High-quality binary interactome mapping

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms

Most human transcription factor (TF) genes encode multiple protein isoforms differing in DNA-binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators," both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

The Legionella pneumophila effector PieF modulates mRNA stability through association with eukaryotic CCR4-NOT

The eukaryotic CCR4-NOT deadenylase complex is a highly conserved regulator of mRNA metabolism that influences the expression of the complete transcriptome, representing a prime target for a generalist bacterial pathogen. We show that a translocated bacterial effector protein, PieF (Lpg1972) of Legionella pneumophila, directly interacts with the CNOT7/8 nuclease module of CCR4-NOT, with a dissociation constant in the low nanomolar range. PieF is a robust in vitro inhibitor of the DEDD-type nuclease, CNOT7, acting in a stoichiometric, dose-dependent manner. Heterologous expression of PieF phenocopies knockout of the CNOT7 ortholog (POP2) in Saccharomyces cerevisiae, resulting in 6-azauracil sensitivity. In mammalian cells, expression of PieF leads to a variety of quantifiable phenotypes: PieF silences gene expression and reduces mRNA steady-state levels when artificially tethered to a reporter transcript, and its overexpression results in the nuclear exclusion of CNOT7. PieF expression also disrupts the association between CNOT6/6L EEP-type nucleases and CNOT7. Adding to the complexities of PieF activity in vivo, we identified a separate domain of PieF responsible for binding to eukaryotic kinases. Unlike what we observe for CNOT6/6L, we show that these interactions can occur concomitantly with PieF's binding to CNOT7. Collectively, this work reveals a new, highly conserved target of L. pneumophila effectors and suggests a mechanism by which the pathogen may be modulating host mRNA stability and expression during infection.

IMPORTANCE

The intracellular bacterial pathogen Legionella pneumophila targets conserved eukaryotic pathways to establish a replicative niche inside host cells. With a host range that spans billions of years of evolution (from protists to humans), the interaction between L. pneumophila and its hosts frequently involves conserved eukaryotic pathways (protein translation, ubiquitination, membrane trafficking, autophagy, and the cytoskeleton). Here, we present the identification of a new, highly conserved host target of L. pneumophila effectors: the CCR4-NOT complex. CCR4-NOT modulates mRNA stability in eukaryotes from yeast to humans, making it an attractive target for a generalist pathogen, such as L. pneumophila. We show that the uncharacterized L. pneumophila effector PieF specifically targets one component of this complex, the deadenylase subunit CNOT7/8. We show that the interaction between PieF and CNOT7 is direct, occurs with high affinity, and reshapes the catalytic activity, localization, and composition of the complex across evolutionarily diverse eukaryotic cells.

Trypanosoma cruzi eIF4E3- and eIF4E4-containing complexes bind different mRNAs and may sequester inactive mRNAs during nutritional stress

Many eIF4F and poly(A)-binding protein (PABP) paralogues are found in trypanosomes: six eIF4E, five eIF4G, one eIF4A and two PABPs. They are expressed simultaneously and assemble into different complexes, contrasting the situation in metazoans that use distinct complexes in different cell types/developmental stages. Each eIF4F complex has its own proteins, messenger RNAs (mRNAs) and, consequently, a distinct function. We set out to study the function and regulation of the two eIF4F complexes of the parasite Trypanosoma cruzi and identified the associated proteins and mRNAs of eIF4E3 and eIF4E4 in cells in exponential growth and in nutritional stress, an inducer of differentiation to an infective stage. Upon stress, eIF4G and PABP remain associated with the eIF4E, but the associations with other 43S pre-initiation factors decrease, indicating ribosome attachment is impaired. Most eIF4E3-associated mRNAs encode for proteins involved in anabolic metabolism, while eIF4E4 associate with mRNAs encoding ribosomal proteins as in Trypanosoma brucei. Interestingly, for both eIF4E3/4, more mRNAs were associated in stressed cells than in non-stressed cells, even though these have lower translational efficiencies in stress. In summary, trypanosomes have two co-existing eIF4F complexes associating to different mRNAs, but not stress/differentiation-associated mRNAs. Under stress, both complexes exit translation but remain bound to their mRNA targets.

Deciphering sperm functions using biological networks

The global human population is exponentially increasing, which requires the production of quality food through efficient reproduction as well as sustainable production of livestock. Lack of knowledge and technology for assessing semen quality and predicting bull fertility is hindering advances in animal science and food animal production and causing millions of dollars of economic losses annually. The intent of this systemic review is to summarize methods from computational biology for analysis of gene, metabolite, and protein networks to identify potential markers that can be applied to improve livestock reproduction, with a focus on bull fertility. We provide examples of available gene, metabolic, and protein networks and computational biology methods to show how the interactions between genes, proteins, and metabolites together drive the complex process of spermatogenesis and regulate fertility in animals. We demonstrate the use of the National Center for Biotechnology Information (NCBI) and Ensembl for finding gene sequences, and then use them to create and understand gene, protein and metabolite networks for sperm associated factors to elucidate global cellular processes in sperm. This study highlights the value of mapping complex biological pathways among livestock and potential for conducting studies on promoting livestock improvement for global food security.

Arabidopsis thaliana protein NSL1 interacts with Pseudomonas syringae pv. tomato DC3000 effector HopM1 in a yeast 2-hybrid assay

Arabidopsis thaliana proteins NECROTIC SPOTTED LESIONS 1 ( NSL1 ) and CONSTITUTIVE ACTIVE DEFENSE 1 ( CAD1 ) have previously been linked to immunity against phytopathogens such as Pseudomonas syringae pv. tomato ( Pst ) DC3000 (Noutoshi et al. 2006; Tsutsui et al. 2008; Asada et al. 2011; Fukunaga et al. 2017; Holmes et al. 2021). Here, we used a yeast 2-hybrid (Y2H) approach to explore their potential to interact with Pst DC3000 effectors. We found that NSL1 , but not CAD1 , interacted with the Pst DC3000 effector HopM1. Although further experiments are needed to validate this interaction, our results suggest that NSL1 may be a host target of HopM1.

Adaptive Evolution Signatures in Prochlorococcus: Open Reading Frame (ORF)eome Resources and Insights from Comparative Genomics

Prochlorococcus, a cyanobacteria genus of the smallest and most abundant oceanic phototrophs, encompasses ecotype strains adapted to high-light (HL) and low-light (LL) niches. To elucidate the adaptive evolution of this genus, we analyzed 40 Prochlorococcus marinus ORFeomes, including two cornerstone strains, MED4 and NATL1A. Employing deep learning with robust statistical methods, we detected new protein family distributions in the strains and identified key genes differentiating the HL and LL strains. The HL strains harbor genes (ABC-2 transporters) related to stress resistance, such as DNA repair and RNA processing, while the LL strains exhibit unique chlorophyll adaptations (ion transport proteins, HEAT repeats). Additionally, we report the finding of variable, depth-dependent endogenous viral elements in the 40 strains. To generate biological resources to experimentally study the HL and LL adaptations, we constructed the ORFeomes of two representative strains, MED4 and NATL1A synthetically, covering 99% of the annotated protein-coding sequences of the two species, totaling 3976 cloned, sequence-verified open reading frames (ORFs). These comparative genomic analyses, paired with MED4 and NATL1A ORFeomes, will facilitate future genotype-to-phenotype mappings and the systems biology exploration of Prochlorococcus ecology.

Powdery mildew effectors AVRA1 and BEC1016 target the ER J-domain protein HvERdj3B required for immunity in barley

The barley powdery mildew fungus, Blumeria hordei (Bh), secretes hundreds of candidate secreted effector proteins (CSEPs) to facilitate pathogen infection and colonization. One of these, CSEP0008, is directly recognized by the barley nucleotide-binding leucine-rich-repeat (NLR) receptor MLA1 and therefore is designated AVRA1. Here, we show that AVRA1 and the sequence-unrelated Bh effector BEC1016 (CSEP0491) suppress immunity in barley. We used yeast two-hybrid next-generation interaction screens (Y2H-NGIS), followed by binary Y2H and in planta protein-protein interactions studies, and identified a common barley target of AVRA1 and BEC1016, the endoplasmic reticulum (ER)-localized J-domain protein HvERdj3B. Silencing of this ER quality control (ERQC) protein increased Bh penetration. HvERdj3B is ER luminal, and we showed using split GFP that AVRA1 and BEC1016 translocate into the ER signal peptide-independently. Overexpression of the two effectors impeded trafficking of a vacuolar marker through the ER; silencing of HvERdj3B also exhibited this same cellular phenotype, coinciding with the effectors targeting this ERQC component. Together, these results suggest that the barley innate immunity, preventing Bh entry into epidermal cells, requires ERQC. Here, the J-domain protein HvERdj3B appears to be essential and can be regulated by AVRA1 and BEC1016. Plant disease resistance often occurs upon direct or indirect recognition of pathogen effectors by host NLR receptors. Previous work has shown that AVRA1 is directly recognized in the cytosol by the immune receptor MLA1. We speculate that the AVRA1 J-domain target being inside the ER, where it is inapproachable by NLRs, has forced the plant to evolve this challenging direct recognition.

Functional diversification despite structural congruence in the HipBST toxin-antitoxin system of Legionella pneumophila

IMPORTANCE

Toxin-antitoxin (TA) systems are parasitic genetic elements found in almost all bacterial genomes. They are exchanged horizontally between cells and are typically poorly conserved across closely related strains and species. Here, we report the characterization of a tripartite TA system in the bacterial pathogen Legionella pneumophila that is highly conserved across Legionella species genomes. This system (denoted HipBSTLp) is a distant homolog of the recently discovered split-HipA system in Escherichia coli (HipBSTEc). We present bioinformatic, molecular, and structural analyses of the divergence between these two systems and the functionality of this newly described TA system family. Furthermore, we provide evidence to refute previous claims that the toxin in this system (HipTLp) possesses bifunctionality as an L. pneumophila virulence protein. Overall, this work expands our understanding of the split-HipA system architecture and illustrates the potential for undiscovered biology in these abundant genetic elements.

High-Throughput Protein-Protein Interactions Screening Using Pool-Based Liquid Yeast Two-Hybrid Pipeline

Because of its adaptability to high-throughput approaches and a low operating cost, the yeast two-hybrid (Y2H) assay remains the most widely used one for high-throughput protein-protein interactions (PPI) mapping experiments. Here we provide a detailed protocol for a liquid culture-based high-throughput binary protein-protein Y2H screen pipeline of a pool of 50 proteins used as baits against a collection of ~12,000 Arabidopsis proteins encoded by sequence-verified open reading frames (ORFs).

Bioinformatic Analysis of Yeast Two-Hybrid Next-Generation Interaction Screen Data

Yeast two-hybrid next-generation interaction screening (Y2H-NGIS) uses the output of next-generation sequencing to mine for novel protein-protein interactions. Here, we outline the analytics underlying Y2H-NGIS datasets. Different systems, libraries, and experimental designs comprise Y2H-NGIS methodologies. We summarize the analysis in several layers that comprise the characterization of baits and preys, quantification, and identification of true interactions for subsequent secondary validation. We present two software designed for this purpose, NGPINT and Y2H-SCORES, which are used as front-end and back-end tools in the analysis. Y2H-SCORES software can be used and adapted to analyze different datasets not only from Y2H-NGIS but from other techniques ruled by similar biological principles.

Intersection of network medicine and machine learning towards investigating the key biomarkers and pathways underlying amyotrophic lateral sclerosis: a systematic review

BACKGROUND

Network medicine is an emerging area of research that focuses on delving into the molecular complexity of the disease, leading to the discovery of network biomarkers and therapeutic target discovery. Amyotrophic lateral sclerosis (ALS) is a complicated rare disease with unknown pathogenesis and no available treatment. In ALS, network properties appear to be potential biomarkers that can be beneficial in disease-related applications when explored independently or in tandem with machine learning (ML) techniques.

OBJECTIVE

This systematic literature review explores recent trends in network medicine and implementations of network-based ML algorithms in ALS. We aim to provide an overview of the identified primary studies and gather details on identifying the potential biomarkers and delineated pathways.

METHODS

The current study consists of searching for and investigating primary studies from PubMed and Dimensions.ai, published between 2018 and 2022 that reported network medicine perspectives and the coupling of ML techniques. Each abstract and full-text study was individually evaluated, and the relevant studies were finally included in the review for discussion once they met the inclusion and exclusion criteria.

RESULTS

We identified 109 eligible publications from primary studies representing this systematic review. The data coalesced into two themes: application of network science to identify disease modules and promising biomarkers in ALS, along with network-based ML approaches. Conclusion This systematic review gives an overview of the network medicine approaches and implementations of network-based ML algorithms in ALS to determine new disease genes, and identify critical pathways and therapeutic target discovery for personalized treatment.

Exploiting breakdown in nonhost effector-target interactions to boost host disease resistance

Plants are resistant to most microbial species due to nonhost resistance (NHR), providing broad-spectrum and durable immunity. However, the molecular components contributing to NHR are poorly characterised. We address the question of whether failure of pathogen effectors to manipulate nonhost plants plays a critical role in NHR. RxLR (Arg-any amino acid-Leu-Arg) effectors from two oomycete pathogens, Phytophthora infestans and Hyaloperonospora arabidopsidis, enhanced pathogen infection when expressed in host plants (Nicotiana benthamiana and Arabidopsis, respectively) but the same effectors performed poorly in distantly related nonhost pathosystems. Putative target proteins in the host plant potato were identified for 64 P. infestans RxLR effectors using yeast 2-hybrid (Y2H) screens. Candidate orthologues of these target proteins in the distantly related non-host plant Arabidopsis were identified and screened using matrix Y2H for interaction with RxLR effectors from both P. infestans and H. arabidopsidis. Few P. infestans effector-target protein interactions were conserved from potato to candidate Arabidopsis target orthologues (cAtOrths). However, there was an enrichment of H. arabidopsidis RxLR effectors interacting with cAtOrths. We expressed the cAtOrth AtPUB33, which unlike its potato orthologue did not interact with P. infestans effector PiSFI3, in potato and Nicotiana benthamiana. Expression of AtPUB33 significantly reduced P. infestans colonization in both host plants. Our results provide evidence that failure of pathogen effectors to interact with and/or correctly manipulate target proteins in distantly related non-host plants contributes to NHR. Moreover, exploiting this breakdown in effector-nonhost target interaction, transferring effector target orthologues from non-host to host plants is a strategy to reduce disease.

Adenylates regulate Arabidopsis plastidial thioredoxin activities through the binding of a CBS domain protein

Cystathionine-β-synthase (CBS) domains are found in proteins of all living organisms and have been proposed to play a role as energy sensors regulating protein activities through their adenosyl ligand binding capacity. In plants, members of the CBSX protein family carry a stand-alone pair of CBS domains. In Arabidopsis (Arabidopsis thaliana), CBSX1 and CBSX2 are targeted to plastids where they have been proposed to regulate thioredoxins (TRXs). TRXs are ubiquitous cysteine thiol oxido-reductases involved in the redox-based regulation of numerous enzymatic activities as well as in the regeneration of thiol-dependent peroxidases. In Arabidopsis, 10 TRX isoforms have been identified in plastids and divided into five sub-types. Here, we show that CBSX2 specifically inhibits the activities of m-type TRXs toward two chloroplast TRX-related targets. By testing activation of NADP-malate dehydrogenase and reduction of 2-Cys peroxiredoxin, we found that TRXm1/2 inhibition by CBSX2 was alleviated in the presence of AMP or ATP. We also determined, by pull-down assays, a direct interaction of CBSX2 with reduced TRXm1 and m2 that was abolished in the presence of adenosyl ligands. In addition, we report that, compared with wild-type plants, the Arabidopsis T-DNA double mutant cbsx1 cbsx2 exhibits growth and chlorophyll accumulation defects in cold conditions, suggesting a function of plastidial CBSX proteins in plant stress adaptation. Together, our results show an energy-sensing regulation of plastid TRX m activities by CBSX, possibly allowing a feedback regulation of ATP homeostasis via activation of cyclic electron flow in the chloroplast, to maintain a high energy level for optimal growth.

Metabolic evidence for distinct pyruvate pools inside plant mitochondria

The majority of the pyruvate inside plant mitochondria is either transported into the matrix from the cytosol via the mitochondria pyruvate carrier (MPC) or synthesized in the matrix by alanine aminotransferase (AlaAT) or NAD-malic enzyme (NAD-ME). Pyruvate from these origins could mix into a single pool in the matrix and contribute indistinguishably to respiration via the pyruvate dehydrogenase complex (PDC), or these molecules could maintain a degree of independence in metabolic regulation. Here we demonstrate that feeding isolated mitochondria with uniformly labelled ¹³C-pyruvate and unlabelled malate enables the assessment of pyruvate contribution from different sources to intermediate production in the tricarboxylic acid cycle. Imported pyruvate was the preferred source for citrate production even when the synthesis of NAD-ME-derived pyruvate was optimized. Genetic or pharmacological elimination of MPC activity removed this preference and allowed an equivalent amount of citrate to be generated from the pyruvate produced by NAD-ME. Increasing the mitochondrial pyruvate pool size by exogenous addition affected only metabolites from pyruvate transported by MPC, whereas depleting the pyruvate pool size by transamination to alanine affected only metabolic products derived from NAD-ME. PDC was more membrane-associated than AlaAT and NAD-ME, suggesting that the physical organization of metabolic machinery may influence metabolic rates. Together, these data reveal that the respiratory substrate supply in plants involves distinct pyruvate pools inside the matrix that can be flexibly mixed on the basis of the rate of pyruvate transport from the cytosol. These pools are independently regulated and contribute differentially to organic acid export from plant mitochondria.

SGT1-Specific Domain Mutations Impair Interactions with the Barley MLA6 Immune Receptor in Association with Loss of NLR Protein

The Mla (Mildew resistance locus a) of barley (Hordeum vulgare L.) is an effective model for cereal immunity against fungal pathogens. Like many resistance proteins, variants of the MLA coiled-coil nucleotide-binding leucine-rich repeat (CC-NLR) receptor often require the HRS complex (HSP90, RAR1, and SGT1) to function. However, functional analysis of Sgt1 has been particularly difficult, as deletions are often lethal. Recently, we identified rar3 (required for Mla6 resistance 3), an in-frame Sgt1_ΔKL308-309 mutation in the SGT1-specific domain, that alters resistance conferred by MLA but without lethality. Here, we use autoactive MLA6 and recombinant yeast-two-hybrid strains with stably integrated HvRar1 and HvHsp90 to determine that this mutation weakens but does not entirely disrupt the interaction between SGT1 and MLA. This causes a concomitant reduction in MLA6 protein accumulation below the apparent threshold required for effective resistance. The ΔKL308-309 deletion had a lesser effect on intramolecular interactions than alanine or arginine substitutions, and MLA variants that display diminished interactions with SGT1 appear to be disproportionately affected by the SGT1_ΔKL308-309 mutation. We hypothesize that those dimeric plant CC-NLRs that appear unaffected by Sgt1 silencing are those with the strongest intermolecular interactions with it. Combining our data with recent work in CC-NLRs, we propose a cyclical model of the MLA-HRS resistosome interactions.[Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 "No Rights Reserved" license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2022.

OUP accepted manuscript

Barcode fusion genetics (BFG) utilizes deep sequencing to improve the throughput of protein–protein interaction (PPI) screening in pools. BFG has been implemented in Yeast two-hybrid (Y2H) screens (BFG-Y2H). While Y2H requires test protein pairs to localize in the nucleus for reporter reconstruction, dihydrofolate reductase protein-fragment complementation assay (DHFR-PCA) allows proteins to localize in broader subcellular contexts and proves to be largely orthogonal to Y2H. Here, we implemented BFG to DHFR-PCA (BFG-PCA). This plasmid-based system can leverage ORF collections across model organisms to perform comparative analysis, unlike the original DHFR-PCA that requires yeast genomic integration. The scalability and quality of BFG-PCA were demonstrated by screening human and yeast interactions for >11 000 bait-prey pairs. BFG-PCA showed high-sensitivity and high-specificity for capturing known interactions for both species. BFG-Y2H and BFG-PCA capture distinct sets of PPIs, which can partially be explained based on the domain orientation of the reporter tags. BFG-PCA is a high-throughput protein interaction technology to interrogate binary PPIs that exploits clone collections from any species of interest, expanding the scope of PPI assays.

CRISPR/SpCas9-mediated double knockout of barley Microrchidia MORC1 and MORC6a reveals their strong involvement in plant immunity, transcriptional gene silencing and plant growth

The Microrchidia (MORC) family proteins are important nuclear regulators in both animals and plants with critical roles in epigenetic gene silencing and genome stabilization. In the crop plant barley (Hordeum vulgare), seven MORC gene family members have been described. While barley HvMORC1 has been functionally characterized, very little information is available about other HvMORC paralogs. In this study, we elucidate the role of HvMORC6a and its potential interactors in regulating plant immunity via analysis of CRISPR/SpCas9-mediated single and double knockout (dKO) mutants, hvmorc1 (previously generated and characterized by our group), hvmorc6a, and hvmorc1/6a. For generation of hvmorc1/6a, we utilized two different strategies: (i) successive Agrobacterium-mediated transformation of homozygous single mutants, hvmorc1 and hvmorc6a, with the respective second construct, and (ii) simultaneous transformation with both hvmorc1 and hvmorc6a CRISPR/SpCas9 constructs. Total mutation efficiency in transformed homozygous single mutants ranged from 80 to 90%, while upon simultaneous transformation, SpCas9-induced mutation in both HvMORC1 and HvMORC6a genes was observed in 58% of T0 plants. Subsequent infection assays showed that HvMORC6a covers a key role in resistance to biotrophic (Blumeria graminis) and necrotrophic (Fusarium graminearum) plant pathogenic fungi, where the dKO hvmorc1/6a showed the strongest resistant phenotype. Consistent with this, the dKO showed highest levels of basal PR gene expression and derepression of TEs. Finally, we demonstrate that HvMORC1 and HvMORC6a form distinct nucleocytoplasmic homo-/heteromers with other HvMORCs and interact with components of the RNA-directed DNA methylation (RdDM) pathway, further substantiating that MORC proteins are involved in the regulation of TEs in barley.

Proteome-scale mapping of binding sites in the unstructured regions of the human proteome

Specific protein-protein interactions are central to all processes that underlie cell physiology. Numerous studies have together identified hundreds of thousands of human protein-protein interactions. However, many interactions remain to be discovered, and low affinity, conditional, and cell type-specific interactions are likely to be disproportionately underrepresented. Here, we describe an optimized proteomic peptide-phage display library that tiles all disordered regions of the human proteome and allows the screening of ~ 1,000,000 overlapping peptides in a single binding assay. We define guidelines for processing, filtering, and ranking the results and provide PepTools, a toolkit to annotate the identified hits. We uncovered >2,000 interaction pairs for 35 known short linear motif (SLiM)-binding domains and confirmed the quality of the produced data by complementary biophysical or cell-based assays. Finally, we show how the amino acid resolution-binding site information can be used to pinpoint functionally important disease mutations and phosphorylation events in intrinsically disordered regions of the proteome. The optimized human disorderome library paired with PepTools represents a powerful pipeline for unbiased proteome-wide discovery of SLiM-based interactions.

The HTLV-1 viral oncoproteins Tax and HBZ reprogram the cellular mRNA splicing landscape

Viral infections are known to hijack the transcription and translation of the host cell. However, the extent to which viral proteins coordinate these perturbations remains unclear. Here we used a model system, the human T-cell leukemia virus type 1 (HTLV-1), and systematically analyzed the transcriptome and interactome of key effectors oncoviral proteins Tax and HBZ. We showed that Tax and HBZ target distinct but also common transcription factors. Unexpectedly, we also uncovered a large set of interactions with RNA-binding proteins, including the U2 auxiliary factor large subunit (U2AF2), a key cellular regulator of pre-mRNA splicing. We discovered that Tax and HBZ perturb the splicing landscape by altering cassette exons in opposing manners, with Tax inducing exon inclusion while HBZ induces exon exclusion. Among Tax- and HBZ-dependent splicing changes, we identify events that are also altered in Adult T cell leukemia/lymphoma (ATLL) samples from two independent patient cohorts, and in well-known cancer census genes. Our interactome mapping approach, applicable to other viral oncogenes, has identified spliceosome perturbation as a novel mechanism coordinated by Tax and HBZ to reprogram the transcriptome.

Tax and HBZ are two viral regulatory proteins encoded by the human T-cell leukemia virus type 1 (HTLV-1) via sense and antisense transcripts, respectively. Both proteins are known to drive oncogenic processes that culminate in a T-cell neoplasm, known as Adult T cell leukemia/lymphoma (ATLL). We measured the effects of Tax and HBZ on host gene expression pathway by analyzing the interactome with cellular transcriptional and post-transcriptional regulators, and the transcriptome and mRNA splicing of cell lines expressing either Tax or HBZ. We compared our results with data obtained from independent cohorts of Japanese and Afro-Caribbean patients, and identified common splicing changes that might represent clinically useful biomarkers for ATLL. Finally, we provide evidence that the viral protein Tax can reprogram initial steps of the T-cell transcriptome diversification by hijacking the U2AF complex, a key cellular regulator of pre-mRNA splicing.

Removing auto-activators from yeast-two-hybrid assays by conditional negative selection

Yeast-two-hybrid (Y2H) is widely used as a strategy to detect protein–protein interactions (PPIs). Recent advancements have made it possible to generate and analyse genome-wide PPI networks en masse by coupling Y2H with next-generation sequencing technology. However, one of the major challenges of yeast two-hybrid assay is the large amount of false-positive hits caused by auto-activators (AAs), which are proteins that activate the reporter genes without the presence of an interacting protein partner. Here, we have developed a negative selection to minimize these auto-activators by integrating the pGAL2-URA3 fragment into the yeast genome. Upon activation of the pGAL2 promoter by an AA, yeast cells expressing URA3 cannot grow in media supplemented with 5-Fluoroorotic acid (5-FOA). Hence, we selectively inhibit the growth of yeast cells expressing auto-activators and thus minimizing the amount of false-positive hits. Here, we have demonstrated that auto-activators can be successfully removed from a Marchantia polymorpha cDNA library using pGAL2-URA3 and 5-FOA treatment, in liquid and solid-grown cultures. Furthermore, since URA3 can also serve as a marker for uracil autotrophy, we propose that our approach is a valuable addition to any large-scale Y2H screen.

EffectorK, a comprehensive resource to mine for Ralstonia, Xanthomonas, and other published effector interactors in the Arabidopsis proteome

Pathogens deploy effector proteins that interact with host proteins to manipulate the host physiology to the pathogen's own benefit. However, effectors can also be recognized by host immune proteins, leading to the activation of defence responses. Effectors are thus essential components in determining the outcome of plant-pathogen interactions. Despite major efforts to decipher effector functions, our current knowledge on effector biology is scattered and often limited. In this study, we conducted two systematic large-scale yeast two-hybrid screenings to detect interactions between Arabidopsis thaliana proteins and effectors from two vascular bacterial pathogens: Ralstonia pseudosolanacearum and Xanthomonas campestris. We then constructed an interactomic network focused on Arabidopsis and effector proteins from a wide variety of bacterial, oomycete, fungal, and invertebrate pathogens. This network contains our experimental data and protein-protein interactions from 2,035 peer-reviewed publications (48,200 Arabidopsis-Arabidopsis and 1,300 Arabidopsis-effector protein interactions). Our results show that effectors from different species interact with both common and specific Arabidopsis interactors, suggesting dual roles as modulators of generic and adaptive host processes. Network analyses revealed that effector interactors, particularly "effector hubs" and bacterial core effector interactors, occupy important positions for network organization, as shown by their larger number of protein interactions and centrality. These interactomic data were incorporated in EffectorK, a new graph-oriented knowledge database that allows users to navigate the network, search for homology, or find possible paths between host and/or effector proteins. EffectorK is available at www.effectork.org and allows users to submit their own interactomic data.

ARMADILLO REPEAT ONLY proteins confine Rho GTPase signalling to polar growth sites

Polar growth requires the precise tuning of Rho GTPase signalling at distinct plasma membrane domains. The activity of Rho of plant (ROP) GTPases is regulated by the opposing action of guanine nucleotide-exchange factors (GEFs) and GTPase-activating proteins (GAPs). Whereas plant-specific ROPGEFs have been shown to be embedded in higher-level regulatory mechanisms involving membrane-bound receptor-like kinases, the regulation of GAPs has remained enigmatic. Here, we show that three Arabidopsis ARMADILLO REPEAT ONLY (ARO) proteins are essential for the stabilization of growth sites in root hair cells and trichomes. AROs interact with ROP1 enhancer GAPs (RENGAPs) and bind to the plasma membrane via a conserved polybasic region at the ARO amino terminus. The ectopic spreading of ROP2 in aro2/3/4 mutant root hair cells and the preferential interaction of AROs with active ROPs and anionic phospholipids suggests that AROs recruit RENGAPs into complexes with ROPs to confine ROP signalling to distinct membrane regions.

Downy Mildew effector HaRxL21 interacts with the transcriptional repressor TOPLESS to promote pathogen susceptibility

Hyaloperonospora arabidopsidis (Hpa) is an oomycete pathogen causing Arabidopsis downy mildew. Effector proteins secreted from the pathogen into the plant play key roles in promoting infection by suppressing plant immunity and manipulating the host to the pathogen's advantage. One class of oomycete effectors share a conserved 'RxLR' motif critical for their translocation into the host cell. Here we characterize the interaction between an RxLR effector, HaRxL21 (RxL21), and the Arabidopsis transcriptional co-repressor Topless (TPL). We establish that RxL21 and TPL interact via an EAR motif at the C-terminus of the effector, mimicking the host plant mechanism for recruiting TPL to sites of transcriptional repression. We show that this motif, and hence interaction with TPL, is necessary for the virulence function of the effector. Furthermore, we provide evidence that RxL21 uses the interaction with TPL, and its close relative TPL-related 1, to repress plant immunity and enhance host susceptibility to both biotrophic and necrotrophic pathogens.

Interactions between Transport Protein Particle (TRAPP) complexes and Rab GTPases in Arabidopsis

Transport Protein Particle II (TRAPPII) is essential for exocytosis, endocytosis, protein sorting and cytokinesis. In spite of a considerable understanding of its biological role, little information is known about Arabidopsis TRAPPII complex topology and molecular function. In this study, independent proteomic approaches initiated with TRAPP components or Rab-A GTPase variants converge on the TRAPPII complex. We show that the Arabidopsis genome encodes the full complement of 13 TRAPPC subunits, including four previously unidentified components. A dimerization model is proposed to account for binary interactions between TRAPPII subunits. Preferential binding to dominant negative (GDP-bound) versus wild-type or constitutively active (GTP-bound) RAB-A2a variants discriminates between TRAPPII and TRAPPIII subunits and shows that Arabidopsis complexes differ from yeast but resemble metazoan TRAPP complexes. Analyzes of Rab-A mutant variants in trappii backgrounds provide genetic evidence that TRAPPII functions upstream of RAB-A2a, allowing us to propose that TRAPPII is likely to behave as a guanine nucleotide exchange factor (GEF) for the RAB-A2a GTPase. GEFs catalyze exchange of GDP for GTP; the GTP-bound, activated, Rab then recruits a diverse local network of Rab effectors to specify membrane identity in subsequent vesicle fusion events. Understanding GEF-Rab interactions will be crucial to unravel the co-ordination of plant membrane traffic.

Network Medicine in the Age of Biomedical Big Data

Network medicine is an emerging area of research dealing with molecular and genetic interactions, network biomarkers of disease, and therapeutic target discovery. Large-scale biomedical data generation offers a unique opportunity to assess the effect and impact of cellular heterogeneity and environmental perturbations on the observed phenotype. Marrying the two, network medicine with biomedical data provides a framework to build meaningful models and extract impactful results at a network level. In this review, we survey existing network types and biomedical data sources. More importantly, we delve into ways in which the network medicine approach, aided by phenotype-specific biomedical data, can be gainfully applied. We provide three paradigms, mainly dealing with three major biological network archetypes: protein-protein interaction, expression-based, and gene regulatory networks. For each of these paradigms, we discuss a broad overview of philosophies under which various network methods work. We also provide a few examples in each paradigm as a test case of its successful application. Finally, we delineate several opportunities and challenges in the field of network medicine. We hope this review provides a lexicon for researchers from biological sciences and network theory to come on the same page to work on research areas that require interdisciplinary expertise. Taken together, the understanding gained from combining biomedical data with networks can be useful for characterizing disease etiologies and identifying therapeutic targets, which, in turn, will lead to better preventive medicine with translational impact on personalized healthcare.

Protein interactome mapping in Caenorhabditis elegans

The systematic identification of all protein-protein interactions that take place in an organism (the 'interactome') is an important goal in modern biology. The nematode Caenorhabditis elegans was one of the first multicellular models for which a proteome-wide interactome mapping project was initiated. Most Caenorhabditis elegans interactome mapping efforts have utilized the yeast two-hybrid system, yielding an extensive binary interactome, while recent developments in mass spectrometry-based approaches hold great potential for further improving our understanding of protein interactome networks in a multicellular context. For example, methods like co-fractionation, proximity labeling, and tissue-specific protein purification not only identify protein-protein interactions, but have the potential to provide crucial insight into when and where interactions take place. Here we review current standards and recent improvements in protein interaction mapping in C. elegans.

High-Quality Yeast-2-Hybrid Interaction Network Mapping

In this article, we describe a Y2H interaction mapping protocol for systematically screening medium-to-large collections of open reading frames (ORFs) against each other. The protocol is well suited for analysis of focused networks, for modules of interest, assembling genome-scale interactome maps, and investigating host-microbe interactions. The four-step high-throughput protocol has a demonstrated low false-discovery rate that is essential for producing meaningful network maps. Following the assembly of yeast expression clones from an existing ORFeome collection, we describe in detail the four-step procedure that begins with the primary screen using minipools, followed by secondary verification of primary positives, identification of candidate interaction pairs by sequencing, and a final verification step using fresh inoculants. In addition to this core protocol, aspects of network mapping and quality control will be discussed briefly. © 2018 by John Wiley & Sons, Inc.

Network Analysis of UBE3A/E6AP-Associated Proteins Provides Connections to Several Distinct Cellular Processes

Perturbations in activity and dosage of the UBE3A ubiquitin-ligase have been linked to Angelman syndrome and autism spectrum disorders. UBE3A was initially identified as the cellular protein hijacked by the human papillomavirus E6 protein to mediate the ubiquitylation of p53, a function critical to the oncogenic potential of these viruses. Although a number of substrates have been identified, the normal cellular functions and pathways affected by UBE3A are largely unknown. Previously, we showed that UBE3A associates with HERC2, NEURL4, and MAPK6/ERK3 in a high-molecular-weight complex of unknown function that we refer to as the HUN complex (HERC2, UBE3A, and NEURL4). In this study, the combination of two complementary proteomic approaches with a rigorous network analysis revealed cellular functions and pathways in which UBE3A and the HUN complex are involved. In addition to finding new UBE3A-associated proteins, such as MCM6, SUGT1, EIF3C, and ASPP2, network analysis revealed that UBE3A-associated proteins are connected to several fundamental cellular processes including translation, DNA replication, intracellular trafficking, and centrosome regulation. Our analysis suggests that UBE3A could be involved in the control and/or integration of these cellular processes, in some cases as a component of the HUN complex, and also provides evidence for crosstalk between the HUN complex and CAMKII interaction networks. This study contributes to a deeper understanding of the cellular functions of UBE3A and its potential role in pathways that may be affected in Angelman syndrome, UBE3A-associated autism spectrum disorders, and human papillomavirus-associated cancers.

Legionella effector AnkX interacts with host nuclear protein PLEKHN1

Background

The intracellular bacterial pathogen Legionella pneumophila proliferates in human alveolar macrophages, resulting in a severe pneumonia termed Legionnaires’ disease. Throughout the course of infection, L. pneumophila remains enclosed in a specialized membrane compartment that evades fusion with lysosomes. The pathogen delivers over 300 effector proteins into the host cell, altering host pathways in a manner that sets the stage for efficient pathogen replication. The L. pneumophila effector protein AnkX targets host Rab GTPases and functions in preventing fusion of the Legionella-containing vacuole with lysosomes. However, the current understanding of AnkX’s interaction with host proteins and the means through which it exerts its cellular function is limited.

Results

Here, we investigated the protein interaction network of AnkX by using the nucleic acid programmable protein array (NAPPA), a high-density platform comprising 10,000 unique human ORFs. This approach facilitated the discovery of PLEKHN1 as a novel interaction partner of AnkX. We confirmed this interaction through multiple independent in vitro pull-down, co-immunoprecipitation, and cell-based assays. Structured illumination microscopy revealed that endogenous PLEKHN1 is found in the nucleus and on vesicular compartments, whereas ectopically produced AnkX co-localized with lipid rafts at the plasma membrane. In mammalian cells, HaloTag-AnkX co-localized with endogenous PLEKHN1 on vesicular compartments. A central fragment of AnkX (amino acids 491–809), containing eight ankyrin repeats, extensively co-localized with endogenous PLEKHN1, indicating that this region may harbor a new function. Further, we found that PLEKHN1 associated with multiple proteins involved in the inflammatory response.

Conclusions

Altogether, our study provides evidence that in addition to Rab GTPases, the L. pneumophila effector AnkX targets nuclear host proteins and suggests that AnkX may have novel functions related to manipulating the inflammatory response.

Electronic supplementary material

The online version of this article (10.1186/s12866-017-1147-7) contains supplementary material, which is available to authorized users.

RBPJ/CBF1 interacts with L3MBTL3/MBT1 to promote repression of Notch signaling via histone demethylase KDM1A/LSD1

Notch signaling is an evolutionarily conserved signal transduction pathway that is essential for metazoan development. Upon ligand binding, the Notch intracellular domain (NOTCH ICD) translocates into the nucleus and forms a complex with the transcription factor RBPJ (also known as CBF1 or CSL) to activate expression of Notch target genes. In the absence of a Notch signal, RBPJ acts as a transcriptional repressor. Using a proteomic approach, we identified L3MBTL3 (also known as MBT1) as a novel RBPJ interactor. L3MBTL3 competes with NOTCH ICD for binding to RBPJ. In the absence of NOTCH ICD, RBPJ recruits L3MBTL3 and the histone demethylase KDM1A (also known as LSD1) to the enhancers of Notch target genes, leading to H3K4me2 demethylation and to transcriptional repression. Importantly, in vivo analyses of the homologs of RBPJ and L3MBTL3 in Drosophila melanogaster and Caenorhabditis elegans demonstrate that the functional link between RBPJ and L3MBTL3 is evolutionarily conserved, thus identifying L3MBTL3 as a universal modulator of Notch signaling in metazoans.

Base-resolution stratification of cancer mutations using functional variomics

A complete understanding of human cancer variants requires new methods to systematically and efficiently assess the functional effects of genomic mutations at a large scale. Here, we describe a set of tools to rapidly clone and stratify thousands of cancer mutations at base resolution. This protocol provides a massively parallel pipeline to achieve high stringency and throughput. The approach includes high-throughput generation of mutant clones by Gateway, confirmation of variant identity by barcoding and next-generation sequencing, and stratification of cancer variants by multiplexed interaction profiling. Compared with alternative site-directed mutagenesis methods, our protocol requires less sequencing effort and enables robust statistical calling of allele-specific effects. To ensure the precision of variant interaction profiling, we further describe two complementary methods-a high-throughput enhanced yeast two-hybrid (HT-eY2H) assay and a mammalian-cell-based Gaussia princeps luciferase protein-fragment complementation assay (GPCA). These independent assays with standard controls validate mutational interaction profiles with high quality. This protocol provides experimentally derived guidelines for classifying candidate cancer alleles emerging from whole-genome or whole-exome sequencing projects as 'drivers' or 'passengers'. For ∼100 genomic mutations, the protocol-including target primer design, variant library construction, and sequence verification-can be completed within as little as 2-3 weeks, and cancer variant stratification can be completed within 2 weeks.

CrY2H-seq: a massively multiplexed assay for deep-coverage interactome mapping

Broad-scale protein-protein interaction mapping is a major challenge given the cost, time, and sensitivity constraints of existing technologies. Here, we present a massively multiplexed yeast two-hybrid method, CrY2H-seq, which uses a Cre recombinase interaction reporter to intracellularly fuse the coding sequences of two interacting proteins and next-generation DNA sequencing to identify these interactions en masse. We applied CrY2H-seq to investigate sparsely annotated Arabidopsis thaliana transcription factors interactions. By performing ten independent screens testing a total of 36 million binary interaction combinations, and uncovering a network of 8,577 interactions among 1,453 transcription factors, we demonstrate CrY2H-seq's improved screening capacity, efficiency, and sensitivity over those of existing technologies. The deep-coverage network resource we call AtTFIN-1 recapitulates one-third of previously reported interactions derived from diverse methods, expands the number of known plant transcription factor interactions by three-fold, and reveals previously unknown family-specific interaction module associations with plant reproductive development, root architecture, and circadian coordination.

Two interacting PPR proteins are major Arabidopsis editing factors in plastid and mitochondria

RNA editing is converting hundreds of cytosines into uridines during organelle gene expression of land plants. The pentatricopeptide repeat (PPR) proteins are at the core of this posttranscriptional RNA modification. Even if a PPR protein defines the editing site, a DYW domain of the same or another PPR protein is believed to catalyze the deamination. To give insight into the organelle RNA editosome, we performed tandem affinity purification of the plastidial CHLOROPLAST BIOGENESIS 19 (CLB19) PPR editing factor. Two PPR proteins, dually targeted to mitochondria and chloroplasts, were identified as potential partners of CLB19. These two proteins, a P-type PPR and a member of a small PPR-DYW subfamily, were shown to interact in yeast. Insertional mutations resulted in embryo lethality that could be rescued by embryo-specific complementation. A transcriptome analysis of these complemented plants showed major editing defects in both organelles with a very high PPR type specificity, indicating that the two proteins are core members of E+-type PPR editosomes.

An inference method from multi-layered structure of biomedical data

Background

Biological system is a multi-layered structure of omics with genome, epigenome, transcriptome, metabolome, proteome, etc., and can be further stretched to clinical/medical layers such as diseasome, drugs, and symptoms. One advantage of omics is that we can figure out an unknown component or its trait by inferring from known omics components. The component can be inferred by the ones in the same level of omics or the ones in different levels.

Methods

To implement the inference process, an algorithm that can be applied to the multi-layered complex system is required. In this study, we develop a semi-supervised learning algorithm that can be applied to the multi-layered complex system. In order to verify the validity of the inference, it was applied to the prediction problem of disease co-occurrence with a two-layered network composed of symptom-layer and disease-layer.

Results

The symptom-disease layered network obtained a fairly high value of AUC, 0.74, which is regarded as noticeable improvement when comparing 0.59 AUC of single-layered disease network. If further stretched to whole layered structure of omics, the proposed method is expected to produce more promising results.

Conclusion

This research has novelty in that it is a new integrative algorithm that incorporates the vertical structure of omics data, on contrary to other existing methods that integrate the data in parallel fashion. The results can provide enhanced guideline for disease co-occurrence prediction, thereby serve as a valuable tool for inference process of multi-layered biological system.

Proteome-Scale Human Interactomics

Cellular functions are mediated by complex interactome networks of physical, biochemical, and functional interactions between DNA sequences, RNA molecules, proteins, lipids, and small metabolites. A thorough understanding of cellular organization requires accurate and relatively complete models of interactome networks at proteome scale. The recent publication of four human protein-protein interaction (PPI) maps represents a technological breakthrough and an unprecedented resource for the scientific community, heralding a new era of proteome-scale human interactomics. Our knowledge gained from these and complementary studies provides fresh insights into the opportunities and challenges when analyzing systematically generated interactome data, defines a clear roadmap towards the generation of a first reference interactome, and reveals new perspectives on the organization of cellular life.

Loss of Pin1 Suppresses Hedgehog-Driven Medulloblastoma Tumorigenesis

Medulloblastoma is the most common malignant brain tumor in children. Therapeutic approaches to medulloblastoma (combination of surgery, radiotherapy, and chemotherapy) have led to significant improvements, but these are achieved at a high cost to quality of life. Alternative therapeutic approaches are needed. Genetic mutations leading to the activation of the Hedgehog pathway drive tumorigenesis in ~30% of medulloblastoma. In a yeast two-hybrid proteomic screen, we discovered a novel interaction between GLI1, a key transcription factor for the mediation of Hedgehog signals, and PIN1, a peptidylprolyl cis/trans isomerase that regulates the postphosphorylation fate of its targets. The GLI1/PIN1 interaction was validated by reciprocal pulldowns using epitope-tagged proteins in HEK293T cells as well as by co-immunoprecipiations of the endogenous proteins in a medulloblastoma cell line. Our results support a molecular model in which PIN1 promotes GLI1 protein abundance, thus contributing to the positive regulation of Hedgehog signals. Most importantly, in vivo functional analyses of Pin1 in the GFAP-tTA;TRE-SmoA1 mouse model of Hedgehog-driven medulloblastoma demonstrate that the loss of Pin1 impairs tumor development and dramatically increases survival. In summary, the discovery of the GLI1/PIN1 interaction uncovers PIN1 as a novel therapeutic target in Hedgehog-driven medulloblastoma tumorigenesis.

LSU network hubs integrate abiotic and biotic stress responses via interaction with the superoxide dismutase FSD2

In natural environments, plants often experience different stresses simultaneously, and adverse abiotic conditions can weaken the plant immune system. Interactome mapping revealed that the LOW SULPHUR UPREGULATED (LSU) proteins are hubs in an Arabidopsis protein interaction network that are targeted by virulence effectors from evolutionarily diverse pathogens. Here we show that LSU proteins are up-regulated in several abiotic and biotic stress conditions, such as nutrient depletion or salt stress, by both transcriptional and post-translational mechanisms. Interference with LSU expression prevents chloroplastic reactive oxygen species (ROS) production and proper stomatal closure during sulphur stress. We demonstrate that LSU1 interacts with the chloroplastic superoxide dismutase FSD2 and stimulates its enzymatic activity in vivo and in vitro. Pseudomonas syringae virulence effectors interfere with this interaction and preclude re-localization of LSU1 to chloroplasts. We demonstrate that reduced LSU levels cause a moderately enhanced disease susceptibility in plants exposed to abiotic stresses such as nutrient deficiency, high salinity, or heavy metal toxicity, whereas LSU1 overexpression confers significant disease resistance in several of these conditions. Our data suggest that the network hub LSU1 plays an important role in co-ordinating plant immune responses across a spectrum of abiotic stress conditions.

Mapping Protein-Protein Interaction Using High-Throughput Yeast 2-Hybrid

A tremendous asset to the analysis of protein-protein interactions is the yeast-2-hybrid (Y2H) method. The Y2H assay is a heterologous system that is expanding network biology knowledge via in vivo investigations of binary protein-protein interactions. Traditionally, the Y2H protocol entails the mating or co-transformation of yeast in solid agar media followed by visual analysis for diploid selection. Having played a key role in identifying protein-protein interactions for nearly three decades in a wide range of biological systems, the Y2H system assays the interaction between two proteins of interest which results in a reconstituted and/or activation of transcription factor allowing a reporter gene to be transcribed. Overall, the Y2H method takes advantage of two factors: (1) the auxotrophic yeast requires expression of the reporter gene to grow in media purposefully designed to lack one or more essential amino acids, and (2) the DNA-binding (DB) domain of transcription factor GAL4 is unable to initiate transcription unless it is physically associated with an activating domain (AD), which, together, DBs and ADs are fused to proteins of interest that must interact with each other to reconstitute the transcription factor and activate the reporter gene. The applications of Y2H are broad, entailing fields such as drug discovery, clinical trials for human disease including cancer and neurodegenerative disease, and extend even into synthetic biology applications and cellular engineering. This chapter begins with an introduction to the fundamental mechanics of Y2H utilizing a genetically engineered strain of yeast and proceeds with an in-depth look at the different types of Y2H and turn our focus particularly to the GAL4-based Y2H system to map protein-protein interactions. We will then provide a step-by-step protocol for the Y2H experimentation preceded by a materials listing while simultaneously including key notes throughout the entire experimental process of biological-mechanistic and historical understandings of the steps.

Diverse mechanisms of metaeffector activity in an intracellular bacterial pathogen, Legionella pneumophila

Pathogens deliver complex arsenals of translocated effector proteins to host cells during infection, but the extent to which these proteins are regulated once inside the eukaryotic cell remains poorly defined. Among all bacterial pathogens, Legionella pneumophila maintains the largest known set of translocated substrates, delivering over 300 proteins to the host cell via its Type IVB, Icm/Dot translocation system. Backed by a few notable examples of effector–effector regulation in L. pneumophila, we sought to define the extent of this phenomenon through a systematic analysis of effector–effector functional interaction. We used Saccharomyces cerevisiae, an established proxy for the eukaryotic host, to query > 108,000 pairwise genetic interactions between two compatible expression libraries of ~330 L. pneumophila‐translocated substrates. While capturing all known examples of effector–effector suppression, we identify fourteen novel translocated substrates that suppress the activity of other bacterial effectors and one pair with synergistic activities. In at least nine instances, this regulation is direct—a hallmark of an emerging class of proteins called metaeffectors, or “effectors of effectors”. Through detailed structural and functional analysis, we show that metaeffector activity derives from a diverse range of mechanisms, shapes evolution, and can be used to reveal important aspects of each cognate effector's function. Metaeffectors, along with other, indirect, forms of effector–effector modulation, may be a common feature of many intracellular pathogens—with unrealized potential to inform our understanding of how pathogens regulate their interactions with the host cell.

Challenges in Targeting a Basic Helix-Loop-Helix Transcription Factor with Hydrocarbon-Stapled Peptides

Basic helix-loop-helix (bHLH) transcription factors play critical roles in organism development and disease by regulating cell proliferation and differentiation. Transcriptional activity, whether by bHLH homo- or heterodimerization, is dependent on protein-protein and protein-DNA interactions mediated by α-helices. Thus, α-helical decoys have been proposed as potential targeted therapies for pathologic bHLH transcription. Here, we developed a library of stabilized α-helices of OLIG2 (SAH-OLIG2) to test the capacity of hydrocarbon-stapled peptides to disrupt OLIG2 homodimerization, which drives the development and chemoresistance of glioblastoma multiforme, one of the deadliest forms of human brain cancer. Although stapling successfully reinforced the α-helical structure of bHLH constructs of varying length, sequence-specific dissociation of OLIG2 dimers from DNA was not achieved. Re-evaluation of the binding determinants for OLIG2 self-association and stability revealed an unanticipated role of the C-terminal domain. These data highlight potential pitfalls in peptide-based targeting of bHLH transcription factors given the liabilities of their positively charged amino acid sequences and multifactorial binding determinants.

Mapping transcription factor interactome networks using HaloTag protein arrays

Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein-protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor-protein interactions and led to the development of a proteome-wide plant hormone TF interactome network.

The transcription factor ERG recruits CCR4-NOT to control mRNA decay and mitotic progression

Control of mRNA levels, a fundamental aspect in the regulation of gene expression, is achieved through a balance between mRNA synthesis and decay. E26-related gene (Erg) proteins are canonical transcription factors whose previously described functions are confined to the control of mRNA synthesis. Here, we report that ERG also regulates gene expression by affecting mRNA stability and identify the molecular mechanisms underlying this function in human cells. ERG is recruited to mRNAs via interaction with the RNA-binding protein RBPMS, and it promotes mRNA decay by binding CNOT2, a component of the CCR4-NOT deadenylation complex. Transcriptome-wide mRNA stability analysis revealed that ERG controls the degradation of a subset of mRNAs highly connected to Aurora signaling, whose decay during S phase is necessary for mitotic progression. Our data indicate that control of gene expression by mammalian transcription factors may follow a more complex scheme than previously anticipated, integrating mRNA synthesis and degradation.

The stripe rust fungal effector PEC6 suppresses pattern-triggered immunity in a host species-independent manner and interacts with adenosine kinases

We identified a wheat stripe rust (Puccinia striiformis) effector candidate (PEC6) with pattern-triggered immunity (PTI) suppression function and its corresponding host target. PEC6 compromised PTI host species-independently. In Nicotiana benthamiana, it hampers reactive oxygen species (ROS) accumulation and callose deposition induced by Pseudomonas fluorescens. In Arabidopsis, plants expressing PEC6 were more susceptible to Pseudomonas syringae pv. tomato (Pto) DC3000 ΔAvrPto/ΔAvrPtoB. In wheat, PEC6-suppression of P. fluorescens-elicited PTI was revealed by the fact that it allowed activation of effector-triggered immunity by Pto DC3000. Knocking down of PEC6 expression by virus-mediated host-induced gene silencing decreased the number of rust pustules, uncovering PEC6 as an important pathogenicity factor. PEC6, overexpressed in plant cells without its signal peptide, was localized to the nucleus and cytoplasm. A yeast two-hybrid assay showed that PEC6 interacts with both wheat and Arabidopsis adenosine kinases (ADKs). Knocking down wheat ADK expression by virus-induced gene silencing reduced leaf growth and enhanced the number of rust pustules, indicating that ADK is important in plant development and defence. ADK plays essential roles in regulating metabolism, cytokinin interconversion and methyl transfer reactions, and our data propose a model where PEC6 may affect one of these processes by targeting ADK to favour fungal growth.

Pooled-matrix protein interaction screens using Barcode Fusion Genetics

High‐throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome‐scale interaction mapping. Here, we report Barcode Fusion Genetics‐Yeast Two‐Hybrid (BFG‐Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG‐Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein‐pair barcodes that can be quantified via next‐generation sequencing. We applied BFG‐Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG‐Y2H increases the efficiency of protein matrix screening, with quality that is on par with state‐of‐the‐art Y2H methods.

An inter-species protein-protein interaction network across vast evolutionary distance

In cellular systems, biophysical interactions between macromolecules underlie a complex web of functional interactions. How biophysical and functional networks are coordinated, whether all biophysical interactions correspond to functional interactions, and how such biophysical-versus-functional network coordination is shaped by evolutionary forces are all largely unanswered questions. Here, we investigate these questions using an "inter-interactome" approach. We systematically probed the yeast and human proteomes for interactions between proteins from these two species and functionally characterized the resulting inter-interactome network. After a billion years of evolutionary divergence, the yeast and human proteomes are still capable of forming a biophysical network with properties that resemble those of intra-species networks. Although substantially reduced relative to intra-species networks, the levels of functional overlap in the yeast-human inter-interactome network uncover significant remnants of co-functionality widely preserved in the two proteomes beyond human-yeast homologs. Our data support evolutionary selection against biophysical interactions between proteins with little or no co-functionality. Such non-functional interactions, however, represent a reservoir from which nascent functional interactions may arise.

Toward precision medicine of breast cancer

In this review, we report on breast cancer's molecular features and on how high throughput technologies are helping in understanding the dynamics of tumorigenesis and cancer progression with the aim of developing precision medicine methods. We first address the current state of the art in breast cancer therapies and challenges in order to progress towards its cure. Then, we show how the interaction of high-throughput technologies with in silico modeling has led to set up useful inferences for promising strategies of target-specific therapies with low secondary effect incidence for patients. Finally, we discuss the challenge of pharmacogenetics in the clinical practice of cancer therapy. All these issues are explored within the context of precision medicine.

Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing

While alternative splicing is known to diversify the functional characteristics of some genes, the extent to which protein isoforms globally contribute to functional complexity on a proteomic scale remains unknown. To address this systematically, we cloned full-length open reading frames of alternatively spliced transcripts for a large number of human genes and used protein-protein interaction profiling to functionally compare hundreds of protein isoform pairs. The majority of isoform pairs share less than 50% of their interactions. In the global context of interactome network maps, alternative isoforms tend to behave like distinct proteins rather than minor variants of each other. Interaction partners specific to alternative isoforms tend to be expressed in a highly tissue-specific manner and belong to distinct functional modules. Our strategy, applicable to other functional characteristics, reveals a widespread expansion of protein interaction capabilities through alternative splicing and suggests that many alternative "isoforms" are functionally divergent (i.e., "functional alloforms").