A Conserved Circular Network of Coregulated Lipids Modulates Innate Immune Responses.

Lipid composition affects the biophysical properties of membranes that provide a platform for receptor-mediated cellular signaling. To study the regulatory role of membrane lipid composition, we combined genetic perturbations of sphingolipid metabolism with the quantification of diverse steps in Toll-like receptor (TLR) signaling and mass spectrometry-based lipidomics. Membrane lipid composition was broadly affected by these perturbations, revealing a circular network of coregulated sphingolipids and glycerophospholipids. This evolutionarily conserved network architecture simultaneously reflected membrane lipid metabolism, subcellular localization, and adaptation mechanisms. Integration of the diverse TLR-induced inflammatory phenotypes with changes in lipid abundance assigned distinct functional roles to individual lipid species organized across the network. This functional annotation accurately predicted the inflammatory response of cells derived from patients suffering from lipid storage disorders, based solely on their altered membrane lipid composition. The analytical strategy described here empowers the understanding of higher-level organization of membrane lipid function in diverse biological systems.

The systematic analysis of protein-lipid interactions comes of age.

Lipids tailor membrane identities and function as molecular hubs in all cellular processes. However, the ways in which lipids modulate protein function and structure are poorly understood and still require systematic investigation. In this Innovation article, we summarize pioneering technologies, including lipid-overlay assays, lipid pull-down assays, affinity-purification lipidomics and the liposome microarray-based assay (LiMA), that will enable protein-lipid interactions to be deciphered on a systems level. We discuss how these technologies can be applied to the charting of system-wide networks and to the development of new pharmaceutical strategies.

Development of Genetically Encoded Fluorescent KSR1-Based Probes to Track Ceramides during Phagocytosis.

Ceramides regulate phagocytosis; however, their exact function remains poorly understood. Here, we sought (1) to develop genetically encoded fluorescent tools for imaging ceramides, and (2) to use them to examine ceramide dynamics during phagocytosis. Fourteen enhanced green fluorescent protein (EGFP) fusion constructs based on four known ceramide-binding domains were generated and screened. While most constructs localized to the nucleus or cytosol, three based on the CA3 ceramide-binding domain of kinase suppressor of ras 1 (KSR1) localized to the plasma membrane or autolysosomes. C-terminally tagged CA3 with a vector-based (C-KSR) or glycine-serine linker (C-KSR-GS) responded sensitively and similarly to ceramide depletion and accumulation using a panel of ceramide modifying drugs, whereas N-terminally tagged CA3 (N-KSR) responded differently to a subset of treatments. Lipidomic and liposome microarray analysis suggested that, instead, N-KSR may preferentially bind glucosyl-ceramide. Additionally, the three probes showed distinct dynamics during phagocytosis. Despite partial autolysosomal degradation, C-KSR and C-KSR-GS accumulated at the plasma membrane during phagocytosis, whereas N-KSR did not. Moreover, the weak recruitment of C-KSR-GS to the endoplasmic reticulum and phagosomes was enhanced through overexpression of the endoplasmic reticulum proteins stromal interaction molecule 1 (STIM1) and Sec22b, and was more salient in dendritic cells. The data suggest these novel probes can be used to analyze sphingolipid dynamics and function in living cells.

Glucose Metabolism and Aging of Hematopoietic Stem and Progenitor Cells.

Comprehensive proteomics studies of human hematopoietic stem and progenitor cells (HSPC) have revealed that aging of the HSPC compartment is characterized by elevated glycolysis. This is in addition to deregulations found in murine transcriptomics studies, such as an increased differentiation bias towards the myeloid lineage, alterations in DNA repair, and a decrease in lymphoid development. The increase in glycolytic enzyme activity is caused by the expansion of a more glycolytic HSPC subset. We therefore developed a method to isolate HSPC into three distinct categories according to their glucose uptake (GU) levels, namely the GUhigh, GUinter and GUlow subsets. Single-cell transcriptomics studies showed that the GUhigh subset is highly enriched for HSPC with a differentiation bias towards myeloid lineages. Gene set enrichment analysis (GSEA) demonstrated that the gene sets for cell cycle arrest, senescence-associated secretory phenotype, and the anti-apoptosis and P53 pathways are significantly upregulated in the GUhigh population. With this series of studies, we have produced a comprehensive proteomics and single-cell transcriptomics atlas of molecular changes in human HSPC upon aging. Although many of the molecular deregulations are similar to those found in mice, there are significant differences. The most unique finding is the association of elevated central carbon metabolism with senescence. Due to the lack of specific markers, the isolation and collection of senescent cells have yet to be developed, especially for human HSPC. The GUhigh subset from the human HSPC compartment possesses all the transcriptome characteristics of senescence. This property may be exploited to accurately enrich, visualize, and trace senescence development in human bone marrow.

Identification of metabolites from tandem mass spectra with a machine learning approach utilizing structural features.

MOTIVATION: Untargeted mass spectrometry (MS/MS) is a powerful method for detecting metabolites in biological samples. However, fast and accurate identification of the metabolites' structures from MS/MS spectra is still a great challenge. RESULTS: We present a new analysis method, called SubFragment-Matching (SF-Matching) that is based on the hypothesis that molecules with similar structural features will exhibit similar fragmentation patterns. We combine information on fragmentation patterns of molecules with shared substructures and then use random forest models to predict whether a given structure can yield a certain fragmentation pattern. These models can then be used to score candidate molecules for a given mass spectrum. For rapid identification, we pre-compute such scores for common biological molecular structure databases. Using benchmarking datasets, we find that our method has similar performance to CSI: FingerID and those very high accuracies can be achieved by combining our method with CSI: FingerID. Rarefaction analysis of the training dataset shows that the performance of our method will increase as more experimental data become available. AVAILABILITY AND IMPLEMENTATION: SF-Matching is available from http://www.bork.embl.de/Docu/sf_matching. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Impact of spliceosome mutations on RNA splicing in myelodysplasia: dysregulated genes/pathways and clinical associations.

SF3B1, SRSF2, and U2AF1 are the most frequently mutated splicing factor genes in the myelodysplastic syndromes (MDS). We have performed a comprehensive and systematic analysis to determine the effect of these commonly mutated splicing factors on pre-mRNA splicing in the bone marrow stem/progenitor cells and in the erythroid and myeloid precursors in splicing factor mutant MDS. Using RNA-seq, we determined the aberrantly spliced genes and dysregulated pathways in CD34+ cells of 84 patients with MDS. Splicing factor mutations result in different alterations in splicing and largely affect different genes, but these converge in common dysregulated pathways and cellular processes, focused on RNA splicing, protein synthesis, and mitochondrial dysfunction, suggesting common mechanisms of action in MDS. Many of these dysregulated pathways and cellular processes can be linked to the known disease pathophysiology associated with splicing factor mutations in MDS, whereas several others have not been previously associated with MDS, such as sirtuin signaling. We identified aberrantly spliced events associated with clinical variables, and isoforms that independently predict survival in MDS and implicate dysregulation of focal adhesion and extracellular exosomes as drivers of poor survival. Aberrantly spliced genes and dysregulated pathways were identified in the MDS-affected lineages in splicing factor mutant MDS. Functional studies demonstrated that knockdown of the mitosis regulators SEPT2 and AKAP8, aberrantly spliced target genes of SF3B1 and SRSF2 mutations, respectively, led to impaired erythroid cell growth and differentiation. This study illuminates the effect of the common spliceosome mutations on the MDS phenotype and provides novel insights into disease pathophysiology.

Effects of Acetylation and Phosphorylation on Subunit Interactions in Three Large Eukaryotic Complexes.

Protein post-translational modifications (PTMs) have an indispensable role in living cells as they expand chemical diversity of the proteome, providing a fine regulatory layer that can govern protein-protein interactions in changing environmental conditions. Here we investigated the effects of acetylation and phosphorylation on the stability of subunit interactions in purified Saccharomyces cerevisiae complexes, namely exosome, RNA polymerase II and proteasome. We propose a computational framework that consists of conformational sampling of the complexes by molecular dynamics simulations, followed by Gibbs energy calculation by MM/GBSA. After benchmarking against published tools such as FoldX and Mechismo, we could apply the framework for the first time on large protein assemblies with the aim of predicting the effects of PTMs located on interfaces of subunits on binding stability. We discovered that acetylation predominantly contributes to subunits' interactions in a locally stabilizing manner, while phosphorylation shows the opposite effect. Even though the local binding contributions of PTMs may be predictable to an extent, the long range effects and overall impact on subunits' binding were only captured because of our dynamical approach. Employing the developed, widely applicable workflow on other large systems will shed more light on the roles of PTMs in protein complex formation.

Interactome map uncovers phosphatidylserine transport by oxysterol-binding proteins.

The internal organization of eukaryotic cells into functionally specialized, membrane-delimited organelles of unique composition implies a need for active, regulated lipid transport. Phosphatidylserine (PS), for example, is synthesized in the endoplasmic reticulum and then preferentially associates--through mechanisms not fully elucidated--with the inner leaflet of the plasma membrane. Lipids can travel via transport vesicles. Alternatively, several protein families known as lipid-transfer proteins (LTPs) can extract a variety of specific lipids from biological membranes and transport them, within a hydrophobic pocket, through aqueous phases. Here we report the development of an integrated approach that combines protein fractionation and lipidomics to characterize the LTP-lipid complexes formed in vivo. We applied the procedure to 13 LTPs in the yeast Saccharomyces cerevisiae: the six Sec14 homology (Sfh) proteins and the seven oxysterol-binding homology (Osh) proteins. We found that Osh6 and Osh7 have an unexpected specificity for PS. In vivo, they participate in PS homeostasis and the transport of this lipid to the plasma membrane. The structure of Osh6 bound to PS reveals unique features that are conserved among other metazoan oxysterol-binding proteins (OSBPs) and are required for PS recognition. Our findings represent the first direct evidence, to our knowledge, for the non-vesicular transfer of PS from its site of biosynthesis (the endoplasmic reticulum) to its site of biological activity (the plasma membrane). We describe a new subfamily of OSBPs, including human ORP5 and ORP10, that transfer PS and propose new mechanisms of action for a protein family that is involved in several human pathologies such as cancer, dyslipidaemia and metabolic syndrome.

PRL-3 disrupts epithelial architecture by altering the post-mitotic midbody position.

Disruption of epithelial architecture is a fundamental event during epithelial tumorigenesis. We show that the expression of the cancer-promoting phosphatase PRL-3 (PTP4A3), which is overexpressed in several epithelial cancers, in polarized epithelial MDCK and Caco2 cells leads to invasion and the formation of multiple ectopic, fully polarized lumens in cysts. Both processes disrupt epithelial architecture and are hallmarks of cancer. The pathological relevance of these findings is supported by the knockdown of endogenous PRL-3 in MCF-7 breast cancer cells grown in three-dimensional branched structures, showing the rescue from multiple-lumen- to single-lumen-containing branch ends. Mechanistically, it has been previously shown that ectopic lumens can arise from midbodies that have been mislocalized through the loss of mitotic spindle orientation or through the loss of asymmetric abscission. Here, we show that PRL-3 triggers ectopic lumen formation through midbody mispositioning without altering the spindle orientation or asymmetric abscission, instead, PRL-3 accelerates cytokinesis, suggesting that this process is an alternative new mechanism for ectopic lumen formation in MDCK cysts. The disruption of epithelial architecture by PRL-3 revealed here is a newly recognized mechanism for PRL-3-promoted cancer progression.

Capturing protein communities by structural proteomics in a thermophilic eukaryote.

The arrangement of proteins into complexes is a key organizational principle for many cellular functions. Although the topology of many complexes has been systematically analyzed in isolation, their molecular sociology in situ remains elusive. Here, we show that crude cellular extracts of a eukaryotic thermophile, Chaetomium thermophilum, retain basic principles of cellular organization. Using a structural proteomics approach, we simultaneously characterized the abundance, interactions, and structure of a third of the C. thermophilum proteome within these extracts. We identified 27 distinct protein communities that include 108 interconnected complexes, which dynamically associate with each other and functionally benefit from being in close proximity in the cell. Furthermore, we investigated the structure of fatty acid synthase within these extracts by cryoEM and this revealed multiple, flexible states of the enzyme in adaptation to its association with other complexes, thus exemplifying the need for in situ studies. As the components of the captured protein communities are known-at both the protein and complex levels-this study constitutes another step forward toward a molecular understanding of subcellular organization.

Systematic identification of phosphorylation-mediated protein interaction switches.

Proteomics techniques can identify thousands of phosphorylation sites in a single experiment, the majority of which are new and lack precise information about function or molecular mechanism. Here we present a fast method to predict potential phosphorylation switches by mapping phosphorylation sites to protein-protein interactions of known structure and analysing the properties of the protein interface. We predict 1024 sites that could potentially enable or disable particular interactions. We tested a selection of these switches and showed that phosphomimetic mutations indeed affect interactions. We estimate that there are likely thousands of phosphorylation mediated switches yet to be uncovered, even among existing phosphorylation datasets. The results suggest that phosphorylation sites on globular, as distinct from disordered, parts of the proteome frequently function as switches, which might be one of the ancient roles for kinase phosphorylation.

Integration of multi-omics data of a genome-reduced bacterium: Prevalence of post-transcriptional regulation and its correlation with protein abundances.

We developed a comprehensive resource for the genome-reduced bacterium Mycoplasma pneumoniae comprising 1748 consistently generated '-omics' data sets, and used it to quantify the power of antisense non-coding RNAs (ncRNAs), lysine acetylation, and protein phosphorylation in predicting protein abundance (11%, 24% and 8%, respectively). These factors taken together are four times more predictive of the proteome abundance than of mRNA abundance. In bacteria, post-translational modifications (PTMs) and ncRNA transcription were both found to increase with decreasing genomic GC-content and genome size. Thus, the evolutionary forces constraining genome size and GC-content modify the relative contributions of the different regulatory layers to proteome homeostasis, and impact more genomic and genetic features than previously appreciated. Indeed, these scaling principles will enable us to develop more informed approaches when engineering minimal synthetic genomes.

A quantitative liposome microarray to systematically characterize protein-lipid interactions.

Lipids have a role in virtually all biological processes, acting as structural elements, scaffolds and signaling molecules, but they are still largely under-represented in known biological networks. Here we describe a liposome microarray-based assay (LiMA), a method that measures protein recruitment to membranes in a quantitative, automated, multiplexed and high-throughput manner.

Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions.

Systematic interrogation of mutation or protein modification data is important to identify sites with functional consequences and to deduce global consequences from large data sets. Mechismo (mechismo.russellab.org) enables simultaneous consideration of thousands of 3D structures and biomolecular interactions to predict rapidly mechanistic consequences for mutations and modifications. As useful functional information often only comes from homologous proteins, we benchmarked the accuracy of predictions as a function of protein/structure sequence similarity, which permits the use of relatively weak sequence similarities with an appropriate confidence measure. For protein-protein, protein-nucleic acid and a subset of protein-chemical interactions, we also developed and benchmarked a measure of whether modifications are likely to enhance or diminish the interactions, which can assist the detection of modifications with specific effects. Analysis of high-throughput sequencing data shows that the approach can identify interesting differences between cancers, and application to proteomics data finds potential mechanistic insights for how post-translational modifications can alter biomolecular interactions.

Defining a minimal cell: essentiality of small ORFs and ncRNAs in a genome-reduced bacterium.

Identifying all essential genomic components is critical for the assembly of minimal artificial life. In the genome-reduced bacterium Mycoplasma pneumoniae, we found that small ORFs (smORFs; < 100 residues), accounting for 10% of all ORFs, are the most frequently essential genomic components (53%), followed by conventional ORFs (49%). Essentiality of smORFs may be explained by their function as members of protein and/or DNA/RNA complexes. In larger proteins, essentiality applied to individual domains and not entire proteins, a notion we could confirm by expression of truncated domains. The fraction of essential non-coding RNAs (ncRNAs) non-overlapping with essential genes is 5% higher than of non-transcribed regions (0.9%), pointing to the important functions of the former. We found that the minimal essential genome is comprised of 33% (269,410 bp) of the M. pneumoniae genome. Our data highlight an unexpected hidden layer of smORFs with essential functions, as well as non-coding regions, thus changing the focus when aiming to define the minimal essential genome.

An integrated approach for genome annotation of the eukaryotic thermophile Chaetomium thermophilum.

The thermophilic fungus Chaetomium thermophilum holds great promise for structural biology. To increase the efficiency of its biochemical and structural characterization and to explore its thermophilic properties beyond those of individual proteins, we obtained transcriptomics and proteomics data, and integrated them with computational annotation methods and a multitude of biochemical experiments conducted by the structural biology community. We considerably improved the genome annotation of Chaetomium thermophilum and characterized the transcripts and expression of thousands of genes. We furthermore show that the composition and structure of the expressed proteome of Chaetomium thermophilum is similar to its mesophilic relatives. Data were deposited in a publicly available repository and provide a rich source to the structural biology community.

Structural and functional characterization of a phosphatase domain within yeast general transcription factor IIIC.

Saccharomyces cerevisiae τ55, a subunit of the RNA polymerase III-specific general transcription factor TFIIIC, comprises an N-terminal histidine phosphatase domain (τ55-HPD) whose catalytic activity and cellular function is poorly understood. We solved the crystal structures of τ55-HPD and its closely related paralogue Huf and used in silico docking methods to identify phosphoserine- and phosphotyrosine-containing peptides as possible substrates that were subsequently validated using in vitro phosphatase assays. A comparative phosphoproteomic study identified additional phosphopeptides as possible targets that show the involvement of these two phosphatases in the regulation of a variety of cellular functions. Our results identify τ55-HPD and Huf as bona fide protein phosphatases, characterize their substrate specificities, and provide a small set of regulated phosphosite targets in vivo.

Systematic identification of proteins that elicit drug side effects.

Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug-target relations to identify overrepresented protein-side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause side effects. Of 1428 side effects studied, 732 were predicted to be predominantly caused by individual proteins, at least 137 of them backed by existing pharmacological or phenotypic data. We prove this concept in vivo by confirming our prediction that activation of the serotonin 7 receptor (HTR7) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations.

Characterization of drug-induced transcriptional modules: towards drug repositioning and functional understanding.

In pharmacology, it is crucial to understand the complex biological responses that drugs elicit in the human organism and how well they can be inferred from model organisms. We therefore identified a large set of drug-induced transcriptional modules from genome-wide microarray data of drug-treated human cell lines and rat liver, and first characterized their conservation. Over 70% of these modules were common for multiple cell lines and 15% were conserved between the human in vitro and the rat in vivo system. We then illustrate the utility of conserved and cell-type-specific drug-induced modules by predicting and experimentally validating (i) gene functions, e.g., 10 novel regulators of cellular cholesterol homeostasis and (ii) new mechanisms of action for existing drugs, thereby providing a starting point for drug repositioning, e.g., novel cell cycle inhibitors and new modulators of α-adrenergic receptor, peroxisome proliferator-activated receptor and estrogen receptor. Taken together, the identified modules reveal the conservation of transcriptional responses towards drugs across cell types and organisms, and improve our understanding of both the molecular basis of drug action and human biology.