scholarly journals Mapping the Melanoma Plasma Proteome (MPP) Using Single-Shot Proteomics Interfaced with the WiMT Database

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6224
Author(s):  
Natália Almeida ◽  
Jimmy Rodriguez ◽  
Indira Pla Parada ◽  
Yasset Perez-Riverol ◽  
Nicole Woldmar ◽  
...  
Keyword(s):  
Sample Preparation ◽  
Large Scale ◽  
Protein Identification ◽  
Dynamic Range ◽  
Protein Sequences ◽  
Single Shot ◽  
Protein Database ◽  
Plasma Analysis ◽  
Novel Proteins ◽  
Simple Sample Preparation

Plasma analysis by mass spectrometry-based proteomics remains a challenge due to its large dynamic range of 10 orders in magnitude. We created a methodology for protein identification known as Wise MS Transfer (WiMT). Melanoma plasma samples from biobank archives were directly analyzed using simple sample preparation. WiMT is based on MS1 features between several MS runs together with custom protein databases for ID generation. This entails a multi-level dynamic protein database with different immunodepletion strategies by applying single-shot proteomics. The highest number of melanoma plasma proteins from undepleted and unfractionated plasma was reported, mapping >1200 proteins from >10,000 protein sequences with confirmed significance scoring. Of these, more than 660 proteins were annotated by WiMT from the resulting ~5800 protein sequences. We could verify 4000 proteins by MS1t analysis from HeLA extracts. The WiMT platform provided an output in which 12 previously well-known candidate markers were identified. We also identified low-abundant proteins with functions related to (i) cell signaling, (ii) immune system regulators, and (iii) proteins regulating folding, sorting, and degradation, as well as (iv) vesicular transport proteins. WiMT holds the potential for use in large-scale screening studies with simple sample preparation, and can lead to the discovery of novel proteins with key melanoma disease functions.

scholarly journals Shotgun Proteomics and Biomarker Discovery

2002 ◽  
Vol 18 (2) ◽  
pp. 99-105 ◽  
Author(s):  
W. Hayes McDonald ◽  
John R. Yates
Keyword(s):  
Large Scale ◽  
Protein Identification ◽  
Biomarker Discovery ◽  
Dynamic Range ◽  
Shotgun Proteomics ◽  
Sequence Information ◽  
Protein Biomarkers ◽  
Post Translational Modifications ◽  
Multidimensional Protein Identification Technology ◽  
Shotgun Approach

Coupling large-scale sequencing projects with the amino acid sequence information that can be gleaned from tandem mass spectrometry (MS/MS) has made it much easier to analyze complex mixtures of proteins. The limits of this “shotgun” approach, in which the protein mixture is proteolytically digested before separation, can be further expanded by separating the resulting mixture of peptides prior to MS/MS analysis. Both single dimensional high pressure liquid chromatography (LC) and multidimensional LC (LC/LC) can be directly interfaced with the mass spectrometer to allow for automated collection of tremendous quantities of data. While there is no single technique that addresses all proteomic challenges, the shotgun approaches, especially LC/LC-MS/MS-based techniques such as MudPIT (multidimensional protein identification technology), show advantages over gel-based techniques in speed, sensitivity, scope of analysis, and dynamic range. Advances in the ability to quantitate differences between samples and to detect for an array of post-translational modifications allow for the discovery of classes of protein biomarkers that were previously unassailable.

scholarly journals Rapid and Sensitive Quantification of Intracellular Glycyl-Sarcosine for Semi-High-Throughput Screening for Inhibitors of PEPT-1

Pharmaceutics ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1019
Author(s):  
Teresa von Linde ◽  
Gzona Bajraktari-Sylejmani ◽  
Walter E. Haefeli ◽  
Jürgen Burhenne ◽  
Johanna Weiss ◽  
...  
Keyword(s):  
Sample Preparation ◽  
High Throughput ◽  
High Throughput Screening ◽  
Dynamic Range ◽  
High Sensitivity ◽  
Peptide Bond ◽  
Peptide Transporter ◽  
Systemic Absorption ◽  
Screening Assay ◽  
Limit Of Quantification

The peptide transporter PEPT-1 (SLC15A1) plays a major role in nutritional supply with amino acids by mediating the intestinal influx of dipeptides and tripeptides generated during food digestion. Its role in the uptake of small bioactive peptides and various therapeutics makes it an important target for the investigation of the systemic absorption of small peptide-like active compounds and prodrug strategies of poorly absorbed therapeutics. The dipeptide glycyl-sarcosine (Gly-Sar), which comprises an N-methylated peptide bond that increases stability against enzymatic degradation, is widely utilized for studying PEPT-1-mediated transport. To support experiments on PEPT-1 inhibitor screening to identify potential substrates, we developed a highly sensitive Gly-Sar quantification assay for Caco-2 cell lysates with a dynamic range of 0.1 to 1000 ng/mL (lower limit of quantification 0.68 nM) in 50 µL of cell lysate. The assay was validated following the applicable recommendations for bioanalytic method validation of the FDA and EMA. Sample preparation and quantification were established in 96-well cell culture plates that were also used for the cellular uptake studies, resulting in a rapid and robust screening assay for PEPT-1 inhibitors. This sample preparation principle, combined with the high sensitivity of the UPLC-MS/MS quantification, is suitable for screening assays for PEPT-1 inhibitors and substrates in high-throughput formats and holds the potential for automation. Applicability was demonstrated by IC50 determinations of the known PEPT-1 inhibitor losartan, the known substrates glycyl-proline (Gly-Pro), and valaciclovir, the prodrug of aciclovir, which itself is no substrate of PEPT-1 and consequently showed no inhibition in our assay.

scholarly journals KK-DBP: A Multi-Feature Fusion Method for DNA-Binding Protein Identification Based on Random Forest

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuran Jia ◽  
Shan Huang ◽  
Tianjiao Zhang
Keyword(s):  
Dna Binding ◽  
Prediction Accuracy ◽  
Large Scale ◽  
Protein Identification ◽  
Feature Fusion ◽  
Binding Protein ◽  
Rapid Development ◽  
Dna Binding Protein ◽  
Feature Extraction Method ◽  
Independent Test Dataset

DNA-binding protein (DBP) is a protein with a special DNA binding domain that is associated with many important molecular biological mechanisms. Rapid development of computational methods has made it possible to predict DBP on a large scale; however, existing methods do not fully integrate DBP-related features, resulting in rough prediction results. In this article, we develop a DNA-binding protein identification method called KK-DBP. To improve prediction accuracy, we propose a feature extraction method that fuses multiple PSSM features. The experimental results show a prediction accuracy on the independent test dataset PDB186 of 81.22%, which is the highest of all existing methods.

scholarly journals PaperBLAST: Text-mining papers for information about homologs

2017 ◽  
Author(s):  
Morgan N. Price ◽  
Adam P. Arkin
Keyword(s):  
Text Mining ◽  
Genome Sequencing ◽  
Full Text ◽  
Large Scale ◽  
Scientific Literature ◽  
Protein Sequences ◽  
Protein Coding ◽  
Link Protein ◽  
Protein Coding Genes ◽  
Link Type

AbstractLarge-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources that link protein sequences to scientific articles (Swiss-Prot, GeneRIF, and EcoCyc). PaperBLAST’s database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quickly finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. PaperBLAST is available at http://papers.genomics.lbl.gov/.

scholarly journals Recent developments and prospects in the composition, extraction, stability, delivery system, digestion and food applications of plant oil bodies

2021 ◽  
Author(s):  
Jia Hao ◽  
Duoxia Xu ◽  
Yangping Cao
Keyword(s):  
Delivery System ◽  
Large Scale ◽  
Protein Identification ◽  
Meat Products ◽  
Calorie Intake ◽  
Oil Bodies ◽  
Plant Oil ◽  
Electrostatic Deposition ◽  
Food Applications ◽  
The Stability

Oil bodies (OBs) are micron- or submicron-sized sub-organelles widely found in plants seeds and nuts. The structure OBs is composed of a core of triglycerides covered by a phospholipid-protein layer, which ensures the stability of the OBs under extreme environmental conditions and further protects core lipids as energy reserves. As naturally pre-emulsified oil-in-water emulsions, OBs have been gradually applied to replace synthetically engineered oil droplets. In this paper, the recent research on the composition, extraction, stability, delivery system, digestion, food applications and future perspectives of plant OBs are reviewed. Recent studies have focused on the OBs surface protein identification and function, large-scale extraction techniques such as enzyme assisted, high pressure, ultrasound, and extrusion and the reconstituted OBs. Electrostatic deposition of polysaccharides significantly improves the stability of OBs emulsions. OBs emulsions have promising applications to encapsulate bioactive compounds, deliver targeted drugs, and prepare gels and edible functional films. The digestive behavior of OBs emulsions is similar to that of protein-stabilized emulsions, which can increase the satiety, effectively help reduce calorie intake and improve the bioavailability of functional factors. It has also promoted the development of simulated dairy, spices and meat products.

scholarly journals LSTrAP-Crowd: Prediction of novel components of bacterial ribosomes with crowd-sourced analysis of RNA sequencing data

2020 ◽  
Author(s):  
Benedict Hew ◽  
Qiao Wen Tan ◽  
William Goh ◽  
Jonathan Wei Xiong Ng ◽  
Kenny Koh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Synthesis ◽  
Rna Sequencing ◽  
Gene Expression Data ◽  
Large Scale ◽  
Bacterial Resistance ◽  
Expression Data ◽  
Sequencing Data ◽  
Novel Proteins ◽  
Novel Antibiotics

AbstractBacterial resistance to antibiotics is a growing problem that is projected to cause more deaths than cancer in 2050. Consequently, novel antibiotics are urgently needed. Since more than half of the available antibiotics target the bacterial ribosomes, proteins that are involved in protein synthesis are thus prime targets for the development of novel antibiotics. However, experimental identification of these potential antibiotic target proteins can be labor-intensive and challenging, as these proteins are likely to be poorly characterized and specific to few bacteria. In order to identify these novel proteins, we established a Large-Scale Transcriptomic Analysis Pipeline in Crowd (LSTrAP-Crowd), where 285 individuals processed 26 terabytes of RNA-sequencing data of the 17 most notorious bacterial pathogens. In total, the crowd processed 26,269 RNA-seq experiments and used the data to construct gene co-expression networks, which were used to identify more than a hundred uncharacterized genes that were transcriptionally associated with protein synthesis. We provide the identity of these genes together with the processed gene expression data. The data can be used to identify other vulnerabilities or bacteria, while our approach demonstrates how the processing of gene expression data can be easily crowdsourced.

scholarly journals Beyond History: The List of The Most Well Studied Human Protein Structures

2020 ◽  
Author(s):  
Zhenlu Li ◽  
Matthias Buck
Keyword(s):  
Protein Structures ◽  
Protein Sequences ◽  
Human Protein ◽  
Current Status ◽  
Protein Database ◽  
X Ray ◽  
X Ray Crystallography ◽  
Protein Biophysics ◽  
The Relationship ◽  
Past Trend

Of 20,000 or so canonical human protein sequences, as of July 2020, 6,747 proteins have had their full or partial medium to high-resolution structures determined by x-ray crystallography or other methods. Which of these proteins dominate the protein database (the PDB) and why? In this paper, we list the 272 top protein structures based on the number of their PDB depositions. This set of proteins accounts for more than 40% of all available human PDB entries and represent past trend and current status for protein science. We briefly discuss the relationship which some of the prominent protein structures have with protein biophysics research and mention their relevance to human diseases. The information may inspire researchers who are new to protein science, but it also provides a year 2020 snap-shot for the state of protein science.

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