Protein expression dynamics during Escherichia Coli glucose-lactose diauxie

BACKGROUND: Escherichia coli is a well-studied anaerobic bacteria which is able to regulate metabolic pathways depending on the type of sugar presented in the medium. We have studied the glucose-lactose shift in E. coli at the protein level using a recently developed mass spectrometry platform. METHOD: Cells were grown in minimal medium containing two sugars (glucose and lactose) and analyzed using novel mass spectrometry cluster. The cluster combines the high resolving power and dynamic range of Fourier transform ion cyclotron resonance (FTICR) for accurate mass measurement and quantitation with multiple ion traps for fast and sensitive tandem mass spectrometry. The protein expression profile was followed in time across the glucose-lactose diauxic shift using label-free quantitation from the FTICR data. RESULTS AND CONCLUSION: The entire dataset was interrogated by KEGG pathway analysis, mapping measured changes in protein abundance onto known metabolic pathways. The obtained results were consistent with previously published gene expression data, with β-galactosidase being the most strongly induced protein during the diauxic shift

Scientific workflows for bibliometrics

Scientific workflows organize the assembly of specialized software into an overall data flow and are particularly well suited for multi-step analyses using different types of software tools. They are also favorable in terms of reusability, as previously designed workflows could be made publicly available through the myExperiment community and then used in other workflows. We here illustrate how scientific workflows and the Taverna workbench in particular can be used in bibliometrics. We discuss the specific capabilities of Taverna that makes this software a powerful tool in this field, such as automated data import via Web services, data extraction from XML by XPaths, and statistical analysis and visualization with R. The support of the latter is particularly relevant, as it allows integration of a number of recently developed R packages specifically for bibliometrics. Examples are used to illustrate the possibilities of Taverna in the fields of bibliometrics and scientometrics.Proteomic

Surface activity and film formation from the surface associated material of artificial surfactant preparations

AbstractSurfactant proteins B and C (SP-B and SP-C) are present in natural derived surfactant preparations used for treatment of respiratory distress syndrome. Herein the surface activity of an SP-C analogue (SP-C(LKS)), a hybrid peptide between SP-C and bacteriorhodopsin (SP-C/BR) and a model peptide (KL4) was studied with a captive bubble surfactometer (CBS). The peptides were mixed with either 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC)/phosphatidylglycerol (PG) (7:3, by weight) or DPPC/PG/palmitic acid (68:22:9, by weight) at a concentration of 1 mg/ml in HEPES buffer, pH 6.9 and a polypeptide/lipid weight ratio of 0.02–0.03. In some lipid/peptide preparations also 2% of SP-B was included. Adsorption, monitored as surface tension vs. time for 10 min after bubble formation did not show discernible differences for the whole set of preparations. Equilibrium surface tensions of approximately 25 mN/m were reached after 5–10 min for all preparations, although those with SP-C/BR appeared not to reach end point of adsorption within 10 min. Area compression needed to reach minimum surface tension of 0.5–2.0 mN/m was least for the KL4 preparation, about 13% in the first cycle. 3% SP-C(LKS) in DPPC:PG (7:3, by weight) reached minimum surface tension upon 27% compression in the first cycle. If DPPC:PG:PA (68:22:9, by weight) was used instead only 16% area compression was needed and 14% if also 2% SP-B was included. 3% SP-C(LKS) in DPPC:PG (7:3, by weight)+2% SP-B needed 34% compression to reach minimum surface tension. The replenishment of material from a surface associated surfactant reservoir was estimated with subphase depletion experiments. With the 2% KL4 preparation incorporation of excess material took place at a surface tension of 25–35 mN/m during stepwise bubble expansion and excess material equivalent to 4.3 monolayers was found. When 2% SP-B was added to 3% SP-C(LKS) in DPPC:PG (7:3, by weight) the number of excess monolayers increased from 1.5 to 3.6 and the incorporation took place at 30–40 mN/m. When SP-B was added to 3% SP-C(LKS) in DPPC:PG:PA (68:22:9, by weight) the number of excess monolayers increased from 0.5 to 3.4 and incorporation took place at 40–50 mN/m. With 2% SP-C/BR incorporation took place at 40–45 mN/m, frequent instability clicks were observed and excess material of approximately 1.1 monolayer was estimated

Shotgun proteomics approaches for authentication, biological analyses, and allergen detection in feed and food-grade insect species

Untargeted proteomics can contribute to composition and authenticity analyses of highly processed mixed food and feed products. Here, we present the setup of an analytical flow tandem mass spectrometry method (AF-HPLC HR-MS) for analysis of insect meal from five different species. Data acquired were compared with previously published data employing spectra matching and standard bottom-up proteomics bioinformatics analyses. In addition, data were screened for insect species marker peptides and common allergens, respectively. The results obtained indicate that the performance of the newly established AF-HPLC HR-MS workflow is in line with previously published methods for insect species differentiation. Data obtained in the present study, also lead to the discovery of novel markers for the development of targeted MS analyses of insect species in food- and feed-mixes and highlighted that known allergen such as arginine kinase or tropomyosin were consistently detected across all five species tested.publishedVersio

CompareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry Datasets

It has long been known that biological species can be identified from mass spectrometry data alone. Ten years ago, we described a method and software tool, compareMS2, for calculating a distance between sets of tandem mass spectra, as routinely collected in proteomics. This method has seen use in species identification and mixture characterization in food and feed products, as well as other applications. Here, we present the first major update of this software, including a new metric, a graphical user interface and additional functionality. The data have been deposited to ProteomeXchange with dataset identifier PXD034932.publishedVersio

Perspectives on automated composition of workflows in the life sciences [version 1; peer review: 2 approved]

Scientific data analyses often combine several computational tools in automated pipelines, or workflows. Thousands of such workflows have been used in the life sciences, though their composition has remained a cumbersome manual process due to a lack of standards for annotation, assembly, and implementation. Recent technological advances have returned the long-standing vision of automated workflow composition into focus. This article summarizes a recent Lorentz Center workshop dedicated to automated composition of workflows in the life sciences. We survey previous initiatives to automate the composition process, and discuss the current state of the art and future perspectives. We start by drawing the “big picture” of the scientific workflow development life cycle, before surveying and discussing current methods, technologies and practices for semantic domain modelling, automation in workflow development, and workflow assessment. Finally, we derive a roadmap of individual and community-based actions to work toward the vision of automated workflow development in the forthcoming years. A central outcome of the workshop is a general description of the workflow life cycle in six stages: 1) scientific question or hypothesis, 2) conceptual workflow, 3) abstract workflow, 4) concrete workflow, 5) production workflow, and 6) scientific results. The transitions between stages are facilitated by diverse tools and methods, usually incorporating domain knowledge in some form. Formal semantic domain modelling is hard and often a bottleneck for the application of semantic technologies. However, life science communities have made considerable progress here in recent years and are continuously improving, renewing interest in the application of semantic technologies for workflow exploration, composition and instantiation. Combined with systematic benchmarking with reference data and large-scale deployment of production-stage workflows, such technologies enable a more systematic process of workflow development than we know today. We believe that this can lead to more robust, reusable, and sustainable workflows in the future.Stian Soiland-Reyes was supported by BioExcel-2 Centre of Excellence, funded by European Commission Horizon 2020 programme under European Commission contract H2020-INFRAEDI-02-2018 823830. Carole Goble was supported by EOSC-Life, funded by European Commission Horizon 2020 programme under grant agreement H2020-INFRAEOSC-2018-2 824087. We gratefully acknowledge the financial support from the Lorentz Center, ELIXIR, and the Leiden University Medical Center (LUMC) that made the workshop possible. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscriptPeer Reviewed"Article signat per 33 autors/es: Anna-Lena Lamprecht , Magnus Palmblad, Jon Ison, Veit Schwämmle , Mohammad Sadnan Al Manir, Ilkay Altintas, Christopher J. O. Baker, Ammar Ben Hadj Amor, Salvador Capella-Gutierrez, Paulos Charonyktakis, Michael R. Crusoe, Yolanda Gil, Carole Goble, Timothy J. Griffin , Paul Groth , Hans Ienasescu, Pratik Jagtap, Matúš Kalaš , Vedran Kasalica, Alireza Khanteymoori , Tobias Kuhn12, Hailiang Mei, Hervé Ménager, Steffen Möller, Robin A. Richardson, Vincent Robert9, Stian Soiland-Reyes, Robert Stevens, Szoke Szaniszlo, Suzan Verberne, Aswin Verhoeven, Katherine Wolstencroft "Postprint (published version

Use of expressed sequence tags as an alternative approach for the identification of Taenia solium metacestode excretion/secretion proteins

BACKGROUND: Taenia solium taeniasis/cysticercosis is a zoonotic helminth infection mainly found in rural regions of Africa, Asia and Latin America. In endemic areas, diagnosis of cysticercosis largely depends on serology, but these methods have their drawbacks and require improvement. This implies better knowledge of the proteins secreted and excreted by the parasite. In a previous study, we used a custom protein database containing protein sequences from related helminths to identify T. solium metacestode excretion/secretion proteins. An alternative or complementary approach would be to use expressed sequence tags combined with BLAST and protein mapping to supercontigs of Echinococcus granulosus, a closely related cestode. In this study, we evaluate this approach and compare the results to those obtained in the previous study. FINDINGS: We report 297 proteins organized in 106 protein groups based on homology. Additional classification was done using Gene Ontology information on biological process and molecular function. Of the 106 protein groups, 58 groups were newly identified, while 48 groups confirmed previous findings. Blast2GO analysis revealed that the majority of the proteins were involved in catalytic activities and binding. CONCLUSIONS: In this study, we used translated expressed sequence tags combined with BLAST and mapping strategies to both confirm and complement previous research. Our findings are comparable to recent studies on other helminth genera like Echinococcus, Schistosoma and Clonorchis, indicating similarities between helminth excretion/secretion proteomes

“Lossless” compression of high resolution mass spectra of small molecules

Fourier transform ion cyclotron resonance (FTICR) provides the highest resolving power of any commercially available mass spectrometer. This advantage is most significant for species of low mass-to-charge ratio (m/z), such as metabolites. Unfortunately, FTICR spectra contain a very large number of data points, most of which are noise. This is most pronounced at the low m/z end of spectra, where data point density is the highest but peak density low. We therefore developed a filter that offers lossless compression of FTICR mass spectra from singly charged metabolites. The filter relies on the high resolving power and mass measurement precision of FTICR and removes only those m/z channels that cannot contain signal from singly charged organic species. The resulting pseudospectra still contain the same signal as the original spectra but less uninformative background. The filter does not affect the outcome of standard downstream chemometric analysis methods, such as principal component analysis, but use of the filter significantly reduces memory requirements and CPU time for such analyses. We demonstrate the utility of the filter for urinary metabolite profiling using direct infusion electrospray ionization and a 15 tesla FTICR mass spectrometer