Data Exploration, Quality Control and Testing in Single-Cell qPCR-Based Gene Expression Experiments

Cell populations are never truly homogeneous; individual cells exist in biochemical states that define functional differences between them. New technology based on microfluidic arrays combined with multiplexed quantitative polymerase chain reactions (qPCR) now enables high-throughput single-cell gene expression measurement, allowing assessment of cellular heterogeneity. However very little analytic tools have been developed specifically for the statistical and analytical challenges of single-cell qPCR data. We present a statistical framework for the exploration, quality control, and analysis of single-cell gene expression data from microfluidic arrays. We assess accuracy and within-sample heterogeneity of single-cell expression and develop quality control criteria to filter unreliable cell measurements. We propose a statistical model accounting for the fact that genes at the single-cell level can be on (and for which a continuous expression measure is recorded) or dichotomously off (and the recorded expression is zero). Based on this model, we derive a combined likelihood-ratio test for differential expression that incorporates both the discrete and continuous components. Using an experiment that examines treatment-specific changes in expression, we show that this combined test is more powerful than either the continuous or dichotomous component in isolation, or a t-test on the zero-inflated data. While developed for measurements from a specific platform (Fluidigm), these tools are generalizable to other multi-parametric measures over large numbers of events.Comment: 9 pages, 5 figure

The Simian Immunodeficiency Virus Targets Central Cell Cycle Functions through Transcriptional Repression In vivo

A massive and selective loss of CD4+ memory T cells occurs during the acute phase of immunodeficiency virus infections. The mechanism of this depletion is poorly understood but constitutes a key event with implications for progression. We assessed gene expression of purified T cells in Rhesus Macaques during acute SIVmac239 infection in order to define mechanisms of pathogenesis. We observe a general transcriptional program of over 1,600 interferon-stimulated genes induced in all T cells by the infection. Furthermore, we identify 113 transcriptional changes that are specific to virally infected cells. A striking downregulation of several key cell cycle regulator genes was observed and shared promotor-region E2F binding sites in downregulated genes suggested a targeted transcriptional control of an E2F regulated cell cycle program. In addition, the upregulation of the gene for the fundamental regulator of RNA polymerase II, TAF7, demonstrates that viral interference with the cell cycle and transcriptional regulation programs may be critical components during the establishment of a pathogenic infection in vivo

Innate and adaptive immune traits are differentially affected by genetic and environmental factors

The diversity and activity of leukocytes is controlled by genetic and environmental influences to maintain balanced immune responses. However, the relative contribution of environmental compared with genetic factors that affect variations in immune traits is unknown. Here we analyse 23,394 immune phenotypes in 497 adult female twins. 76% of these traits show a predominantly heritable influence, whereas 24% are mostly influenced by environment. These data highlight the importance of shared childhood environmental influences such as diet, infections or microbes in shaping immune homeostasis for monocytes, B1 cells, γδ T cells and NKT cells, whereas dendritic cells, B2 cells, CD4(+) T and CD8(+) T cells are more influenced by genetics. Although leukocyte subsets are influenced by genetics and environment, adaptive immune traits are more affected by genetics, whereas innate immune traits are more affected by environment

Neutralization tiers of HIV-1

Purpose of review HIV-1 isolates are often classified on the basis of neutralization ‘tier’ phenotype. Tier classification has important implications for the monitoring and interpretation of vaccine-elicited neutralizing antibody responses. The molecular basis that distinguishes the multiple neutralization phenotypes of HIV-1 has been unclear. We present a model based on the dynamic nature of the HIV-1 envelope glycoproteins and its impact on epitope exposure. We also describe a new approach for ranking HIV-1 vaccine-elicited neutralizing antibody responses. Recent findings The unliganded trimeric HIV-1 envelope glycoprotein spike spontaneously transitions through at least three conformations. Neutralization tier phenotypes correspond to the frequency by which the trimer exists in a closed (tiers 2 and 3), open (tier 1A), or intermediate (tier 1B) conformation. An increasing number of epitopes become exposed as the trimer opens, making the virus more sensitive to neutralization by certain antibodies. The closed conformation is stabilized by many broadly neutralizing antibodies. Summary The tier 2 neutralization phenotype is typical of most circulating strains and is associated with a predominantly closed Env trimer configuration that is a high priority to target with vaccines. Assays with tier 1A viruses should be interpreted with caution and with the understanding that they detect many antibody specificities that do not neutralize tier 2 viruses and do not protect against HIV-1 infection

Immune phenotypes that are associated with subsequent COVID-19 severity inferred from post-recovery samples

Severe COVID-19 causes profound immune perturbations, but pre-infection immune signatures contributing to severe COVID-19 remain unknown. Genome-wide association studies (GWAS) identified strong associations between severe disease and several chemokine receptors and molecules from the type I interferon pathway. Here, we define immune signatures associated with severe COVID-19 using high-dimensional flow cytometry. We measure the cells of the peripheral immune system from individuals who recovered from mild, moderate, severe or critical COVID-19 and focused only on those immune signatures returning to steady-state. Individuals that suffered from severe COVID-19 show reduced frequencies of T cell, mucosal-associated invariant T cell (MAIT) and dendritic cell (DC) subsets and altered chemokine receptor expression on several subsets, such as reduced levels of CCR1 and CCR2 on monocyte subsets. Furthermore, we find reduced frequencies of type I interferon-producing plasmacytoid DCs and altered IFNAR2 expression on several myeloid cells in individuals recovered from severe COVID-19. Thus, these data identify potential immune mechanisms contributing to severe COVID-19