Proteomic analysis of the developing mammalian brain links PCDH19 to the Wnt/ß-catenin signalling pathway.

Clustering Epilepsy (CE) is a neurological disorder caused by pathogenic variants of the Protocadherin 19 (PCDH19) gene. PCDH19 encodes a protein involved in cell adhesion and Estrogen Receptor α mediated-gene regulation. To gain further insights into the molecular role of PCDH19 in the brain, we investigated the PCDH19 interactome in the developing mouse hippocampus and cortex. Combined with a meta-analysis of all reported PCDH19 interacting proteins, our results show that PCDH19 interacts with proteins involved in actin, microtubule, and gene regulation. We report CAPZA1, αN-catenin and, importantly, ß-catenin as novel PCDH19 interacting proteins. Furthermore, we show that PCDH19 is a regulator of ß-catenin transcriptional activity, and that this pathway is disrupted in CE individuals. Overall, our results support the involvement of PCDH19 in the cytoskeletal network and point to signalling pathways where PCDH19 plays critical roles.

Precision Targeting of Endogenous Epidermal Growth Factor Receptor (EGFR) by Structurally Aligned Dual-Modifier Labeling.

Covalent modification of endogenous proteins by chemical probes is used for proteome-wide profiling of cellular protein function and drug discovery. However, probe selectivity in the complex cellular environment is a challenge, and new probes with better target selectivity are continuously needed. On the basis of the success of monocovalent activity-based and reactivity-based probes, an approach of structurally aligned dual-modifier labeling (SADL) was investigated here on its potential in improving target precision. Two reactive groups, based on the acrylamide and NHS ester chemistry, were linked with structural alignment to be under the same anilinoquinazoline ligand-directive for targeting the epidermal growth factor receptor (EGFR) protein kinase as the model system for proteome-wide profiling. The SADL approach was compared with its monocovalent precursors in a label-free MaxLFQ workflow using MDA-MB-468 triple negative breast cancer cells. The dual-modifier probe consistently showed labeling of EGFR with improved precision over both monocovalent precursors under various controls. The workflow also labeled endogenous USP34 and PKMYT1 with high selectivity. Precision labeling with two covalent modifiers under a common ligand directive may broaden protein identification opportunities in the native environment to complement genetic and antibody-based approaches for elucidating biological or disease mechanisms, as well as accelerating drug target discovery.

Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins.

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

Amyloid-beta peptide neurotoxicity in human neuronal cells is associated with modulation of insulin-like growth factor transport, lysosomal machinery and extracellular matrix receptor interactions.

Extracellular deposits of the amyloid-beta peptide (Aß) are known as the main pathological hallmark of Alzheimer's disease. In Alzheimer's disease, neurons are injured and die throughout the brain, a process in which Aß neurotoxicity is considered to play an important role. However, the molecular mechanisms underlying Aß toxicity that lead to neurodegeneration are not clearly established. Here we have elucidated the molecular pathways and networks which are impacted by Aß in neurons using SH-SY5Y human neuroblastoma cells as a model. These cells were treated with Aß1-42 peptides to study changes in biochemical networks using tandem mass tag labeled quantitative proteomic technique followed by computational analysis of the data. The molecular impacts of Aß on cells were evident in a time- and dose-dependent manner, albeit the duration of treatment induced greater differential changes in cellular proteome compared to the effects of concentration. Aß induced early changes in proteins associated with lysosomes, collagen chain trimerization and extracellular matrix receptor interaction, complement and coagulation cascade, oxidative stress induced senescence, ribosome biogenesis, regulation of insulin-like growth factor transport and uptake by insulin-like growth factor-binding protein. These novel findings provide molecular insights on the effects of Aß on neurons, with implications for better understanding the impacts of Aß on early neurodegeneration in Alzheimer's disease pathology.

Two of a kind: transmissible Schwann cell cancers in the endangered Tasmanian devil (Sarcophilus harrisii).

Devil facial tumour disease (DFTD) comprises two genetically distinct transmissible cancers (DFT1 and DFT2) endangering the survival of the Tasmanian devil (Sarcophilus harrisii) in the wild. DFT1 first arose from a cell of the Schwann cell lineage; however, the tissue-of-origin of the recently discovered DFT2 cancer is unknown. In this study, we compared the transcriptome and proteome of DFT2 tumours to DFT1 and normal Tasmanian devil tissues to determine the tissue-of-origin of the DFT2 cancer. Our findings demonstrate that DFT2 expresses a range of Schwann cell markers and exhibits expression patterns consistent with a similar origin to the DFT1 cancer. Furthermore, DFT2 cells express genes associated with the repair response to peripheral nerve damage. These findings suggest that devils may be predisposed to transmissible cancers of Schwann cell origin. The combined effect of factors such as frequent nerve damage from biting, Schwann cell plasticity and low genetic diversity may allow these cancers to develop on rare occasions. The emergence of two independent transmissible cancers from the same tissue in the Tasmanian devil presents an unprecedented opportunity to gain insight into cancer development, evolution and immune evasion in mammalian species.

Clinically Relevant Post-Translational Modification Analyses-Maturing Workflows and Bioinformatics Tools.

Post-translational modifications (PTMs) can occur soon after translation or at any stage in the lifecycle of a given protein, and they may help regulate protein folding, stability, cellular localisation, activity, or the interactions proteins have with other proteins or biomolecular species. PTMs are crucial to our functional understanding of biology, and new quantitative mass spectrometry (MS) and bioinformatics workflows are maturing both in labelled multiplexed and label-free techniques, offering increasing coverage and new opportunities to study human health and disease. Techniques such as Data Independent Acquisition (DIA) are emerging as promising approaches due to their re-mining capability. Many bioinformatics tools have been developed to support the analysis of PTMs by mass spectrometry, from prediction and identifying PTM site assignment, open searches enabling better mining of unassigned mass spectra-many of which likely harbour PTMs-through to understanding PTM associations and interactions. The remaining challenge lies in extracting functional information from clinically relevant PTM studies. This review focuses on canvassing the options and progress of PTM analysis for large quantitative studies, from choosing the platform, through to data analysis, with an emphasis on clinically relevant samples such as plasma and other body fluids, and well-established tools and options for data interpretation.

Pseudomonas aeruginosa Proteome under Hypoxic Stress Conditions Mimicking the Cystic Fibrosis Lung.

Pseudomonas aeruginosa is a ubiquitous Gram-negative pathogen known to inhabit hypoxic mucus plugs of cystic fibrosis (CF) patient lungs. Despite the high prevalence and related patient mortality, the protein machinery enabling the bacterium to adapt to low oxygen environment remains to be fully elucidated. We investigated this by performing both SWATH mass spectrometry and data-dependent SPS-MS3 of TMT-labeled peptides to profile the proteomes of two P. aeruginosa CF isolates, PASS2 and PASS3, and a laboratory reference strain, PAO1, grown under hypoxic stress (O2 < 1%) in media that mimic the nutrient components of the CF lung. Quantitated across all three strains were 3967 P. aeruginosa proteins, reflecting approximately 71% of predicted ORFs in PAO1 and representing the most comprehensive proteome of clinically relevant P. aeruginosa to date. Comparative analysis revealed 735, 640, and 364 proteins were altered by 2-fold or more when comparing low oxygen to aerobic growth in PAO1, PASS2, and PASS3, respectively. Strikingly, under hypoxic stress, all strains showed concurrent increased abundance of proteins required for both aerobic (cbb3-1 and cbb3-2 terminal oxidases) and anaerobic denitrification and arginine fermentation, with the two clinical isolates showing higher relative expression of proteins in these pathways. Additionally, functional annotation revealed that clinical strains portray a unique expression profile of replication, membrane biogenesis, and virulence proteins during hypoxia which may endow these bacteria with a survival advantage. These protein profiles illuminate the diversity of P. aeruginosa mechanisms to adapt to low oxygen and shows that CF isolates initiate a robust molecular response to persist under these conditions.

Pseudomonas aeruginosa Cell Membrane Protein Expression from Phenotypically Diverse Cystic Fibrosis Isolates Demonstrates Host-Specific Adaptations.

Pseudomonas aeruginosa is a Gram-negative, nosocomial, highly adaptable opportunistic pathogen especially prevalent in immuno-compromised cystic fibrosis (CF) patients. The bacterial cell surface proteins are important contributors to virulence, yet the membrane subproteomes of phenotypically diverse P. aeruginosa strains are poorly characterized. We carried out mass spectrometry (MS)-based proteome analysis of the membrane proteins of three novel P. aeruginosa strains isolated from the sputum of CF patients and compared protein expression to the widely used laboratory strain, PAO1. Microbes were grown in planktonic growth condition using minimal M9 media, and a defined synthetic lung nutrient mimicking medium (SCFM) limited passaging. Two-dimensional LC-MS/MS using iTRAQ labeling enabled quantitative comparisons among 3171 and 2442 proteins from the minimal M9 medium and in the SCFM, respectively. The CF isolates showed marked differences in membrane protein expression in comparison with PAO1 including up-regulation of drug resistance proteins (MexY, MexB, MexC) and down-regulation of chemotaxis and aerotaxis proteins (PA1561, PctA, PctB) and motility and adhesion proteins (FliK, FlgE, FliD, PilJ). Phenotypic analysis using adhesion, motility, and drug susceptibility assays confirmed the proteomics findings. These results provide evidence of host-specific microevolution of P. aeruginosa in the CF lung and shed light on the adaptation strategies used by CF pathogens.

Genetically and Phenotypically Distinct Pseudomonas aeruginosa Cystic Fibrosis Isolates Share a Core Proteomic Signature.

The opportunistic pathogen Pseudomonas aeruginosa is among the main colonizers of the lungs of cystic fibrosis (CF) patients. We have isolated and sequenced several P. aeruginosa isolates from the sputum of CF patients and compared them with each other and with the model strain PAO1. Phenotypic analysis of CF isolates showed significant variability in colonization and virulence-related traits suggesting different strategies for adaptation to the CF lung. Genomic analysis indicated these strains shared a large set of core genes with the standard laboratory strain PAO1, and identified the genetic basis for some of the observed phenotypic differences. Proteomics revealed that in a conventional laboratory medium PAO1 expressed 827 proteins that were absent in the CF isolates while the CF isolates shared a distinctive signature set of 703 proteins not detected in PAO1. PAO1 expressed many transporters for the uptake of organic nutrients and relatively few biosynthetic pathways. Conversely, the CF isolates expressed a narrower range of transporters and a broader set of metabolic pathways for the biosynthesis of amino acids, carbohydrates, nucleotides and polyamines. The proteomic data suggests that in a common laboratory medium PAO1 may transport a diverse set of "ready-made" nutrients from the rich medium, whereas the CF isolates may only utilize a limited number of nutrients from the medium relying mainly on their own metabolism for synthesis of essential nutrients. These variations indicate significant differences between the metabolism and physiology of P. aeruginosa CF isolates and PAO1 that cannot be detected at the genome level alone. The widening gap between the increasing genomic data and the lack of phenotypic data means that researchers are increasingly reliant on extrapolating from genomic comparisons using experimentally characterized model organisms such as PAO1. While comparative genomics can provide valuable information, our data suggests that such extrapolations may be fraught with peril.

Proteomics of hosts and pathogens in cystic fibrosis.

Cystic fibrosis (CF) is a congenital disease that results in great morbidity and mortality mainly in the Caucasian population. Although CF is a monogenic disease caused by mutation in the CF conductance transmembrane regulator (CFTR) gene, most of the related mortality can be attributed to infection mediated by opportunistic bacterial and fungal pathogens. Over the past decade, advancements in the field of proteomics have helped to gain insight into the repertoire of host and pathogen proteins involved in CF pathophysiology. This review provides an overview of the contributions of proteomic studies in advancing our knowledge of the biology of CF and disease progression associated with pathogen infection and host defense responses.

Proteomic databases and tools to decipher post-translational modifications.

Post-translational modifications (PTMs) are vital cellular control mechanism, which affect protein properties, including folding, conformation, activity and consequently, their functions. As a result they play a key role in various disease conditions, including cancer and diabetes. Proteomics as a rapidly growing field has witnessed tremendous advancement during the last decade, which has led to the generation of prodigious quantity of data for various organisms' proteome. PTMs being biologically and chemically dynamic process, pose greater challenges for its study. Amidst these complexities connecting the modifications with physiological and cellular cascade of events are still very challenging. Advancement in proteomic technologies such as mass spectrometry and microarray provides HT platform to study PTMs and help to decipher role of some of the very essential biological phenomenon. To enhance our understanding of various PTMs in different organisms, and to simplify the analysis of complex PTM data, many databases, software and tools have been developed. These PTM databases and tools contain crucial information and provide a valuable resource to the research community. This article intends to provide a comprehensive overview of various PTM databases, software tools, and analyze critical information available from these resources to study PTMs in various biological organisms.