A novel method to analyze leukocyte rolling behavior in vivo

Leukocyte endothelial cell interaction is a fundamentally important process in many disease states. Current methods to analyze such interactions include the parallel-plate flow chamber and intravital microscopy. Here, we present an improvement of the traditional intravital microscopy that allows leukocyte-endothelial cell interaction to be studied from the time the leukocyte makes its initial contact with the endothelium until it adheres to or detaches from the endothelium. The leukocyte is tracked throughout the venular tree with the aid of a motorized stage and the rolling and adhesive behavior is measured off-line. Because this method can involve human error, methods to automate the tracking procedure have been developed. This novel tracking method allows for a more detailed examination of leukocyte-endothelial cell interactions

An optimized protocol for microarray validation by quantitative PCR using amplified amino allyl labeled RNA

<p>Abstract</p> <p>Background</p> <p>Validation of microarrays data by quantitative real-time PCR (qPCR) is often limited by the low amount of available RNA. This raised the possibility to perform validation experiments on the amplified amino allyl labeled RNA (AA-aRNA) leftover from microarrays. To test this possibility, we used an ongoing study of our laboratory aiming at identifying new biomarkers of graft rejection by the transcriptomic analysis of blood cells from brain-dead organ donors.</p> <p>Results</p> <p>qPCR for ACTB performed on AA-aRNA from 15 donors provided Cq values 8 cycles higher than when original RNA was used (P < 0.001), suggesting a strong inhibition of qPCR performed on AA-aRNA. When expression levels of 5 other genes were measured in AA-aRNA generated from a universal reference RNA, qPCR sensitivity and efficiency were decreased. This prevented the quantification of one low-abundant gene, which was readily quantified in un-amplified and un-labeled RNA. To overcome this limitation, we modified the reverse transcription (RT) protocol that generates cDNA from AA-aRNA as follows: addition of a denaturation step and 2-min incubation at room temperature to improve random primers annealing, a transcription initiation step to improve RT, and a final treatment with RNase H to degrade remaining RNA. Tested on universal reference AA-aRNA, these modifications provided a gain of 3.4 Cq (average from 5 genes, P < 0.001) and an increase of qPCR efficiency (from -1.96 to -2.88; P = 0.02). They also allowed for the detection of a low-abundant gene that was previously undetectable. Tested on AA-aRNA from 15 brain-dead organ donors, RT optimization provided a gain of 2.7 cycles (average from 7 genes, P = 0.004). Finally, qPCR results significantly correlated with microarrays.</p> <p>Conclusion</p> <p>We present here an optimized RT protocol for validation of microarrays by qPCR from AA-aRNA. This is particularly valuable in experiments where limited amount of RNA is available.</p

An atlas of genetic scores to predict multi-omic traits

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1. Here we examine a large cohort (the INTERVAL study2; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores

T Cell Integrin Overexpression as a Model of Murine Autoimmunity

Integrin adhesion molecules have important adhesion and signaling functions. They also play a central role in the pathogenesis of many autoimmune diseases. Over the past few years we have described a T cell adoptive transfer model to investigate the role of T cell integrin adhesion molecules in the development of autoimmunity. This report summarizes the methods we used in establishing this murine model. By treating murine CD4+ T cells with DNA hypomethylating agents and by transfection we were able to test the in vitro effects of integrin overexpression on T cell autoreactive proliferation, cytotoxicity, adhesion and trafficking. Furthermore, we showed that the ability to induce in vivo autoimmunity may be unique to the integrin lymphocyte function associated antigen-1 (LFA-1)

Regulation of Endothelial Cell Adhesion Molecule Expression by Mast Cells, Macrophages, and Neutrophils

Leukocyte adhesion to the vascular endothelium and subsequent transendothelial migration play essential roles in the pathogenesis of cardiovascular diseases such as atherosclerosis. The leukocyte adhesion is mediated by localized activation of the endothelium through the action of inflammatory cytokines. The exact proinflammatory factors, however, that activate the endothelium and their cellular sources remain incompletely defined.Using bone marrow-derived mast cells from wild-type, Tnf(-/-), Ifng(-/-), Il6(-/-) mice, we demonstrated that all three of these pro-inflammatory cytokines from mast cells induced the expression of vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-1), P-selectin, and E-selectin in murine heart endothelial cells (MHEC) at both mRNA and protein levels. Compared with TNF-α and IL6, IFN-γ appeared weaker in the induction of the mRNA levels, but at protein levels, both IL6 and IFN-γ were weaker inducers than TNF-α. Under physiological shear flow conditions, mast cell-derived TNF-α and IL6 were more potent than IFN-γ in activating MHEC and in promoting neutrophil adhesion. Similar observations were made when neutrophils or macrophages were used. Neutrophils and macrophages produced the same sets of pro-inflammatory cytokines as did mast cells to induce MHEC adhesion molecule expression, with the exception that macrophage-derived IFN-γ showed negligible effect in inducing VCAM-1 expression in MHEC.Mast cells, neutrophils, and macrophages release pro-inflammatory cytokines such as TNF-α, IFN-γ, and IL6 that induce expression of adhesion molecules in endothelium and recruit of leukocytes, which is essential to the pathogenesis of vascular inflammatory diseases

Hydrodynamic Regulation of Monocyte Inflammatory Response to an Intracellular Pathogen

Systemic bacterial infections elicit inflammatory response that promotes acute or chronic complications such as sepsis, arthritis or atherosclerosis. Of interest, cells in circulation experience hydrodynamic shear forces, which have been shown to be a potent regulator of cellular function in the vasculature and play an important role in maintaining tissue homeostasis. In this study, we have examined the effect of shear forces due to blood flow in modulating the inflammatory response of cells to infection. Using an in vitro model, we analyzed the effects of physiological levels of shear stress on the inflammatory response of monocytes infected with chlamydia, an intracellular pathogen which causes bronchitis and is implicated in the development of atherosclerosis. We found that chlamydial infection alters the morphology of monocytes and trigger the release of pro-inflammatory cytokines TNF-α, IL-8, IL-1β and IL-6. We also found that the exposure of chlamydia-infected monocytes to short durations of arterial shear stress significantly enhances the secretion of cytokines in a time-dependent manner and the expression of surface adhesion molecule ICAM-1. As a functional consequence, infection and shear stress increased monocyte adhesion to endothelial cells under flow and in the activation and aggregation of platelets. Overall, our study demonstrates that shear stress enhances the inflammatory response of monocytes to infection, suggesting that mechanical forces may contribute to disease pathophysiology. These results provide a novel perspective on our understanding of systemic infection and inflammation

Identification of circulating proteins associated with general cognitive function among middle-aged and older adults

Identifying circulating proteins associated with cognitive function may point to biomarkers and molecular process of cognitive impairment. Few studies have investigated the association between circulating proteins and cognitive function. We identify 246 protein measures quantified by the SomaScan assay as associated with cognitive function (p < 4.9E-5, n up to 7289). Of these, 45 were replicated using SomaScan data, and three were replicated using Olink data at Bonferroni-corrected significance. Enrichment analysis linked the proteins associated with general cognitive function to cell signaling pathways and synapse architecture. Mendelian randomization analysis implicated higher levels of NECTIN2, a protein mediating viral entry into neuronal cells, with higher Alzheimer’s disease (AD) risk (p = 2.5E-26). Levels of 14 other protein measures were implicated as consequences of AD susceptibility (p < 2.0E-4). Proteins implicated as causes or consequences of AD susceptibility may provide new insight into the potential relationship between immunity and AD susceptibility as well as potential therapeutic targets

Coordinated modular functionality and prognostic potential of a heart failure biomarker-driven interaction network

<p>Abstract</p> <p>Background</p> <p>The identification of potentially relevant biomarkers and a deeper understanding of molecular mechanisms related to heart failure (HF) development can be enhanced by the implementation of biological network-based analyses. To support these efforts, here we report a global network of protein-protein interactions (PPIs) relevant to HF, which was characterized through integrative bioinformatic analyses of multiple sources of "omic" information.</p> <p>Results</p> <p>We found that the structural and functional architecture of this PPI network is highly modular. These network modules can be assigned to specialized processes, specific cellular regions and their functional roles tend to partially overlap. Our results suggest that HF biomarkers may be defined as key coordinators of intra- and inter-module communication. Putative biomarkers can, in general, be distinguished as "information traffic" mediators within this network. The top high traffic proteins are encoded by genes that are not highly differentially expressed across HF and non-HF patients. Nevertheless, we present evidence that the integration of expression patterns from high traffic genes may support accurate prediction of HF. We quantitatively demonstrate that intra- and inter-module functional activity may be controlled by a family of transcription factors known to be associated with the prevention of hypertrophy.</p> <p>Conclusion</p> <p>The systems-driven analysis reported here provides the basis for the identification of potentially novel biomarkers and understanding HF-related mechanisms in a more comprehensive and integrated way.</p