An integrative proteomics method identifies a regulator of translation during stem cell maintenance and differentiation

To characterize molecular changes during cell type transitions, the authors develop a method to simultaneously measure protein expression and thermal stability changes. They apply this approach to study differences between human pluripotent stem cells, their progenies, parental and allogeneic cells. Detailed characterization of cell type transitions is essential for cell biology in general and particularly for the development of stem cell-based therapies in regenerative medicine. To systematically study such transitions, we introduce a method that simultaneously measures protein expression and thermal stability changes in cells and provide the web-based visualization tool ProteoTracker. We apply our method to study differences between human pluripotent stem cells and several cell types including their parental cell line and differentiated progeny. We detect alterations of protein properties in numerous cellular pathways and components including ribosome biogenesis and demonstrate that modulation of ribosome maturation through SBDS protein can be helpful for manipulating cell stemness in vitro. Using our integrative proteomics approach and the web-based tool, we uncover a molecular basis for the uncoupling of robust transcription from parsimonious translation in stem cells and propose a method for maintaining pluripotency in vitro

Chemical proteomics for drug target deconvolution and to study biological systems

Mass spectrometry-based proteomics has become an irreplaceable method for the unbiased and system-wide study of protein chemistry. As modern proteomics methods can not only be applied to quantify protein expression levels, but also monitor changes in post-translational modifications, subcellular localization, turnover rate, and lastly protein structures, it has become a method of choice for drug discovery and dissecting cellular processes. The work presented in this thesis is the combined effort of developing modification-free chemical proteomics methods and their interchangeable application for both drug target deconvolution and cell transition elucidation. In addition, as proteomics becomes more accessible and multidimensional, a focus was set on the development of user-friendly databases and analytical workflows, facilitating the exploration of generated data and the adoption of our methods. In paper I, we compiled a database containing the proteome responses of cancer cells to 56 anti-cancer drugs and used Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) modeling to extract specific regulated proteins. We show that our approach determines both proteins for target deconvolution and mechanisms of action elucidation. Additionally, after empirically determining the minimal number of contrasting drugs, we performed three experiments in different cancer cell lines at an increased analytical depth, showing the importance of cell-line dependencies in drug discovery. Lastly, we created an intuitive graphical user interface for easy exploration of all acquired data and allowing straightforward analysis of custom-generated data sets. In paper II, we extended Thermal Proteome Profiling (TPP) to identify enzyme-substrate associations. We leveraged the fact that the thermal stability of the substrates might change upon the addition of PTMs, terming the new method System-wide identification and prioritization of enzyme substrates by thermal analysis (SIESTA). We showed the generality of our method with three enzyme systems, TXNRD1, AKT1, and PARP10, all with their distinct PTMs. The putative substrates identified by SIESTA show a good overlap with known ones and allow for prioritized validation based on the magnitude of the thermal shift. Additionally, we also determine the interactome of the three different cosubstrates as well as protein-protein interactions with the added enzymes. In paper III, we studied protein stability alterations and expression changes of cells transitioning from pluripotency to differentiated cells. We reprogrammed human foreskin fibroblasts into induced pluripotent stem cells, which we differentiated into embryoid bodies. Developing PISA-Express allowed us to simultaneously quantify protein stability alterations and expression changes along these transitions. Merging these changes into a single analysis by Sankey diagrams, we identified key differences between pluripotent and terminally differentiated cells. This included ribosomal proteins, which show lower thermal stability in pluripotent cells compared to differentiated ones. Further experiments showed that this is caused by a lower pool of functionally assembled ribosomes, controlled by SBDS. Collectively, we developed a new method for the simultaneous analysis of protein thermal stability and expression during cell transitions and created a matching innovative analysis approach. Ultimately, a web interface was created allowing for the exploration of our data and the user-friendly analysis of custom-generated data based on our Sankey diagram approach. False negatives lead to blind spots for every drug target deconvolution method. Therefore, in paper IV we develop a novel method leveraging the kosmotropic effect of ions belonging to the Hofmeister series for TPP and PISA-style experiments, providing much-needed orthogonality. Intending to efficiently pool multiple concentrations samples, as in a PISA-style experiment, we develop a straightforward quenching approach for the kosmotropic ions. We benchmarked this novel method against several drugs in complex cellular lysate, detecting known direct targets, as well downstream events when treating intact cells. We compared the ion-based protein precipitation with the temperature-based one in a full-curve experiment as well as in a PISA experiment using a clinically approved kinase inhibitor, showing the partial orthogonality between them. Ultimately, we performed a PISA experiment with minute amounts of samples on microscopy over slides, potentially opening chemical proteomics methods for paucicellular samples. Finally, in paper V we develop a novel method for the system-wide characterization of drug residence time in cellular lysate and intact cells based on PISA. To validate our approach, we studied two kinase inhibitors as well as a covalent small molecule, allowing us to prioritize their target landscape. Interestingly, we detected no correlation of drug residence time with either the magnitude of the thermal shift or the binding affinity, underlying the importance of determining this parameter. Additionally, we created a higher throughput version of our method, allowing the characterization of the target landscape, drug residence time, and binding affinity in a single mass spectrometer injection. Ultimately, we extended our method for use in intact cells, following the approach developed in paper III, providing a more holistic picture compared to the lysate, as they can actively import, metabolize, and export small molecules. For custom-generated data we also implemented an easy-to-use graphical user interface, allowing for the analysis of various PISA design experiments

Ultralight Ultrafast Enzymes

Inorganic materials depleted of heavy stable isotopes are known to deviate strongly in some physicochemical properties from their isotopically natural counterparts. Here we explored for the first time the effect of simultaneous depletion of the heavy carbon, hydrogen, oxygen and nitrogen isotopes on the bacterium E. coli and the enzymes expressed in it. Bacteria showed faster growth, with most proteins exhibiting higher thermal stability, while for recombinant enzymes expressed in depleted media, faster kinetics was discovered. At room temperature, luciferase, thioredoxin and dihydrofolate reductase and Pfu DNA polymerase showed up to a 250 % increase in activity compared to the native counterparts, with an additional ∼50 % increase at 10 °C. Diminished conformational and vibrational entropy is hypothesized to be the cause of the accelerated kinetics. Ultralight enzymes may find an application where extreme reaction rates are required.</p

GLP-1R signaling neighborhoods associate with the susceptibility to adverse drug reactions of incretin mimetics

G protein-coupled receptors are important drug targets that engage and activate signaling transducers in multiple cellular compartments. Delineating therapeutic signaling from signaling associated with adverse events is an important step towards rational drug design. The glucagon-like peptide-1 receptor (GLP-1R) is a validated target for the treatment of diabetes and obesity, but drugs that target this receptor are a frequent cause of adverse events. Using recently developed biosensors, we explored the ability of GLP-1R to activate 15 pathways in 4 cellular compartments and demonstrate that modifications aimed at improving the therapeutic potential of GLP-1R agonists greatly influence compound efficacy, potency, and safety in a pathway- and compartment-selective manner. These findings, together with comparative structure analysis, time-lapse microscopy, and phosphoproteomics, reveal unique signaling signatures for GLP-1R agonists at the level of receptor conformation, functional selectivity, and location bias, thus associating signaling neighborhoods with functionally distinct cellular outcomes and clinical consequences. Agonists of the glucagon-like peptide-1 receptor are used to treat diabetes and obesity. Here, Wright et al. investigate the subcellular location of the receptor's signaling events and uncover associations between signaling profiles and adverse drug reactions

Analysis of local extracellular matrix identifies different aetiologies behind bicuspid and tricuspid aortic valve degeneration and suggests therapies

Aortic valve degeneration (AVD) is a life-threatening condition that has no medical treatment and lacks individual therapies. Although extensively studied with standard approaches, aetiologies behind AVD are unclear. We compared abundances of extracellular matrix (ECM) proteins from excised valve tissues of 88 patients with isolated AVD of normal tricuspid (TAV) and congenital bicuspid aortic valves (BAV), quantified more than 1400 proteins per ECM sample by mass spectrometry, and demonstrated that local ECM preserves molecular cues of the pathophysiological processes. The BAV ECM showed enrichment with fibrosis markers, namely Tenascin C, Osteoprotegerin, and Thrombospondin-2. The abnormal physical stress on BAV may cause a mechanical injury leading to a continuous Tenascin C-driven presence of myofibroblasts and persistent fibrosis. The TAV ECM exhibited enrichment with Annexin A3 (p = 1.1 x 10(-16) and the fold change 6.5) and a significant deficit in proteins involved in high-density lipid metabolism. These results were validated by orthogonal methods. The difference in the ECM landscape suggests distinct aetiologies between AVD of BAV and TAV; warrants different treatments of the patients with BAV and TAV; elucidates the molecular basis of AVD; and implies possible new therapeutic approaches. Our publicly available database (human_avd_ecm.surgsci. uu.se) is a rich source for medical doctors and researchers who are interested in AVD or heart ECM in general. Systematic proteomic analysis of local ECM using the methods described here may facilitate future studies of various tissues and organs in development and disease

System-wide identification and prioritization of enzyme substrates by thermal analysis

Despite the immense importance of enzyme-substrate reactions, there is a lack of general and unbiased tools for identifying and prioritizing substrate proteins that are modified by the enzyme on the structural level. Here we describe a high-throughput unbiased proteomics method called System-wide Identification and prioritization of Enzyme Substrates by Thermal Analysis (SIESTA). The approach assumes that the enzymatic post-translational modification of substrate proteins is likely to change their thermal stability. In our proof-of-concept studies, SIESTA successfully identifies several known and novel substrate candidates for selenoprotein thioredoxin reductase 1, protein kinase B (AKT1) and poly-(ADP-ribose) polymerase-10 systems. Wider application of SIESTA can enhance our understanding of the role of enzymes in homeostasis and disease, opening opportunities to investigate the effect of post-translational modifications on signal transduction and facilitate drug discovery

A subset of antibodies targeting citrullinated proteins confers protection from rheumatoid arthritis

Although anti-citrullinated protein antibodies (ACPAs) are a hallmark of rheumatoid arthritis and generally considered pathogenic, their functional relevance is incompletely understood. In this study, the authors describe an ACPA with a protective effect against antibody-induced arthritis in mice