Stochastic Inheritance of Division and Death Times Determines the Size and Phenotype of CD8+ T Cell Families

After antigen stimulation cognate naïve CD8+ T cells undergo rapid proliferation and ultimately their progeny differentiates into short-lived effectors and longer-lived memory T cells. Although the expansion of individual cells is very heterogeneous, the kinetics are reproducible at the level of the total population of cognate cells. After the expansion phase, the population contracts, and if antigen is cleared, a population of memory T cells remains behind. Different markers like CD62L, CD27, and KLRG1 have been used to define several T cell subsets (or cell fates) developing from individual naïve CD8+ T cells during the expansion phase. Growing evidence from high-throughput experiments, like single cell RNA sequencing, epigenetic profiling, and lineage tracing, highlights the need to model this differentiation process at the level of single cells. We model CD8+ T cell proliferation and differentiation as a competitive process between the division and death probabilities of individual cells (like in the Cyton model). We use an extended form of the Cyton model in which daughter cells inherit the division and death times from their mother cell in a stochastic manner (using lognormal distributions). We show that this stochastic model reproduces the dynamics of CD8+ T cells both at the population and at the single cell level. Modeling the expression of the CD62L, CD27, and KLRG1 markers of each individual cell, we find agreement with the changing phenotypic distributions of these markers in single cell RNA sequencing data. Retrospectively re-defining conventional T-cell subsets by “gating” on these markers, we find agreement with published population data, without having to assume that these subsets have different properties, i.e., correspond to different fates

Dissecting the influence of Neolithic demic diffusion on Indian Y-chromosome pool through J2-M172 haplogroup

The global distribution of J2-M172 sub-haplogroups has been associated with Neolithic demic diffusion. Two branches of J2-M172, J2a-M410 and J2b-M102 make a considerable part of Y chromosome gene pool of the Indian subcontinent. We investigated the Neolithic contribution of demic dispersal from West to Indian paternal lineages, which majorly consists of haplogroups of Late Pleistocene ancestry. To accomplish this, we have analysed 3023 Y-chromosomes from different ethnic populations, of which 355 belonged to J2-M172. Comparison of our data with worldwide data, including Y-STRs of 1157 individuals and haplogroup frequencies of 6966 individuals, suggested a complex scenario that cannot be explained by a single wave of agricultural expansion from Near East to South Asia. Contrary to the widely accepted elite dominance model, we found a substantial presence of J2a-M410 and J2b-M102 haplogroups in both caste and tribal populations of India. Unlike demic spread in Eurasia, our results advocate a unique, complex and ancient arrival of J2a-M410 and J2b-M102 haplogroups into Indian subcontinent

microRNA downregulation in plasmacytoid dendritic cells in interferon-positive systemic lupus erythematosus and antiphospholipid syndrome

To investigate miRNA expression in relation to transcriptomic changes in plasmacytoid dendritic cells (pDCs) in SLE and APS. pDCs are major producers of IFN\u3b1 in SLE and APS, and miRNAs are emerging as regulators of pDC activation

Galectin-9 is an easy to measure biomarker for the interferon signature in systemic lupus erythematosus and antiphospholipid syndrome

The interferon (IFN) signature is related to disease activity and vascular disease in systemic lupus erythematosus (SLE) and antiphospholipid syndrome (APS) and represents a promising therapeutic target. Quantification of the IFN signature is currently performed by gene expression analysis, limiting its current applicability in clinical practice. Therefore, the objective of this study was to establish an easy to measure biomarker for the IFN signature

Neutrophil GM-CSF receptor dynamics in acute lung injury.

GM-CSF is important in regulating acute, persistent neutrophilic inflammation in certain settings, including lung injury. Ligand binding induces rapid internalization of the GM-CSF receptor (GM-CSFRα) complex, a process essential for signaling. Whereas GM-CSF controls many aspects of neutrophil biology, regulation of GM-CSFRα expression is poorly understood, particularly the role of GM-CSFRα in ligand clearance and whether signaling is sustained despite major down-regulation of GM-CSFRα surface expression. We established a quantitative assay of GM-CSFRα surface expression and used this, together with selective anti-GM-CSFR antibodies, to define GM-CSFRα kinetics in human neutrophils, and in murine blood and alveolar neutrophils in a lung injury model. Despite rapid sustained ligand-induced GM-CSFRα loss from the neutrophil surface, which persisted even following ligand removal, pro-survival effects of GM-CSF required ongoing ligand-receptor interaction. Neutrophils recruited to the lungs following LPS challenge showed initially high mGM-CSFRα expression, which along with mGM-CSFRβ declined over 24 hr; this was associated with a transient increase in bronchoalveolar lavage fluid (BALF) mGM-CSF concentration. Treating mice in an LPS challenge model with CAM-3003, an anti-mGM-CSFRα mAb, inhibited inflammatory cell influx into the lung and maintained the level of BALF mGM-CSF. Consistent with neutrophil consumption of GM-CSF, human neutrophils depleted exogenous GM-CSF, independent of protease activity. These data show that loss of membrane GM-CSFRα following GM-CSF exposure does not preclude sustained GM-CSF/GM-CSFRα signaling and that this receptor plays a key role in ligand clearance. Hence neutrophilic activation via GM-CSFR may play an important role in neutrophilic lung inflammation even in the absence of high GM-CSF levels or GM-CSFRα expression

A Disease-Associated MicroRNA Cluster Links Inflammatory Pathways and an Altered Composition of Leukocyte Subsets to Noninfectious Uveitis

PURPOSE. The cause of noninfectious uveitis (NIU) is poorly understood but is considered to be mediated by a complex interplay between genetic, environmental, and-relatively unexplored-epigenetic factors. MicroRNAs (miRNAs) are noncoding small RNAs that are important epigenetic regulators implicated in pathologic signaling. Therefore, we mapped the circulating miRNA-ome of NIU patients and studied miRNA perturbations within the broader context of the immune system.METHODS. We designed a strategy to robustly identify changes in the miRNA profiles of two independent cohorts totaling 54 untreated patients with active and eye-restricted disease and 26 age-matched controls. High-resolution miRNA-ome data were obtained by TaqMan OpenArray technology and subsequent RT-qPCR. Flow cytometry data, and proteomic data spanning the cellular immune system, were used to map the uveitis-miRNA signature to changes in the composition of specific leukocyte subsets in blood.RESULTS. Using stringent selection criteria, we identified and independently validated an miRNA cluster that is associated with NIU. Pathway enrichment analysis for genes targeted by this cluster revealed significant enrichment for the PI3K/Akt, MAPK, FOXO, and VEGF signaling pathways, and photoreceptor development. In addition, unsupervised multidomain analyses linked the presence of the uveitis-associated miRNA cluster to a different composition of leukocyte subsets, more specifically, CD16(+)CD11c(+)HLA-DR- cells.CONCLUSIONS. Together, this study identified a unique miRNA cluster associated with NIU that was related to changes in leukocyte subsets demonstrating systemic changes in epigenetic regulation underlying NIU

Differential Trends in the Codon Usage Patterns in HIV-1 Genes

Host-pathogen interactions underlie one of the most complex evolutionary phenomena resulting in continual adaptive genetic changes, where pathogens exploit the host's molecular resources for growth and survival, while hosts try to eliminate the pathogen. Deciphering the molecular basis of host–pathogen interactions is useful in understanding the factors governing pathogen evolution and disease propagation. In host-pathogen context, a balance between mutation, selection, and genetic drift is known to maintain codon bias in both organisms. Studies revealing determinants of the bias and its dynamics are central to the understanding of host-pathogen evolution. We considered the Human Immunodeficiency Virus (HIV) type 1 and its human host to search for evolutionary signatures in the viral genome. Positive selection is known to dominate intra-host evolution of HIV-1, whereas high genetic variability underlies the belief that neutral processes drive inter-host differences. In this study, we analyze the codon usage patterns of HIV-1 genomes across all subtypes and clades sequenced over a period of 23 years. We show presence of unique temporal correlations in the codon bias of three HIV-1 genes illustrating differential adaptation of the HIV-1 genes towards the host preferred codons. Our results point towards gene-specific translational selection to be an important force driving the evolution of HIV-1 at the population level

HIV-1 CCR5 gene therapy will fail unless it is combined with a suicide gene

Highly active antiretroviral therapy (ART) has successfully turned Human immunodeficiency virus type 1 (HIV-1) from a deadly pathogen into a manageable chronic infection. ART is a lifelong therapy which is both expensive and toxic, and HIV can become resistant to it. An alternative to lifelong ART is gene therapy that targets the CCR5 co-receptor and creates a population of genetically modified host cells that are less susceptible to viral infection. With generic mathematical models we show that gene therapy that only targets the CCR5 co-receptor fails to suppress HIV-1 (which is in agreement with current data). We predict that the same gene therapy can be markedly improved if it is combined with a suicide gene that is only expressed upon HIV-1 infection

Stochastic inheritance of division and death times determines the size and phenotype of CD8+ T cell families

After antigen stimulation cognate naïve CD8+ T cells undergo rapid proliferation and ultimately their progeny differentiates into short-lived effectors and longer-lived memory T cells. Although the expansion of individual cells is very heterogeneous, the kinetics are reproducible at the level of the total population of cognate cells. After the expansion phase, the population contracts, and if antigen is cleared, a population of memory T cells remains behind. Different markers like CD62L, CD27, and KLRG1 have been used to define several T cell subsets (or cell fates) developing from individual naïve CD8+ T cells during the expansion phase. Growing evidence from high-throughput experiments, like single cell RNA sequencing, epigenetic profiling, and lineage tracing, highlights the need to model this differentiation process at the level of single cells. We model CD8+ T cell proliferation and differentiation as a competitive process between the division and death probabilities of individual cells (like in the Cyton model). We use an extended form of the Cyton model in which daughter cells inherit the division and death times from their mother cell in a stochastic manner (using lognormal distributions). We show that this stochastic model reproduces the dynamics of CD8+ T cells both at the population and at the single cell level. Modeling the expression of the CD62L, CD27, and KLRG1 markers of each individual cell, we find agreement with the changing phenotypic distributions of these markers in single cell RNA sequencing data. Retrospectively re-defining conventional T-cell subsets by “gating” on these markers, we find agreement with published population data, without having to assume that these subsets have different properties, i.e., correspond to different fates