Googling the brain: discovering hierarchical and asymmetric network structures, with applications in neuroscience

Hierarchical organisation is a common feature of many directed networks arising in nature and technology. For example, a well-defined message-passing framework based on managerial status typically exists in a business organisation. However, in many real-world networks such patterns of hierarchy are unlikely to be quite so transparent. Due to the nature in which empirical data is collated the nodes will often be ordered so as to obscure any underlying structure. In addition, the possibility of even a small number of links violating any overall “chain of command” makes the determination of such structures extremely challenging. Here we address the issue of how to reorder a directed network in order to reveal this type of hierarchy. In doing so we also look at the task of quantifying the level of hierarchy, given a particular node ordering. We look at a variety of approaches. Using ideas from the graph Laplacian literature, we show that a relevant discrete optimization problem leads to a natural hierarchical node ranking. We also show that this ranking arises via a maximum likelihood problem associated with a new range-dependent hierarchical random graph model. This random graph insight allows us to compute a likelihood ratio that quantifies the overall tendency for a given network to be hierarchical. We also develop a generalization of this node ordering algorithm based on the combinatorics of directed walks. In passing, we note that Google’s PageRank algorithm tackles a closely related problem, and may also be motivated from a combinatoric, walk-counting viewpoint. We illustrate the performance of the resulting algorithms on synthetic network data, and on a real-world network from neuroscience where results may be validated biologically

Cripto enhances the tyrosine phosphorylation of Shc and activates mitogen-activated protein kinase (MAPK) in mammary epithelial cells

Cripto-1 (CR-1), a recently discovered protein of the epidermal growth factor (EGF) family, was found to interact with a high affinity, saturable binding site(s) on HC-11 mouse mammary epithelial cells and on several different human breast cancer cell lines. This receptor exhibits specificity for CR-1, since other EGF-related peptides including EGF, transforming growth factor alpha, heparin-binding EGF-like growth factor, amphiregulin, epiregulin, betacellulin, or heregulin beta1 that bind to either the EGF receptor or to other type 1 receptor tyrosine kinases such as erb B-3 or erb B-4 fail to compete for binding. Conversely, CR-1 was found not to directly bind to or to activate the tyrosine kinases associated with the EGFR, erb B-2, erb B-3, or erb B-4 either alone or in various pairwise combinations which have been ectopically expressed in Ba/F3 mouse pro-B lymphocyte cells. However, exogenous CR-1 could induce an increase in the tyrosine phosphorylation of 185- and 120-kDa proteins and a rapid (within 3-5 min) increase in the tyrosine phosphorylation of the SH2-containing adaptor proteins p66, p52, and p46 Shc in mouse mammary HC-11 epithelial cells and in human MDA-MB-453 and SKBr-3 breast cancer cells. CR-1 was also found to promote an increase in the association of the adaptor Grb2-guanine nucleotide exchange factor-mouse son of sevenless (mSOS) signaling complex with tyrosine-phosphorylated Shc in HC-11 cells. Finally, CR-1 was able to increase p42(erk-2) mitogen-activated protein kinase (MAPK) activity in HC-11 cells within 5-10 min of treatment. These data demonstrate that CR-1 can function through a receptor which activates intracellular components in the ras/raf/MEK/MAPK pathway

Analyses of the Microbial Diversity across the Human Microbiome

Analysis of human body microbial diversity is fundamental to understanding community structure, biology and ecology. The National Institutes of Health Human Microbiome Project (HMP) has provided an unprecedented opportunity to examine microbial diversity within and across body habitats and individuals through pyrosequencing-based profiling of 16 S rRNA gene sequences (16 S) from habits of the oral, skin, distal gut, and vaginal body regions from over 200 healthy individuals enabling the application of statistical techniques. In this study, two approaches were applied to elucidate the nature and extent of human microbiome diversity. First, bootstrap and parametric curve fitting techniques were evaluated to estimate the maximum number of unique taxa, Smax, and taxa discovery rate for habitats across individuals. Next, our results demonstrated that the variation of diversity within low abundant taxa across habitats and individuals was not sufficiently quantified with standard ecological diversity indices. This impact from low abundant taxa motivated us to introduce a novel rank-based diversity measure, the Tail statistic, (“τ”), based on the standard deviation of the rank abundance curve if made symmetric by reflection around the most abundant taxon. Due to τ’s greater sensitivity to low abundant taxa, its application to diversity estimation of taxonomic units using taxonomic dependent and independent methods revealed a greater range of values recovered between individuals versus body habitats, and different patterns of diversity within habitats. The greatest range of τ values within and across individuals was found in stool, which also exhibited the most undiscovered taxa. Oral and skin habitats revealed variable diversity patterns, while vaginal habitats were consistently the least diverse. Collectively, these results demonstrate the importance, and motivate the introduction, of several visualization and analysis methods tuned specifically for next-generation sequence data, further revealing that low abundant taxa serve as an important reservoir of genetic diversity in the human microbiome

The host ubiquitin-dependent segregase VCP/p97 is required for the onset of human cytomegalovirus replication

The human cytomegalovirus major immediate early proteins IE1 and IE2 are critical drivers of virus replication and are considered pivotal in determining the balance between productive and latent infection. IE1 and IE2 are derived from the same primary transcript by alternative splicing and regulation of their expression likely involves a complex interplay between cellular and viral factors. Here we show that knockdown of the host ubiquitin-dependent segregase VCP/p97, results in loss of IE2 expression, subsequent suppression of early and late gene expression and, ultimately, failure in virus replication. RNAseq analysis showed increased levels of IE1 splicing, with a corresponding decrease in IE2 splicing following VCP knockdown. Global analysis of viral transcription showed the expression of a subset of viral genes is not reduced despite the loss of IE2 expression, including UL112/113. Furthermore, Immunofluorescence studies demonstrated that VCP strongly colocalised with the viral replication compartments in the nucleus. Finally, we show that NMS-873, a small molecule inhibitor of VCP, is a potent HCMV antiviral with potential as a novel host targeting therapeutic for HCMV infection