Biology subjects

Quake, S. R.

Publications and source records attributed to Quake, S. R..

At least 19 recordsLinked to original sources

bioRxiv2018

Detection of early stage pancreatic cancer using 5-hydroxymethylcytosine signatures in circulating cell free DNA

Pancreatic cancers are typically diagnosed at late stage where disease prognosis is poor as exemplified by a 5-year survival rate of 8.2%. Earlier diagnosis would be beneficial by enabling surgical resection or earlier application of therapeutic regimens. We investigated the detection of pancreatic ductal adenocarcinoma (PDAC) in a non-invasive manner by interrogating changes in 5-hydroxymethylation cytosine status (5hmC) of circulating cell free DNA in the plasma of a PDAC cohort (n=51) in comparison with a non-cancer cohort (n=41). We found that 5hmC sites are enriched in a disease and stage specific manner in exons, 3UTRs and transcription termination sites. Our data show that 5hmC density is reduced in promoters and histone H3K4me3-associated sites with progressive disease suggesting increased transcriptional activity. 5hmC density is differentially represented in thousands of genes, and a stringently filtered set of the most significant genes points to biology related to pancreas (GATA4, GATA6, PROX1, ONECUT1) and/or cancer development (YAP1, TEAD1, PROX1, ONECUT1, ONECUT2, IGF1 and IGF2). Regularized regression models were built using 5hmC densities in statistically filtered genes or a comprehensive set of highly variable 5hmC counts in genes and performed with an AUC = 0.94-0.96 on training data. We were able to test the ability to classify PDAC and non-cancer samples with the Elastic net and Lasso models on two external pancreatic cancer 5hmC data sets and found validation performance to be AUC = 0.74-0.97. The findings suggest that 5hmC changes enable classification of PDAC patients with high fidelity and are worthy of further investigation on larger cohorts of patient samples.

cancer biology↗

bioRxiv2018

Developmental heterogeneity of microglia and brain myeloid cells revealed by deep single-cell RNA sequencing

Microglia are increasingly recognized for their major contributions during brain development and neurodegenerative disease. It is currently unknown if these functions are carried out by subsets of microglia during different stages of development and adulthood or within specific brain regions. Here, we performed deep single-cell RNA sequencing (scRNA-seq) of microglia and related myeloid cells sorted from various regions of embryonic, postnatal, and adult mouse brains. We found that the majority of adult microglia with homeostatic signatures are remarkably similar in transcriptomes, regardless of brain region. By contrast, postnatal microglia represent a more heterogeneous population. We discovered that postnatal white matter-associated microglia (WAM) are strikingly different from microglia in other regions and express genes enriched in degenerative disease-associated microglia. These postnatal WAM have distinct amoeboid morphology, are metabolically active, and phagocytose newly formed oligodendrocytes. This scRNA-seq atlas will be a valuable resource for dissecting innate immune functions in health and disease.\n\nHighlightsO_LIMyeloid scRNA-seq atlas across brain regions and developmental stages\nC_LIO_LILimited transcriptomic heterogeneity of homeostatic microglia in the adult brain\nC_LIO_LIPhase-specific gene sets of proliferating microglia along cell cycle pseudotime\nC_LIO_LIPhagocytic postnatal white matter-associated microglia sharing DAM gene signatures\nC_LI

neuroscience↗

bioRxiv2018

Modeling Spatial Correlation of Transcripts With Application to Developing Pancreas

Recently high-throughput image-based transcriptomic methods were developed and enabled researchers to spatially resolve gene expression variation at the molecular level for the first time. In this work, we develop a general analysis tool to quantitatively study the spatial correlations of gene expression in fixed tissue sections. As an illustration, we analyze the spatial distribution of single mRNA molecules measured by in situ sequencing on human fetal pancreas at three developmental time points 80, 87 and 117 days post-fertilization. We develop a density profile-based method to capture the spatial relationship between gene expression and other morphological features of the tissue sample such as position of nuclei and endocrine cells of the pancreas. In addition, we build a statistical model to characterize correlations in the spatial distribution of the expression level among different genes. This model enables us to infer the inhibitory and clustering effects throughout different time points. Our analysis framework is applicable to a wide variety of spatially-resolved transcriptomic data to derive biological insights.

bioinformatics↗

bioRxiv2018

Self-assembling Manifolds in Single-cell RNA Sequencing Data

Single-cell RNA sequencing has spurred the development of computational methods that enable researchers to classify cell types, delineate developmental trajectories, and measure molecular responses to external perturbations. Many of these technologies rely on their ability to detect genes whose cell-to-cell variations arise from the biological processes of interest rather than transcriptional or technical noise. However, for datasets in which the biologically relevant differences between cells are subtle, identifying these genes is a challenging task. We present the self-assembling manifold (SAM) algorithm, an iterative soft feature selection strategy to quantify gene relevance and improve dimensionality reduction. We demonstrate its advantages over other state-of-the-art methods with experimental validation in identifying novel stem cell populations of Schistosoma, a prevalent parasite that infects hundreds of millions of people. Extending our analysis to a total of 56 datasets, we show that SAM is generalizable and consistently outperforms other methods in a variety of biological and quantitative benchmarks.

bioinformatics↗

bioRxiv2018

Single cell RNAseq provides a molecular and cellular cartography of changes to the human endometrium through the menstrual cycle

In a human menstrual cycle, the endometrium undergoes remodeling, shedding, and regeneration, all of which are driven by substantial gene expression changes in the underlying cellular hierarchy. Despite its importance in human fertility and regenerative biology, mechanistic understanding of this unique type of tissue homeostasis remains rudimentary. We characterized the transcriptomic transformation of human endometrium at single cell resolution, dissecting the multidimensional cellular heterogeneity of this tissue across the entire natural menstrual cycle. We profiled the behavior of 6 endometrial cell types, including a previously uncharacterized ciliated epithelial cell type, during four major phases of endometrial transformation, and found characteristic signatures for each cell type and phase. We discovered that human window of implantation opens with an abrupt and discontinuous transcriptomic activation in the epithelia, accompanied with widespread decidualized feature in the stromal fibroblasts. These data reveal signatures in the luminal and glandular epithelia during epithelial gland reconstruction, and suggest a mechanism for adult gland formation.

genomics↗

bioRxiv2018

Human IgE producing B cells have a unique transcriptional program and generate high affinity, allergen-specific antibodies

IgE antibodies provide defense against helminth infections, but can also cause life-threatening allergic reactions. Despite their importance to human health, these antibodies and the cells that produce them remain enigmatic due to their scarcity in humans; much of our knowledge of their properties is derived from model organisms. Here we describe the isolation of IgE producing B cells from the blood of individuals with food allergies, followed by a detailed study of their properties by single cell RNA sequencing (scRNA-seq). We discovered that IgE B cells are deficient in membrane immunoglobulin expression and that the IgE plasmablast state is more immature than that of other antibody producing cells. Through recombinant expression of monoclonal antibodies derived from single cells, we identified IgE antibodies which had unexpected cross-reactive specificity for major peanut allergens Ara h 2 and Ara h 3; not only are these among the highest affinity native human antibodies discovered to date, they represent a surprising example of convergent evolution in unrelated individuals who independently evolved nearly identical antibodies. Finally, we discovered that splicing within B cells of all isotypes reveals polarized germline transcription of the IgE, but not IgG4, isotype as well as several examples of biallelic expression of germline transcripts. Our results offer insights into IgE B cell transcriptomics, clonality and regulation, provide a striking example of adaptive immune convergence, and offer an approach for accelerating mechanistic disease understanding by characterizing a rare B cell population underlying IgE-mediated disease at single cell resolution.

immunology↗

bioRxiv2018

Viral Taxonomy Derived From Evolutionary Genome Relationships

We describe a new genome alignment-based model for classification of viruses based on evolutionary genetic relationships. This approach uses information theory and a physical model to determine the information shared by the genes in two genomes. Pairwise comparisons of genes from the viruses are created from alignments using NCBI BLAST, and their match scores are combined to produce a metric between genomes, which is in turn used to determine a global classification using the 5,817 viruses on RefSeq. In cases where there is no measurable alignment between any genes, the method falls back to a coarser measure of genome relationship: the mutual information of k-mer frequency. This results in a principled model which depends only on the genome sequence, which captures many interesting relationships between viral families, and which creates clusters which correlate well with both the Baltimore and ICTV classifications. The incremental computational cost of classifying a novel virus is low and therefore newly discovered viruses can be quickly identified and classified.

genomics↗

bioRxiv2018

Single-cell analysis identifies EpCAM+/CDH6+/TROP-2- cells as human liver progenitors.

The liver is largely composed of hepatocytes and bile duct epithelial cells (BECs). Controversy exists as to whether a liver stem/progenitor cell capable of renewing both hepatocytes and BECs exists. Single cell RNA sequencing of freshly isolated human foetal and healthy adult liver identified hepatocyte, hepatoblast and liver progenitor cell (hLPC) populations. hLPCs, found at the interface between hepatocytes and bile ducts in both foetal and adult tissue, were distinguishable from BECs by their negative expression of TROP-2. Prospective isolation followed by in vitro culture demonstrated their potential for expansion and bi-lineage differentiation. The hLPC expression signature was also conserved within expanded cell populations specific to certain cases of liver injury and cancer. These data support the idea of a true progenitor existing within healthy adult liver that can be activated upon injury. Further work to define the mechanisms regulating hLPC behaviour could advance understanding of human development and disease.

cell biology↗

bioRxiv2017

Evolutionary Origin of the Mammalian Hematopoietic System Found in a Colonial Chordate

Hematopoiesis is an essential process that evolved in multicellular animals. At the heart of this process are hematopoietic stem cells (HSCs), which are multipotent, self-renewing and generate the entire repertoire of blood and immune cells throughout life. Here we studied the hematopoietic system of Botryllus schlosseri, a colonial tunicate that has vasculature, circulating blood cells, and interesting characteristics of stem cell biology and immunity. Self-recognition between genetically compatible B. schlosseri colonies leads to the formation of natural parabionts with shared circulation, whereas incompatible colonies reject each other. Using flow-cytometry, whole-transcriptome sequencing of defined cell populations, and diverse functional assays, we identified HSCs, progenitors, immune-effector cells, the HSC niche, and demonstrated that self-recognition inhibits cytotoxic reaction. Our study implies that the HSC and myeloid lineages emerged in a common ancestor of tunicates and vertebrates and suggests that hematopoietic bone marrow and the B. schlosseri endostyle niche evolved from the same origin.

immunology↗

bioRxiv2017

Transcriptomic characterization of 20 organs and tissues from mouse at single cell resolution creates a Tabula Muris

The Tabula Muris ConsortiumWe have created a compendium of single cell transcriptome data from the model organism Mus musculus comprising more than 100,000 cells from 20 organs and tissues. These data represent a new resource for cell biology, revealing gene expression in poorly characterized cell populations and allowing for direct and controlled comparison of gene expression in cell types shared between tissues, such as T-lymphocytes and endothelial cells from distinct anatomical locations. Two distinct technical approaches were used for most tissues: one approach, microfluidic droplet-based 3-end counting, enabled the survey of thousands of cells at relatively low coverage, while the other, FACS-based full length transcript analysis, enabled characterization of cell types with high sensitivity and coverage. The cumulative data provide the foundation for an atlas of transcriptomic cell biology.

cell biology↗

bioRxiv2017

Matrix-corrected mass spectrometry enables sensitive detection of food allergens and reveals widespread soy contamination of processed foods

The frequent use of precautionary food allergen labeling statements such as \"may contain\" poses challenges to allergic individuals who rely on such labeling to determine whether a food is safe to consume. We developed a multiplexed liquid chromatography-mass spectrometry assay targeting 14 common allergens in order to survey how frequently these precautionary statements indicate allergen contamination and to assess whether variations in precautionary phrasing affect the likelihood of allergen contamination. A survey of 84 foods revealed how scheduled multiple reaction monitoring (MRM) transition interference derived from complex and heterogeneous sample matrices hinders sensitive analyte detection. As a solution, we developed MAtrix-Dependent Interference Correction (MADIC), an approach to sensitively detect trace peptide quantities through interference identification and stringent peptide quality control criteria. Applying this method, we find frequent contamination of soy in breads and corn flour, and observe additional instances of food contamination with tree nuts, wheat, milk, and egg. In some of these cases, the food had no precautionary labeling for the offending allergen. We also find that only 10% of warning labels are indicative of contamination, and that products with \"same facility\" precautionary labeling are not necessarily less likely to contain trace amounts of allergens than products labeled \"may contain.\"

immunology↗

bioRxiv2017

A Noninvasive Molecular Clock for Fetal Development Predicts Gestational Age and Preterm Delivery

We performed a high time-resolution, longitudinal study of normal pregnancy development by measuring cell-free RNA (cfRNA) in blood from women during each week of pregnancy. Analysis of tissue-specific transcripts in these samples enabled us to follow fetal and placental development with high resolution and sensitivity, and also to detect gene-specific responses of the maternal immune system to pregnancy. We established a \"clock\" for normal pregnancy development and enabled a direct molecular approach to determine expected delivery dates with comparable accuracy to ultrasound, creating the basis for a portable, inexpensive fetal dating method. We also identified a related gene set that accurately discriminated women at risk for spontaneous preterm delivery up to two months in advance of labor, forming the basis of a potential screening test for risk of preterm delivery.

bioengineering↗

bioRxiv2017

Signatures of Selection in the Human Antibody Repertoire: Selective Sweeps, Competing Subclones, and Neutral Drift

Antibodies are created and refined by somatic evolution in B cell populations, which endows the human immune system with the ability to recognize and eliminate diverse pathogens. However, the evolutionary processes that sculpt antibody repertoires remain poorly understood. Here, using an unbiased repertoire-scale approach, we show that the molecular signatures of evolution are evident in human B cell lineages and reveal how antibodies evolve somatically. We measured the dynamics and genetic diversity of B cell responses of five adults longitudinally before and after influenza vaccination using high-throughput antibody repertoire sequencing. We identified vaccine-responsive B cell lineages that carry signatures of selective sweeps driven by positive selection, and discovered that they often display evidence for selective sweeps favoring multiple subclones. We also found persistent B cell lineages that exhibit stable population dynamics and carry signatures of neutral drift. By exploiting the linkage between B cell fitness and antibody binding affinity, we demonstrated the potential for using signatures of selection to identify antibodies with high binding affinity. This quantitative characterization reveals that antibody repertoires are shaped by an unexpectedly broad spectrum of evolutionary processes and shows how signatures of evolutionary history can be harnessed for antibody discovery and engineering.\n\nOne Sentence SummaryMolecular signatures of somatic evolution reveal that diverse evolutionary processes ranging from strong positive selection to neutral drift sculpt human antibodies.

immunology↗

bioRxiv2017

Single-cell transcriptional dynamics of flavivirus infection

Dengue and Zika viral infections affect millions of people annually and can be complicated by hemorrhage or neurological manifestations, respectively. However, a thorough understanding of the host response to these viruses is lacking, partly because conventional approaches ignore heterogeneity in virus abundance across cells. We present viscRNA-Seq (virus-inclusive single cell RNA-Seq), an approach to probe the host transcriptome together with intracellular viral RNA at the single cell level. We applied viscRNA-Seq to monitor dengue and Zika virus infection in cultured cells and discovered extreme heterogeneity in virus abundance. We exploited this variation to identify host factors that show complex dynamics and a high degree of specificity for either virus, including proteins involved in the endoplasmic reticulum translocon, signal peptide processing, and membrane trafficking. We validated the viscRNA-Seq hits and discovered novel proviral and antiviral factors. viscRNA-Seq is a powerful approach to assess the genome-wide virus-host dynamics at single cell level.

microbiology↗

bioRxiv2017

Nonivasive prenatal diagnosis of single-gene disorders using droplet digital PCR

BackgroundPrenatal diagnosis in pregnancies at risk of single-gene disorders is currently performed using invasive methods such as chorionic villus sampling and amniocentesis. This is in contrast with screening for common aneuploidies, for which noninvasive methods with a single maternal blood sample have become standard clinical practice.\n\nMethodsWe developed a protocol for noninvasive prenatal diagnosis of inherited single gene disorders using droplet digital PCR (ddPCR) from circulating cell-free DNA (cfDNA) in maternal plasma. First, the amount of cfDNA and fetal fraction are determined using a panel of Taqman assays targeting high-variability SNPs. Second, the ratio of healthy and diseased alleles in maternal plasma are quantified using Taqman assays targeting the mutations carried by the parents. Two validation approaches of the mutation assay are presented.\n\nResultsWe collected blood samples from 9 pregnancies at risk for different single gene disorders including common conditions and rare metabolic disorders. We measured cases at risk of hemophilia, ornithine transcarbamylase deficiency, cystic fibrosis, {beta}-thalassemia, mevalonate kinase deficiency, acetylcholine receptor deficiency and DFNB1 nonsyndromic hearing loss. We correctly differentiated affected and unaffected pregnancies (2 affected, 7 unaffected), confirmed by neonatal testing. We successfully measured an affected pregnancy as early as week 11, and with a fetal fraction as low as 3.7{+/-}0.3%.\n\nConclusionOur method detects single nucleotide mutations of autosomal recessive diseases as early as the first trimester of pregnancy. This is of importance for metabolic disorders where early diagnosis can affect management of the disease and reduce complications and anxiety related to invasive testing.

genetics↗

bioRxiv2017

Single-cell RNA-seq reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress

From bacteria to humans, individual cells within isogenic populations can show significant variation in stress tolerance, but the nature of this heterogeneity is not clear. To investigate this, we used single-cell RNA sequencing to quantify transcript heterogeneity in single S. cerevisiae cells treated with and without salt stress, to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. Leveraging the extensive knowledge of yeast transcriptional regulation, we uncovered significant regulatory variation in individual yeast cells, both before and after stress. We also discovered that a subset of cells decouple expression of ribosomal protein genes from the environmental stress response, in a manner partly correlated with the cell cycle but unrelated to the yeast ultradian metabolic cycle. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1, revealed both coordinated and decoupled nucleocytoplasmic shuttling. Together with transcriptomic analysis, our results reveal that cells maintain a cellular filter against decoupled bursts of transcription-factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells.

systems biology↗

bioRxiv2017

T-cell receptor sequencing of early stage breast cancer tumors identifies altered clonal structure of the T-cell repertoire

Tumor infiltrating T-cells play an important role in many cancers, and can improve prognosis and yield therapeutic targets. We characterized T-cells infiltrating both breast cancer tumors and the surrounding normal breast tissue to identify T-cells specific to each, as well as their abundance in peripheral blood. Using immune profiling of the T-cell beta chain repertoire in 16 patients with early stage breast cancer, we show that the clonal structure of the tumor is significantly different from adjacent breast tissue, with the tumor containing approximately 3-fold more T-cells, but with a lower fraction of unique sequences and higher clonality compared to normal breast. The clonal structure of T-cells in blood and normal breast is more similar than between blood and tumor and can be used to distinguish tumor from normal breast tissue in 14 of 16 patients. Many T-cells overlap between tissues from the same patient, including approximately 50% of T-cells between tumor and normal breast. Both solid tissues contain high-abundance "enriched" sequences that are absent or of low abundance in the other tissue. Many of these T-cells are either not detected or detected with very low frequency in the blood, suggesting the existence of separate compartments of T-cells in both tumor and normal breast. Enriched T-cell sequences are typically unique to each patient, but there is a subset of sequences that are shared between many different patients. We show that most of these are commonly generated sequences and thus unlikely to play an important role in the tumor microenvironment.

immunology↗

bioRxiv2017

Single-Cell RNAseq analysis of infiltrating neoplastic cells at the migrating front of human glioblastoma

Glioblastoma is the most common primary brain cancer in adults and is notoriously difficult to treat due to its diffuse nature. We performed single-cell RNAseq on 3589 cells in a cohort of four patients. We obtained cells from the tumor core as well as surrounding peripheral tissue. Our analysis revealed cellular variation in the tumors genome and transcriptome, We were able to identify infiltrating neoplastic cells in regions peripheral to the core lesions. Despite the existence of significant heterogeneity among neoplastic cells, we found that infiltrating GBM cells share a consistent gene signature between patients, suggesting a common mechanism of infiltration. Additionally, in investigating the immunological response to the tumors, we found transcriptionally distinct myeloid cell populations residing in the tumor core and the surrounding peritumoral space. Our data provide a detailed dissection of GBM cell types, revealing an abundance of novel information about tumor formation and migration.

cancer biology↗