Assessment and Prediction of Human Proteotypic Peptide Stability for Proteomics Quantification.

Mass spectrometry coupled to liquid chromatography is one of the most powerful technologies for proteome quantification in biomedical samples. In peptide-centric workflows, protein mixtures are enzymatically digested to peptides prior their analysis. However, proteome-wide quantification studies rarely identify all potential peptides for any given protein, and targeted proteomics experiments focus on a set of peptides for the proteins of interest. Consequently, proteomics relies on the use of a limited subset of all possible peptides as proxies for protein quantitation. In this work, we evaluated the stability of the human proteotypic peptides during 21 days and trained a deep learning model to predict peptide stability directly from tryptic sequences, which together constitute a resource of broad interest to prioritize and select peptides in proteome quantification experiments.

Stepwise emergence of the neuronal gene expression program in early animal evolution.

The assembly of the neuronal and other major cell type programs occurred early in animal evolution. We can reconstruct this process by studying non-bilaterians like placozoans. These small disc-shaped animals not only have nine morphologically described cell types and no neurons but also show coordinated behaviors triggered by peptide-secreting cells. We investigated possible neuronal affinities of these peptidergic cells using phylogenetics, chromatin profiling, and comparative single-cell genomics in four placozoans. We found conserved cell type expression programs across placozoans, including populations of transdifferentiating and cycling cells, suggestive of active cell type homeostasis. We also uncovered fourteen peptidergic cell types expressing neuronal-associated components like the pre-synaptic scaffold that derive from progenitor cells with neurogenesis signatures. In contrast, earlier-branching animals like sponges and ctenophores lacked this conserved expression. Our findings indicate that key neuronal developmental and effector gene modules evolved before the advent of cnidarian/bilaterian neurons in the context of paracrine cell signaling.

Updated MS²PIP web server supports cutting-edge proteomics applications.

Interest in the use of machine learning for peptide fragmentation spectrum prediction has been strongly on the rise over the past years, especially for applications in challenging proteomics identification workflows such as immunopeptidomics and the full-proteome identification of data independent acquisition spectra. Since its inception, the MS²PIP peptide spectrum predictor has been widely used for various downstream applications, mostly thanks to its accuracy, ease-of-use, and broad applicability. We here present a thoroughly updated version of the MS²PIP web server, which includes new and more performant prediction models for both tryptic- and non-tryptic peptides, for immunopeptides, and for CID-fragmented TMT-labeled peptides. Additionally, we have also added new functionality to greatly facilitate the generation of proteome-wide predicted spectral libraries, requiring only a FASTA protein file as input. These libraries also include retention time predictions from DeepLC. Moreover, we now provide pre-built and ready-to-download spectral libraries for various model organisms in multiple DIA-compatible spectral library formats. Besides upgrading the back-end models, the user experience on the MS²PIP web server is thus also greatly enhanced, extending its applicability to new domains, including immunopeptidomics and MS3-based TMT quantification experiments. MS²PIP is freely available at https://iomics.ugent.be/ms2pip/.

Transcriptome innovations in primates revealed by single-molecule long-read sequencing.

Transcriptomic diversity greatly contributes to the fundamentals of disease, lineage-specific biology, and environmental adaptation. However, much of the actual isoform repertoire contributing to shaping primate evolution remains unknown. Here, we combined deep long- and short-read sequencing complemented with mass spectrometry proteomics in a panel of lymphoblastoid cell lines (LCLs) from human, three other great apes, and rhesus macaque, producing the largest full-length isoform catalog in primates to date. Around half of the captured isoforms are not annotated in their reference genomes, significantly expanding the gene models in primates. Furthermore, our comparative analyses unveil hundreds of transcriptomic innovations and isoform usage changes related to immune function and immunological disorders. The confluence of these evolutionary innovations with signals of positive selection and their limited impact in the proteome points to changes in alternative splicing in genes involved in immune response as an important target of recent regulatory divergence in primates.

A phylogenetic and proteomic reconstruction of eukaryotic chromatin evolution.

Histones and associated chromatin proteins have essential functions in eukaryotic genome organization and regulation. Despite this fundamental role in eukaryotic cell biology, we lack a phylogenetically comprehensive understanding of chromatin evolution. Here, we combine comparative proteomics and genomics analysis of chromatin in eukaryotes and archaea. Proteomics uncovers the existence of histone post-translational modifications in archaea. However, archaeal histone modifications are scarce, in contrast with the highly conserved and abundant marks we identify across eukaryotes. Phylogenetic analysis reveals that chromatin-associated catalytic functions (for example, methyltransferases) have pre-eukaryotic origins, whereas histone mark readers and chaperones are eukaryotic innovations. We show that further chromatin evolution is characterized by expansion of readers, including capture by transposable elements and viruses. Overall, our study infers detailed evolutionary history of eukaryotic chromatin: from its archaeal roots, through the emergence of nucleosome-based regulation in the eukaryotic ancestor, to the diversification of chromatin regulators and their hijacking by genomic parasites.

Molecular characterization of triple negative breast cancer formaldehyde-fixed paraffin-embedded samples by data-independent acquisition proteomics.

Triple negative breast cancer accounts for 15%-20% of all breast carcinomas and is clinically characterized by an aggressive phenotype and poor prognosis. Triple negative tumors do not benefit from targeted therapies, so further characterization is needed to define subgroups with potential therapeutic value. In this work, the proteomes of 125 formalin-fixed paraffin-embedded samples from patients diagnosed with non-metastatic triple negative breast cancer were analyzed using data-independent acquisition + in a LTQ-Orbitrap Fusion Lumos mass spectrometer coupled to an EASY-nLC 1000. 1206 proteins were identified in at least 66% of the samples. Hierarchical clustering, probabilistic graphical models and Significance Analysis of Microarrays were combined to characterize proteomics-based molecular groups. Two molecular groups were defined with differences in biological processes such as glycolysis, translation and immune response. These two molecular groups showed also several differentially expressed proteins. This clinically homogenous dataset may serve to design new therapeutic strategies in the future.

Multi-laboratory experiment PME11 for the standardization of phosphoproteome analysis.

Global analysis of protein phosphorylation by mass spectrometry proteomic techniques has emerged in the last decades as a powerful tool in biological and biomedical research. However, there are several factors that make the global study of the phosphoproteome more challenging than measuring non-modified proteins. The low stoichiometry of the phosphorylated species and the need to retrieve residue specific information require particular attention on sample preparation, data acquisition and processing to ensure reproducibility, qualitative and quantitative robustness and ample phosphoproteome coverage in phosphoproteomic workflows. Aiming to investigate the effect of different variables in the performance of proteome wide phosphoprotein analysis protocols, ProteoRed-ISCIII and EuPA launched the Proteomics Multicentric Experiment 11 (PME11). A reference sample consisting of a yeast protein extract spiked in with different amounts of a phosphomix standard (Sigma/Merck) was distributed to 31 laboratories around the globe. Thirty-six datasets from 23 laboratories were analyzed. Our results indicate the suitability of the PME11 reference sample to benchmark and optimize phosphoproteomics strategies, weighing the influence of different factors, as well as to rank intra and inter laboratory performance.

Quality standards in proteomics research facilities: Common standards and quality procedures are essential for proteomics facilities and their users.

Proteomics research infrastructures and core facilities within the Core for Life alliance advocate for community policies for quality control to ensure high standards in proteomics services.

QCloud2: An Improved Cloud-based Quality-Control System for Mass-Spectrometry-based Proteomics Laboratories.

QCloud is a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, and automated data processing. Since its release, QCloud has facilitated automated quality control for proteomics experiments in many laboratories. QCloud provides a quick and effortless evaluation of instrument performance that helps to overcome many analytical challenges derived from clinical and translational research. Here we present an improved version of the system, QCloud2. This new version includes enhancements in the scalability and reproducibility of the quality-control pipelines, and it features an improved front end for data visualization, user management, and chart annotation. The QCloud2 system also includes programmatic access and a standalone local version.

MassIVE.quant: a community resource of quantitative mass spectrometry-based proteomics datasets.

MassIVE.quant is a repository infrastructure and data resource for reproducible quantitative mass spectrometry-based proteomics, which is compatible with all mass spectrometry data acquisition types and computational analysis tools. A branch structure enables MassIVE.quant to systematically store raw experimental data, metadata of the experimental design, scripts of the quantitative analysis workflow, intermediate input and output files, as well as alternative reanalyses of the same dataset.

Author Correction: The dental proteome of Homo antecessor.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The dental proteome of Homo antecessor.

The phylogenetic relationships between hominins of the Early Pleistocene epoch in Eurasia, such as Homo antecessor, and hominins that appear later in the fossil record during the Middle Pleistocene epoch, such as Homo sapiens, are highly debated1-5. For the oldest remains, the molecular study of these relationships is hindered by the degradation of ancient DNA. However, recent research has demonstrated that the analysis of ancient proteins can address this challenge6-8. Here we present the dental enamel proteomes of H. antecessor from Atapuerca (Spain)9,10 and Homo erectus from Dmanisi (Georgia)1, two key fossil assemblages that have a central role in models of Pleistocene hominin morphology, dispersal and divergence. We provide evidence that H. antecessor is a close sister lineage to subsequent Middle and Late Pleistocene hominins, including modern humans, Neanderthals and Denisovans. This placement implies that the modern-like face of H. antecessor-that is, similar to that of modern humans-may have a considerably deep ancestry in the genus Homo, and that the cranial morphology of Neanderthals represents a derived form. By recovering AMELY-specific peptide sequences, we also conclude that the H. antecessor molar fragment from Atapuerca that we analysed belonged to a male individual. Finally, these H. antecessor and H. erectus fossils preserve evidence of enamel proteome phosphorylation and proteolytic digestion that occurred in vivo during tooth formation. Our results provide important insights into the evolutionary relationships between H. antecessor and other hominin groups, and pave the way for future studies using enamel proteomes to investigate hominin biology across the existence of the genus Homo.

Proteomic study of the membrane components of signalling cascades of Botrytis cinerea controlled by phosphorylation.

Protein phosphorylation and membrane proteins play an important role in the infection of plants by phytopathogenic fungi, given their involvement in signal transduction cascades. Botrytis cinerea is a well-studied necrotrophic fungus taken as a model organism in fungal plant pathology, given its broad host range and adverse economic impact. To elucidate relevant events during infection, several proteomics analyses have been performed in B. cinerea, but they cover only 10% of the total proteins predicted in the genome database of this fungus. To increase coverage, we analysed by LC-MS/MS the first-reported overlapped proteome in phytopathogenic fungi, the "phosphomembranome" of B. cinerea, combining the two most important signal transduction subproteomes. Of the 1112 membrane-associated phosphoproteins identified, 64 and 243 were classified as exclusively identified or overexpressed under glucose and deproteinized tomato cell wall conditions, respectively. Seven proteins were found under both conditions, but these presented a specific phosphorylation pattern, so they were considered as exclusively identified or overexpressed proteins. From bioinformatics analysis, those differences in the membrane-associated phosphoproteins composition were associated with various processes, including pyruvate metabolism, unfolded protein response, oxidative stress response, autophagy and cell death. Our results suggest these proteins play a significant role in the B. cinerea pathogenic cycle.

Molecular basis for the protective effects of low-density lipoprotein receptor-related protein 1 (LRP1)-derived peptides against LDL aggregation.

Aggregated LDL is the first ligand reported to interact with the cluster II CR9 domain of low-density lipoprotein receptor-related protein 1 (LRP1). In particular, the C-terminal half of domain CR9, comprising the region Gly1127-Cys1140 exclusively recognizes aggregated LDL and it is crucial for aggregated LDL binding. Our aim was to study the effect of the sequence Gly1127-Cys1140 (named peptide LP3 and its retro-enantio version, named peptide DP3) on the structural characteristics of sphingomyelinase- (SMase) and phospholipase 2 (PLA2)-modified LDL particles. Turbidimetry, gel filtration chromatography (GFC) and transmission electronic microscopy (TEM) analysis showed that LP3 and DP3 peptides strongly inhibited SMase- and PLA2-induced LDL aggregation. Nondenaturing polyacrylamide gradient gel electrophoresis (GGE), agarose gel electrophoresis and high-performance thin-layer chromatography (HPTLC) indicated that LP3 and DP3 prevented SMase-induced alterations in LDL particle size, electric charge and phospholipid content, respectively, but not those induced by PLA2. Western blot analysis showed that LP3 and DP3 counteracted changes in ApoB-100 conformation induced by the two enzymes. LDL proteomics (LDL trypsin digestion followed by mass spectroscopy) and computational modeling methods evidenced that peptides preserve ApoB-100 conformation due to their electrostatic interactions with a basic region of ApoB-100. These results demonstrate that LRP1-derived peptides are protective against LDL aggregation, even in conditions of extreme lipolysis, through their capacity to bind to ApoB-100 regions critical for ApoB-100 conformational preservation. These results suggests that these LRP1(CR9) derived peptides could be promising tools to prevent LDL aggregation induced by the main proteolytic enzymes acting in the arterial intima.

Isotopologue Multipoint Calibration for Proteomics Biomarker Quantification in Clinical Practice.

Targeted proteomics has become the method of choice for biomarker validation in human biopsies due to its high sensitivity, reproducibility, accuracy, and precision. However, for targeted proteomics to be transferred to clinical routine there is the need to reduce its complexity, make its procedures simpler, increase its throughput, and improve its analytical performance. Here we present the Isotopologue Multipoint Calibration (ImCal) quantification strategy, which uses a mix of isotopologue peptides to generate internal multipoint calibration curves for each individual sample and to accurately quantify biomarker peptides in clinical applications without the need of expert supervision. ImCal relies on the use of five different isotopically-labelled peptides of different nominal mass mixed at different concentrations to be used as an internal calibration curve for each endogenous peptide. The use of internal multipoint calibration curves is well-suited for the generation of ready-to-use biomarker kits for clinical applications as it is compatible with both high- and low-resolution mass spectrometers and different levels of endogenous peptide, it eliminates the need for blank matrixes required in external curves, it allows the evaluation of matrix effects and the valid quantification range in each individual sample, and it does not require expert adjustment. We used the ImCal method to quantify HER2 in 35 breast cancer formalin-fixed paraffin-embedded patient samples, revealing a high degree of heterogeneity among patients, which contrasts with the homogeneous immunohistochemistry patient classification. Our work illustrates how an improvement of mass spectrometry methods for biomarker quantification can provide fine-grain patient stratification, and thus better disease diagnostic and prognosis.

Proteomics characterisation of central nervous system metastasis biomarkers in triple negative breast cancer.

BACKGROUND: Breast cancer (BC) is the most frequent tumour in women. Triple negative tumours (TNBC)-which are associated with minor survival rates-lack markers predictive of response to anticancer drugs. Triple negative tumours frequently metastasise to the central nervous system (CNS). OBJECTIVE: The main objective of this study was to study differences in tumour protein expression between patients with CNS metastases and those without this kind of spread, and propose new biomarkers. METHODS: A retrospective study was performed. Targeted proteomics and statistical analyses were used to identify possible biomarkers. RESULTS: Proteins were quantified by a targeted proteomics approach and protein expression data were successfully obtained from 51 triple negative formalin-fixed paraffin-embedded samples. ISG15, THBS1 and AP1M1 were identified as possible biomarkers related with CNS metastasis development. CONCLUSIONS: Three possible biomarkers associated with CNS metastases in TNBC tumours were identified: ISG15, THBS1 and AP1M1. They may become markers predicting the appearance of CNS infiltration in triple negative BC.

Changes in Synaptic Proteins Precede Neurodegeneration Markers in Preclinical Alzheimer's Disease Cerebrospinal Fluid.

A biomarker of synapse loss, an early event in Alzheimer's disease (AD) pathophysiology that precedes neuronal death and symptom onset, would be a much-needed prognostic biomarker. With direct access to the brain interstitial fluid, the cerebrospinal fluid (CSF) is a potential source of synapse-derived proteins. In this study, we aimed to identify and validate novel CSF biomarkers of synapse loss in AD. Discovery: Combining shotgun proteomics of the CSF with an exhaustive search of the literature and public databases, we identified 251 synaptic proteins, from which we selected 22 for further study. Verification: Twelve proteins were discarded because of poor detection by Selected Reaction Monitoring (SRM). We confirmed the specific expression of 9 of the remaining proteins (Calsynytenin-1, GluR2, GluR4, Neurexin-2A, Neurexin-3A, Neuroligin-2, Syntaxin-1B, Thy-1, Vamp-2) at the human synapse using Array Tomography microscopy and biochemical fractionation methods. Exploration: Using SRM, we monitored these 9 synaptic proteins (20 peptides) in a cohort of CSF from cognitively normal controls and subjects in the pre-clinical and clinical AD stages (n = 80). Compared with controls, peptides from 8 proteins were elevated 1.3 to 1.6-fold (p < 0.04) in prodromal AD patients. Validation: Elevated levels of a GluR4 peptide at the prodromal stage were replicated (1.3-fold, p = 0.04) in an independent cohort (n = 60). Moreover, 7 proteins were reduced at preclinical stage 1 (0.6 to 0.8-fold, p < 0.04), a finding that was replicated (0.7 to 0.8-fold, p < 0.05) for 6 proteins in a third cohort (n = 38). In a cross-cohort meta-analysis, 6 synaptic proteins (Calsyntenin-1, GluR4, Neurexin-2A, Neurexin-3A, Syntaxin-1B and Thy-1) were reduced 0.8-fold (p < 0.05) in preclinical AD, changes that precede clinical symptoms and CSF markers of neurodegeneration. Therefore, these proteins could have clinical value for assessing disease progression, especially in preclinical stages of AD.

QCloud: A cloud-based quality control system for mass spectrometry-based proteomics laboratories.

The increasing number of biomedical and translational applications in mass spectrometry-based proteomics poses new analytical challenges and raises the need for automated quality control systems. Despite previous efforts to set standard file formats, data processing workflows and key evaluation parameters for quality control, automated quality control systems are not yet widespread among proteomics laboratories, which limits the acquisition of high-quality results, inter-laboratory comparisons and the assessment of variability of instrumental platforms. Here we present QCloud, a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, automated data processing and archiving, and unbiased instrument evaluation. QCloud supports the most common targeted and untargeted proteomics workflows, it accepts data formats from different vendors and it enables the annotation of acquired data and reporting incidences. A complete version of the QCloud system has successfully been developed and it is now open to the proteomics community (http://qcloud.crg.eu). QCloud system is an open source project, publicly available under a Creative Commons License Attribution-ShareAlike 4.0.

Prediction of adjuvant chemotherapy response in triple negative breast cancer with discovery and targeted proteomics.

BACKGROUND: Triple-negative breast cancer (TNBC) accounts for 15-20% of all breast cancers and usually requires the administration of adjuvant chemotherapy after surgery but even with this treatment many patients still suffer from a relapse. The main objective of this study was to identify proteomics-based biomarkers that predict the response to standard adjuvant chemotherapy, so that patients at are not going to benefit from it can be offered therapeutic alternatives. METHODS: We analyzed the proteome of a retrospective series of formalin-fixed, paraffin-embedded TNBC tissue applying high-throughput label-free quantitative proteomics. We identified several protein signatures with predictive value, which were validated with quantitative targeted proteomics in an independent cohort of patients and further evaluated in publicly available transcriptomics data. RESULTS: Using univariate Cox analysis, a panel of 18 proteins was significantly associated with distant metastasis-free survival of patients (p<0.01). A reduced 5-protein profile with prognostic value was identified and its prediction performance was assessed in an independent targeted proteomics experiment and a publicly available transcriptomics dataset. Predictor P5 including peptides from proteins RAC2, RAB6A, BIEA and IPYR was the best performance protein combination in predicting relapse after adjuvant chemotherapy in TNBC patients. CONCLUSIONS: This study identified a protein combination signature that complements histopathological prognostic factors in TNBC treated with adjuvant chemotherapy. The protein signature can be used in paraffin-embedded samples, and after a prospective validation in independent series, it could be used as predictive clinical test in order to recommend participation in clinical trials or a more exhaustive follow-up.

Evaluation of different peptide fragmentation types and mass analyzers in data-dependent methods using an Orbitrap Fusion Lumos Tribrid mass spectrometer.

One of the major additions in MS technology has been the irruption of the Orbitrap mass analyzer, which has boosted the proteomics analyses of biological complex samples since its introduction. Here, we took advantage of the capabilities of the new Orbitrap Fusion Lumos Tribrid mass spectrometer to assess the performance of different data-dependent acquisition methods for the identification and quantitation of peptides and phosphopeptides in single-shot analysis of human whole cell lysates. Our study explored the capabilities of tri-hibrid mass spectrometers for (phospho-) peptide identification and quantitation using different gradient lengths, sample amounts, and combinations of different peptide fragmentation types and mass analyzers. Moreover, the acquisition of the same complex sample with different acquisition methods resulted in the generation of a dataset to be used as a reference for further analyses, and a starting point for future optimizations in particular applications.