Surgical sepsis has evolved into two major subpopulations: patients who rapidly recover, and those who develop chronic critical illness (CCI). Our primary aim was to determine whether CCI sepsis ...survivors manifest unique blood leukocyte transcriptomes in late sepsis that differ from transcriptomes among sepsis survivors with rapid recovery. In a prospective cohort study of surgical ICU patients, genome-wide expression analysis was conducted on total leukocytes in human whole blood collected on days 1 and 14 from sepsis survivors who rapidly recovered or developed CCI, defined as ICU length of stay ≥ 14 days with persistent organ dysfunction. Both sepsis patients who developed CCI and those who rapidly recovered exhibited marked changes in genome-wide expression at day 1 which remained abnormal through day 14. Although summary changes in gene expression were similar between CCI patients and subjects who rapidly recovered, CCI patients exhibited differential expression of 185 unique genes compared with rapid recovery patients at day 14 (
< 0.001). The transcriptomic patterns in sepsis survivors reveal an ongoing immune dyscrasia at the level of the blood leukocyte transcriptome, consistent with persistent inflammation and immune suppression. Furthermore, the findings highlight important genes that could compose a prognostic transcriptomic metric or serve as therapeutic targets among sepsis patients that develop CCI.
Abstract
Motivation
Normalization to remove technical or experimental artifacts is critical in the analysis of single-cell RNA-sequencing experiments, even those for which unique molecular ...identifiers are available. The majority of methods for normalizing single-cell RNA-sequencing data adjust average expression for library size (LS), allowing the variance and other properties of the gene-specific expression distribution to be non-constant in LS. This often results in reduced power and increased false discoveries in downstream analyses, a problem which is exacerbated by the high proportion of zeros present in most datasets.
Results
To address this, we present Dino, a normalization method based on a flexible negative-binomial mixture model of gene expression. As demonstrated in both simulated and case study datasets, by normalizing the entire gene expression distribution, Dino is robust to shallow sequencing, sample heterogeneity and varying zero proportions, leading to improved performance in downstream analyses in a number of settings.
Availability and implementation
The R package, Dino, is available on GitHub at https://github.com/JBrownBiostat/Dino. The Dino package is further archived and freely available on Zenodo at https://doi.org/10.5281/zenodo.4897558.
Supplementary information
Supplementary data are available at Bioinformatics online.
Single-cell RNA sequencing (scRNA-seq) experiments have become instrumental in developmental and differentiation studies, enabling the profiling of cells at a single or multiple time-points to ...uncover subtle variations in expression profiles reflecting underlying biological processes. Benchmarking studies have compared many of the computational methods used to reconstruct cellular dynamics; however, researchers still encounter challenges in their analysis due to uncertainty with respect to selecting the most appropriate methods and parameters. Even among universal data processing steps used by trajectory inference methods such as feature selection and dimension reduction, trajectory methods' performances are highly dataset-specific. To address these challenges, we developed Escort, a novel framework for evaluating a dataset's suitability for trajectory inference and quantifying trajectory properties influenced by analysis decisions. Escort evaluates the suitability of trajectory analysis and the combined effects of processing choices using trajectory-specific metrics. Escort navigates single-cell trajectory analysis through these data-driven assessments, reducing uncertainty and much of the decision burden inherent to trajectory inference analyses. Escort is implemented in an accessible R package and R/Shiny application, providing researchers with the necessary tools to make informed decisions during trajectory analysis and enabling new insights into dynamic biological processes at single-cell resolution.
Type 1 diabetes (T1D) presents with two therapeutic challenges: the need to correct underlying autoimmunity and restore β‐cell mass. We harnessed the unique capacity of regulatory T cells (Tregs) and ...the T cell receptor (TCR) to direct tolerance induction along with tissue‐localized delivery of therapeutic agents to restore endogenous β‐cell function. Specifically, we designed a combinatorial therapy involving biomaterials‐based poly(lactic‐co‐glycolic acid) nanoparticles co‐loaded with the Treg growth factor, IL‐2, and the β‐cell regenerative agent, harmine (a tyrosine‐regulated kinase 1A DYRK1A inhibitor), conjugated to the surface of Tregs. We observed continuous elution of IL‐2 and harmine from nanoparticles for at least 7 days in vitro. When conjugated to primary human Tregs, IL‐2 nanoparticles provided sufficient IL‐2 receptor signaling to support STAT5 phosphorylation for sustained phenotypic stability and viability in culture. Inclusion of poly‐L‐lysine (PLL) during nanoparticle‐cell coupling dramatically increased conjugation efficiency, providing sufficient IL‐2 to support in vitro proliferation of IL‐2‐dependent CTLL‐2 cells and primary murine Tregs. In 12‐week‐old female non‐obese diabetic mice, adoptive transfer of IL‐2/harmine nanoparticle‐conjugated NOD.BDC2.5 Tregs, which express an islet antigen‐specific TCR, significantly prevented diabetes demonstrating preserved in vivo viability. These data provide the preclinical basis to develop a biomaterials‐optimized cellular therapy to restore immune tolerance and promote β‐cell proliferation in T1D through receptor‐targeted drug delivery within pancreatic islets.
Abstract
Considerable effort has been devoted to refining experimental protocols to reduce levels of technical variability and artifacts in single-cell RNA-sequencing data (scRNA-seq). We here ...present evidence that equalizing the concentration of cDNA libraries prior to pooling, a step not consistently performed in single-cell experiments, improves gene detection rates, enhances biological signals, and reduces technical artifacts in scRNA-seq data. To evaluate the effect of equalization on various protocols, we developed Scaffold, a simulation framework that models each step of an scRNA-seq experiment. Numerical experiments demonstrate that equalization reduces variation in sequencing depth and gene-specific expression variability. We then performed a set of experiments in vitro with and without the equalization step and found that equalization increases the number of genes that are detected in every cell by 17–31%, improves discovery of biologically relevant genes, and reduces nuisance signals associated with cell cycle. Further support is provided in an analysis of publicly available data.
Exocrine pancreas abnormalities are increasingly recognized as features of type 1 diabetes. We previously reported reduced serum trypsinogen levels and in a separate study, smaller pancreata at and ...before disease onset. We hypothesized that three pancreas enzymes (amylase, lipase, and trypsinogen) might serve as serological biomarkers of pancreas volume and risk for type 1 diabetes. Amylase, lipase, and trypsinogen were measured from two independent cohorts, together comprising 800 serum samples from single-autoantibody-positive (1AAb
) and multiple-AAb
(≥2AAb
) subjects, individuals with recent-onset or established type 1 diabetes, their AAb-negative (AAb
) first-degree relatives, and AAb
control subjects. Lipase and trypsinogen were significantly reduced in ≥2AAb
, recent-onset, and established type 1 diabetes subjects versus control subjects and 1AAb
, while amylase was reduced only in established type 1 diabetes. Logistic regression models demonstrated trypsinogen plus lipase (area under the receiver operating characteristic curve AUROC = 81.4%) performed equivalently to all three enzymes (AUROC = 81.4%) in categorizing ≥2AAb
versus 1AAb
subjects. For cohort 2 (
= 246), linear regression demonstrated lipase and trypsinogen levels could individually and collectively serve as indicators of BMI-normalized relative pancreas volume (RPV
,
< 0.001), previously measured by MRI. Serum lipase and trypsinogen levels together provide the most sensitive serological biomarker of RPV
and may improve disease staging in pretype 1 diabetes.
The majority of gene loci that have been associated with type 2 diabetes play a role in pancreatic islet function. To evaluate the role of islet gene expression in the etiology of diabetes, we ...sensitized a genetically diverse mouse population with a Western diet high in fat (45% kcal) and sucrose (34%) and carried out genome-wide association mapping of diabetes-related phenotypes. We quantified mRNA abundance in the islets and identified 18,820 expression QTL. We applied mediation analysis to identify candidate causal driver genes at loci that affect the abundance of numerous transcripts. These include two genes previously associated with monogenic diabetes (
and
), as well as three genes with nominal association with diabetes-related traits in humans (
,
, and
). We grouped transcripts into gene modules and mapped regulatory loci for modules enriched with transcripts specific for α-cells, and another specific for δ-cells. However, no single module enriched for β-cell-specific transcripts, suggesting heterogeneity of gene expression patterns within the β-cell population. A module enriched in transcripts associated with branched-chain amino acid metabolism was the most strongly correlated with physiological traits that reflect insulin resistance. Although the mice in this study were not overtly diabetic, the analysis of pancreatic islet gene expression under dietary-induced stress enabled us to identify correlated variation in groups of genes that are functionally linked to diabetes-associated physiological traits. Our analysis suggests an expected degree of concordance between diabetes-associated loci in the mouse and those found in human populations, and demonstrates how the mouse can provide evidence to support nominal associations found in human genome-wide association mapping.
Increased circulating myeloid-derived suppressor cells (MDSCs) are independently associated with poor long-term clinical outcomes in sepsis. Studies implicate subsets of MDSCs having unique roles in ...lymphocyte suppression; however, characterization of these cells after sepsis remains incomplete. We performed a pilot study to determine the transcriptomic landscape in MDSC subsets in sepsis using single-cell RNAseq (scRNA-seq).
A mixture of whole blood myeloid-enriched and Ficoll-enriched PBMCs from two late septic patients on post-sepsis day 21 and two control subjects underwent Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq).
We successfully identified the three MDSC subset clusters-granulocytic (G-), monocytic (M-), and early (E-) MDSCs. Sepsis was associated with a greater relative expansion of G-MDSCs versus M-MDSCs at 21 days as compared to control subjects. Genomic analysis between septic patients and control subjects revealed cell-specific and common differential expression of genes in both G-MDSC and M-MDSC subsets. Many of the common genes have previously been associated with MDSC proliferation and immunosuppressive function. Interestingly, there was no differential expression of several genes demonstrated in the literature to be vital to immunosuppression in cancer-induced MDSC.
This pilot study successfully demonstrated that MDSCs maintain a transcriptomic profile that is immunosuppressive in late sepsis. Interestingly, the landscape in chronic critical illness is partially dependent on the original septic insult. Preliminary data would also indicate immunosuppressive MDSCs from late sepsis patients appear to have a somewhat unique transcriptome from cancer and/or other inflammatory diseases.
We and others previously demonstrated that a type 1 diabetes genetic risk score (GRS) improves the ability to predict disease progression and onset in at-risk subjects with islet autoantibodies. ...Here, we hypothesized that GRS and islet autoantibodies, combined with age at onset and disease duration, could serve as markers of residual β-cell function following type 1 diabetes diagnosis. Generalized estimating equations were used to investigate whether GRS along with insulinoma-associated protein-2 autoantibody (IA-2A), zinc transporter 8 autoantibody (ZnT8A), and GAD autoantibody (GADA) titers were predictive of C-peptide detection in a largely cross-sectional cohort of 401 subjects with type 1 diabetes (median duration 4.5 years range 0-60). Indeed, a combined model with incorporation of disease duration, age at onset, GRS, and titers of IA-2A, ZnT8A, and GADA provided superior capacity to predict C-peptide detection (quasi-likelihood information criterion QIC = 334.6) compared with the capacity of disease duration, age at onset, and GRS as the sole parameters (QIC = 359.2). These findings support the need for longitudinal validation of our combinatorial model. The ability to project the rate and extent of decline in residual C-peptide production for individuals with type 1 diabetes could critically inform enrollment and benchmarking for clinical trials where investigators are seeking to preserve or restore endogenous β-cell function.
How species-specific developmental timing is controlled is largely unknown. By following human embryonic stem (ES) cell and mouse epiblast stem (EpiS) cell differentiation through detailed ...RNA-sequencing time courses, here we show that pluripotent stem cells closely retain in vivo species-specific developmental timing in vitro. In identical neural differentiation conditions in vitro, gene expression profiles are accelerated in mouse EpiS cells compared to human ES cells with relative rates of differentiation closely reflecting the rates of progression through the Carnegie stages in utero. Dynamic Time Warping analysis identified 3389 genes that were regulated more quickly in mouse EpiS cells and identified none that were regulated more quickly in human ES cells. Interestingly, we also find that human ES cells differentiated in teratomas maintain the same rate of differentiation observed in vitro in spite of being grown in a mouse host. These results suggest the existence of a cell autonomous, species-specific developmental clock that pluripotent stem cells maintain even out of context of an intact embryo.
•Human and mouse stem cells retain species-dependent rates of development in vitro.•Human ES cell differentiation is not accelerated by mouse factors in teratomas.•Ex utero differentiation mirrors Carnegie stage progression in utero.
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