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.

The Dynamic Regulatory Genome of Capsaspora and the Origin of Animal Multicellularity.

The unicellular ancestor of animals had a complex repertoire of genes linked to multicellular processes. This suggests that changes in the regulatory genome, rather than in gene innovation, were key to the origin of animals. Here, we carry out multiple functional genomic assays in Capsaspora owczarzaki, the unicellular relative of animals with the largest known gene repertoire for transcriptional regulation. We show that changing chromatin states, differential lincRNA expression, and dynamic cis-regulatory sites are associated with life cycle transitions in Capsaspora. Moreover, we demonstrate conservation of animal developmental transcription-factor networks and extensive network interconnection in this premetazoan organism. In contrast, however, Capsaspora lacks animal promoter types, and its regulatory sites are small, proximal, and lack signatures of animal enhancers. Overall, our results indicate that the emergence of animal multicellularity was linked to a major shift in genome cis-regulatory complexity, most notably the appearance of distal enhancer regulation.

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.

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.

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/.

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.

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.

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.

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.

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.

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.

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.

Protein-Based Classifier to Predict Conversion from Clinically Isolated Syndrome to Multiple Sclerosis.

Multiple sclerosis is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. In most patients, the disease initiates with an episode of neurological disturbance referred to as clinically isolated syndrome, but not all patients with this syndrome develop multiple sclerosis over time, and currently, there is no clinical test that can conclusively establish whether a patient with a clinically isolated syndrome will eventually develop clinically defined multiple sclerosis. Here, we took advantage of the capabilities of targeted mass spectrometry to establish a diagnostic molecular classifier with high sensitivity and specificity able to differentiate between clinically isolated syndrome patients with a high and a low risk of developing multiple sclerosis. Based on the combination of abundances of proteins chitinase 3-like 1 and ala-ß-his-dipeptidase in cerebrospinal fluid, we built a statistical model able to assign to each patient a precise probability of conversion to clinically defined multiple sclerosis. Our results are of special relevance for patients affected by multiple sclerosis as early treatment can prevent brain damage and slow down the disease progression.

Origins of De Novo Genes in Human and Chimpanzee.

The birth of new genes is an important motor of evolutionary innovation. Whereas many new genes arise by gene duplication, others originate at genomic regions that did not contain any genes or gene copies. Some of these newly expressed genes may acquire coding or non-coding functions and be preserved by natural selection. However, it is yet unclear which is the prevalence and underlying mechanisms of de novo gene emergence. In order to obtain a comprehensive view of this process, we have performed in-depth sequencing of the transcriptomes of four mammalian species--human, chimpanzee, macaque, and mouse--and subsequently compared the assembled transcripts and the corresponding syntenic genomic regions. This has resulted in the identification of over five thousand new multiexonic transcriptional events in human and/or chimpanzee that are not observed in the rest of species. Using comparative genomics, we show that the expression of these transcripts is associated with the gain of regulatory motifs upstream of the transcription start site (TSS) and of U1 snRNP sites downstream of the TSS. In general, these transcripts show little evidence of purifying selection, suggesting that many of them are not functional. However, we find signatures of selection in a subset of de novo genes which have evidence of protein translation. Taken together, the data support a model in which frequently-occurring new transcriptional events in the genome provide the raw material for the evolution of new proteins.

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.

Peptide Selection for Targeted Protein Quantitation.

Targeted proteomics methods in their different flavors rely on the use of a few peptides as proxies for protein quantitation, which need to be specified either prior to or after data acquisition. However, in contrast with discovery methods that use all identified peptides for a given protein to estimate its abundance, targeted proteomics methods are limited in the number of peptides that are used for protein quantitation. Because only a few peptides per protein are acquired or extracted in targeted experiments, the selection of peptides that are used for targeted protein quantitation becomes crucial. Several rules have been proposed to guide peptide selection for targeted proteomics studies, which have generally been based on the amino acidic composition of the peptide sequences. However, the compliance of these rules does not imply that not-conformed peptides are not reproducibly generated nor do they guarantee that the selected peptides correctly represent the behavior of the protein abundance under different conditions.

Modifications of fungal membrane proteins profile under pathogenicity induction: A proteomic analysis of Botrytis cinerea membranome.

Botrytis cinerea is a model fungus for the study of phytopathogenicity that exhibits a wide arsenal of tools to infect plant tissues. Most of these factors are related to signal transduction cascades, in which membrane proteins play a key role as a bridge between environment and intracellular molecular processes. This work describes the first description of the membranome of Botrytis under different pathogenicity conditions induced by different plant-based elicitors: glucose and tomato cell wall (TCW). A discovery proteomics analysis of membrane proteins was carried out by mass spectrometry. A total of 2794 proteins were successfully identified, 46% of them were classified as membrane proteins based on the presence of transmembrane regions and lipidation. Further analyses showed significant differences in the membranome composition depending on the available carbon source: 804 proteins were exclusively identified when the fungus was cultured with glucose as a sole carbon source, and 251 proteins were exclusively identified with TCW. Besides, among the 1737 common proteins, a subset of 898 proteins presented clear differences in their abundance. GO enrichment and clustering interaction analysis revealed changes in the composition of membranome with increase of signalling function in glucose conditions and carbohydrate degradation process in TCW conditions. All MS data have been deposited in the ProteomeXchange with identifier PXD003099 (http://proteomecentral.proteomexchange.org/dataset/PXD003099).

Profiling the secretome and extracellular proteome of the potato late blight pathogen Phytophthora infestans.

Oomycetes are filamentous organisms that cause notorious diseases, several of which have a high economic impact. Well known is Phytophthora infestans, the causal agent of potato late blight. Previously, in silico analyses of the genome and transcriptome of P. infestans resulted in the annotation of a large number of genes encoding proteins with an N-terminal signal peptide. This set is collectively referred to as the secretome and comprises proteins involved in, for example, cell wall growth and modification, proteolytic processes, and the promotion of successful invasion of plant cells. So far, proteomic profiling in oomycetes was primarily focused on subcellular, intracellular or cell wall fractions; the extracellular proteome has not been studied systematically. Here we present the first comprehensive characterization of the in vivo secretome and extracellular proteome of P. infestans. We have used mass spectrometry to analyze P. infestans proteins present in seven different growth media with mycelial cultures and this resulted in the consistent identification of over two hundred proteins. Gene ontology classification pinpointed proteins involved in cell wall modifications, pathogenesis, defense responses, and proteolytic processes. Moreover, we found members of the RXLR and CRN effector families as well as several proteins lacking an obvious signal peptide. The latter were confirmed to be bona fide extracellular proteins and this suggests that, similar to other organisms, oomycetes exploit non-conventional secretion mechanisms to transfer certain proteins to the extracellular environment.

Identification of N-terminal protein acetylation and arginine methylation of the voltage-gated sodium channel in end-stage heart failure human heart.

The α subunit of the cardiac voltage-gated sodium channel, NaV1.5, provides the rapid sodium inward current that initiates cardiomyocyte action potentials. Here, we analyzed for the first time the post-translational modifications of NaV1.5 purified from end-stage heart failure human cardiac tissue. We identified R526 methylation as the major post-translational modification of any NaV1.5 arginine or lysine residue. Unexpectedly, we found that the N terminus of NaV1.5 was: 1) devoid of the initiation methionine, and 2) acetylated at the resulting initial alanine residue. This is the first evidence for N-terminal acetylation in any member of the voltage-gated ion channel superfamily. Our results open the door to explore NaV1.5 N-terminal acetylation and arginine methylation levels as drivers or markers of end-stage heart failure.