Phenotypic Screen with the Human Secretome Identifies FGF16 as Inducing Proliferation of iPSC-Derived Cardiac Progenitor Cells.

Paracrine factors can induce cardiac regeneration and repair post myocardial infarction by stimulating proliferation of cardiac cells and inducing the anti-fibrotic, antiapoptotic, and immunomodulatory effects of angiogenesis. Here, we screened a human secretome library, consisting of 923 growth factors, cytokines, and proteins with unknown function, in a phenotypic screen with human cardiac progenitor cells. The primary readout in the screen was proliferation measured by nuclear count. From this screen, we identified FGF1, FGF4, FGF9, FGF16, FGF18, and seven additional proteins that induce proliferation of cardiac progenitor cells. FGF9 and FGF16 belong to the same FGF subfamily, share high sequence identity, and are described to have similar receptor preferences. Interestingly, FGF16 was shown to be specific for proliferation of cardiac progenitor cells, whereas FGF9 also proliferated human cardiac fibroblasts. Biosensor analysis of receptor preferences and quantification of receptor abundances suggested that FGF16 and FGF9 bind to different FGF receptors on the cardiac progenitor cells and cardiac fibroblasts. FGF16 also proliferated naïve cardiac progenitor cells isolated from mouse heart and human cardiomyocytes derived from induced pluripotent cells. Taken together, the data suggest that FGF16 could be a suitable paracrine factor to induce cardiac regeneration and repair.

Impact of Case and Control Selection on Training Artificial Intelligence Screening of Cardiac Amyloidosis.

Background: Recent studies suggest that cardiac amyloidosis (CA) is significantly underdiagnosed. For rare diseases like CA, the optimal selection of cases and controls for artificial intelligence model training is unknown and can significantly impact model performance. Objectives: This study evaluates the performance of electrocardiogram (ECG) waveform-based artificial intelligence models for CA screening and assesses impact of different criteria for defining cases and controls. Methods: Using a primary cohort of ∼1.3 million ECGs from 341,989 patients, models were trained using different case and control definitions. Case definitions included ECGs from patients with an amyloidosis diagnosis by International Classification of Diseases-9/10 code, patients with CA, and patients seen in CA clinic. Models were then tested on test cohorts with identical selection criteria as well as a Cedars-Sinai general patient population cohort. Results: In matched held-out test data sets, different model AUCs ranged from 0.660 (95% CI: 0.642-0.736) to 0.898 (95% CI: 0.868-0.924). However, algorithms exhibited variable generalizability when tested on a Cedars-Sinai general patient population cohort, with AUCs dropping to 0.467 (95% CI: 0.443-0.491) to 0.898 (95% CI: 0.870-0.923). Models trained on more well-curated patient cases resulted in higher AUCs on similarly constructed test cohorts. However, all models performed similarly in the overall Cedars-Sinai general patient population cohort. A model trained with International Classification of Diseases 9/10 cases and population controls matched for age and sex resulted in the best screening performance. Conclusions: Models performed similarly in population screening, regardless of stringency of cases used during training, showing that institutions without dedicated amyloid clinics can train meaningful models on less curated CA cases. Additionally, AUC or other metrics alone are insufficient in evaluating deep learning algorithm performance. Instead, evaluation in the most clinically meaningful population is key.

Mechanistic Insights into a CDK9 Inhibitor Via Orthogonal Proteomics Methods.

Cyclin-dependent-kinases (CDKs) are members of the serine/threonine kinase family and are highly regulated by cyclins, a family of regulatory subunits that bind to CDKs. CDK9 represents one of the most studied examples of these transcriptional CDKs. CDK9 forms a heterodimeric complex with its regulatory subunit cyclins T1, T2 and K to form the positive transcription elongation factor b (P-TEFb). This complex regulates transcription via the phosphorylation of RNA polymerase II (RNAPolII) on Ser-2, facilitating promoter clearance and transcription elongation and thus remains an attractive therapeutic target. Herein, we have utilized classical affinity purification chemical proteomics, kinobeads assay, compressed CEllular Thermal Shift Assay (CETSA)-MS and Limited Proteolysis (LiP) to study the selectivity, target engagement and downstream mechanistic insights of a CDK9 tool compound. The above experiments highlight the value of quantitative mass spectrometry approaches to drug discovery, specifically proteome wide target identification and selectivity profiling. The approaches utilized in this study unanimously indicated that the CDK family of kinases are the main target of the compound of interest, with CDK9, showing the highest target affinity with remarkable consistency across approaches. We aim to provide guidance to the scientific community on the available chemical biology/proteomic tools to study advanced lead molecules and to highlight pros and cons of each technology while describing our findings in the context of the CDKs biology.

Communication: Conformation state diagram of polypeptides: a chain length induced α-ß transition.

By using a generic coarse grained polypeptide model, we perform multicanonical molecular dynamics simulations for determining the equilibrium conformation state diagram of a single homopolypeptide chain as a function of the chain length and temperature. The state diagram highlights the thermal regimes of stability for various conformational patterns in polypeptides, including swollen, random and collapsed coils, globular structures, extended and bended α helices, and compact ß bundles. Remarkably, at low temperatures we observe a sharp transition from extended α helix to compact ß bundles as the chain length increases. This finding indicates that the chain length is one of the intrisic factors that can trigger α-ß transformations in a broad class of polypeptides.

A systems-based method to repurpose marketed therapeutics for antiviral use: a SARS-CoV-2 case study.

This study describes two complementary methods that use network-based and sequence similarity tools to identify drug repurposing opportunities predicted to modulate viral proteins. This approach could be rapidly adapted to new and emerging viruses. The first method built and studied a virus-host-physical interaction network; a three-layer multimodal network of drug target proteins, human protein-protein interactions, and viral-host protein-protein interactions. The second method evaluated sequence similarity between viral proteins and other proteins, visualized by constructing a virus-host-similarity interaction network. Methods were validated on the human immunodeficiency virus, hepatitis B, hepatitis C, and human papillomavirus, then deployed on SARS-CoV-2. Comparison of virus-host-physical interaction predictions to known antiviral drugs had AUCs of 0.69, 0.59, 0.78, and 0.67, respectively, reflecting that the scores are predictive of effective drugs. For SARS-CoV-2, 569 candidate drugs were predicted, of which 37 had been included in clinical trials for SARS-CoV-2 (AUC = 0.75, P-value 3.21 × 10-3). As further validation, top-ranked candidate antiviral drugs were analyzed for binding to protein targets in silico; binding scores generated by BindScope indicated a 70% success rate.

hiPS-Derived Astroglia Model Shows Temporal Transcriptomic Profile Related to Human Neural Development and Glia Competence Acquisition of a Maturing Astrocytic Identity.

Astrocyte biology has a functional and cellular diversity only observed in humans. The understanding of the regulatory network governing outer radial glia (RG), responsible for the expansion of the outer subventricular zone (oSVZ), and astrocyte cellular development remains elusive, partly since relevant human material to study these features is not readily available. A human-induced pluripotent stem cell derived astrocytic model, NES-Astro, has been recently developed, with high expression of astrocyte-associated markers and high astrocyte-relevant functionality. Here it is studied how the NES-Astro phenotype develops during specification and its correlation to known RG and astrocyte characteristics in human brain development. It is demonstrated that directed differentiation of neurogenic long-term neuroepithelial stem cells undergo a neurogenic-to-gliogenic competence preferential change, acquiring a glial fate. Temporal transcript profiles of long- and small RNA corroborate previously shown neurogenic restriction by glia-associated let-7 expression. Furthermore, NES-Astro differentiation displays proposed mechanistic features important for the evolutionary expansion of the oSVZ together with an astroglia/astrocyte transcriptome. The NES-Astro generation is a straight-forward differentiation protocol from stable and expandable neuroepithelial stem cell lines derived from iPS cells. Thus, the NES-Astro is an easy-access cell system with high biological relevance for studies of mechanistic traits of glia and astrocyte.

Characterization of the protein unfolding processes induced by urea and temperature.

Correct folding is critical for the biological activities of proteins. As a contribution to a better understanding of the protein (un)folding problem, we studied the effect of temperature and of urea on peptostreptococcal Protein L destructuration. We performed standard molecular dynamics simulations at 300 K, 350 K, 400 K, and 480 K, both in 10 M urea and in water. Protein L followed at least two alternative unfolding pathways. Urea caused the loss of secondary structure acting preferentially on the beta-sheets, while leaving the alpha-helices almost intact; on the contrary, high temperature preserved the beta-sheets and led to a complete loss of the alpha-helices. These data suggest that urea and high temperature act through different unfolding mechanisms, and protein secondary motives reveal a differential sensitivity to various denaturant treatments. As further validation of our results, replica-exchange molecular dynamics simulations of the temperature-induced unfolding process in the presence of urea were performed. This set of simulations allowed us to compute the thermodynamical parameters of the process and confirmed that, in the configurational space of Protein L unfolding, both of the above pathways are accessible, although to a different relative extent.

Human iPS-Derived Astroglia from a Stable Neural Precursor State Show Improved Functionality Compared with Conventional Astrocytic Models.

In vivo studies of human brain cellular function face challenging ethical and practical difficulties. Animal models are typically used but display distinct cellular differences. One specific example is astrocytes, recently recognized for contribution to neurological diseases and a link to the genetic risk factor apolipoprotein E (APOE). Current astrocytic in vitro models are questioned for lack of biological characterization. Here, we report human induced pluripotent stem cell (hiPSC)-derived astroglia (NES-Astro) developed under defined conditions through long-term neuroepithelial-like stem (ltNES) cells. We characterized NES-Astro and astrocytic models from primary sources, astrocytoma (CCF-STTG1), and hiPSCs through transcriptomics, proteomics, glutamate uptake, inflammatory competence, calcium signaling response, and APOE secretion. Finally, we assess modulation of astrocyte biology using APOE-annotated compounds, confirming hits of the cholesterol biosynthesis pathway in adult and hiPSC-derived astrocytes. Our data show large diversity among astrocytic models and emphasize a cellular context when studying astrocyte biology.

Development of a Novel B-Cell Lymphoma 6 (BCL6) PROTAC To Provide Insight into Small Molecule Targeting of BCL6.

B-cell lymphoma 6 (BCL6) inhibition is a promising mechanism for treating hematological cancers but high quality chemical probes are necessary to evaluate its therapeutic potential. Here we report potent BCL6 inhibitors that demonstrate cellular target engagement and exhibit exquisite selectivity for BCL6 based on mass spectrometry analyses following chemical proteomic pull down. Importantly, a proteolysis-targeting chimera (PROTAC) was also developed and shown to significantly degrade BCL6 in a number of diffuse large B-cell lymphoma (DLBCL) cell lines, but neither BCL6 inhibition nor degradation selectively induced marked phenotypic response. To investigate, we monitored PROTAC directed BCL6 degradation in DLBCL OCI-Ly1 cells by immunofluorescence and discovered a residual BCL6 population. Analysis of subcellular fractions also showed incomplete BCL6 degradation in all fractions despite having measurable PROTAC concentrations, together providing a rationale for the weak antiproliferative response seen with both BCL6 inhibitor and degrader. In summary, we have developed potent and selective BCL6 inhibitors and a BCL6 PROTAC that effectively degraded BCL6, but both modalities failed to induce a significant phenotypic response in DLBCL despite achieving cellular concentrations.

PARP9 and PARP14 cross-regulate macrophage activation via STAT1 ADP-ribosylation.

Despite the global impact of macrophage activation in vascular disease, the underlying mechanisms remain obscure. Here we show, with global proteomic analysis of macrophage cell lines treated with either IFNγ or IL-4, that PARP9 and PARP14 regulate macrophage activation. In primary macrophages, PARP9 and PARP14 have opposing roles in macrophage activation. PARP14 silencing induces pro-inflammatory genes and STAT1 phosphorylation in M(IFNγ) cells, whereas it suppresses anti-inflammatory gene expression and STAT6 phosphorylation in M(IL-4) cells. PARP9 silencing suppresses pro-inflammatory genes and STAT1 phosphorylation in M(IFNγ) cells. PARP14 induces ADP-ribosylation of STAT1, which is suppressed by PARP9. Mutations at these ADP-ribosylation sites lead to increased phosphorylation. Network analysis links PARP9-PARP14 with human coronary artery disease. PARP14 deficiency in haematopoietic cells accelerates the development and inflammatory burden of acute and chronic arterial lesions in mice. These findings suggest that PARP9 and PARP14 cross-regulate macrophage activation.

Endophenotype Network Models: Common Core of Complex Diseases.

Historically, human diseases have been differentiated and categorized based on the organ system in which they primarily manifest. Recently, an alternative view is emerging that emphasizes that different diseases often have common underlying mechanisms and shared intermediate pathophenotypes, or endo(pheno)types. Within this framework, a specific disease's expression is a consequence of the interplay between the relevant endophenotypes and their local, organ-based environment. Important examples of such endophenotypes are inflammation, fibrosis, and thrombosis and their essential roles in many developing diseases. In this study, we construct endophenotype network models and explore their relation to different diseases in general and to cardiovascular diseases in particular. We identify the local neighborhoods (module) within the interconnected map of molecular components, i.e., the subnetworks of the human interactome that represent the inflammasome, thrombosome, and fibrosome. We find that these neighborhoods are highly overlapping and significantly enriched with disease-associated genes. In particular they are also enriched with differentially expressed genes linked to cardiovascular disease (risk). Finally, using proteomic data, we explore how macrophage activation contributes to our understanding of inflammatory processes and responses. The results of our analysis show that inflammatory responses initiate from within the cross-talk of the three identified endophenotypic modules.

Analysing extremely small sized ratio datasets.

The naïve use of expression ratios in high-throughput biological studies can greatly limit analytical outcome especially when sample size is small. In the worst-case scenario, with only one reference and one test state each (often due to the severe lack of study material); such limitations make it difficult to perform statistically meaningful analysis. Workarounds include the single sample Z-test or through network inference. Here, we describe a complementary plot-based approach for analysing such extremely small sized ratio (ESSR) data - a generalisation of the Bland-Altman plot, which we shall refer to as the Dodeca-Panels. Included in this paper is an R implementation of the Dodeca-Panels method.

mIMT-visHTS: A novel method for multiplexing isobaric mass tagged datasets with an accompanying visualization high throughput screening tool for protein profiling.

Isobaric mass tagging (IMT) methods enable the analysis of thousands of proteins simultaneously. We used tandem mass tagging reagents (TMT™) to monitor the relative changes in the proteome of the mouse macrophage cell line RAW264.7 at the same six time points after no stimulation (baseline phenotype), stimulation with interferon gamma (pro-inflammatory phenotype) or stimulation with interleukin-4 (anti-inflammatory phenotype). The combined TMT datasets yielded nearly 12,000 protein profiles for comparison. To facilitate this large analysis, we developed a novel method that combines or multiplexes the separate IMT (mIMT) datasets into a single super dataset for subsequent model-based clustering and co-regulation analysis. Specially designed visual High Throughput Screening (visHTS) software screened co-regulated proteins. visHTS generates an interactive and visually intuitive color-coded bullseye plot that enables users to browse the cluster outputs and identify co-regulated proteins.

Two-step nucleation of amyloid fibrils: omnipresent or not?

Amyloid protein fibrils feature in various diseases and nanotechnological products. Currently, it is debated whether they nucleate in one step (i.e., directly from the protein solution) or in two steps (step one being the appearance of nonfibrillar oligomers in the solution and step two being the oligomer conversion into fibrils). We employ nucleation theory to gain insight into the idiosyncrasy of two-step fibril nucleation and to determine the conditions under which this process can take place. Presenting an expression for the rate of two-step fibril nucleation, we use it to qualitatively describe experimental data for two-step nucleated amyloid-ß fibrils. Our analysis helps in understanding why, in some experiments, oligomers rather than fibrils form and remain structurally unchanged and why, in others, the oligomers convert into fibrils.

Tracking polypeptide folds on the free energy surface: effects of the chain length and sequence.

Characterization of the folding transition in polypeptides and assessing the thermodynamic stability of their structured folds are of primary importance for approaching the problem of protein folding. We use molecular dynamics simulations for a coarse grained polypeptide model in order to (1) obtain the equilibrium conformation diagram of homopolypeptides in a broad range of the chain lengths, N = 10, ..., 100, and temperatures, T (in a multicanonical ensemble), and (2) determine free energy profiles (FEPs) projected onto an optimal, so-called "natural", reaction coordinate that preserves the height of barriers and the diffusion coefficients on the underlying free energy hyper-surface. We then address the following fundamental questions. (i) How well does a kinetically determined free energy landscape of a single chain represent the polypeptide equilibrium (ensemble) behavior? In particular, under which conditions might the correspondence be lost, and what are the possible implications for the folding processes? (ii) How does the free energy landscape depend on the chain length (homopolypeptides) and the monomer interaction sequence (heteropolypeptides)? Our data reveal that at low T values equilibrium structures adopted by relatively short homopolypeptides (N < 60) are dominated by α-helical folds which correspond to the primary and secondary minima of the FEP. In contrast, longer homopolypeptides (N > 70), upon quasi-equilibrium cooling, fold preferentially in ß-bundles with small helical portions, while the FEPs exhibit no distinct global minima. Moreover, subject to the choice of the initial configuration, at sufficiently low T, essentially metastable structures can be found and prevail far from the true thermodynamic equilibrium. We also show that, by sequence-enabling the polypeptide model, it is possible to restrict the chain to a very specific part of the configuration space, which results in substantial simplification and smoothing of the free energy landscape as compared to the case of the corresponding homopolypeptide.

Protein aggregation: kinetics versus thermodynamics.

In this study, we address the questions of how important is the kinetics in protein aggregation, and what are the intrinsic properties of proteins that cause this behavior. On the basis of our recent quantitative calculation of the equilibrium phase diagram of natively folded α-helical and ß-sheet forming peptides, we perform molecular dynamics simulations to demonstrate how the aggregation mechanism and end product depend on the temperature, concentration, and starting point in the phase diagram. The results obtained show that there are severe differences between the thermodynamically predicted and the kinetically obtained aggregate structures. The observed differences help to rationalize the suggestion that monomeric proteins in their native functional structure can be metastable with respect to the amyloid state, and that the native fold is a special property that protects them from aggregation.

Simulation of urea-induced protein unfolding: a lesson from bovine ß-lactoglobulin.

To investigate the molecular mechanisms involved in the very initial stages of protein unfolding, we carried out one long (1 µs) simulation of bovine ß-lactoglobulin (BLG) together with three (500 ns) supporting MD runs, in which the unfolding conditions were produced by adding the osmolyte urea to the simulated systems and/or by increasing the thermal energy raising the temperature from 300 to 350 K. BLG was chosen, since it is a well-characterized model protein, for which structural and folding properties have been widely investigated by X-ray and NMR. MD trajectories were analyzed not only in terms of standard progress variables, such as backbone H-bonds, gyration radius width, secondary structure elements, but also through the scrutiny of interactions and dynamical behavior of specific key residues previously pointed out and investigated by NMR and belonging to a well known hydrophobic cluster. MD trajectories simulated in different unfolding conditions suggest that urea destabilizes BLG structure weakening protein::protein hydrophobic interactions and the hydrogen bond network. The early unfolding events, better observed at higher temperature, affect both secondary and tertiary structure of the protein.

Nephrocystin-1 forms a complex with polycystin-1 via a polyproline motif/SH3 domain interaction and regulates the apoptotic response in mammals.

Mutations in PKD1, the gene encoding for the receptor Polycystin-1 (PC-1), cause autosomal dominant polycystic kidney disease (ADPKD). The cytoplasmic C-terminus of PC-1 contains a coiled-coil domain that mediates an interaction with the PKD2 gene product, Polycystin-2 (PC-2). Here we identify a novel domain in the PC-1 C-terminal tail, a polyproline motif mediating an interaction with Src homology domain 3 (SH3). A screen for interactions using the PC-1 C-terminal tail identified the SH3 domain of nephrocystin-1 (NPHP1) as a potential binding partner of PC-1. NPHP1 is the product of a gene that is mutated in a different form of renal cystic disease, nephronophthisis (NPHP). We show that in vitro pull-down assays and NMR structural studies confirmed the interaction between the PC-1 polyproline motif and the NPHP1 SH3 domain. Furthermore, the two full-length proteins interact through these domains; using a recently generated model system allowing us to track endogenous PC-1, we confirm the interaction between the endogenous proteins. Finally, we show that NPHP1 trafficking to cilia does not require PC-1 and that PC-1 may require NPHP1 to regulate resistance to apoptosis, but not to regulate cell cycle progression. In line with this, we find high levels of apoptosis in renal specimens of NPHP patients. Our data uncover a link between two different ciliopathies, ADPKD and NPHP, supporting the notion that common pathogenetic defects, possibly involving de-regulated apoptosis, underlie renal cyst formation.

Structural and dynamic roles of permanent water molecules in ligand molecular recognition by chicken liver bile acid binding protein.

Chicken liver bile acid binding protein (cL-BABP) crystallizes with water molecules in its binding site. To obtain insights on the role of internal water, we performed two 100 ns molecular dynamics (MD) simulations in explicit solvent for cL-BABP, as apo form and as a complex with two molecules of cholic acid, and analyzed in detail the dynamics properties of all water molecules. The diffusion coefficients of the more persistent internal water molecules are significantly different from the bulk, but similar between the two protein forms. A different number of molecules and a different organization are observed for apo- and holo-cL-BABP. Most water molecules identified in the binding site of the apo-crystal diffuse to the bulk during the simulation. In contrast, almost all the internal waters of the holo-crystal maintain the same interactions with internal sidechains and ligands, which suggests they have a relevant role in protein-ligand molecular recognition. Only in the presence of these water molecules we were able to reproduce, by a classical molecular docking approach, the structure of the complex cL-BABP::cholic acid with a low ligand root mean square deviation (RMSD) with respect to its reference positioning. Literature data reported a conserved pattern of hydrogen bonds between a single water molecule and three amino acid residues of the binding site in a series of crystallized FABP. In cL-BABP, the interactions between this conserved water molecule and the three residues are present in the crystal of both apo- and holo-cL-BABP but are lost immediately after the start of molecular dynamics.

Pigment epithelium-derived factor is differentially expressed in peripheral neuropathies.

Peripheral neuropathies are characterized by asymmetrical slowly progressive weakness with no upper motor neuron signs, and can occur either with or without pain. Due to poor knowledge of the disease mechanisms, available pain treatment is very limited. Because of the difficulties and invasiveness involved when performing direct analysis on peripheral and CNS, pathological markers can be searched for in the cerebrospinal fluid (CSF) as an alternative. To investigate pain mechanisms in peripheral neuropathy and find diagnostic markers, CSF samples were analyzed by a differential expression proteomic approach. We studied CSF from: neuropathic patients with pain (PN), without pain (NPN) and healthy controls (CN). 2-DE analysis showed ten protein spots differentially expressed, and six of these were identified by MS. In NPN patients we found an expression level decrease of three pigment epithelium-derived factor (PEDF) protein isoforms. Immunoblot with a specific antibody revealed the presence of additional PEDF isoforms not highlighted by differential expression analysis. Fucose residues on the oligosaccharide chain were found only in the isoforms down regulated in NPN patients. Considered as PEDF has important neurobiological effects, it might be considered an interesting pathology marker.