A protein complex network of Drosophila melanogaster

The Nitrogen Regulatory PII Protein (GlnB) and N-Acetylglucosamine 6-Phosphate Epimerase (NanE) Allosterically Activate Glucosamine 6-Phosphate Deaminase (NagB) in Escherichia coli

Amino sugars are good sources of both ammonia and fructose-6-phosphate, produced by the glucosamine 6-phosphate deaminase, NagB. NagB is known to be allosterically regulated by N-acetylglucosamine 6-phosphate (GlcNAc-6P) and the phosphocarrier protein of the bacterial phosphotransferase system, HPr, in Escherichia coli We provide evidence that NanE, GlcNAc-6P epimerase, and the uridylylated PII protein (U-PII) also allosterically activate NagB by direct protein-protein interactions. NanE is essential for neuraminic acid (NANA) and N-acetylmannosamine (ManNAc) utilization, and PII is known to be a central metabolic nitrogen regulator. We demonstrate that uridylylated PII (but not underivatized PII) activates NagB >10-fold at low concentrations of substrate, whereas NanE increases NagB activity >2-fold. NanE activates NagB in the absence or presence of GlcNAc-6P, but HPr and U-PII activation requires the presence of GlcNAc-6P. Activation of NagB by HPr and uridylylated PII, as well as by NanE and HPr (but not by NanE and U-PII), is synergistic, and the modeling, which suggests specific residues involved in complex formation, provides possible explanations. Specific physiological functions for the regulation of NagB by its three protein activators are proposed. Each regulatory agent is suggested to mediate signal transduction in response to a different stimulus.IMPORTANCE The regulation of amino sugar utilization is important for the survival of bacteria in a competitive environment. NagB, a glucosamine 6-phosphate deaminase in Escherichia coli, is essential for amino sugar utilization and is known to be allosterically regulated by N-acetylglucosamine 6-phosphate (GlcNAc-6P) and the histidine-phosphorylatable phosphocarrier protein, HPr. We provide evidence here that NanE, GlcNAc-6P epimerase, and the uridylylated PII protein allosterically activate NagB by direct protein-protein interactions. NanE is essential for N-acetylneuraminic acid (NANA) and N-acetylmannosamine (ManNAc) utilization, and the PII protein is known to be a central metabolic nitrogen regulator. Regulatory links between carbon and nitrogen metabolism are important for adaptation of metabolism to different growth conditions.

Antibody Validation by Immunoprecipitation Followed by Mass Spectrometry Analysis

We describe a mass spectrometry-based approach for validation of antibody specificity. This method allows validation of antibodies or antibody fragments, against their endogenous targets. It can assess if the antibody is able to bind to its native antigen in cell lysates among thousands of other proteins, DNA, RNA, and other cellular components. In addition, it identifies other proteins the antibody is able to immunoprecipitate allowing for the assessment of antibody specificity and selectivity. This method is easily scalable, adaptable to different cell lines and conditions and has been shown to be reproducible between multiple laboratories.

Self-oligomerization regulates stability of survival motor neuron protein isoforms by sequestering an SCFSlmb degron

Spinal muscular atrophy (SMA) is caused by homozygous mutations in human SMN1 Expression of a duplicate gene (SMN2) primarily results in skipping of exon 7 and production of an unstable protein isoform, SMNΔ7. Although SMN2 exon skipping is the principal contributor to SMA severity, mechanisms governing stability of survival motor neuron (SMN) isoforms are poorly understood. We used a Drosophila model system and label-free proteomics to identify the SCFSlmb ubiquitin E3 ligase complex as a novel SMN binding partner. SCFSlmb interacts with a phosphor degron embedded within the human and fruitfly SMN YG-box oligomerization domains. Substitution of a conserved serine (S270A) interferes with SCFSlmb binding and stabilizes SMNΔ7. SMA-causing missense mutations that block multimerization of full-length SMN are also stabilized in the degron mutant background. Overexpression of SMNΔ7S270A, but not wild-type (WT) SMNΔ7, provides a protective effect in SMA model mice and human motor neuron cell culture systems. Our findings support a model wherein the degron is exposed when SMN is monomeric and sequestered when SMN forms higher-order multimers.

Peroxisome Protein Prediction in Drosophila melanogaster

As a laboratory animal, Drosophila melanogaster has made extensive contributions to understanding many areas of fundamental biology as well as being an effective model for human disease. Until recently, there was relatively little known about fly peroxisomes. There were early studies that examined the role of peroxisome enzymes during development of organs like the eye. However, with the advent of a well-annotated, sequenced genome, several groups have collectively determined, first by sequence homology and increasingly by functional studies, Drosophila Peroxins and related peroxisome proteins. Notably, it was shown that Drosophila peroxisome biogenesis is mediated via a well-conserved PTS1 import system. Although the fly genome encodes a Pex7 homologue, a canonical PTS2 import system does not seem to be conserved in Drosophila. Given the homology between Drosophila and Saccharomyces cerevisiae or Homo sapiens peroxisome biogenesis and function, Drosophila has emerged as an effective multicellular system to model human Peroxisome Biogenesis Disorders. Finally, Drosophila peroxisome research has recently come into its own, facilitating new discoveries into the role of peroxisomes within specific tissues, such as testes or immune cells.

Integration of Drosophila and Human Genetics to Understand Notch Signaling Related Diseases

Notch signaling research dates back to more than one hundred years, beginning with the identification of the Notch mutant in the fruit fly Drosophila melanogaster. Since then, research on Notch and related genes in flies has laid the foundation of what we now know as the Notch signaling pathway. In the 1990s, basic biological and biochemical studies of Notch signaling components in mammalian systems, as well as identification of rare mutations in Notch signaling pathway genes in human patients with rare Mendelian diseases or cancer, increased the significance of this pathway in human biology and medicine. In the 21st century, Drosophila and other genetic model organisms continue to play a leading role in understanding basic Notch biology. Furthermore, these model organisms can be used in a translational manner to study underlying mechanisms of Notch-related human diseases and to investigate the function of novel disease associated genes and variants. In this chapter, we first briefly review the major contributions of Drosophila to Notch signaling research, discussing the similarities and differences between the fly and human pathways. Next, we introduce several biological contexts in Drosophila in which Notch signaling has been extensively characterized. Finally, we discuss a number of genetic diseases caused by mutations in genes in the Notch signaling pathway in humans and we expand on how Drosophila can be used to study rare genetic variants associated with these and novel disorders. By combining modern genomics and state-of-the art technologies, Drosophila research is continuing to reveal exciting biology that sheds light onto mechanisms of disease.

The Notch Interactome: Complexity in Signaling Circuitry

The Notch pathway controls a very broad spectrum of cell fates in metazoans during development, influencing proliferation, differentiation and cell death. Given its central role in normal development and homeostasis, misregulation of Notch signals can lead to various disorders including cancer. How the Notch pathway mediates such pleiotropic and differential effects is of fundamental importance. It is becoming increasingly clear through a number of large-scale genetic and proteomic studies that Notch interacts with a staggeringly large number of other genes and pathways in a context-dependent, complex, and highly regulated network, which determines the ultimate biological outcome. How best to interpret and analyze the continuously increasing wealth of data on Notch interactors remains a challenge. Here we review the current state of genetic and proteomic data related to the Notch interactome.

The Drosophila CLAMP protein associates with diverse proteins on chromatin

Gaining new insights into gene regulation involves an in-depth understanding of protein-protein interactions on chromatin. A powerful model for studying mechanisms of gene regulation is dosage compensation, a process that targets the X-chromosome to equalize gene expression between XY males and XX females. We previously identified a zinc finger protein in Drosophila melanogaster that plays a sex-specific role in targeting the Male-specific lethal (MSL) dosage compensation complex to the male X-chromosome, called the Chromatin-Linked Adapter for MSL Proteins (CLAMP). More recently, we established that CLAMP has non-sex-specific roles as an essential protein that regulates chromatin accessibility at promoters genome-wide. To identify associations between CLAMP and other factors in both male and female cells, we used two complementary mass spectrometry approaches. We demonstrate that CLAMP associates with the transcriptional regulator complex Negative Elongation Factor (NELF) in both sexes and determine that CLAMP reduces NELF recruitment to several target genes. In sum, we have identified many new CLAMP-associated factors and provide a resource for further study of this little understood essential protein.

Widespread Rewiring of Genetic Networks upon Cancer Signaling Pathway Activation

Cellular signaling networks coordinate physiological processes in all multicellular organisms. Within networks, modules switch their function to control signaling activity in response to the cellular context. However, systematic approaches to map the interplay of such modules have been lacking. Here, we generated a context-dependent genetic interaction network of a metazoan's signaling pathway. Using Wnt signaling in Drosophila as a model, we measured >290,000 double perturbations of the pathway in a baseline state, after activation by Wnt ligand or after loss of the tumor suppressor APC. We found that genetic interactions within the Wnt network globally rewired after pathway activation. We derived between-state networks that showed how genes changed their function between state-specific networks. This related pathway inhibitors across states and identified genes required for pathway activation. For instance, we predicted and confirmed the ER-resident protein Catsup to be required for ligand-mediated Wnt signaling activation. Together, state-dependent and between-state genetic interaction networks identify responsive functional modules that control cellular pathways.

•

Genetic interaction networks of Wnt signaling in three cellular states

•

Networks rewire upon activation of Wnt pathway by ligand or by loss of APC

•

Interaction profiles identify known and novel state-dependent pathway modules

•

State-specific and between-state profile similarity identify signaling regulators

Stratum, a Homolog of the Human GEF Mss4, Partnered with Rab8, Controls the Basal Restriction of Basement Membrane Proteins in Epithelial Cells

The basement membrane (BM), a sheet of extracellular matrix lining the basal side of epithelia, is essential for epithelial cell function and integrity, yet the mechanisms that control the basal restriction of BM proteins are poorly understood. In epithelial cells, a specialized pathway is dedicated to restrict the deposition of BM proteins basally. Here, we report the identification of a factor in this pathway, a homolog of the mammalian guanine nucleotide exchange factor (GEF) Mss4, which we have named Stratum. The loss of Stratum leads to the missecretion of BM proteins at the apical side of the cells, forming aberrant layers in close contact with the plasma membrane. We found that Rab8GTPase acts downstream of Stratum in this process. Altogether, our results uncover the importance of this GEF/Rab complex in specifically coordinating the basal restriction of BM proteins, a critical process for the establishment and maintenance of epithelial cell polarity.

Global landscape of cell envelope protein complexes in Escherichia coli

Bacterial cell envelope protein (CEP) complexes mediate a range of processes, including membrane assembly, antibiotic resistance and metabolic coordination. However, only limited characterization of relevant macromolecules has been reported to date. Here we present a proteomic survey of 1,347 CEPs encompassing 90% inner- and outer-membrane and periplasmic proteins of Escherichia coli. After extraction with non-denaturing detergents, we affinity-purified 785 endogenously tagged CEPs and identified stably associated polypeptides by precision mass spectrometry. The resulting high-quality physical interaction network, comprising 77% of targeted CEPs, revealed many previously uncharacterized heteromeric complexes. We found that the secretion of autotransporters requires translocation and the assembly module TamB to nucleate proper folding from periplasm to cell surface through a cooperative mechanism involving the β-barrel assembly machinery. We also establish that an ABC transporter of unknown function, YadH, together with the Mla system preserves outer membrane lipid asymmetry. This E. coli CEP 'interactome' provides insights into the functional landscape governing CE systems essential to bacterial growth, metabolism and drug resistance.

An Integrative Analysis of the InR/PI3K/Akt Network Identifies the Dynamic Response to Insulin Signaling

Insulin regulates an essential conserved signaling pathway affecting growth, proliferation, and metabolism. To expand our understanding of the insulin pathway, we combine biochemical, genetic, and computational approaches to build a comprehensive Drosophila InR/PI3K/Akt network. First, we map the dynamic protein-protein interaction network surrounding the insulin core pathway using bait-prey interactions connecting 566 proteins. Combining RNAi screening and phospho-specific antibodies, we find that 47% of interacting proteins affect pathway activity, and, using quantitative phosphoproteomics, we demonstrate that ∼10% of interacting proteins are regulated by insulin stimulation at the level of phosphorylation. Next, we integrate these orthogonal datasets to characterize the structure and dynamics of the insulin network at the level of protein complexes and validate our method by identifying regulatory roles for the Protein Phosphatase 2A (PP2A) and Reptin-Pontin chromatin-remodeling complexes as negative and positive regulators of ribosome biogenesis, respectively. Altogether, our study represents a comprehensive resource for the study of the evolutionary conserved insulin network.

Comparison of ancient and modern Chinese based on complex weighted networks

In this study, we compare statistical properties of ancient and modern Chinese within the framework of weighted complex networks. We examine two language networks based on different Chinese versions of the Records of the Grand Historian. The comparative results show that Zipf's law holds and that both networks are scale-free and disassortative. The interactivity and connectivity of the two networks lead us to expect that the modern Chinese text would have more phrases than the ancient Chinese one. Furthermore, by considering some of the topological and weighted quantities, we find that expressions in ancient Chinese are briefer than in modern Chinese. These observations indicate that the two languages might have different linguistic mechanisms and combinatorial natures, which we attribute to the stylistic differences and evolution of written Chinese.

Taking Stock of the Drosophila Research Ecosystem

With a century-old history of fundamental discoveries, the fruit fly has long been a favored experimental organism for a wide range of scientific inquiries. But Drosophila is not a “legacy” model organism; technical and intellectual innovations continue to revitalize fly research and drive advances in our understanding of conserved mechanisms of animal biology. Here, we provide an overview of this “ecosystem” and discuss how to address emerging challenges to ensure its continued productivity. Drosophila researchers are fortunate to have a sophisticated and ever-growing toolkit for the analysis of gene function. Access to these tools depends upon continued support for both physical and informational resources. Uncertainty regarding stable support for bioinformatic databases is a particular concern, at a time when there is the need to make the vast knowledge of functional biology provided by this model animal accessible to scientists studying other organisms. Communication and advocacy efforts will promote appreciation of the value of the fly in delivering biomedically important insights. Well-tended traditions of large-scale tool development, open sharing of reagents, and community engagement provide a strong basis for coordinated and proactive initiatives to improve the fly research ecosystem. Overall, there has never been a better time to be a fly pusher.

Digging deep into Golgi phenotypic diversity with unsupervised machine learning

Structural alterations of the Golgi apparatus may lead to phenotypes that human vision cannot easily discriminate. In this work, we present a high-content analysis framework including an unsupervised clustering step to automatically uncover Golgi phenotypic diversity. We use this deep phenotyping to quantitatively compare the effects of gene depletion.

The synthesis of glycans and the sorting of proteins are critical functions of the Golgi apparatus and depend on its highly complex and compartmentalized architecture. High-content image analysis coupled to RNA interference screening offers opportunities to explore this organelle organization and the gene network underlying it. To date, image-based Golgi screens have based on a single parameter or supervised analysis with predefined Golgi structural classes. Here, we report the use of multiparametric data extracted from a single marker and a computational unsupervised analysis framework to explore Golgi phenotypic diversity more extensively. In contrast with the three visually definable phenotypes, our framework reproducibly identified 10 Golgi phenotypes. They were used to quantify and stratify phenotypic similarities among genetic perturbations. The derived phenotypic network partially overlaps previously reported protein–protein interactions as well as suggesting novel functional interactions. Our workflow suggests the existence of multiple stable Golgi organizational states and provides a proof of concept for the classification of drugs and genes using fine-grained phenotypic information.

Novel roles of HP1a and Mcm10 in DNA replication, genome maintenance and photoreceptor cell differentiation

Both Mcm10 and HP1a are known to be required for DNA replication. However, underlying mechanism is not clarified yet especially for HP1. Knockdown of both HP1a and Mcm10 genes inhibited the progression of S phase in Drosophila eye imaginal discs. Proximity Ligation Assay (PLA) demonstrated that HP1a is in close proximity to DNA replication proteins including Mcm10, RFC140 and DNA polymerase ε 255 kDa subunit in S-phase. This was further confirmed by co-immunoprecipitation assay. The PLA signals between Mcm10 and HP1a are specifically observed in the mitotic cycling cells, but not in the endocycling cells. Interestingly, many cells in the posterior regions of eye imaginal discs carrying a double knockdown of Mcm10 and HP1a induced ectopic DNA synthesis and DNA damage without much of ectopic apoptosis. Therefore, the G1-S checkpoint may be affected by knockdown of both proteins. This event was also the case with other HP family proteins such as HP4 and HP6. In addition, both Mcm10 and HP1a are required for differentiation of photoreceptor cells R1, R6 and R7. Further analyses on several developmental genes involved in the photoreceptor cell differentiation suggest that a role of both proteins is mediated by regulation of the lozenge gene.

A two-step framework for inferring direct protein-protein interaction network from AP-MS data

Background

Affinity purification-mass spectrometry (AP-MS) has been widely used for generating bait-prey data sets so as to identify underlying protein-protein interactions and protein complexes. However, the AP-MS data sets in terms of bait-prey pairs are highly noisy, where candidate pairs contain many false positives. Recently, numerous computational methods have been developed to identify genuine interactions from AP-MS data sets. However, most of these methods aim at removing false positives that contain contaminants, ignoring the distinction between direct interactions and indirect interactions.

Results

In this paper, we present an initialization-and-refinement framework for inferring direct PPI networks from AP-MS data, in which an initial network is first generated with existing scoring methods and then a refined network is constructed by the application of indirect association removal methods. Experimental results on several real AP-MS data sets show that our method is capable of identifying more direct interactions than traditional scoring methods.

Conclusions

The proposed framework is sufficiently general to incorporate any feasible methods in each step so as to have potential for handling different types of AP-MS data in the future applications.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0452-y) contains supplementary material, which is available to authorized users.

Tango7 regulates cortical activity of caspases during reaper-triggered changes in tissue elasticity

Caspases perform critical functions in both living and dying cells; however, how caspases perform physiological functions without killing the cell remains unclear. Here we identify a novel physiological function of caspases at the cortex of Drosophila salivary glands. In living glands, activation of the initiator caspase dronc triggers cortical F-actin dismantling, enabling the glands to stretch as they accumulate secreted products in the lumen. We demonstrate that tango7, not the canonical Apaf-1-adaptor dark, regulates dronc activity at the cortex; in contrast, dark is required for cytoplasmic activity of dronc during salivary gland death. Therefore, tango7 and dark define distinct subcellular domains of caspase activity. Furthermore, tango7-dependent cortical dronc activity is initiated by a sublethal pulse of the inhibitor of apoptosis protein (IAP) antagonist reaper. Our results support a model in which biological outcomes of caspase activation are regulated by differential amplification of IAP antagonists, unique caspase adaptor proteins, and mutually exclusive subcellular domains of caspase activity.

Caspases are known for their role in cell death, but they can also participate in other physiological functions without killing the cells. Here the authors show that unique caspase adaptor proteins can regulate caspase activity within mutually-exclusive and independently regulated subcellular domains.

Protein complexes, big data, machine learning and integrative proteomics: lessons learned over a decade of systematic analysis of protein interaction networks

OVERVIEW

Elucidation of the networks of physical (functional) interactions present in cells and tissues is fundamental for understanding the molecular organization of biological systems, the mechanistic basis of essential and disease-related processes, and for functional annotation of previously uncharacterized proteins (via guilt-by-association or -correlation). After a decade in the field, we felt it timely to document our own experiences in the systematic analysis of protein interaction networks. Areas covered: Researchers worldwide have contributed innovative experimental and computational approaches that have driven the rapidly evolving field of 'functional proteomics'. These include mass spectrometry-based methods to characterize macromolecular complexes on a global-scale and sophisticated data analysis tools - most notably machine learning - that allow for the generation of high-quality protein association maps. Expert commentary: Here, we recount some key lessons learned, with an emphasis on successful workflows, and challenges, arising from our own and other groups' ongoing efforts to generate, interpret and report proteome-scale interaction networks in increasingly diverse biological contexts.

LSM12 and ME31B/DDX6 Define Distinct Modes of Posttranscriptional Regulation by ATAXIN-2 Protein Complex in Drosophila Circadian Pacemaker Neurons

ATAXIN-2 (ATX2) has been implicated in human neurodegenerative diseases, yet it remains elusive how ATX2 assembles specific protein complexes to execute its physiological roles. Here we employ the posttranscriptional co-activator function of Drosophila ATX2 to demonstrate that LSM12 and ME31B/DDX6 are two ATX2-associating factors crucial for sustaining circadian rhythms. LSM12 acts as a molecular adaptor for the recruitment of TWENTY-FOUR (TYF) to ATX2. The ATX2-LSM12-TYF complex thereby stimulates TYF-dependent translation of the rate-limiting clock gene period (per) to maintain 24 hr periodicity in circadian behaviors. In contrast, ATX2 contributes to NOT1-mediated gene silencing and associates with NOT1 in a ME31B/DDX6-dependent manner. The ME31B/DDX6-NOT1 complex does not affect PER translation but supports high-amplitude behavioral rhythms along with ATX2, indicating a PER-independent clock function of ATX2. Taken together, these data suggest that the ATX2 complex may switch distinct modes of posttranscriptional regulation through its associating factors to control circadian clocks and ATX2-related physiology.

Protein complex analysis: From raw protein lists to protein interaction networks

The elucidation of molecular interaction networks is one of the pivotal challenges in the study of biology. Affinity purification-mass spectrometry and other co-complex methods have become widely employed experimental techniques to identify protein complexes. These techniques typically suffer from a high number of false negatives and false positive contaminants due to technical shortcomings and purification biases. To support a diverse range of experimental designs and approaches, a large number of computational methods have been proposed to filter, infer and validate protein interaction networks from experimental pull-down MS data. Nevertheless, this expansion of available methods complicates the selection of the most optimal ones to support systems biology-driven knowledge extraction. In this review, we give an overview of the most commonly used computational methods to process and interpret co-complex results, and we discuss the issues and unsolved problems that still exist within the field. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:600-614, 2017.

Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing

Alternative splicing is known to remodel protein-protein interaction networks (“interactomes”), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing.

Protein-protein interaction networks have been extensively used in systems biology to study the role of proteins in cell function and disease. However, current network biology studies typically assume that one gene encodes one protein isoform, ignoring the effect of alternative splicing. Alternative splicing allows a gene to produce multiple protein isoforms, by alternatively selecting distinct regions in the gene to be translated to protein products. Here, we present a computational method to predict and analyze the large-scale effect of alternative splicing on protein-protein interaction networks. Starting with a reference protein-protein interaction network determined by experiments, our method annotates protein-protein interactions with domain-domain interactions, and predicts that a protein isoform loses an interaction if it loses the domain mediating the interaction as a result of alternative splicing. Our predictions reveal the central role of alternative splicing in extensively remodeling the human protein-protein interaction network, and in increasing the functional complexity of the human cell. Our prediction method complements ongoing experimental efforts by predicting isoform-specific interactions for genes not tested yet by experiments and providing insights into the functional impact of alternative splicing.

Signal Integration by the IκB Protein Pickle Shapes Drosophila Innate Host Defense

Pattern recognition receptors are activated following infection and trigger transcriptional programs important for host defense. Tight regulation of NF-κB activation is critical to avoid detrimental and misbalanced responses. We describe Pickle, a Drosophila nuclear IκB that integrates signaling inputs from both the Imd and Toll pathways by skewing the transcriptional output of the NF-κB dimer repertoire. Pickle interacts with the NF-κB protein Relish and the histone deacetylase dHDAC1, selectively repressing Relish homodimers while leaving other NF-κB dimer combinations unscathed. Pickle's ability to selectively inhibit Relish homodimer activity contributes to proper host immunity and organismal health. Although loss of pickle results in hyper-induction of Relish target genes and improved host resistance to pathogenic bacteria in the short term, chronic inactivation of pickle causes loss of immune tolerance and shortened lifespan. Pickle therefore allows balanced immune responses that protect from pathogenic microbes while permitting the establishment of beneficial commensal host-microbe relationships.

Linker histone H1 prevents R-loop accumulation and genome instability in heterochromatin

Linker histone H1 is an important structural component of chromatin that stabilizes the nucleosome and compacts the nucleofilament into higher-order structures. The biology of histone H1 remains, however, poorly understood. Here we show that Drosophila histone H1 (dH1) prevents genome instability as indicated by the increased γH2Av (H2AvS137P) content and the high incidence of DNA breaks and sister-chromatid exchanges observed in dH1-depleted cells. Increased γH2Av occurs preferentially at heterochromatic elements, which are upregulated upon dH1 depletion, and is due to the abnormal accumulation of DNA:RNA hybrids (R-loops). R-loops accumulation is readily detectable in G1-phase, whereas γH2Av increases mainly during DNA replication. These defects induce JNK-mediated apoptosis and are specific of dH1 depletion since they are not observed when heterochromatin silencing is relieved by HP1a depletion. Altogether, our results suggest that histone H1 prevents R-loops-induced DNA damage in heterochromatin and unveil its essential contribution to maintenance of genome stability.While structural importance of linker histone H1 in packaging eukaryotic genome into chromatin is well known, its biological function remains poorly understood. Here the authors reveal that Drosophila linker histone H1 prevents DNA:RNA hybrids accumulation and genome instability in heterochromatin.

Deconstruction of the beaten Path-Sidestep interaction network provides insights into neuromuscular system development

An ‘interactome’ screen of all Drosophila cell-surface and secreted proteins containing immunoglobulin superfamily (IgSF) domains discovered a network formed by paralogs of Beaten Path (Beat) and Sidestep (Side), a ligand-receptor pair that is central to motor axon guidance. Here we describe a new method for interactome screening, the Bio-Plex Interactome Assay (BPIA), which allows identification of many interactions in a single sample. Using the BPIA, we ‘deorphanized’ four more members of the Beat-Side network. We confirmed interactions using surface plasmon resonance. The expression patterns of beat and side genes suggest that Beats are neuronal receptors for Sides expressed on peripheral tissues. side-VI is expressed in muscle fibers targeted by the ISNb nerve, as well as at growth cone choice points and synaptic targets for the ISN and TN nerves. beat-V genes, encoding Side-VI receptors, are expressed in ISNb and ISN motor neurons.

Within every organ of the body, cells must be able to recognise and communicate with one another in order to work together to perform a particular role. Each cell has a specific protein on its surface that acts like a molecular identity card, and which can form weak bonds with a complementary protein on another cell. There are thousands of different cell surface proteins, and the interactions between them – known collectively as the interactome – dictate the how cells interact with one another.

Many cell surface proteins are similar across species. Humans and fruit flies, for example, both possess a family of cell surface proteins that contain a region called the Immunoglobulin Superfamily domain. This family can be further divided into subfamilies, two of which are known as “Beats” and “Sides” for short. As the nervous system develops, nerve cells carrying a particular Beat protein interact with nerve or muscle cells carrying a corresponding Side protein. Yet while experiments have matched up many Beats and Sides, the partners of others remain unknown.

Li et al. have now developed a new technique called the Bio-Plex Interactome Assay to rapidly screen for interactions between multiple cell surface proteins in a single sample. Applying the technique to cells from fruit flies revealed new binding partners within the Beats and the Sides. After verifying several of these interactions, Li et al. explored the role of various Beats and Sides in the developing nervous system of fruit fly embryos by mapping the cells that display them on their surfaces.

This increased knowledge of the Beat-Side binding network should provide further insights into how connections form between nerve cells. The new screening technique could also eventually be used to map the cell surface protein interactome in humans. A number of key drugs, including the breast cancer drug Herceptin, target cell surface proteins. Identifying interactions among cell surface proteins could thus provide additional leads for developing new therapies.

An Ultraconserved Element (UCE) controls homeostatic splicing of ARGLU1 mRNA

Arginine and Glutamate-Rich protein 1 (ARGLU1) is a protein whose function is poorly understood, but may act in both transcription and pre-mRNA splicing. We demonstrate that the ARGLU1 gene expresses at least three distinct RNA splice isoforms – a fully spliced isoform coding for the protein, an isoform containing a retained intron that is detained in the nucleus, and an isoform containing an alternative exon that targets the transcript for nonsense mediated decay. Furthermore, ARGLU1 contains a long, highly evolutionarily conserved sequence known as an Ultraconserved Element (UCE) that is within the retained intron and overlaps the alternative exon. Manipulation of the UCE, in a reporter minigene or via random mutations in the genomic context using CRISPR/Cas9, changed the splicing pattern. Further, overexpression of the ARGLU1 protein shifted the splicing of endogenous ARGLU1 mRNA, resulting in an increase in the retained intron isoform and nonsense mediated decay susceptible isoform and a decrease in the fully spliced isoform. Taken together with data showing that functional protein knockout shifts splicing toward the fully spliced isoform, our data are consistent with a model in which unproductive splicing complexes assembled at the alternative exon lead to inefficient splicing and intron retention.

Acyl modification and binding of mitochondrial ACP to multiprotein complexes

The mitochondrial acyl carrier protein (ACPM/NDUFAB1) is a central element of the mitochondrial fatty acid synthesis type II machinery. Originally ACPM was detected as a subunit of respiratory complex I but the reason for the association with the large enzyme complex remained elusive. Complex I from the aerobic yeast Yarrowia lipolytica comprises two different ACPMs, ACPM1 and ACPM2. They are anchored to the protein complex by LYR (leucine-tyrosine-arginine) motif containing protein (LYRM) subunits LYRM3 (NDUFB9) and LYRM6 (NDUFA6). The ACPM1-LYRM6 and ACPM2-LYRM3 modules are essential for complex I activity and assembly/stability, respectively. We show that in addition to the complex I bound fraction, ACPM1 is present as a free matrix protein and in complex with the soluble LYRM4(ISD11)/NFS1 complex implicated in Fe-S cluster biogenesis. We show that the presence of a long acyl chain bound to the phosphopantetheine cofactor is important for docking ACPMs to protein complexes and we propose that association of ACPMs and LYRMs is universally based on a new protein-protein interaction motif.

Translational compensation of gene copy number alterations by aneuploidy in Drosophila melanogaster

Chromosomal or segmental aneuploidy—the gain or loss of whole or partial chromosomes—is typically deleterious for organisms, a hallmark of cancers, and only occasionally adaptive. To understand the cellular and organismal consequences of aneuploidy, it is important to determine how altered gene doses impact gene expression. Previous studies show that, for some Drosophila cell lines but not others, the dose effect of segmental aneuploidy can be moderately compensated at the mRNA level – aneuploid gene expression is shifted towards wild-type levels. Here, by analyzing genome-wide translation efficiency estimated with ribosome footprint data from the aneuploid Drosophila S2 cell line, we report that the dose effect of aneuploidy can be further compensated at the translational level. Intriguingly, we find no comparable translational compensation in the aneuploid Kc167 cell line. Comparing the properties of aneuploid genes from the two cell lines suggests that selective constraint on gene expression, but neither sequence features nor functions, may partly explain why the two cell lines differ in translational compensation. Our results, together with previous observations that compensation at the mRNA level also varies among Drosophila cell lines and yeast strains, suggest that dosage compensation of aneuploidy is not general but contingent on genotypic and/or developmental context.

A Kinome RNAi Screen in Drosophila Identifies Novel Genes Interacting with Lgl, aPKC, and Crb Cell Polarity Genes in Epithelial Tissues

In both Drosophila melanogaster and mammalian systems, epithelial structure and underlying cell polarity are essential for proper tissue morphogenesis and organ growth. Cell polarity interfaces with multiple cellular processes that are regulated by the phosphorylation status of large protein networks. To gain insight into the molecular mechanisms that coordinate cell polarity with tissue growth, we screened a boutique collection of RNAi stocks targeting the kinome for their capacity to modify Drosophila “cell polarity” eye and wing phenotypes. Initially, we identified kinase or phosphatase genes whose depletion modified adult eye phenotypes associated with the manipulation of cell polarity complexes (via overexpression of Crb or aPKC). We next conducted a secondary screen to test whether these cell polarity modifiers altered tissue overgrowth associated with depletion of Lgl in the wing. These screens identified Hippo, Jun kinase (JNK), and Notch signaling pathways, previously linked to cell polarity regulation of tissue growth. Furthermore, novel pathways not previously connected to cell polarity regulation of tissue growth were identified, including Wingless (Wg/Wnt), Ras, and lipid/Phospho-inositol-3-kinase (PI3K) signaling pathways. Additionally, we demonstrated that the “nutrient sensing” kinases Salt Inducible Kinase 2 and 3 (SIK2 and 3) are potent modifiers of cell polarity phenotypes and regulators of tissue growth. Overall, our screen has revealed novel cell polarity-interacting kinases and phosphatases that affect tissue growth, providing a platform for investigating molecular mechanisms coordinating cell polarity and tissue growth during development.

Recruitment of histone modifications to assist mRNA dosage maintenance after degeneration of cytosine DNA methylation during animal evolution

Following gene duplication, mRNA expression of the duplicated gene is reduced to maintain mRNA dosage. In mammals, this process is achieved with increased cytosine DNA methylation of the promoters of duplicated genes to suppress transcriptional initiation. However, not all animal species possess a full apparatus for cytosine DNA methylation. For such species, such as the roundworm (Caenorhabditis elegans, "worm" hereafter) or fruit fly (Drosophila melanogaster, "fly" hereafter), it is unclear how reduced expression of duplicated genes has been achieved evolutionarily. Here, we hypothesize that in the absence of a classical cytosine DNA methylation pathway, histone modifications play an increasing role in maintaining mRNA dosage following gene duplication. We initially verified that reduced gene expression of duplicated genes had occurred in the worm, fly, and mouse (Mus musculus). Next, several histone marks, with the capacity to control mRNA abundance in the models studied, were examined. In the worm and fly, but not in the mouse, multiple histone modifications were found to assist mRNA dosage maintenance following gene duplication events and the possible involvement of adenine DNA methylation in this process was excluded. Furthermore, the histone marks and acting regions that mediated the reduction in duplicated gene expression were found to be largely organism specific. Thus, it appears that many of the histone marks that maintain mRNA dosage were independently recruited during the evolution of worms and flies to compensate for the loss of cytosine DNA methylation machinery from their genomes.

Small chaperons and autophagy protected neurons from necrotic cell death

Neuronal necrosis occurs during early phase of ischemic insult. However, our knowledge of neuronal necrosis is still inadequate. To study the mechanism of neuronal necrosis, we previously established a Drosophila genetic model of neuronal necrosis by calcium overloading through expression of a constitutively opened cation channel mutant. Here, we performed further genetic screens and identified a suppressor of neuronal necrosis, CG17259, which encodes a seryl-tRNA synthetase. We found that loss-of-function (LOF) CG17259 activated eIF2α phosphorylation and subsequent up-regulation of chaperons (Hsp26 and Hsp27) and autophagy. Genetically, down-regulation of eIF2α phosphorylation, Hsp26/Hsp27 or autophagy reduced the protective effect of LOF CG17259, indicating they function downstream of CG17259. The protective effect of these protein degradation pathways indicated activation of a toxic protein during neuronal necrosis. Our data indicated that p53 was likely one such protein, because p53 was accumulated in the necrotic neurons and down-regulation of p53 rescued necrosis. In the SH-SY5Y human cells, tunicamycin (TM), a PERK activator, promoted transcription of hsp27; and necrosis induced by glutamate could be rescued by TM, associated with reduced p53 accumulation. In an ischemic stroke model in rats, p53 protein was also increased, and TM treatment could reduce the p53 accumulation and brain damage.

NetProt: Complex-based Feature Selection

Protein complex-based feature selection (PCBFS) provides unparalleled reproducibility with high phenotypic relevance on proteomics data. Currently, there are five PCBFS paradigms, but not all representative methods have been implemented or made readily available. To allow general users to take advantage of these methods, we developed the R-package NetProt, which provides implementations of representative feature-selection methods. NetProt also provides methods for generating simulated differential data and generating pseudocomplexes for complex-based performance benchmarking. The NetProt open source R package is available for download from https://github.com/gohwils/NetProt/releases/ , and online documentation is available at http://rpubs.com/gohwils/204259 .

Integrated genome and transcriptome sequencing identifies a noncoding mutation in the genome replication factor DONSON as the cause of microcephaly-micromelia syndrome

While next-generation sequencing has accelerated the discovery of human disease genes, progress has been largely limited to the “low hanging fruit” of mutations with obvious exonic coding or canonical splice site impact. In contrast, the lack of high-throughput, unbiased approaches for functional assessment of most noncoding variants has bottlenecked gene discovery. We report the integration of transcriptome sequencing (RNA-seq), which surveys all mRNAs to reveal functional impacts of variants at the transcription level, into the gene discovery framework for a unique human disease, microcephaly-micromelia syndrome (MMS). MMS is an autosomal recessive condition described thus far in only a single First Nations population and causes intrauterine growth restriction, severe microcephaly, craniofacial anomalies, skeletal dysplasia, and neonatal lethality. Linkage analysis of affected families, including a very large pedigree, identified a single locus on Chromosome 21 linked to the disease (LOD > 9). Comprehensive genome sequencing did not reveal any pathogenic coding or canonical splicing mutations within the linkage region but identified several nonconserved noncoding variants. RNA-seq analysis detected aberrant splicing in DONSON due to one of these noncoding variants, showing a causative role for DONSON disruption in MMS. We show that DONSON is expressed in progenitor cells of embryonic human brain and other proliferating tissues, is co-expressed with components of the DNA replication machinery, and that Donson is essential for early embryonic development in mice as well, suggesting an essential conserved role for DONSON in the cell cycle. Our results demonstrate the utility of integrating transcriptomics into the study of human genetic disease when DNA sequencing alone is not sufficient to reveal the underlying pathogenic mutation.

COP9 signalosome subunits protect Capicua from MAPK-dependent and -independent mechanisms of degradation

The COP9 signalosome removes Nedd8 modifications from the Cullin subunits of ubiquitin ligase complexes, reducing their activity. Here, we show that mutations in the Drosophila COP9 signalosome subunit 1b (CSN1b) gene increase the activity of ubiquitin ligases that contain Cullin 1. Analysis of CSN1b mutant phenotypes revealed a requirement for the COP9 signalosome to prevent ectopic expression of Epidermal growth factor receptor (EGFR) target genes. It does so by protecting Capicua, a transcriptional repressor of EGFR target genes, from EGFR pathway-dependent ubiquitylation by a Cullin 1/SKP1-related A/Archipelago E3 ligase and subsequent proteasomal degradation. The CSN1b subunit also maintains basal Capicua levels by protecting it from a separate mechanism of degradation that is independent of EGFR signaling. As a suppressor of tumor growth and metastasis, Capicua may be an important target of the COP9 signalosome in cancer.

Integration of over 9,000 mass spectrometry experiments builds a global map of human protein complexes

Macromolecular protein complexes carry out many of the essential functions of cells, and many genetic diseases arise from disrupting the functions of such complexes. Currently, there is great interest in defining the complete set of human protein complexes, but recent published maps lack comprehensive coverage. Here, through the synthesis of over 9,000 published mass spectrometry experiments, we present hu.MAP, the most comprehensive and accurate human protein complex map to date, containing > 4,600 total complexes, > 7,700 proteins, and > 56,000 unique interactions, including thousands of confident protein interactions not identified by the original publications. hu.MAP accurately recapitulates known complexes withheld from the learning procedure, which was optimized with the aid of a new quantitative metric (k‐cliques) for comparing sets of sets. The vast majority of complexes in our map are significantly enriched with literature annotations, and the map overall shows improved coverage of many disease‐associated proteins, as we describe in detail for ciliopathies. Using hu.MAP, we predicted and experimentally validated candidate ciliopathy disease genes in vivo in a model vertebrate, discovering CCDC138, WDR90, and KIAA1328 to be new cilia basal body/centriolar satellite proteins, and identifying ANKRD55 as a novel member of the intraflagellar transport machinery. By offering significant improvements to the accuracy and coverage of human protein complexes, hu.MAP (http://proteincomplexes.org) serves as a valuable resource for better understanding the core cellular functions of human proteins and helping to determine mechanistic foundations of human disease.

Spinal Muscular Atrophy: From Defective Chaperoning of snRNP Assembly to Neuromuscular Dysfunction

Spinal Muscular Atrophy (SMA) is a neuromuscular disorder that results from decreased levels of the survival motor neuron (SMN) protein. SMN is part of a multiprotein complex that also includes Gemins 2–8 and Unrip. The SMN-Gemins complex cooperates with the protein arginine methyltransferase 5 (PRMT5) complex, whose constituents include WD45, PRMT5 and pICln. Both complexes function as molecular chaperones, interacting with and assisting in the assembly of an Sm protein core onto small nuclear RNAs (snRNAs) to generate small nuclear ribonucleoproteins (snRNPs), which are the operating components of the spliceosome. Molecular and structural studies have refined our knowledge of the key events taking place within the crowded environment of cells and the numerous precautions undertaken to ensure the faithful assembly of snRNPs. Nonetheless, it remains unclear whether a loss of chaperoning in snRNP assembly, considered as a “housekeeping” activity, is responsible for the selective neuromuscular phenotype in SMA. This review thus shines light on in vivo studies that point toward disturbances in snRNP assembly and the consequential transcriptome abnormalities as the primary drivers of the progressive neuromuscular degeneration underpinning the disease. Disruption of U1 snRNP or snRNP assembly factors other than SMN induces phenotypes that mirror aspects of SMN deficiency, and splicing defects, described in numerous SMA models, can lead to a DNA damage and stress response that compromises the survival of the motor system. Restoring the correct chaperoning of snRNP assembly is therefore predicted to enhance the benefit of SMA therapeutic modalities based on augmenting SMN expression.

Autophagy suppresses Ras-driven epithelial tumourigenesis by limiting the accumulation of reactive oxygen species

Activation of Ras signalling occurs in ~30% of human cancers; however, activated Ras alone is not sufficient for tumourigenesis. In a screen for tumour suppressors that cooperate with oncogenic Ras (Ras^V12) in Drosophila, we identified genes involved in the autophagy pathway. Bioinformatic analysis of human tumours revealed that several core autophagy genes, including GABARAP, correlate with oncogenic KRAS mutations and poor prognosis in human pancreatic cancer, supporting a potential tumour-suppressive effect of the pathway in Ras-driven human cancers. In Drosophila, we demonstrate that blocking autophagy at any step of the pathway enhances Ras^V12-driven epithelial tissue overgrowth via the accumulation of reactive oxygen species and activation of the Jun kinase stress response pathway. Blocking autophagy in Ras^V12 clones also results in non-cell-autonomous effects with autophagy, cell proliferation and caspase activation induced in adjacent wild-type cells. Our study has implications for understanding the interplay between perturbations in Ras signalling and autophagy in tumourigenesis, which might inform the development of novel therapeutics targeting Ras-driven cancers.

Identification of protein complexes by integrating multiple alignment of protein interaction networks

MOTIVATION

Protein complexes are one of the keys to studying the behavior of a cell system. Many biological functions are carried out by protein complexes. During the past decade, the main strategy used to identify protein complexes from high-throughput network data has been to extract near-cliques or highly dense subgraphs from a single protein-protein interaction (PPI) network. Although experimental PPI data have increased significantly over recent years, most PPI networks still have many false positive interactions and false negative edge loss due to the limitations of high-throughput experiments. In particular, the false negative errors restrict the search space of such conventional protein complex identification approaches. Thus, it has become one of the most challenging tasks in systems biology to automatically identify protein complexes.

RESULTS

In this study, we propose a new algorithm, NEOComplex ( NE CC- and O rtholog-based Complex identification by multiple network alignment), which integrates functional orthology information that can be obtained from different types of multiple network alignment (MNA) approaches to expand the search space of protein complex detection. As part of our approach, we also define a new edge clustering coefficient (NECC) to assign weights to interaction edges in PPI networks so that protein complexes can be identified more accurately. The NECC is based on the intuition that there is functional information captured in the common neighbors of the common neighbors as well. Our results show that our algorithm outperforms well-known protein complex identification tools in a balance between precision and recall on three eukaryotic species: human, yeast, and fly. As a result of MNAs of the species, the proposed approach can tolerate edge loss in PPI networks and even discover sparse protein complexes which have traditionally been a challenge to predict.

AVAILABILITY AND IMPLEMENTATION

http://acolab.ie.nthu.edu.tw/bionetwork/NEOComplex.

CONTACT

bab@csail.mit.edu or csliao@ie.nthu.edu.tw.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Translationally controlled tumour protein (TCTP) from tomato and Nicotiana benthamiana is necessary for successful infection by a potyvirus

Translationally controlled tumour protein (TCTP) is a ubiquitously distributed protein in eukaryotes, involved in the regulation of several processes, including cell cycle progression, cell growth, stress protection, apoptosis and maintenance of genomic integrity. Its expression is induced during the early stages of tomato (Solanum lycopersicum) infection by the potyvirus Pepper yellow mosaic virus (PepYMV, a close relative of Potato virus Y). Tomato TCTP is a protein of 168 amino acids, which contains all the conserved domains of the TCTP family. To study the effects of TCTP silencing in PepYMV infection, Nicotiana benthamiana plants were silenced by virus-induced gene silencing (VIGS) and transgenic tomato plants silenced for TCTP were obtained. In the early stages of infection, both tomato and N. benthamiana silenced plants accumulated less virus than control plants. Transgenic tomato plants showed a drastic reduction in symptoms and no viral accumulation at 14 days post-inoculation. Subcellular localization of TCTP was determined in healthy and systemically infected N. benthamiana leaves. TCTP was observed in both the nuclei and cytoplasm of non-infected cells, but only in the cytoplasm of infected cells. Our results indicate that TCTP is a growth regulator necessary for successful PepYMV infection and that its localization is altered by the virus, probably to favour the establishment of virus infection. A network with putative interactions that may occur between TCTP and Arabidopsis thaliana proteins was built. This network brings together experimental data of interactions that occur in other eukaryotes and helps us to discuss the possibilities of TCTP involvement in viral infection.

Mapping, modeling, and characterization of protein-protein interactions on a proteomic scale

Proteins effect a number of biological functions, from cellular signaling, organization, mobility, and transport to catalyzing biochemical reactions and coordinating an immune response. These varied functions are often dependent upon macromolecular interactions, particularly with other proteins. Small-scale studies in the scientific literature report protein-protein interactions (PPIs), but slowly and with bias towards well-studied proteins. In an era where genomic sequence is readily available, deducing genotype-phenotype relationships requires an understanding of protein connectivity at proteome-scale. A proteome-scale map of the protein-protein interaction network provides a global view of cellular organization and function. Here, we discuss a summary of methods for building proteome-scale interactome maps and the current status and implications of mapping achievements. Not only do interactome maps serve as a reference, detailing global cellular function and organization patterns, but they can also reveal the mechanisms altered by disease alleles, highlight the patterns of interaction rewiring across evolution, and help pinpoint biologically and therapeutically relevant proteins. Despite the considerable strides made in proteome-wide mapping, several technical challenges persist. Therefore, future considerations that impact current mapping efforts are also discussed.

Mouse Rif1 is a regulatory subunit of protein phosphatase 1 (PP1)

Rif1 is a conserved protein that plays essential roles in orchestrating DNA replication timing, controlling nuclear architecture, telomere length and DNA repair. However, the relationship between these different roles, as well as the molecular basis of Rif1 function is still unclear. The association of Rif1 with insoluble nuclear lamina has thus far hampered exhaustive characterization of the associated protein complexes. We devised a protocol that overcomes this problem, and were thus able to discover a number of novel Rif1 interactors, involved in chromatin metabolism and phosphorylation. Among them, we focus here on PP1. Data from different systems have suggested that Rif1-PP1 interaction is conserved and has important biological roles. Using mutagenesis, NMR, isothermal calorimetry and surface plasmon resonance we demonstrate that Rif1 is a high-affinity PP1 adaptor, able to out-compete the well-established PP1-inhibitor I2 in vitro. Our conclusions have important implications for understanding Rif1 diverse roles and the relationship between the biological processes controlled by Rif1.

Architecture of the human interactome defines protein communities and disease networks

The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein-protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidation of how genome variation contributes to disease^1–3. Here, we present BioPlex 2.0 (Biophysical Interactions of ORFEOME-derived complexes), which employs robust affinity purification-mass spectrometry (AP-MS) methodology⁴ to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein coding genes from the human genome, and constitutes the largest such network to date. With >56,000 candidate interactions, BioPlex 2.0 contains >29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering (MCL)⁵ of interacting proteins identified more than 1300 protein communities representing diverse cellular activities. Genes essential for cell fitness^6,7 are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.

Enzyme-substrate relationships in the ubiquitin system: approaches for identifying substrates of ubiquitin ligases

Protein ubiquitylation is an important post-translational modification, regulating aspects of virtually every biochemical pathway in eukaryotic cells. Hundreds of enzymes participate in the conjugation and deconjugation of ubiquitin, as well as the recognition, signaling functions, and degradation of ubiquitylated proteins. Regulation of ubiquitylation is most commonly at the level of recognition of substrates by E3 ubiquitin ligases. Characterization of the network of E3-substrate relationships is a major goal and challenge in the field, as this expected to yield fundamental biological insights and opportunities for drug development. There has been remarkable success in identifying substrates for some E3 ligases, in many instances using the standard protein-protein interaction techniques (e.g., two-hybrid screens and co-immunoprecipitations paired with mass spectrometry). However, some E3s have remained refractory to characterization, while others have simply not yet been studied due to the sheer number and diversity of E3s. This review will discuss the range of tools and techniques that can be used for substrate profiling of E3 ligases.

Controlling the Master: Chromatin Dynamics at the MYC Promoter Integrate Developmental Signaling

The transcription factor and cell growth regulator MYC is potently oncogenic and estimated to contribute to most cancers. Decades of attempts to therapeutically target MYC directly have not resulted in feasible clinical applications, and efforts have moved toward indirectly targeting MYC expression, function and/or activity to treat MYC-driven cancer. A multitude of developmental and growth signaling pathways converge on the MYC promoter to modulate transcription through their downstream effectors. Critically, even small increases in MYC abundance (<2 fold) are sufficient to drive overproliferation; however, the details of how oncogenic/growth signaling networks regulate MYC at the level of transcription remain nebulous even during normal development. It is therefore essential to first decipher mechanisms of growth signal-stimulated MYC transcription using in vivo models, with intact signaling environments, to determine exactly how these networks are dysregulated in human cancer. This in turn will provide new modalities and approaches to treat MYC-driven malignancy. Drosophila genetic studies have shed much light on how complex networks signal to transcription factors and enhancers to orchestrate Drosophila MYC (dMYC) transcription, and thus growth and patterning of complex multicellular tissue and organs. This review will discuss the many pathways implicated in patterning MYC transcription during development and the molecular events at the MYC promoter that link signaling to expression. Attention will also be drawn to parallels between mammalian and fly regulation of MYC at the level of transcription.

PTMOracle: A Cytoscape App for Covisualizing and Coanalyzing Post-Translational Modifications in Protein Interaction Networks

Post-translational modifications of proteins (PTMs) act as key regulators of protein activity and of protein-protein interactions (PPIs). To date, it has been difficult to comprehensively explore functional links between PTMs and PPIs. To address this, we developed PTMOracle, a Cytoscape app for coanalyzing PTMs within PPI networks. PTMOracle also allows extensive data to be integrated and coanalyzed with PPI networks, allowing the role of domains, motifs, and disordered regions to be considered. For proteins of interest, or a whole proteome, PTMOracle can generate network visualizations to reveal complex PTM-associated relationships. This is assisted by OraclePainter for coloring proteins by modifications, OracleTools for network analytics, and OracleResults for exploring tabulated findings. To illustrate the use of PTMOracle, we investigate PTM-associated relationships and their role in PPIs in four case studies. In the yeast interactome and its rich set of PTMs, we construct and explore histone-associated and domain-domain interaction networks and show how integrative approaches can predict kinases involved in phosphodegrons. In the human interactome, a phosphotyrosine-associated network is analyzed but highlights the sparse nature of human PPI networks and lack of PTM-associated data. PTMOracle is open source and available at the Cytoscape app store: http://apps.cytoscape.org/apps/ptmoracle .

A computational interactome for prioritizing genes associated with complex agronomic traits in rice (Oryza sativa)

Rice (Oryza sativa) is one of the most important staple foods for more than half of the global population. Many rice traits are quantitative, complex and controlled by multiple interacting genes. Thus, a full understanding of genetic relationships will be critical to systematically identify genes controlling agronomic traits. We developed a genome-wide rice protein-protein interaction network (RicePPINet, http://netbio.sjtu.edu.cn/riceppinet) using machine learning with structural relationship and functional information. RicePPINet contained 708 819 predicted interactions for 16 895 non-transposable element related proteins. The power of the network for discovering novel protein interactions was demonstrated through comparison with other publicly available protein-protein interaction (PPI) prediction methods, and by experimentally determined PPI data sets. Furthermore, global analysis of domain-mediated interactions revealed RicePPINet accurately reflects PPIs at the domain level. Our studies showed the efficiency of the RicePPINet-based method in prioritizing candidate genes involved in complex agronomic traits, such as disease resistance and drought tolerance, was approximately 2-11 times better than random prediction. RicePPINet provides an expanded landscape of computational interactome for the genetic dissection of agronomically important traits in rice.

Systematic Analysis of Human Protein Phosphatase Interactions and Dynamics

Coordinated activities of protein kinases and phosphatases ensure phosphorylation homeostasis, which, when perturbed, can instigate diseases, including cancer. Yet, in contrast to kinases, much less is known about protein phosphatase functions and their interactions and complexes. Here, we used quantitative affinity proteomics to assay protein-protein interactions for 54 phosphatases distributed across the three major protein phosphatase families, with additional analysis of their 12 co-factors. We identified 838 high-confidence interactions, of which 631, to our knowledge, have not been reported before. We show that inhibiting the activity of phosphatases PP1 and PP2A by okadaic acid disrupts their specific interactions, supporting the potential of therapeutics that target these proteins. Additional analyses revealed candidate physical and functional interaction links to phosphatase-based regulation of several signaling pathways and to human cancer. Our study provides an initial glimpse of the protein interaction landscape of phosphatases and their functions in cellular regulation.