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Quantitative phosphoproteomics has transformed investigations of cell signaling, but it remains challenging to scale the technology for high-throughput analyses. Here we report a rapid and reproducible approach to analyze hundreds of phosphoproteomes using data-independent acquisition (DIA) with an accurate site localization score incorporated into Spectronaut. DIA-based phosphoproteomics achieves an order of magnitude broader dynamic range, higher reproducibility of identification, and improved sensitivity and accuracy of quantification compared to state-of-the-art data-dependent acquisition (DDA)-based phosphoproteomics. Notably, direct DIA without the need of spectral libraries performs close to analyses using project-specific libraries, quantifying > 20,000 phosphopeptides in 15 min single-shot LC-MS analysis per condition. Adaptation of a 3D multiple regression model-based algorithm enables global determination of phosphorylation site stoichiometry in DIA. Scalability of the DIA approach is demonstrated by systematically analyzing the effects of thirty kinase inhibitors in context of epidermal growth factor (EGF) signaling showing that specific protein kinases mediate EGF-dependent phospho-regulation. Localizing phosphorylation sites by data-independent acquisition (DIA)-based proteomics is still challenging. Here, the authors develop algorithms for phosphosite localization and stoichiometry determination, and incorporate them into single-shot DIA-phosphoproteomics workflows.

Comprehensive mass spectrometry (MS)-based proteomics is now feasible, but reproducible quantification remains challenging, especially for post-translational modifications such as phosphorylation. Here, we compare the most popular quantification techniques for global phosphoproteomics: label-free quantification (LFQ), stable isotope labeling by amino acids in cell culture (SILAC) and MS 2 - and MS 3 -measured tandem mass tags (TMT). In a mixed species comparison with fixed phosphopeptide ratios, we find LFQ and SILAC to be the most accurate techniques. MS 2 -based TMT yields the highest precision but lowest accuracy due to ratio compression, which MS 3 -based TMT can partly rescue. However, MS 2 -based TMT outperforms MS 3 -based TMT when analyzing phosphoproteome changes in the DNA damage response, since its higher precision and larger identification numbers allow detection of a greater number of significantly regulated phosphopeptides. Finally, we utilize the TMT multiplexing capabilities to develop an algorithm for determining phosphorylation site stoichiometry, showing that such applications benefit from the high accuracy of MS 3 -based TMT. Quantitative phosphoproteomics has become a standard method in molecular and cell biology. Here, the authors compare performance and parameters of phosphoproteome quantification by LFQ, SILAC, and MS 2 -/MS 3 -based TMT and introduce a TMT-adapted algorithm for calculating phosphorylation site stoichiometry.

Ubiquitination is a post-translational modification (PTM) that is essential for balancing numerous physiological processes. To enable delineation of protein ubiquitination at a site-specific level, we generated an antibody, denoted UbiSite, recognizing the C-terminal 13 amino acids of ubiquitin, which remain attached to modified peptides after proteolytic digestion with the endoproteinase LysC. Notably, UbiSite is specific to ubiquitin. Furthermore, besides ubiquitination on lysine residues, protein N-terminal ubiquitination is readily detected as well. By combining UbiSite enrichment with sequential LysC and trypsin digestion and high-accuracy MS, we identified over 63,000 unique ubiquitination sites on 9,200 proteins in two human cell lines. In addition to uncovering widespread involvement of this PTM in all cellular aspects, the analyses reveal an inverse association between protein N-terminal ubiquitination and acetylation, as well as a complete lack of correlation between changes in protein abundance and alterations in ubiquitination sites upon proteasome inhibition.

The composition of ancient oral microbiomes has recently become accessible owing to advanced biomolecular methods such as metagenomics and metaproteomics, but the utility of metaproteomics for such analyses is less explored. Here, we use quantitative metaproteomics to characterize the dental calculus associated with the remains of 21 humans retrieved during the archeological excavation of the medieval (ca. 1100–1450 CE) cemetery of Tjærby, Denmark. We identify 3671 protein groups, covering 220 bacterial species and 81 genera across all medieval samples. The metaproteome profiles of bacterial and human proteins suggest two distinct groups of archeological remains corresponding to health-predisposed and oral disease-susceptible individuals, which is supported by comparison to the calculus metaproteomes of healthy living individuals. Notably, the groupings identified by metaproteomics are not apparent from the bioarchaeological analysis, illustrating that quantitative metaproteomics has the potential to provide additional levels of molecular information about the oral health status of individuals from archeological contexts. Mineralized plaque, or dental calculus, is a valuable reservoir of the ancient oral microbiome. Here, the authors use quantitative metaproteomics to analyze the dental calculus of 21 individuals from a medieval cemetery, identifying human and microbial proteins that shed light on their oral health status.

Large-scale mass spectrometry-based peptidomics for drug discovery is relatively unexplored because of challenges in peptide degradation and identification following tissue extraction. Here we present a streamlined analytical pipeline for large-scale peptidomics. We developed an optimized sample preparation protocol to achieve fast, reproducible and effective extraction of endogenous peptides from sub-dissected organs such as the brain, while diminishing unspecific protease activity. Each peptidome sample was analysed by high-resolution tandem mass spectrometry and the resulting data set was integrated with publically available databases. We developed and applied an algorithm that reduces the peptide complexity for identification of biologically relevant peptides. The developed pipeline was applied to rat hypothalamus and identifies thousands of neuropeptides and their post-translational modifications, which is combined in a resource format for visualization, qualitative and quantitative analyses. Neuropeptide research is challenged by technical difficulties in identifying new bioactive peptides. Here the authors present an analytical pipeline for large-scale peptidomics applied to the rat hypothalamus, identifying thousands of endogenous neuropeptides and their post-translational modifications.

Peptides play important roles in regulating biological processes and form the basis of a multiplicity of therapeutic drugs. To date, only about 300 peptides in human have confirmed bioactivity, although tens of thousands have been reported in the literature. The majority of these are inactive degradation products of endogenous proteins and peptides, presenting a needle-in-a-haystack problem of identifying the most promising candidate peptides from large-scale peptidomics experiments to test for bioactivity. To address this challenge, we conducted a comprehensive analysis of the mammalian peptidome across seven tissues in four different mouse strains and used the data to train a machine learning model that predicts hundreds of peptide candidates based on patterns in the mass spectrometry data. We provide in silico validation examples and experimental confirmation of bioactivity for two peptides, demonstrating the utility of this resource for discovering lead peptides for further characterization and therapeutic development. Bioactive peptides regulate many physiological functions but progress in discovering them has been slow. Here, the authors use a machine learning framework to predict mammalian peptide candidates from the global and local structure of large-scale tissue-specific mass spectrometry data.

Denmark has an extraordinarily large and well-preserved collection of archaeological skin garments found in peat bogs, dated to approximately 920 BC - AD 775. These objects provide not only the possibility to study prehistoric skin costume and technologies, but also to investigate the animal species used for the production of skin garments. Until recently, species identification of archaeological skin was primarily performed by light and scanning electron microscopy or the analysis of ancient DNA. However, the efficacy of these methods can be limited due to the harsh, mostly acidic environment of peat bogs leading to morphological and molecular degradation within the samples. We compared species assignment results of twelve archaeological skin samples from Danish bogs using Mass Spectrometry (MS)-based peptide sequencing, against results obtained using light and scanning electron microscopy. While it was difficult to obtain reliable results using microscopy, MS enabled the identification of several species-diagnostic peptides, mostly from collagen and keratins, allowing confident species discrimination even among taxonomically close organisms, such as sheep and goat. Unlike previous MS-based methods, mostly relying on peptide fingerprinting, the shotgun sequencing approach we describe aims to identify the complete extracted ancient proteome, without preselected specific targets. As an example, we report the identification, in one of the samples, of two peptides uniquely assigned to bovine foetal haemoglobin, indicating the production of skin from a calf slaughtered within the first months of its life. We conclude that MS-based peptide sequencing is a reliable method for species identification of samples from bogs. The mass spectrometry proteomics data were deposited in the ProteomeXchange Consortium with the dataset identifier PXD001029.

During mitosis large alterations in cellular structures occur rapidly, which to a large extent is regulated by post-translational modification of proteins. Modification of proteins with the small ubiquitin-related protein SUMO2/3 regulates mitotic progression, but few mitotic targets have been identified so far. To deepen our understanding of SUMO2/3 during this window of the cell cycle, we undertook a comprehensive proteomic characterization of SUMO2/3 modified proteins in mitosis and upon mitotic exit. We developed an efficient tandem affinity purification strategy of SUMO2/3 modified proteins from mitotic cells. Combining this purification strategy with cell synchronization procedures and quantitative mass spectrometry allowed for the mapping of numerous novel targets and their dynamics as cells progressed out of mitosis. This identified RhoGDIα as a major SUMO2/3 modified protein, specifically during mitosis, mediated by the SUMO ligases PIAS2 and PIAS3. Our data provide a rich resource for further exploring the role of SUMO2/3 modifications in mitosis and cell cycle regulation.

Christina Warinner and colleagues report a high-resolution characterization of the oral microbiome isolated from the dental tissues of adult skeletons dating to 1100 CE and showing evidence of periodontal disease. They show the long-term carriage of a diverse range of opportunistic pathogens in the oral cavity and reconstruct the genome of the periodontal pathogen Tannerella forsythia . Calcified dental plaque (dental calculus) preserves for millennia and entraps biomolecules from all domains of life and viruses. We report the first, to our knowledge, high-resolution taxonomic and protein functional characterization of the ancient oral microbiome and demonstrate that the oral cavity has long served as a reservoir for bacteria implicated in both local and systemic disease. We characterize (i) the ancient oral microbiome in a diseased state, (ii) 40 opportunistic pathogens, (iii) ancient human–associated putative antibiotic resistance genes, (iv) a genome reconstruction of the periodontal pathogen Tannerella forsythia , (v) 239 bacterial and 43 human proteins, allowing confirmation of a long-term association between host immune factors, 'red complex' pathogens and periodontal disease, and (vi) DNA sequences matching dietary sources. Directly datable and nearly ubiquitous, dental calculus permits the simultaneous investigation of pathogen activity, host immunity and diet, thereby extending direct investigation of common diseases into the human evolutionary past.

Protein sequences preserved in two Quaternary taxa, Macrauchenia and Toxodon , resolve the evolutionary history of South American native ungulates. South American ungulates demystified When Charles Darwin first unearthed the remains of the South American native ungulates — herbivorous mammals that evolved in isolation on the South American continent for tens of millions of years — he declared them “the strangest animals ever discovered”. Their origins are obscured by rampant convergence of morphology, and work with ancient DNA has been similarly frustrating. Ian Barnes and colleagues have circumvented these problems by screening protein sequences preserved in two Quaternary taxa, Macrauchenia and Toxodon , to show that their closest relatives among other mammals are the Perissodactyls (odd-toed ungulates such as horses and rhinos) rather than among the Afrotheres (elephants, sirenians and allies). No large group of recently extinct placental mammals remains as evolutionarily cryptic as the approximately 280 genera grouped as ‘South American native ungulates’. To Charles Darwin 1 , 2 , who first collected their remains, they included perhaps the ‘strangest animal[s] ever discovered’. Today, much like 180 years ago, it is no clearer whether they had one origin or several, arose before or after the Cretaceous/Palaeogene transition 66.2 million years ago 3 , or are more likely to belong with the elephants and sirenians of superorder Afrotheria than with the euungulates (cattle, horses, and allies) of superorder Laurasiatheria 4 , 5 , 6 . Morphology-based analyses have proved unconvincing because convergences are pervasive among unrelated ungulate-like placentals. Approaches using ancient DNA have also been unsuccessful, probably because of rapid DNA degradation in semitropical and temperate deposits. Here we apply proteomic analysis to screen bone samples of the Late Quaternary South American native ungulate taxa Toxodon (Notoungulata) and Macrauchenia (Litopterna) for phylogenetically informative protein sequences. For each ungulate, we obtain approximately 90% direct sequence coverage of type I collagen α1- and α2-chains, representing approximately 900 of 1,140 amino-acid residues for each subunit. A phylogeny is estimated from an alignment of these fossil sequences with collagen (I) gene transcripts from available mammalian genomes or mass spectrometrically derived sequence data obtained for this study. The resulting consensus tree agrees well with recent higher-level mammalian phylogenies 7 , 8 , 9 . Toxodon and Macrauchenia form a monophyletic group whose sister taxon is not Afrotheria or any of its constituent clades as recently claimed 5 , 6 , but instead crown Perissodactyla (horses, tapirs, and rhinoceroses). These results are consistent with the origin of at least some South American native ungulates 4 , 6 from ‘condylarths’, a paraphyletic assembly of archaic placentals. With ongoing improvements in instrumentation and analytical procedures, proteomics may produce a revolution in systematics such as that achieved by genomics, but with the possibility of reaching much further back in time.