Comparative proteomic analysis of eleven common cell lines reveals ubiquitous but varying expression of most proteins

Kv2.1 mediates spatial and functional coupling of L-type calcium channels and ryanodine receptors in mammalian neurons

The voltage-gated K⁺ channel Kv2.1 serves a major structural role in the soma and proximal dendrites of mammalian brain neurons, tethering the plasma membrane (PM) to endoplasmic reticulum (ER). Although Kv2.1 clustering at neuronal ER-PM junctions (EPJs) is tightly regulated and highly conserved, its function remains unclear. By identifying and evaluating proteins in close spatial proximity to Kv2.1-containing EPJs, we discovered that a significant role of Kv2.1 at EPJs is to promote the clustering and functional coupling of PM L-type Ca²⁺ channels (LTCCs) to ryanodine receptor (RyR) ER Ca²⁺ release channels. Kv2.1 clustering also unexpectedly enhanced LTCC opening at polarized membrane potentials. This enabled Kv2.1-LTCC-RyR triads to generate localized Ca²⁺ release events (i.e., Ca²⁺ sparks) independently of action potentials. Together, these findings uncover a novel mode of LTCC regulation and establish a unique mechanism whereby Kv2.1-associated EPJs provide a molecular platform for localized somatodendritic Ca²⁺ signals in mammalian brain neurons.

A framework for TRIM21-mediated protein depletion in early mouse embryos: recapitulation of Tead4 null phenotype over three days

Background

While DNA and RNA methods are routine to disrupt the expression of specific genes, complete understanding of developmental processes requires also protein methods, because: oocytes and early embryos accumulate proteins and these are not directly affected by DNA and RNA methods. When proteins in the oocyte encounter a specific antibody and the TRIpartite Motiv-containing 21 (TRIM21) ubiquitin-protein ligase, they can be committed to degradation in the proteasome, producing a transient functional knock-out that reveals the role of the protein. However, there are doubts about whether this targeted proteolysis could be successfully used to study mammalian development, because duration of the transient effect is unknown, and also because amounts of reagents delivered must be adequate in relation to the amount of target protein, which is unknown, too.

Results

We show that the mouse egg contains up to 1E-02 picomoles/protein, as estimated by mass spectrometry using the intensity-based absolute quantification (iBAQ) algorithm. However, the egg can only accommodate ≈1E-04 picomoles of antibody or TRIM21 without incurring toxic effects. Within this framework, we demonstrate that TRIM21-mediated protein depletion efficiently disrupts the embryonic process of trophectoderm formation, which critically depends on the TEA domain family member 4 (Tead4) gene. TEAD4 depletion starting at the 1-cell stage lasts for 3 days prior to a return of gene and protein expression to baseline. This time period is long enough to result in a phenotype entirely consistent with that of the published null mutation and RNA interference studies: significant underexpression of trophectodermal genes Cdx2 and Gata3 and strongly impaired ability of embryos to cavitate and implant in the uterus. Omics data are available via ProteomeXchange (PXD012613) and GEO (GSE124844).

Conclusions

TRIM21-mediated protein depletion can be an effective means to disrupt gene function in mouse development, provided the target gene is chosen carefully and the method is tuned accurately. The knowledge gathered in this study provides the basic know-how (prerequisites, requirements, limitations) to expedite the protein depletion of other genes besides Tead4.

Rearrangement of the Protein Phosphatase 1 Interactome During Heart Failure Progression

BACKGROUND

Heart failure (HF) is a complex disease with a rising prevalence despite advances in treatment. Protein phosphatase 1 (PP1) has long been implicated in HF pathogenesis, but its exact role is both unclear and controversial. Most previous studies measured only the PP1 catalytic subunit (PP1c) without investigating its diverse set of interactors, which confer localization and substrate specificity to the holoenzyme. In this study, we define the PP1 interactome in cardiac tissue and test the hypothesis that this interactome becomes rearranged during HF progression at the level of specific PP1c interactors.

METHODS

Mice were subjected to transverse aortic constriction and grouped on the basis of ejection fraction into sham, hypertrophy, moderate HF (ejection fraction, 30%-40%), and severe HF (ejection fraction <30%). Cardiac lysates were subjected to affinity purification with anti-PP1c antibodies followed by high-resolution mass spectrometry. PP1 regulatory subunit 7 (Ppp1r7) was knocked down in mouse cardiomyocytes and HeLa cells with adeno-associated virus serotype 9 and siRNA, respectively. Calcium imaging was performed on isolated ventricular myocytes.

RESULTS

Seventy-one and 98 PP1c interactors were quantified from mouse cardiac and HeLa lysates, respectively, including many novel interactors and protein complexes. This represents the largest reproducible PP1 interactome data set ever captured from any tissue, including both primary and secondary/tertiary interactors. Nine PP1c interactors with changes in their binding to PP1c were strongly associated with HF progression, including 2 known (Ppp1r7 and Ppp1r18) and 7 novel interactors. Within the entire cardiac PP1 interactome, Ppp1r7 had the highest binding to PP1c. Cardiac-specific knockdown in mice led to cardiac dysfunction and disruption of calcium release from the sarcoplasmic reticulum.

CONCLUSIONS

PP1 is best studied at the level of its interactome, which undergoes significant rearrangement during HF progression. The 9 key interactors that are associated with HF progression may represent potential targets in HF therapy. In particular, Ppp1r7 may play a central role in regulating the PP1 interactome by acting as a competitive molecular "sponge" of PP1c.

Heterogeneous responses to low level death receptor activation are explained by random molecular assembly of the Caspase-8 activation platform

Ligand binding to death receptors activates apoptosis in cancer cells. Stimulation of death receptors results in the formation of intracellular multiprotein platforms that either activate the apoptotic initiator Caspase-8 to trigger cell death, or signal through kinases to initiate inflammatory and cell survival signalling. Two of these platforms, the Death-Inducing Signalling Complex (DISC) and the RIPoptosome, also initiate necroptosis by building filamentous scaffolds that lead to the activation of mixed lineage kinase domain-like pseudokinase. To explain cell decision making downstream of death receptor activation, we developed a semi-stochastic model of DISC/RIPoptosome formation. The model is a hybrid of a direct Gillespie stochastic simulation algorithm for slow assembly of the RIPoptosome and a deterministic model of downstream caspase activation. The model explains how alterations in the level of death receptor-ligand complexes, their clustering properties and intrinsic molecular fluctuations in RIPoptosome assembly drive heterogeneous dynamics of Caspase-8 activation. The model highlights how kinetic proofreading leads to heterogeneous cell responses and results in fractional cell killing at low levels of receptor stimulation. It reveals that the noise in Caspase-8 activation-exclusively caused by the stochastic molecular assembly of the DISC/RIPoptosome platform-has a key function in extrinsic apoptotic stimuli recognition.

A genome-wide screen for human salicylic acid (SA)-binding proteins reveals targets through which SA may influence development of various diseases

Salicylic acid (SA) is the major metabolite and active ingredient of aspirin; both compounds reduce pain, fever, and inflammation. Despite over a century of research, aspirin/SA's mechanism(s) of action is still only partially understood. Here we report the results of a genome-wide, high-throughput screen to identify potential SA-binding proteins (SABPs) in human HEK293 cells. Following photo-affinity crosslinking to 4-azidoSA and immuno-selection with an anti-SA antibody, approximately 2,000 proteins were identified. Among these, 95 were enriched more than 10-fold. Pathway enrichment analysis with these 95 candidate SABPs (cSABPs) revealed possible involvement of SA in multiple biological pathways, including (i) glycolysis, (ii) cytoskeletal assembly and/or signaling, and (iii) NF-κB-mediated immune signaling. The two most enriched cSABPs, which corresponded to the glycolytic enzymes alpha-enolase (ENO1) and pyruvate kinase isozyme M2 (PKM2), were assessed for their ability to bind SA and SA's more potent derivative amorfrutin B1 (amoB1). SA and amoB1 bound recombinant ENO1 and PKM2 at low millimolar and micromolar concentrations, respectively, and inhibited their enzymatic activities in vitro. Consistent with these results, low millimolar concentrations of SA suppressed glycolytic activity in HEK293 cells. To provide insights into how SA might affect various human diseases, a cSABP-human disorder/disease network map was also generated.

Lack of activity of recombinant HIF prolyl hydroxylases (PHDs) on reported non-HIF substrates

Human and other animal cells deploy three closely related dioxygenases (PHD 1, 2 and 3) to signal oxygen levels by catalysing oxygen regulated prolyl hydroxylation of the transcription factor HIF. The discovery of the HIF prolyl-hydroxylase (PHD) enzymes as oxygen sensors raises a key question as to the existence and nature of non-HIF substrates, potentially transducing other biological responses to hypoxia. Over 20 such substrates are reported. We therefore sought to characterise their reactivity with recombinant PHD enzymes. Unexpectedly, we did not detect prolyl-hydroxylase activity on any reported non-HIF protein or peptide, using conditions supporting robust HIF-α hydroxylation. We cannot exclude PHD-catalysed prolyl hydroxylation occurring under conditions other than those we have examined. However, our findings using recombinant enzymes provide no support for the wide range of non-HIF PHD substrates that have been reported.

Dynamic modeling of signal transduction by mTOR complexes in cancer

Signal integration has a crucial role in the cell fate decision and dysregulation of the cellular signaling pathways is a primary characteristic of cancer. As a signal integrator, mTOR shows a complex dynamical behavior which determines the cell fate at different cellular processes levels, including cell cycle progression, cell survival, cell death, metabolic reprogramming, and aging. The dynamics of the complex responses to rapamycin in cancer cells have been attributed to its differential time-dependent inhibitory effects on mTORC1 and mTORC2, the two main complexes of mTOR. Two explanations were previously provided for this phenomenon: 1-Rapamycin does not inhibit mTORC2 directly, whereas it prevents mTORC2 formation by sequestering free mTOR protein (Le Chatelier's principle). 2-Components like Phosphatidic Acid (PA) further stabilize mTORC2 compared with mTORC1. To understand the mechanism by which rapamycin differentially inhibits the mTOR complexes in the cancer cells, we present a mathematical model of rapamycin mode of action based on the first explanation, i.e., Le Chatelier's principle. Translating the interactions among components of mTORC1 and mTORC2 into a mathematical model revealed the dynamics of rapamycin action in different doses and time-intervals of rapamycin treatment. This model shows that rapamycin has stronger effects on mTORC1 compared with mTORC2, simply due to its direct interaction with free mTOR and mTORC1, but not mTORC2, without the need to consider other components that might further stabilize mTORC2. Based on our results, even when mTORC2 is less stable compared with mTORC1, it can be less inhibited by rapamycin.

Harnessing the tissue and plasma lncRNA-peptidome to discover peptide-based cancer biomarkers

Proteome-centric studies, although have identified numerous lncRNA-encoded polypeptides, lack differential expression analysis of lncRNA-peptidome across primary tissues, cell lines and cancer states. We established a computational-proteogenomic workflow involving re-processing of publicly available LC-MS/MS data, which facilitated the identification of tissue-specific and universally expressed (UExp) lncRNA-polypeptides across 14 primary human tissues and 11 cell lines. The utility of lncRNA-peptidome as cancer-biomarkers was investigated by re-processing LC-MS/MS data from 92 colon-adenocarcinoma (COAD) and 30 normal colon-epithelium tissues. Intriguingly, a significant upregulation of five lncRNA UExp-polypeptides in COAD tissues was observed. Furthermore, clustering of the UExp-polypeptides led to the classification of COAD patients that coincided with the clinical stratification, underlining the prognostic potential of the UExp-polypeptides. Lastly, we identified differential abundance of the UExp-polypeptides in the plasma of prostate-cancer patients highlighting their potential as plasma-biomarker. The analysis of lncRNA-peptidome may pave the way to identify effective tissue/plasma biomarkers for different cancer types.

Target-small decoy search strategy for false discovery rate estimation

Background

One of the most important steps in peptide identification is to estimate the false discovery rate (FDR). The most commonly used method for estimating FDR is the target-decoy search strategy (TDS). While this method is simple and effective, it is time/space-inefficient because it searches a database that is twice as large as the original protein database. This inefficiency problem becomes more evident as protein databases get bigger and bigger. We propose a target-small decoy search strategy and present a rigorous verification that it reduces the database size and search time while retaining the accuracy of target-decoy search strategy (TDS).

Results

We show that peptide spectrum matches (PSMs) obtained at 1% FDR in TDS overlap ~ 99% with those in our method. (Considering that 1% FDR is used, 99% overlap means our method is very accurate.) Moreover, our method is more time/space-efficient than TDS. The search time of our method is reduced to only 1/4 of that of TDS when UniProt and its 1/8 decoy database are used.

Conclusions

We demonstrate that our method is almost as accurate as TDS and more time/space-efficient than TDS. Since the efficiency of our method is more evident as the database size increases, our method is expected to be useful for identifying peptides in proteogenomics databases constructed from inflated databases using genomic data.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3034-8) contains supplementary material, which is available to authorized users.

MODplus: Robust and Unrestrictive Identification of Post-Translational Modifications Using Mass Spectrometry

Post-translational modifications regulate various cellular processes and are of great biological interest. Unrestrictive searches of mass spectrometry data enable the detection of any type of modification. Here we propose MODplus, which makes practical unrestrictive searches possible by allowing (1) hundreds of modifications, (2) multiple modifications per peptide, (3) the whole proteome database, and (4) any tolerant values in search parameters. The utility of MODplus was demonstrated in large human data sets of HEK293 cells and TMT-labeled phosphorylation enrichment. Notably, MODplus supports identifying different modification types at multiple sites and reports real chemical and biological modifications, as it has been very labor intensive to link unrestrictive search results to real modifications. We also confirmed the presence of Missing Precursor (MP) spectra that were not identifiable using targeted precursor masses. The MP spectra mostly resulted in identifications of wrong modifications and negatively affected the overall performance, often by as much as 10%. MODplus can rapidly recognize MP spectra and correct their identifications, resulting in increased identification rate up to 70% in the HEK293 data set as well as improved reliability.

FusionPro, a Versatile Proteogenomic Tool for Identification of Novel Fusion Transcripts and Their Potential Translation Products in Cancer Cells

Fusion proteoforms are translation products derived from gene fusion. Although very rare, the fusion proteoforms play important roles in biomedical science. For example, fusion proteoforms influence the development of tumors by serving as cancer markers or cell cycle regulators. Although numerous studies have reported bioinformatics tools that can predict fusion transcripts, few proteogenomic tools are available that can predict and identify proteoforms. In this study, we develop a versatile proteogenomic tool "FusionPro," which facilitates the identification of fusion transcripts and their potential translatable peptides. FusionPro provides an independent gene fusion prediction module and can build sequence databases for annotated fusion proteoforms. FusionPro shows greater sensitivity than the available fusion finders when analyzing simulated or real RNA sequencing data sets. We use FusionPro to identify 18 fusion junction peptides and three potential fusion-derived peptides by MS/MS-based analysis of leukemia cell lines (Jurkat and K562) and ovarian cancer tissues from the Clinical Proteomic Tumor Analysis Consortium. Among the identified fusion proteins, we molecularly validate two fusion junction isoforms and a translation product of FAM133B:CDK6. Moreover, sequence analysis suggests that the fusion protein participates in the cell cycle progression. In addition, our prediction results indicate that fusion transcripts often have multiple fusion junctions and that these fusion junctions tend to be distributed in a nonrandom pattern at both the chromosome and gene levels. Thus, FusionPro allows users to detect various types of fusion translation products using a transcriptome-informed approach and to gain a comprehensive understanding of the formation and biological roles of fusion proteoforms.

Comprehensive map and functional annotation of the mouse white adipose tissue proteome

White adipose tissue (WAT) plays a significant role in energy metabolism and the obesity epidemic. In this study, we sought to (1) profile the mouse WAT proteome with advanced 2DLC/MS/MS approach, (2) provide insight into WAT function based on protein functional annotation, and (3) predict potentially secreted proteins. A label-free 2DLC/MS/MS proteomic approach was used to identify the WAT proteome from female mouse WAT. A total of 6,039 proteins in WAT were identified, among which 5,160 were quantified (spanning a magnitude of 10⁶) using an intensity-based absolute quantification algorithm, and 3,117 proteins were reported by proteomics technology for the first time in WAT. To comprehensively analyze the function of WAT, the proteins were divided into three quantiles based on abundance and we found that proteins of different abundance performed different functions. High-abundance proteins (the top 90%, 1,219 proteins) were involved in energy metabolism; middle-abundance proteins (90–99%, 2,273 proteins) were involved in the regulation of protein synthesis; and low-abundance proteins (99–100%, 1,668 proteins) were associated with lipid metabolism and WAT beiging. Furthermore, 800 proteins were predicted by SignalP4.0 to have signal peptides, 265 proteins had never been reported, and five have been reported as adipokines. The above results provide a large dataset of the normal mouse WAT proteome, which might be useful for WAT function research.

Diminished inhibition and facilitated activation of RyR2-mediated Ca2+ release is a common defect of arrhythmogenic calmodulin mutations

A number of calmodulin (CaM) mutations cause severe cardiac arrhythmias, but their arrhythmogenic mechanisms are unclear. While some of the arrhythmogenic CaM mutations have been shown to impair CaM-dependent inhibition of intracellular Ca²⁺ release through the ryanodine receptor type 2 (RyR2), the impact of a majority of these mutations on RyR2 function is unknown. Here, we investigated the effect of 14 arrhythmogenic CaM mutations on the CaM-dependent RyR2 inhibition. We found that all the arrhythmogenic CaM mutations tested diminished CaM-dependent inhibition of RyR2-mediated Ca²⁺ release and increased store-overload induced Ca²⁺ release (SOICR) in HEK293 cells. Moreover, all the arrhythmogenic CaM mutations tested either failed to inhibit or even promoted RyR2-mediated Ca²⁺ release in permeabilized HEK293 cells with elevated cytosolic Ca²⁺ , which was markedly different from the inhibitory action of CaM wild-type. The CaM mutations also altered the Ca²⁺ -dependency of CaM binding to the RyR2 CaM-binding domain. These results demonstrate that diminished inhibition, and even facilitated activation, of RyR2-mediated Ca²⁺ release is a common defect of arrhythmogenic CaM mutations.

A trap mutant reveals the physiological client spectrum of TRC40

The transmembrane recognition complex (TRC) pathway targets tail-anchored (TA) proteins to the membrane of the endoplasmic reticulum (ER). While many TA proteins are known to be able to use this pathway, it is essential for the targeting of only a few. Here, we uncover a large number of TA proteins that engage with TRC40 when other targeting machineries are fully operational. We use a dominant-negative ATPase-impaired mutant of TRC40 in which aspartate 74 was replaced by a glutamate residue to trap TA proteins in the cytoplasm. Manipulation of the hydrophobic TA-binding groove in TRC40 (also known as ASNA1) reduces interaction with most, but not all, substrates suggesting that co-purification may also reflect interactions unrelated to precursor protein targeting. We confirm known TRC40 substrates and identify many additional TA proteins interacting with TRC40. By using the trap approach in combination with quantitative mass spectrometry, we show that Golgi-resident TA proteins such as the golgins golgin-84, CASP and giantin as well as the vesicle-associated membrane-protein-associated proteins VAPA and VAPB interact with TRC40. Thus, our results provide new avenues to assess the essential role of TRC40 in metazoan organisms.

This article has an associated First Person interview with the first author of the paper.

Summary: A strategy to decipher which tail-anchored proteins do (as opposed to can or must) use the TRC pathway in intact cells generates a comprehensive list of human TRC40 clients.

A sensitive and simple targeted proteomics approach to quantify transcription factor and membrane proteins of the unfolded protein response pathway in glioblastoma cells

Many cellular events are driven by changes in protein expression, measurable by mass spectrometry or antibody-based assays. However, using conventional technology, the analysis of transcription factor or membrane receptor expression is often limited by an insufficient sensitivity and specificity. To overcome this limitation, we have developed a high-resolution targeted proteomics strategy, which allows quantification down to the lower attomol range in a straightforward way without any prior enrichment or fractionation approaches. The method applies isotope-labeled peptide standards for quantification of the protein of interest. As proof of principle, we applied the improved workflow to proteins of the unfolded protein response (UPR), a signaling pathway of great clinical importance, and could for the first time detect and quantify all major UPR receptors, transducers and effectors that are not readily detectable via antibody-based-, SRM- or conventional PRM assays. As transcription and translation is central to the regulation of UPR, quantification and determination of protein copy numbers in the cell is important for our understanding of the signaling process as well as how pharmacologic modulation of these pathways impacts on the signaling. These questions can be answered using our newly established workflow as exemplified in an experiment using UPR perturbation in a glioblastoma cell lines.

Proteome Analysis Using Gel-LC-MS/MS

This article describes processing of protein samples using 1D SDS gels prior to protease digestion for proteomics workflows that subsequently utilize reversed-phase nanocapillary ultra-high-pressure liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS). The resulting LC-MS/MS data are used to identify peptides and thereby infer proteins present in samples ranging from simple mixtures to very complex proteomes. Bottom-up proteome studies usually involve quantitative comparisons across several or many samples. For either situation, 1D SDS gels represent a simple, widely available technique that can be used to either fractionate complex proteomes or rapidly clean up low microgram samples with minimal losses. After gel separation and staining/destaining, appropriate gel slices are excised, and in-gel reduction, alkylation, and protease digestion are performed. Digests are then processed for LC-MS/MS analysis. Protocols are described for either sample fractionation with high-throughput processing of many samples or simple cleanup without fractionation. An optional strategy is to conduct in-solution reduction and alkylation prior to running gels, which is advantageous when a large number of samples will be separated into large numbers of fractions. Optimization of trypsin digestion parameters and comparison to in-solution protease digestion are also described. © 2019 by John Wiley & Sons, Inc.

Antibody-Driven Proximity Labeling in Fixed Tissues

Protein function often depends on assemblies and interactions. These show complex spatial and temporal organization within the cell. Analysis of protein function can be greatly assisted by grouping proteins with their neighbors. Rather than relying on affinity, proximity labeling targets proteins proximal to the target of interest. We describe a protocol for antibody-guided deposition of tags in fixed and permeabilized cell lines and primary human tissue samples.

Surface Glycoproteomic Analysis Reveals That Both Unique and Differential Expression of Surface Glycoproteins Determine the Cell Type

Proteins on the cell surface are frequently glycosylated, and they are essential for cells. Surface glycoproteins regulate nearly every extracellular event, but compared with global analysis of proteins, comprehensive and site-specific analysis of surface glycoproteins is much more challenging and dramatically understudied. Here, combining metabolic labeling, click-chemistry and enzymatic reactions, and mass spectrometry-based proteomics, we globally characterized surface glycoproteins from eight popular types of human cells. This integrative and effective method allowed for the identification of 2172 N-glycosylation sites and 1047 surface glycoproteins. The distribution and occurrence of N-glycosylation sites were systematically investigated, and protein secondary structures were found to have a dramatic influence on glycosylation sites. As expected, most sites are located on disordered regions. For the sites with the motif N-!P-C, about one-third of them are located on helix structures, while those with the motif N-!P-S/T prefer strand structures. There is almost no correlation between the number of glycosylation sites and protein length, but the number of sites corresponds well with the frequencies of the motif. Quantification results reveal that besides cell-specific glycoproteins, the uniqueness of each cell type further arises from differential expression of surface glycoproteins. The current research indicates that multiple surface glycoproteins including their abundances need to be considered for cell classification rather than a single cluster of differentiation (CD) protein normally used in conventional methods. These results provide valuable information to the glycoscience and biomedical communities and aid in the discovery of surface glycoproteins as disease biomarkers and drug targets.

New Apex in Proteome Analysis

Improved sample processing workflows enable rapid, deep analysis of human cellular and tissue proteomes.

Quantitative Proteomics of Presynaptic Mitochondria Reveal an Overexpression and Biological Relevance of Neuronal MitoNEET in Postnatal Brain Development

Although it has been recognized that energy metabolism and mitochondrial structure and functional activity in the immature brain differs from that of the adult, few studies have examined mitochondria specifically at the neuronal synapse during postnatal brain development. In this study, we examined the presynaptic mitochondrial proteome in mice at postnatal day 7 and 42, a period that involves the formation and maturation of synapses. Application of two independent quantitative proteomics approaches - SWATH-MS and super-SILAC - revealed a total of 40 proteins as significantly differentially expressed in the presynaptic mitochondria. In addition to elevated levels of proteins known to be involved in ATP metabolic processes, our results identified increased levels of mitoNEET (Cisd1), an iron-sulfur containing protein that regulates mitochondrial bioenergetics. We found that mitoNEET overexpression plays a cell-type specific role in ATP synthesis and in neuronal cells promotes ATP generation. The elevated ATP levels in SH-SY5Y neuroblastoma cells were associated with increased mitochondrial membrane potential and a fragmented mitochondrial network, further supporting a role for mitoNEET as a key regulator of mitochondrial function.

Biased signaling of G protein coupled receptors (GPCRs): Molecular determinants of GPCR/transducer selectivity and therapeutic potential

G protein coupled receptors (GPCRs) convey signals across membranes via interaction with G proteins. Originally, an individual GPCR was thought to signal through one G protein family, comprising cognate G proteins that mediate canonical receptor signaling. However, several deviations from canonical signaling pathways for GPCRs have been described. It is now clear that GPCRs can engage with multiple G proteins and the line between cognate and non-cognate signaling is increasingly blurred. Furthermore, GPCRs couple to non-G protein transducers, including β-arrestins or other scaffold proteins, to initiate additional signaling cascades. Receptor/transducer selectivity is dictated by agonist-induced receptor conformations as well as by collateral factors. In particular, ligands stabilize distinct receptor conformations to preferentially activate certain pathways, designated 'biased signaling'. In this regard, receptor sequence alignment and mutagenesis have helped to identify key receptor domains for receptor/transducer specificity. Furthermore, molecular structures of GPCRs bound to different ligands or transducers have provided detailed insights into mechanisms of coupling selectivity. However, receptor dimerization, compartmentalization, and trafficking, receptor-transducer-effector stoichiometry, and ligand residence and exposure times can each affect GPCR coupling. Extrinsic factors including cell type or assay conditions can also influence receptor signaling. Understanding these factors may lead to the development of improved biased ligands with the potential to enhance therapeutic benefit, while minimizing adverse effects. In this review, evidence for ligand-specific GPCR signaling toward different transducers or pathways is elaborated. Furthermore, molecular determinants of biased signaling toward these pathways and relevant examples of the potential clinical benefits and pitfalls of biased ligands are discussed.

Maspin binds to cardiolipin in mitochondria and triggers apoptosis

A central question in cell biology is how cells respond to stress signals and biochemically regulate apoptosis. One critical pathway involves the change of mitochondrial function and release of cytochrome c to initiate apoptosis. In response to apoptotic stimuli, we found that maspin-a noninhibitory member of the serine protease inhibitor superfamily-translocates from the cytosol to mitochondria and binds to cardiolipin in the inner mitochondrial membrane. Biolayer interferometry assay revealed that recombinant maspin binds cardiolipin with an apparent Kd,of ∼15.8 μM and competes with cytochrome c (apparent Kd of ∼1.31 μM) for binding to cardiolipin-enriched membranes. A hydrophobic, lysine-rich domain in maspin consists of 27 aa, is located at position 268-294, and is responsible for the interaction of this protein with cardiolipin. Depletion of cardiolipin in cells significantly prevents maspin binding to the inner mitochondrial membrane and decreases cytochrome c release and apoptosis. Alteration to maspin's cardiolipin binding domain changes its ability to bind cardiolipin, and tumor cells expressing this mutant have a low frequency of apoptosis. We propose a model of apoptosis in which maspin binds to cardiolipin, displaces cytochrome c from the membrane, and facilitates its release to the cytoplasm.-Mahajan, N., Hoover, B., Rajendram, M., Shi, H. Y., Kawasaki, K., Weibel, D. B., Zhang, M. Maspin binds to cardiolipin in mitochondria and triggers apoptosis.

The compromise of virtual screening and its impact on drug discovery

Introduction: Docking and structure-based virtual screening (VS) have been standard approaches in structure-based design for over two decades. However, our understanding of the limitations, potential, and strength of these techniques has enhanced, raising expectations. Areas covered: Based on a survey of reports in the past five years, we assess whether VS: (1) predicts binding poses in agreement with crystallographic data (when available); (2) is a superior screening tool, as often claimed; (3) is successful in identifying chemical scaffolds that can be starting points for subsequent lead optimization cycles. Data shows that knowledge of the target and its chemotypes in postprocessing lead to viable hits in early drug discovery endeavors. Expert opinion: VS is capable of accurate placements in the pocket for the most part, but does not consistently score screening collections accurately. What matters is capitalization on available resources to get closer to a viable lead or optimizable series. Integration of approaches, subjective hit selection guided by knowledge of the receptor or endogenous ligand, libraries driven by experimental guides, validation studies to identify the best docking/scoring that reproduces experimental findings, constraints regarding receptor-ligand interactions, thoroughly designed methodologies, and predefined cutoff scoring criteria strengthen VS's position in pharmaceutical research.

Disentangling Genetic and Environmental Effects on the Proteotypes of Individuals

Proteotypes, like genotypes, have been found to vary between individuals in several studies, but consistent molecular functional traits across studies remain to be quantified. In a meta-analysis of 11 proteomics datasets from humans and mice, we use co-variation of proteins in known functional modules across datasets and individuals to obtain a consensus landscape of proteotype variation. We find that individuals differ considerably in both protein complex abundances and stoichiometry. We disentangle genetic and environmental factors impacting these metrics, with genetic sex and specific diets together explaining 13.5% and 11.6% of the observed variation of complex abundance and stoichiometry, respectively. Sex-specific differences, for example, include various proteins and complexes, where the respective genes are not located on sex-specific chromosomes. Diet-specific differences, added to the individual genetic backgrounds, might become a starting point for personalized proteotype modulation toward desired features.

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Benchmarking of datasets on human and mouse proteotypes

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Consistent co-variation landscape of functional modules across individuals

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Protein complexes vary in their stoichiometry across individuals

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Quantifying effects of genetic sex and specific diets on complexes

TCellXTalk facilitates the detection of co-modified peptides for the study of protein post-translational modification cross-talk in T cells

MOTIVATION

Protein function is regulated by post-translational modifications (PTMs) that may act individually or interact with others in a phenomenon termed PTM cross-talk. Multiple databases have been dedicated to PTMs, including recent initiatives oriented towards the in silico prediction of PTM interactions. The study of PTM cross-talk ultimately requires experimental evidence about whether certain PTMs coexist in a single protein molecule. However, available resources do not assist researchers in the experimental detection of co-modified peptides.

RESULTS

Herein, we present TCellXTalk, a comprehensive database of phosphorylation, ubiquitination and acetylation sites in human T cells that supports the experimental detection of co-modified peptides using targeted or directed mass spectrometry. We demonstrate the efficacy of TCellXTalk and the strategy presented here in a proof of concept experiment that enabled the identification and quantification of 15 co-modified (phosphorylated and ubiquitinated) peptides from CD3 proteins of the T-cell receptor complex. To our knowledge, these are the first co-modified peptide sequences described in this widely studied cell type. Furthermore, quantitative data showed distinct dynamics for co-modified peptides upon T cell activation, demonstrating differential regulation of co-occurring PTMs in this biological context. Overall, TCellXTalk facilitates the experimental detection of co-modified peptides in human T cells and puts forward a novel and generic strategy for the study of PTM cross-talk.

AVAILABILITY AND IMPLEMENTATION

TCellXTalk is available at https://www.tcellxtalk.org. Source Code is available at https://bitbucket.org/lp-csic-uab/tcellxtalk.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Phosphoproteomic approach for agonist-specific signaling in mouse brains: mTOR pathway is involved in κ opioid aversion

Kappa opioid receptor (KOR) agonists produce analgesic and anti-pruritic effects, but their clinical application was limited by dysphoria and hallucinations. Nalfurafine, a clinically used KOR agonist, does not cause dysphoria or hallucinations at therapeutic doses in humans. We found that in CD-1 mice nalfurafine produced analgesic and anti-scratch effects dose-dependently, like the prototypic KOR agonist U50,488H. In contrast, unlike U50,488H, nalfurafine caused no aversion, anhedonia, or sedation or and a low level of motor incoordination at the effective analgesia and anti-scratch doses. Thus, we established a mouse model that recapitulated important aspects of the clinical observations. We then employed a phosphoproteomics approach to investigate mechanisms underlying differential KOR-mediated effects. A large-scale mass spectrometry (MS)-based analysis on brains revealed that nalfurafine perturbed phosphoproteomes differently from U50,488H in a brain-region specific manner after 30-min treatment. In particular, U50,488H and nalfurafine imparted phosphorylation changes to proteins found in different cellular components or signaling pathways in different brain regions. Notably, we observed that U50,488H, but not nalfurafine, activated the mammalian target of rapamycin (mTOR) pathway in the striatum and cortex. Inhibition of the mTOR pathway by rapamycin abolished U50,488H-induced aversion, without affecting analgesic, anti-scratch, and sedative effects and motor incoordination. The results indicate that the mTOR pathway is involved in KOR agonist-induced aversion. This is the first demonstration that phosphoproteomics can be applied to agonist-specific signaling of G protein-coupled receptors (GPCRs) in mouse brains to unravel pharmacologically important pathways. Furthermore, this is one of the first two reports that the mTOR pathway mediates aversion caused by KOR activation.

Proteomic Analysis of Human Plasma during Intermittent Fasting

Intermittent fasting (IF) increases lifespan and decreases metabolic disease phenotypes and cancer risk in model organisms, but the health benefits of IF in humans are less clear. Human plasma derived from clinical trials is one of the most difficult sample sets to analyze using mass spectrometry-based proteomics due to the extensive sample preparation required and the need to process many samples to achieve statistical significance. Here, we describe an optimized and accessible device (Spin96) to accommodate up to 96 StageTips, a widely used sample preparation medium enabling efficient and consistent processing of samples prior to LC-MS/MS. We have applied this device to the analysis of human plasma from a clinical trial of IF. In this longitudinal study employing 8-weeks IF, we identified significant abundance differences induced by the IF intervention, including increased apolipoprotein A4 (APOA4) and decreased apolipoprotein C2 (APOC2) and C3 (APOC3). These changes correlated with a significant decrease in plasma triglycerides after the IF intervention. Given that these proteins have a role in regulating apolipoprotein particle metabolism, we propose that IF had a positive effect on lipid metabolism through modulation of HDL particle size and function. In addition, we applied a novel human protein variant database to detect common protein variants across the participants. We show that consistent detection of clinically relevant peptides derived from both alleles of many proteins is possible, including some that are associated with human metabolic phenotypes. Together, these findings illustrate the power of accessible workflows for proteomics analysis of clinical samples to yield significant biological insight.

Biased Receptor Signaling in Drug Discovery

A great deal of experimental evidence suggests that ligands can stabilize different receptor active states that go on to interact with cellular signaling proteins to form a range of different complexes in varying quantities. In pleiotropically linked receptor systems, this leads to selective activation of some signaling pathways at the expense of others (biased signaling). This article summarizes the current knowledge about the complex components of receptor systems, the evidence that biased signaling is used in natural physiology to fine-tune signaling, and the current thoughts on how this mechanism may be applied to the design of better drugs. Although this is a fairly newly discovered phenomenon, theoretical and experimental data suggest that it is a ubiquitous behavior of ligands and receptors and to be expected. Biased signaling is simple to detect in vitro and there are numerous methods to quantify the effect with scales that can be used to optimize this activity in structure-activity medicinal chemistry studies. At present, the major hurdle in the application of this mechanism to therapeutics is the translation of in vitro bias to in vivo effect; this is because of the numerous factors that can modify measures of bias in natural physiologic systems. In spite of this, biased signaling still has the potential to justify revisiting of receptor targets previously thought to be intractable and also furnishes the means to pursue targets previously thought to be forbidden due to deleterious physiology (as these may be eliminated through biased signaling).

Native Nanodiscs and the Convergence of Lipidomics, Metabolomics, Interactomics and Proteomics

The omics disciplines remain largely distinct sciences due to the necessity of separating molecular classes for different assays. For example, water-soluble and lipid bilayer-bound proteins and metabolites are usually studied separately. Nonetheless, it is at the interface between these sciences where biology happens. That is, lipid-interacting proteins typically recognize and transduce signals and regulate the flow of metabolites in the cell. Technologies are emerging to converge the omics. It is now possible to separate intact membrane:protein assemblies (memteins) directly from intact cells or cell membranes. Such complexes mediate complete metabolon, receptor, channel, and transporter functions. The use of poly(styrene-co-maleic acid) (SMA) copolymers has allowed their separation in a single step without any exposure to synthetic detergents or artificial lipids. This is a critical development as these agents typically strip away biological lipids, signals, and metabolites from their physiologically-relevant positions on proteins. The resulting SMA lipid particles (SMALPs) represent native nanodiscs that are suitable for elucidation of structures and interactions that occur in vivo. Compatible tools for resolving the contained memteins include X-ray diffraction (XRD), cryo-electron microscopy (cryoEM), mass spectrometry (MS), and nuclear magnetic resonance (NMR) spectroscopy. Recent progress shows that memteins are more representative than naked membrane proteins devoid of natural lipid and is driving the development of next generation polymers.

Human leukemia cells (HL-60) proteomic and biological signatures underpinning cryo-damage are differentially modulated by novel cryo-additives

BACKGROUND

Cryopreservation is a routinely used methodology for prolonged storage of viable cells. The use of cryo-protective agents (CPAs) such as dimethylsulfoxide (DMSO), glycerol, or trehalose is paramount to reducing cellular cryo-injury, but their effectiveness is still limited. The current study focuses on establishing and modulating the proteomic and the corresponding biological profiles associated with the cryo-injury of human leukemia (HL-60) cells cryopreserved in DMSO alone or DMSO +/- novel CPAs (e.g., nigerose [Nig] or salidroside [Sal]).

FINDINGS

To reduce cryo-damage, HL-60 cells were cultured prior and post cryopreservation in malondialdehyde Roswell Park Memorial Institute medium-1640 media +/- Nig or Sal. Shotgun proteomic analysis showed significant alterations in the levels of proteins in cells cryopreserved in Nig or Sal compared to DMSO. Nig mostly affected cellular metabolism and energy pathways, whereas Sal increased the levels of proteins associated with DNA repair/duplication, RNA transcription, and cell proliferation. Validation testing showed that the proteome profile associated with Sal was correlated with a 2.8-fold increase in cell proliferative rate. At the functional level, both Nig and Sal increased glutathione reductase (0.0012±6.19E-05 and 0.0016±3.04E-05 mU/mL, respectively) compared to DMSO controls (0.0003±3.7E-05 mU/mL) and reduced cytotoxicity by decreasing lactate dehydrogenase activities (from -2.5 to -4.75 fold) and lipid oxidation (-1.6 fold). In contrast, only Nig attenuated protein carbonylation or oxidation.

CONCLUSIONS

We have identified key molecules and corresponding functional pathways underpinning the effect of cryopreservation (+/- CPAs) of HL-60 cells. We also validated the proteomic findings by identifying the corresponding biological profiles associated with promoting an anti-oxidative environment post cryopreservation. Nig or Sal in comparison to DMSO showed differential or additive effects in regard to reducing cryo-injury and enhancing cell survival/proliferation post thaw. These results can provide useful insight to cryo-damage and the design of enhanced cryomedia formulation.

Purification of cross-linked RNA-protein complexes by phenol-toluol extraction

Recent methodological advances allowed the identification of an increasing number of RNA-binding proteins (RBPs) and their RNA-binding sites. Most of those methods rely, however, on capturing proteins associated to polyadenylated RNAs which neglects RBPs bound to non-adenylate RNA classes (tRNA, rRNA, pre-mRNA) as well as the vast majority of species that lack poly-A tails in their mRNAs (including all archea and bacteria). We have developed the Phenol Toluol extraction (PTex) protocol that does not rely on a specific RNA sequence or motif for isolation of cross-linked ribonucleoproteins (RNPs), but rather purifies them based entirely on their physicochemical properties. PTex captures RBPs that bind to RNA as short as 30 nt, RNPs directly from animal tissue and can be used to simplify complex workflows such as PAR-CLIP. Finally, we provide a global RNA-bound proteome of human HEK293 cells and the bacterium Salmonella Typhimurium.

Chemically reprogramming the phospho-transfer reaction to crosslink protein kinases to their substrates

The proteomic mapping of enzyme-substrate interactions is challenged by their transient nature. A method to capture interacting protein kinases in complexes with a single substrate of interest would provide a new tool for mapping kinase signaling networks. Here, we describe a nucleotide-based substrate analog capable of reprogramming the wild-type phosphoryl-transfer reaction to produce a kinase-acrylamide-based thioether crosslink to mutant substrates with a cysteine nucleophile substituted at the native phosphorylation site. A previously reported ATP-based methacrylate crosslinker (ATP-MA) was capable of mediating kinase crosslinking to short peptides but not protein substrates. Exploration of structural variants of ATP-MA to enable crosslinking of protein substrates to kinases led to the discovery that an ADP-based methacrylate (ADP-MA) crosslinker was superior to the ATP scaffold at crosslinking in vitro. The improved efficiency of ADP-MA over ATP-MA is due to reduced inhibition of the second step of the kinase-substrate crosslinking reaction by the product of the first step of the reaction. The new probe, ADP-MA, demonstrated enhanced in vitro crosslinking between the Src tyrosine kinase and its substrate Cortactin in a phosphorylation site-specific manner. The kinase-substrate crosslinking reaction can be carried out in a complex mammalian cell lysate setting, although the low abundance of endogenous kinases remains a significant challenge for efficient capture.

A Dual-Purpose Bromocoumarin Tag Enables Deep Profiling of the Cellular Cysteinome

Chemical proteomics enables comprehensive profiling of small molecules in complex proteomes. A critical component to understand the interactome of a small molecule is the precise location on a protein where the interaction takes place. Several approaches have been developed that take advantage of bio-orthogonal chemistry and subsequent enrichment steps to isolate peptides modified by small molecules. These methods rely on target identification at the level of mass spectrometry making it difficult to interpret an experiment when modified peptides are not identified. Herein, an approach in which fluorescence-triggered two-dimensional chromatography enables the isolation of small molecule-conjugated peptides prior to mass spectrometry analysis is described. In this study, a bromocoumarin moiety has been utilized that fluoresces and generates a distinct isotopic signature to locate and identify modified peptides. Profiling of a cellular cysteinome with the use of a bromocoumarin tag demonstrates that two-dimensional fluorescence-based chromatography separation can enable the identification of proteins containing reactive cysteine residues. Moreover, the method facilitates the interrogation of low abundance proteins with greater depth and sensitivity than a previously reported isotope-targeted approach. Lastly, this workflow enables the identification of small-molecule modified peptides from a protein-of-interest.

MaxQuant.Live Enables Global Targeting of More Than 25,000 Peptides

Mass spectrometry (MS)-based proteomics is often performed in a shotgun format, in which as many peptide precursors as possible are selected from full or MS1 scans so that their fragment spectra can be recorded in MS2 scans. Although achieving great proteome depths, shotgun proteomics cannot guarantee that each precursor will be fragmented in each run. In contrast, targeted proteomics aims to reproducibly and sensitively record a restricted number of precursor/fragment combinations in each run, based on prescheduled mass-to-charge and retention time windows. Here we set out to unify these two concepts by a global targeting approach in which an arbitrary number of precursors of interest are detected in real-time, followed by standard fragmentation or advanced peptide-specific analyses. We made use of a fast application programming interface to a quadrupole Orbitrap instrument and real-time recalibration in mass, retention time and intensity dimensions to predict precursor identity. MaxQuant.Live is freely available (www.maxquant.live) and has a graphical user interface to specify many predefined data acquisition strategies. Acquisition speed is as fast as with the vendor software and the power of our approach is demonstrated with the acquisition of breakdown curves for hundreds of precursors of interest. We also uncover precursors that are not even visible in MS1 scans, using elution time prediction based on the auto-adjusted retention time alone. Finally, we successfully recognized and targeted more than 25,000 peptides in single LC-MS runs. Global targeting combines the advantages of two classical approaches in MS-based proteomics, whereas greatly expanding the analytical toolbox.

New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling

RAS is the most frequently mutated gene across human cancers, but developing inhibitors of mutant RAS has proven to be challenging. Given the difficulties of targeting RAS directly, drugs that impact the other components of pathways where mutant RAS operates may potentially be effective. However, the system-level features, including different localizations of RAS isoforms, competition between downstream effectors, and interlocking feedback and feed-forward loops, must be understood to fully grasp the opportunities and limitations of inhibiting specific targets. Mathematical modeling can help us discern the system-level impacts of these features in normal and cancer cells. New technologies enable the acquisition of experimental data that will facilitate development of realistic models of oncogenic RAS behavior. In light of the wealth of empirical data accumulated over decades of study and the advancement of experimental methods for gathering new data, modelers now have the opportunity to advance progress toward realization of targeted treatment for mutant RAS-driven cancers.

Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics

The study of protein localisation has greatly benefited from high-throughput methods utilising cellular fractionation and proteomic profiling. Hyperplexed Localisation of Organelle Proteins by Isotope Tagging (hyperLOPIT) is a well-established method in this area. It achieves high-resolution separation of organelles and subcellular compartments but is relatively time- and resource-intensive. As a simpler alternative, we here develop Localisation of Organelle Proteins by Isotope Tagging after Differential ultraCentrifugation (LOPIT-DC) and compare this method to the density gradient-based hyperLOPIT approach. We confirm that high-resolution maps can be obtained using differential centrifugation down to the suborganellar and protein complex level. HyperLOPIT and LOPIT-DC yield highly similar results, facilitating the identification of isoform-specific localisations and high-confidence localisation assignment for proteins in suborganellar structures, protein complexes and signalling pathways. By combining both approaches, we present a comprehensive high-resolution dataset of human protein localisations and deliver a flexible set of protocols for subcellular proteomics.

Modeling cell line-specific recruitment of signaling proteins to the insulin-like growth factor 1 receptor

Receptor tyrosine kinases (RTKs) typically contain multiple autophosphorylation sites in their cytoplasmic domains. Once activated, these autophosphorylation sites can recruit downstream signaling proteins containing Src homology 2 (SH2) and phosphotyrosine-binding (PTB) domains, which recognize phosphotyrosine-containing short linear motifs (SLiMs). These domains and SLiMs have polyspecific or promiscuous binding activities. Thus, multiple signaling proteins may compete for binding to a common SLiM and vice versa. To investigate the effects of competition on RTK signaling, we used a rule-based modeling approach to develop and analyze models for ligand-induced recruitment of SH2/PTB domain-containing proteins to autophosphorylation sites in the insulin-like growth factor 1 (IGF1) receptor (IGF1R). Models were parameterized using published datasets reporting protein copy numbers and site-specific binding affinities. Simulations were facilitated by a novel application of model restructuration, to reduce redundancy in rule-derived equations. We compare predictions obtained via numerical simulation of the model to those obtained through simple prediction methods, such as through an analytical approximation, or ranking by copy number and/or K_D value, and find that the simple methods are unable to recapitulate the predictions of numerical simulations. We created 45 cell line-specific models that demonstrate how early events in IGF1R signaling depend on the protein abundance profile of a cell. Simulations, facilitated by model restructuration, identified pairs of IGF1R binding partners that are recruited in anti-correlated and correlated fashions, despite no inclusion of cooperativity in our models. This work shows that the outcome of competition depends on the physicochemical parameters that characterize pairwise interactions, as well as network properties, including network connectivity and the relative abundances of competitors.

Cells rely on networks of interacting biomolecules to sense and respond to environmental perturbations and signals. However, it is unclear how information is processed to generate appropriate and specific responses to signals, especially given that these networks tend to share many components. For example, receptors that detect distinct ligands and regulate distinct cellular activities commonly interact with overlapping sets of downstream signaling proteins. Here, to investigate the downstream signaling of a well-studied receptor tyrosine kinase (RTK), the insulin-like growth factor 1 (IGF1) receptor (IGF1R), we formulated and analyzed 45 cell line-specific mathematical models, which account for recruitment of 18 different binding partners to six sites of receptor autophosphorylation in IGF1R. The models were parameterized using available protein copy number and site-specific affinity measurements, and restructured to allow for network generation. We find that recruitment is influenced by the protein abundance profile of a cell, with different patterns of recruitment in different cell lines. Furthermore, in a given cell line, we find that pairs of IGF1R binding partners may be recruited in a correlated or anti-correlated fashion. We demonstrate that the simulations of the model have greater predictive power than protein copy number and/or binding affinity data, and that even a simple analytical model cannot reproduce the predicted recruitment ranking obtained via simulations. These findings represent testable predictions and indicate that the outputs of IGF1R signaling depend on cell line-specific properties in addition to the properties that are intrinsic to the biomolecules involved.

CYC27 Synthetic Derivative of Bromophenol from Red Alga Rhodomela confervoides: Anti-Diabetic Effects of Sensitizing Insulin Signaling Pathways and Modulating RNA Splicing-Associated RBPs

RNA-binding proteins (RBPs) lie at the center of posttranscriptional regulation and the dysregulation of RBPs contributes to diabetes. Therefore, the modulation of RBPs is anticipated to become a potential therapeutic approach to diabetes. CYC27 is a synthetic derivative of marine bromophenol BDB, which is isolated from red alga Rhodomela confervoides. In this study, we found that CYC27 significantly lowered the blood glucose levels of diabetic BKS db mice. Moreover, CYC27 effectively ameliorated dyslipidemia in BKS db mice by reducing their total serum cholesterol (TC) and triglyceride (TG) levels. Furthermore, CYC27 was an insulin-sensitizing agent with increased insulin-stimulated phosphorylation of insulin receptors and relevant downstream factors. Finally, to systemically study the mechanisms of CYC27, label-free quantitative phosphoproteomic analysis was performed to investigate global changes in phosphorylation. Enriched GO annotation showed that most regulated phosphoproteins were related to RNA splicing and RNA processing. Enriched KEGG analysis showed that a spliceosome-associated pathway was the predominant pathway after CYC27 treatment. Protein-protein interaction (PPI) analysis showed that CYC27 modulated the process of mRNA splicing via phosphorylation of the relevant RBPs, including upregulated Cstf3 and Srrt. Our results suggested that CYC27 treatment exerted promising anti-diabetic effects by sensitizing the insulin signaling pathways and modulating RNA splicing-associated RBPs.

The Human RNA-Binding Proteome and Its Dynamics during Translational Arrest

Proteins and RNA functionally and physically intersect in multiple biological processes, however, currently no universal method is available to purify protein-RNA complexes. Here, we introduce XRNAX, a method for the generic purification of protein-crosslinked RNA, and demonstrate its versatility to study the composition and dynamics of protein-RNA interactions by various transcriptomic and proteomic approaches. We show that XRNAX captures all RNA biotypes and use this to characterize the sub-proteomes that interact with coding and non-coding RNAs (ncRNAs) and to identify hundreds of protein-RNA interfaces. Exploiting the quantitative nature of XRNAX, we observe drastic remodeling of the RNA-bound proteome during arsenite-induced stress, distinct from autophagy-related changes in the total proteome. In addition, we combine XRNAX with crosslinking immunoprecipitation sequencing (CLIP-seq) to validate the interaction of ncRNA with lamin B1 and EXOSC2. Thus, XRNAX is a resourceful approach to study structural and compositional aspects of protein-RNA interactions to address fundamental questions in RNA-biology.

Subcellular transcriptomes and proteomes of developing axon projections in the cerebral cortex

The development of neural circuits relies on axon projections establishing diverse, yet well-defined, connections between areas of the nervous system. Each projection is formed by growth cones-subcellular specializations at the tips of growing axons, encompassing sets of molecules that control projection-specific growth, guidance, and target selection¹. To investigate the set of molecules within native growth cones that form specific connections, here we developed growth cone sorting and subcellular RNA-proteome mapping, an approach that identifies and quantifies local transcriptomes and proteomes from labelled growth cones of single projections in vivo. Using this approach on the developing callosal projection of the mouse cerebral cortex, we mapped molecular enrichments in trans-hemispheric growth cones relative to their parent cell bodies, producing paired subcellular proteomes and transcriptomes from single neuron subtypes directly from the brain. These data provide generalizable proof-of-principle for this approach, and reveal molecular specializations of the growth cone, including accumulations of the growth-regulating kinase mTOR², together with mRNAs that contain mTOR-dependent motifs^3,4. These findings illuminate the relationships between subcellular distributions of RNA and protein in developing projection neurons, and provide a systems-level approach for the discovery of subtype- and stage-specific molecular substrates of circuit wiring, miswiring, and the potential for regeneration.

Comprehensive identification of RNA-protein interactions in any organism using orthogonal organic phase separation (OOPS)

Existing high-throughput methods to identify RNA-binding proteins (RBPs) are based on capture of polyadenylated RNAs and cannot recover proteins that interact with nonadenylated RNAs, including long noncoding RNA, pre-mRNAs and bacterial RNAs. We present orthogonal organic phase separation (OOPS), which does not require molecular tagging or capture of polyadenylated RNA, and apply it to recover cross-linked protein-RNA and free protein, or protein-bound RNA and free RNA, in an unbiased way. We validated OOPS in HEK293, U2OS and MCF10A human cell lines, and show that 96% of proteins recovered were bound to RNA. We show that all long RNAs can be cross-linked to proteins, and recovered 1,838 RBPs, including 926 putative novel RBPs. OOPS is approximately 100-fold more efficient than existing methods and can enable analyses of dynamic RNA-protein interactions. We also characterize dynamic changes in RNA-protein interactions in mammalian cells following nocodazole arrest, and present a bacterial RNA-interactome for Escherichia coli. OOPS is compatible with downstream proteomics and RNA sequencing, and can be applied in any organism.

Application of a Sensitive and Reproducible Label-Free Proteomic Approach to Explore the Proteome of Individual Meiotic-Phase Barley Anthers

Meiosis is a highly dynamic and precisely regulated process of cell division, leading to the production of haploid gametes from one diploid parental cell. In the crop plant barley (Hordeum vulgare), male meiosis occurs in anthers, in specialized cells called meiocytes. Barley meiotic tissue is scarce and not easily accessible, making meiosis study a challenging task. We describe here a new micro-proteomics workflow that allows sensitive and reproducible genome-wide label-free proteomic analysis of individual staged barley anthers. This micro-proteomic approach detects more than 4,000 proteins from such small amounts of material as two individual anthers, covering a dynamic range of protein relative abundance levels across five orders of magnitude. We applied our micro-proteomics workflow to investigate the proteome of the developing barley anther containing pollen mother cells in the early stages of meiosis and we successfully identified 57 known and putative meiosis-related proteins. Meiotic proteins identified in our study were found to be key players of many steps and processes in early prophase such as: chromosome condensation, synapsis, DNA double-strand breaks or crossover formation. Considering the small amount of starting material, this work demonstrates an important technological advance in plant proteomics and can be applied for proteomic examination of many size-limited plant specimens. Moreover, it is the first insight into the proteome of individual barley anther at early meiosis. The proteomic data have been deposited to the ProteomeXchange with the accession number PXD010887.

An Overview of Mass Spectrometry-Based Methods for Functional Proteomics

The mechanism underlying many biological phenotypes remains unknown despite the increasing availability of whole genome and transcriptome sequencing. Direct measurement of changes in protein expression is an attractive alternative and has the potential to reveal novel processes. Mass spectrometry has become the standard method for proteomics, allowing both the confident identification and quantification of thousands of proteins from biological samples. In this review, mass spectrometry-based proteomic methods and their applications are described.

Network-Guided Discovery of Influenza Virus Replication Host Factors

Integrating virus-host interactions with host protein-protein interactions, we have created a method using these established network practices to identify host factors (i.e., proteins) that are likely candidates for antiviral drug targeting. We demonstrate that interaction cascades between host proteins that directly interact with viral proteins and host factors that are important to influenza virus replication are enriched for signaling and immune processes. Additionally, we show that host proteins that interact with viral proteins are in network locations of power. Finally, we demonstrate a new network methodology to predict novel host factors and validate predictions with an siRNA screen. Our results show that integrating virus-host proteins interactions is useful in the identification of antiviral drug target candidates.

The positions of host factors required for viral replication within a human protein-protein interaction (PPI) network can be exploited to identify drug targets that are robust to drug-mediated selective pressure. Host factors can physically interact with viral proteins, be a component of virus-regulated pathways (where proteins do not interact with viral proteins), or be required for viral replication but unregulated by viruses. Here, we demonstrate a method of combining human PPI networks with virus-host PPI data to improve antiviral drug discovery for influenza viruses by identifying target host proteins. Analysis shows that influenza virus proteins physically interact with host proteins in network positions significant for information flow, even after the removal of known abundance-degree bias within PPI data. We have isolated a subnetwork of the human PPI network that connects virus-interacting host proteins to host factors that are important for influenza virus replication without physically interacting with viral proteins. The subnetwork is enriched for signaling and immune processes distinct from those associated with virus-interacting proteins. Selecting proteins based on subnetwork topology, we performed an siRNA screen to determine whether the subnetwork was enriched for virus replication host factors and whether network position within the subnetwork offers an advantage in prioritization of drug targets to control influenza virus replication. We found that the subnetwork is highly enriched for target host proteins—more so than the set of host factors that physically interact with viral proteins. Our findings demonstrate that network positions are a powerful predictor to guide antiviral drug candidate prioritization.

Improved SILAC method for double labeling of bacterial proteome

Stable isotope labeling with amino acids in cell culture (SILAC) is a robust proteomics method with advantages such as reproducibility and easy handling. This method is popular for the analysis of mammalian cells. However, amino acid conversion in bacteria decreases the labeling efficiency and quantification accuracy, limiting the application of SILAC in bacterial proteomics to auxotrophic bacteria or to single labeling with lysine. In this study, we found that adding high concentrations of isotope-labeled (heavy) and natural (light) amino acids into SILAC minimal medium can efficiently inhibit the complicated amino acid conversions. This simple and straightforward strategy facilitated complete incorporation of amino acids into the bacterial proteome with good accuracy. High labeling efficiency can be achieved in different bacteria by slightly modifying the supplementation of amino acids in culture media, promoting the widespread application of SILAC technique in bacterial proteomics. SIGNIFICANCE: Amino acid conversion in bacteria decreases labeling efficiency, limiting the application of Stable isotope labeling with amino acids in cell culture (SILAC) in bacterial proteomics to auxotrophic bacteria or single labeling with lysine. In this study, we found that high concentrations of isotope-labeled (heavy) and natural (light) amino acids facilitate full incorporation of amino acids into the bacterial proteome with good reproducibility. This improved double labeling SILAC technique using medium supplemented with high concentrations of amino acids is suitable for quantitative proteomics research on both gram-positive and -negative bacteria, facilitating the broad application of quantitative proteomics in bacterial studies.

Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins

Quantitative proteomics has been extensively applied in the screening of differentially regulated proteins in various research areas for decades, but its sensitivity and accuracy have been a bottleneck for many applications. Every step in the proteomics workflow can potentially affect the quantification of low-abundance proteins, but a systematic evaluation of their effects has not been done yet. In this work, to improve the sensitivity and accuracy of label-free quantification and tandem mass tags (TMT) labeling in quantifying low-abundance proteins, multiparameter optimization was carried out using a complex 2-proteome artificial sample mixture for a series of steps from sample preparation to data analysis, including the desalting of peptides, peptide injection amount for LC-MS/MS, MS1 resolution, the length of LC-MS/MS gradient, AGC targets, ion accumulation time, MS2 resolution, precursor coisolation threshold, data analysis software, statistical calculation methods, and protein fold changes, and the best settings for each parameter were defined. The suitable cutoffs for detecting low-abundance proteins with at least 1.5-fold and 2-fold changes were identified for label-free and TMT methods, respectively. The use of optimized parameters will significantly improve the overall performance of quantitative proteomics in quantifying low-abundance proteins and thus promote its application in other research areas.

The human olfactory cleft mucus proteome and its age-related changes

Age-related decreases in olfactory sensitivity are often accompanied by a decrease in the quality of life. However, the molecular mechanisms underlying these changes are not well described. Inhaled substances including odorants are detected by sensory neurons in the olfactory cleft covered with a layer of mucus. This olfactory mucus is the first molecular machinery responsible for tissue protection and for detection of environmental odorants. Yet, little is known about the molecular identities of the actors because of the lack of information on the mucus proteome and its age-related changes. Here, we sampled human mucus from different nasal locations and from young and elderly subjects. The composition of the mucus was extensively analyzed by shotgun proteomic analysis for a vast array of proteins. We also explored correlations between the levels of each mucus proteins with the olfactory sensitivity of subjects. This analysis revealed previously unrecognized proteins with potentially important functions in olfaction. Taken together, this report describes the most comprehensive catalogue of the nasal mucus proteins to date, their positional and age-related differences, and candidate proteins associated with olfaction. This catalogue will provide fundamental information useful for future studies, such as identification of olfactory auxiliary proteins, causes of age-related declines in olfaction, and biomarkers for neurodegenerative disorders.