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APP: An Automated Proteomics Pipeline for the analysis of mass spectrometry data based on multiple open access tools
KTH, School of Biotechnology (BIO), Glycoscience. (Bulone)
KTH, School of Biotechnology (BIO), Glycoscience. (Bulone)ORCID iD: 0000-0003-1877-4154
KTH, School of Biotechnology (BIO), Glycoscience. (Bulone)
KTH, School of Biotechnology (BIO), Glycoscience. (Bulone)
2014 (English)In: BMC Bioinformatics, ISSN 1471-2105, Vol. 15, no 1, 345Article in journal (Refereed) Published
Abstract [en]

Background: Mass spectrometry analyses of complex protein samples yield large amounts of data and specific expertise is needed for data analysis, in addition to a dedicated computer infrastructure. Furthermore, the identification of proteins and their specific properties require the use of multiple independent bioinformatics tools and several database search algorithms to process the same datasets. In order to facilitate and increase the speed of data analysis, there is a need for an integrated platform that would allow a comprehensive profiling of thousands of peptides and proteins in a single process through the simultaneous exploitation of multiple complementary algorithms. Results: We have established a new proteomics pipeline designated as APP that fulfills these objectives using a complete series of tools freely available from open sources. APP automates the processing of proteomics tasks such as peptide identification, validation and quantitation from LC-MS/MS data and allows easy integration of many separate proteomics tools. Distributed processing is at the core of APP, allowing the processing of very large datasets using any combination of Windows/Linux physical or virtual computing resources. Conclusions: APP provides distributed computing nodes that are simple to set up, greatly relieving the need for separate IT competence when handling large datasets. The modular nature of APP allows complex workflows to be managed and distributed, speeding up throughput and setup. Additionally, APP logs execution information on all executed tasks and generated results, simplifying information management and validation.

Place, publisher, year, edition, pages
2014. Vol. 15, no 1, 345
Keyword [en]
Automation, Distributed processing, Proteomics, Validation
National Category
Bioinformatics and Systems Biology
Research subject
URN: urn:nbn:se:kth:diva-147931DOI: 10.1186/s12859-014-0441-8ScopusID: 2-s2.0-84923858672OAI: diva2:733478

QC 20150529. Updated from manuscript to article in journal.

Available from: 2014-07-09 Created: 2014-07-09 Last updated: 2015-05-29Bibliographically approved
In thesis
1. Analyzing the properties and biosynthesis of β-glucans from Gluconacetobacter and poplar
Open this publication in new window or tab >>Analyzing the properties and biosynthesis of β-glucans from Gluconacetobacter and poplar
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Glucans are polysaccharides integral to many materials and biological functions. Under the umbrella of Biomime, the Swedish Center for Biomimetic Fiber Engineering, this work has aimed to improve basic understanding of the biosynthesis of such glucans. This has been achieved through direct investigation of cellulose structure, and by developing the tools to analyze glucan biosynthesis. Notably we have identified a novel chemical effector of glucan synthesis processes and developed a proteomic toolkit useful for analyzing membrane-bound glycosyltransferases, the enzyme group responsible for glucan biosynthesis. During this work, glucan synthesis has been studied using both Gluconacetobacter and Populus cell suspension cultures.

Publication I. Gluconacetobacter cellulose (BC) was used as a base to create a novel and well characterized nano-material with improved mechanical properties. This novel composite of BC and hydroxyethylcellulose (HEC) had improved tensile strength compared to pure BC. Through thorough study utilizing dispersion measurements, electron microscopy, nuclear magnetic resonance and X-ray diffraction it was shown that the improved properties derived from a layer of HEC coating each fibril.

Publication II. Bacterial cellulose was labeled in specific positions with 13C (C4 and C6). These samples were analyzed by CP/MAS NMR along with cellulose samples from cotton and Halocynthia sp. For each sample spectral fitting was performed and general properties of crystal allomorph composition and fibril widths were determined. Calculations were also made for water accessible surfaces of the fibrils. The results showed that water accessible C4 surface signals are reflective of the allomorph composition of the sample, along with a distorted signal that derives due to fibril imperfections. Water accessible surface signals from the C6 region are instead derived from rotamer conformations of the C6 hydroxymethyl groupsfrom glucose residues.

In Publication III, a high-throughput screen was used to identify an inhibitor of Golgi-derived glycosyltransferase activity, termed chemical A. The structural basis for inhibition was determined and in vitro assays of callose synthesis were performed. The in vitro assays revealed chemical A to also be an activator of callose synthesis. To understand this activation kinetic studies were performed, showing that chemical A is a mixed type of activator, which can bind either the free enzyme or the enzyme-substrate complex. Chemical A has uses in chemical genetics for dissecting processes involving callose synthesis, such as stress response and cell-plate formation.

In publication IV, we present an in-house developed platform for proteomics with a distributed processing model. This in-house system has been central to many proteomics tasks, including for those presented in publication V, and is being distributed as the Automated Proteomics Pipeline (APP).

In publication V, conditions for enrichment of Detergent-Resistant Microdomains (DRM) have been optimized for Populus trichocarpa cell cultures. The proteins enriched in DRM were identified using mass spectrometry based proteomics, and a functional model for DRM was proposed. This model involves proteins specialized in stress response, including callose synthase, and cell signaling. This further strengthens the arguments for DRMs as sites of specific cellular functions and confirms they play a role in glucan synthesis.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2014. 66 p.
TRITA-BIO-Report, ISSN 1654-2312 ; 2014:8
Cellulose synthesis, Bioinformatics, Proteomics, Cell wall
National Category
Biological Sciences Bioinformatics and Systems Biology
urn:nbn:se:kth:diva-147932 (URN)978-91-7595-184-3 (ISBN)
Public defence
2014-09-05, FR4, AlbaNova, Roslagstullsbacken 21, Stockholm, 13:00 (English)

QC 20140710

Available from: 2014-07-10 Created: 2014-07-09 Last updated: 2014-07-10Bibliographically approved

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