Project description:Rapid advances in the fields of DNA-, RNA-, polypeptide-sequencing and metabolomics have markedly enhanced our understanding of fundamental biological processes. In contrast to other post-translational modifications (PTMs), the most abundant PTM, glycosylation, remains largely unexplored at the proteome scale because of a scarcity of technologies for profiling the immensely complex glycoproteome. We developed a novel quantitative approach for the identification of intact glycopeptides from comparative proteomic data-sets, allowing us to not only identify complex sugar structures but also to directly map them to the corresponding glycosylation sites in the associated proteins at the proteome scale. Applying this method to human and murine embryonic stem cells, we were able to nearly double the number of all experimentally confirmed glycoproteins, including the identification of completely unknown glycosylation sites, multiple glycosylated stemness factors and the elucidation of evolutionary conserved core as well as species-specific glycoproteins in embryonic stem cells. Specificity of our method was confirmed in sister stem cells carrying repairable mutations in enzymes required for fucosylation, Fut9 and Slc35c1. Since ablation of fucosylation confers cellular resistance towards the bioweapon ricin (see accompanying paper), our method also allowed us to directly identify the proteins that carry the terminal fucosylation code for ricin toxicity; genetic mutations in these proteins functionally confirmed their role in ricin killing. This novel comparative and high-throughput glycoproteomics platform should allow for entirely novel insights in protein glycosylation and sugar modifications involved in nearly all biological systems.
Project description:Although splicing is essential for the expression of most eukaryotic genes, inactivation of splicing factors causes specific defects in mitosis. The molecular cause of this defect is unknown. Here we show that the spliceosome subunits SNW1 and PRPF8 are essential for sister chromatid cohesion in human cells. A transcriptome-wide analysis revealed that SNW1 or PRPF8 depletion affects the splicing of specific introns in a subset of pre-mRNAs, including pre-mRNAs encoding the cohesion protein sororin and the APC/C subunit APC2. SNW1 depletion causes cohesion defects predominantly by reducing sororin levels, which causes destabilisation of cohesin on DNA. SNW1 depletion also reduces APC/C activity and contributes to cohesion defects indirectly by delaying mitosis and causing ‘cohesion fatigue’. Simultaneous expression of sororin and APC2 from intron-less cDNAs restores cohesion in SNW1 depleted cells. These results indicate that the spliceosome is required for mitosis because it enables expression of genes essential for cohesion. Our transcriptome-wide identification of retained introns in SNW1 and PRPF8 depleted cells may help to understand the aetiology of diseases associated with splicing defects, such as retinosa pigmentosum and cancer.
Project description:Protein expression is regulated by production and degradation of mRNAs and proteins, but their specific relationships remain unknown. We combine measurements of protein production and degradation and mRNA dynamics to build a quantitative genomic model of the differential regulation of gene expression in LPS stimulated mouse dendritic cells. Changes in mRNA abundance play a dominant role in determining most dynamic fold changes in protein levels. Conversely, the preexisting proteome of proteins performing basic cellular functions is remodeled primarily through changes in protein production or degradation, accounting for over half of the absolute change in protein molecules in the cell. Thus, the proteome is regulated by transcriptional induction of novel cellular functions and remodeling of preexisting functions through the protein life cycle. Mouse primary dendritic cells were treated with LPS or mock stimulus and profiled over a 12-hour time course. Cells were grown in M-labeled SILAC media, which was replaced with H-labeled SILAC media at time 0. Aliquots were taken at 0, 0.5, 1, 2, 3, 4, 5, 6, 9, and 12 hours post-stimulation and added to equal volumes of a master mix of unlabeled (L) cells for the purpose of normalization. RNA-Seq was performed at 0, 1, 2, 4, 6, 9, and 12 hours post-stimulation.
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:Parkinson disease (PD) is a neurodegenerative disease characterized by the accumulation of alpha-synuclein (SNCA) and other proteins in aggregates termed âLewy Bodiesâ within neurons. PD has both genetic and environmental risk factors, and while processes leading to aberrant protein aggregation are unknown, past work points to abnormal levels of SNCA and other proteins. Although several genome-wide studies have been performed for PD, these have focused on DNA sequence variants by genome-wide association studies (GWAS) and on RNA levels (microarray transcriptomics), while genome-wide proteomics analysis has been lacking. After appropriate filters, proteomics identified 3,558 unique proteins and 283 of these (7.9%) were significantly different between PD and controls (q-value<0.05). RNA-sequencing identified 17,580 protein-coding genes and 1,095 of these (6.2%) were significantly different (FDR p-value<0.05), but only 166 of the FDR significant protein-coding genes (0.94%) were present among the 3,558 proteins characterized. Of these 166, eight genes (4.8%) were significant in both studies, with the same direction of effect. Functional enrichment analysis of the proteomics results strongly supports mitochondrial-related pathways, while comparable analysis of the RNA-sequencing results implicates protein folding pathways and metallothioneins. Ten of the implicated genes or proteins co-localized to GWAS loci. Evidence implicating SNCA was stronger in proteomics than in RNA-sequencing analyses. Notably, differentially expressed protein-coding genes were more likely to not be characterized in the proteomics analysis, which lessens the ability to compare across platforms. Combining multiple genome-wide platforms offers novel insights into the pathological processes responsible for this disease by identifying pathways implicated across methodologies. The study consists of mRNA-Seq (29 PD, 44 neurologically normal controls) and three-stage Mass Spectrometry Tandem Mass Tag Proteomics (12 PD, 12 neurologically normal controls) performed in post-mortem BA9 brain tissue. The proteomics samples are a subset of the RNA-Seq samples.
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: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.
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:Label-free global and phopshoproteomic acnalysis of Lp02-ΔDenR vs. Lp02-ΔDenR-pDenR infected Raw 264.7 macrophages 10 hours post-infection.