Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA- and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry–based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, “How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?” We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype.

Our knowledge of proteins has greatly improved in recent years, driven by new technologies in the fields of molecular biology and proteome research. It has become clear that from a single gene not only one single gene product but many different ones - termed protein species - are generated, all of which may be associated with different functions. Nonetheless, an unambiguous nomenclature for describing individual protein species is still lacking. With the present paper we therefore propose a systematic nomenclature for the comprehensive description of protein species. The protein species nomenclature is flexible and adaptable to every level of knowledge and of experimental data in accordance with the exact chemical composition of individual protein species. As a minimum description the entry name (gene name + species according to the UniProt knowledgebase) can be used, if no analytical data about the target protein species are available.

Human pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal malignancies in the world and despite great efforts in research types of treatment remain limited. A frequently detected alteration in PDACs is a truncated O-linked N-acetylgalactosamine (GalNAc) glycosylation with expression of the Tn antigen. Changes in O-glycosylation affect posttranslationally modified O-GalNAc proteins resulting in profound cellular alterations. Tn antigen is a tumor associated glycan detected in 75-90 % of PDACs and up to 67 % in its precursor lesions. Since the role of Tn antigen expression in PDAC is insufficiently understood we analyzed the impact of COSMC mediated Tn antigen expression in two human PDAC cell lines on cellular oncogenic properties. Forced expression of Tn antigen on O-glycosylated proteins in pancreatic cancer cells was induced by lentiviral-mediated knockdown of the COSMC chaperone, which prevented O-glycan elongation beyond the initial GalNAcα1- residue on O-linked glycoproteins. Altered O-GalNAc glycosylation was analyzed in human pancreatic cancer cell lines Panc-1 and L3.6pl using Western and Far-Western blot as well as immunocytochemical techniques. To assess the biological implications of COSMC function on oncogenic properties, cell viability assays, scratch assays combined with live cell imaging, migration and apoptosis assays were performed. Lectin based glycoprotein enrichment with subsequent mass spectrometric analysis identified new cancer O-GalNAc modified proteins. Expression of Tn antigen bearing Nucleolin in patient derived PDAC tumor specimens was evaluated and correlated with clinicopathological data. Tn antigen expression was induced on various O-GalNAc glycoproteins in COSMC deficient cell lines compared to the control. Proliferation was reduced (p < 0.001) in COSMC knockdown cells, whereas migration was increased (p < 0.001) and apoptosis was decreased (p = 0.03), highlighting the importance of Tn antigen expression on metastatic and anti-apoptotic behavior of PDAC derived cells. Nucleolin was identified as O-GalNAc modified protein in COSMC deficient PDAC cell lines. Interestingly, immunohistochemical staining and co-localization studies of patient derived PDACs revealed poor survival for patients with strong co-localization of Tn antigen and Nucleolin (p = 0.037). This study substantiates the influence of altered O-glycan (Tn/STn) expression on oncogenic properties in pancreatic cancer and identifies O-GalNAc modified Nucleolin as novel prognostic marker.

Extracellular vesicles (EVs) are important means of intercellular communication and a potent tool for regenerative therapy. In ischaemic stroke, transient blockage of a brain artery leads to a lack of glucose and oxygen in the affected brain tissue, provoking neuronal death by necrosis in the core of the ischaemic region. The fate of neurons in the surrounding penumbra region depends on the stimuli, including EVs, received during the following hours. A detailed characterization of such stimuli is crucial not only for understanding stroke pathophysiology but also for new therapeutic interventions. In the present study, we characterize the EVs in mouse brain under physiological conditions and 24 h after induction of transient ischaemia in mice. We show that, in steady‐state conditions, microglia are the main source of small EVs (sEVs), whereas after ischaemia the main sEV population originates from astrocytes. Brain sEVs presented high amounts of the prion protein (PrP), which were further increased after stroke. Moreover, EVs were enriched in a proteolytically truncated PrP fragment (PrP‐C1). Because of similarities between PrP‐C1 and certain viral surface proteins, we studied the cellular uptake of brain‐derived sEVs from mice lacking (PrP‐KO) or expressing PrP (WT). We show that PrP‐KO‐sEVs are taken up significantly faster and more efficiently than WT‐EVs by primary neurons. Furthermore, microglia and astrocytes engulf PrP‐KO‐sEVs more readily than WT‐sEVs. Our results provide novel information on the relative contribution of brain cell types to the sEV pool in murine brain and indicate that increased release of sEVs by astrocytes together with elevated levels of PrP in sEVs may play a role in intercellular communication at early stages after stroke. In addition, amounts of PrP (and probably PrP‐C1) in brain sEVs seem to contribute to regulating their cellular uptake.

NAADP-evoked Ca²⁺ release through type 1 ryanodine receptors (RYR1) is a major mechanism underlying the earliest signals in T cell activation, which are the formation of Ca²⁺ microdomains. In our characterization of the molecular machinery underlying NAADP action, we identified an NAADP-binding protein, called hematological and neurological expressed 1–like protein (HN1L) [also known as Jupiter microtubule-associated homolog 2 (JPT2)]. Gene deletion of Hn1l/Jpt2 in human Jurkat and primary rat T cells resulted in decreased numbers of initial Ca²⁺ microdomains and delayed the onset and decreased the amplitude of global Ca²⁺ signaling. Photoaffinity labeling demonstrated direct binding of NAADP to recombinant HN1L/JPT2. T cell receptor/CD3–dependent coprecipitation of HN1L/JPT2 with RYRs and colocalization of these proteins suggest that HN1L/JPT2 connects NAADP formation with the activation of RYR channels within the first seconds of T cell activation. Thus, HN1L/JPT2 enables NAADP to activate Ca²⁺ release from the endoplasmic reticulum through RYR.

Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Proteome datasets display high technical variability and frequent missing values. Sophisticated strategies for batch effect reduction are lacking or rely on error-prone data imputation. Here we introduce HarmonizR, a data harmonization tool with appropriate missing value handling. The method exploits the structure of available data and matrix dissection for minimal data loss, without data imputation. This strategy implements two common batch effect reduction methods—ComBat and limma (removeBatchEffect()). The HarmonizR strategy, evaluated on four exemplarily analyzed datasets with up to 23 batches, demonstrated successful data harmonization for different tissue preservation techniques, LC-MS/MS instrumentation setups, and quantification approaches. Compared to data imputation methods, HarmonizR was more efficient and performed superior regarding the detection of significant proteins. HarmonizR is an efficient tool for missing data tolerant experimental variance reduction and is easily adjustable for individual dataset properties and user preferences.