Project description:The experiment was performed using three N. gonorrhoeae clinical isolates and N. gonorrhoeae strain ATCC 49226 was used as a reference strain. Tandem mass spectra were processed by PEAKS Studio version 8.5 (Bioinformatics Solutions Inc., Waterloo, Canada). PEAKS DB was set up to search the database assuming trypsin as the digestion enzyme and searched with a fragment ion mass tolerance of 0.05 Da and a parent ion tolerance of 7 ppm. Carbamidomethylation (C) and iTRAQ 4plex (K, N-term) were specified as the fixed modification. Oxidation (M), Deamidation (NQ), and Acetylation (Protein N-term) were specified as the variable modifications. Peptides were filtered with a 1% false discovery rate (FDR) and were required to be a unique peptide. PEAKSQ was used for peptide and protein abundance calculation. Normalization was performed by averaging the abundance of all peptides, and medians were used for averaging.
Project description:SuperQuant is a quantitative proteomics data processing workflow that utilizes fragment ion complementarity to identify multiple co-isolated peptides in tandem mass spectra. Parent ion and label-free quantification method are supported. The performance of the developed approach was tested using dimethyl labeled HeLa lysate sample having artificially created ratio between channels (10(heavy):4(medium):1(light)). Developed software is implemented as a processing node to Thermo Proteome Discoverer 2.x and freely available for the community at https://github.com/caetera/SuperQuantNode.
2015-05-26 | PXD001907 | Pride
Project description:Genetic Improvement of Rice Quality
Project description:Thinning is indispensable practice in peach cultivation aiming to reduce fruit number per plant, promoting sink-source balance and reducing competition among fruit, which results in bigger fruit and the improvement of other fruit-quality parameters. Inhibition of floral induction by GAs has been largely demonstrated and commercial products based on GAs have been used to this aim. We tested a product GA4/7 based in different moments after full bloom in peach to reduce the number of flowers in the following season. Return to bloom and transcriptome analysis were performed to identify the best moment for the treatment, increasing the product efficacy and understanding the product action at genetic level.
Project description:Data analysis. Spot detection and matching were performed with a comparative cross analysis of all the gels using DeCyder software v.6.5 (GE Healthcare). 178 spots were selected based on 1.15-fold for protein ratio cut-off, allowing for the appearance of the spots in 23 out of 28 gels (69 out of 84 total images). Data from 95 spots were submitted. 93 spots were identified with high confidence. Spot picking and Trypsin digestion. The spots of interest were picked up by Ettan Spot Picker (GE Healthcare) based on the in-gel analysis and spot picking design by DeCyder software. The gel spots were washed a few times then digested in-gel with modified porcine trypsin protease (Promega, Fitchburg, WI). The digested tryptic peptides were desalted using a Zip-tip C18 (Millipore, Billerica, MA). Peptides were eluted from the Zip-tip with 0.5 uL of matrix solution (alpha-cyano-4-hydroxycinnamic acid, 5 mg/mL in 50% acetonitrile, 0.1% trifluoroacetic acid, 25mM ammonium bicarbonate) and spotted on a MALDI plate. Mass Spectrometry. MALDI-TOF MS and TOF/TOF tandem MS/MS were performed on AB SCIEX TOF/TOF 5800 System (AB SCIEX). MALDI-TOF mass spectra were acquired in reflectron positive ion mode, averaging 4000 laser shots per spectrum. TOF/TOF tandem MS fragmentation spectra were acquired for each sample, averaging 4000 laser shots per fragmentation spectrum on each of the 7-10 most abundant ions present in each sample (excluding trypsin autolytic peptides and other known background ions). Database search. Both the resulting peptide mass and the associated fragmentation spectra were submitted to GPS Explorer workstation equipped with MASCOT search engine (Matrix Science, Boston, MA) to search the Swiss-Prot database. Searches were performed without constraining protein molecular weight or isoelectric point, with variable carbamidomethylation of cysteine and oxidation of methionine residues, and with one missed cleavage also allowed in the search parameters. Candidates with either protein score C.I.% or Ion C.I.% greater than 95 were considered significant. When multiple IDs were significant for a given spot, the selection was made by evaluating apparent molecular weight, isoelectric point, the location of the spot in the gel, and the presence of strips of multiple protein isoforms in the adjacent spots.
Project description:Host cell proteins (HCPs) are process-related impurities generated during biotherapeutic protein production. HCPs can be problematic if they pose a significant metabolic demand, degrade product quality, or contaminate the final product. Here, we present an effort to create a “clean” Chinese hamster ovary (CHO) cell by disrupting multiple genes to eliminate HCPs. Using a model of CHO cell protein secretion, we predicted the elimination of unnecessary HCPs could have a non-negligible impact on protein production. We analyzed the total HCP content of 6-protein, 11-protein, and 14-protein knockout clones and characterized their growth in shake flasks and bioreactors. These cell lines exhibited a substantial reduction in total HCP content (40%-70%). We also observed higher productivity and improved growth characteristics, in specific clones. With the reduced HCP content, protein A and ion exchange chromatography more efficiently purified a monoclonal antibody (mAb) produced in these cells during a three-step purification process. Thus, substantial improvements can be made in protein titer and purity through large-scale HCP deletion, providing an avenue to increased quality and affordability of high-value biopharmaceuticals.
Project description:This model has been trained using the GROVER embedding with the QM8 dataset from Molecule Net, where the electronic properties have been calculated by multiple quantum mechanic methods.
Model Type: Molecular properties prediction ML model.
Model Relevance: Predicts electronic spectra and excited state energy of small molecules.
Model Encoded by: Amna Ali (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos3xip
Project description:Highly homogenous zein protein was isolated from maize kernels in an environment-friendly process using 95 % ethanol as solvent. High purity of the zein protein product was determined by SDS PAGE analysis and by 2 D gel electrophoresis followed by MALDI-ToF-MS peptide mass fingerprinting after in-gel chymotrypsin digestion. Being a natural product that is encoded by multiple gene copies, the polymorphic zein protein product revealed two rows of protein spots, one at 25 kDa and one at 20 kDa apparent molecular mass. MALDI-ToF-MS peptide mapping of the proteins from all spots indicated the presence of only alpha zein proteins. The most prominent ion signals in the MALDI mass spectra after in-gel digestion were recorded at m/z 1083.5 and m/z 1691.8. These ion signals have been found typical for zein proteins and may serve as marker ion signals which upon chymotryptic digestion reliably indicate the presence of zein protein in both hybrid corn products. Due to the given polyploidy and genetic polymorphism of the plant source the application of high resolution separation methods in conjunction with precise analytical methods, such as MALDI-ToF-MS, is required to accurately estimate homogeneity of products that contain natural zein protein.
Project description:For data-independent acquisition by means of sequential window acquisition of all theoretical fragment ion spectra (SWATH), a reference library of data-dependent acquisition (DDA) runs is typically used to correlate the quantitative data from the fragment ion spectra with peptide identifications. The quality and coverage of such a reference library is therefore essential when processing SWATH data. In general, library sizes can be increased by reducing the impact of DDA precursor selection with replicate runs or fractionation. However, these strategies can affect the match between the library and SWATH measurement, and thus larger library sizes do not necessarily correspond to improved SWATH quantification. Here, three fractionation strategies to increase local library size were compared to standard library building using replicate DDA injection: protein SDS-PAGE fractionation, peptide high-pH RP-HPLC fractionation and MS-acquisition gas phase fractionation. The impact of these libraries on SWATH performance was evaluated in terms of the number of extracted peptides and proteins, the match quality of the peptides and the extraction reproducibility of the transitions. These analyses were conducted using the hydrophilic proteome of differentiating human embryonic stem cells.
Project description:Parallel reaction monitoring (PRM) is an increasingly popular alternative to selected reaction monitoring (SRM) for targeted proteomics. PRM’s strengths over SRM are that it monitors all product ions in a single spectrum, thus eliminating the need to select interference-free product ions prior to data acquisition, and that it is most frequently performed on high-resolution instruments, such as quadrupole-orbitrap and quadrupole-time of flight instruments. Here, we show that the primary advantage of PRM is the ability to monitor all transitions in parallel, and that high-resolution data are not necessary to obtain high quality quantitative data. We run the same scheduled PRM assay, measuring 432 peptides from 126 plasma proteins, multiple times on a Orbitrap Eclipse Tribrid mass spectrometer, alternating separate liquid chromatography-tandem mass spectrometry runs between the high resolution Orbitrap and the unit resolution linear ion trap for PRM. We find that both mass analyzers have similar technical precision, and that the linear ion trap’s superior sensitivity gives it better lower limits of quantitation on over 62% of peptides in the assay.