The Arabidopsis thaliana PeptideAtlas; harnessing world-wide proteomics data for a comprehensive community proteomics resource

We developed a new resource, the Arabidopsis PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/), to solve central questions about the Arabidopsis proteome, such as the significance of protein splice forms, post-translational modifications (PTMs), or simply obtain reliable information about specific proteins. PeptideAtlas is based on published mass spectrometry (MS) analyses collected through ProteomeXchange and reanalyzed through a uniform processing and metadata annotation pipeline. All matched MS-derived peptide data are linked to spectral, technical and biological metadata. Nearly 40 million out of ~143 million MSMS spectra were matched to the reference genome Araport11, identifying ~0.5 million unique peptides and 17858 uniquely identified proteins (only isoform per gene) at the highest confidence level (FDR 0.0004; 2 non-nested peptides ≥ 9 aa each), assigned canonical proteins, and 3543 lower confidence proteins. Physicochemical protein properties were evaluated for targeted identification of unobserved proteins. Additional proteins and isoforms currently not in Araport11 were identified, generated from pseudogenes, alternative start, stops and/or splice variants and sORFs; these features should be considered for updates to the Arabidopsis genome. Phosphorylation can be inspected through a sophisticated PTM viewer. This new PeptideAtlas is integrated with community resources including TAIR, tracks in JBrowse, PPDB and UniProtKB. Subsequent PeptideAtlas builds will incorporate millions more MS data.

Impact of Truncated O-glycans in Gastric-Cancer-Associated CD44v9 Detection

CD44 variant isoforms are often upregulated in cancer and associated with increased aggressive tumor phenotypes. The CD44v9 is one of the major protein splice variant isoforms expressed in human gastrointestinal cancer cells. Immunodetection of CD44 isoforms like CD44v9 in tumor tissue is almost exclusively performed by using specific monoclonal antibodies. However, the structural variability conferred by both the alternative splicing and CD44 protein glycosylation is disregarded. In the present work, we have evaluated the role of O-glycosylation using glycoengineered gastric cancer models in the detection of CD44v9 by monoclonal antibodies. We demonstrated, using different technical approaches, that the presence of immature O-glycan structures, such as Tn and STn, enhance CD44v9 protein detection. These findings can have significant implications in clinical applications mainly at the detection and targeting of this cancer-related CD44v9 isoform and highlight the utmost importance of considering glycan structures in cancer biomarker detection and in therapy targeting.

PSSP: Protein splice site prediction algorithm using Bayesian approach

This study aimed to introduce an algorithm and identify intein motif and blocks involved in protein splicing, and explore the underlying methods in the development of detection of protein motifs. Inteins are mobile protein splicing elements capable of self-splicing post-translationally. They exist in viruses and bacteriophage, notwithstanding this broad phylogenetic distribution, all inteins apportion common structural features. A method was developed to predict intein in a raw sequence, using a ranking and scoring scheme based on amino acid [Formula: see text] value tables. This method aided in the identification and assessment of patterns characterizing the intein sequences. New intein conserved properties are revealed and the known ones are described and localized. We have computed the [Formula: see text] value of each amino acid at block A positions [Formula: see text] to [Formula: see text], block B positions [Formula: see text] to [Formula: see text] and block G positions [Formula: see text]7 to [Formula: see text] for the three categories. The consensus amino acids thus found are listed at the end of each row. We gave statistics for the distance between the blocks, block A to B, block B to F, and block F to G with the average being 66.1, 294, and 10.2 amino acids, respectively. The actual blocks A, B, and G of the one intein found in vacuolar membrane ATPase subunit, a precursor protein, are ranked 1. The results indicate all of the block sequences that are found in nine proteins are ranked at top of the list. The intein sequence is used to search the databases for intein-like proteins. Understanding the functional, structural, and dynamical aspects of inteins is important for intein engineering and the betterment of intein database.

Dissecting splicing decisions and cell-to-cell variability with designed sequence libraries

Most human genes are alternatively spliced, allowing for a large expansion of the proteome. The multitude of regulatory inputs to splicing limits the potential to infer general principles from investigating native sequences. Here, we create a rationally designed library of >32,000 splicing events to dissect the complexity of splicing regulation through systematic sequence alterations. Measuring RNA and protein splice isoforms allows us to investigate both cause and effect of splicing decisions, quantify diverse regulatory inputs and accurately predict (R2 = 0.73–0.85) isoform ratios from sequence and secondary structure. By profiling individual cells, we measure the cell-to-cell variability of splicing decisions and show that it can be encoded in the DNA and influenced by regulatory inputs, opening the door for a novel, single-cell perspective on splicing regulation.

Dissecting splicing decisions and cell-to-cell variability with designed sequence libraries

Most human genes are alternatively spliced, allowing for a large expansion of the proteome.The multitude of regulatory inputs to splicing limits the potential to infer general principles from investigating native sequences. Here, we created a rationally designed library of >32,000 splicing events to dissect the complexity of splicing regulation through systematicsequence alterations. Measuring RNA and protein splice isoforms allowed us to investigate bothcause and effect of splicing decisions, quantify diverse regulatory inputs and accurately predict (R2=0.75–0.85) isoform ratios from sequence and secondary structure. By profiling individual cells, we measure the cell-to-cell variability of splicing decisions and show that it can be encoded in the DNA and influenced by regulatory inputs, opening the door for a novel,single-cell perspective on splicing regulation.

Intra- or extra-exosomal secretion of HDGF isoforms: the extraordinary function of the HDGF-A N-terminal peptide

Hepatoma-derived growth factor (HDGF) is a protein with diverse intracellular functions. Moreover, after non-conventional secretion, extracellular HDGF is able to influence different signaling pathways, leading for example to induction of processes like epithelial-mesenchymal transition (EMT) and cell migration. Intriguingly, in recent proteome studies, HDGF was also found secreted by special microvesicles called exosomes. Recently, we demonstrated the existence of two new HDGF isoforms (B and C). These isoforms are involved in different cellular processes than HDGF-A. Along this line, in the present study we discovered that full length HDGF-A clearly is located inside of exosomes, whereas the isoforms HDGF-B and HDGF-C are found exclusively on the outer surface. Furthermore, while HDGF-B and HDGF-C seem to use exosomes mediated pathway exclusively, HDGF-A was found also as unbound protein in the conditioned media. The new finding of an intra- or extra-exosomal localisation of protein splice variants opens a fascinating new perspective concerning functional diversity of HDGF isoforms. Dysregulation of HDGF expression during cancer development and tumor progression is a commonly known fact. With our new findings, unraveling the potential functional impact according to physiological versus pathophysiologically altered levels and compositions of intra- and extra-exosomal HDGF has to be addressed in future studies.

Inverting proteomics analysis provides powerful insight into the peptide/protein conundrum

In proteomics, a large proportion of mass spectrometry (MS) data is ignored due to the lack of, or insufficient statistical evidence for mappable peptides. In reality, only a small fraction of features are expected to be differentially relevant anyway. Mapping spectra to peptides and subsequently, proteins, produces uncertainty at several levels. We propose it is better to analyze proteomic profiling data directly at MS level, and then relate these features to peptides/proteins. In a renal cancer data comprising 12 normal and 12 cancer subjects, we demonstrate that a simple rule-based binning approach can give rise to informative features. We note that the peptides associated with significant spectral bins gave rise to better class separation than the corresponding proteins, suggesting a loss of signal in the peptide-to-protein transition. Additionally, the binning approach sharpens focus on relevant protein splice forms rather than just canonical sequences. Taken together, the inverted raw spectra analysis paradigm, which is realised by the MZ-Bin method described in this article, provides new possibilities and insights, in how MS-data can be interpreted.