Measuring the physical cohesiveness of proteins using physical interaction enrichment

Motivation: Protein–protein interaction (PPI) networks are a valuable resource for the interpretation of genomics data. However, such networks have interaction enrichment biases for proteins that are often studied. These biases skew quantitative results from comparing PPI networks with genomics data. Here, we introduce an approach named physical interaction enrichment (PIE) to eliminate these biases

Transcriptome Kinetics of Circulating Neutrophils during Human Experimental Endotoxemia

Polymorphonuclear cells (neutrophils) play an important role in the systemic inflammatory response syndrome and the development of sepsis. These cells are essential for the defense against microorganisms, but may also cause tissue damage. Therefore, neutrophil numbers and activity are considered to be tightly regulated. Previous studies have investigated gene transcription during experimental endotoxemia in whole blood and peripheral blood mononuclear cells. However, the gene transcription response of the circulating pool of neutrophils to systemic inflammatory stimulation in vivo is currently unclear. We examined neutrophil gene transcription kinetics in healthy human subjects (n = 4) administered a single dose of endotoxin (LPS, 2 ng/kg iv). In addition, freshly isolated neutrophils were stimulated ex vivo with LPS, TNFα, G-CSF and GM-CSF to identify stimulus-specific gene transcription responses. Whole transcriptome microarray analysis of circulating neutrophils at 2, 4 and 6 hours after LPS infusion revealed activation of inflammatory networks which are involved in signaling of TNFα and IL-1α and IL-1β. The transcriptome profile of inflammatory activated neutrophils in vivo reflects extended survival and regulation of inflammatory responses. These changes in neutrophil transcriptome suggest a combination of early activation of circulating neutrophils by TNFα and G-CSF and a mobilization of young neutrophils from the bone marrow

Clinical parameters in time after LPS infusion.

<p>A, Leukocyte count with total leukocytes, Polymorphonuclear cell fraction and mononuclear cell fraction. Error bars represent SEM (N = 4). B, Plasma cytokines at different time points measured by luminex or ELISA (IL8). Error bars represent SEM (N = 4). C, Plasma GM-CSF and G-CSF measured by cytometric bead array. Error bars represent SEM (N = 4).</p

Kinetic behavior of inflammatory genes.

<p>A Genes of the NFκB family. Fold change in time relative to t = 0 h. B TNF related genes and genes from TNF receptor family. Fold change in time relative to t = 0. C Apoptosis mediating genes. Fold change in time relative to t = 0 h.</p

Persistent changes in gene expression.

<p>A Genes which are persistently upregulated in time, B Genes which are persistently downregulated in time, C Genes which are regulated in opposite direction between t = 2 h and t = 4 h/t = 6 h after LPS infusion (wavy genes). D, Heat map with fold change of genes relative to t = 0. Green represents downregulation and red upregulation.</p

Functional networks of persistent changes in gene expression.

<p>Cohesive network based on 233 upregulated genes. ‘Wavy’ genes are marked blue and persistent upregulated genes are represented by large nodes.</p

Ex vivo neutrophil stimulation.

<p>A Gene expression in <i>in vitro</i> stimulated neutrophils. Cells were stimulated with 10 ng LPS, 10 ng rTNFα, 50 ng rG-CSF or 50 ng rGM-CSF. At t = 2 h after stimulation RNA was isolated and q-pcr was performed with taqman probes for specific genes. Fold change relative to unstimulated. Error bars represent SEM (N = 4). B Survival after stimulation with 10 ng LPS, 10 ng rTNFα, 50 ng rG-CSF or 50 ng rGM-CSF. Cell viability was determined in ≥1×10⁵ cells with Annexin V apoptosis detection kit at 7 hours after stimulation. Dots represent the percentage of viable (Annexin V negative and 7 AAD negative) cells. N = 4 *p<0.05.</p