Highlights • Single-pot workflow for manual or automated enrichment of N-terminal peptides. • Sensitive enrichment of protein N termini from 10,000 cells or 2 g crude proteome. • Data independent acquisition improves precision of peptide level quantification. • First degradomic analyses of sorted immune cells, single seedlings, and mitochondria from patient cells.

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We previously reported that the expression of KIAA1199 in human colorectal tumors (benign and malignant) is markedly higher than that in the normal colonic mucosa. In this study, we investigated the functions of the protein encoded by this gene, which are thus far unknown. Immunostaining studies were used to reveal its subcellular localization, and proteomic and gene expression experiments were conducted to identify proteins that might interact with KIAA1199 and molecular pathways in which it might play roles. Using colon cancer cell lines, we showed that both endogenous and ectopically expressed KIAA1199 is secreted into the extracellular environment. In the cells, it was found mainly in the perinuclear space (probably the ER) and cell membrane. Both cellular compartments were also over-represented in lists of proteins identified by mass spectrometry as putative KIAA1199 interactors and/or proteins encoded by genes whose transcription was significantly changed by KIAA1199 expression. These proteomic and transcriptomic datasets concordantly link KIAA1199 to several genes/proteins and molecular pathways, including ER processes like protein binding, transport, and folding; and Ca2+, G-protein, ephrin, and Wnt signaling. Immunoprecipitation experiments confirmed KIAA1199’s interaction with the cell-membrane receptor ephrin A2 and with the ER receptor ITPR3, a key player in Ca2+ signaling. By modulating Ca2+ signaling, KIAA1199 could affect different branches of the Wnt network. Our findings suggest it may negatively regulate the Wnt/CTNNB1 signaling, and its expression is associated with decreased cell proliferation and invasiveness.

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Targeted proteomic methods can accelerate the verification of multiple tumor marker candidates in large series of patient samples. We utilized the targeted approach known as selected/multiple reaction monitoring (S/MRM) to verify potential protein markers of colorectal adenoma identified by our group in previous transcriptomic and quantitative shotgun proteomic studies of a large cohort of precancerous colorectal lesions. We developed SRM assays to reproducibly detect and quantify 25 (62.5%) of the 40 selected proteins in an independent series of precancerous and cancerous tissue samples (19 adenoma/ normal mucosa pairs; 17 adenocarcinoma/normal mucosa pairs). Twenty-three proteins were significantly upregulated (n ‫؍‬ 17) or downregulated (n ‫؍‬ 6) in adenomas and/or adenocarcinomas, as compared with normal mucosa (linear fold changes > ؎1.3, adjusted p value <0.05). Most changes were observed in both tumor types (up-regulation of ANP32A, ANXA3, SORD, LDHA, LCN2, NCL, S100A11, SERPINB5, CDV3, OLFM4, and REG4; downregulation of ARF6 and PGM5), and a fiveprotein biomarker signature distinguished neoplastic tissue from normal mucosa with a maximum area under the receiver operating curve greater than 0.83. Other changes were specific for adenomas (PPA1 and PPA2 up-regulation; KCTD12 downregulation) or adenocarcinoma (ANP32B, G6PD, RCN1, and SET up-regulation; downregulated AKR1B1, APEX1, and PPA1). Some changes significantly correlated with a few patient-or tumor-related phenotypes. Twenty-two (96%) of the 23 proteins have a potential to be released from the tumors into the bloodstream, and their detectability in plasma has been previously reported. The proteins identified in this study expand the pool of biomarker candidates that can be used to develop a standardized precolonoscopy blood test for the early detection of colorectal tumors. Molecular & Cellular

The local sequence context is the most fundamental feature determining the post-translational modification (PTM) of proteins. Recent technological improvements allow for the detection of new and less prevalent modifications. We found that established state-of-the-art algorithms for the detection of PTM motifs in complex datasets failed to keep up with this technological development and are no longer robust. To overcome this limitation, we developed RoLiM, a new linear motif deconvolution algorithm and webserver, that enables robust and unbiased identification of local amino acid sequence determinants in complex biological systems demonstrated here by the analysis of 68 modifications found across 30 tissues in the human draft proteome map. Furthermore, RoLiM analysis of a large-scale phosphorylation dataset comprising 30 kinase inhibitors of 10 protein kinases in the EGF signalling pathway identified prospective substrate motifs for PI3K and EGFR.

X-linked adrenoleukodystrophy (ALD) is a peroxisomal metabolic disorder with a highly complex clinical presentation. ALD is caused by mutations in the ABCD1 gene, and is characterized by the accumulation of very long-chain fatty acids in plasma and tissues. Disease-causing mutations are 'loss of function' mutations, with no prognostic value with respect to the clinical outcome of an individual. All male patients with ALD develop spinal cord disease and a peripheral neuropathy in adulthood, although age of onset is highly variable. However, the lifetime prevalence to develop progressive white matter lesions, termed cerebral ALD (CALD), is only about 60%. Early identification of transition to CALD is critical since it can be halted by allogeneic hematopoietic stem cell therapy only in an early stage. The primary goal of this study is to identify molecular markers which may be prognostic of cerebral demyelination from a simple blood sample, with the hope that blood-based assays can replace the current protocols for diagnosis. We collected six well-characterized brother pairs affected by ALD and discordant for the presence of CALD and performed multi-omic profiling of blood samples including genome, epigenome, transcriptome, metabolome/lipidome, and proteome profiling. In our analysis we identify discordant genomic alleles present across all families as well as differentially abundant molecular features across the omics technologies. The analysis was focused on univariate modeling to discriminate the two phenotypic groups, but was unable to identify statistically significant candidate molecular markers. Our study

Introduction: Cancer changes the proteome in complex ways that reach well beyond simple changes in protein abundance. Genomic and transcriptional variations and post-translational protein modification create functional variants of a protein, known as proteoforms. Childhood cancers have fewer genomic alterations but show equally dramatic phenotypic changes as malignant cells in adults. Therefore, unraveling the complexities of the proteome is even more important in pediatric malignancies. Areas covered: In this review, the biological origins of proteoforms and technological advancements in the study of proteoforms are discussed. Particular emphasis is given to their implication in childhood malignancies and the critical role of cancer-specific proteoforms for the next generation of cancer therapies and diagnostics. Expert opinion: Recent advancements in technology have led to a better understanding of the underlying mechanisms of tumorigenesis. This has been critical for the development of more effective and less harmful treatments that are based on direct targeting of altered proteins and deregulated pathways. As proteome coverage and the ability to detect complex proteoforms increase, the most need for change is in data compilation and database availability to mediate high-level data analysis and allow for better functional annotation of proteoforms.