A Call for Systematic Research on Solute Carriers.

Solute carrier (SLC) membrane transport proteins control essential physiological functions, including nutrient uptake, ion transport, and waste removal. SLCs interact with several important drugs, and a quarter of the more than 400 SLC genes are associated with human diseases. Yet, compared to other gene families of similar stature, SLCs are relatively understudied. The time is right for a systematic attack on SLC structure, specificity, and function, taking into account kinship and expression, as well as the dependencies that arise from the common metabolic space.

netDx: interpretable patient classification using integrated patient similarity networks.

Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis, and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse data types, and handle sparse data. A clinical predictor based on genomic data needs to be interpretable to drive hypothesis-driven research into new treatments. We describe netDx, a novel supervised patient classification framework based on patient similarity networks, which meets these criteria. In a cancer survival benchmark dataset integrating up to six data types in four cancer types, netDx significantly outperforms most other machine-learning approaches across most cancer types. Compared to traditional machine-learning-based patient classifiers, netDx results are more interpretable, visualizing the decision boundary in the context of patient similarity space. When patient similarity is defined by pathway-level gene expression, netDx identifies biological pathways important for outcome prediction, as demonstrated in breast cancer and asthma. netDx can serve as a patient classifier and as a tool for discovery of biological features characteristic of disease. We provide a free software implementation of netDx with automation workflows.

A draft map of the human proteome.

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

Bmi1 regulates human glioblastoma stem cells through activation of differential gene networks in CD133+ brain tumor initiating cells.

PURPOSE: Glioblastoma (GBM) is the most aggressive adult brain cancer, with a 15 month median survivorship attributed to the existence of treatment-refractory brain tumor initiating cells (BTICs). In order to better understand the mechanisms regulating the tumorigenic properties of this population, we studied the role of the polycomb group member BMI1 in our patient-derived GBM BTICs and its relationship with CD133, a well-established marker of BTICs. METHODS: Using gain and loss-of-function studies for Bmi1 in neural stem cells (NSCs) and patient-derived GBM BTICs respectively, we assessed in vitro self-renewal and in vivo tumor formation in these two cell populations. We further explored the BMI1 transcriptional regulatory network through RNA sequencing of different GBM BTIC populations that were knocked down for Bmi1. RESULTS: There is a differential role of BMI1 in CD133-positive cells, notably involving cell metabolism. In addition, we identified pivotal targets downstream of BMI1 in CD133+ cells such as integrin alpha 2 (ITGA2), that may contribute to regulating GBM stem cell properties. CONCLUSIONS: Our work sheds light on the association of three genes with CD133-BMI1 circuitry, their importance as downstream effectors of the BMI1 signalling pathway, and their potential as future targets for tackling GBM treatment-resistant cell populations.

Global phosphoproteomic profiling reveals perturbed signaling in a mouse model of dilated cardiomyopathy.

Phospholamban (PLN) plays a central role in Ca2+ homeostasis in cardiac myocytes through regulation of the sarco(endo)plasmic reticulum Ca2+-ATPase 2A (SERCA2A) Ca2+ pump. An inherited mutation converting arginine residue 9 in PLN to cysteine (R9C) results in dilated cardiomyopathy (DCM) in humans and transgenic mice, but the downstream signaling defects leading to decompensation and heart failure are poorly understood. Here we used precision mass spectrometry to study the global phosphorylation dynamics of 1,887 cardiac phosphoproteins in early affected heart tissue in a transgenic R9C mouse model of DCM compared with wild-type littermates. Dysregulated phosphorylation sites were quantified after affinity capture and identification of 3,908 phosphopeptides from fractionated whole-heart homogenates. Global statistical enrichment analysis of the differential phosphoprotein patterns revealed selective perturbation of signaling pathways regulating cardiovascular activity in early stages of DCM. Strikingly, dysregulated signaling through the Notch-1 receptor, recently linked to cardiomyogenesis and embryonic cardiac stem cell development and differentiation but never directly implicated in DCM before, was a prominently perturbed pathway. We verified alterations in Notch-1 downstream components in early symptomatic R9C transgenic mouse cardiomyocytes compared with wild type by immunoblot analysis and confocal immunofluorescence microscopy. These data reveal unexpected connections between stress-regulated cell signaling networks, specific protein kinases, and downstream effectors essential for proper cardiac function.

Unbiased phosphoproteomic method identifies the initial effects of a methacrylic acid copolymer on macrophages.

An unbiased phosphoproteomic method was used to identify biomaterial-associated changes in the phosphorylation patterns of macrophage-like cells. The phosphorylation differences between differentiated THP1 (dTHP1) cells treated for 10, 20, or 30 min with a vascular regenerative methacrylic acid (MAA) copolymer or a control methyl methacrylate (MM) copolymer were determined by MS. There were 1,470 peptides (corresponding to 729 proteins) that were differentially phosphorylated in dTHP1 cells treated with the two materials with a greater cellular response to MAA treatment. In addition to identifying pathways (such as integrin signaling and cytoskeletal arrangement) that are well known to change with cell-material interaction, previously unidentified pathways, such as apoptosis and mRNA splicing, were also discovered.

Exercise-responsive phosphoproteins in the heart.

Endurance exercise improves cardiac performance and affords protection against cardiovascular diseases but the signalling events that mediate these benefits are largely unexplored. Phosphorylation is a widely studied post-translational modification involved in intracellular signalling, and to discover novel phosphorylation events associated with exercise we have profiled the cardiac phosphoproteome response to a standardised exercise test to peak oxygen uptake (VO2peak). Male Wistar rats (346±18g) were assigned to 3 independent groups (n=6, in each) that were familiarised with running on a motorised treadmill within a metabolic chamber. Animals performed a graded exercise test and were killed either immediately (0h) after or 3h after terminating the test at a standardised physiological end point (i.e. peak oxygen uptake; VO2peak). Control rats were killed at a similar time of day to the exercised animals, to minimise possible circadian effects. Cardiac proteins were digested with trypsin and phosphopeptides were enriched by selective binding to titanium dioxide (TiO2). Phosphopeptides were analysed by liquid chromatography and high-resolution tandem mass spectrometry, and phosphopeptides were quantified by MS1 intensities and identified against the UniProt knowledgebase using MaxQuant (data are available via ProteomeXchange, ID PXD006646). The VO2peak of rats in the 0h and 3h groups was 66±5mlkg-1min-1 and 69.8±5mlkg-1min-1, respectively. Proteome profiling detected 1169 phosphopeptides and one-way ANOVA found 141 significant (P<0.05 with a false discovery rate of 10%) differences. Almost all (97%) of the phosphosites that were responsive to exercise are annotated in the PhosphoSitePlus database but, importantly, the majority of these have not previously been associated with the cardiac response to exercise. More than two-thirds of the exercise-responsive phosphosites were different from those identified in previous phosphoproteome profiling of the cardiac response to ß1-adrenergic receptor stimulation. Moreover, we report entirely new phosphorylation sites on 4 cardiac proteins, including S81 of muscle LIM protein, and identified 7 exercise-responsive kinases, including myofibrillar protein kinases such as obscurin, titin and the striated-muscle-specific serine/threonine kinase (SPEG) that may be worthwhile targets for future investigation.

Discovery of novel disease-specific and membrane-associated candidate markers in a mouse model of multiple sclerosis.

Multiple sclerosis is a chronic demyelinating disorder characterized by the infiltration of auto-reactive immune cells from the periphery into the central nervous system resulting in axonal injury and neuronal cell death. Experimental autoimmune encephalomyelitis represents the best characterized animal model as common clinical, histological, and immunological features are recapitulated. A label-free mass spectrometric proteomics approach was used to detect differences in protein abundance within specific fractions of disease-affected tissues including the soluble lysate derived from the spinal cord and membrane protein-enriched peripheral blood mononuclear cells. Tissues were harvested from actively induced experimental autoimmune encephalomyelitis mice and sham-induced ("vehicle" control) counterparts at the disease peak followed by subsequent analysis by nanoflow liquid chromatography tandem mass spectrometry. Relative protein quantitation was performed using both intensity- and fragmentation-based approaches. After statistical evaluation of the data, over 500 and 250 differentially abundant proteins were identified in the spinal cord and peripheral blood mononuclear cell data sets, respectively. More than half of these observations have not previously been linked to the disease. The biological significance of all candidate disease markers has been elucidated through rigorous literature searches, pathway analysis, and validation studies. Results from comprehensive targeted mass spectrometry analyses have confirmed the differential abundance of ∼ 200 candidate markers (≥ twofold dysregulated expression) at a 70% success rate. This study is, to our knowledge, the first to examine the cell-surface proteome of peripheral blood mononuclear cells in experimental autoimmune encephalomyelitis. These data provide a unique mechanistic insight into the dynamics of peripheral immune cell infiltration into CNS-privileged sites at a molecular level and has identified several candidate markers, which represent promising targets for future multiple sclerosis therapies. The mass spectrometry proteomics data associated with this manuscript have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000255.

Metabolomic profiling in liver of adiponectin-knockout mice uncovers lysophospholipid metabolism as an important target of adiponectin action.

Adiponectin mediates anti-diabetic effects via increasing hepatic insulin sensitivity and direct metabolic effects. In the present study, we conducted a comprehensive and unbiased metabolomic profiling of liver tissue from AdKO (adiponectin-knockout) mice, with and without adiponectin supplementation, fed on an HFD (high-fat diet) to derive insight into the mechanisms and consequences of insulin resistance. Hepatic lipid accumulation and insulin resistance induced by the HFD were reduced by adiponectin. The HFD significantly altered levels of 147 metabolites, and bioinformatic analysis indicated that one of the most striking changes was the profile of increased lysophospholipids. These changes were largely corrected by adiponectin, at least in part via direct regulation of PLA2 (phospholipase A2) as palmitate-induced PLA2 activation was attenuated by adiponectin in primary hepatocytes. Notable decreases in several glycerolipids after the HFD were reversed by adiponectin, which also corrected elevations in several diacyglycerol and ceramide species. Our data also indicate that stimulation of ω-oxidation of fatty acids by the HFD is enhanced by adiponectin. In conclusion, this metabolomic profiling approach in AdKO mice identified important targets of adiponectin action, including PLA2, to regulate lysophospholipid metabolism and ω-oxidation of fatty acids.

Phosphoproteomic network analysis in the sea urchin Strongylocentrotus purpuratus reveals new candidates in egg activation.

Fertilization triggers a dynamic symphony of molecular transformations induced by a rapid rise in intracellular calcium. Most prominent are surface alterations, metabolic activation, cytoskeletal reorganization, and cell-cycle reentry. While the activation process appears to be broadly evolutionarily conserved, and protein phosphorylation is known to play a key role, the signaling networks mediating the response to fertilization are not well described. To address this gap, we performed a time course phosphoproteomic analysis of egg activation in the sea urchin Strongylocentrotus purpuratus, a system that offers biochemical tractability coupled with exquisite synchronicity. By coupling large-scale phosphopeptide enrichment with unbiased quantitative MS, we identified striking changes in global phosphoprotein patterns at 2- and 5-min postfertilization as compared to unfertilized eggs. Overall, we mapped 8796 distinct phosphosite modifications on 2833 phosphoproteins, of which 15% were differentially regulated in early egg activation. Activated kinases were identified by phosphosite mapping, while enrichment analyses revealed conserved signaling cascades not previously associated with egg activation. This work represents the most comprehensive study of signaling associated with egg activation to date, suggesting novel mechanisms that can be experimentally tested and providing a valuable resource for the broader research community. All MS data have been deposited in the ProteomeXchange with identifier PXD002239 (http://proteomecentral.proteomexchange.org/dataset/PXD002239).

Integrative network analysis of signaling in human CD34(+) hematopoietic progenitor cells by global phosphoproteomic profiling using TiO2 enrichment combined with 2D LC-MS/MS and pathway mapping.

Protein kinase signaling regulates human hematopoietic stem/progenitor cell (HSPC) fate, yet little is known about critical pathway substrates. To address this, we have developed and applied a large-scale, empirically optimized phosphopeptide affinity enrichment strategy with high-throughput 2D LC-MS/MS screening to evaluate the phosphoproteome of an isolated human CD34(+) HSPC population. We first used hydrophilic interaction chromatography as a first dimension separation to separate and simplify protein digest mixtures into discrete fractions. Phosphopeptides were then enriched off-line using TiO2 -coated magnetic beads and subsequently detected online by C18 RP nanoflow HPLC using data-dependent MS/MS high-energy collision-activated dissociation fragmentation on a high-performance Orbitrap hybrid tandem mass spectrometer. We identified 15 533 unique phosphopeptides in 3574 putative phosphoproteins. Systematic computational analysis revealed biological pathways and phosphopeptide motifs enriched in CD34(+) HSPC that are markedly different from those observed in an analogous parallel analysis of isolated human T cells, pointing to the possible involvement of specific kinase-substrate relationships within activated cascades driving hematopoietic renewal, commitment, and differentiation.

Constitutively active calcineurin induces cardiac endoplasmic reticulum stress and protects against apoptosis that is mediated by alpha-crystallin-B.

Cardiac-specific overexpression of a constitutively active form of calcineurin A (CNA) leads directly to cardiac hypertrophy in the CNA mouse model. Because cardiac hypertrophy is a prominent characteristic of many cardiomyopathies, we deduced that delineating the proteomic profile of ventricular tissue from this model might identify novel, widely applicable therapeutic targets. Proteomic analysis was carried out by subjecting fractionated cardiac samples from CNA mice and their WT littermates to gel-free liquid chromatography linked to shotgun tandem mass spectrometry. We identified 1,918 proteins with high confidence, of which 290 were differentially expressed. Microarray analysis of the same tissue provided us with alterations in the ventricular transcriptome. Because bioinformatic analyses of both the proteome and transcriptome demonstrated the up-regulation of endoplasmic reticulum stress, we validated its occurrence in adult CNA hearts through a series of immunoblots and RT-PCR analyses. Endoplasmic reticulum stress often leads to increased apoptosis, but apoptosis was minimal in CNA hearts, suggesting that activated calcineurin might protect against apoptosis. Indeed, the viability of cultured neonatal mouse cardiomyocytes (NCMs) from CNA mice was higher than WT after serum starvation, an apoptotic trigger. Proteomic data identified α-crystallin B (Cryab) as a potential mediator of this protective effect and we showed that silencing of Cryab via lentivector-mediated transduction of shRNAs in NCMs led to a significant reduction in NCM viability and loss of protection against apoptosis. The identification of Cryab as a downstream effector of calcineurin-induced protection against apoptosis will permit elucidation of its role in cardiac apoptosis and its potential as a therapeutic target.

A lentiviral functional proteomics approach identifies chromatin remodeling complexes important for the induction of pluripotency.

Protein complexes and protein-protein interactions are essential for almost all cellular processes. Here, we establish a mammalian affinity purification and lentiviral expression (MAPLE) system for characterizing the subunit compositions of protein complexes. The system is flexible (i.e. multiple N- and C-terminal tags and multiple promoters), is compatible with Gateway cloning, and incorporates a reference peptide. Its major advantage is that it permits efficient and stable delivery of affinity-tagged open reading frames into most mammalian cell types. We benchmarked MAPLE with a number of human protein complexes involved in transcription, including the RNA polymerase II-associated factor, negative elongation factor, positive transcription elongation factor b, SWI/SNF, and mixed lineage leukemia complexes. In addition, MAPLE was used to identify an interaction between the reprogramming factor Klf4 and the Swi/Snf chromatin remodeling complex in mouse embryonic stem cells. We show that the SWI/SNF catalytic subunit Smarca2/Brm is up-regulated during the process of induced pluripotency and demonstrate a role for the catalytic subunits of the SWI/SNF complex during somatic cell reprogramming. Our data suggest that the transcription factor Klf4 facilitates chromatin remodeling during reprogramming.

Control of tissue development and cell diversity by cell cycle-dependent transcriptional filtering.

Cell cycle duration changes dramatically during development, starting out fast to generate cells quickly and slowing down over time as the organism matures. The cell cycle can also act as a transcriptional filter to control the expression of long gene transcripts, which are partially transcribed in short cycles. Using mathematical simulations of cell proliferation, we identify an emergent property that this filter can act as a tuning knob to control gene transcript expression, cell diversity, and the number and proportion of different cell types in a tissue. Our predictions are supported by comparison to single-cell RNA-seq data captured over embryonic development. Additionally, evolutionary genome analysis shows that fast-developing organisms have a narrow genomic distribution of gene lengths while slower developers have an expanded number of long genes. Our results support the idea that cell cycle dynamics may be important across multicellular animals for controlling gene transcript expression and cell fate.

Distinct DNA methylation patterns associated with treatment resistance in metastatic castration resistant prostate cancer.

Androgens are a major driver of prostate cancer (PCa) and continue to be a critical treatment target for advanced disease, which includes castration therapy and antiandrogens. However, resistance to these therapies leading to metastatic castration-resistant prostate cancer (mCRPC), and the emergence of treatment-induced neuroendocrine disease (tNEPC) remains an ongoing challenge. Instability of the DNA methylome is well established as a major hallmark of PCa development and progression. Therefore, investigating the dynamics of the methylation changes going from the castration sensitive to the tNEPC state would provide insights into novel mechanisms of resistance. Using an established xenograft model of CRPC, genome-wide methylation analysis was performed on cell lines representing various stages of PCa progression. We confirmed extensive methylation changes with the development of CRPC and tNEPC using this model. This included key genes and pathways associated with cellular differentiation and neurodevelopment. Combined analysis of methylation and gene expression changes further highlighted genes that could potentially serve as therapeutic targets. Furthermore, tNEPC-related methylation signals from this model were detectable in circulating cell free DNA (cfDNA) from mCRPC patients undergoing androgen-targeting therapies and were associated with a faster time to clinical progression. These potential biomarkers could help with identifying patients with aggressive disease.

Pathway analysis of dilated cardiomyopathy using global proteomic profiling and enrichment maps.

Global protein expression profiling can potentially uncover perturbations associated with common forms of heart disease. We have used shotgun MS/MS to monitor the state of biological systems in cardiac tissue correlating with disease onset, cardiac insufficiency and progression to heart failure in a time-course mouse model of dilated cardiomyopathy. However, interpreting the functional significance of the hundreds of differentially expressed proteins has been challenging. Here, we utilize improved enrichment statistical methods and an extensive collection of functionally related gene sets, gaining a more comprehensive understanding of the progressive alterations associated with functional decline in dilated cardiomyopathy. We visualize the enrichment results as an Enrichment Map, where significant gene sets are grouped based on annotation similarity. This approach vastly simplifies the interpretation of the large number of enriched gene sets found. For pathways of specific interest, such as Apoptosis and the MAPK (mitogen-activated protein kinase) cascade, we performed a more detailed analysis of the underlying signaling network, including experimental validation of expression patterns.

Comparative proteomics profiling of a phospholamban mutant mouse model of dilated cardiomyopathy reveals progressive intracellular stress responses.

Defective mobilization of Ca2+ by cardiomyocytes can lead to cardiac insufficiency, but the causative mechanisms leading to congestive heart failure (HF) remain unclear. In the present study we performed exhaustive global proteomics surveys of cardiac ventricle isolated from a mouse model of cardiomyopathy overexpressing a phospholamban mutant, R9C (PLN-R9C), and exhibiting impaired Ca2+ handling and death at 24 weeks and compared them with normal control littermates. The relative expression patterns of 6190 high confidence proteins were monitored by shotgun tandem mass spectrometry at 8, 16, and 24 weeks of disease progression. Significant differential abundance of 593 proteins was detected. These proteins mapped to select biological pathways such as endoplasmic reticulum stress response, cytoskeletal remodeling, and apoptosis and included known biomarkers of HF (e.g. brain natriuretic peptide/atrial natriuretic factor and angiotensin-converting enzyme) and other indicators of presymptomatic functional impairment. These altered proteomic profiles were concordant with cognate mRNA patterns recorded in parallel using high density mRNA microarrays, and top candidates were validated by RT-PCR and Western blotting. Mapping of our highest ranked proteins against a human diseased explant and to available data sets indicated that many of these proteins could serve as markers of disease. Indeed we showed that several of these proteins are detectable in mouse and human plasma and display differential abundance in the plasma of diseased mice and affected patients. These results offer a systems-wide perspective of the dynamic maladaptions associated with impaired Ca2+ homeostasis that perturb myocyte function and ultimately converge to cause HF.

netDx: Software for building interpretable patient classifiers by multi-'omic data integration using patient similarity networks.

Patient classification based on clinical and genomic data will further the goal of precision medicine. Interpretability is of particular relevance for models based on genomic data, where sample sizes are relatively small (in the hundreds), increasing overfitting risk netDx is a machine learning method to integrate multi-modal patient data and build a patient classifier. Patient data are converted into networks of patient similarity, which is intuitive to clinicians who also use patient similarity for medical diagnosis. Features passing selection are integrated, and new patients are assigned to the class with the greatest profile similarity. netDx has excellent performance, outperforming most machine-learning methods in binary cancer survival prediction. It handles missing data - a common problem in real-world data - without requiring imputation. netDx also has excellent interpretability, with native support to group genes into pathways for mechanistic insight into predictive features. The netDx Bioconductor package provides multiple workflows for users to build custom patient classifiers. It provides turnkey functions for one-step predictor generation from multi-modal data, including feature selection over multiple train/test data splits. Workflows offer versatility with custom feature design, choice of similarity metric; speed is improved by parallel execution. Built-in functions and examples allow users to compute model performance metrics such as AUROC, AUPR, and accuracy. netDx uses RCy3 to visualize top-scoring pathways and the final integrated patient network in Cytoscape. Advanced users can build more complex predictor designs with functional building blocks used in the default design. Finally, the netDx Bioconductor package provides a novel workflow for pathway-based patient classification from sparse genetic data.

Dynamics of the cell-free DNA methylome of metastatic prostate cancer during androgen-targeting treatment.

Aim: We examined methylation changes in cell-free DNA (cfDNA) in metastatic castration-resistant prostate cancer (mCRPC) during treatment. Patients & methods: Genome-wide methylation analysis of sequentially collected cfDNA samples derived from mCRPC patients undergoing androgen-targeting therapy was performed. Results: Alterations in methylation states of genes previously implicated in prostate cancer progression were observed and patients that maintained methylation changes throughout therapy tended to have a longer time to clinical progression. Importantly, we also report that markers associated with a highly aggressive form of the disease, neuroendocrine-CRPC, were associated with a faster time to clinical progression. Conclusion: Our findings highlight the potential of monitoring the cfDNA methylome during therapy in mCRPC, which may serve as predictive markers of response to androgen-targeting agents.