Protein Regulatory Networks Research Articles

A Model for Manganese interaction with Deinococcus radiodurans proteome network involved in ROS response and defense

A complex network of regulatory proteins takes part in the mechanism underlying the radioresistance of Deinoccocus radiodurans bacterium (DR). The interaction of Mn(II) ions with DR-proteins and peptides seems to be responsible for proteins protection from oxidative damage induced by Reactive Oxygen Species during irradiation.In the present work we describe a combined approach of bioinformatic strategies based on structural data and annotation to predict the Mn(II)-binding proteins encoded by the genome of DR and, in parallel, the same predictions for other bacteria were performed; the comparison revealed that, in most of the cases, the content of Mn(II)-binding proteins is significantly higher in radioresistant than in radiosensitive bacteria. Moreover, we report the in silico protein–protein interaction network of the putative Mn(II)-proteins, remodeled in order to enhance the knowledge about the impact of Mn-binding proteins in DR ability to protect also DNA from various damaging agents such as ionizing radiation, UV radiation and oxidative stress.

Differential roles of ERRFI1 in EGFR and AKT pathway regulation affect cancer proliferation

AKT signaling is modulated by a complex network of regulatory proteins and is commonly deregulated in cancer. Here, we present a dual mechanism of AKT regulation by the ERBB receptor feedback inhibitor 1 (ERRFI1). We show that in cells expressing high levels of EGFR, ERRF1 inhibits growth and enhances responses to chemotherapy. This is mediated in part through the negative regulation of AKT signaling by direct ERRFI1‐dependent inhibition of EGFR. In cells expressing low levels of EGFR, ERRFI1 positively modulates AKT signaling by interfering with the interaction of the inactivating phosphatase PHLPP with AKT, thereby promoting cell growth and chemotherapy desensitization. These observations broaden our understanding of chemotherapy response and have important implications for the selection of targeted therapies in a cell context‐dependent manner. EGFR inhibition can only sensitize EGFR‐high cells for chemotherapy, while AKT inhibition increases chemosensitivity in EGFR‐low cells. By understanding these mechanisms, we can take advantage of the cellular context to individualize antineoplastic therapy. Finally, our data also suggest targeting of EFFRI1 in EGFR‐low cancer as a promising therapeutic approach.

Quantitative proteomic analysis of deciduous molars during cap to bell transition in miniature pig

Taking advantage of genetic manipulation tools and accessibility, almost all molecular knowledge on vertebrate tooth development was obtained from rodent models that only have one dentition in their entire lives. Whether the tooth development in other vertebrates such as swine or human follows the same rules remains elusive. Rodent dentitions differ considerably from human dentitions, therefore limiting the application of knowledge from rodent tooth to human tooth. Signal-mediated communication between cells and complex gene and protein regulatory networks are key components of tooth development. By combining isobaric tandem mass tag (TMT) labeling with liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) technology, we constructed the proteomic profile of deciduous molars at embryonic days 40 and 50 in miniature pig (Sus scrofa). During the ten days of prenatal development of the miniature pig, the morphology of the lower deciduous molar moves from the early cap to the bell stage. Thus, we identified proteins that are associated with these developing stages and identified differentially regulated proteins (DRPs) that are potential or novel drivers of tooth morphogenesis. Three candidate proteins were validated via qRT-PCR, western blotting analysis, and the location of those proteins in tooth germ were observed by immunohistochemical staining. Multiple signaling pathways and protein interaction network revealed potential mechanisms of early tooth programming in a large mammal. Bioinformatic analysis also showed that cross interaction of Wnt and Sonic hedgehog pathways may play a key role in deciduous development during cap to bell transition in miniature pig. SignificanceWe performed the most comprehensive study of the whole tooth germ proteome in mammals to date. The high-throughput proteomic analysis identifies differentially regulated proteins and pathways that will help elucidate the mechanisms of tooth development.

Determination of The Properties of Rat Brain Thermostable Protein Complex which Inhibit Cell Proliferation.

Objective Cell proliferation is known to be controlled by many networks of regulatory proteins. These multiple and complicated mechanisms of control are still being investigated. The aim of the present study is to determine the different properties of adult rat brain thermostable protein complex (TPC) which affect cell proliferation. Materials and Methods This experimental study used brain, kidney and liver tissue from adult (150-170 g) and adolescent (7, 10, 21, 28 days) white rats, adult pigeons and mice. Brain TPC was isolated by alcohol extraction, and primary antibodies Ki67 and GAD65/67 were used for immunohistochemistry, evaluation of transcriptional activity of the tissues and determination of the mitotic index. Results The results show that brain TPC from rats reversibly decreases cell proliferation by inhibiting transcription. The evidence suggests that TPC is not species-specific, but expresses tissue specificity with regards to terminally differentiated cells. Rat brain TPC inhibits mitotic activity of the progenitor cells in the dentate gyrus of adolescent rats, and corresponding with this decrease in the mitotic index the number of Ki67 positive cells increases. Simultaneously, the number of GAD65/67-positive cells in the hippocampus decreases by approximately threefold. ConclusionThese results indicate that rat brain TPC causes the reversible suppression of cell proliferation through the inhibition of transcription. Inhibitory effects of rat brain TPC leads to an increase the number of cells in the cell cycle, in tissues of adolescent rats.

Evolution of new regulatory functions on biophysically realistic fitness landscapes

Gene expression is controlled by networks of regulatory proteins that interact specifically with external signals and DNA regulatory sequences. These interactions force the network components to co-evolve so as to continually maintain function. Yet, existing models of evolution mostly focus on isolated genetic elements. In contrast, we study the essential process by which regulatory networks grow: the duplication and subsequent specialization of network components. We synthesize a biophysical model of molecular interactions with the evolutionary framework to find the conditions and pathways by which new regulatory functions emerge. We show that specialization of new network components is usually slow, but can be drastically accelerated in the presence of regulatory crosstalk and mutations that promote promiscuous interactions between network components.

Image-based spatiotemporal causality inference for protein signaling networks.

MotivationEfforts to model how signaling and regulatory networks work in cells have largely either not considered spatial organization or have used compartmental models with minimal spatial resolution. Fluorescence microscopy provides the ability to monitor the spatiotemporal distribution of many molecules during signaling events, but as of yet no methods have been described for large scale image analysis to learn a complex protein regulatory network. Here we present and evaluate methods for identifying how changes in concentration in one cell region influence concentration of other proteins in other regions.ResultsUsing 3D confocal microscope movies of GFP-tagged T cells undergoing costimulation, we learned models containing putative causal relationships among 12 proteins involved in T cell signaling. The models included both relationships consistent with current knowledge and novel predictions deserving further exploration. Further, when these models were applied to the initial frames of movies of T cells that had been only partially stimulated, they predicted the localization of proteins at later times with statistically significant accuracy. The methods, consisting of spatiotemporal alignment, automated region identification, and causal inference, are anticipated to be applicable to a number of biological systems.Availability and implementationThe source code and data are available as a Reproducible Research Archive at http://murphylab.cbd.cmu.edu/software/2017_TcellCausalModels/

Reduction of multiscale stochastic biochemical reaction networks using exact moment derivation.

Biochemical reaction networks (BRNs) in a cell frequently consist of reactions with disparate timescales. The stochastic simulations of such multiscale BRNs are prohibitively slow due to high computational cost for the simulations of fast reactions. One way to resolve this problem uses the fact that fast species regulated by fast reactions quickly equilibrate to their stationary distribution while slow species are unlikely to be changed. Thus, on a slow timescale, fast species can be replaced by their quasi-steady state (QSS): their stationary conditional expectation values for given slow species. As the QSS are determined solely by the state of slow species, such replacement leads to a reduced model, where fast species are eliminated. However, it is challenging to derive the QSS in the presence of nonlinear reactions. While various approximation schemes for the QSS have been developed, they often lead to considerable errors. Here, we propose two classes of multiscale BRNs which can be reduced by deriving an exact QSS rather than approximations. Specifically, if fast species constitute either a feedforward network or a complex balanced network, the reduced model based on the exact QSS can be derived. Such BRNs are frequently observed in a cell as the feedforward network is one of fundamental motifs of gene or protein regulatory networks. Furthermore, complex balanced networks also include various types of fast reversible bindings such as bindings between transcriptional factors and gene regulatory sites. The reduced models based on exact QSS, which can be calculated by the computational packages provided in this work, accurately approximate the slow scale dynamics of the original full model with much lower computational cost.

Axons get ahead: Insights into axon guidance and congenital cranial dysinnervation disorders.

Cranial nerves innervate head muscles in a well-characterized and highly conserved pattern. Identification of genes responsible for human congenital disorders of these nerves, combined with the analysis of their role in axonal development in animal models, has advanced understanding of how neuromuscular connectivity is established. Here, we focus on the ocular motor system, as an instructive example of the success of this approach in unravelling the aetiology of human strabismus. The discovery that ocular motility disorders can arise from mutations in transcription factors, including HoxA1, HoxB1, MafB, Phox2A, and Sall4, has revealed gene regulatory networks that pattern the brainstem and/or govern the differentiation of cranial motor neurons. Mutations in genes involved in axon growth and guidance disrupt specific stages of the extension and pathfinding of ocular motor nerves, and have been implicated in human strabismus. These genes encompass varied classes of molecule, from receptor complexes to dynamic effectors to cytoskeletal components, including Robo3/Rig1, Alpha2-chimaerin, Kif21A, TUBB2, and TUBB3. A current challenge is to understand the protein regulatory networks that link the cell surface to the cytoskeleton and to dissect the co-ordinated signalling cascades and motile responses that underpin axonal navigation. Here we review recent insights derived from basic and clinical science approaches, to show how, by capitalising on the strengths of each, a more complete picture of the aetiology of human congenital cranial dysinnervation disorders can be achieved. This elucidation of these principles illustrates the success of clinical genetic studies working in tandem with molecular and cellular models to enhance our understanding of human disease. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 861-875, 2017.

Exploring the FGFR3-related oncogenic mechanism in bladder cancer using bioinformatics strategy

BackgroundAberrant activation of fibroblast growth factor receptor 3 (FGFR3) is frequently observed in bladder cancer, but how it involved in carcinogenesis is not well understood. The current study was aimed to investigate the underlying mechanism on the progression of bladder cancer.MethodsThe GSE41035 dataset downloaded from Gene Expression Omnibus was used to identify the differentially expressed genes (DEGs) between bladder cancer cell line RT112 with or without depletion of FGFR3, and gene ontology enrichment analysis was performed. Then, FGFR3-centered protein–protein interaction (PPI) and regulatory networks were constructed. Combined with the data retrieved from GSE31684, prognostic makers for bladder cancer were predicted.ResultsWe identified a total of 2855 DEGs, and most of them were associated with blood vessel morphogenesis and cell division. In addition, KIAA1377, POLA2, FGFR3, and EPHA4 were the hub genes with high degree in the FGFR3-centered PPI network. Besides, 17 microRNAs (miRNAs) and 6 transcriptional factors (TFs) were predicted to be the regulators of the nodes in PPI network. Moreover, CSTF2, POLA1, HMOX2, and EFNB2 may be associated with the prognosis of bladder cancer patient.ConclusionsThe current study may provide some insights into the molecular mechanism of FGFR3 as a mediator in bladder cancer.

Early Heat Shock Protein Response and Selection of Reference Genes in Arabidopsis thaliana Seedlings Subjected to Marine Fuel Contamination

Strategies for management of damaged environments can benefit from understanding of how early petrochemical pollution affect living organisms. One of the general responses to environmental stress in plants is mediated by the regulatory network of heat shock proteins (HSP). Arabidopsis thaliana is a model plant for genetic studies, and laboratory experiments with this species might be informative for predicting analogous responses to toxicants in other species. Here, Arabidopsis seedlings were exposed to time-varying contamination (up to 24 h) with the water soluble fraction of MF380 marine fuel (WSF-MF380). An accurate estimation of expression differences in HSP genes was obtained by real-time quantitative polymerase chain reaction (qPCR). After a thorough selection and validation of reference genes, two gene pairs were found to be stably expressed across control and WSF-MF380-treated samples and were used as normalization factors. Next, we evaluated the normalized expression of five HSP genes in response to the time-varying WSF-MF380 contamination. Four HSPs presented a significant increase in gene expression, which suggests that they might be tested as biomarkers for early exposure to petrochemical compounds. While a nearly immediate response (3 h after contamination) was found for HSP90.1 and two small HSP genes localized in the mitochondria (sHSP23.5 and sHSP26.5), a slightly later response (20 h) was observed for a third small HSP with a cytoplasmic/nuclear localization (sHSP18.2). Overall, these expression changes suggest the existence of a genetic cross-talk between canonical regulatory networks of HSPs and the cellular response to non-heat stress factors, such as marine oil contamination.

The OsHAPL1-DTH8-Hd1 complex functions as the transcription regulator to repress heading date in rice.

Heading date is an important agronomic trait related to crop yield. Many genes related to heading date have already been identified in rice (Oryza sativa), and a complicated, preliminary regulatory genetic network has also already been established, but the protein regulatory network is poorly understood. We have identified a novel heading date regulator, Heme Activator Protein like 1 (OsHAPL1), which inhibits flowering under long-day conditions. OsHAPL1 is a nuclear-localized protein that is highly expressed in leaves in a rhythmic manner. OsHAPL1 can physically interact with Days To Heading on chromosome 8 (DTH8), which physically interacts with Heading date 1 (Hd1) both in vitro and in vivo. OsHAPL1 forms a complex with DTH8 and Hd1 in Escherichia coli. OsHAPL1, DTH8, and Hd1 physically interact with the HAP complex, and also with general transcription factors in yeast (Saccharomyces cerevisiae). Further studies showed that OsHAPL1 represses the expression of the florigen genes and FLOWERING LOCUS T 1 (RFT1) and Hd3a through Early heading date 1 (Ehd1). We propose that OsHAPL1 functions as a transcriptional regulator and, together with DTH8, Hd1, the HAP complex, and general transcription factors, regulates the expression of target genes and then affects heading date by influencing the expression of Hd3a and RFT1 through Ehd1.

MYC and RAF: Key Effectors in Cellular Signaling and Major Drivers in Human Cancer.

The prototypes of the human MYC and RAF gene families are orthologs of animal proto-oncogenes that were originally identified as transduced alleles in the genomes of highly oncogenic retroviruses. MYC and RAF genes are now established as key regulatory elements in normal cellular physiology, but also as major cancer driver genes. Although the predominantly nuclear MYC proteins and the cytoplasmic RAF proteins have different biochemical functions, they are functionally linked in pivotal signaling cascades and circuits. The MYC protein is a transcription factor and together with its dimerization partner MAX holds a central position in a regulatory network of bHLH-LZ proteins. MYC regulates transcription conducted by all RNA polymerases and controls virtually the entire transcriptome. Fundamental cellular processes including distinct catabolic and anabolic branches of metabolism, cell cycle regulation, cell growth and proliferation, differentiation, stem cell regulation, and apoptosis are under MYC control. Deregulation of MYC expression by rearrangement or amplification of the MYC locus or by defects in kinase-mediated upstream signaling, accompanied by loss of apoptotic checkpoints, leads to tumorigenesis and is a hallmark of most human cancers. The critically controlled serine/threonine RAF kinases are central nodes of the cytoplasmic MAPK signaling cascade transducing converted extracellular signals to the nucleus for reshaping transcription factor controlled gene expression profiles. Specific mutations of RAF kinases, such as the prevalent BRAF(V600E) mutation in melanoma, or defects in upstream signaling or feedback loops cause decoupled kinase activities which lead to tumorigenesis. Different strategies for pharmacological interference with MYC- or RAF-induced tumorigenesis are being developed and several RAF kinase inhibitors are already in clinical use.

Rapid kinetic BRET measurements to monitor G protein activation by GPCR and non-GPCR proteins.

Heterotrimeric G proteins are central hubs of signal transduction whose activity is controlled by G protein-coupled receptors (GPCRs) as well as by a complex network of regulatory proteins. Recently, bioluminescence resonance energy transfer (BRET)-based assays have been used to monitor real-time activation of heterotrimeric G proteins in cells. Here we describe the use of a previously established BRET assay to monitor G protein activation upon GPCR stimulation and its adaptation to measure G protein activation by non-GPCR proteins, such as by cytoplasmic guanine nucleotide exchange factors (GEFs) like GIV/Girdin. The BRET assay monitors the release of free Gβγ from Gα-Gβγ heterotrimers as a readout of G protein activation, which is readily observable upon agonist stimulation of GPCRs. To control the signal input for non-GPCR activators, we describe the use of a chemically induced dimerization strategy to promote rapid membrane translocation of proteins containing the Gα-binding and -activating (GBA) motif found in some nonreceptor GEFs. The assay described here allows the kinetic measurement of G protein activation with subsecond temporal resolution and to compare the levels of activation induced by GPCR agonists vs those induced by the membrane recruitment of nonreceptor G protein signaling activators.

Fluorescence polarization assays to measure interactions between Gα subunits of heterotrimeric G proteins and regulatory motifs.

Fluorescence polarization (FP) is a simple and sensitive method allowing for the quantification of interactions between proteins and fluorescently tagged small molecules like peptides. Heterotrimeric G proteins are critical signal transducing molecules and their activity is controlled by a complex network of regulatory proteins. Some of these regulators have defined short motifs (<40 amino acids) that are sufficient to bind G proteins and subsequently modulate their activity. For these cases, FP represents a robust and quantitative method to characterize the G protein regulator interaction. Here we describe FP assays in a 384-well plate format to quantify interactions between Gα subunits of heterotrimeric G proteins and peptides corresponding to the Gα binding and activating (GBA) or GoLoco motifs, which are present in some proteins with guanine nucleotide exchange factor (GEF) (e.g., GIV/Girdin) or guanine nucleotide dissociation inhibitor (GDI) (e.g., RGS12) activity, respectively. This assay can be used to determine equilibrium dissociation constants, characterize the impact of single amino acid point mutations on the Gα-peptide interaction, and is suitable for high-throughput screening.

Proteomic analysis of maize grain development using iTRAQ reveals temporal programs of diverse metabolic processes.

BackgroundGrain development in maize is an essential process in the plant’s life cycle and is vital for use of the plant as a crop for animals and humans. However, little is known regarding the protein regulatory networks that control grain development. Here, isobaric tag for relative and absolute quantification (iTRAQ) technology was used to analyze temporal changes in protein expression during maize grain development.ResultsMaize grain proteins and changes in protein expression at eight developmental stages from 3 to 50 d after pollination (DAP) were performed using iTRAQ-based proteomics. Overall, 4751 proteins were identified; 2639 of these were quantified and 1235 showed at least 1.5-fold changes in expression levels at different developmental stages and were identified as differentially expressed proteins (DEPs). The DEPs were involved in different cellular and metabolic processes with a preferential distribution to protein synthesis/destination and metabolism categories. A K-means clustering analysis revealed coordinated protein expression associated with different functional categories/subcategories at different development stages.ConclusionsOur results revealed developing maize grain display different proteomic characteristics at distinct stages, such as numerous DEPs for cell growth/division were highly expressed during early stages, whereas those for starch biosynthesis and defense/stress accumulated in middle and late stages, respectively. We also observed coordinated expression of multiple proteins of the antioxidant system, which are essential for the maintenance of reactive oxygen species (ROS) homeostasis during grain development. Particularly, some DEPs, such as zinc metallothionein class II, pyruvate orthophosphate dikinase (PPDK) and 14-3-3 proteins, undergo major changes in expression at specific developmental stages, suggesting their roles in maize grain development. These results provide a valuable resource for analyzing protein function on a global scale and also provide new insights into the potential protein regulatory networks that control grain yield and quality.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-016-0878-1) contains supplementary material, which is available to authorized users.

Prediction of thioredoxin and glutaredoxin target proteins by identifying reversibly oxidized cysteinyl residues.

A significant part of cellular proteins undergo reversible thiol-dependent redox transitions which often control or switch protein functions. Thioredoxins and glutaredoxins constitute two key players in this redox regulatory protein network. Both interact with various categories of proteins containing reversibly oxidized cysteinyl residues. The identification of thioredoxin/glutaredoxin target proteins is a critical step in constructing the redox regulatory network of cells or subcellular compartments. Due to the scarcity of thioredoxin/glutaredoxin target protein records in the public database, a tool called Reversibly Oxidized Cysteine Detector (ROCD) is implemented here to identify potential thioredoxin/glutaredoxin target proteins computationally, so that the in silico construction of redox regulatory network may become feasible. ROCD was tested on 46 thioredoxin target proteins in plant mitochondrion, and the recall rate was 66.7% when 50% sequence identity was chosen for structural model selection. ROCD will be used to predict the thioredoxin/glutaredoxin target proteins in human liver mitochondrion for our redox regulatory network construction project. The ROCD will be developed further to provide prediction with more reliability and incorporated into biological network visualization tools as a node prediction component. This work will advance the capability of traditional database- or text mining-based method in the network construction.

ChemInform Abstract: Cross‐Linking and Other Structural Proteomics Techniques: How Chemistry Is Enabling Mass Spectrometry Applications in Structural Biology

AbstractReview: 123 refs.

Global proteomic and phosphoproteomic analysis of the premature maize anther

Reversible phosphorylation plays a crucial role in regulating protein activities and functions. Sexual reproduction directly affects yield of most agricultural crops. As the male reproductive organ, anther generates microspores (pollen), delivering gametes (sperms) to complete double fertilization in higher plants. Here, we took the advantage of Nano UHPLC-MS/MS to analyze maize (Zea mays, B73) early anthers at proteomic and phosphoproteomic levels, to explore the protein and phosphorylation modification regulatory networks controlling maize anther development. Our proteomic analysis identified 3 016 unique peptides, belonging to 1 032 maize proteins. MapMan analysis revealed variously potential proteins associated with maize anther development, such as receptor-like kinases (GRMZM2G082823_P01 and GRMZM5G805485_P01). Using phospho-peptides enriched by TiO2 affinity chromatography, our phosphoproteomic analysis detected 257 phospho-peptides from 210 phosphoproteins, discovering 223 phosphosites. Compared to the 86 maize phosphoproteins collected in the Plant Protein Phosphorylation Data Base (P3DB), we found that 203 phosphoproteins and 218 phosphosites were not revealed before. Further bioinformatics analysis revealed that phosphorylation of 14-3-3 proteins, kinases, phosphatases, transcription factors, cell cycle and chromatin structure related proteins might play important roles in regulating normal anther development in maize. Our findings not only enlarged the maize phosphoproteome data, but also provided information for analyzing the molecular mechanism controlling maize anther development at genetic and biochemical levels.

A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks.

To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a “standard component” modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with “standard components” can capture in quantitative detail many essential properties of cell cycle control in budding yeast.

Global De Novo Protein-Protein Interactome Elucidates Interactions of Drought-Responsive Proteins in Horse Gram (Macrotyloma uniflorum).

Inspired by the availability of de novo transcriptome of horse gram (Macrotyloma uniflorum) and recent developments in systems biology studies, the first ever global protein-protein interactome (PPI) map was constructed for this highly drought-tolerant legume. Large-scale studies of PPIs and the constructed database would provide rationale behind the interplay at cascading translational levels for drought stress-adaptive mechanisms in horse gram. Using a bidirectional approach (interolog and domain-based), a high-confidence interactome map and database for horse gram was constructed. Available transcriptomic information for shoot and root tissues of a sensitive (M-191; genotype 1) and a drought-tolerant (M-249; genotype 2) genotype of horse gram was utilized to draw comparative PPI subnetworks under drought stress. High-confidence 6804 interactions were predicted among 1812 proteins covering about one-fourth of the horse gram proteome. The highest number of interactions (33.86%) in horse gram interactome matched with Arabidopsis PPI data. The top five hub nodes mostly included ubiquitin and heat-shock-related proteins. Higher numbers of PPIs were found to be responsive in shoot tissue (416) and root tissue (2228) of genotype 2 compared with shoot tissue (136) and root tissue (579) of genotype 1. Characterization of PPIs using gene ontology analysis revealed that kinase and transferase activities involved in signal transduction, cellular processes, nucleocytoplasmic transport, protein ubiquitination, and localization of molecules were most responsive to drought stress. Hence, these could be framed in stress adaptive mechanisms of horse gram. Being the first legume global PPI map, it would provide new insights into gene and protein regulatory networks for drought stress tolerance mechanisms in horse gram. Information compiled in the form of database (MauPIR) will provide the much needed high-confidence systems biology information for horse gram genes, proteins, and involved processes. This information would ease the effort and increase the efficacy for similar studies on other legumes. Public access is available at http://14.139.59.221/MauPIR/ .