A protein complex network of Drosophila melanogaster

Mitochondrial targets for pharmacological intervention in human disease

Over the past several years, mitochondrial dysfunction has been linked to an increasing number of human illnesses, making mitochondrial proteins (MPs) an ever more appealing target for therapeutic intervention. With 20% of the mitochondrial proteome (312 of an estimated 1500 MPs) having known interactions with small molecules, MPs appear to be highly targetable. Yet, despite these targeted proteins functioning in a range of biological processes (including induction of apoptosis, calcium homeostasis, and metabolism), very few of the compounds targeting MPs find clinical use. Recent work has greatly expanded the number of proteins known to localize to the mitochondria and has generated a considerable increase in MP 3D structures available in public databases, allowing experimental screening and in silico prediction of mitochondrial drug targets on an unprecedented scale. Here, we summarize the current literature on clinically active drugs that target MPs, with a focus on how existing drug targets are distributed across biochemical pathways and organelle substructures. Also, we examine current strategies for mitochondrial drug discovery, focusing on genetic, proteomic, and chemogenomic assays, and relevant model systems. As cell models and screening techniques improve, MPs appear poised to emerge as relevant targets for a wide range of complex human diseases, an eventuality that can be expedited through systematic analysis of MP function.

p38 MAP kinase regulates circadian rhythms in Drosophila

The large repertoire of circadian rhythms in diverse organisms depends on oscillating central clock genes, input pathways for entrainment, and output pathways for controlling rhythmic behaviors. Stress-activated p38 MAP Kinases (p38K), although sparsely investigated in this context, show circadian rhythmicity in mammalian brains and are considered part of the circadian output machinery in Neurospora. We find that Drosophila p38Kb is expressed in clock neurons, and mutants in p38Kb either are arrhythmic or have a longer free-running periodicity, especially as they age. Paradoxically, similar phenotypes are observed through either transgenic inhibition or activation of p38Kb in clock neurons, suggesting a requirement for optimal p38Kb function for normal free-running circadian rhythms. We also find that p38Kb genetically interacts with multiple downstream targets to regulate circadian locomotor rhythms. More specifically, p38Kb interacts with the period gene to regulate period length and the strength of rhythmicity. In addition, we show that p38Kb suppresses the arrhythmic behavior associated with inhibition of a second p38Kb target, the transcription factor Mef2. Finally, we find that manipulating p38K signaling in free-running conditions alters the expression of another downstream target, MNK/Lk6, which has been shown to cycle with the clock and to play a role in regulating circadian rhythms. These data suggest that p38Kb may affect circadian locomotor rhythms through the regulation of multiple downstream pathways.

Beadex function in the motor neurons is essential for female reproduction in Drosophila melanogaster

Drosophila melanogaster has served as an excellent model system for understanding the neuronal circuits and molecular mechanisms regulating complex behaviors. The Drosophila female reproductive circuits, in particular, are well studied and can be used as a tool to understand the role of novel genes in neuronal function in general and female reproduction in particular. In the present study, the role of Beadex, a transcription co-activator, in Drosophila female reproduction was assessed by generation of mutant and knock down studies. Null allele of Beadex was generated by transposase induced excision of P-element present within an intron of Beadex gene. The mutant showed highly compromised reproductive abilities as evaluated by reduced fecundity and fertility, abnormal oviposition and more importantly, the failure of sperm release from storage organs. However, no defect was found in the overall ovariole development. Tissue specific, targeted knock down of Beadex indicated that its function in neurons is important for efficient female reproduction, since its neuronal knock down led to compromised female reproductive abilities, similar to Beadex null females. Further, different neuronal class specific knock down studies revealed that Beadex function is required in motor neurons for normal fecundity and fertility of females. Thus, the present study attributes a novel and essential role for Beadex in female reproduction through neurons.

Accurate protein complex retrieval by affinity enrichment mass spectrometry (AE-MS) rather than affinity purification mass spectrometry (AP-MS)

Protein–protein interactions are fundamental to the understanding of biological processes. Affinity purification coupled to mass spectrometry (AP-MS) is one of the most promising methods for their investigation. Previously, complexes were purified as much as possible, frequently followed by identification of individual gel bands. However, todays mass spectrometers are highly sensitive, and powerful quantitative proteomics strategies are available to distinguish true interactors from background binders. Here we describe a high performance affinity enrichment-mass spectrometry method for investigating protein–protein interactions, in which no attempt at purifying complexes to homogeneity is made. Instead, we developed analysis methods that take advantage of specific enrichment of interactors in the context of a large amount of unspecific background binders. We perform single-step affinity enrichment of endogenously expressed GFP-tagged proteins and their interactors in budding yeast, followed by single-run, intensity-based label-free quantitative LC-MS/MS analysis. Each pull-down contains around 2000 background binders, which are reinterpreted from troubling contaminants to crucial elements in a novel data analysis strategy. First the background serves for accurate normalization. Second, interacting proteins are not identified by comparison to a single untagged control strain, but instead to the other tagged strains. Third, potential interactors are further validated by their intensity profiles across all samples. We demonstrate the power of our AE-MS method using several well-known and challenging yeast complexes of various abundances. AE-MS is not only highly efficient and robust, but also cost effective, broadly applicable, and can be performed in any laboratory with access to high-resolution mass spectrometers.

Expanding the roles of chromatin insulators in nuclear architecture, chromatin organization and genome function

Of the numerous classes of elements involved in modulating eukaryotic chromosome structure and function, chromatin insulators arguably remain the most poorly understood in their contribution to these processes in vivo. Indeed, our view of chromatin insulators has evolved dramatically since their chromatin boundary and enhancer blocking properties were elucidated roughly a quarter of a century ago as a result of recent genome-wide, high-throughput methods better suited to probing the role of these elements in their native genomic contexts. The overall theme that has emerged from these studies is that chromatin insulators function as general facilitators of higher-order chromatin loop structures that exert both physical and functional constraints on the genome. In this review, we summarize the result of recent work that supports this idea as well as a number of other studies linking these elements to a diverse array of nuclear processes, suggesting that chromatin insulators exert master control over genome organization and behavior.

Affinity purification-mass spectrometry and network analysis to understand protein-protein interactions

By determining protein-protein interactions in normal, diseased and infected cells, we can improve our understanding of cellular systems and their reaction to various perturbations. In this protocol, we discuss how to use data obtained in affinity purification-mass spectrometry (AP-MS) experiments to generate meaningful interaction networks and effective figures. We begin with an overview of common epitope tagging, expression and AP practices, followed by liquid chromatography-MS (LC-MS) data collection. We then provide a detailed procedure covering a pipeline approach to (i) pre-processing the data by filtering against contaminant lists such as the Contaminant Repository for Affinity Purification (CRAPome) and normalization using the spectral index (SIN) or normalized spectral abundance factor (NSAF); (ii) scoring via methods such as MiST, SAInt and CompPASS; and (iii) testing the resulting scores. Data formats familiar to MS practitioners are then transformed to those most useful for network-based analyses. The protocol also explores methods available in Cytoscape to visualize and analyze these types of interaction data. The scoring pipeline can take anywhere from 1 d to 1 week, depending on one's familiarity with the tools and data peculiarities. Similarly, the network analysis and visualization protocol in Cytoscape takes 2-4 h to complete with the provided sample data, but we recommend taking days or even weeks to explore one's data and find the right questions.

A genetic screen identifies Tor as an interactor of VAPB in a Drosophila model of amyotrophic lateral sclerosis

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder characterized by selective death of motor neurons. In 5–10% of the familial cases, the disease is inherited because of mutations. One such mutation, P56S, was identified in human VAPB that behaves in a dominant negative manner, sequestering wild type protein into cytoplasmic inclusions.

We have conducted a reverse genetic screen to identify interactors of Drosophila VAPB. We screened 2635 genes and identified 103 interactors, of which 45 were enhancers and 58 were suppressors of VAPB function. Interestingly, the screen identified known ALS loci – TBPH, alsin2 and SOD1. Also identified were genes involved in cellular energetics and homeostasis which were used to build a gene regulatory network of VAPB modifiers. One key modifier identified was Tor, whose knockdown reversed the large bouton phenotype associated with VAP(P58S) expression in neurons. A similar reversal was seen by over-expressing Tuberous Sclerosis Complex (Tsc1,2) that negatively regulates TOR signaling as also by reduction of S6K activity. In comparison, the small bouton phenotype associated with VAP(wt) expression was reversed with Tsc1 knock down as well as S6K-CA expression. Tor therefore interacts with both VAP(wt) and VAP(P58S), but in a contrasting manner. Reversal of VAP(P58S) bouton phenotypes in larvae fed with the TOR inhibitor Rapamycin suggests upregulation of TOR signaling in response to VAP(P58S) expression.

The VAPB network and further mechanistic understanding of interactions with key pathways, such as the TOR cassette, will pave the way for a better understanding of the mechanisms of onset and progression of motor neuron disease.

A quantitative chaperone interaction network reveals the architecture of cellular protein homeostasis pathways

Chaperones are abundant cellular proteins that promote the folding and function of their substrate proteins (clients). In vivo, chaperones also associate with a large and diverse set of cofactors (cochaperones) that regulate their specificity and function. However, how these cochaperones regulate protein folding and whether they have chaperone-independent biological functions is largely unknown. We combined mass spectrometry and quantitative high-throughput LUMIER assays to systematically characterize the chaperone-cochaperone-client interaction network in human cells. We uncover hundreds of chaperone clients, delineate their participation in specific cochaperone complexes, and establish a surprisingly distinct network of protein-protein interactions for cochaperones. As a salient example of the power of such analysis, we establish that NUDC family cochaperones specifically associate with structurally related but evolutionarily distinct β-propeller folds. We provide a framework for deciphering the proteostasis network and its regulation in development and disease and expand the use of chaperones as sensors for drug-target engagement.

Substrate trapping proteomics reveals targets of the βTrCP2/FBXW11 ubiquitin ligase

Defining the full complement of substrates for each ubiquitin ligase remains an important challenge. Improvements in mass spectrometry instrumentation and computation and in protein biochemistry methods have resulted in several new methods for ubiquitin ligase substrate identification. Here we used the parallel adapter capture (PAC) proteomics approach to study βTrCP2/FBXW11, a substrate adaptor for the SKP1-CUL1-F-box (SCF) E3 ubiquitin ligase complex. The processivity of the ubiquitylation reaction necessitates transient physical interactions between FBXW11 and its substrates, thus making biochemical purification of FBXW11-bound substrates difficult. Using the PAC-based approach, we inhibited the proteasome to "trap" ubiquitylated substrates on the SCF(FBXW11) E3 complex. Comparative mass spectrometry analysis of immunopurified FBXW11 protein complexes before and after proteasome inhibition revealed 21 known and 23 putatively novel substrates. In focused studies, we found that SCF(FBXW11) bound, polyubiquitylated, and destabilized RAPGEF2, a guanine nucleotide exchange factor that activates the small GTPase RAP1. High RAPGEF2 protein levels promoted cell-cell fusion and, consequently, multinucleation. Surprisingly, this occurred independently of the guanine nucleotide exchange factor (GEF) catalytic activity and of the presence of RAP1. Our data establish new functions for RAPGEF2 that may contribute to aneuploidy in cancer. More broadly, this report supports the continued use of substrate trapping proteomics to comprehensively define targets for E3 ubiquitin ligases. All proteomic data are available via ProteomeXchange with identifier PXD001062.

Spotlite: web application and augmented algorithms for predicting co-complexed proteins from affinity purification--mass spectrometry data

Protein-protein interactions defined by affinity purification and mass spectrometry (APMS) suffer from high false discovery rates. Consequently, lists of potential interactions must be pruned of contaminants before network construction and interpretation, historically an expensive, time-intensive, and error-prone task. In recent years, numerous computational methods were developed to identify genuine interactions from the hundreds of candidates. Here, comparative analysis of three popular algorithms, HGSCore, CompPASS, and SAINT, revealed complementarity in their classification accuracies, which is supported by their divergent scoring strategies. We improved each algorithm by an average area under a receiver operating characteristics curve increase of 16% by integrating a variety of indirect data known to correlate with established protein-protein interactions, including mRNA coexpression, gene ontologies, domain-domain binding affinities, and homologous protein interactions. Each APMS scoring approach was incorporated into a separate logistic regression model along with the indirect features; the resulting three classifiers demonstrate improved performance on five diverse APMS data sets. To facilitate APMS data scoring within the scientific community, we created Spotlite, a user-friendly and fast web application. Within Spotlite, data can be scored with the augmented classifiers, annotated, and visualized ( http://cancer.unc.edu/majorlab/software.php ). The utility of the Spotlite platform to reveal physical, functional, and disease-relevant characteristics within APMS data is established through a focused analysis of the KEAP1 E3 ubiquitin ligase.

From pathways to networks: connecting dots by establishing protein-protein interaction networks in signaling pathways using affinity purification and mass spectrometry

Signal transductions are the basis of biological activities in all living organisms. Studying the signaling pathways, especially under physiological conditions, has become one of the most important facets of modern biological research. During the last decade, MS has been used extensively in biological research and is proven to be effective in addressing important biological questions. Here, we review the current progress in the understanding of signaling networks using MS approaches. We will focus on studies of protein-protein interactions that use affinity purification followed by MS approach. We discuss obstacles to affinity purification, data processing, functional validation, and identification of transient interactions and provide potential solutions for pathway-specific proteomics analysis, which we hope one day will lead to a comprehensive understanding of signaling networks in humans.

Combining genetic perturbations and proteomics to examine kinase-phosphatase networks in Drosophila embryos

Connecting phosphorylation events to kinases and phosphatases is key to understanding the molecular organization and signaling dynamics of networks. We have generated a validated set of transgenic RNA-interference reagents for knockdown and characterization of all protein kinases and phosphatases present during early Drosophila melanogaster development. These genetic tools enable collection of sufficient quantities of embryos depleted of single gene products for proteomics. As a demonstration of an application of the collection, we have used multiplexed isobaric labeling for quantitative proteomics to derive global phosphorylation signatures associated with kinase-depleted embryos to systematically link phosphosites with relevant kinases. We demonstrate how this strategy uncovers kinase consensus motifs and prioritizes phosphoproteins for kinase target validation. We validate this approach by providing auxiliary evidence for Wee kinase-directed regulation of the chromatin regulator Stonewall. Further, we show how correlative phosphorylation at the site level can indicate function, as exemplified by Sterile20-like kinase-dependent regulation of Stat92E.

Analysis of the expression patterns, subcellular localisations and interaction partners of Drosophila proteins using a pigP protein trap library

Although we now have a wealth of information on the transcription patterns of all the genes in the Drosophila genome, much less is known about the properties of the encoded proteins. To provide information on the expression patterns and subcellular localisations of many proteins in parallel, we have performed a large-scale protein trap screen using a hybrid piggyBac vector carrying an artificial exon encoding yellow fluorescent protein (YFP) and protein affinity tags. From screening 41 million embryos, we recovered 616 verified independent YFP-positive lines representing protein traps in 374 genes, two-thirds of which had not been tagged in previous P element protein trap screens. Over 20 different research groups then characterized the expression patterns of the tagged proteins in a variety of tissues and at several developmental stages. In parallel, we purified many of the tagged proteins from embryos using the affinity tags and identified co-purifying proteins by mass spectrometry. The fly stocks are publicly available through the Kyoto Drosophila Genetics Resource Center. All our data are available via an open access database (Flannotator), which provides comprehensive information on the expression patterns, subcellular localisations and in vivo interaction partners of the trapped proteins. Our resource substantially increases the number of available protein traps in Drosophila and identifies new markers for cellular organelles and structures.

Transcription factor networks in Drosophila melanogaster

Specific cellular fates and functions depend on differential gene expression, which occurs primarily at the transcriptional level and is controlled by complex regulatory networks of transcription factors (TFs). TFs act through combinatorial interactions with other TFs, cofactors, and chromatin-remodeling proteins. Here, we define protein-protein interactions using a coaffinity purification/mass spectrometry method and study 459 Drosophila melanogaster transcription-related factors, representing approximately half of the established catalog of TFs. We probe this network in vivo, demonstrating functional interactions for many interacting proteins, and test the predictive value of our data set. Building on these analyses, we combine regulatory network inference models with physical interactions to define an integrated network that connects combinatorial TF protein interactions to the transcriptional regulatory network of the cell. We use this integrated network as a tool to connect the functional network of genetic modifiers related to mastermind, a transcriptional cofactor of the Notch pathway.

Drosophila TAP/p32 is a core histone chaperone that cooperates with NAP-1, NLP, and nucleophosmin in sperm chromatin remodeling during fertilization

Nuclear DNA in the male gamete of sexually reproducing animals is organized as sperm chromatin compacted primarily by sperm-specific protamines. Fertilization leads to sperm chromatin remodeling, during which protamines are expelled and replaced by histones. Despite our increased understanding of the factors that mediate nucleosome assembly in the nascent male pronucleus, the machinery for protamine removal remains largely unknown. Here we identify four Drosophila protamine chaperones that mediate the dissociation of protamine-DNA complexes: NAP-1, NLP, and nucleophosmin are previously characterized histone chaperones, and TAP/p32 has no known function in chromatin metabolism. We show that TAP/p32 is required for the removal of Drosophila protamine B in vitro, whereas NAP-1, NLP, and Nph share roles in the removal of protamine A. Embryos from P32-null females show defective formation of the male pronucleus in vivo. TAP/p32, similar to NAP-1, NLP, and Nph, facilitates nucleosome assembly in vitro and is therefore a histone chaperone. Furthermore, mutants of P32, Nlp, and Nph exhibit synthetic-lethal genetic interactions. In summary, we identified factors mediating protamine removal from DNA and reconstituted in a defined system the process of sperm chromatin remodeling that exchanges protamines for histones to form the nucleosome-based chromatin characteristic of somatic cells.

κB-Ras proteins regulate both NF-κB-dependent inflammation and Ral-dependent proliferation

The transformation of cells generally involves multiple genetic lesions that undermine control of both cell death and proliferation. We now report that κB-Ras proteins act as regulators of NF-κB and Ral pathways, which control inflammation/cell death and proliferation, respectively. Cells lacking κB-Ras therefore not only show increased NF-κB activity, which results in increased expression of inflammatory mediators, but also exhibit elevated Ral activity, which leads to enhanced anchorage-independent proliferation (AIP). κB-Ras deficiency consequently leads to significantly increased tumor growth that can be dampened by inhibiting either Ral or NF-κB pathways, revealing the unique tumor-suppressive potential of κB-Ras proteins. Remarkably, numerous human tumors show reduced levels of κB-Ras, and increasing the level of κB-Ras in these tumor cells impairs their ability to undergo AIP, thereby implicating κB-Ras proteins in human disease.

Discovery and characterization of two Nimrod superfamily members in Anopheles gambiae

Anti-bacterial proteins in mosquitoes are known to play an important modulatory role on immune responses to infections with human pathogens including malaria parasites. In this study we characterized two members of the Anopheles gambiae Nimrod superfamily, namely AgNimB2 and AgEater. We confirm that current annotation of the An. gambiae genome incorrectly identifies AgNimB2 and AgEater as a single gene, AGAP009762. Through in silico and experimental approaches, it has been shown that AgNimB2 is a secreted protein that mediates phagocytosis of Staphylococcus aureus but not of Escherichia coli bacteria. We also reveal that this function does not involve a direct interaction of AgNimB2 with S. aureus. Therefore, AgNimB2 may act downstream of complement-like pathway activation, first requiring bacterial opsonization. In addition, it has been shown that AgNimB2 has an anti-Plasmodium effect. Conversely, AgEater is a membrane-bound protein that either functions redundantly or is dispensable for phagocytosis of E. coli or S. aureus. Our study provides insights into the role of members of the complex Nimrod superfamily in An. gambiae, the most important African vector of human malaria.

From proteomes to complexomes in the era of systems biology

Protein complexes carry out almost the entire signaling and functional processes in the cell. The protein complex complement of a cell, and its network of complex-complex interactions, is referred to here as the complexome. Computational methods to predict protein complexes from proteomics data, resulting in network representations of complexomes, have recently being developed. In addition, key advances have been made toward understanding the network and structural organization of complexomes. We review these bioinformatics advances, and their discovery-potential, as well as the merits of integrating proteomics data with emerging methods in systems biology to study protein complex signaling. It is envisioned that improved integration of proteomics and systems biology, incorporating the dynamics of protein complexes in space and time, may lead to more predictive models of cell signaling networks for effective modulation.

Heterochromatin-associated interactions of Drosophila HP1a with dADD1, HIPP1, and repetitive RNAs

Heterochromatin protein 1 (HP1a) plays conserved roles in gene silencing and heterochromatin and is also implicated in transcription, DNA replication, and repair. Using BioTAP-XL mass spectrometry and sequencing across multiple life stages of Drosophila, Alekseyenko et al. identify HP1a chromatin-associated protein and RNA interactions. They discover 13 novel candidates among the top interactions. Furthermore, HP1a selectively associates with a broad set of RNAs transcribed from repetitive regions. The validation of several novel HP1a protein interactors reveals new HP1a links to chromatin organization and function.

Heterochromatin protein 1 (HP1a) has conserved roles in gene silencing and heterochromatin and is also implicated in transcription, DNA replication, and repair. Here we identify chromatin-associated protein and RNA interactions of HP1a by BioTAP-XL mass spectrometry and sequencing from Drosophila S2 cells, embryos, larvae, and adults. Our results reveal an extensive list of known and novel HP1a-interacting proteins, of which we selected three for validation. A strong novel interactor, dADD1 (Drosophila ADD1) (CG8290), is highly enriched in heterochromatin, harbors an ADD domain similar to human ATRX, displays selective binding to H3K9me2 and H3K9me3, and is a classic genetic suppressor of position-effect variegation. Unexpectedly, a second hit, HIPP1 (HP1 and insulator partner protein-1) (CG3680), is strongly connected to CP190-related complexes localized at putative insulator sequences throughout the genome in addition to its colocalization with HP1a in heterochromatin. A third interactor, the histone methyltransferase MES-4, is also enriched in heterochromatin. In addition to these protein–protein interactions, we found that HP1a selectively associated with a broad set of RNAs transcribed from repetitive regions. We propose that this rich network of previously undiscovered interactions will define how HP1a complexes perform their diverse functions in cells and developing organisms.

DNA copy number evolution in Drosophila cell lines

BACKGROUND

Structural rearrangements of the genome resulting in genic imbalance due to copy number change are often deleterious at the organismal level, but are common in immortalized cell lines and tumors, where they may be an advantage to cells. In order to explore the biological consequences of copy number changes in the Drosophila genome, we resequenced the genomes of 19 tissue-culture cell lines and generated RNA-Seq profiles.

RESULTS

Our work revealed dramatic duplications and deletions in all cell lines. We found three lines of evidence indicating that copy number changes were due to selection during tissue culture. First, we found that copy numbers correlated to maintain stoichiometric balance in protein complexes and biochemical pathways, consistent with the gene balance hypothesis. Second, while most copy number changes were cell line-specific, we identified some copy number changes shared by many of the independent cell lines. These included dramatic recurrence of increased copy number of the PDGF/VEGF receptor, which is also over-expressed in many cancer cells, and of bantam, an anti-apoptosis miRNA. Third, even when copy number changes seemed distinct between lines, there was strong evidence that they supported a common phenotypic outcome. For example, we found that proto-oncogenes were over-represented in one cell line (S2-DRSC), whereas tumor suppressor genes were under-represented in another (Kc167).

CONCLUSION

Our study illustrates how genome structure changes may contribute to selection of cell lines in vitro. This has implications for other cell-level natural selection progressions, including tumorigenesis.

The Ca2+ sensor protein swiprosin-1/EFhd2 is present in neurites and involved in kinesin-mediated transport in neurons

Swiprosin-1/EFhd2 (EFhd2) is a cytoskeletal Ca²⁺ sensor protein strongly expressed in the brain. It has been shown to interact with mutant tau, which can promote neurodegeneration, but nothing is known about the physiological function of EFhd2 in the nervous system. To elucidate this question, we analyzed EFhd2^−/−/lacZ reporter mice and showed that lacZ was strongly expressed in the cortex, the dentate gyrus, the CA1 and CA2 regions of the hippocampus, the thalamus, and the olfactory bulb. Immunohistochemistry and western blotting confirmed this pattern and revealed expression of EFhd2 during neuronal maturation. In cortical neurons, EFhd2 was detected in neurites marked by MAP2 and co-localized with pre- and post-synaptic markers. Approximately one third of EFhd2 associated with a biochemically isolated synaptosome preparation. There, EFhd2 was mostly confined to the cytosolic and plasma membrane fractions. Both synaptic endocytosis and exocytosis in primary hippocampal EFhd2^−/− neurons were unaltered but transport of synaptophysin-GFP containing vesicles was enhanced in EFhd2^−/− primary hippocampal neurons, and notably, EFhd2 inhibited kinesin mediated microtubule gliding. Therefore, we found that EFhd2 is a neuronal protein that interferes with kinesin-mediated transport.

Pogo-like transposases have been repeatedly domesticated into CENP-B-related proteins

The centromere is a chromatin region that is required for accurate inheritance of eukaryotic chromosomes during cell divisions. Among the different centromere-associated proteins (CENP) identified, CENP-B has been independently domesticated from a pogo-like transposase twice: Once in mammals and once in fission yeast. Recently, a third independent domestication restricted to holocentric lepidoptera has been described. In this work, we take advantage of the high-quality genome sequence and the wealth of functional information available for Drosophila melanogaster to further investigate the possibility of additional independent domestications of pogo-like transposases into host CENP-B related proteins. Our results showed that CENP-B related genes are not restricted to holocentric insects. Furthermore, we showed that at least three independent domestications of pogo-like transposases have occurred in metazoans. Our results highlight the importance of transposable elements as raw material for the recurrent evolution of important cellular functions.

Identification of novel Drosophila centromere-associated proteins

Centromeres are chromosomal regions crucial for correct chromosome segregation during mitosis and meiosis. They are epigenetically defined by centromeric proteins such as the centromere-specific histone H3-variant centromere protein A (CENP-A). In humans, 16 additional proteins have been described to be constitutively associated with centromeres throughout the cell cycle, known as the constitutive centromere-associated network (CCAN). In contrast, only one additional constitutive centromeric protein is known in Drosophila melanogaster (D.mel), the conserved CCAN member CENP-C. To gain further insights into D.mel centromere composition and biology, we analyzed affinity-purified chromatin prepared from D.mel cell lines expressing green fluorescent protein tagged histone three variants by MS. In addition to already-known centromeric proteins, we identified novel factors that were repeatedly enriched in affinity purification-MS experiments. We analyzed the cellular localization of selected candidates by immunocytochemistry and confirmed localization to the centromere and other genomic regions for ten factors. Furthermore, RNA interference mediated depletion of CG2051, CG14480, and hyperplastic discs, three of our strongest candidates, leads to elevated mitotic defects. Knockdowns of these candidates neither impair the localization of several known kinetochore proteins nor CENP-A(CID) loading, suggesting their involvement in alternative pathways that contribute to proper centromere function. In summary, we provide a comprehensive analysis of the proteomic composition of Drosophila centromeres. All MS data have been deposited in the ProteomeXchange with identifier PXD000758 (http://proteomecentral.proteomexchange.org/dataset/PXD000758).

Spatiotemporal positioning of multipotent modules in diverse biological networks

A biological network exhibits a modular organization. The modular structure dependent on functional module is of great significance in understanding the organization and dynamics of network functions. A huge variety of module identification methods as well as approaches to analyze modularity and dynamics of the inter- and intra-module interactions have emerged recently, but they are facing unexpected challenges in further practical applications. Here, we discuss recent progress in understanding how such a modular network can be deconstructed spatiotemporally. We focus particularly on elucidating how various deciphering mechanisms operate to ensure precise module identification and assembly. In this case, a system-level understanding of the entire mechanism of module construction is within reach, with important implications for reasonable perspectives in both constructing a modular analysis framework and deconstructing different modular hierarchical structures.

Integrating the interactome and the transcriptome of Drosophila

Background

Networks of interacting genes and gene products mediate most cellular and developmental processes. High throughput screening methods combined with literature curation are identifying many of the protein-protein interactions (PPI) and protein-DNA interactions (PDI) that constitute these networks. Most of the detection methods, however, fail to identify the in vivo spatial or temporal context of the interactions. Thus, the interaction data are a composite of the individual networks that may operate in specific tissues or developmental stages. Genome-wide expression data may be useful for filtering interaction data to identify the subnetworks that operate in specific spatial or temporal contexts. Here we take advantage of the extensive interaction and expression data available for Drosophila to analyze how interaction networks may be unique to specific tissues and developmental stages.

Results

We ranked genes on a scale from ubiquitously expressed to tissue or stage specific and examined their interaction patterns. Interestingly, ubiquitously expressed genes have many more interactions among themselves than do non-ubiquitously expressed genes both in PPI and PDI networks. While the PDI network is enriched for interactions between tissue-specific transcription factors and their tissue-specific targets, a preponderance of the PDI interactions are between ubiquitous and non-ubiquitously expressed genes and proteins. In contrast to PDI, PPI networks are depleted for interactions among tissue- or stage- specific proteins, which instead interact primarily with widely expressed proteins. In light of these findings, we present an approach to filter interaction data based on gene expression levels normalized across tissues or developmental stages. We show that this filter (the percent maximum or pmax filter) can be used to identify subnetworks that function within individual tissues or developmental stages.

Conclusions

These observations suggest that protein networks are frequently organized into hubs of widely expressed proteins to which are attached various tissue- or stage-specific proteins. This is consistent with earlier analyses of human PPI data and suggests a similar organization of interaction networks across species. This organization implies that tissue or stage specific networks can be best identified from interactome data by using filters designed to include both ubiquitously expressed and specifically expressed genes and proteins.

Singlet oxygen triplet energy transfer-based imaging technology for mapping protein-protein proximity in intact cells

Many cellular processes are carried out by large protein complexes that can span several tens of nanometres. Whereas forster resonance energy transfer has a detection range of <10 nm, here we report the theoretical development and experimental demonstration of a new fluorescence-imaging technology with a detection range of up to several tens of nanometres: singlet oxygen triplet energy transfer. We demonstrate that our method confirms the topology of a large protein complex in intact cells, which spans from the endoplasmic reticulum to the outer mitochondrial membrane and the matrix. This new method is thus suited for mapping protein proximity in large protein complexes.

Messages do diffuse faster than messengers: reconciling disparate estimates of the morphogen bicoid diffusion coefficient

The gradient of Bicoid (Bcd) is key for the establishment of the anterior-posterior axis in Drosophila embryos. The gradient properties are compatible with the SDD model in which Bcd is synthesized at the anterior pole and then diffuses into the embryo and is degraded with a characteristic time. Within this model, the Bcd diffusion coefficient is critical to set the timescale of gradient formation. This coefficient has been measured using two optical techniques, Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Correlation Spectroscopy (FCS), obtaining estimates in which the FCS value is an order of magnitude larger than the FRAP one. This discrepancy raises the following questions: which estimate is "correct''; what is the reason for the disparity; and can the SDD model explain Bcd gradient formation within the experimentally observed times? In this paper, we use a simple biophysical model in which Bcd diffuses and interacts with binding sites to show that both the FRAP and the FCS estimates may be correct and compatible with the observed timescale of gradient formation. The discrepancy arises from the fact that FCS and FRAP report on different effective (concentration dependent) diffusion coefficients, one of which describes the spreading rate of the individual Bcd molecules (the messengers) and the other one that of their concentration (the message). The latter is the one that is more relevant for the gradient establishment and is compatible with its formation within the experimentally observed times.

Understanding the mechanisms by which equivalent cells develop into different body parts is a fundamental question in biology. One well-studied example is the patterning along the anterior-posterior axis of Drosophila melanogaster embryos for which the spatial gradient of the protein Bicoid is determinant. The localized production of Bicoid is implicated in its inhomogeneous distribution. Diffusion then determines the time and spatial scales of the gradient as it is formed. Estimates of Bicoid diffusion coefficients made with the optical techniques, FRAP and FCS resulted in largely different values, one of which was too slow to account for the observed time of gradient formation. In this paper, we present a model in which Bicoid diffuses and interacts with binding sites so that its transport is described by a "single molecule'' and a "collective'' diffusion coefficient. The latter can be arbitrarily larger than the former coefficient and sets the rate for bulk processes such as the formation of the gradient. In this way we obtain a self-consistent picture in which the FRAP and FCS estimates are accurate and where the gradient can be established within the experimentally observed times.

Protein-protein interactions and genetic diseases: The interactome

Protein-protein interactions mediate essentially all biological processes. Despite the quality of these data being widely questioned a decade ago, the reproducibility of large-scale protein interaction data is now much improved and there is little question that the latest screens are of high quality. Moreover, common data standards and coordinated curation practices between the databases that collect the interactions have made these valuable data available to a wide group of researchers. Here, I will review how protein-protein interactions are measured, collected and quality controlled. I discuss how the architecture of molecular protein networks has informed disease biology, and how these data are now being computationally integrated with the newest genomic technologies, in particular genome-wide association studies and exome-sequencing projects, to improve our understanding of molecular processes perturbed by genetics in human diseases. This article is part of a Special Issue entitled: From Genome to Function.

Proteogenomic convergence for understanding cancer pathways and networks

During the past several decades, the understanding of cancer at the molecular level has been primarily focused on mechanisms on how signaling molecules transform homeostatically balanced cells into malignant ones within an individual pathway. However, it is becoming more apparent that pathways are dynamic and crosstalk at different control points of the signaling cascades, making the traditional linear signaling models inadequate to interpret complex biological systems. Recent technological advances in high throughput, deep sequencing for the human genomes and proteomic technologies to comprehensively characterize the human proteomes in conjunction with multiplexed targeted proteomic assays to measure panels of proteins involved in biologically relevant pathways have made significant progress in understanding cancer at the molecular level. It is undeniable that proteomic profiling of differentially expressed proteins under many perturbation conditions, or between normal and "diseased" states is important to capture a first glance at the overall proteomic landscape, which has been a main focus of proteomics research during the past 15-20 years. However, the research community is gradually shifting its heavy focus from that initial discovery step to protein target verification using multiplexed quantitative proteomic assays, capable of measuring changes in proteins and their interacting partners, isoforms, and post-translational modifications (PTMs) in response to stimuli in the context of signaling pathways and protein networks. With a critical link to genotypes (i.e., high throughput genomics and transcriptomics data), new and complementary information can be gleaned from multi-dimensional omics data to (1) assess the effect of genomic and transcriptomic aberrations on such complex molecular machinery in the context of cell signaling architectures associated with pathological diseases such as cancer (i.e., from genotype to proteotype to phenotype); and (2) target pathway- and network-driven changes and map the fluctuations of these functional units (proteins) responsible for cellular activities in response to perturbation in a spatiotemporal fashion to better understand cancer biology as a whole system.

Increasing the precision of orthology-based complex prediction through network alignment

Macromolecular assemblies play an important role in almost all cellular processes. However, despite several large-scale studies, our current knowledge about protein complexes is still quite limited, thus advocating the use of in silico predictions to gather information on complex composition in model organisms. Since protein–protein interactions present certain constraints on the functional divergence of macromolecular assemblies during evolution, it is possible to predict complexes based on orthology data. Here, we show that incorporating interaction information through network alignment significantly increases the precision of orthology-based complex prediction. Moreover, we performed a large-scale in silico screen for protein complexes in human, yeast and fly, through the alignment of hundreds of known complexes to whole organism interactomes. Systematic comparison of the resulting network alignments to all complexes currently known in those species revealed many conserved complexes, as well as several novel complex components. In addition to validating our predictions using orthogonal data, we were able to assign specific functional roles to the predicted complexes. In several cases, the incorporation of interaction data through network alignment allowed to distinguish real complex components from other orthologous proteins. Our analyses indicate that current knowledge of yeast protein complexes exceeds that in other organisms and that predicting complexes in fly based on human and yeast data is complementary rather than redundant. Lastly, assessing the conservation of protein complexes of the human pathogen Mycoplasma pneumoniae, we discovered that its complexes repertoire is different from that of eukaryotes, suggesting new points of therapeutic intervention, whereas targeting the pathogen’s Restriction enzyme complex might lead to adverse effects due to its similarity to ATP-dependent metalloproteases in the human host.

Atg6/UVRAG/Vps34-containing lipid kinase complex is required for receptor downregulation through endolysosomal degradation and epithelial polarity during Drosophila wing development

Atg6 (Beclin 1 in mammals) is a core component of the Vps34 PI3K (III) complex, which promotes multiple vesicle trafficking pathways. Atg6 and Vps34 form two distinct PI3K (III) complexes in yeast and mammalian cells, either with Atg14 or with UVRAG. The functions of these two complexes are not entirely clear, as both Atg14 and UVRAG have been suggested to regulate both endocytosis and autophagy. In this study, we performed a microscopic analysis of UVRAG, Atg14, or Atg6 loss-of-function cells in the developing Drosophila wing. Both autophagy and endocytosis are seriously impaired and defective endolysosomes accumulate upon loss of Atg6. We show that Atg6 is required for the downregulation of Notch and Wingless signaling pathways; thus it is essential for normal wing development. Moreover, the loss of Atg6 impairs cell polarity. Atg14 depletion results in autophagy defects with no effect on endocytosis or cell polarity, while the silencing of UVRAG phenocopies all but the autophagy defect of Atg6 depleted cells. Thus, our results indicate that the UVRAG-containing PI3K (III) complex is required for receptor downregulation through endolysosomal degradation and for the establishment of proper cell polarity in the developing wing, while the Atg14-containing complex is involved in autophagosome formation.

The Drosophila Kctd-family homologue Kctd12-like modulates male aggression and mating behaviour

In Drosophila, serotonin (5-HT) regulates aggression, mating behaviour and sleep/wake behaviour through different receptors. Currently, how these various receptors are themselves regulated is still not completely understood. The KCTD12-family of proteins, which have been shown to modify G-protein-coupled receptor (GPCR) signalling in mammals, are one possibility of auxiliary proteins modulating 5-HT receptor signalling. The KCTD12-family was found to be remarkably conserved and present in species from C. elegans to humans. The Drosophila KCTD12 homologue Kctd12-like (Ktl) was highly expressed in both the larval and adult CNS. By performing behavioural assays in male Drosophila, we now reveal that Ktl is required for proper male aggression and mating behaviour. Previously, it was shown that Ktl is in a complex with the Drosophila 5-HT receptor 5-HT7, and we observed that both Ktl and the 5-HT1A receptor are required in insulin-producing cells (IPCs) for proper adult male behaviour, as well as for hyperaggressive activity induced by the mammalian 5-HT1A receptor agonist 8-hydroxy-2-dipropylaminotetralin-hydrobromide. Finally, we show that Ktl expression in the IPCs is necessary to regulate locomotion and normal sleep/wake patterns in Drosophila, but not the 5-HT1A receptor. Similar to what was observed with mammalian KCTD12-family members that interact physically with a GPCR receptor to regulate desensitization, in Drosophila Ktl may function in GPCR 5-HT receptor pathways to regulate their signalling, which is required for proper adult male behaviour.

The putative HORMA domain protein Atg101 dimerizes and is required for starvation-induced and selective autophagy in Drosophila

The large-scale turnover of intracellular material including organelles is achieved by autophagy-mediated degradation in lysosomes. Initiation of autophagy is controlled by a protein kinase complex consisting of an Atg1-family kinase, Atg13, FIP200/Atg17, and the metazoan-specific subunit Atg101. Here we show that loss of Atg101 impairs both starvation-induced and basal autophagy in Drosophila. This leads to accumulation of protein aggregates containing the selective autophagy cargo ref(2)P/p62. Mapping experiments suggest that Atg101 binds to the N-terminal HORMA domain of Atg13 and may also interact with two unstructured regions of Atg1. Another HORMA domain-containing protein, Mad2, forms a conformational homodimer. We show that Drosophila Atg101 also dimerizes, and it is predicted to fold into a HORMA domain. Atg101 interacts with ref(2)P as well, similar to Atg13, Atg8a, Atg16, Atg18, Keap1, and RagC, a known regulator of Tor kinase which coordinates cell growth and autophagy. These results raise the possibility that the interactions and dimerization of the putative HORMA domain protein Atg101 play critical roles in starvation-induced autophagy and proteostasis, by promoting the formation of protein aggregate-containing autophagosomes.

The Drosophila Chmp1 protein determines wing cell fate through regulation of epidermal growth factor receptor signaling

BACKGROUND

Receptor down-regulation by the multivesicular body (MVB) pathway is critical for many cellular signaling events. MVB generation is mediated by the highly conserved ESCRT (0, I, II, and III) protein complexes. Chmp1 is an ESCRT-III component and a putative tumor suppressor in humans. However, published data on Chmp1 activity are conflicting and its role during tissue development is not well defined.

RESULTS

We investigated the function of Drosophila Chmp1 and found that it is an essential gene. In the wing, loss of Chmp1 activity causes a cell fate change from intervein to vein, and interactions between Chmp1 and Drosophila Epidermal Growth Factor Receptor (DER) regulators suggest that Chmp1 negatively regulates DER signaling. Chmp1 knockdown also decreases Blistered expression, which is repressed by DER signaling. We find that Chmp1 protein localizes to the late endosome in Drosophila embryos, which is consistent with its effects on DER signaling resulting from its function in the ESCRT-III complex.

CONCLUSIONS

Drosophila Chmp1 negatively regulates DER signaling, likely through its role in MVB formation. Loss of Chmp1 activity in the Drosophila wing induces a cell fate change from intervein to vein that should provide a useful tool for future studies of ESCRT protein activity.

Improving the Robustness of Local Network Alignment: Design and Extensive Assessment of a Markov Clustering-Based Approach

The analysis of protein behavior at the network level had been applied to elucidate the mechanisms of protein interaction that are similar in different species. Published network alignment algorithms proved to be able to recapitulate known conserved modules and protein complexes, and infer new conserved interactions confirmed by wet lab experiments. In the meantime, however, a plethora of continuously evolving protein-protein interaction (PPI) data sets have been developed, each featuring different levels of completeness and reliability. For instance, algorithms performance may vary significantly when changing the data set used in their assessment. Moreover, existing papers did not deeply investigate the robustness of alignment algorithms. For instance, some algorithms performances vary significantly when changing the data set used in their assessment. In this work, we design an extensive assessment of current algorithms discussing the robustness of the results on the basis of input networks. We also present AlignMCL, a local network alignment algorithm based on an improved model of alignment graph and Markov Clustering. AlignMCL performs better than other state-of-the-art local alignment algorithms over different updated data sets. In addition, AlignMCL features high levels of robustness, producing similar results regardless the selected data set.

Altering the sex determination pathway in Drosophila fat body modifies sex-specific stress responses

The stress response in Drosophila melanogaster reveals sex differences in behavior, similar to what has been observed in mammals. However, unlike mammals, the sex determination pathway in Drosophila is well established, making this an ideal system to identify factors involved in the modulation of sex-specific responses to stress. In this study, we show that the Drosophila fat body, which has been shown to be important for energy homeostasis and sex determination, is a dynamic tissue that is altered in response to stress in a sex and time-dependent manner. We manipulated the sex determination pathway in the fat body via targeted expression of transformer and transformer-2 and analyzed these animals for changes in their response to stress. In the majority of cases, manipulation of transformer or transformer-2 was able to change the physiological output in response to starvation and oxidative stress to that of the opposite sex. Our data also uncover the possibility of additional downstream targets for transformer and transformer-2 that are separate from the sex determination pathway and can influence behavioral and physiological responses.

Large-scale imaginal disc sorting: A protocol for "omics"-approaches

Imaginal discs, especially the wing imaginal disc, are powerful model systems to study organ development. The traditional methods to analyze wing imaginal discs depend on the laborious and time-consuming dissection of larvae. "Omics"-based approaches, such as RNA-seq, ChIP-seq, proteomics and lipidomics, offer new opportunities for the systems-level investigation of organ development. However, it is impractical to manually isolate the required starting material. This is even more problematic when experiments strive for enhanced temporal and spatial resolution. The mass isolation workflow discussed in this review, solves this problem. The semi-automated sorting of 1000 wing imaginal discs in less than 3h forms the basis of a workflow that can be connected to biochemical analyses of organ patterning and growth. In addition to the mass isolation workflow we briefly describe key "omics" technologies and their applications. The combination of mass isolation and "omics"-approaches ensures that the wing imaginal disc will continue to be a key model organ for studying developmental processes, both on the genetic, but increasingly also on the biochemical level.

Unexpected role of the steroid-deficiency protein ecdysoneless in pre-mRNA splicing

The steroid hormone ecdysone coordinates insect growth and development, directing the major postembryonic transition of forms, metamorphosis. The steroid-deficient ecdysoneless1 (ecd1) strain of Drosophila melanogaster has long served to assess the impact of ecdysone on gene regulation, morphogenesis, or reproduction. However, ecd also exerts cell-autonomous effects independently of the hormone, and mammalian Ecd homologs have been implicated in cell cycle regulation and cancer. Why the Drosophila ecd1 mutants lack ecdysone has not been resolved. Here, we show that in Drosophila cells, Ecd directly interacts with core components of the U5 snRNP spliceosomal complex, including the conserved Prp8 protein. In accord with a function in pre-mRNA splicing, Ecd and Prp8 are cell-autonomously required for survival of proliferating cells within the larval imaginal discs. In the steroidogenic prothoracic gland, loss of Ecd or Prp8 prevents splicing of a large intron from CYP307A2/spookier (spok) pre-mRNA, thus eliminating this essential ecdysone-biosynthetic enzyme and blocking the entry to metamorphosis. Human Ecd (hEcd) can substitute for its missing fly ortholog. When expressed in the Ecd-deficient prothoracic gland, hEcd re-establishes spok pre-mRNA splicing and protein expression, restoring ecdysone synthesis and normal development. Our work identifies Ecd as a novel pre-mRNA splicing factor whose function has been conserved in its human counterpart. Whether the role of mammalian Ecd in cancer involves pre-mRNA splicing remains to be discovered.

The protein-protein interaction network of eyestalk, Y-organ and hepatopancreas in Chinese mitten crab Eriocheir sinensis

Background

The protein-protein interaction network (PIN) is an effective information tool for understanding the complex biological processes inside the cell and solving many biological problems such as signaling pathway identification and prediction of protein functions. Eriocheir sinensis is a highly-commercial aquaculture species with an unclear proteome background which hinders the construction and development of PIN for E. sinensis. However, in recent years, the development of next-generation deep-sequencing techniques makes it possible to get high throughput data of E. sinensis tanscriptome and subsequently obtain a systematic overview of the protein-protein interaction system.

Results

In this work we sequenced the transcriptional RNA of eyestalk, Y-organ and hepatopancreas in E. sinensis and generated a PIN of E. sinensis which included 3,223 proteins and 35,787 interactions. Each protein-protein interaction in the network was scored according to the homology and genetic relationship. The signaling sub-network, representing the signal transduction pathways in E. sinensis, was extracted from the global network, which depicted a global view of the signaling systems in E. sinensis. Seven basic signal transduction pathways were identified in E. sinensis. By investigating the evolution paths of the seven pathways, we found that these pathways got mature in different evolutionary stages. Moreover, the functions of unclassified proteins and unigenes in the PIN of E. sinensis were predicted. Specifically, the functions of 549 unclassified proteins related to 864 unclassified unigenes were assigned, which respectively covered 76% and 73% of all the unclassified proteins and unigenes in the network.

Conclusions

The PIN generated in this work is the first large-scale PIN of aquatic crustacean, thereby providing a paradigmatic blueprint of the aquatic crustacean interactome. Signaling sub-network extracted from the global PIN depicts the interaction of different signaling proteins and the evolutionary paths of the identified signal transduction pathways. Furthermore, the function assignment of unclassified proteins based on the PIN offers a new reference in protein function exploration. More importantly, the construction of the E. sinensis PIN provides necessary experience for the exploration of PINs in other aquatic crustacean species.

A simple TALEN-based protocol for efficient genome-editing in Drosophila

Drosophila is a well-established genetic model organism: thousands of point mutations, deficiencies or transposon insertions are available from stock centres. However, to date, it is still difficult to modify a specific gene locus in a defined manner. A potential solution is the application of transcription activator-like effector nucleases (TALENs), which have been used successfully to mutate genes in various model organisms. TALENs are constructed by fusion of TALE proteins to the endonuclease FokI, resulting in artificial, sequence-specific endonucleases. They induce double strand breaks, which are either repaired by error-prone non-homologous end joining (NHEJ) or homology directed repair (HDR). We developed a simple TALEN-based protocol to mutate any gene of interest in Drosophila within approximately 2 months. We inject mRNA coding for two TALEN pairs targeting the same gene into embryos, employ T7 endonuclease I screening of pooled F1 flies to identify mutations and generate a stable mutant stock in the F3 generation. We illustrate the efficacy of our strategy by mutating CG11617, a previously uncharacterized putative transcription factor with an unknown function in Drosophila. This demonstrates that TALENs are a reliable and efficient strategy to mutate any gene of interest in Drosophila.

Resources for functional genomics studies in Drosophila melanogaster

Drosophila melanogaster has become a system of choice for functional genomic studies. Many resources, including online databases and software tools, are now available to support design or identification of relevant fly stocks and reagents or analysis and mining of existing functional genomic, transcriptomic, proteomic, etc. datasets. These include large community collections of fly stocks and plasmid clones, "meta" information sites like FlyBase and FlyMine, and an increasing number of more specialized reagents, databases, and online tools. Here, we introduce key resources useful to plan large-scale functional genomics studies in Drosophila and to analyze, integrate, and mine the results of those studies in ways that facilitate identification of highest-confidence results and generation of new hypotheses. We also discuss ways in which existing resources can be used and might be improved and suggest a few areas of future development that would further support large- and small-scale studies in Drosophila and facilitate use of Drosophila information by the research community more generally.

Drosophila mbm is a nucleolar myc and casein kinase 2 target required for ribosome biogenesis and cell growth of central brain neuroblasts

Proper cell growth is a prerequisite for maintaining repeated cell divisions. Cells need to translate information about intracellular nutrient availability and growth cues from energy-sensing organs into growth-promoting processes, such as sufficient supply with ribosomes for protein synthesis. Mutations in the mushroom body miniature (mbm) gene impair proliferation of neural progenitor cells (neuroblasts) in the central brain of Drosophila melanogaster. Yet the molecular function of Mbm has so far been unknown. Here we show that mbm does not affect the molecular machinery controlling asymmetric cell division of neuroblasts but instead decreases their cell size. Mbm is a nucleolar protein required for small ribosomal subunit biogenesis in neuroblasts. Accordingly, levels of protein synthesis are reduced in mbm neuroblasts. Mbm expression is transcriptionally regulated by Myc, which, among other functions, relays information from nutrient-dependent signaling pathways to ribosomal gene expression. At the posttranslational level, Mbm becomes phosphorylated by casein kinase 2 (CK2), which has an impact on localization of the protein. We conclude that Mbm is a new part of the Myc target network involved in ribosome biogenesis, which, together with CK2-mediated signals, enables neuroblasts to synthesize sufficient amounts of proteins required for proper cell growth.

Imaging dynamic molecular signaling by the Cdc42 GTPase within the developing CNS

Protein interactions underlie the complexity of neuronal function. Potential interactions between specific proteins in the brain are predicted from assays based on genetic interaction and/or biochemistry. Genetic interaction reveals endogenous, but not necessarily direct, interactions between the proteins. Biochemistry-based assays, on the other hand, demonstrate direct interactions between proteins, but often outside their native environment or without a subcellular context. We aimed to achieve the best of both approaches by visualizing protein interaction directly within the brain of a live animal. Here, we show a proof-of-principle experiment in which the Cdc42 GTPase associates with its alleged partner WASp within neurons during the time and space that coincide with the newly developing CNS.

Prioritizing protein complexes implicated in human diseases by network optimization

Background

The detection of associations between protein complexes and human inherited diseases is of great importance in understanding mechanisms of diseases. Dysfunctions of a protein complex are usually defined by its member disturbance and consequently result in certain diseases. Although individual disease proteins have been widely predicted, computational methods are still absent for systematically investigating disease-related protein complexes.

Results

We propose a method, MAXCOM, for the prioritization of candidate protein complexes. MAXCOM performs a maximum information flow algorithm to optimize relationships between a query disease and candidate protein complexes through a heterogeneous network that is constructed by combining protein-protein interactions and disease phenotypic similarities. Cross-validation experiments on 539 protein complexes show that MAXCOM can rank 382 (70.87%) protein complexes at the top against protein complexes constructed at random. Permutation experiments further confirm that MAXCOM is robust to the network structure and parameters involved. We further analyze protein complexes ranked among top ten for breast cancer and demonstrate that the SWI/SNF complex is potentially associated with breast cancer.

Conclusions

MAXCOM is an effective method for the discovery of disease-related protein complexes based on network optimization. The high performance and robustness of this approach can facilitate not only pathologic studies of diseases, but also the design of drugs targeting on multiple proteins.

A computation using mutually exclusive processing is sufficient to identify specific Hedgehog signaling components

A system of more than one part can be deciphered by observing differences between the parts. A simple way to do this is by recording something absolute displaying a trait in one part and not in another: in other words, mutually exclusive computation. Conditional directed expression in vivo offers processing in more than one part of the system giving increased computation power for biological systems analysis. Here, I report the consideration of these aspects in the development of an in vivo screening assay that appears sufficient to identify components specific to a system.

Genetic screens to identify new Notch pathway mutants in Drosophila

Notch signaling controls a wide range of developmental processes, including proliferation, apoptosis, and cell fate specification during both development and adult tissue homeostasis. The functional versatility of the Notch signaling pathway is tightly linked with the complexity of its regulation in different cellular contexts. To unravel the complexity of Notch signaling, it is important to identify the different components of the Notch signaling pathway. A powerful strategy to accomplish this task is based on genetic screens. Given that the developmental context of signaling is important, these screens should be customized to specific cell populations or tissues. Here, I describe how to perform F1 clonal forward genetic screens in Drosophila to identify novel components of the Notch signaling pathway. These screens combine a classical EMS (ethyl methanesulfonate) chemical mutagenesis protocol along with clonal analysis via FRT-mediated mitotic recombination. These F1 clonal screens allow rapid phenotypic screening within clones of mutant cells induced at specific developmental stages and in tissues of interest, bypassing the pleiotropic effects of isolated mutations. More importantly, since EMS mutations have been notoriously difficult to map to specific genes in the past, I briefly discuss mapping methods that allow rapid identification of the causative mutations.

Proteomic analysis of the Notch interactome

Recent large-scale studies have provided a global description of the interactome-the whole network of protein interactions in a cell or an organism-for several model organisms. Defining protein interactions on a proteome-wide scale has led to a better understanding of the cellular functions of many proteins, especially those that have not been studied by classical molecular genetic approaches. Here we describe the resources, methods, and techniques necessary for generation of such a proteome-scale interactome in a high throughput manner. These procedures will also be applicable to low or medium throughput focused studies aimed at understanding interactions between members of specific pathways such as Notch signaling.