representative of samples around the world and across physiological conditions, contained many genomes from Candidate phyla radiation (CPR) which lack monoculture, and enabled discovery of new taxa such as a family within the Acholeplasmataceae order. New biomarkers were identified for rheumatoid arthritis or colorectal cancer, which would be more convenient than fecal samples. The large number of metagenomic samples also allowed assembly of many strains from important oral taxa such as Porphyromonas and Neisseria. Predicted functions enrich in drug metabolism and small molecule synthesis. Thus, these data lay down a genomic framework for future inquiries of the human oral microbiome.

microbiology↗

bioRxiv2019

Single-Cell RNA-Seq Reveals Endocardial Defect in Hypoplastic Left Heart Syndrome

Hypoplastic left heart syndrome (HLHS) is one of the most challenging forms of congenital heart diseases. Previous studies were mainly focused on intrinsic defects in myocardium. However, this does not sufficiently explain the abnormal development of the cardiac valve, septum, and vasculature, known to originate from the endocardium. Here, using single-cell RNA profiling, induced pluripotent stem cells, and human fetal heart tissue with an underdeveloped left ventricle, we identified a developmentally impaired endocardial population in HLHS. The intrinsic endocardial deficits contributed to abnormal endothelial to mesenchymal transition, NOTCH signaling, and extracellular matrix organization, all of which are key factors in valve formation. Consequently, endocardial abnormalities conferred reduced proliferation and maturation of cardiomyocytes through a disrupted fibronectin-integrin interaction. Several recently described HLHS de novo mutations were associated with abnormal endocardial gene and FN1 regulation and expression. Our studies provide a rationale for considering endocardial function in future regenerative strategies for HLHS.

developmental biology↗

bioRxiv2019

Strain-level identification of bacterial tomato pathogens directly from metagenomic sequences

Routine strain-level identification of plant pathogens directly from symptomatic tissue could significantly improve plant disease control and prevention. Here we tested the Oxford Nanopore Technologies (ONT) MinION sequencer for metagenomic sequencing of tomato plants either artificially inoculated with a known strain of the bacterial speck pathogen Pseudomonas syringae pv. tomato (Pto), or collected in the field and showing bacterial spot symptoms caused by either one of four Xanthomonas species. After species-level identification using ONTs WIMP software and the third party tools Sourmash and MetaMaps, we used Sourmash and MetaMaps with a custom database of representative genomes of bacterial tomato pathogens to attempt strain-level identification. In parallel, each metagenome was assembled and the longest contigs were used as query with the genome-based microbial identification Web service LINbase. Both the read-based and assembly-based approaches correctly identified Pto strain T1 in the artificially inoculated samples. The pathogen strain in most field samples was identified as a member of Xanthomonas perforans group 2. This result was confirmed by whole genome sequencing of colonies isolated from one of the samples. Although in our case, metagenome-based pathogen identification at the strain-level was achieved, caution still needs to be exerted when interpreting strain-level results because of the challenges inherent to assigning reads to specific strains and the error rate of nanopore sequencing.

microbiology↗

bioRxiv2019

LINbase: A Web service for genome-based identification of microbes as members of crowdsourced taxa

The development of next generation and third generation DNA sequencing technologies in combination with new efficient algorithms allows scientists to economically, quickly, and precisely identify microbes at all taxonomic levels and even attribute pathogen isolates to specific disease outbreaks. However, current taxonomic practice has not kept up with the sequencing revolution and continues to rely on cumbersome journal publications to describe new species. Here we introduce a Web service that allows any user to genomically circumscribe any monophyletic group of bacteria as a taxon and associate with each taxon a name and short description. Any other user can immediately identify their unknown microbe as a member of any of these crowdsourced taxa using gene or genome sequences. The Web service is called LINbase. It leverages the previously described concept of Life Identification Numbers (LINs), which are codes assigned to individual organisms based on genome similarity. Most genomes currently in LINbase were imported from GenBank, but users have the option to upload their own genome sequences as well. Importantly, LINbase allows users to share the precise identity of their sequenced genomes without sharing the actual genome sequences, making not yet published or private genome sequences discoverable by the scientific community stimulating collaboration between academia and industry. LINbase is available at http://www.LINbase.org.

bioinformatics↗

bioRxiv2019

CSF sTREM2 correlates with CSF tau in advancing Parkinson’s disease

Parkinsons disease (PD) is the second most common neurodegenerative disease after Alzheimers disease (AD) and affects 1% of the population above 60 years old. Although PD commonly manifests with motor symptoms, a majority of patients with PD subsequently develop cognitive impairment which often progresses to dementia, a major cause of morbidity and disability. PD is characterized by -synuclein accumulation that frequently associates with amyloid beta (A{beta}) and tau fibrils, the hallmarks of AD neuropathologic changes; this co-occurrence suggests that onset of cognitive decline in PD may be associated with appearance of pathologic A{beta} and/or tau. Recent studies have highlighted the appearance of the soluble form of the Triggering Receptor Expressed on Myeloid cells 2 (sTREM2) receptor in CSF during development of AD. Given the known association of microglial activation with advancing PD, we investigated whether CSF and/or plasma sTREM2 increased with progression to PD dementia. We examined 165 participants consisting of 17 cognitively normal elderly, 45 PD patients with no cognitive impairment, 86 with mild cognitive impairment, and 17 with dementia. Stratification of subjects by CSF A{beta} and tau levels revealed that CSF sTREM2 concentrations were elevated in PD subgroups with abnormal tau, but not A{beta}, CSF concentration. These findings indicate that CSF sTREM2 could serve as a surrogate immune biomarker of neuronal injury in PD that is associated with cognitive decline.\n\nOne sentence summaryCSF sTREM2 correlates with CSF tau in PD

neuroscience↗