Stressed cells coordinate a multi-faceted response spanning many levels of physiology. Yet knowledge of the complete stress-activated regulatory network as well as design principles for signal integration remains incomplete. We developed an experimental and computational approach to integrate available protein interaction data with gene fitness contributions, mutant transcriptome profiles, and phospho-proteome changes in cells responding to salt stress, to infer the salt-responsive signaling network in yeast. The inferred subnetwork presented many novel predictions by implicating new regulators, uncovering unrecognized crosstalk between known pathways, and pointing to previously unknown ‘hubs’ of signal integration. We exploited these predictions to show that Cdc14 phosphatase is a central hub in the network and that modification of RNA polymerase II coordinates induction of stress-defense genes with reduction of growth-related transcripts. We find that the orthologous human network is enriched for cancer-causing genes, underscoring the importance of the subnetwork's predictions in understanding stress biology.

We describe a synthesis strategy for the preparation of lysine isotopologues that differ in mass by as little as 6 mDa. We demonstrate that incorporation of these molecules into the proteomes of actively growing cells does not affect cellular proliferation, and we discuss how to use the embedded mass signatures (neutron encoding (NeuCode)) for multiplexed proteome quantification by means of high-resolution mass spectrometry. NeuCode SILAC amalgamates the quantitative accuracy of SILAC with the multiplexing of isobaric tags and, in doing so, offers up new opportunities for biological investigation. Large-scale technologies for the comparative analysis of proteomes have become essential for modern biology and medicine (1, 2). To satisfy this increasing demand and boost statistical power, parallel processing of proteomes (i.e. multiplexing) is key. The ground was broken in this field about two decades ago by advances in both MS and stable isotope labeling (3-5). Since then, two distinct strategies have emerged, each with its own strengths and weaknesses. The first approach, stable isotope labeling by amino acids in cell culture (SILAC), 1 metabolically incorporates labeled amino acids into proteins and is considered the gold standard (6 -8). SILAC quantification provides unmatched accuracy, but simultaneous comparison of more than three proteomes, although possible, is not practical for most global studies (9, 10). A second, and increasingly popular, method is to chemically modify peptides originating from up to 10 different sources (a 3-to 5-fold boost in throughput over SILAC) with isobaric reagents (e.g. TMT or iTRAQ) (11)(12)(13)(14). The escalated throughput afforded by this strategy is, for many applications, essential; however, multiplexing via isobaric tagging comes at the cost of quantitative accuracy (15-17). Furthermore, because each sample is handled independently prior to labeling, systematic and random variation that occurs during sample processing cannot be accounted for as it is with metabolic labeling. Thus, experimenters designing a quantitative proteomics experiment must choose between accuracy and throughput.Recently we described a new approach that blends the SILAC and isobaric tagging methods (18). The strategy, neutron encoding (NeuCode), relies on the mass defects of atoms and their isotopes (19). In studies using two isotopologues of lysine, differing by 36 mDa, NeuCode SILAC quantified proteins as well as traditional SILAC, but it allowed deeper proteome coverage. NeuCode harnesses the exceptional resolving power of modern FT-MS systems so that quantitative information is only revealed by high-resolution scanning when desired, in either MS or tandem MS scans (20,21).Owing to the lack of suitable lysine isotopologues, our initial work with NeuCode SILAC offered only duplex quantification; consequently, we could only predict the utility of NeuCode SILAC (18). To test our supposition that NeuCode SILAC has the potential to combine the benefits of traditional SILAC and

Microbes can be metabolically engineered to produce biofuels and biochemicals, but rerouting metabolic flux toward products is a major hurdle without a systems-level understanding of how cellular flux is controlled. To understand flux rerouting, we investigated a panel of Saccharomyces cerevisiae strains with progressive improvements in anaerobic fermentation of xylose, a sugar abundant in sustainable plant biomass used for biofuel production. We combined comparative transcriptomics, proteomics, and phosphoproteomics with network analysis to understand the physiology of improved anaerobic xylose fermentation. Our results show that upstream regulatory changes produce a suite of physiological effects that collectively impact the phenotype. Evolved strains show an unusual co-activation of Protein Kinase A (PKA) and Snf1, thus combining responses seen during feast on glucose and famine on non-preferred sugars. Surprisingly, these regulatory changes were required to mount the hypoxic response when cells were grown on xylose, revealing a previously unknown connection between sugar source and anaerobic response. Network analysis identified several downstream transcription factors that play a significant, but on their own minor, role in anaerobic xylose fermentation, consistent with the combinatorial effects of small-impact changes. We also discovered that different routes of PKA activation produce distinct phenotypes: deletion of the RAS/PKA inhibitor IRA2 promotes xylose growth and metabolism, whereas deletion of PKA inhibitor BCY1 decouples growth from metabolism to enable robust fermentation without division. Comparing phosphoproteomic changes across ira2Δ and bcy1Δ strains implicated regulatory changes linked to xylose-dependent growth versus metabolism. Together, our results present a picture of the metabolic logic behind anaerobic xylose flux and suggest that widespread cellular remodeling, rather than individual metabolic changes, is an important goal for metabolic engineering.

Here we constructed and characterized an ilvE deletion mutant of S. mutans UA159. Growth experiments revealed that the ilvE mutant strain has a lag in growth when nutritionally limited for branched-chain amino acids. We further demonstrated that the loss of ilvE causes a decrease in acid tolerance. The ilvE strain exhibits a defect in F 1 -F o ATPase activity and has reduced catabolic activity for isoleucine and valine. Results from transcriptional studies showed that the ilvE promoter is upregulated during growth at low pH. Collectively, the results of this investigation show that amino acid metabolism is a component of the acidadaptive repertoire of S. mutans.

c NADH oxidase (Nox, encoded by nox) is a flavin-containing enzyme used by the oral pathogen Streptococcus mutans to reduce diatomic oxygen to water while oxidizing NADH to NAD ؉ . The critical nature of Nox is 2-fold: it serves to regenerate NAD ؉ , a carbon cycle metabolite, and to reduce intracellular oxygen, preventing formation of destructive reactive oxygen species (ROS). As oxygen and NAD؉ have been shown to modulate the activity of the global transcription factors Spx and Rex, respectively, Nox is potentially poised at a critical junction of two stress regulons. In this study, microarray data showed that either addition of oxygen or loss of nox resulted in altered expression of genes involved in energy metabolism and transport and the upregulation of genes encoding ROS-metabolizing enzymes. Loss of nox also resulted in upregulation of several genes encoding transcription factors and signaling molecules, including the redox-sensing regulator gene rex. Characterization of the nox promoter revealed that nox was regulated by oxygen, through SpxA, and by Rex. These data suggest a regulatory loop in which the roles of nox in reduction of oxygen and regeneration of NAD ؉ affect the activity levels of Spx and Rex, respectively, and their regulons, which control several genes, including nox, crucial to growth of S. mutans under conditions of oxidative stress.

Summary A collection of tagged deletion mutant strains was created in Streptococcus mutans UA159 to facilitate investigation of the aciduric capability of this oral pathogen. Gene-specific barcoded deletions were attempted in 1432 open reading frames (representing 73% of the genome), and resulted in the isolation of 1112 strains (56% coverage) carrying deletions in distinct non-essential genes. Since S. mutans virulence is predicated upon the ability of the organism to survive an acidic pH environment, form biofilms on tooth surfaces, and out-compete other oral microflora, we assayed individual mutant strains for the relative fitness of the deletion strain, compared to the parent strain, under acidic and oxidative stress conditions, as well as for their ability to form biofilms in glucose- or sucrose-containing medium. Our studies revealed a total of 51 deletion strains with defects in both aciduricity and biofilm formation. We have also identified 49 strains whose gene deletion confers sensitivity to oxidative damage and deficiencies in biofilm formation. We demonstrate the ability to examine competitive fitness of mutant organisms using the barcode tags incorporated into each deletion strain to examine the representation of a particular strain in a population. Co-cultures of deletion strains were grown either in vitro in a chemostat to steady-state values of pH 7 and 5 or in vivo in an animal model for oral infection. Taken together, this data represents a mechanism for assessing the virulence capacity of this pathogenic microorganism and a resource for identifying future targets for drug intervention to promote healthy oral microflora.

To cope with sudden changes in the external environment, the budding yeast Saccharomyces cerevisiae orchestrates a multifaceted response that spans many levels of physiology. Several studies have interrogated the transcriptome response to endoplasmic reticulum (ER) stress and the role of regulators such as the Ire1 kinase and Hac1 transcription factors. However, less is known about responses to ER stress at other levels of physiology. Here, we used quantitative phosphoproteomics and computational network inference to uncover the yeast phosphoproteome response to the reducing agent dithiothreitol (DTT) and the upstream signaling network that controls it. We profiled wild-type cells and mutants lacking IRE1 or MAPK kinases MKK1 and MKK2, before and at various times after DTT treatment. In addition to revealing downstream targets of these kinases, our inference approach predicted new regulators in the DTT response, including cell-cycle regulator Cdc28 and osmotic-response kinase Rck2, which we validated computationally. Our results also revealed similarities and surprising differences in responses to different stress conditions, especially in the response of protein kinase A targets. These results have implications for the breadth of signaling programs that can give rise to common stress response signatures.

Cells respond to stressful conditions by coordinating a complex, multi-faceted response that spans many levels of physiology. Much of the response is coordinated by changes in protein phosphorylation. Although the regulators of transcriptome changes during stress are well characterized in Saccharomyces cerevisiae, the upstream regulatory network controlling protein phosphorylation is less well dissected. Here, we developed a computational approach to infer the signaling network that regulates phosphorylation changes in response to salt stress. We developed an approach to link predicted regulators to groups of likely co-regulated phospho-peptides responding to stress, thereby creating new edges in a background protein interaction network. We then use integer linear programming (ILP) to integrate wild type and mutant phospho-proteomic data and predict the network controlling stress-activated phospho-proteomic changes. The network we inferred predicted new regulatory connections between stress-activated and growth-regulating pathways and suggested mechanisms coordinating metabolism, cell-cycle progression, and growth during stress. We confirmed several network predictions with co-immunoprecipitations coupled with mass-spectrometry protein identification and mutant phospho-proteomic analysis. Results show that the cAMP-phosphodiesterase Pde2 physically interacts with many stress-regulated transcription factors targeted by PKA, and that reduced phosphorylation of those factors during stress requires the Rck2 kinase that we show physically interacts with Pde2. Together, our work shows how a high-quality computational network model can facilitate discovery of new pathway interactions during osmotic stress.