An inhibitor of apoptosis (SfIAP) interacts with SQUAMOSA promoter-binding protein (SBP) transcription factors that exhibit pro-cell death characteristics

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.

The conservation of IAP-like proteins in fungi, and their potential role in fungal programmed cell death

Programmed cell death (PCD) is a tightly regulated process which is required for survival and proper development of all cellular life. Despite this ubiquity, the precise molecular underpinnings of PCD have been primarily characterized in animals. Attempts to expand our understanding of this process in fungi have proven difficult as core regulators of animal PCD are apparently absent in fungal genomes, with the notable exception of a class of proteins referred to as inhibitors of apoptosis proteins (IAPs). These proteins are characterized by the conservation of a distinct Baculovirus IAP Repeat (BIR) domain and animal IAPs are known to regulate a number of processes, including cellular death, development, organogenesis, immune system maturation, host-pathogen interactions and more. IAP homologs are broadly conserved throughout the fungal kingdom, but our understanding of both their mechanism and role in fungal development/virulence is still unclear. In this review, we provide a broad and comparative overview of IAP function across taxa, with a particular focus on fungal processes regulated by IAPs. Furthermore, their putative modes of action in the absence of canonical interactors will be discussed.

Salmonella enterica changes Macrosteles quadrilineatus feeding behaviors resulting in altered S. enterica distribution on leaves and increased populations

Hemipteran insects are ubiquitous inhabitants of the phyllosphere. Changes in microbial phyllosphere communities have recently been demonstrated following infestation by Macrosteles quadrilineatus (Aster Leafhopper). Although epiphytic Salmonella enterica populations naturally decline in the phyllosphere of plants, M. quadrilineatus infestation facilitated the growth of the bacterial pathogen populations. Here, we demonstrate that cellular damage by insect stylet penetration results in a localized beneficial niche on the leaf surface, leading to enhanced S. enterica populations. We measured S. enterica populations and colonization patterns on plants infested with Hemipterans with distinct feeding behaviors. M. quadrilineatus infestation resulted in higher solute leakage and significantly greater bacterial populations than plants absent of insects. Following immigration via contaminated irrigation water, the highest populations of S. enterica are naturally found on the tips of tomato leaflets. We discovered M. quadrilineatus feeding preference altered the natural distribution of S. enterica populations, and that the presence of S. enterica altered the distribution of probing attempts. These findings elucidate how cellular damage resulting from insect feeding drives changes in bacterial colonization of the phyllosphere.

Next-generation yeast-two-hybrid analysis with Y2H-SCORES identifies novel interactors of the MLA immune receptor

Protein-protein interaction networks are one of the most effective representations of cellular behavior. In order to build these models, high-throughput techniques are required. Next-generation interaction screening (NGIS) protocols that combine yeast two-hybrid (Y2H) with deep sequencing are promising approaches to generate interactome networks in any organism. However, challenges remain to mining reliable information from these screens and thus, limit its broader implementation. Here, we present a computational framework, designated Y2H-SCORES, for analyzing high-throughput Y2H screens. Y2H-SCORES considers key aspects of NGIS experimental design and important characteristics of the resulting data that distinguish it from RNA-seq expression datasets. Three quantitative ranking scores were implemented to identify interacting partners, comprising: 1) significant enrichment under selection for positive interactions, 2) degree of interaction specificity among multi-bait comparisons, and 3) selection of in-frame interactors. Using simulation and an empirical dataset, we provide a quantitative assessment to predict interacting partners under a wide range of experimental scenarios, facilitating independent confirmation by one-to-one bait-prey tests. Simulation of Y2H-NGIS enabled us to identify conditions that maximize detection of true interactors, which can be achieved with protocols such as prey library normalization, maintenance of larger culture volumes and replication of experimental treatments. Y2H-SCORES can be implemented in different yeast-based interaction screenings, with an equivalent or superior performance than existing methods. Proof-of-concept was demonstrated by discovery and validation of novel interactions between the barley nucleotide-binding leucine-rich repeat (NLR) immune receptor MLA6, and fourteen proteins, including those that function in signaling, transcriptional regulation, and intracellular trafficking.

Frankliniella occidentalis facilitate Salmonella enterica survival in the phyllosphere

The human enteric bacterial pathogen Salmonella enterica causes approximately 1.35 million cases of food borne illnesses annually in the United States. Of these salmonellosis cases, almost half are derived from the consumption of fresh, raw produce. Although epiphytic S. enterica populations naturally decline in the phyllosphere, a subset of phytophagous insects have recently been identified as biological multipliers, consequently facilitating the growth of bacterial populations. We investigated whether tomato leaves with macroscopic feeding damage, caused by infestation of adult Western flower thrips (Frankliniella occidentalis), support higher S. enterica populations. To explore this hypothesis, we assessed S. enterica populations in response to thrips feeding by varying insect density, plant age, and the gender of the insect. As a reference control, direct leaf damage analogous to thrips feeding was also evaluated using directed, hydraulic pressure. In a supplementary set series of experiments, groups of F. occidentalis infested tomato plants were later inoculated with S. enterica to determine how prior insect infestation might influence bacterial survival and persistence. Following an infestation period, leaves visibly damaged by adult F. occidentalis supported significantly higher S. enterica populations and resulted in greater amounts of electrolyte leakage (measured as electrical conductivity) than leaves lacking visible feeding damage. Plant age did not significantly influence S. enterica populations or estimates of electrolyte leakage, independent of initial infestation. Additionally, the gender of the insect did not uniquely influence S. enterica population dynamics. Finally, applications of aggressive water bombardment resulted in more electrolyte leakage than leaves damaged by F. occidentalis, yet supported comparable S. enterica populations. Together, this study indicates that F. occidentalis feeding is one of the many potential biological mechanisms creating a more habitable environment for S. enterica.

NGPINT: a next-generation protein-protein interaction software

Mapping protein-protein interactions at a proteome scale is critical to understanding how cellular signaling networks respond to stimuli. Since eukaryotic genomes encode thousands of proteins, testing their interactions one-by-one is a challenging prospect. High-throughput yeast-two hybrid (Y2H) assays that employ next-generation sequencing to interrogate complementary DNA (cDNA) libraries represent an alternative approach that optimizes scale, cost and effort. We present NGPINT, a robust and scalable software to identify all putative interactors of a protein using Y2H in batch culture. NGPINT combines diverse tools to align sequence reads to target genomes, reconstruct prey fragments and compute gene enrichment under reporter selection. Central to this pipeline is the identification of fusion reads containing sequences derived from both the Y2H expression plasmid and the cDNA of interest. To reduce false positives, these fusion reads are evaluated as to whether the cDNA fragment forms an in-frame translational fusion with the Y2H transcription factor. NGPINT successfully recognized 95% of interactions in simulated test runs. As proof of concept, NGPINT was tested using published data sets and it recognized all validated interactions. NGPINT can process interaction data from any biosystem with an available genome or transcriptome reference, thus facilitating the discovery of protein-protein interactions in model and non-model organisms.

Identification of MicroRNAs and Their Targets That Respond to Powdery Mildew Infection in Cucumber by Small RNA and Degradome Sequencing

Powdery mildew (PM) is a prevalent disease known to limit cucumber production worldwide. MicroRNAs (miRNAs) are single-stranded molecules that regulate host defense responses through posttranscriptional gene regulation. However, which specific miRNAs are involved and how they regulate cucumber PM resistance remain elusive. A PM-resistant single-segment substitution line, SSSL508-28, was developed previously using marker-assisted backcrossing of the PM-susceptible cucumber inbred D8 line. In this study, we applied small RNA and degradome sequencing to identify PM-responsive miRNAs and their target genes in the D8 and SSSL508-28 lines. The deep sequencing resulted in the identification of 156 known and 147 novel miRNAs. Among them, 32 and six differentially expressed miRNAs (DEMs) were detected in D8 and SSSL508-28, respectively. The positive correlation between DEMs measured by small RNA sequencing and stem-loop quantitative real-time reverse transcription-polymerase chain reaction confirmed the accuracy of the observed miRNA abundances. The 32 DEMs identified in the PM-susceptible D8 were all upregulated, whereas four of the six DEMs identified in the PM-resistant SSSL508-28 were downregulated. Using in silico and degradome sequencing approaches, 517 and 20 target genes were predicted for the D8 and SSSL508-28 DEMs, respectively. Comparison of the DEM expression profiles with the corresponding mRNA expression profiles obtained in a previous study with the same experimental design identified 60 and three target genes in D8 and SSSL508-28, respectively, which exhibited inverse expression patterns with their respective miRNAs. In particular, five DEMs were located in the substituted segment that contained two upregulated DEMs, Csa-miR172c-3p and Csa-miR395a-3p, in D8 and two downregulated DEMs, Csa-miR395d-3p and Csa-miR398b-3p, in SSSL508-28. One gene encoding L-aspartate oxidase, which was targeted by Csa-miR162a, was also located on the same segment and was specifically downregulated in PM-inoculated D8 leaves. Our results will facilitate the future use of miRNAs in breeding cucumber varieties with enhanced resistance to PM.