Much of a cell's activity is organized as a network of interacting modules: sets of genes coregulated to respond to different conditions. We present a probabilistic method for identifying regulatory modules from gene expression data. Our procedure identifies modules of coregulated genes, their regulators and the conditions under which regulation occurs, generating testable hypotheses in the form 'regulator X regulates module Y under conditions W'. We applied the method to a Saccharomyces cerevisiae expression data set, showing its ability to identify functionally coherent modules and their correct regulators. We present microarray experiments supporting three novel predictions, suggesting regulatory roles for previously uncharacterized proteins.

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Innate immunity is an ancient and conserved defense mechanism. Although host responses toward various pathogens have been delineated, how these responses are orchestrated in a whole animal is less understood. Through an unbiased genome-wide study performed in Caenorhabditis elegans, we identified a conserved function for endodermal GATA transcription factors in regulating local epithelial innate immune responses. Gene expression and functional RNAi-based analyses identified the tissuespecific GATA transcription factor ELT-2 as a major regulator of an early intestinal protective response to infection with the human bacterial pathogen Pseudomonas aeruginosa. In the adult worm, ELT-2 is required specifically for infection responses and survival on pathogen but makes no significant contribution to gene expression associated with intestinal maintenance or to resistance to cadmium, heat, and oxidative stress. We further demonstrate that this function is conserved, because the human endodermal transcription factor GATA6 has a protective function in lung epithelial cells exposed to P. aeruginosa. These findings expand the repertoire of innate immunity mechanisms and illuminate a yet-unknown function of endodermal GATA proteins.gene expression ͉ innate immunity ͉ infection ͉ ELT-2 ͉ Pseudomonas aeruginosa

It is now well accepted that the gut microbiota contributes to our health. However, what determines the microbiota composition is still unclear. Whereas it might be expected that the intestinal niche would be dominant in shaping the microbiota, studies in vertebrates have repeatedly demonstrated dominant effects of external factors such as host diet and environmental microbial diversity. Hypothesizing that genetic variation may interfere with discerning contributions of host factors, we turned to Caenorhabditis elegans as a new model, offering the ability to work with genetically homogenous populations. Deep sequencing of 16S rDNA was used to characterize the (previously unknown) worm gut microbiota as assembled from diverse produce-enriched soil environments under laboratory conditions. Comparisons of worm microbiotas with those in their soil environment revealed that worm microbiotas resembled each other even when assembled from different microbial environments, and enabled defining a shared core gut microbiota. Community analyses indicated that species assortment in the worm gut was non-random and that assembly rules differed from those in their soil habitat, pointing at the importance of competitive interactions between gut-residing taxa. The data presented fills a gap in C. elegans biology. Furthermore, our results demonstrate a dominant contribution of the host niche in shaping the gut microbiota.

Brain injury may result in the development of epilepsy, one of the most common neurological disorders. We previously demonstrated that albumin is critical in the generation of epilepsy after blood-brain barrier (BBB) compromise. Here, we identify TGF-␤ pathway activation as the underlying mechanism. We demonstrate that direct activation of the TGF-␤ pathway by TGF-␤1 results in epileptiform activity similar to that after exposure to albumin. Coimmunoprecipitation revealed binding of albumin to TGF-␤ receptor II, and Smad2 phosphorylation confirmed downstream activation of this pathway. Transcriptome profiling demonstrated similar expression patterns after BBB breakdown, albumin, and TGF-␤1 exposure, including modulation of genes associated with the TGF-␤ pathway, early astrocytic activation, inflammation, and reduced inhibitory transmission. Importantly, TGF-␤ pathway blockers suppressed most albumininduced transcriptional changes and prevented the generation of epileptiform activity. Our present data identifies the TGF-␤ pathway as a novel putative epileptogenic signaling cascade and therapeutic target for the prevention of injury-induced epilepsy.