A previous systematic review reported that topical NSAIDs were effective in relieving pain in chronic conditions like osteoarthritis and tendinitis. More trials, a better understanding of trial quality and bias, and a reclassification of certain drugs necessitate a new review.Studies were identified by searching electronic databases, and writing to manufacturers. We identified randomised, double blind trials comparing topical NSAID with either placebo or another active treatment, in adults with chronic pain. The primary outcome was a reduction in pain of approximately 50% at two weeks, and secondary outcomes were local and systemic adverse events and adverse event-related withdrawals. Relative benefit and number-needed-to-treat (NNT), and relative harm and number-needed-to-harm (NNH) were calculated, and the effects of trial quality, validity and size, outcome reported, and condition treated, were examined by sensitivity analyses.Twelve new trials were added to 13 trials from a previous review. Fourteen double blind placebo-controlled trials had information from almost 1,500 patients. Topical NSAID was significantly better than placebo with relative benefit 1.9 , NNT 4.6 . Results were not affected by trial quality, validity or size, outcome reported, or condition treated. Three trials with 764 patients comparing a topical with an oral NSAID found no difference in efficacy. Local adverse events (6%), systemic adverse events (3%), or the numbers withdrawing due to an adverse event were the same for topical NSAID and placebo.Topical NSAIDs were effective and safe in treating chronic musculoskeletal conditions for two weeks. Larger and longer trials are necessary to fully elucidate the place of topical NSAIDs in clinical practice. A systematic review of topical NSAIDs reported that they were effective for relieving pain in both acute and chronic conditions . Number-There are three reasons why an updated review of topical NSAIDs in chronic pain is needed. First, we have a better appreciation of factors that can introduce bias -4, and wRelevant studies were sought regardless of publication language, type, date or status. Studies included in the previous review were considered for inclusion, and the Cochrane Library, MEDLINE and PreMedline, EMBASE and PubMed, were searched for relevant studies published since the last review, for the years 1996 to April 2003. The search strategy included "application: topical" together with "cream", "gel" etc, together with generic names of NSAIDs, and proprietary preparations of topical treatment in which the principal active ingredient was an NSAID   were extracted. Longer outcomes were also accepted when available.Trial quality was assessed using a validated three-item scale with a maximum quality score of five . IncludeWe defined our own outcome of clinical success, representing approximately a 50% reduction in pain . This wa1) number of patients with a 50% or more reduction in pain2) patient reported global assessment of treatment3) pain on movement4) pain on rest or spontaneous pain5) physician or investigator global assessment of treatmentIn addition, the number of patients showing undefined "improvement" was also accepted. All of these outcomes were grouped together as a "success", and categories 1–4 were used as preferred outcomes in the sensitivity analysis.Secondary outcomes were extracted from included papers that reported them. These were the number of patients (i) reporting one or more local adverse event , (ii) reporting one or more systemic adverse event (iii) withdrawing from trials due to adverse events.The number of patients randomised into each treatment group (intention to treat) was used in the efficacy analysis. Information was pooled for the number of patients in each trial approximating at least 50% pain relief, or similar measure, for both topical NSAID and control. These were used to calculate NNT with a 95% confidence interval (CI) . RelativOur prior intention was to perform sensitivity analyses on pooled outcomes using the z test  for qualTen out of the 20 UK companies, and two out of the 66 continental European companies replied to our request for studies. Only three companies supplied useful material, either published studies or bibliographies. None provided unpublished material.Searches identified 60 target papers, but 35 were excluded; 23 studies failed to meet the inclusion criteria and 12 had no useable data. Twenty-four of these 60 target papers were included in the previous review. We included 13 of those in this review, and excluded 11; seven were not double blind, two compared a salicylate with placebo or oral analgesics, one did not have daily application, and one had insufficient data . Five studies in osteoarthritis specified use of a standard scale  to assess the severity of disease, four specified that the disease was radiologically confirmed, one specified that patients had "well documented mild osteoarthritis", and one made no statement.Quality scores were high, with 16/18 placebo controlled and 9/10 active controlled trials scoring 3 or more points out of a maximum of 5. Validity scores were also high, with 14/18 placebo controlled and 8/10 active controlled trials scoring 9 or more out of a maximum of 16  and 5.Dichotomous information was available to pool from 14 placebo controlled trials for efficacy, from 16 placebo controlled trials for local adverse events, 17 placebo controlled trials for systemic adverse events, and from 11 placebo controlled trials for adverse event related withdrawals.Fourteen trials  provided data on efficacy. Topical NSAIDs were significantly better than placebo  provided some information on adverse events  provided some information on adverse events Table . In two Patients in these trials all had moderate to severe baseline pain, and for those with osteoarthritis, disease severity was generally mild to moderate. Patients with most severe disease were specifically excluded in several trials because authors regarded topical NSAID to be inappropriate for their treatment.Both the original and this updated review concluded that topical NSAIDs were effective in chronic conditions. However, removing trials of lower quality, and topical agents that are not now regarded as topical NSAIDs, increased (worsened) the NNT from 3.1 (95% CI 2.7 to 3.8) to 4.7 (95% CI 3.8 to 5.9) for the outcome of at least half pain relief at two weeks for all topical NSAIDs compared to placebo. For every four or five patients with chronic pain treated with topical NSAID, one would benefit who would not have done with placebo. Three trials comparing topical with oral NSAID found no difference in efficacy.There are a number of aspects of this review that might question this demonstration of efficacy. The trials spanned several decades and retrospective examination finds fault with them in several respects. Many trials were small, and small size can allow chance effects to influence treatment and placebo event rates . DiffereWe addressed these limitations with pre-planned sensitivity analyses. Using studies with higher quality and validity scores, larger size, or higher rather than lower preference outcomes made no difference. Patients treated for knee osteoarthritis derived the same degree of pain relief as those treated for general musculoskeletal conditions. The evidence was that topical NSAIDs were effective whatever strategy was used for sensitivity analysis, improving the robustness of the overall result.A possible criticism might be that there has been selective publication of trials showing topical NSAIDs to be effective, and suppression of trials where there was no difference between topical NSAID and placebo. Funnel plots do not reliably detect publication bias ,14, so wIt is important to emphasise that both active and placebo treatments were rubbed on, making any effect of rubbing equal in both groups. The mean placebo response in the included trials was 26%, compared with the mean response of 48% with topical NSAID. The response with placebo is consistent with that found in acute and chronic pain with a variety of conditions and endpoints .Local adverse events were reported with equal frequency for topical NSAID and topical placebo in placebo-controlled trials, but more often for topical NSAID than oral NSAID in active controlled trials. There were no differences between topical NSAID and topical placebo, or topical NSAID and oral NSAID, for systemic adverse events, or withdrawals due to adverse events. Studies of short duration will not capture important long-term safety information, and this may be important for ongoing applications of gels, creams or sprays in chronic conditions. There is, however, information that indicates that topical NSAIDs do not cause the gastrointestinal harm found with oral NSAIDs , nor areClearly there is a body of evidence to support the efficacy of topical NSAIDs in chronic painful musculoskeletal conditions. Despite removing smaller studies that were not double blind, and substituting newer, larger trials of higher quality, topical NSAIDs remained effective, though the NNT was higher (worse) than originally estimated . More inWe are able to compare the evidence for different topical analgesics in chronic musculoskeletal pain Table . SystemaLM was involved with planning the study, searching, data extraction, analysis, and preparing a manuscript; RAM with planning, data extraction, analysis and writing the manuscript; JE with searching, data extraction, and writing; SD with data extraction, analysis, and writing; HJM with planning, analysis and writing. All authors read and approved the final manuscript.RAM & HJM have consulted for various pharmaceutical companies. RAM, HJM & JE have received lecture fees from pharmaceutical companies related to analgesics and other healthcare interventions. All authors have received research support from charities, government and industry sources at various times, but no such support was received for this work. No author has any direct stock holding in any pharmaceutical company.The pre-publication history for this paper can be accessed here:Search strategy for RCTs of topical NSAIDs in chronic painClick here for fileExcluded studiesClick here for fileQUOROM flow diagramClick here for fileOutcome details of placebo-controlled trialsClick here for fileOutcome details of active-controlled trialsClick here for file


Coccidioidomycosis was first recognized as a serious disease over 100 years ago, but the disease remains an enigma and often goes undiagnosed, even in endemic areas It has been more than a century since coccidioidomycosis was first recognized as a serious disease, and its etiology and epidemiology have been well documented. But the disease remains an enigma to many, and it often goes undiagnosed, even in endemic areas. As management of this chronic disease remains problematic, new preventive or therapeutic options are needed.Coccidioides immitis and C. posadasii, generically referred to as the “Californian” and “non-Californian” species respectively Coccidioidomycosis is a fungal disease found only in the Western Hemisphere. It is caused by two nearly identical species, Mycelial phase—The growth form in the soil, composed of filamentous hyphae and reproductive spores called arthroconidia.Arthroconidia—Reproductive spores, highly resistant to dessication, which are the infectious particles inhaled by man and animals.Spherules—The parasitic phase of this dimorphic fungus; spherules are round cells of 30–100 µM or more that reproduce the progeny endospores.Endospores—The progeny units of the parasitic phase, derived from spherules.C. posadasii is thought to be the predominant species in Mexico Endemic regions for coccidioidomycosis have long been identified in semiarid areas in Mexico As the soil dries or nutrients become limiting, the fungus reproduces asexually by disarticulating the hyphae into small, environmentally-resistant arthroconidia (reproductive spores) . These aIt is estimated that upwards of 100,000 primary coccidioidal infections occur in humans each year in the endemic areas of the United States In their pioneering epidemiologic studies, Smith and colleagues found that about 60% of exposures to the fungus result in asymptomatic infection In regions where tuberculosis rates are high, the two diseases may occur together. Tuberculosis and coccidioidomycosis share common epidemiological, clinical, radiographic, and even histopathological features, making a correct diagnosis extremely difficult in cases where both diseases coexist. In areas where both diseases are endemic, the pertinent studies for diagnosing both conditions should be performed in every patient with compatible clinical features. The diagnosis of one of them does not exclude the possible existence of the other Historically, patients with the primary respiratory form of the disease were not treated because the vast majority recovered on their own. Instead, such patients were given supportive care and were monitored, often with radiographs, until the disease resolved. In recent years, however, an increasing number of physicians are prescribing azole antifungals in cases of primary disease, both because drugs like fluconazole have a good safety record, and because there is a perception that treatment may prevent progression to more serious forms of the disease. This latter presumption, however, is not supported by controlled trial data.All cases of chronic or disseminated disease call for antifungal therapy, but the choice of drugs, route, and duration of therapy is highly dependent on the form of the disease, the severity and site(s) of infection, and the immune status of the patient. Galgiani and colleagues have published clinical practice guidelines on the choice of drug and duration of therapy for a given form of the disease There are only two classes of antifungal therapy routinely used for treatment of coccidioidomycosis. The first class is the polyenes, with amphotericin B desoxycholate and the newer lipid formulations used for the more serious forms of disease. The second class is the azoles, with ketoconazole, fluconazole, itraconazole, and the newer analogue voriconazole as available options. Voriconazole, in particular, is being used more and more often in life-threatening mycoses, and was found to be better than amphotericin B in the primary therapy of invasive aspergillosis Treatment of the more serious or aggressive forms of the disease is typically of long duration and often results in less than complete resolution of disease; relapse is common In addition to drugs, surgery is sometimes indicated to remove focalized infections, such as pulmonary cavities, or to debride osseous forms of the disease Acquired resistance to coccidioidomycosis strongly correlates with the development of a delayed-type hypersensitivity skin test response to coccidioidal antigens Although all humans are equally susceptible to initial infection, there is evidence of genetic predisposition to dissemination, independent of socioeconomic or environmental factors, particularly among African-Americans and Filipinos In cases of marked immunosuppression, either in advanced AIDS or other forms of depressed cellular immunity, the management of coccidioidomycosis is particularly challenging and requires aggressive treatment www.valleyfever.com), has identified and cloned immunogenic proteins that have proven effective in the prevention of deaths and fungal burdens in mouse models of coccidioidomycosis. This suggests that a vaccine for use in humans could be created As previously mentioned, recovery from disease confers lifelong immunity to reinfection, and is a rationale for the development and implementation of a vaccine for the prevention of symptomatic or serious forms of the disease. The combination of increasing incidence of disease, a growing population in the endemic area, and the lack of a highly effective drug treatment justifies efforts to prevent (rather than treat) this disease. To that end, a university-based consortium, the Valley Fever Vaccine Project (Although the vast majority of infected individuals emerge from coccidioidomycosis without complications, an unlucky minority are faced with a debilitating disease that lacks adequate drug options for rapid and completely effective treatment. In the absence of newer therapeutics, discoveries that lead to immunologic intervention


By integrating phenotypic and transcriptional profiling and mapping the data onto metabolic and regulatory networks, it was shown that arsenic probably channels sulfur into glutathione for detoxification, leads to indirect oxidative stress by depleting glutathione pools, and alters protein turnover via arsenation of sulfhydryl groups on proteins. Saccharomyces cerevisiae was determined by profiling global gene expression and sensitivity phenotypes. These data were then mapped to a metabolic network composed of all known biochemical reactions in yeast, as well as the yeast network of 20,985 protein-protein/protein-DNA interactions.Arsenic is a nonmutagenic carcinogen affecting millions of people. The cellular impact of this metalloid in While the expression data unveiled no significant nodes in the metabolic network, the regulatory network revealed several important nodes as centers of arsenic-induced activity. The highest-scoring proteins included Fhl1, Msn2, Msn4, Yap1, Cad1 (Yap2), Pre1, Hsf1 and Met31. Contrary to the gene-expression analyses, the phenotypic-profiling data mapped to the metabolic network. The two significant metabolic networks unveiled were shikimate, and serine, threonine and glutamate biosynthesis. We also carried out transcriptional profiling of specific deletion strains, confirming that the transcription factors Yap1, Arr1 (Yap8), and Rpn4 strongly mediate the cell's adaptation to arsenic-induced stress but that Cad1 has negligible impact.By integrating phenotypic and transcriptional profiling and mapping the data onto the metabolic and regulatory networks, we have shown that arsenic is likely to channel sulfur into glutathione for detoxification, leads to indirect oxidative stress by depleting glutathione pools, and alters protein turnover via arsenation of sulfhydryl groups on proteins. Furthermore, we show that phenotypically sensitive pathways are upstream of differentially expressed ones, indicating that transcriptional and phenotypic profiling implicate distinct, but related, pathways. Saccharomyces cerevisiae have changed the face of biological study from the investigation of individual genes and proteins to a systems-biology approach involving integration of global gene expression with protein-protein and protein-DNA information [Global technologies in the budding yeast ormation . These dormation -4. In thormation .Arsenic, a ubiquitous environmental pollutant found in drinking water, is a metalloid and human carcinogen affecting the skin and other internal organs . It is aSaccharomyces cerevisiae. Bobrowicz et al. [YCF1 [Bacillus subtilis putative arsenic-resistance protein and encodes a small ) efflux transporter that extrudes arsenite from the cytosol [et al. [et al. [A number of proteins involved in metalloid detoxification have been described in different organisms, including z et al.  found thl. [YCF1 . Arr3 is cytosol ,23. Ycf1 cytosol ,22. Unti [et al.  found th [et al. , on the YAP1.Although Arr1 and Yap1 seem specifically suited for arsenic tolerance, the other seven YAP-family proteins are still worthy of investigation in light of the fact that each one regulates a specific set of genes involved in multidrug resistance with overlaps in downstream targets. One such interesting protein is Cad1 (Yap2). Although Yap1 and Cad1 are nearly identical in their DNA-binding domains, Yap1 controls a set of genes (including Ycf1) involved in detoxifying the effects of reactive oxygen species, whereas Cad1 controls genes that are over-represented for the function of stabilizing proteins in an oxidant environment . HoweverUnderstanding the role of AP-1-like proteins (such as YAP family members) in metalloid tolerance was one of the goals in this study within the realm of the larger objective - using an integrative experimental and computational approach to combine gene expression and phenotypic profiles (multiplexed competitive growth assay) with existing high-throughput molecular interaction networks for yeast. As a consequence we uncovered the pathways that influence the recovery and detoxification of eukaryotic cells after exposure to arsenic. Networks were analyzed to identify particular network regions that showed significant changes in gene expression or systematic phenotype. For each data type, independent searches were performed against two networks: the network of yeast protein-protein and protein-DNA interactions, corresponding to signaling and regulatory effects (the regulatory network); and the network of all known biochemical reactions in yeast (the metabolic network). For the gene-expression analysis, we found several significant regions in the regulatory network, suggesting that Yap1 and Cad1 have an important role. However, no significant regions in the metabolic network were found. In order to test the functional significance of Yap1 and Cad1, we used targeted gene deletions of these and other genes, to test a specific model of transcriptional control of arsenic responses.In contrast to the gene-expression data, the phenotypic profile analysis revealed no significant regions in the regulatory network, but two significant metabolic networks. Furthermore, we found that phenotypically sensitive pathways are upstream of differentially expressed ones, indicating that metabolic pathway associations can be discerned between phenotypic and transcriptional profiling. This is the first study to show a relationship between transcriptional and phenotypic profiles in the response to an environmental stress.S. cerevisiae, we performed a series of dose-response studies. We found that treatment of wild type cells with 100 μM and 1 mM AsIII had a negligible effect on growth, but that these cells still exhibited a pronounced transcriptional response . Microarray analysis of biological replicates (four chips per replicate experiment) of the high-dose treated cells (1 mM AsIII) clustered extremely well together when using Treeview . The lower dose time-course (100 μM AsIII) showed the beginning of gene-expression changes at 30 minutes, with the robust changes occurring at 2 hours, or one cell division . The 2 hour, 100 μM dose clustered together with the 30 minute, 1 mM biological replicates and was in fact so similar to them that an experiment of one set of four chips for the 2 hour lower dose was deemed sufficient. Furthermore, when combining the three datasets  and using a 95% confidence interval  we found 271 genes that were not only statistically significant in at least 75% of the total data (9 out of 12 chips), but also that the direction and level of expression of these genes were similar between the datasets. The lower dose time-course also included a 4 hour treatment, or two cell divisions. This experiment demonstrated the greatest degree of variability, indicating either a cycling effect or the cell's return to homeostasis, which was further exemplified by a decrease in the transcriptional response .Before gene-expression analysis of arsenic responses in Genes were categorized by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Simplified Gene Ontology  Table . In totaet al. [We used the Cytoscape network visualization and modeling environment together with the ActiveModules network search plug-in to carry out a comprehensive search of the regulatory and metabolic networks ,28. The et al.  with 2,2de novo protein synthesis in response to arsenic allows energy to be diverted to the increased expression of genes involved in stress responses and protection of the cell. One such pathway may involve sulfur metabolism, which leads to glutathione synthesis. In fact, included in Figure The highest-scoring regulatory network neighborhood was defined by the transcription factor Fhl1 Figure . Its expAnother high-scoring neighborhood comprises part of the proteasome protein complex Figure . The comMany of the central proteins in the significant neighborhoods uncovered by ActiveModules were transcription factors Figure . AlthougTranscription factors Msn2, Yap1, Msn4, Cad1 and Hsf1 were the central proteins for many of the significant neighborhoods found Figure . Togethe2O2) [OYE3 (encoding a NADPH dehydrogenase)). Moreover, Yap1 regulates GSH1, which encodes γ-glutamylcysteine synthetase (an enzyme involved in the biosynthesis of antioxidant glutathione), TRX2 (the antioxidant thioredoxin), GLR1 (glutathione reductase) and drug-efflux pumps ATR1 and FLR1 [GSH1 and ATR1 are examples of several genes also targeted by Cad1. All of these specified Yap1 targets are induced after arsenic exposure, recapitulating the toxicant's role as a likely oxidant. During the course of this work, Wysocki et al. [When overexpressed, Yap1 confers resistance to several toxic agents, and Yap1 mutants are hypersensitive to oxidants ,40-44. C2O2) ,35. Folland FLR1 -50. It si et al.  also impyap1Δ and cad1Δ deletion strains with 100 μM AsIII for 2 hours . Surprisingly, we did not find that Cad1 was involved in regulation in response to arsenic-mediated stress. The yap1Δ strain was not only sensitive to AsIII by phenotypic profiling  but also defective in the induction of several downstream enzymes with antioxidant properties . These were generated using Rosetta Resolver with a p-value less than 0.001 . Also, Additional data files 8 and 9 contain tables of genes failing to be induced or repressed (or showing such a decrease in expression that they no longer make significantly expressed gene lists) in the yap1Δ and cad1Δ experiments, compared to the parent experiment, after treatment with 100 μM AsIII for 2 hours. These are lists of genes that would be potentially regulated by Yap1 and Cad1 in the presence of arsenic.As Cad1 and Yap1 share many downstream targets, the genes defined by these transcription factors are very similar. To determine which transcription factor is playing the most active role in the high level of differential expression for this group  of YAP1, indicating that Yap1 not only activates Rpn4, but that Rpn4 may in fact activate Yap1 [rpn4Δ strain under arsenic stress conditions, whereas Rpn4 was equally induced in the yap1Δ strain .Rpn4 is required for tolerance to cytotoxic compounds and may regulate multidrug resistance via the proteasome . Moreoveet al.  identifiate Yap1 . In supprpn4Δ after treatment with arsenic was the most dramatically altered, save for arr1Δ  in the ARR1 mutant, but show defective induction in the yap1Δ strain treated in parallel . These results indicate that Yap1 may control Arr2 and Arr3 when yeast is subjected to 100 μM AsIII for 2 hours.Arr1 is structurally related to Yap1 and Cad1 ,24. Howeet al. ,59 show  [et al.  supportss et al.  which foet al. [et al.'s studies looked at genes in the normal chromosome context rather than genes ectopically expressed from a plasmid; in addition, in our study, we treated the yeast with 100 μM AsIII while Wysocki et al. [et al. [ARR2 or ARR3 in either the ARR1- or YAP1-deleted strains. Taken together, these data indicate that both ARR1 and YAP1 are important genes involved in the process of arsenite detoxification in the yeast cell, but because of the different strains and treatment protocols used between these three studies, further experiments are warranted to resolve the differences.Our results and those of Menezes et al. , in contet al. , might bi et al.  started  [et al.  used an arr1Δ and parent strains after arsenic treatment  and suggesting that it may have a role in protein degradation as well.These observations indicate that Arr1 may regulate sulfur-assimilation enzymes that are necessary for arsenic detoxification. This is particularly interesting considering that the ActiveModules algorithm identified the node Met31 Figure , the traOur arsenic-treatment experiments revealed the strong induction of over 20 enzymes in the KEGG sulfur amino acid and glutathione biosynthesis pathways Table . This iset al. [GSH1 induction by cadmium is dependent on the presence of Met4, Met31, Met32 and Cbf1 in the transcriptional complex of MET genes. Met4 and Met32 are also differentially expressed in response to arsenic and interact with Met31, which defines a network neighborhood as shown in Figure 2O2 profiles (400 μM H2O2) from Causton et al. [2O2 gene-expression profiles in regard to oxidative-stress response genes, sulfur and methionine metabolism genes, in response to H2O2, were either repressed or did not change  .To identify genes and pathways that confer sensitivity to arsenic, we identified deletion mutants with increased sensitivity to growth inhibition using a deletion mutant library of nonessential genes  . Each stERO1 (7- to 10-fold induced), HCA4 (5- to 9-fold induced), and DCP1 (9- to 22-fold induced). Second, there are redundant pathways mediated by multiple genes, such that deletion of one does not lead to sensitivity. OYE2, OYE3, and a large number of reductases fall into this category. Finally, gene products that do not change significantly, mediate important biological responses and thus when deleted could sensitize the cell to a specific stressor. ARO1, ARO2, THR4 and HOM2 are examples of genes that are not differentially expressed but are very sensitive to arsenic.Only 10% of the top 50 sensitive mutant strains were significantly differentially expressed in the transcript profile. This lack of direct correlation between gene expression and fitness data is consistent with data from our own and other laboratories ,4,65. Atp-aminobenzoic acid (PABA) and folates, which are donors to homocysteine [Like the gene-expression data, the phenotypic data was subjected to searches performed against the regulatory network of yeast protein-protein and protein-DNA interactions as well as the metabolic network of all known biochemical reactions in yeast. Unlike the transcription profile, the phenotypic data analysis revealed no significant regions in the regulatory network, but did map to two statistically significant metabolic networks. The first significant pathway was amino acid synthesis/degradation with the terminal products being L-threonine and L-homoserine, beginning with precursors such as L-arginine, fumarate and oxaloacetate Figure . These pcysteine -69.Combining transcript profiling and phenotypic profiling provides deeper insights into the biology of arsenic responses. Until now there has been a lack of correlation between the differential expression of genes and sensitivity of deletion mutants ,4,65 andThus, we believe our work shows that the deletion of an individual gene can lead to a change in sensitivity to an agent only if the protein product of that gene is important for some process . On the other hand, expression profiling shows the end product of the cell's response to arsenic. Therefore, an agent such as arsenic might cause a transcription factor  to increase the expression of as many as 50 genes, 20 of which might help to protect against the agent. However, deletion of any of the 50 would not be expected to have an effect on the response to arsenic. The effect of gene deletion would be on the transcription factor itself (whose expression might not be affected by the agent). Thus, in the case of arsenic exposure, we conclude that phenotypic profiling interrogates genes upstream of the genes that ultimately protect against arsenic toxicity and that the downstream targets that demonstrate differential expression probably share redundant functions and are not vulnerable in the phenotypic profiling Figure .Systems biology represents an important set of methods for understanding stress responses to environmental toxicants, such as arsenic. In this study we have catalogued the centers of activity associated with arsenic exposure in yeast, identifying the key neighborhoods of activity in the regulatory and metabolic networks using the visualization tools and algorithms in Cytoscape. The transcriptional profile mapped to the regulatory network, revealing several important nodes  as centers of arsenic-induced activity. From these results we can conclude that arsenic detoxification in yeast focuses around: nucleotide and RNA synthesis; methionine metabolism and sulfur assimilation; protein degradation; and transcriptional regulation by proteins that form a stress-response network. In summary, protein synthesis in response to arsenic allows energy to be diverted toward the genes channeling sulfur into glutathione, which then leads to indirect oxidative stress by depleting glutathione pools and alters protein turnover. These processes require regulation by transcription factors, the understanding of which we refined by analysis of specific knockout strains. Our experiments, in fact, confirmed that the transcription factors Yap1, Arr1 and Rpn4 strongly mediate the cell's adaptation to arsenic-induced stress but that Cad1 has negligible impact. Finally, contrary to the gene-expression analyses, the phenotypic profiling data mapped to the metabolic network. The two significant metabolic networks unveiled were shikimate and serine, threonine and glutamate biosynthesis. Our goal was to integrate the computational identification of these important pathways found via transcript and phenotypic profiling by regulatory and metabolic network mapping. In doing so, we have shown that genes that confer sensitivity to arsenic are in pathways that are upstream of the genes that are transcriptionally controlled by arsenic and share redundant functions.S. cerevisiae strain BY4741  was used and grown in synthetic complete medium at 30°C. Cells were grown to a density of 1 × 107 cells per ml. Cultures were split into two; NaAsO2  was added to one culture, and both were incubated at 30°C for 0.5, 2 or 4 h. Cells were pelleted and washed in distilled water before RNA extraction. Deletion strains  of the same background were obtained from Research Genetics, confirmed and treated the same way, for 2 h and 100 μM NaAsO2.+ RNA purification with the Oligotex oligo (dT) selection step. Total RNA for the specific knockout strains and parent experiment was isolated by enzymatic reaction, following the RNeasy yeast protocol (Qiagen).For the cDNA hybridization experiments, total RNA was isolated using an acid-phenol method. Pellets were resuspended in 4 ml lysis buffer . Four milliliters of acid  phenol was added followed by vortexing. The lysing cell solutions were incubated at 65°C for 1 h with occasional vigorous vortexing and then placed on ice for 10 min before centrifuging at 4°C for 10 min. The aqueous layers were re-extracted with phenol  and extracted once with chloroform. Sodium acetate was then added to 0.3 M with 2 volumes of absolute ethanol, placed at -20°C for 30 min, and then spun. Pellets were washed two or three times with 70% ethanol followed by Qiagen Poly(A)et al. [A cDNA yeast chip, developed in-house at National Institute of Environmental Health Sciences (NIEHS), was used for gene-expression profiling experiments. A complete listing of the ORFs on this chip is available at . cDNA miet al.  except tet al. . Genes tet al. . GeneSpret al.  were useThe knockout experiments were conducted on an Agilent yeast oligo array platform. Samples of 10 μg total RNA were labeled using the Agilent fluorescent direct label kit protocol and hybridizations were performed for 16 h in a rotating hybridization oven using the Agilent 60-mer oligo microarray-processing protocol. Slides were washed as indicated and scanned with an Agilent scanner. Data was gathered using the Agilent feature extraction software, using defaults for all parameters, save the ratio terms. To account for the use of the direct label protocol, error terms were changed to: Cy5 multiplicative error = 0.15; Cy3 multiplicative error = 0.25; Cy5 additive error = 20; Cy3 additive error = 20.p-value was less than 0.001. p-values were calculated using the Rosetta Resolver error model with Agilent error terms. The signature genes were analyzed with GeneSpring. The entire in-house and Agilent-based dataset is available in the Additional data files.GEML files and images were exported from the Agilent feature extraction software and deposited into Rosetta Resolver  (Rosetta Biosoftware). Two arrays for each sample pair, including a fluor reversal, were combined into ratio experiments in Rosetta Resolver. Intensity plots were generated for each ratio experiment and genes were considered 'signature genes' if the Genes have previously been categorized into various ontologies and pathways. If a particular pathway is enriched for genes that are significantly expressed in response to a process, we conclude that the pathway is likely to be involved in this process. In total, 829 genes out of 6,240 had a significant alteration in expression in at least one experimental condition. Along with the size of each functional category, a statistical measure for the significance of the enrichment was calculated by using a hypergeometric test. The level of significance for this test was determined using the Bonferroni correction, where the α value was set at 0.05 and the number of tests conducted for KEGG pathway and Simplified Gene Ontology  were 27 and 11, respectively.et al. [The ActiveModules algorithm was used to identify neighborhoods in the regulatory network corresponding to significant levels of differential expression. In this search, if a protein has many neighbors, it is likely that at random a few will show significant changes in expression and these could be selected as a significant sub-network. Neighborhood scoring is a method we used to correct for this bias. In this scheme, a significant sub-network must contain either all or none of the neighbors of each protein. The significance then represents an aggregate over all neighbors of a protein. This prevents the biased selection of a few top-scoring proteins out of a large neighborhood in the search for significant sub-networks. For an in-depth description of this algorithm see Ideker et al. .2O from the search. Scores for each ORF were generated by mapping the fitness significance value to a Z-score. To assign scores to the individual reactions, Förster's mapping from ORF to reaction was used to generate a list of ORFs for each reaction. The Z-scores of these ORFs were then aggregated into a single score for that reaction using the following equation:In defining the network used in the metabolic analysis, edges corresponding to metabolites linking more than 175 reactions were eliminated. This excludes metabolic cofactors such as ATP, NADH and Het al. [n) ending at each node is determined by combining the scores of the individual node and the highest-scoring path of length (n - 1) ending at a neighbor node using the following formula:We used a dynamic programming algorithm adapted from Kelley et al.  to identSince a node with many neighbors is more likely to belong to a high-scoring path by random chance, the score of the neighboring path is corrected against the extreme-value statistic with the number of observations equal to the number of neighbors.p-value, which represents the null hypothesis that there is no significant correlation between the topology of the metabolic network and the assignment of significance values to nodes in that network.The significances of the top-scoring networks were determined by comparison to a distribution of the top-scoring networks from random data (reaction scores randomized with respect to the nodes of the network). After running the path finding/scoring algorithm, the score of the single highest-scoring path was added to the null distribution. This process was repeated for 10,000 interactions. This null distribution was then used to determine an empirical p-value was less than 0.001 and if the fold-change value was greater than or equal to twofold. Signature genes were then broadcasted on the intensity plot and exported as text files. Lists were imported into GeneSpring. The 'Filter on Fold Change' function was used to compare the parent control vs. parent AsIII experiment with each deletion (AsIII) experiment. The gene list selected for each filter on fold change analysis was a combination of the parent signature gene list and the signature gene list of the AsIII-treated deletion being analyzed at the time. For example, if the comparison was being done between parent (AsIII-treated) and Yap1 (AsIII-treated), the list used in the analysis was the combination of the parent signature genes and the Yap1 signature genes. The filter on fold change function reports genes that were selected from the one condition (parent) that had normalized data values that were greater or less than those in the other condition (deletion under investigation) by a factor of twofold. Each resulting gene list was saved. All the resulting gene lists were combined and an annotated gene list was exported for use in Eisen's Cluster/Treeview package (described earlier). The format of the exported data was the natural log. The gene tree generated for the paper was generated in GeneSpring. Each filter on fold change was saved as an annotated gene list.The intensity plots were generated from each experiment in Rosetta Resolver. A gene was considered a signature gene if the Signature gene lists were generated in Rosetta Resolver from intensity plots as described above. Each signature gene list was saved as a 'Bioset' in Resolver. The parent Bioset was compared to each deletion Bioset using the 'Minus' function. This function finds those members in Bioset group 1 (parent) that do not exist in Bioset group 2 (deletion). Each of the resulting lists was saved as a new Bioset. The new 'minus' Bioset was broadcasted on its corresponding intensity plot and exported as a text file. This was repeated for each experiment with fine-tuning of the data using GeneSpring.600 0.05-0.1, split into tubes and treated with arsenic for 1-2 h at 1 mM, 2 mM and 5 mM concentrations. Similar responses were observed at each concentration, so the results were pooled. These cultures and a mock-treated sample were maintained in logarithmic phase growth by periodic dilution for 16-18 h. UPTAG and DOWNTAG sequences were separately amplified from genomic DNA of the drug and mock-treated samples by PCR using biotin-labeled primers as described previously [Homozygous diploid deletion strains and pooling of the strains were done as described . Aliquoteviously . The ampeviously , and acceviously .S. cerevisiae strain BY4741  grown in synthetic complete medium at 30°C after treatment with arsenic. Treatment with 1 mM, 2 mM and 5 mM AsIII resulted in a negligible effect on growth (after 18 h) and survival (1 h treatment followed by plating and colony formation counting), but still exhibited a pronounced transcriptional response . The control parent vs. parent experiment (100 μM AsIII for 2 h) was compared with the yap1Δ . Additional data files yap1Δ, cad1Δ, rpn4Δ and arr1Δ, respectively, compared to the parent without arsenic treatment. Additional data file The following additional data files are available with the online version of this article and at . Additioe et al. ). The deh after 1 h and suh after 1 h and suth after  h and suS. cerevisiae strain, BY4741The dose-response curve of Click here for additional data fileA self-organized tree of arsenite treated yeast experiments and a table depicting the numbers of significant genesClick here for additional data fileThe primary raw cDNA data from all the experimentsClick here for additional data fileThe primary raw data for all the deletion experimentsClick here for additional data fileThe ranked arsenite sensitivity (phenotypic profiling) dataClick here for additional data fileGenes two-fold or more differentially expressed after arsenite in the Yap1 deletion strain compared to the parentClick here for additional data fileGenes two-fold or more differentially expressed after arsenite in the Cad1 deletion strain compared to the parentClick here for additional data fileGenes failing to be induced or repressed by arsenite in the Yap1 deleted strainClick here for additional data fileGenes failing to be induced or repressed by arsenite in the Cad1 deleted strainClick here for additional data fileUnder arsenite-treated conditions, Yap1 might regulate Arr2 and Arr3, and does not regulate Rpn4Click here for additional data fileGenes two-fold or more differentially expressed after arsenite in the Rpn4 deletion strain compared to the parentClick here for additional data fileGenes failing to be induced or repressed by arsenite in the Rpn4 deleted strainClick here for additional data fileGenes two-fold or more differentially expressed after arsenite in the Arr1 deletion strain compared to the parentClick here for additional data fileGenes failing to be induced or repressed by arsenite in the Arr1 deleted strainClick here for additional data fileSelf-organized clustering of deletion strains with AsIII treatment and parent strain vs. deletion strains without arsenicClick here for additional data fileyap1Δ vs. parent without arsenic treatmentGene list of two-fold differential expression in Click here for additional data filecad1Δ vs. parent without arsenic treatmentGene list of two-fold differential expression in Click here for additional data filerpn4Δ vs. parent without arsenic treatmentGene list of two-fold differential expression in Click here for additional data filearr1Δ vs. parent without arsenic treatmentGene list of two-fold differential expression in Click here for additional data fileA file of all the genes mentioned in the paperClick here for additional data file


Bacillus anthracis strains. Sequence quality was shown to be very high by replication and by comparison to independently generated shotgun sequenceCustom-designed resequencing arrays were used to generate 3.1 Mb of genomic sequence from a panel of 56  Bacillus anthracis strains. Sequence quality was shown to be very high by replication (discrepancy rate of 7.4 × 10-7) and by comparison to independently generated shotgun sequence (discrepancy rate < 2.5 × 10-6). Population genomics studies of microbial pathogens using rapid resequencing technologies such as resequencing arrays are critical for recognizing newly emerging or genetically engineered strains.We used custom-designed resequencing arrays to generate 3.1 Mb of genomic sequence from a panel of 56  Bacillus anthracis, genomic sequences from multiple strains and non-pathogenic close relatives could aid studies that definitively identify B. anthracis in environmental and clinical samples, determine forensic attribution and phylogenetic relationships of strains, and uncover the genetic basis of phenotypic variation in traits such as mammalian virulence. Moreover, first recognizing the presence of a novel pathogen, and then attempting the difficult task of discerning between novel naturally occurring pathogenic organisms  and plasmids pXO1 (181.6 kilobases (kb), NC_001496) and pXO2  have been determined /L, where Sn is the number of observed segregating sites at positions with exactly n alleles sequenced , an = Σn-1 i = 1..1/i, and L is the total length of the sequence examined. Var{θ} is estimated by [Σn (Lnθ/an + (Ln)2bnθ2/(an)2]/L2, where Ln is the number of sites with data from exactly n alleles, and bn = Σn-1 i = 1..1/i2. With missing data π is estimated by [Σi 2piqini/(ni - 1)]/L, where the sum is taken over all sites i, pi and qi are the allele frequencies at site i, and ni is the number of alleles sequenced at site i.To account for missing data, θ is estimated by  and from this determine the expected percent of sites under the neutral expectation. This is directly compared with the observed percent of SNPs in Figure Comparing the observed site frequency spectrum with that expected under the neutral theory is a powerful approach to detect unusual patterns of genetic diversity. We employed two different approaches for this analysis. First, we calculated the expected number of sites with minor allele frequency i as Σ is their observed frequency, and .where N is the number of SNPs observed for each class, B. anthracis genome length , to determine the expected number of SNPs that we would expect to observe among two B. anthracis strains sampled in same random fashion as isolates in this study were chosen. Using Equations 6-9 in [ and θ estimators. The one standard deviation (SD) that we report is the square root of this variance.As a second method, we employed Tajima's D statistic , estimats 6-9 in , we calcThe 37 variable positions identified in this study were concatenated together to create artificial sequence types. A DNA distance matrix was created using DNADIST, plotted as a UPGMA tree using NEIGHBOR and the tree plotted using DRAWGRAM .B. anthracis strains from the Biological Defense Research Directorate (BDRD) strain collection resequenced in this study. Additional data file B. anthracis SNPs identified in this study. The data include the BDRD SNP ID, the GenBank reference sequence and RA fragment containing the SNP, the SNP position relative to the GenBank reference sequence and the RA sequence, the SNP frequency, and the listing of the base calls in all strains at sites harboring SNPs. Additional data file B. anthracis genes partially or wholly resequenced in this study. The observed number SNPs by SNP type (silent vs replacement) for each gene are provided. Finally, Additional data file The following additional data are available with the online version of this article. Additional data file B. anthracis strains from the Biological Defense Research Directorate (BDRD) strain collection resequenced in this studyClick here for additional data fileThe BDRD-01 RA fragment names, the GenBank reference sequence from which they are derived, the length of the unique genomic sequences submitted to RA design, the length of the unique genomic sequences capable of being queried, and the LPCR primer pairs used to amplify the RA fragmentsClick here for additional data fileB. anthracis SNPs identified in this study. The data include the BDRD SNP ID, the GenBank reference sequence and RA fragment containing the SNP, the SNP position relative to the GenBank reference sequence and the RA sequence, the SNP frequency, and the listing of the base calls in all strains at sites harboring SNPsThe Click here for additional data fileB. anthracis genes partially or wholly resequenced in this studyThe 31 Click here for additional data fileThe genomic sequences submitted to RA design for BDRD-01Click here for additional data file


West Nile virus (WNV) recently became a major public health concern in North America, the Middle East, and Europe. In contrast with the investigations of the North-American isolates, the neurovirulence properties of Middle-Eastern strains of WNV have not been extensively characterized. Israeli WNV strain IS-98-ST1 that has been isolated from a white stork in 1998, was found to be highly neuroinvasive in adult C57BL/6 mice. Strain IS-98-ST1 infects primary neuronal cells from mouse cortex, causing neuronal death. These results demonstrate that Israeli strain IS-98-ST1 provides a suitable viral model for WNV-induced disease associated with recent WNV outbreaks in the Old World. Flaviviridae, genus flavivirus) with a worldwide distribution ranging Africa, Europe, the Middle East, and Asia. WNV was first recognized in the Western Hemisphere in 1999. The emergence of WNV has been associated with a dramatic increase in severity of disease in humans and other species[West Nile virus (WNV) is a single-stranded RNA flavivirus  and the lineage I  that caused the outbreaks of WNV infection in North Africa, Europe, Israel, and in the United States. Nucleotide sequencing revealed that American strains of WNV isolated between 1999 and 2000 are nearly identical to Israeli strains of WNV isolated in 1998 and 2000 ,4. This Aedes pseudoscutellaris AP61[The murine model of WNV-associated encephalitis has been widely used to address the viral pathogenesis. Strainsaris AP61 and its aris AP61. InfectiIn this study, we demonstrated that IS-98-ST1 has a high neuroinvasive potential in adult C57Bl/6 mice, and that the virus is capable to replicate in primary neuronal cultures from mouse brain cortex.Mouse experiments were performed according to the European Convention 2001–486. After anesthesia, six-week-old female C57BL/6 mice  were inoculated with 1,000 FFU of WNV via different routes : intraperitoneal (i.p.), intradermal (i.d.), intracerebral (i.c.), and intranasal (i.n.). At Days 5 and 7 of infection, three animals per group were euthanasied; brain and spinal cord were rapidly removed, processed for viral titration or sectioned on cryostat . Sections were fixed with 3.7% formaldehyde or acetone for 30 min and processed for indirect immunofluorescence with mouse polyclonal anti-WNV antibodies[5 (i.d. route) to 3.108 FFU/g (i.c. route).When infected i.c., mice died at day 7.3 ± 1 post-infection (p.i.) ; 100% mortality was also reached after i.p., i.n., or i.d. inoculation but with delayed kinetics . In all cases, WNV-infected mice exhibited characteristic disease progression with hind limb paralysis, cachexia and tremors. By day 7 p.i., WNV was found in brain tissue in all mice, reaching virus titers from 3.10To investigate WNV location within the CNS, cryostat brain sections from three WNV-infected mice were assessed for the presence of viral antigens by immunofluorescence at day 7 p.i. When inoculated i.c, virus was found widespread in most of the brain structures , including cortex Fig. , pyramid7 FFU of WNV per ml was detected in the culture supernatant. Time course studies showed that IS-98-ST1 infection induced cell death through neuronal necrosis within 48 h of infection, and ~90% of cells had detached by 96 h  . Briefly6 h Fig. . Whateve6 h Fig. . GFAP poAlthough our study was limited in its scope, the results indicate that WNV strain IS-98-ST1 is suitable as viral model for West Nile encephalitis in the Old World. The Israeli strain IS-98-ST1 that caused the epizootic in Israel in 1998, was found to be highly neuroinvasive in mice following peripheral inoculation. Consistent with this observation, we reported that IS-98-ST1 has an i.p. LD50 value as low as 10 FFU. High viin vivo. Because neurons are believed to be main target neural cells of WNV, we developed an ex-vivo model of infection, by culturing primary neural cells from the brain cortex of susceptible mice. More than 90% of the neurons are found to be infected by IS-98-ST1 and infected neurons undergo necrosis. In contrast, astrocytes were mainly resistant to WNV infection. This is consistent with in vivo data showing a massive infection of brain structures such as brain stem, hippocampus and cortex of WNV-infected animals [Our study confirms the neurotropism of WNV and the huge preferential infection of neurons  animals  and huma animals . The hig animals ,19. In cex-vivo studies, M-PF and TM participated in in vivo experiments, VD and J-LG revised critically the article, PD and P-EC have written, drafted the article, and participated to in vivo and ex-vivo experiments.ML carried out The authors declare that they have no competing interests.