Research resource: Gonadotropin-releasing hormone receptor-mediated signaling network in LbetaT2 cells: a pathway-based web-accessible knowledgebase

Genome-wide selection signatures address trait specific candidate genes in cattle indigenous to arid regions of India

The peculiarity of Indian cattle lies in milk quality, resistance to diseases and stressors as well as adaptability. The investigation addressed selection signatures in Gir and Tharparkar cattle, belonging to arid ecotypes of India. Double digest restriction-site associated DNA sequencing (ddRAD-seq) yielded nearly 26 million high-quality reads from unrelated seven Gir and seven Tharparkar cows. In all, 19,127 high-quality SNPs were processed for selection signature analysis. An approach involving within-population composite likelihood ratio (CLR) statistics and between-population FST statistics was used to capture selection signatures within and between the breeds, respectively. A total of 191 selection signatures were addressed using CLR and FST approaches. Selection signatures overlapping 86 and 73 genes were detected as Gir- and Tharparkar-specific, respectively. Notably, genes related to production (CACNA1D, GHRHR), reproduction (ESR1, RBMS3), immunity (NOSTRIN, IL12B) and adaptation (ADAM22, ASL) were annotated to selection signatures. Gene pathway analysis revealed genes in insulin/IGF pathway for milk production, gonadotropin releasing hormone pathway for reproduction, Wnt signalling pathway and chemokine and cytokine signalling pathway for adaptation. This is the first study where selection signatures are identified using ddRAD-seq in indicine cattle breeds. The study shall help in conservation and leveraging genetic improvements in Gir and Tharparkar cattle.

Label-free quantitative proteomic analysis of gingival crevicular fluid to identify potential early markers for root resorption

Background

Orthodontically-induced root resorption is an iatrogenic effect and it cannot be examined regularly due to the harmful effects of sequential doses of radiation with more frequent radiography. This study aims to compare protein abundance (PA) of pre-treatment and during orthodontic treatment for root resorption and to determine potential early markers for root resorption.

Methods

Ten subjects (n = 10) who had upper and lower fixed appliances (MBT, 3 M Unitek, 0.022″ × 0.028″) were recruited for this study. Human gingival crevicular fluid (GCF) was obtained using periopaper strips at pre-treatment (T0), 1 month (T1), 3 months (T3), and 6 months (T6) of orthodontic treatment. Periapical radiographs of the upper permanent central incisors were taken at T0 and T6 to measure the amount of root resorption. Identification of changes in PA was performed using liquid chromatography-tandem mass spectrometry. Student’s t-test was then performed to determine the significance of the differences in protein abundance before and after orthodontic treatment.

Results

Our findings showed that all ten subjects had mild root resorption, with an average resorption length of 0.56 ± 0.30 mm. A total of 186 proteins were found to be commonly present at T0, T1, T3, and T6. There were significant changes in the abundance of 16 proteins (student’s t-test, p ≤ 0.05). The increased PA of S100A9, immunoglobulin J chain, heat shock protein 1A, immunoglobulin heavy variable 4–34 and vitronectin at T1 suggested a response to stress that involved inflammation during the early phase of orthodontic treatment. On the other hand, the increased PA of thymidine phosphorylase at T3 suggested growth promotion and, angiogenic and chemotactic activities.

Conclusions

The identified proteins can be potential early markers for root resorption based on the increase in their respective PA and predicted roles during the early phase of orthodontic treatment. Non-invasive detection of root resorption using protein markers as early as possible is extremely important as it can aid orthodontists in successful orthodontic treatment.

Gonadotropin-releasing hormone signaling: An information theoretic approach

Gonadotropin-releasing hormone (GnRH) is a peptide hormone that mediates central control of reproduction, acting via G-protein coupled receptors that are primarily G_q coupled and mediate GnRH effects on the synthesis and secretion of luteinizing hormone and follicle-stimulating hormone. A great deal is known about the GnRH receptor signaling network but GnRH is secreted in short pulses and much less is known about how gonadotropes decode this pulsatile signal. Similarly, single cell measures reveal considerable cell-cell heterogeneity in responses to GnRH but the impact of this variability on signaling is largely unknown. Ordinary differential equation-based mathematical models have been used to explore the decoding of pulse dynamics and information theory-derived statistical measures are increasingly used to address the influence of cell-cell variability on the amount of information transferred by signaling pathways. Here, we describe both approaches for GnRH signaling, with emphasis on novel insights gained from the information theoretic approach and on the fundamental question of why GnRH is secreted in pulses.

The gastrin and cholecystokinin receptors mediated signaling network: a scaffold for data analysis and new hypotheses on regulatory mechanisms

Background

The gastrointestinal peptide hormones cholecystokinin and gastrin exert their biological functions via cholecystokinin receptors CCK1R and CCK2R respectively. Gastrin, a central regulator of gastric acid secretion, is involved in growth and differentiation of gastric and colonic mucosa, and there is evidence that it is pro-carcinogenic. Cholecystokinin is implicated in digestion, appetite control and body weight regulation, and may play a role in several digestive disorders.

Results

We performed a detailed analysis of the literature reporting experimental evidence on signaling pathways triggered by CCK1R and CCK2R, in order to create a comprehensive map of gastrin and cholecystokinin-mediated intracellular signaling cascades. The resulting signaling map captures 413 reactions involving 530 molecular species, and incorporates the currently available knowledge into one integrated signaling network. The decomposition of the signaling map into sub-networks revealed 18 modules that represent higher-level structures of the signaling map. These modules allow a more compact mapping of intracellular signaling reactions to known cell behavioral outcomes such as proliferation, migration and apoptosis. The integration of large-scale protein-protein interaction data to this literature-based signaling map in combination with topological analyses allowed us to identify 70 proteins able to increase the compactness of the map. These proteins represent experimentally testable hypotheses for gaining new knowledge on gastrin- and cholecystokinin receptor signaling. The CCKR map is freely available both in a downloadable, machine-readable SBML-compatible format and as a web resource through PAYAO (http://sblab.celldesigner.org:18080/Payao11/bin/).

Conclusion

We have demonstrated how a literature-based CCKR signaling map together with its protein interaction extensions can be analyzed to generate new hypotheses on molecular mechanisms involved in gastrin- and cholecystokinin-mediated regulation of cellular processes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0181-z) contains supplementary material, which is available to authorized users.

Atlas of Cancer Signalling Network: a systems biology resource for integrative analysis of cancer data with Google Maps

Cancerogenesis is driven by mutations leading to aberrant functioning of a complex network of molecular interactions and simultaneously affecting multiple cellular functions. Therefore, the successful application of bioinformatics and systems biology methods for analysis of high-throughput data in cancer research heavily depends on availability of global and detailed reconstructions of signalling networks amenable for computational analysis. We present here the Atlas of Cancer Signalling Network (ACSN), an interactive and comprehensive map of molecular mechanisms implicated in cancer. The resource includes tools for map navigation, visualization and analysis of molecular data in the context of signalling network maps. Constructing and updating ACSN involves careful manual curation of molecular biology literature and participation of experts in the corresponding fields. The cancer-oriented content of ACSN is completely original and covers major mechanisms involved in cancer progression, including DNA repair, cell survival, apoptosis, cell cycle, EMT and cell motility. Cell signalling mechanisms are depicted in detail, together creating a seamless ‘geographic-like' map of molecular interactions frequently deregulated in cancer. The map is browsable using NaviCell web interface using the Google Maps engine and semantic zooming principle. The associated web-blog provides a forum for commenting and curating the ACSN content. ACSN allows uploading heterogeneous omics data from users on top of the maps for visualization and performing functional analyses. We suggest several scenarios for ACSN application in cancer research, particularly for visualizing high-throughput data, starting from small interfering RNA-based screening results or mutation frequencies to innovative ways of exploring transcriptomes and phosphoproteomes. Integration and analysis of these data in the context of ACSN may help interpret their biological significance and formulate mechanistic hypotheses. ACSN may also support patient stratification, prediction of treatment response and resistance to cancer drugs, as well as design of novel treatment strategies.

In silico model-based inference: a contemporary approach for hypothesis testing in network biology

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics.

Outside the box signaling: secreted factors modulate GnRH receptor-mediated gonadotropin regulation

Control of gene expression following activation of membrane receptors results from the regulation of intracellular signaling pathways and transcription factors. Accordingly, research to elucidate the regulatory control circuits and cellular data processing mechanisms focuses on intracellular mechanisms. While autocrine and paracrine signaling are acknowledged in endocrinology, secreted factors are not typically recognized as fundamental components of the pathways connecting cell surface receptors to gene control in the nucleus. Studies of the gonadotrope suggest that extracellular regulatory loops may play a central role in the regulation of gonadotropin gene expression by gonadotropin-releasing hormone (GnRH) receptor activation. We review emerging evidence for this phenomenon, which we refer to as exosignaling, in gonadotropin gene control and in other receptor-mediated signaling systems. We propose that basic signaling circuit modules controlling gene expression can be seamlessly distributed across intracellular and exosignaling components that together orchestrate the precise physiological control of gene expression.

PANTHER in 2013: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees

The data and tools in PANTHER-a comprehensive, curated database of protein families, trees, subfamilies and functions available at http://pantherdb.org-have undergone continual, extensive improvement for over a decade. Here, we describe the current PANTHER process as a whole, as well as the website tools for analysis of user-uploaded data. The main goals of PANTHER remain essentially unchanged: the accurate inference (and practical application) of gene and protein function over large sequence databases, using phylogenetic trees to extrapolate from the relatively sparse experimental information from a few model organisms. Yet the focus of PANTHER has continually shifted toward more accurate and detailed representations of evolutionary events in gene family histories. The trees are now designed to represent gene family evolution, including inference of evolutionary events, such as speciation and gene duplication. Subfamilies are still curated and used to define HMMs, but gene ontology functional annotations can now be made at any node in the tree, and are designed to represent gain and loss of function by ancestral genes during evolution. Finally, PANTHER now includes stable database identifiers for inferred ancestral genes, which are used to associate inferred gene attributes with particular genes in the common ancestral genomes of extant species.

PANTHER in 2013: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees

The data and tools in PANTHER-a comprehensive, curated database of protein families, trees, subfamilies and functions available at http://pantherdb.org-have undergone continual, extensive improvement for over a decade. Here, we describe the current PANTHER process as a whole, as well as the website tools for analysis of user-uploaded data. The main goals of PANTHER remain essentially unchanged: the accurate inference (and practical application) of gene and protein function over large sequence databases, using phylogenetic trees to extrapolate from the relatively sparse experimental information from a few model organisms. Yet the focus of PANTHER has continually shifted toward more accurate and detailed representations of evolutionary events in gene family histories. The trees are now designed to represent gene family evolution, including inference of evolutionary events, such as speciation and gene duplication. Subfamilies are still curated and used to define HMMs, but gene ontology functional annotations can now be made at any node in the tree, and are designed to represent gain and loss of function by ancestral genes during evolution. Finally, PANTHER now includes stable database identifiers for inferred ancestral genes, which are used to associate inferred gene attributes with particular genes in the common ancestral genomes of extant species.

G proteins and autocrine signaling differentially regulate gonadotropin subunit expression in pituitary gonadotrope

Gonadotropin-releasing hormone (GnRH) acts at gonadotropes to direct the synthesis of the gonadotropins, follicle-stimulating hormone (FSH), and luteinizing hormone (LH). The frequency of GnRH pulses determines the pattern of gonadotropin synthesis. Several hypotheses for how the gonadotrope decodes GnRH frequency to regulate gonadotropin subunit genes differentially have been proposed. However, key regulators and underlying mechanisms remain uncertain. We investigated the role of individual G proteins by perturbations using siRNA or bacterial toxins. In LβT2 gonadotrope cells, FSHβ gene induction depended predominantly on Gα(q/11), whereas LHβ expression depended on Gα(s). Specifically reducing Gα(s) signaling also disinhibited FSHβ expression, suggesting the presence of a Gα(s)-dependent signal that suppressed FSH biosynthesis. The presence of secreted factors influencing FSHβ expression levels was tested by studying the effects of conditioned media from Gα(s) knockdown and cholera toxin-treated cells on FSHβ expression. These studies and related Transwell culture experiments implicate Gα(s)-dependent secreted factors in regulating both FSHβ and LHβ gene expression. siRNA studies identify inhibinα as a Gα(s)-dependent GnRH-induced autocrine regulatory factor that contributes to feedback suppression of FSHβ expression. These results uncover differential regulation of the gonadotropin genes by Gα(q/11) and by Gα(s) and implicate autocrine and gonadotrope-gonadotrope paracrine regulatory loops in the differential induction of gonadotropin genes.

Characterization of a MAPK scaffolding protein logic gate in gonadotropes

In the pituitary gonadotropes, both protein kinase C (PKC) and MAPK/ERK signaling cascades are activated by GnRH. Phosphoprotein-enriched in astrocytes 15 (PEA-15) is a cytosolic ERK scaffolding protein, which is expressed in LβT2 gonadotrope cells. Pharmacological inhibition of PKC and small interfering RNA-mediated silencing of Gαq/11 revealed that GnRH induces accumulation of phosphorylated PEA-15 in a PKC-dependent manner. To investigate the potential role of PEA-15 in GnRH signaling, we examined the regulation of ERK subcellular localization and the activation of ribosomal S6 kinase, a substrate of ERK. Results obtained by cellular fractionation/Western blot analysis and immunohistochemistry revealed that GnRH-induced accumulation of phosphorylated ERK in the nucleus was attenuated when PEA-15 expression was reduced. Conversely, in the absence of GnRH stimulation, PEA-15 anchors ERK in the cytosol. Our data suggest that GnRH-induced nuclear translocation of ERK requires its release from PEA-15, which occurs upon PEA-15 phosphorylation by PKC. Additional gene-silencing experiments in GnRH-stimulated cells demonstrated that ribosomal S6 kinase activation was dependent on both PEA-15 and PKC. Furthermore, small interfering RNA-mediated knockdown of PEA-15 caused a reduction in GnRH-stimulated expression of early response genes Egr2 and c-Jun, as well as gonadotropin FSHβ-subunit gene expression. PEA-15 knockdown increased LHβ and common α-glycoprotein subunit mRNAs, suggesting a possible role in differential regulation of gonadotropin subunit gene expression. We propose that PEA-15 represents a novel point of convergence of the PKC and MAPK/ERK pathways under GnRH stimulation. PKC, ERK, and PEA-15 form an AND logic gate that shapes the response of the gonadotrope cell to GnRH.

Gonadotropin-releasing hormone induces miR-132 and miR-212 to regulate cellular morphology and migration in immortalized LbetaT2 pituitary gonadotrope cells

GnRH is central to the regulation of reproductive function. It acts on pituitary gonadotropes to stimulate LH and FSH synthesis and secretion. We had previously presented evidence for translational control of LHβ synthesis; therefore we investigated whether micro-RNAs might play a role in GnRH regulation in LβT2 cells. We show here that GnRH strongly induces the AK006051 gene transcript that encodes two micro-RNAs, miR-132 and miR-212, within the first intron. We show furthermore that the AK006051 promoter region is highly GnRH responsive. We verify that the p250Rho GTPase activating protein (GAP) is a target of miR-132/212 and show that GnRH treatment leads to a decrease in mRNA and protein expression. This reduction is blocked by an anti-miR to miR-132/212 and mimicked by a pre-miR-132. GnRH inhibits p250RhoGAP expression through a miR-132/212 response element within the 3'-untranslated region. The loss of p250RhoGAP expression leads to activation of Rac and marked increases in both the number and length of neurite-like processes extending from the cell. Knockdown of p250RhoGAP by small interfering RNA induces the same morphological changes observed with GnRH treatment. In addition, loss of p250RhoGAP causes an increase in cellular motility. Our findings suggest a novel pathway regulating long-term changes in cellular motility and process formation via the GnRH induction of miR-132/212 with the subsequent down-regulation of p250RhoGAP.