Predicting Quantitative Genetic Interactions by Means of Sequential Matrix Approximation

Despite the emerging experimental techniques for perturbing multiple genes and measuring their quantitative phenotypic effects, genetic interactions have remained extremely difficult to predict on a large scale. Using a recent high-resolution screen of genetic interactions in yeast as a case study, we investigated whether the extraction of pertinent information encoded in the quantitative phenotypic measurements could be improved by computational means. By taking advantage of the observation that most gene pairs in the genetic interaction screens have no significant interactions with each other, we developed a sequential approximation procedure which ranks the mutation pairs in order of evidence for a genetic interaction. The sequential approximations can efficiently remove background variation in the double-mutation screens and give increasingly accurate estimates of the single-mutant fitness measurements. Interestingly, these estimates not only provide predictions for genetic interactions which are consistent with those obtained using the measured fitness, but they can even significantly improve the accuracy with which one can distinguish functionally-related gene pairs from the non-interacting pairs. The computational approach, in general, enables an efficient exploration and classification of genetic interactions in other studies and systems as well

Why Amphibians Are More Sensitive than Mammals to Xenobiotics

Dramatic declines in amphibian populations have been described all over the world since the 1980s. The evidence that the sensitivity to environmental threats is greater in amphibians than in mammals has been generally linked to the observation that amphibians are characterized by a rather permeable skin. Nevertheless, a numerical comparison of data of percutaneous (through the skin) passage between amphibians and mammals is lacking. Therefore, in this investigation we have measured the percutaneous passage of two test molecules (mannitol and antipyrine) and three heavily used herbicides (atrazine, paraquat and glyphosate) in the skin of the frog Rana esculenta (amphibians) and of the pig ear (mammals), by using the same experimental protocol and a simple apparatus which minimizes the edge effect, occurring when the tissue is clamped in the usually used experimental device

TNFAIP3 Maintains Intestinal Barrier Function and Supports Epithelial Cell Tight Junctions

Tight junctions between intestinal epithelial cells mediate the permeability of the intestinal barrier, and loss of intestinal barrier function mediated by TNF signaling is associated with the inflammatory pathophysiology observed in Crohn's disease and celiac disease. Thus, factors that modulate intestinal epithelial cell response to TNF may be critical for the maintenance of barrier function. TNF alpha-induced protein 3 (TNFAIP3) is a cytosolic protein that acts in a negative feedback loop to regulate cell signaling induced by Toll-like receptor ligands and TNF, suggesting that TNFAIP3 may play a role in regulating the intestinal barrier. To investigate the specific role of TNFAIP3 in intestinal barrier function we assessed barrier permeability in TNFAIP3−/− mice and LPS-treated villin-TNFAIP3 transgenic mice. TNFAIP3−/− mice had greater intestinal permeability compared to wild-type littermates, while villin-TNFAIP3 transgenic mice were protected from increases in permeability seen within LPS-treated wild-type littermates, indicating that barrier permeability is controlled by TNFAIP3. In cultured human intestinal epithelial cell lines, TNFAIP3 expression regulated both TNF-induced and myosin light chain kinase-regulated tight junction dynamics but did not affect myosin light chain kinase activity. Immunohistochemistry of mouse intestine revealed that TNFAIP3 expression inhibits LPS-induced loss of the tight junction protein occludin from the apical border of the intestinal epithelium. We also found that TNFAIP3 deubiquitinates polyubiquitinated occludin. These in vivo and in vitro studies support the role of TNFAIP3 in promoting intestinal epithelial barrier integrity and demonstrate its novel ability to maintain intestinal homeostasis through tight junction protein regulation

An Integrative Multi-Network and Multi-Classifier Approach to Predict Genetic Interactions

Genetic interactions occur when a combination of mutations results in a surprising phenotype. These interactions capture functional redundancy, and thus are important for predicting function, dissecting protein complexes into functional pathways, and exploring the mechanistic underpinnings of common human diseases. Synthetic sickness and lethality are the most studied types of genetic interactions in yeast. However, even in yeast, only a small proportion of gene pairs have been tested for genetic interactions due to the large number of possible combinations of gene pairs. To expand the set of known synthetic lethal (SL) interactions, we have devised an integrative, multi-network approach for predicting these interactions that significantly improves upon the existing approaches. First, we defined a large number of features for characterizing the relationships between pairs of genes from various data sources. In particular, these features are independent of the known SL interactions, in contrast to some previous approaches. Using these features, we developed a non-parametric multi-classifier system for predicting SL interactions that enabled the simultaneous use of multiple classification procedures. Several comprehensive experiments demonstrated that the SL-independent features in conjunction with the advanced classification scheme led to an improved performance when compared to the current state of the art method. Using this approach, we derived the first yeast transcription factor genetic interaction network, part of which was well supported by literature. We also used this approach to predict SL interactions between all non-essential gene pairs in yeast (http://sage.fhcrc.org/downloads/downloads/predicted_yeast_genetic_interactions.zip). This integrative approach is expected to be more effective and robust in uncovering new genetic interactions from the tens of millions of unknown gene pairs in yeast and from the hundreds of millions of gene pairs in higher organisms like mouse and human, in which very few genetic interactions have been identified to date

Functional Maps of Protein Complexes from Quantitative Genetic Interaction Data

Recently, a number of advanced screening technologies have allowed for the comprehensive quantification of aggravating and alleviating genetic interactions among gene pairs. In parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have been successful at identifying physical protein interactions that can indicate proteins participating in the same molecular complex. Here, we propose a method for the joint learning of protein complexes and their functional relationships by integration of quantitative genetic interactions and TAP-MS data. Using 3 independent benchmark datasets, we demonstrate that this method is >50% more accurate at identifying functionally related protein pairs than previous approaches. Application to genes involved in yeast chromosome organization identifies a functional map of 91 multimeric complexes, a number of which are novel or have been substantially expanded by addition of new subunits. Interestingly, we find that complexes that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely to contain essential genes, linking each of these interactions to an underlying mechanism. These results demonstrate the importance of both large-scale genetic and physical interaction data in mapping pathway architecture and function

Monitoring Functional Capability of Individuals with Lower Limb Amputations Using Mobile Phones

To be effective, a prescribed prosthetic device must match the functional requirements and capabilities of each patient. These capabilities are usually assessed by a clinician and reported by the Medicare K-level designation of mobility. However, it is not clear how the K-level designation objectively relates to the use of prostheses outside of a clinical environment. Here, we quantify participant activity using mobile phones and relate activity measured during real world activity to the assigned K-levels. We observe a correlation between K-level and the proportion of moderate to high activity over the course of a week. This relationship suggests that accelerometry-based technologies such as mobile phones can be used to evaluate real world activity for mobility assessment. Quantifying everyday activity promises to improve assessment of real world prosthesis use, leading to a better matching of prostheses to individuals and enabling better evaluations of future prosthetic devices.Max Nader Center for Rehabilitation Technologies and Outcome

Involvement of ubiquitin-editing protein A20 in modulating in-flammation in rat cochlea associated with silver nanoparti-cles-induced CD68 up-regulation and TLR4 activation

The manuscript was just accepted for publication on Nanoscale Research Letters

IKAP/Elp1 Is Required In Vivo for Neurogenesis and Neuronal Survival, but Not for Neural Crest Migration

Familial Dysautonomia (FD; Hereditary Sensory Autonomic Neuropathy; HSAN III) manifests from a failure in development of the peripheral sensory and autonomic nervous systems. The disease results from a point mutation in the IKBKAP gene, which encodes the IKAP protein, whose function is still unresolved in the developing nervous system. Since the neurons most severely depleted in the disease derive from the neural crest, and in light of data identifying a role for IKAP in cell motility and migration, it has been suggested that FD results from a disruption in neural crest migration. To determine the function of IKAP during development of the nervous system, we (1) first determined the spatial-temporal pattern of IKAP expression in the developing peripheral nervous system, from the onset of neural crest migration through the period of programmed cell death in the dorsal root ganglia, and (2) using RNAi, reduced expression of IKBKAP mRNA in the neural crest lineage throughout the process of dorsal root ganglia (DRG) development in chick embryos in ovo. Here we demonstrate that IKAP is not expressed by neural crest cells and instead is expressed as neurons differentiate both in the CNS and PNS, thus the devastation of the PNS in FD could not be due to disruptions in neural crest motility or migration. In addition, we show that alterations in the levels of IKAP, through both gain and loss of function studies, perturbs neuronal polarity, neuronal differentiation and survival. Thus IKAP plays pleiotropic roles in both the peripheral and central nervous systems