Assembly of a GPCR-G Protein Complex.

The activation of G proteins by G protein-coupled receptors (GPCRs) underlies the majority of transmembrane signaling by hormones and neurotransmitters. Recent structures of GPCR-G protein complexes obtained by crystallography and cryoelectron microscopy (cryo-EM) reveal similar interactions between GPCRs and the alpha subunit of different G protein isoforms. While some G protein subtype-specific differences are observed, there is no clear structural explanation for G protein subtype-selectivity. All of these complexes are stabilized in the nucleotide-free state, a condition that does not exist in living cells. In an effort to better understand the structural basis of coupling specificity, we used time-resolved structural mass spectrometry techniques to investigate GPCR-G protein complex formation and G-protein activation. Our results suggest that coupling specificity is determined by one or more transient intermediate states that serve as selectivity filters and precede the formation of the stable nucleotide-free GPCR-G protein complexes observed in crystal and cryo-EM structures.

Temporal and Sex-Linked Protein Expression Dynamics in a Familial Model of Alzheimer's Disease.

Mouse models of Alzheimer's disease (AD) show progression through stages reflective of human pathology. Proteomics identification of temporal and sex-linked factors driving AD-related pathways can be used to dissect initiating and propagating events of AD stages to develop biomarkers or design interventions. In the present study, we conducted label-free proteome measurements of mouse hippocampus tissue with variables of time (3, 6, and 9 months), genetic background (5XFAD versus WT), and sex (equal males and females). These time points are associated with well-defined phenotypes with respect to the following: Aß42 plaque deposition, memory deficits, and neuronal loss, allowing correlation of proteome-based molecular signatures with the mouse model stages. Our data show 5XFAD mice exhibit increases in known human AD biomarkers as amyloid-beta peptide, APOE, GFAP, and ITM2B are upregulated across all time points/stages. At the same time, 23 proteins are here newly associated with Alzheimer's pathology as they are also dysregulated in 5XFAD mice. At a pathways level, the 5XFAD-specific upregulated proteins are significantly enriched for DNA damage and stress-induced senescence at 3-month only, while at 6-month, the AD-specific proteome signature is altered and significantly enriched for membrane trafficking and vesicle-mediated transport protein annotations. By 9-month, AD-specific dysregulation is also characterized by significant neuroinflammation with innate immune system, platelet activation, and hyper-reactive astrocyte-related enrichments. Aside from these temporal changes, analysis of sex-linked differences in proteome signatures uncovered novel sex and AD-associated proteins. Pathway analysis revealed sex-linked differences in the 5XFAD model to be involved in the regulation of well-known human AD-related processes of amyloid fibril formation, wound healing, lysosome biogenesis, and DNA damage. Verification of the discovery results by Western blot and parallel reaction monitoring confirm the fundamental conclusions of the study and poise the 5XFAD model for further use as a molecular tool for understanding AD.

Methionine Sulfoxide Speciation in Mouse Hippocampus Revealed by Global Proteomics Exhibits Age- and Alzheimer's Disease-Dependent Changes Targeted to Mitochondrial and Glycolytic Pathways.

Methionine oxidation to the sulfoxide form (MSox) is a poorly understood post-translational modification of proteins associated with non-specific chemical oxidation from reactive oxygen species (ROS), whose chemistries are linked to various disease pathologies, including neurodegeneration. Emerging evidence shows MSox site occupancy is, in some cases, under enzymatic regulatory control, mediating cellular signaling, including phosphorylation and/or calcium signaling, and raising questions as to the speciation and functional nature of MSox across the proteome. The 5XFAD lineage of the C57BL/6 mouse has well-defined Alzheimer's and aging states. Using this model, we analyzed age-, sex-, and disease-dependent MSox speciation in the mouse hippocampus. In addition, we explored the chemical stability and statistical variance of oxidized peptide signals to understand the needed power for MSox-based proteome studies. Our results identify mitochondrial and glycolytic pathway targets with increases in MSox with age as well as neuroinflammatory targets accumulating MSox with AD in proteome studies of the mouse hippocampus. Further, this paper establishes a foundation for reproducible and rigorous experimental MSox-omics appropriate for novel target identification in biological discovery and for biomarker analysis in ROS and other oxidation-linked diseases.

Intact mass spectrometry screening to optimize hydroxyl radical dose for protein footprinting.

Hydroxyl radical protein footprinting (HRPF) using synchrotron radiation is a well-validated method to assess protein structure in the native solution state. In this method, X-ray radiolysis of water generates hydroxyl radicals that can react with solvent accessible side chains of proteins, with mass spectrometry used to detect the resulting labeled products. An ideal footprinting dose provides sufficient labeling to measure the structure but not so much as to influence the results. The optimization of hydroxyl radical dose is typically performed using an indirect Alexa488 fluorescence assay sensitive to hydroxyl radical concentration, but full evaluation of the experiment's outcome relies upon bottom-up liquid chromatography mass spectrometry (LC-MS) measurements to directly determine sites and extent of oxidative labeling at the peptide and protein level. A direct evaluation of the extent of labeling to provide direct and absolute measurements of dose and "safe" dose ranges in terms of, for example, average numbers of labels per protein, would provide immediate feedback on experimental outcomes prior to embarking on detailed LC-MS analyses. To this end, we describe an approach to integrate intact MS screening of labeled samples immediately following exposure, along with metrics to quantify the extent of observed labeling from the intact mass spectra. Intact MS results on the model protein lysozyme were evaluated in the context of Alexa488 assay results and a bottom-up LC-MS analysis of the same samples. This approach provides a basis for placing delivered hydroxyl radical dose metrics on firmer technical grounds for synchrotron X-ray footprinting of proteins, with explicit parameters to increase the likelihood of a productive experimental outcome. Further, the method directs approaches to provide absolute and direct dosimetry for all types of labeling for protein footprinting.

Functional characterization of co-phosphorylation networks.

MOTIVATION: Protein phosphorylation is a ubiquitous regulatory mechanism that plays a central role in cellular signaling. According to recent estimates, up to 70% of human proteins can be phosphorylated. Therefore, the characterization of phosphorylation dynamics is critical for understanding a broad range of biological and biochemical processes. Technologies based on mass spectrometry are rapidly advancing to meet the needs for high-throughput screening of phosphorylation. These technologies enable untargeted quantification of thousands of phosphorylation sites in a given sample. Many labs are already utilizing these technologies to comprehensively characterize signaling landscapes by examining perturbations with drugs and knockdown approaches, or by assessing diverse phenotypes in cancers, neuro-degerenational diseases, infectious diseases and normal development. RESULTS: We comprehensively investigate the concept of 'co-phosphorylation' (Co-P), defined as the correlated phosphorylation of a pair of phosphosites across various biological states. We integrate nine publicly available phosphoproteomics datasets for various diseases (including breast cancer, ovarian cancer and Alzheimer's disease) and utilize functional data related to sequence, evolutionary histories, kinase annotations and pathway annotations to investigate the functional relevance of Co-P. Our results across a broad range of studies consistently show that functionally associated sites tend to exhibit significant positive or negative Co-P. Specifically, we show that Co-P can be used to predict with high precision the sites that are on the same pathway or that are targeted by the same kinase. Overall, these results establish Co-P as a useful resource for analyzing phosphoproteins in a network context, which can help extend our knowledge on cellular signaling and its dysregulation. AVAILABILITY AND IMPLEMENTATION: github.com/msayati/Cophosphorylation. This research used the publicly available datasets published by other researchers as cited in the manuscript. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Structurally distinct external solvent-exposed domains drive replication of major human prions.

There is a limited understanding of structural attributes that encode the iatrogenic transmissibility and various phenotypes of prions causing the most common human prion disease, sporadic Creutzfeldt-Jakob disease (sCJD). Here we report the detailed structural differences between major sCJD MM1, MM2, and VV2 prions determined with two complementary synchrotron hydroxyl radical footprinting techniques-mass spectrometry (MS) and conformation dependent immunoassay (CDI) with a panel of Europium-labeled antibodies. Both approaches clearly demonstrate that the phenotypically distant prions differ in a major way with regard to their structural organization, and synchrotron-generated hydroxyl radicals progressively inhibit their seeding potency in a strain and structure-specific manner. Moreover, the seeding rate of sCJD prions is primarily determined by strain-specific structural organization of solvent-exposed external domains of human prion particles that control the seeding activity. Structural characteristics of human prion strains suggest that subtle changes in the organization of surface domains play a critical role as a determinant of human prion infectivity, propagation rate, and targeting of specific brain structures.

The inducible kinase IKKi is required for IL-17-dependent signaling associated with neutrophilia and pulmonary inflammation.

Interleukin 17 (IL-17) is critical in the pathogenesis of inflammatory and autoimmune diseases. Here we report that Act1, the key adaptor for the IL-17 receptor (IL-7R), formed a complex with the inducible kinase IKKi after stimulation with IL-17. Through the use of IKKi-deficient mice, we found that IKKi was required for IL-17-induced expression of genes encoding inflammatory molecules in primary airway epithelial cells, neutrophilia and pulmonary inflammation. IKKi deficiency abolished IL-17-induced formation of the complex of Act1 and the adaptors TRAF2 and TRAF5, activation of mitogen-activated protein kinases (MAPKs) and mRNA stability, whereas the Act1-TRAF6-transcription factor NF-κB axis was retained. IKKi was required for IL-17-induced phosphorylation of Act1 on Ser311, adjacent to a putative TRAF-binding motif. Substitution of the serine at position 311 with alanine impaired the IL-17-mediated Act1-TRAF2-TRAF5 interaction and gene expression. Thus, IKKi is a kinase newly identified as modulating IL-17 signaling through its effect on Act1 phosphorylation and consequent function.

Multiplex Chemical Labeling of Amino Acids for Protein Footprinting Structure Assessment.

Protein footprinting with mass spectrometry is an established structural biology technique for mapping solvent accessibility and assessing molecular-level interactions of proteins. In hydroxyl radical protein footprinting (HRPF), hydroxyl (OH) radicals generated by water radiolysis or other methods covalently label protein side chains. Because of the wide dynamic range of OH reactivity, not all side chains are easily detected in a single experiment. Novel reagent development and the use of radical chain reactions for labeling, including trifluoromethyl radicals, is a potential approach to normalize the labeling across a diverse set of residues. HRPF in the presence of a trifluoromethylation reagent under the right conditions could provide a "one-pot" reaction for multiplex labeling of protein side chains. Toward this goal, we have systematically evaluated amino acid labeling with the recently investigated Langlois' reagent (LR) activated by X-ray-mediated water radiolysis, followed by three different mass spectrometry methods. We compared the reactivity of CF3 and OH radical labeling for all 20 protein side chains in a competition-free environment. We found that all 20 amino acids exhibited CF3 or OH labeling in LR. Our investigations provide the evidence and knowledge set to perfect hydroxyl radical-activated trifluoromethyl chemistry as "one-pot" reaction for multiplex labeling of protein side chains to achieve higher resolution in HRPF.

Co-phosphorylation networks reveal subtype-specific signaling modules in breast cancer.

MOTIVATION: Protein phosphorylation is a ubiquitous mechanism of post-translational modification that plays a central role in cellular signaling. Phosphorylation is particularly important in the context of cancer, as downregulation of tumor suppressors and upregulation of oncogenes by the dysregulation of associated kinase and phosphatase networks are shown to have key roles in tumor growth and progression. Despite recent advances that enable large-scale monitoring of protein phosphorylation, these data are not fully incorporated into such computational tasks as phenotyping and subtyping of cancers. RESULTS: We develop a network-based algorithm, CoPPNet, to enable unsupervised subtyping of cancers using phosphorylation data. For this purpose, we integrate prior knowledge on evolutionary, structural and functional association of phosphosites, kinase-substrate associations and protein-protein interactions with the correlation of phosphorylation of phosphosites across different tumor samples (a.k.a co-phosphorylation) to construct a context-specific-weighted network of phosphosites. We then mine these networks to identify subnetworks with correlated phosphorylation patterns. We apply the proposed framework to two mass-spectrometry-based phosphorylation datasets for breast cancer (BC), and observe that (i) the phosphorylation pattern of the identified subnetworks are highly correlated with clinically identified subtypes, and (ii) the identified subnetworks are highly reproducible across datasets that are derived from different studies. Our results show that integration of quantitative phosphorylation data with network frameworks can provide mechanistic insights into the differences between the signaling mechanisms that drive BC subtypes. Furthermore, the reproducibility of the identified subnetworks suggests that phosphorylation can provide robust classification of disease response and markers. AVAILABILITY AND IMPLEMENTATION: CoPPNet is available at http://compbio.case.edu/coppnet/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

New high-throughput endstation to accelerate the experimental optimization pipeline for synchrotron X-ray footprinting.

Synchrotron X-ray footprinting (XF) is a growing structural biology technique that leverages radiation-induced chemical modifications via X-ray radiolysis of water to produce hydroxyl radicals that probe changes in macromolecular structure and dynamics in solution states of interest. The X-ray Footprinting of Biological Materials (XFP) beamline at the National Synchrotron Light Source II provides the structural biology community with access to instrumentation and expert support in the XF method, and is also a platform for development of new technological capabilities in this field. The design and implementation of a new high-throughput endstation device based around use of a 96-well PCR plate form factor and supporting diagnostic instrumentation for synchrotron XF is described. This development enables a pipeline for rapid comprehensive screening of the influence of sample chemistry on hydroxyl radical dose using a convenient fluorescent assay, illustrated here with a study of 26 organic compounds. The new high-throughput endstation device and sample evaluation pipeline now available at the XFP beamline provide the worldwide structural biology community with a robust resource for carrying out well optimized synchrotron XF studies of challenging biological systems with complex sample compositions.

CoPhosK: A method for comprehensive kinase substrate annotation using co-phosphorylation analysis.

We present CoPhosK to predict kinase-substrate associations for phosphopeptide substrates detected by mass spectrometry (MS). The tool utilizes a Naïve Bayes framework with priors of known kinase-substrate associations (KSAs) to generate its predictions. Through the mining of MS data for the collective dynamic signatures of the kinases' substrates revealed by correlation analysis of phosphopeptide intensity data, the tool infers KSAs in the data for the considerable body of substrates lacking such annotations. We benchmarked the tool against existing approaches for predicting KSAs that rely on static information (e.g. sequences, structures and interactions) using publically available MS data, including breast, colon, and ovarian cancer models. The benchmarking reveals that co-phosphorylation analysis can significantly improve prediction performance when static information is available (about 35% of sites) while providing reliable predictions for the remainder, thus tripling the KSAs available from the experimental MS data providing to a comprehensive and reliable characterization of the landscape of kinase-substrate interactions well beyond current limitations.

Visualizing the kinetic power stroke that drives proton-coupled zinc(II) transport.

The proton gradient is a principal energy source for respiration-dependent active transport, but the structural mechanisms of proton-coupled transport processes are poorly understood. YiiP is a proton-coupled zinc transporter found in the cytoplasmic membrane of Escherichia coli. Its transport site receives protons from water molecules that gain access to its hydrophobic environment and transduces the energy of an inward proton gradient to drive Zn(II) efflux. This membrane protein is a well-characterized member of the family of cation diffusion facilitators that occurs at all phylogenetic levels. Here we show, using X-ray-mediated hydroxyl radical labelling of YiiP and mass spectrometry, that Zn(II) binding triggers a highly localized, all-or-nothing change of water accessibility to the transport site and an adjacent hydrophobic gate. Millisecond time-resolved dynamics reveal a concerted and reciprocal pattern of accessibility changes along a transmembrane helix, suggesting a rigid-body helical re-orientation linked to Zn(II) binding that triggers the closing of the hydrophobic gate. The gated water access to the transport site enables a stationary proton gradient to facilitate the conversion of zinc-binding energy to the kinetic power stroke of a vectorial zinc transport. The kinetic details provide energetic insights into a proton-coupled active-transport reaction.

The XFP (17-BM) beamline for X-ray footprinting at NSLS-II.

Hydroxyl-radical mediated synchrotron X-ray footprinting (XF) is a powerful solution-state technique in structural biology for the study of macromolecular structure and dynamics of proteins and nucleic acids, with several synchrotron resources available to serve the XF community worldwide. The XFP (Biological X-ray Footprinting) beamline at the NSLS-II was constructed on a three-pole wiggler source at 17-BM to serve as the premier beamline for performing this technique, providing an unparalleled combination of high flux density broadband beam, flexibility in beam morphology, and sample handling capabilities specifically designed for XF experiments. The details of beamline design, beam measurements, and science commissioning results for a standard protein using the two distinct XFP endstations are presented here. XFP took first light in 2016 and is now available for general user operations through peer-reviewed proposals. Currently, beam sizes from 450 µm × 120 µm to 2.7 mm × 2.7 mm (FWHM) are available, with a flux of 1.6 × 1016 photons s-1 (measured at 325 mA ring current) in a broadband (∼5-16 keV) beam. This flux is expected to rise to 2.5 × 1016 photons s-1 at the full NSLS-II design current of 500 mA, providing an incident power density of >500 W mm-2 at full focus.

Interplay of transcriptional signaling by progesterone, cyclic AMP, and inflammation in myometrial cells: implications for the control of human parturition.

Parturition involves cellular signaling changes driven by the complex interplay between progesterone (P4), inflammation, and the cyclic adenosine monophosphate (cAMP) pathway. To characterize this interplay, we performed comprehensive transcriptomic studies utilizing eight treatment combinations on myometrial cell lines and tissue samples from pregnant women. We performed genome-wide RNA-sequencing on the hTERT-HM${}^{A/B}$ cell line treated with all combinations of P4, forskolin (FSK) (induces cAMP), and interleukin-1$\beta$ (IL-1$\beta$). We then performed gene set enrichment and regulatory network analyses to identify pathways commonly, differentially, or synergistically regulated by these treatments. Finally, we used tissue similarity index (TSI) to characterize the correspondence between cell lines and tissue phenotypes. We observed that in addition to their individual anti-inflammatory effects, P4 and cAMP synergistically blocked specific inflammatory pathways/regulators including STAT3/6, CEBPA/B, and OCT1/7, but not NF$\kappa$B. TSI analysis indicated that FSK + P4- and IL-1$\beta$-treated cells exhibit transcriptional signatures highly similar to non-laboring and laboring term myometrium, respectively. Our results identify potential therapeutic targets to prevent preterm birth and show that the hTERT-HM${}^{A/B}$ cell line provides an accurate transcriptional model for term myometrial tissue.

Protein Footprinting Comes of Age: Mass Spectrometry for Biophysical Structure Assessment.

Protein footprinting mediated by mass spectrometry has evolved over the last 30 years from proof of concept to commonplace biophysics tool, with unique capabilities for assessing structure and dynamics of purified proteins in physiological states in solution. This review outlines the history and current capabilities of two major methods of protein footprinting: reversible hydrogen-deuterium exchange (HDX) and hydroxyl radical footprinting (HRF), an irreversible covalent labeling approach. Technological advances in both approaches now permit high-resolution assessments of protein structure including secondary and tertiary structure stability mediated by backbone interactions (measured via HDX) and solvent accessibility of side chains (measured via HRF). Applications across many academic fields and in biotechnology drug development are illustrated including: detection of protein interfaces, identification of ligand/drug binding sites, and monitoring dynamics of protein conformational changes along with future prospects for advancement of protein footprinting in structural biology and biophysics research.

Finding lost genes in GWAS via integrative-omics analysis reveals novel sub-networks associated with preterm birth.

Maternal genome influences associate with up to 40% of spontaneous preterm births (PTB). Multiple genome wide association studies (GWAS) have been completed to identify genetic variants associated with PTB. Disappointingly, no highly significant SNPs have replicated in independent cohorts so far. We developed an approach combining protein-protein interaction (PPI) network data with tissue specific gene expression data to "find" SNPs of modest significance to identify candidate genes of functional importance that would otherwise be overlooked. This approach is based on the assumption that "high-ranking" SNPs falling short of genome wide significance may nevertheless indicate genes that have substantial biological value in understanding PTB. We mapped highly-ranked candidate SNPs from a meta-analysis of PTB-GWAS to coding genes and developed a PPI network enriched with PTB-SNP carrying genes. This network was scored with gene expression data from term and preterm myometrium to identify subnetworks of PTB-SNP associated genes coordinately expressed with labour onset in myometrial tissue. Our analysis consistently identified significant sub-networks associated with the interacting transcription factors MEF2C and TWIST1, genes not previously associated with PTB, both of which regulate processes clearly relevant to birth timing. Other genes in the significant sub-networks were also associated with inflammatory pathways, as well as muscle function and ion channels. Gene expression level dysregulation was confirmed for eight of these networks by qRT-PCR in an independent set of term and pre-term subjects. Our method identifies novel genes dysregulated in PTB and provides a generalized framework to identify GWAS SNPs that would otherwise be overlooked.

Global phosphoproteomics of CCR5-tropic HIV-1 signaling reveals reprogramming of cellular protein production pathways and identifies p70-S6K1 and MK2 as HIV-responsive kinases required for optimal infection of CD4+ T cells.

BACKGROUND: Viral reprogramming of host cells enhances replication and is initiated by viral interaction with the cell surface. Upon human immunodeficiency virus (HIV) binding to CD4+ T cells, a signal transduction cascade is initiated that reorganizes the actin cytoskeleton, activates transcription factors, and alters mRNA splicing pathways. METHODS: We used a quantitative mass spectrometry-based phosphoproteomic approach to investigate signal transduction cascades initiated by CCR5-tropic HIV, which accounts for virtually all transmitted viruses and the vast majority of viruses worldwide. RESULTS: CCR5-HIV signaling induced significant reprogramming of the actin cytoskeleton and mRNA splicing pathways, as previously described. In addition, CCR5-HIV signaling induced profound changes to the mRNA transcription, processing, translation, and post-translational modifications pathways, indicating that virtually every stage of protein production is affected. Furthermore, we identified two kinases regulated by CCR5-HIV signaling-p70-S6K1 (RPS6KB1) and MK2 (MAPKAPK2)-that were also required for optimal HIV infection of CD4+ T cells. These kinases regulate protein translation and cytoskeletal architecture, respectively, reinforcing the importance of these pathways in viral replication. Additionally, we found that blockade of CCR5 signaling by maraviroc had relatively modest effects on CCR5-HIV signaling, in agreement with reports that signaling by CCR5 is dispensable for HIV infection but in contrast to the critical effects of CXCR4 on cortical actin reorganization. CONCLUSIONS: These results demonstrate that CCR5-tropic HIV induces significant reprogramming of host CD4+ T cell protein production pathways and identifies two novel kinases induced upon viral binding to the cell surface that are critical for HIV replication in host cells.

Integrated microRNA and mRNA network analysis of the human myometrial transcriptome in the transition from quiescence to labor.

We conducted integrated transcriptomics network analyses of miRNA and mRNA interactions in human myometrium to identify novel molecular candidates potentially involved in human parturition. Myometrial biopsies were collected from women undergoing primary Cesarean deliveries in well-characterized clinical scenarios: (1) spontaneous term labor (TL, n = 5); (2) term nonlabor (TNL, n = 5); (3) spontaneous preterm birth (PTB) with histologic chorioamnionitis (PTB-HCA, n = 5); and (4) indicated PTB nonlabor (PTB-NL, n = 5). RNAs were profiled using RNA sequencing, and miRNA-target interaction networks were mined for key discriminatory subnetworks. Forty miRNAs differed between TL and TNL myometrium, while seven miRNAs differed between PTB-HCA vs. PTB-NL specimens; six of these were cross-validated using quantitative PCR. Based on the combined sequencing data, unsupervised clustering revealed two nonoverlapping cohorts that differed primarily by absence or presence of uterine quiescence, rather than gestational age or original clinical cohort. The intersection of differentially expressed miRNAs and their targets predicted 22 subnetworks with enriched representation of miR-146b-5p, miR-223-3p, and miR-150-5p among miRNAs, and of myocyte enhancer factor-2C (MEF2C) among mRNAs. Of four known MEF2 transcription factors, decreased MEF2A and MEF2C expression in women with uterine nonquiescence was observed in the sequencing data, and validated in a second cohort by quantitative PCR. Immunohistochemistry localized MEF2A and MEF2C to myometrial smooth muscle cells and confirmed decreased abundance with labor. Collectively, these results suggest altered MEF2 expression may represent a previously unrecognized process through which miRNAs contribute to the phenotypic switch from quiescence to labor in human myometrium.

Linearity of network proximity measures: implications for set-based queries and significance testing.

Motivation: In recent years, various network proximity measures have been proposed to facilitate the use of biomolecular interaction data in a broad range of applications. These applications include functional annotation, disease gene prioritization, comparative analysis of biological systems and prediction of new interactions. In such applications, a major task is the scoring or ranking of the nodes in the network in terms of their proximity to a given set of 'seed' nodes (e.g. a group of proteins that are identified to be associated with a disease, or are deferentially expressed in a certain condition). Many different network proximity measures are utilized for this purpose, and these measures are quite diverse in terms of the benefits they offer. Results: We propose a unifying framework for characterizing network proximity measures for set-based queries. We observe that many existing measures are linear, in that the proximity of a node to a set of nodes can be represented as an aggregation of its proximity to the individual nodes in the set. Based on this observation, we propose methods for processing of set-based proximity queries that take advantage of sparse local proximity information. In addition, we provide an analytical framework for characterizing the distribution of proximity scores based on reference models that accurately capture the characteristics of the seed set (e.g. degree distribution and biological function). The resulting framework facilitates computation of exact figures for the statistical significance of network proximity scores, enabling assessment of the accuracy of Monte Carlo simulation based estimation methods. Availability and Implementation: Implementations of the methods in this paper are available at https://bioengine.case.edu/crosstalker which includes a robust visualization for results viewing. Contact: stm@case.edu or mxk331@case.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

The KSEA App: a web-based tool for kinase activity inference from quantitative phosphoproteomics.

Summary: Computational characterization of differential kinase activity from phosphoproteomics datasets is critical for correctly inferring cellular circuitry and how signaling cascades are altered in drug treatment and/or disease. Kinase-Substrate Enrichment Analysis (KSEA) offers a powerful approach to estimating changes in a kinase's activity based on the collective phosphorylation changes of its identified substrates. However, KSEA has been limited to programmers who are able to implement the algorithms. Thus, to make it accessible to the larger scientific community, we present a web-based application of this method: the KSEA App. Overall, we expect that this tool will offer a quick and user-friendly way of generating kinase activity estimates from high-throughput phosphoproteomics datasets. Availability and Implementation: the KSEA App is a free online tool: casecpb.shinyapps.io/ksea/. The source code is on GitHub: github.com/casecpb/KSEA/. The application is also available as the R package "KSEAapp" on CRAN: CRAN.R-project.org/package=KSEAapp/. Contact: mark.chance@case.edu. Supplementary information: Supplementary data are available at Bioinformatics online.