Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

A metabolomics analysis of Salmonella infection

ABSTRACT: The interplay between pathogens and hosts has been studied for decades using targeted approaches such as the analysis of mutants and host immunological responses. Although much has been learned from such studies, they focus on individual pathways and fail to reveal the global effects of infection on the host. To alleviate this issue, high-throughput methods such as transcriptomics and proteomics have been used to study host-pathogen interactions. Recently, metabolomics was established as a new method to study changes in the biochemical composition of host tissues. We report a metabolomics study of Salmonella enterica serovar Typhimurium infection. We used Fourier Transform Ion Cyclotron Resonance Mass Spectrometry with Direct Infusion to reveal that dozens of host metabolic pathways are affected by Salmonella in a murine infection model. In particular, multiple host hormone pathways are disrupted. Our results identify unappreciated effects of infection on host metabolism and shed light on mechanisms used by Salmonella to cause disease, and by the host to counter infection. Female C57BL/6 mice were infected with Salmonella enterica serovar Typhimurium SL1344 cells by oral gavage. Feces and livers were collected and metabolites extracted using acetonitrile. For experiments with feces, samples were collected from 4 mice before and after infection. For liver experiments, 11 uninfected and 11 infected mice were used. Samples were combined into 3 groups of 3-4 mice each, resulting in the analysis of 3 group samples of uninfected and 3 of infected mice. Extracts were infused into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140 [PMID 19081807]). To identify differences in metabolite composition between uninfected and infected samples, we filtered the list of masses for metabolites which were present on one set of samples but not the other. Additionally, we calculated the ratios between averaged intensities of metabolites from uninfected and infected mice. To assign possible metabolite identities, monoisotopic neutral masses of interest were queried against MassTrix (http://masstrix.org). Masses were searched against the Mus musculus database within a mass error of 3 ppm. Data were analyzed by unpaired t tests with 95% confidence intervals.

ORGANISM(S): Mus musculus

SUBMITTER: L. Caetano Antunes

PROVIDER: E-GEOD-21720 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Impact of salmonella infection on host hormone metabolism revealed by metabolomics.

Antunes L Caetano M LC Arena Ellen T ET Menendez Alfredo A Han Jun J Ferreira Rosana B R RB Buckner Michelle M C MM Lolic Petra P Madilao Lufiani L LL Bohlmann Jörg J Borchers Christoph H CH Finlay B Brett BB

Infection and immunity 20110214 4

The interplay between pathogens and their hosts has been studied for decades using targeted approaches, such as the analysis of mutants and host immunological responses. Although much has been learned from such studies, they focus on individual pathways and fail to reveal the global effects of infection on the host. To alleviate this issue, high-throughput methods, such as transcriptomics and proteomics, have been used to study host-pathogen interactions. Recently, metabolomics was established a ...[more]

PMID: 21321075

Similar Datasets

Project description:The importance of the mammalian intestinal microbiota to human health has been intensely studied over the past few years. It is now clear that the interactions between human hosts and their associated microbial communities need to be characterized in molecular detail if we are to truly understand human physiology. Additionally, the study of such host-microbe interactions is likely to provide us with new strategies to manipulate such complex systems to maintain or restore homeostasis in order to prevent or cure pathological states. We describe the use of high-throughput metabolomics to shed light on the interactions between the intestinal microbiota and the host. We show that treatment with the antibiotic streptomycin disrupts intestinal homeostasis and has a profound impact on the intestinal metabolome, affecting the levels of over 87% of all metabolites detected. Many metabolic pathways that are critical for host physiology were affected, including bile acid, eicosanoid and steroid hormone synthesis. Interestingly, many of these pathways are also affected by intestinal pathogens. Dissecting the effect of both beneficial and pathogenic bacteria on some of these pathways will be instrumental in understanding the interplay between the host, the resident microbiota and incoming pathogens and may aid in the design of new therapeutic strategies that target these interactions. Age-matched female C57BL/6 mice were used. Fresh feces were collected and stored at -80 oC. Mice were then treated with 20 mg of streptomycin through oral gavage and fresh feces were collected 24 hours after treatment and stored at -80 oC until used. To extract metabolites from feces, acetonitrile was added to samples (approximately 10-25 μL of acetonitrile per 1 mg of tissue), which were then homogenized. The samples were then cleared by centrifugation and the supernatant was collected and dried at room temperature using a centrifuge equipped with a vacuum pump. All extracts were kept at -80 oC until used. For metabolic profiling, the dried extracts from mouse feces were suspended in a 2:3 mixture of water and acetonitrile (10 μL per 1 mg of tissue), vortexed and cleared by centrifugation. Supernatants were collected and used as described below. Extracts were diluted 1:5 with 60% acetonitrile containing either 0.2% formic acid (for positive ion mode) or 0.5% ammonium hydroxide (for negative ion mode) and spiked with predefined amounts of the "ES tuning mix" solution as the internal standard for mass calibration. The solutions were then infused, using a syringe pump (KDS Scientific, Holliston, USA) at a flow rate of 2.5 µL per minute, into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer (Bruker Daltonics, Billerica, USA) equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Data were recorded in positive and negative ion modes with broadband detection and an FT acquisition size of 1024 kilobytes per second, within a range of m/z 150 to 1100. Under these settings, a mass resolution of ca. 100,000 (full width at half maximum, FWHM) at m/z 400 and a mass accuracy within 2 ppm or less for all detected components, following internal mass calibration, were observed. Other experimental parameters were: capillary electrospray voltage of 3600-3750 V, spray shield voltage of 3300-3450 V, source ion accumulation time of 0.1 s and collision cell ion accumulation time of 0.2 s. To increase detection sensitivity, survey scan mass spectra in positive and negative ion modes were acquired from the accumulation of 200 scans per spectrum, and duplicate acquisitions per sample were carried out to ensure data reproducibility. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140). To identify differences in metabolite composition between untreated and treated samples, we first filtered our list of masses for metabolites that were present on one set of samples (untreated or treated) but not the other. Additionally, we averaged the mass intensities of metabolites in each group and calculated the ratios between averaged intensities of metabolites from untreated and treated samples. To assign possible metabolite identities to the masses present in only one of the sample groups or showing at least a 2-fold change in intensities between the sample groups, the monoisotopic neutral masses of interest were queried against MassTrix (http://masstrix.org), a free-access software designed to incorporate masses into metabolic pathways. Masses were searched against the Mus musculus database within a mass error of 3 ppm. Data were analyzed by unpaired t tests with 95% confidence intervals.

Project description:To cause disease, Salmonella enterica serovar Typhimurium requires two type-III secretion systems, encoded on Salmonella Pathogenicity Islands 1 and 2 (SPI-1 and -2). These secretion systems serve to deliver virulence proteins, termed effectors, into the host cell cytosol. While the importance of these effector proteins to promote colonization and replication within the host has been established, the specific roles of individual secreted effectors in the disease process are not well understood. In this study, we used an in vivo gallbladder epithelial cell infection model to study the function of the SPI-2-encoded effector, SseL. Deletion of the sseL gene resulted in bacterial filamentation and elongation and unusual localization of Salmonella within infected epithelial cells. Infection with the ?sseL strain also caused dramatic changes in lipid metabolism and led to massive accumulation of lipid droplets in infected cells. Some of these changes were investigated through metabolomics of gallbladder tissue. This phenotype was directly attributed to the deubiquitinase activity of SseL, as a Salmonella strain carrying a single point mutation in the catalytic cysteine resulted in the same phenotype as the deletion mutant. Excessive buildup of lipids due to the absence of a functional sseL gene was also observed in S. Typhimurium-infected livers. These results demonstrate that SseL alters host lipid metabolism in infected epithelial cells by modifying ubiquitination patterns of cellular targets. Female C57BL/6 mice were infected with the indicated strain of Salmonella enterica serovar Typhimurium by oral gavage. Four gallbladders were collected and pooled per sample group and metabolites extracted using a mixture of methanol and chloroform. Extracts were infused into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140). To identify differences in metabolite composition between different groups of samples, we filtered the list of masses for metabolites which were present on one set of samples but not the other. Additionally, we calculated the ratios between averaged intensities of metabolites from each group of mice. To assign possible metabolite identities, monoisotopic neutral masses of interest were queried against MassTrix (http://masstrix.org). Masses were searched against the Mus musculus database within a mass error of 3 ppm.

Project description:During the colonization of hosts, bacterial pathogens are presented with many challenges that must be overcome for colonization to successfully occur. This requires bacterial sensing of the surroundings and adaptation to the conditions encountered. One of the major impediments to pathogen colonization of the mammalian gastrointestinal tract is the antibacterial action of bile. Salmonella enterica serovar Typhimurium has specific mechanisms involved in resistance to bile. Besides being resistant to it, Salmonella can also successfully multiply in bile, using it as a source of nutrients. This accomplishment is highly relevant to pathogenesis, as Salmonella colonizes the gallbladder of hosts, where it can be carried asymptomatically and promote further host spread and transmission. In order to gain insights into the mechanisms used by Salmonella to grow in bile, we studied the changes elicited by Salmonella in the chemical composition of bile during growth in vitro and in vivo through a metabolomics approach. Our data suggest that phospholipids are an important source of carbon and energy for Salmonella during growth in the laboratory as well as during gallbladder infections of mice. Further studies in this area will generate a better understanding of how Salmonella exploits this generally hostile environment for its own benefit. For in vitro studies, bile was extracted from C57BL/6 mice and used immediately. An overnight culture of Salmonella enterica serovar Typhimurium SL1344 was used to inoculate 10 ?L of bile at an approximate density of 5x10^6 cells/mL. The experiment was performed in duplicate, and a total of 2 uninfected and 2 infected bile samples were studied. Samples were incubated for 24 hours at 37 oC with shaking. After incubation, samples were centrifuged to remove bacteria and the supernatant was saved for metabolomic analyses. For in vivo studies, C57BL/6 mice were infected with approximately 10^8 bacterial cells by oral gavage. Four groups of three to four mice each were either infected with Salmonella or kept uninfected (total of 11 mice per treatment group). Five days after infection, all mice were sacrificed and bile was collected. Samples were centrifuged and supernatants saved for metabolomic analyses. Samples were prepared by mixing equal volumes of bile from three to four mice, generating three samples per treatment (uninfected and infected), which were used in the subsequent steps. Seven microliters of each sample was evaporated and the residue resuspended in 50% acetonitrine. Extracts were infused into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140). To identify differences in metabolite composition between different groups of samples, we filtered the list of masses for metabolites which were present on one set of samples but not the other. Additionally, we calculated the ratios between averaged intensities of metabolites from each group of mice. To assign possible metabolite identities to the masses selected as described above, the monoisotopic neutral masses of interest were queried against the Human Metabolome Database (HMDB, http://www.hmdb.ca), with a tolerance of 0.001 Da.

Project description:Cyanobacteria are highly abundant in the oceans where they are constantly exposed to lytic viruses. Some viruses are restricted to a narrow host range while others infect a broad range of hosts. It is currently unknown whether broad-host range phages employ the same infection program, or regulate their program in a host-specific manner to accommodate for the different genetic makeup and defense systems of each host. Here we used a combination of microarray and RNA-seq analyses to investigate the interaction of three phylogentically distinct Synechococcus strains, WH7803, WH8102, and WH8109, with the broad-host range T4-like myovirus, Syn9, during infection. Strikingly, we found that the phage led a nearly identical expression program in the three hosts despite considerable differences in host gene content. On the other hand, host responses to infection involved mainly host-specific genes, suggesting variable attempts at defense against infection. A large number of responsive host genes were located in hypervariable genomic islands, substantiating genomic islands as a major axis of phage-bacteria interactions in cyanobacteria. Furthermore, transcriptome analyses and experimental determination of the complete phage promoter map revealed three temporally regulated modules and not two as previously thought for cyanophages. In contrast to T4, an extensive, previously unknown regulatory motif drives expression of early genes and host-like promoters drive middle-gene expression. These promoters are highly conserved among cyanophages and host-like middle promoters extend to other T4-like phages, indicating that the well-known mode of regulation in T4 is not the rule among the broad family of T4-like phages. We investigated the infection process and transcriptional program of the P-TIM40 cyanophage during infection of a Prochlorococcus NATL2A host. The results are discussed in conjunction with results obtained from the infection process for the Syn9 cyanophage in three different Synechococcus hosts: WH7803 (Dufresne et al. 2008), WH8102 (Palenik et al. 2003) and WH8109 (sequenced as part of this study).

Project description:Tuberculosis kills nearly 2 million people through out the world, every year. The outcome of M. tuberculosis infection is determined by the host and bacterial factors. A strong host immune response controls the growth of the bacilli effectively. However, in a host with suboptimal immune response, the bacilli grows and mounts disease. Activation of immune response following M. tuberculosis infection affects the expression of many host genes that are involved in the production of immune system molecules such as cytokines, chemokines, surface receptors and transcriptional regulators that manifest in the change of subsequent cellular events, including chemotaxis and proliferation of effector cells. The infecting bacilli counteracts the bactericidal activities of the host immune cells, primarily by modifying their gene expression. However, the specific nature of the host-pathogen interactions and the outcome of Mtb infection are not fully understood. Tumor necrosis factor-alpha (TNF-a), produced by the immune cells, is an important cytokine in protecting the host against Mtb infection. However, excessive TNF-a production leads to severe inflammation and host cell destruction. In fact, pharmacologic inhibition of TNF-a production has been considered as a therapeutic modality in inflammatory diseases. Interestingly, inhibitors of host phosphodiesterase-4 (PDE4) have been shown to reduce TNF-a production and dampen inflammation without complete immune suppression of the host. In this study, we have explored the use of one of the PDE4 inhibitors, CC-3052, as an adjunct immune modulatory drug, in combination with isoniazid (INH) treatment in rabbit pulmonary tuberculosis. We hypothesize that reducing TNF-a levels during Mtb infection would reduce the environmental pressure on the bacteria, rendering them more amenable to killing by INH. Mtb infected rabbits were treated with CC-3052 or INH or both and the lung tissue were harvested after 4 and 8 weeks of treatment. Lung bacterial load, histologic changes and host and bacterial gene expression were determined for each timepoint and compared between various treatment groups. The results of our study provides data to support the idea that combining anti-TB drugs with an adjunctive immune modulator may enhance the efficacy of current TB therapy regimens and shorten the duration of treatment if applied appropriately to humans. The microarray experiments involves 2 comparison groups. 1) Changes in rabbit gene expression between Mtb infected and uninfected animals; 2). Changes in rabbit gene expression between CC-3052 treated and untreated animals during Mtb infection at 4,8 and 12 weeks post infection. New Zealand White rabbits were infected with Mtb HN878 at 3.2log10 (on day 0). At 4 weeks post infection, one group of infected rabbits were treated with a phosphodiesterase-4 (PDE4) inhibitor, CC-3052, and the treatment was continued up to 12 weeks post infection. The compound was used at 25mg/kg body weight, dissolved in distilled water and administered through gavage five days a weeks. Lung tissue from Uninfected, Mtb-infected and Untreated or CC-3052 treated rabbits were isolated at Day0, 4,8 and 12 weeks post infection and used for total RNA extraction. Only the 8 and 12 week timepoints correspond to the associated publication.

Dataset Information

A metabolomics analysis of Salmonella infection

Publications

Impact of salmonella infection on host hormone metabolism revealed by metabolomics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets