Regulatory effects of post-translational modifications on zDHHC S-acyltransferases

The human zDHHC S-acyltransferase family comprises 23 enzymes that mediate the S-acylation of a multitude of cellular proteins, including channels, receptors, transporters, signaling molecules, scaffolds, and chaperones. This reversible post-transitional modification (PTM) involves the attachment of a fatty acyl chain, usually derived from palmitoyl-CoA, to specific cysteine residues on target proteins, which affects their stability, localization, and function. These outcomes are essential to control many processes, including synaptic transmission and plasticity, cell growth and differentiation, and infectivity of viruses and other pathogens. Given the physiological importance of S-acylation, it is unsurprising that perturbations in this process, including mutations in ZDHHC genes, have been linked to different neurological pathologies and cancers, and there is growing interest in zDHHC enzymes as novel drug targets. Although zDHHC enzymes control a diverse array of cellular processes and are associated with major disorders, our understanding of these enzymes is surprisingly incomplete, particularly with regard to the regulatory mechanisms controlling these enzymes. However, there is growing evidence highlighting the role of different PTMs in this process. In this review, we discuss how PTMs, including phosphorylation, S-acylation, and ubiquitination, affect the stability, localization, and function of zDHHC enzymes and speculate on possible effects of PTMs that have emerged from larger screening studies. Developing a better understanding of the regulatory effects of PTMs on zDHHC enzymes will provide new insight into the intracellular dynamics of S-acylation and may also highlight novel approaches to modulate S-acylation for clinical gain

Scop3P : a comprehensive resource of human phosphosites within their full context

Protein phosphorylation is a key post-translational modification in many biological processes and is associated to human diseases such as cancer and metabolic disorders. The accurate identification, annotation, and functional analysis of phosphosites are therefore crucial to understand their various roles. Phosphosites are mainly analyzed through phosphoproteomics, which has led to increasing amounts of publicly available phosphoproteomics data. Several resources have been built around the resulting phosphosite information, but these are usually restricted to the protein sequence and basic site metadata. What is often missing from these resources, however, is context, including protein structure mapping, experimental provenance information, and biophysical predictions. We therefore developed Scop3P: a comprehensive database of human phosphosites within their full context. Scop3P integrates sequences (UniProtKB/Swiss-Prot), structures (PDB), and uniformly reprocessed phosphoproteomics data (PRIDE) to annotate all known human phosphosites. Furthermore, these sites are put into biophysical context by annotating each phosphoprotein with per-residue structural propensity, solvent accessibility, disordered probability, and early folding information. Scop3P, available at https://iomics.ugent.be/scop3p, presents a unique resource for visualization and analysis of phosphosites and for understanding of phosphosite structure–function relationships

Understanding SUMO-mediated adaptive responses in plants to improve crop productivity

The response to abiotic and biotic stresses in plants and crops is considered a multifaceted process. Due to their sessile nature, plants have evolved unique mechanisms to ensure that developmental plasticity remains during their life cycle. Among these mechanisms, post-translational modifications (PTMs) are crucial components of adaptive responses in plants and transduce environmental stimuli into cellular signalling through the modulation of proteins. SUMOylation is an emerging PTM that has received recent attention due to its dynamic role in protein modification and has quickly been considered a significant component of adaptive mechanisms in plants during stress with great potential for agricultural improvement programs. In the present review, we outline the concept that small ubiquitin-like modifier (SUMO)-mediated response in plants and crops to abiotic and biotic stresses is a multifaceted process with each component of the SUMO cycle facilitating tolerance to several different environmental stresses. We also highlight the clear increase in SUMO genes in crops when compared with Arabidopsis thaliana. The SUMO system is understudied in crops, given the importance of SUMO for stress responses, and for some SUMO genes, the apparent expansion provides new avenues to discover SUMO-conjugated targets that could regulate beneficial agronomical traits

O-GlcNAc transferase – an auxiliary factor or a full-blown oncogene?

The beta-linked N-acetyl-D-glucosamine (GlcNAc) is a posttranslational modification of serine and threonine residues catalyzed by the enzyme O-GlcNAc transferase (OGT). Increased OGT expression is a feature of most human cancers and inhibition of OGT decreases cancer cell proliferation. Antiproliferative effects are attributed to posttranslational modifications of known regulators of cancer cell proliferation, such as MYC, FOXM1, and EZH2. In general, OGT amplifies cell-specific phenotype, for example, OGT overexpression enhances reprogramming efficiency of mouse embryonic fibroblasts into stem cells. Genome-wide screens suggest that certain cancers are particularly dependent on OGT, and understanding these addictions is important when considering OGT as a target for cancer therapy. The O-GlcNAc modification is involved in most cellular processes, which raises concerns of ontarget undesirable effects of OGT-targeting therapy. Yet, emerging evidence suggest that, much like proteasome inhibitors, specific compounds targeting OGT elicit selective antiproliferative effects in cancer cells, and can prime malignant cells to other treatments. It is, therefore, essential to gain mechanistic insights on substrate specificity for OGT, develop reagents to more specifically enrich for O-GlcNAc-modified proteins, identify O-GlcNAc "readers," and develop OGT" small-molecule inhibitors. Here, we review the relevance of OGT in cancer progression and the potential targeting of this metabolic enzyme as a putative oncogene.Peer reviewe

My personal mutanome: a computational genomic medicine platform for searching network perturbing alleles linking genotype to phenotype

Massive genome sequencing data have inspired new challenges in personalized treatments and facilitated oncological drug discovery. We present a comprehensive database, My Personal Mutanome (MPM), for accelerating the development of precision cancer medicine protocols. MPM contains 490,245 mutations from over 10,800 tumor exomes across 33 cancer types in The Cancer Genome Atlas mapped to 94,563 structure-resolved/predicted protein-protein interaction interfaces (“edgetic”) and 311,022 functional sites (“nodetic”), including ligand-protein binding sites and 8 types of protein posttranslational modifications. In total, 8884 survival results and 1,271,132 drug responses are obtained for these mapped interactions. MPM is available at https://mutanome.lerner.ccf.org

Distinct p63 and p73 Protein Interactions Predict Specific Functions in mRNA Splicing and Polyploidy Control in Epithelia.

Epithelial organs are the first barrier against microorganisms and genotoxic stress, in which the p53 family members p63 and p73 have both overlapping and distinct functions. Intriguingly, p73 displays a very specific localization to basal epithelial cells in human tissues, while p63 is expressed in both basal and differentiated cells. Here, we analyse systematically the literature describing p63 and p73 protein-protein interactions to reveal distinct functions underlying the aforementioned distribution. We have found that p73 and p63 cooperate in the genome stability surveillance in proliferating cells; p73 specific interactors contribute to the transcriptional repression, anaphase promoting complex and spindle assembly checkpoint, whereas p63 specific interactors play roles in the regulation of mRNA processing and splicing in both proliferating and differentiated cells. Our analysis reveals the diversification of the RNA and DNA specific functions within the p53 family

DRUM: Inference of Disease-Associated m6A RNA Methylation Sites From a Multi-Layer Heterogeneous Network

Recent studies have revealed that the RNA N6-methyladenosine (m6A) modification plays a critical role in a variety of biological processes and associated with multiple diseases including cancers. Till this day, transcriptome-wide m6A RNA methylation sites have been identified by high-throughput sequencing technique combined with computational methods, and the information is publicly available in a few bioinformatics databases; however, the association between individual m6A sites and various diseases are still largely unknown. There are yet computational approaches developed for investigating potential association between individual m6A sites and diseases, which represents a major challenge in the epitranscriptome analysis. Thus, to infer the disease-related m6A sites, we implemented a novel multi-layer heterogeneous network-based approach, which incorporates the associations among diseases, genes and m6A RNA methylation sites from gene expression, RNA methylation and disease similarities data with the Random Walk with Restart (RWR) algorithm. To evaluate the performance of the proposed approach, a ten-fold cross validation is performed, in which our approach achieved a reasonable good performance (overall AUC: 0.827, average AUC 0.867), higher than a hypergeometric test-based approach (overall AUC: 0.7333 and average AUC: 0.723) and a random predictor (overall AUC: 0.550 and average AUC: 0.486). Additionally, we show that a number of predicted cancer-associated m6A sites are supported by existing literatures, suggesting that the proposed approach can effectively uncover the underlying epitranscriptome circuits of disease mechanisms. An online database DRUM, which stands for disease-associated ribonucleic acid methylation, was built to support the query of disease-associated RNA m6A methylation sites, and is freely available at: www.xjtlu.edu.cn/biologicalsciences/drum

Mechanism and structural requirements for formation of p62 bodies and degradation of p62 by selective autophagy

Selective autophagy is responsible for the lysosomal degradation of damaged and surplus cytoplasmic components, including misfolded proteins and dysfunctional organelles. Selective autophagy is required for protein and organelle quality control basally and upon stress. For the autophagic process to be precise, selective autophagy receptors (SARs) like SQSTM1/p62 are required. Autophagic substrates are often tagged with ubiquitin. Ubiquitinated substrates can be recognized by p62 and other p62-like SARs. SARs bind to lipidated ATG8 protein family members at the inner phagophore membrane and act as bridges that connect the substrate with the phagophore. Both SARs and their substrates are degraded after the fusion of the autophagosome with one or more lysosomes. Hence, p62 is both a substrate and a receptor for selective autophagy. p62 can polymerize into helical filaments via its N-terminal PB1 domain, bind to ATG8 proteins via its LIR (LC3 interacting region) motif and to the ubiquitin E3 ligase subunit KEAP1 via the adjacent KIR (KEAP1 interacting region) motif. The C-terminal UBA domain of p62 interacts with ubiquitinated substrates. The ability to form helical filaments and to bind to ubiquitin chains endows p62 with the property to form droplets in both the cytoplasm and nucleus of cells by liquid-liquid phase transition. The droplets have been called p62 bodies. They contain p62 and also other SARs like NBR1 and TAXBP as well as KEAP1 and ubiquitinated substrates. By recruiting ATG8 proteins and core autophagy components like FIP200 the droplets are degraded by selective autophagy. The p62 bodies can also function as signalosomes (signal transmitting, multimolecular protein complexes) which can also be degraded by selective autophagy to terminate their signaling. This thesis presents new studies of the roles of the PB1 domain, the LIR and KIR motifs and the UBA domain in the formation and degradation of p62 bodies. The first paper, a collaborative study led by the research group of Carsten Sachse, demonstrated the importance of the PB1-mediated polymerization of p62 into filaments for the formation of p62 bodies and their degradation by autophagy. In the second paper, we explored if a specific LIR-mediated binding of LC3B is required for autophagic degradation of p62. In our third paper, we focused on the UBA domain of p62 and post-translational modifications that occur and their effects on p62 droplet formation and degradation. It was clear from our findings that K435 plays a crucial role in the degradation of p62 by selective autophagy

Discovering circulating protein biomarkers through in-depth plasma proteomics

Plasma, i.e., the liquid component of blood, is one of the most clinically used samples for biomarker measurement. Despite that plasma proteins and metabolites are the most frequently analysed biomarkers in practice, identifying and implementing new circulating protein biomarkers for diagnosis, treatment prediction, prognosis, and disease monitoring has been limited. This PhD thesis compiles the discovery of systemic alterations in the blood plasma proteome and potential biomarkers related to disease status, prognosis, or treatment through plasma proteomics. We analysed plasma and serum samples with global proteomics by high-resolution isoelectric focusing (HiRIEF) and liquid chromatography coupled with mass-spectrometry (LC-MS/MS), and targeted proteomics by antibody-based proximity extension assays (PEA) in three diseases that would benefit from blood biomarkers: stage IV metastatic cutaneous melanoma (mCM), glioblastoma (GBM), and coronavirus disease 2019 (COVID-19). Specifically: a.) New treatment options for mCM substantially prolong overall survival (OS), but multiple patients do not respond to treatment or develop treatment resistance, thus having shorter progression free survival (PFS). Corroborated by the presence of multiple metastases, which makes biomarker sampling difficult, circulating proteins derived from the tumour and in response to treatment could serve as predictive and prognostic biomarkers in mCM. b.) GBM is the most malignant primary brain tumour with limited treatment options and notoriously short OS. Sampling biomarkers for GBM requires an invasive surgical intervention on the skull, which makes GBM a good candidate for circulating protein biomarkers for prognosis and monitoring. c.) COVID-19 is an inflammation-driven infectious disease that affects multiple organs and systems, thus making the plasma proteome a good source to explore systemic biological processes occurring in COVID-19. In papers I and II, using HiRIEF LC-MS/MS and PEA, we explored the treatment-driven plasma proteome alterations in mCM patients treated with anti-PD-1 immune checkpoint inhibitors (ICI) and MAPK-inhibitors (MAPKi), respectively, and identified potential treatment predictive and monitoring biomarkers. mCM patients treated with anti-PD-1 ICI had a strong increase in soluble PD-1 levels during treatment, and upregulation of proteins involved in T-cell response. BRAF[V600]-mutated mCM patients treated with MAPKi had deregulation in proteins involved in immune response and proteolysis. CPB1 had the highest increase in patients treated with BRAF- and MEK-inhibitors and was associated with longer PFS. Higher levels of several proteins involved in inflammation before treatment were associated with shorter PFS regardless of ICI or MAPKi treatment. In paper III, using HiRIEF LC-MS/MS and PEA, we longitudinally analysed the plasma proteome dynamics of GBM patients, collecting plasma samples before surgery and at three timepoints after surgery. Through consensus clustering, based on treatment-naïve plasma protein levels, we identified two patient clusters that differed in median OS. The association between the cluster membership and OS remained consistent after adjustment for age, sex, and treatment. Through machine learning, we identified protein panels that separated the patient clusters and may serve as prognostic biomarkers. The largest alterations in the plasma proteome of GBM patients occurred within two months after surgery, whereas the plasma protein levels at later timepoints had no difference compared to pre- surgery levels. We observed a decrease in glioma-elevated proteins in the blood after surgery, identifying potential monitoring biomarkers. In paper IV, using HiRIEF LC-MS/MS, we analysed serum proteome alterations in hospitalised COVID-19 patients in comparison to healthy controls, and identified a strong upregulation in inflammatory, interferon-induced, and proteasomal proteins. Several protein groups showed association with clinical parameters of COVID-19 severity, including proteasomal proteins. Serum proteome alterations were traceable to proteome alterations induced in a lung adenocarcinoma cell line (Calu-3) by infection with SARS-CoV-2. Finally, we performed the first meta-analysis of global proteomics studies of the soluble blood proteome in COVID-19, providing estimates of standardised mean differences and summary receiver operating characteristics curves. We demonstrate the high accuracy and precision of HiRIEF LC-MS/MS when compared to the meta-analysis estimates and pinpoint proteins that may serve as biomarkers of COVID-19. In summary, this thesis postulates that new circulating protein biomarkers would be clinically useful. By combining mass-spectrometry- and antibody-based-proteomics, we demonstrate the potential of in-depth analyses of the plasma proteome in capturing systemic alterations related to treatment, survival, and disease status, pinpointing potentially novel biomarkers that require validation in larger cohorts

Profiling the Human Phosphoproteome to Estimate the True Extent of Protein Phosphorylation

Mass spectrometry-based phosphoproteomics allows large-scale generation of phosphorylation site data. However, analytical pipelines need to be carefully designed and optimised to minimise incorrect identification of phosphopeptide sequences or wrong localisation of phosphorylation sites within those peptides. Public databases such as PhosphoSitePlus (PSP) and PeptideAtlas (PA) compile results from published papers or openly available MS data, but to our knowledge, there is no database-level control for false discovery of sites, subsequently leading to the likely overestimation of true phosphosites. It is therefore difficult for researchers to assess which phosphosites are “real” and which are likely to be artefacts of data processing. By profiling the human phosphoproteome, we aimed to estimate the false discovery rate (FDR) of phosphosites based on available evidence in PSP and/or PA and predict a more realistic count of true phosphosites. We ranked sites into phosphorylation likelihood sets based on layers of accumulated evidence and then analysed them in terms of amino acid conservation across 100 species, sequence properties and functional annotations of associated proteins. We demonstrated significant differences between the sets and developed a method for independent phosphosite FDR estimation. Remarkably, we estimated a false discovery rate of 86.1%, 95.4% and 82.2% within sets of described phosphoserine (pSer), phosphothreonine (pThr) and phosphotyrosine (pTyr) sites respectively for which only a single piece of identification evidence is available (the vast majority of sites in PSP). Overall, we estimate that ∼56,000 Ser, 10,000 Thr and 12,000 Tyr phosphosites in the human proteome have truly been identified to date, based on evidence in PSP and/or PA, which is lower than most published estimates. Furthermore, our analysis estimated ∼91,000 Ser, 49,000 Thr and 26,000 Tyr sites that are likely to represent false-positive phosphosite identifications. We conclude that researchers should be aware of the significant potential for false positive sites to be present in public databases and should evaluate the evidence behind the phosphosites used in their research