A fundamental goal of developmental and stem cell biology is to map the developmental history (ontogeny) of differentiated cell types. Recent advances in high-throughput single-cell sequencing ...technologies have enabled the construction of comprehensive transcriptional atlases of adult tissues and of developing embryos from measurements of up to millions of individual cells. Parallel advances in sequencing-based lineage-tracing methods now facilitate the mapping of clonal relationships onto these landscapes and enable detailed comparisons between molecular and mitotic histories. Here we review recent progress and challenges, as well as the opportunities that emerge when these two complementary representations of cellular history are synthesized into integrated models of cell differentiation.
Sepsis is considered to induce immune suppression, leading to increased susceptibility to secondary infections with associated late mortality.
To determine the clinical and host genomic ...characteristics, incidence, and attributable mortality of intensive care unit (ICU)-acquired infections in patients admitted to the ICU with or without sepsis.
Prospective observational study comprising consecutive admissions of more than 48 hours in 2 ICUs in the Netherlands from January 2011 to July 2013 stratified according to admission diagnosis (sepsis or noninfectious).
The primary outcome was ICU-acquired infection (onset >48 hours). Attributable mortality risk (fraction of mortality that can be prevented by elimination of the risk factor, acquired infection) was determined using time-to-event models accounting for competing risk. In a subset of sepsis admissions (n = 461), blood gene expression (whole-genome transcriptome in leukocytes) was analyzed at baseline and at onset of ICU-acquired infectious (n = 19) and noninfectious (n = 9) events.
The primary cohort included 1719 sepsis admissions (1504 patients; median age, 62 years; interquartile range IQR, 51-71 years; 924 men 61.4%). A comparative cohort included 1921 admissions (1825 patients, median age, 62 years; IQR, 49-71 years; 1128 men 61.8% in whom infection was not present in the first 48 hours. Intensive care unit-acquired infections occurred in 13.5% of sepsis ICU admissions (n = 232) and 15.1% of nonsepsis ICU admissions (n = 291). Patients with sepsis who developed an ICU-acquired infection had higher disease severity scores on admission than patients with sepsis who did not develop an ICU-acquired infection (Acute Physiology and Chronic Health Evaluation IV APACHE IV median score, 90 IQR, 72-107 vs 79 IQR, 62-98; P < .001) and throughout their ICU stay but did not have differences in baseline gene expression. The population attributable mortality fraction of ICU-acquired infections in patients with sepsis was 10.9% (95% CI, 0.9%-20.6%) by day 60; the estimated difference between mortality in all patients with a sepsis admission diagnosis and mortality in those without ICU-acquired infection was 2.0% (95% CI, 0.2%-3.8%; P = .03) by day 60. Among nonsepsis ICU admissions, ICU-acquired infections had a population attributable mortality fraction of 21.1% (95% CI, 0.6%-41.7%) by day 60. Compared with baseline, blood gene expression at the onset of ICU-acquired infections showed reduced expression of genes involved in gluconeogenesis and glycolysis.
Intensive care unit-acquired infections occurred more commonly in patients with sepsis with higher disease severity, but such infections contributed only modestly to overall mortality. The genomic response of patients with sepsis was consistent with immune suppression at the onset of secondary infection.
Abstract
Motivation
Single-cell gene expression profiling technologies can map the cell states in a tissue or organism. As these technologies become more common, there is a need for computational ...tools to explore the data they produce. In particular, visualizing continuous gene expression topologies can be improved, since current tools tend to fragment gene expression continua or capture only limited features of complex population topologies.
Results
Force-directed layouts of k-nearest-neighbor graphs can visualize continuous gene expression topologies in a manner that preserves high-dimensional relationships and captures complex population topologies. We describe SPRING, a pipeline for data filtering, normalization and visualization using force-directed layouts and show that it reveals more detailed biological relationships than existing approaches when applied to branching gene expression trajectories from hematopoietic progenitor cells and cells of the upper airway epithelium. Visualizations from SPRING are also more reproducible than those of stochastic visualization methods such as tSNE, a state-of-the-art tool. We provide SPRING as an interactive web-tool with an easy to use GUI.
Availability and implementation
https://kleintools.hms.harvard.edu/tools/spring.html, https://github.com/AllonKleinLab/SPRING/.
Supplementary information
Supplementary data are available at Bioinformatics online.
It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between ...genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships.
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•Cells are captured and barcoded in nanolitre droplets with high capture efficiency•Each drop hosts a hydrogel carrying photocleavable combinatorially barcoded primers•mRNA of thousands of mouse embryonic stem and differentiating cells are sequenced•Single-cell heterogeneity reveals population structure and gene regulatory linkages
Capturing single cells along with a set of uniquely barcoded primers in tiny droplets enables single-cell transcriptomics of a large number of cells in a heterogeneous population. Applying this analysis to mouse embryonic stem cells reveals their population structure, gene expression relationships, and the heterogeneous onset of differentiation.
Objective: Several health behavior theories converge on the hypothesis that attitudes, norms, and self-efficacy are important determinants of intentions and behavior. However, inferences regarding ...the relation between these cognitions and intention or behavior rest largely on correlational data that preclude causal inferences. To determine whether changing attitudes, norms, or self-efficacy leads to changes in intentions and behavior, investigators need to randomly assign participants to a treatment that significantly increases the respective cognition relative to a control condition, and test for differences in subsequent intentions or behavior. The present review analyzed findings from 204 experimental tests that met these criteria. Method: Studies were located using computerized searches and informal sources and meta-analyzed using STATA Version 11. Results: Experimentally induced changes in attitudes, norms, and self-efficacy all led to medium-sized changes in intention (d+ = .48, .49, and .51, respectively), and engendered small to medium-sized changes in behavior (attitudes-d+ = .38, norms-d+ = .36, self-efficacy-d+ = .47). These effect sizes generally were not qualified by the moderator variables examined (e.g., study quality, theoretical basis of the intervention, methodological characteristics, and features of the targeted behavior), although effects were larger for interventions designed to increase (vs. decrease) behavioral performance. Conclusion: The present review lends novel, experimental support for key predictions from health behavior theories, and demonstrates that interventions that modify attitudes, norms, and self-efficacy are effective in promoting health behavior change.
This volume explores the entangled history of Constantinople and Jerusalem in Late Antiquity. The two cities were powerful symbols of Empire and Church, interconnected and interdependent in multiple ...ways. Covering the transition between Antiquity, Byzantium, and the Middle Ages, distinguished international scholars investigate art, ceremony, religion, ideology, and imperial rule in these vibrant, inspiring and fascinating urban hubs.
Single-cell RNA-sequencing has become a widely used, powerful approach for studying cell populations. However, these methods often generate multiplet artifacts, where two or more cells receive the ...same barcode, resulting in a hybrid transcriptome. In most experiments, multiplets account for several percent of transcriptomes and can confound downstream data analysis. Here, we present Single-Cell Remover of Doublets (Scrublet), a framework for predicting the impact of multiplets in a given analysis and identifying problematic multiplets. Scrublet avoids the need for expert knowledge or cell clustering by simulating multiplets from the data and building a nearest neighbor classifier. To demonstrate the utility of this approach, we test Scrublet on several datasets that include independent knowledge of cell multiplets. Scrublet is freely available for download at github.com/AllonKleinLab/scrublet.
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•We define two multiplet errors in single-cell RNA-seq data: “embedded” and “neotypic”•Neotypic errors can lead to misidentification of cell types or transitional states•Scrublet code identifies neotypic doublets and predicts the overall doublet rate•The algorithm is tested against several experimental methods for labeling multiplets
Single-cell RNA-sequencing experiments generate “multiplet errors” when multiple cells are labeled with the same barcode. Wolock et al. describe Scrublet, a method for predicting the effects of multiplets on downstream analyses and identifying problematic multiplets. They validate the method by applying Scrublet to several datasets with independent knowledge of multiplets.
A challenge in biology is to associate molecular differences among progenitor cells with their capacity to generate mature cell types. Here, we used expressed DNA barcodes to clonally trace ...transcriptomes over time and applied this to study fate determination in hematopoiesis. We identified states of primed fate potential and located them on a continuous transcriptional landscape. We identified two routes of monocyte differentiation that leave an imprint on mature cells. Analysis of sister cells also revealed cells to have intrinsic fate biases not detectable by single-cell RNA sequencing. Finally, we benchmarked computational methods of dynamic inference from single-cell snapshots, showing that fate choice occurs earlier than is detected by state-of the-art algorithms and that cells progress steadily through pseudotime with precise and consistent dynamics.
We present a European land‐only daily high‐resolution gridded data set for precipitation and minimum, maximum, and mean surface temperature for the period 1950–2006. This data set improves on ...previous products in its spatial resolution and extent, time period, number of contributing stations, and attention to finding the most appropriate method for spatial interpolation of daily climate observations. The gridded data are delivered on four spatial resolutions to match the grids used in previous products as well as many of the rotated pole Regional Climate Models (RCMs) currently in use. Each data set has been designed to provide the best estimate of grid box averages rather than point values to enable direct comparison with RCMs. We employ a three‐step process of interpolation, by first interpolating the monthly precipitation totals and monthly mean temperature using three‐dimensional thin‐plate splines, then interpolating the daily anomalies using indicator and universal kriging for precipitation and kriging with an external drift for temperature, then combining the monthly and daily estimates. Interpolation uncertainty is quantified by the provision of daily standard errors for every grid square. The daily uncertainty averaged across the entire region is shown to be largely dependent on the season and number of contributing observations. We examine the effect that interpolation has on the magnitude of the extremes in the observations by calculating areal reduction factors for daily maximum temperature and precipitation events with return periods up to 10 years.
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