Functional characterization of polysaccharide utilization loci in the marine Bacteroidetes ‘Gramella forsetii' KT0803

Members of the phylum Bacteroidetes are abundant in many marine ecosystems and are known to have a pivotal role in the mineralization of complex organic substrates such as polysaccharides and proteins. We studied the decomposition of the algal glycans laminarin and alginate by ‘Gramella forsetii'' KT0803, a bacteroidetal isolate from North Sea surface waters. A combined application of isotope labeling, subcellular protein fractionation and quantitative proteomics revealed two large polysaccharide utilization loci (PULs) that were specifically induced, one by alginate and the other by laminarin. These regulons comprised genes of surface-exposed proteins such as oligomer transporters, substrate-binding proteins, carbohydrate-active enzymes and hypothetical proteins. Besides, several glycan-specific TonB-dependent receptors and SusD-like substrate-binding proteins were expressed also in the absence of polysaccharide substrates, suggesting an anticipatory sensing function. Genes for the utilization of the beta-1,3-glucan laminarin were found to be co-regulated with genes for glucose and alpha-1,4-glucan utilization, which was not the case for the non-glucan alginate. Strong syntenies of the PULs of ‘G. forsetii'' with similar loci in other Bacteroidetes indicate that the specific response mechanisms of ‘G. forsetii'' to changes in polysaccharide availability likely apply to other Bacteroidetes. Our results can thus contribute to an improved understanding of the ecological niches of marine Bacteroidetes and their roles in the polysaccharide decomposition part of carbon cycling in marine ecosystems.     

Identifying evolutionarily conserved genes in the dietary restriction response using bioinformatics and subsequent testing in Caenorhabditis elegans

Dietary restriction (DR) increases life span, health span and resistance to stress in a wide range of organisms. Work from a large number of laboratories has revealed evolutionarily conserved mechanisms that mediate the DR response. Here, we analyzed the genome-wide gene expression profiles of Caenorhabditis elegans under DR versus ad libitum conditions. Using the Ortho2ExpressMatrix tool, we searched for C. elegans orthologs of mouse genes that have been shown to be differentially expressed under DR conditions in nearly 600 experiments. Based on our bioinformatic approaches, we obtained 189 DR-responsive genes, and 45 of these are highly conserved from worm to man. Subsequent testing of sixteen genes that are up-regulated under DR identified eight genes that abolish the DR-induced resistance to heat stress in C. elegans. Further analyses revealed that fkb-4, dod-22 and ikb-1 genes also abolish increased life span in response to DR. The identified genes that are necessary for the DR response are sensitive to certain stress signals such as metabolic perturbances (dod-22, fkb-4 and nhr-85), DNA damage (ikb-1), heat shock (hsp-12.6) and cancer-like overgrowth (prk-2 and tsp-15). We propose that most of the DR-responsive genes identified are components of the recently discovered cellular surveillance-activated detoxification and defenses pathway, which is, among others, important for the survival of organisms in times of food deprivation.

Electronic supplementary material

The online version of this article (doi:10.1007/s12263-013-0363-5) contains supplementary material, which is available to authorized users.     

Subcellular fractionation enhances proteome coverage of pancreatic duct cells

ObjectivesSubcellular fractionation of whole cell lysates offers a means of simplifying protein mixtures, potentially permitting greater depth of proteomic analysis. Here we compare proteins identified from pancreatic duct cells (PaDC) following organelle enrichment to those identified from PaDC whole cell lysates to determine if the additional procedures of subcellular fractionation increase proteome coverage.MethodsWe used differential centrifugation to enrich for nuclear, mitochondrial, membrane, and cytosolic proteins. We then compared – via mass spectrometry-based analysis – the number of proteins identified from these four fractions with four biological replicates of PaDC whole cell lysates.ResultsWe identified similar numbers of proteins among all samples investigated. In total, 1658 non-redundant proteins were identified in the replicate samples, while 2196 were identified in the subcellular fractionation samples, corresponding to a 30% increase. Additionally, we noted that each organelle fraction was in fact enriched with proteins specific to the targeted organelle.ConclusionsSubcellular fractionation of PaDC resulted in greater proteome coverage compared to PaDC whole cell lysate analysis. Although more labor intensive and time consuming, subcellular fractionation provides greater proteome coverage, and enriches for compartmentalized sub-populations of proteins. Application of this subcellular fractionation strategy allows for a greater depth of proteomic analysis and thus a better understanding of the cellular mechanisms of pancreatic disease.     

SweetSEQer,Simple de Novo Filtering and Annotation of Glycoconjugate Mass Spectra

The past 15 years have seen significant progress in LC-MS/MS peptide sequencing, including the advent of successful de novo and database search methods; however, analysis of glycopeptide and, more generally, glycoconjugate spectra remains a much more open problem, and much annotation is still performed manually. This is partly because glycans, unlike peptides, need not be linear chains and are instead described by trees. In this study, we introduce SweetSEQer, an extremely simple open source tool for identifying potential glycopeptide MS/MS spectra. We evaluate SweetSEQer on manually curated glycoconjugate spectra and on negative controls, and we demonstrate high quality filtering that can be easily improved for specific applications. We also demonstrate a high overlap between peaks annotated by experts and peaks annotated by SweetSEQer, as well as demonstrate inferred glycan graphs consistent with canonical glycan tree motifs. This study presents a novel tool for annotating spectra and producing glycan graphs from LC-MS/MS spectra. The tool is evaluated and shown to perform similarly to an expert on manually curated data.Protein glycosylation is a common modification, affecting ∼50% of all expressed proteins (1). Glycosylation affects critical biological functions, including cell-cell recognition, circulating half-life, substrate binding, immunogenicity, and others (2). Regrettably, determining the exact role glycosylation plays in different biological contexts is slowed by a dearth of analytical methods and of appropriate software. Such software is crucial for performing and aiding experts in data analysis complex glycosylation.Glycopeptides are highly heterogeneous in regard to glycan composition, glycan structure, and linkage stereochemistry in addition to the tens of thousands of possible peptides. The analysis of protein glycosylation is often segmented into three distinct types of mass spectrometry experiments, which together help to resolve this complexity. The first analyzes enzymatically or chemically released glycans (which may or may not be chemically modified), and the second determines glycosylation sites after release of glycans from peptides (the resulting mass spectra allow detection of glycosylation sites and the glycans on those sites simultaneously). The third determines the glycosylation sites and the glycans on those sites simultaneously, by MS of intact glycopeptides. Frequently, researchers will perform all three types of analysis, with the first two types providing information about possible combinations of glycan structures and peptides that could be found in the third experiment. Using this MS1 information, the problem is reduced to matching masses observed with a combinatorial pool of all possible glycans and all possible glycosylated peptides within a sample; however, this combinatorial approach alone is insufficient (3), and tandem mass spectrometry can provide copious additional information to help resolve the glycopeptide content from complex samples.The similar problem of inferring peptide sequences from MS/MS spectra has received considerably more attention. Peptide inference is more constrained than glycan inference, because the chain of MS/MS peaks corresponds to a linear peptide sequence; given an MS/MS spectrum, the linear peptide sequence can be inferred through brute force or dynamic programming via de novo methods (4–6) as described in Ref. 7. Additionally, the possible search space of peptides can be dramatically lowered by using database searching (8–21) as described in Ref. 7, which compares the MS/MS spectrum to the predicted spectra from only those peptides resulting from a protein database or translated open reading frames (ORFs) of a genomic database.The possible search space of glycans is larger than the search space of peptides because, in contrast to linear peptide chains, glycans may form branching trees. Identifying glycans using database search methodologies is impractical, as it is impractical to define the database when the detailed activities of the set of glycosyltransferases are not defined. Generating an overly large database would artificially inflate the set of incompletely characterized spectra, and too small of a search space would lead to inaccurate results. Furthermore, as glycosylation is not a template-driven process, no clear choice for a database matching approach is available, and de novo sequencing is therefore a more appropriate approach.As a result, few desirable software options are available for the high throughput analysis of tandem mass spectrometry data from intact glycopeptides (as noted in a recent review (22)). In fact, manual annotation of spectra is still commonplace, despite being slow and despite the potential for disagreement between different experts. Some available software requires user-defined lists of glycan and/or peptide masses as input, which is suboptimal from a sample consumption and throughput perspective (23, 24). These lists must typically be generated by parallel experiments or simply hypothesized a priori, meaning omissions in either list may affect the results. Furthermore, some software does not work on batched input files, meaning each spectrum must be analyzed separately (23, 25–28). Moreover, there is an even greater lack of open source software for glycoproteomics, so modifying the existing software for the researchers individual applications is not easily achieved. The one open source tool that we know of (GlypID) is applicable only to the analysis of glycopeptide spectra acquired from a very specialized workflow, which requires MS1, CID, and higher-energy C-trap type dissociation (HCD) spectra (29). With that approach, oxonium ions from HCD spectra are necessary to predict the glycan class; potential peptide lists are queried by precursor m/z values (requiring accurate a priori knowledge of all modifications), and possible theoretical “N-linked” precursor m/z values are used to select candidate spectra (using templates, unlike de novo characterization). As a result, the tool is specialized and limited to analysis of “N-linked” glycopeptide spectra from very specific experimental setups.Free, open-source glycoproteomic software capable of batch analysis of general tandem mass spectrometry spectra of glycoconjugates is sorely needed. In this work, we present SweetSEQer, a tool for de novo analysis of tandem mass spectra of glycoconjugates (the most general class of spectra containing fragmentation involving sugars). Furthermore, because SweetSEQer is so general and simple, and because it does not require specific experimental setup, it is widely applicable to the analysis of general glycoconjugate spectra (e.g. it is already applicable to “O-linked” glycopeptide and glycoconjugate spectra). Moreover, because it is an open source and does not use external software, it not only eschews solving problems like MS1 deisotoping, it can also be easily customized and even used to augment and complement existing tools like GlypID (and, because we do not use a “copyleft” software license, our algorithm and code can even be added to non-open source and proprietary variants).SweetSEQer''s performance was tested on a validated, manually annotated set of glycoconjugate identifications from a urinary glycoproteomics study. Specificity was demonstrated by showing a low identification rate on negative control spectra from Escherichia coli. Annotated structures are shown to be consistent by a human expert by demonstrating a high overlap in identified glycan fragment ions, as well as a consistency between SweetSEQer''s predicted glycan graph and glycan chains produced by an expert. Our simple object-oriented python implementation is freely available (Apache 2.0 license) on line.     

Thrombin activity throughout the acute phase of acute ST-elevation myocardial infarction and the relation to outcome

Background: Thrombin and plasmin play a central role in ongoing thrombosis and platelet activation in patients with acute ST-elevation myocardial infarction (STEMI). Data of thrombin and plasmin activity in the early course of STEMI and the relation to outcome are scarce.

Methods: We included 68 consecutive patients (53 male, 59?±?11.4 years) with STEMI who underwent acute catheter-based reperfusion therapy within the first 12?h after onset of symptoms. Blood samples were taken at admission and after 4, 8, 12 and 24?h. Thrombin activity and generation was measured by changes in the thrombin/antithrombin-III complex (TAT) and prothrombin fragment (F1.2); plasmin was measured by changes in the plasmin-α₂/antiplasmin complex (PAP). A follow-up with respect to the combined primary endpoint consisting of death, acute myocardial infarction or urgent need for revascularization up to 6 weeks post-discharge was carried out.

Results: TAT values showed no significant change over time in patients with and without the primary endpoint but there was a borderline difference between these groups at 4?h after admission (event group 9.0 vs no event group 4.7?μg l^?1, p?=?0.057). F1.2 values were different between groups only after 24?h (event group 1.5 vs no event group 0.9?nmol l^?1, p?=?0.028) and did not differ in serial sampling of 24?h. PAP values were higher in patients with events after 4 and 8?h and declined over time in the group without events (p?<0.001). Odds ratios (OR) with respect to the primary endpoint were highest for TAT?>4.8?μg l^?1 at 0?h and TAT?>8.4?μg?l^?1 at 4?h (OR 7.1, 95% confidence interval (CI) 1.5–34, p?=?0.015 and OR 5.5, 95% CI 1.5–20.0, p?=?0.01, respectively). The predictive value of plasmin concentrations were equally high after 4?h (PAP?>962?μg l^?1; OR 6.8, 95% CI 1.8–26.2, p?=?0.005) and 8?h (PAP?>495?μg l^?1, OR 6.7, 95% CI 1.4–32.9, p?=?0.024). Values for F1.2 were only predictive after 24?h (F1.2?>0.85?nmol l^?1, OR 13, 95% CI 1.4–117.8, p?=?0.023).

Conclusions: Markers of thrombin and plasmin activity in acute STEMI are related to outcome. The marker for thrombin generation F1.2 becomes a significant predictor of outcome at 24?h after admission, reflecting the potentially adverse effects of ongoing thrombin generation. This underlines the potential for direct thrombin inhibition and individualization of treatment by thrombin markers in STEMI.     

Ambulant 24‐h glucose rhythms mark calendar and biological age in apparently healthy individuals

Glucose metabolism marks health and disease and is causally inferred in the aging process. Ambulant continuous glucose monitoring provides 24‐h glucose rhythms under daily life conditions. We aimed to describe ambulant 24‐h glucose rhythms measured under daily life condition in relation to calendar and biological age in apparently healthy individuals. In the general population and families with propensity for longevity, we studied parameters from 24‐h glucose rhythms; glucose levels; and its variability, obtained by continuous glucose monitoring. Participants were 21 young (aged 22–37 years), 37 middle‐aged (aged 44–72 years) individuals from the general population, and 26 middle‐aged (aged 52–74 years) individuals with propensity for longevity. All were free of diabetes. Compared with young individuals, middle‐aged individuals from the general population had higher mean glucose levels (5.3 vs. 4.7 mmol L^?1, P < 0.001), both diurnally (P < 0.001) and nocturnally (P = 0.002). Glucose variability was higher in the middle‐aged compared with the young (standard deviation 0.70 vs. 0.57 mmol L^?1, P = 0.025). Compared with middle‐aged individuals from the general population, middle‐aged individuals with propensity for longevity had lower overall mean glucose levels (5.2 vs. 5.4 mmol L^?1, P = 0.047), which were more different nocturnally (4.8 vs. 5.2 mmol L^?1, P = 0.003) than diurnally (5.3 vs. 5.5 mmol L^?1, P = 0.14). There were no differences in glucose variability between these groups. Results were independent of body mass index. Among individuals without diabetes, we observed significantly different 24‐h glucose rhythms depending on calendar and biological age.     

Esophageal cancer proliferation is mediated by cytochrome P450 2C9 (CYP2C9)

Cytochrome P450 epoxygenases (CYP450) have been recently shown to promote malignant progression. Here we investigated the mRNA and protein expression and potential clinical relevance of CYP2C9 in esophageal cancer. Highest expression was detected in esophageal adenocarcinoma (EAC; n=78) and adjacent esophageal mucosa (NEM; n=79). Levels of CYP2C9 in EAC and NEM were significantly higher compared to esophageal squamous cell carcinoma (ESCC; n=105). Early tumor stages and well-differentiated tumors showed a significantly higher CYP2C9 expression compared to progressed tumors. Moreover, CYP2C9 expression was correlated to high Ki-67 labeling indices in EAC and Ki-67 positive tumor cells in EAC and ESCC. Selective inhibition of CYP2C9 decreased tumor cell proliferation (KYSE30, PT1590 and OE19) in vitro, which was abolished by 11,12-epoxyeicosatrienoic acid (11,12-EET). Cell-cycle analysis using FACS revealed that inhibition of CYP2C9 leads to a G0/G1 phase cell-cycle arrest. CYP2C9 seems to be relevant for early esophageal cancer development by promoting tumor cell proliferation. Pharmacological inhibition of CYP2C9 might contribute to a more efficient therapy in CYP2C9 highly expressing esophageal cancers.     

Proteomic analysis of a rat pancreatic stellate cell line using liquid chromatography tandem mass spectrometry (LC-MS/MS)

Pancreatic stellate cells (PaSC) are emerging as key mediators in chronic pancreatitis and pancreatic cancer pathogenesis. Proteins regulating the biomolecular pathways involved in the conversion of quiescent to activated PaSC may have a significant influence on the development of chronic pancreatitis. We aim to compare differentially expressed proteins in activated and serum-starved non-proliferating PaSC using a mass spectrometry-based proteomics strategy. We cultured an immortalized rat PaSC cell line in media supplemented with 10% fetal bovine serum and in serum-free media. Using gel-based mass spectrometry (GeLC-MS/MS), we identified nearly 1500 proteins. Qualitative and quantitative proteomic analysis revealed several hundred proteins as differentially abundant between the two cell states. Proteins of greater abundance in activated PaSC included isoforms of actin (e.g., smooth muscle actin) and ribosomal proteins. Conversely, proteins more abundant in non-proliferating PaSC than in activated PaSC included signaling proteins MAP kinase 3 and Ras-related proteins. In addition, we have determined the molecular functions and biological pathways for these proteins. We are confident that the application of mass spectrometry-based strategies, such as that described herein, to investigate specific proteins in PaSC may lead to a better understanding of the molecular mechanisms involved in pancreatic diseases, such as chronic pancreatitis.     

Pattern-dependent response modulations in motion-sensitive visual interneurons--a model study

Even if a stimulus pattern moves at a constant velocity across the receptive field of motion-sensitive neurons, such as lobula plate tangential cells (LPTCs) of flies, the response amplitude modulates over time. The amplitude of these response modulations is related to local pattern properties of the moving retinal image. On the one hand, pattern-dependent response modulations have previously been interpreted as 'pattern-noise', because they deteriorate the neuron's ability to provide unambiguous velocity information. On the other hand, these modulations might also provide the system with valuable information about the textural properties of the environment. We analyzed the influence of the size and shape of receptive fields by simulations of four versions of LPTC models consisting of arrays of elementary motion detectors of the correlation type (EMDs). These models have previously been suggested to account for many aspects of LPTC response properties. Pattern-dependent response modulations decrease with an increasing number of EMDs included in the receptive field of the LPTC models, since spatial changes within the visual field are smoothed out by the summation of spatially displaced EMD responses. This effect depends on the shape of the receptive field, being the more pronounced--for a given total size--the more elongated the receptive field is along the direction of motion. Large elongated receptive fields improve the quality of velocity signals. However, if motion signals need to be localized the velocity coding is only poor but the signal provides--potentially useful--local pattern information. These modelling results suggest that motion vision by correlation type movement detectors is subject to uncertainty: you cannot obtain both an unambiguous and a localized velocity signal from the output of a single cell. Hence, the size and shape of receptive fields of motion sensitive neurons should be matched to their potential computational task.