Dataset Information

MAGIC-web: a platform for untargeted and targeted N-linked glycoprotein identification.

ABSTRACT: MAGIC-web is the first web server, to the best of our knowledge, that performs both untargeted and targeted analyses of mass spectrometry-based glycoproteomics data for site-specific N-linked glycoprotein identification. The first two modules, MAGIC and MAGIC+, are designed for untargeted and targeted analysis, respectively. MAGIC is implemented with our previously proposed novel Y1-ion pattern matching method, which adequately detects Y1- and Y0-ion without prior information of proteins and glycans, and then generates in silico MS(2) spectra that serve as input to a database search engine (e.g. Mascot) to search against a large-scale protein sequence database. On top of that, the newly implemented MAGIC+ allows users to determine glycopeptide sequences using their own protein sequence file. The third module, Reports Integrator, provides the service of combining protein identification results from Mascot and glycan-related information from MAGIC-web to generate a complete site-specific protein-glycan summary report. The last module, Glycan Search, is designed for the users who are interested in finding possible glycan structures with specific numbers and types of monosaccharides. The results from MAGIC, MAGIC+ and Reports Integrator can be downloaded via provided links whereas the annotated spectra and glycan structures can be visualized in the browser. MAGIC-web is accessible from http://ms.iis.sinica.edu.tw/MAGIC-web/index.html.

SUBMITTER: Lih TM

PROVIDER: S-EPMC4987873 | biostudies-other | 2016 Jul

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

MAGIC-web: a platform for untargeted and targeted N-linked glycoprotein identification.

Lih T Mamie TM Choong Wai-Kok WK Chen Chen-Chun CC Cheng Cheng-Wei CW Lin Hsin-Nan HN Chen Ching-Tai CT Chang Hui-Yin HY Hsu Wen-Lian WL Sung Ting-Yi TY

Nucleic acids research 20160415 W1

MAGIC-web is the first web server, to the best of our knowledge, that performs both untargeted and targeted analyses of mass spectrometry-based glycoproteomics data for site-specific N-linked glycoprotein identification. The first two modules, MAGIC and MAGIC+, are designed for untargeted and targeted analysis, respectively. MAGIC is implemented with our previously proposed novel Y1-ion pattern matching method, which adequately detects Y1- and Y0-ion without prior information of proteins and gly ...[more]

PMID: 27084943

Similar Datasets

Project description:Identifying microbial indicators of damp and moldy buildings remains a challenge at the intersection of microbiology, building science, and public health. Sixty homes in New York City were assessed for moisture-related damage, and three types of dust samples were collected for microbiological analysis. We applied four approaches for detecting fungal signatures of moisture damage in these buildings. Two novel targeted approaches selected specific taxa, identified by a priori hypotheses, from the broad mycobiome as detected with amplicon sequencing. We investigated whether (i) hydrophilic fungi (i.e., requiring high moisture) or (ii) fungi previously reported as indicating damp homes would be more abundant in water-damaged rooms/homes than in nondamaged rooms/homes. Two untargeted approaches compared water-damaged to non-water-damaged homes for (i) differences between indoor and outdoor fungal populations or (ii) differences in the presence or relative abundance of particular fungal taxa. Strong relationships with damage indicators were found for some targeted fungal groups in some sampling types, although not always in the hypothesized direction. For example, for vacuum samples, hydrophilic fungi had significantly higher relative abundance in water-damaged homes, but mesophilic fungi, unexpectedly, had significantly lower relative abundance in homes with visible mold. Untargeted approaches identified no microbial community metrics correlated with water damage variables but did identify specific taxa with at least weak positive links to water-damaged homes. These results, although showing a complex relationship between moisture damage and microbial communities, suggest that targeting particular fungi offers a potential route toward identifying a fungal signature of moisture damage in buildings.IMPORTANCE Living or working in damp or moldy buildings increases the risk of many adverse health effects, including asthma and other respiratory diseases. To date, however, the particular environmental exposure(s) from water-damaged buildings that causes the health effects have not been identified. Likewise, a consistent quantitative measurement that would indicate whether a building is water damaged or poses a health risk to occupants has not been found. In this work, we tried to develop analytical tools that would find a microbial signal of moisture damage amid the noisy background of microorganisms in buildings. The most successful approach taken here focused on particular groups of fungi-those considered likely to grow in damp indoor environments-and their associations with observed moisture damage. With further replication and refinement, this hypothesis-based strategy may be effective in finding still-elusive relationships between building damage and microbiomes.

Project description:The Mycobacterium tuberculosis mycolate flippase MmpL3 has been the proposed target for multiple inhibitors with diverse chemical scaffolds. This diversity in chemical scaffolds has made it difficult to predict compounds that inhibit MmpL3 without whole-genome sequencing of isolated resistant mutants. Here, we describe the identification of four new inhibitors that select for resistance mutations in mmpL3. Using these resistant mutants, we conducted a targeted whole-cell phenotypic screen of 163 novel M. tuberculosis growth inhibitors for differential growth inhibition of wild-type M. tuberculosis compared to the growth of a pool of 24 unique mmpL3 mutants. The screen successfully identified six additional putative MmpL3 inhibitors. The compounds were bactericidal both in vitro and against intracellular M. tuberculosisM. tuberculosis cells treated with these compounds were shown to accumulate trehalose monomycolates, have reduced levels of trehalose dimycolate, and displace an MmpL3-specific probe, supporting MmpL3 as the target. The inhibitors were mycobacterium specific, with several also showing activity against the nontuberculous mycobacterial species M. abscessus Cluster analysis of cross-resistance profiles generated by dose-response experiments for each combination of 13 MmpL3 inhibitors against each of the 24 mmpL3 mutants defined two clades of inhibitors and two clades of mmpL3 mutants. Pairwise combination studies of the inhibitors revealed interactions that were specific to the clades identified in the cross-resistance profiling. Additionally, modeling of resistance-conferring substitutions to the MmpL3 crystal structure revealed clade-specific localization of the residues to specific domains of MmpL3, with the clades showing differential resistance. Several compounds exhibited high solubility and stability in microsomes and low cytotoxicity in macrophages, supporting their further development. The combined study of multiple mutants and novel compounds provides new insights into structure-function interactions of MmpL3 and small-molecule inhibitors.

Dataset Information

MAGIC-web: a platform for untargeted and targeted N-linked glycoprotein identification.

Publications

MAGIC-web: a platform for untargeted and targeted N-linked glycoprotein identification.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets