Aurelio A. Moya-Garcia, Carlos E. Rodriguez, Ian Morilla, Francisca Sanchez-Jimenez, Juan A.G. Ranea

Departamento de Biologia Molecular y Bioquimica, Facultad de Ciencias, Campus de Teatinos, Universidad de Malaga, and CIBER de Enfermedades Raras (CIBERER), Valencia, Spain

TABLE OF CONTENTS

1. Abstract

2. Introduction

3. Methods

3.1. The Knowledgegram and the Predictogram

3.2. Mapping functions on networks

4. Results

4.1. Lack of knowledge about H4R relationships

4.2. H3R and H4R predicted functional associations

4.3. H3R and H4R interactors in the human brain

5. Discussion

5.1. Concluding remarks

6.Acknowledgements

7. References

1. ABSTRACT

The histamine H₄ receptor is mainly expressed in haematopoietic cells, hence is linked to inflammatory and immune system conditions. It has been recently discovered that the receptor is expressed also in the mammalian central nervous system (CNS), but its role in the brain remains unclear. We address the potential functions of the histamine H₄ receptor in the human brain using a 'guilty by association' logic, by close examination of protein-protein functional associations networks in the human proteome.

2. INTRODUCTION

Histamine H₄ receptor (H4R), the most recently discovered member of the histamine receptors family, is described as the immune system histamine receptor (1), since it is dominantly expressed in cells of the immune system and in peripheral cells and tissues, such as blood, spleen, lung, liver and gut (2, 3). It has been related to pathological conditions as inflammation (4) and allergy (5, 6), and linked to autoimmune diseases (7, 8) and cancer (9), although its precise functional characterization is an open and very active research field. It is clear that H4R can participate in diverse and complex physiological processes sometimes intertwined, this situation makes the identification and characterization of the receptor functions a hard task, which must be helped by systems biology technologies. Recently H4R has been reported to be functionally expressed on neurons (10), which broads the potential areas of function for this new histamine receptor. In this work we use the principle 'guilty by association' to establish firm hypothesis that drive new experimental approaches to unravel the role of H4R in the brain from its predicted functional partners.

3. METHODS

3.1. The Knowledgegram and the Predictogram

We used the Knowledgegram (KG) to find known functional associations for H4R in the human proteome and the Predictogram (PG) to predict new H4R functional partners. They comprise a set of methods that retrieve and combine protein-protein associations from major biological databases into a network (KG) and predict functional interactions (PG) (11).

Briefly, the KG includes the protein-protein association data from Reactome (12), Kegg (13), GO (14), FunCat (15), Intact (16), MINT (17) and HRPD (18). On the other hand the PG predicts binary protein functional associations in the human proteome (PG) by integrating different computational methods: Gene Expression COmparison (GECO) measures the correlation of gene expression profiles between protein pairs; homology Inherited Protein-Protein Interactions (hIPPI) scores potential protein-protein interactions based on their homology to known interacting protein pairs; and Co-Occurrence Domain Analysis (CODA) (19) looks for and scores protein pairs in a given target genome (e.g. human) found as fused (Co-Occurring) domain architectures in homologues from genomes of 575 different species. The integration of different computational prediction methods in the PG brings more accurate functional associations between proteins than using each individual method. The cumulative frequency distributions were calculated for each of the prediction score datasets (GECO, hiPPI and CODA). The particular Probability Density Functions (PDF) associated with the score distributions for each of the methods was calculated in order to translate the scores into p-values. The different methods p-values for each protein-protein pair were integrated into one single score using the Fisher weighted method (20). Integrated prediction scores were benchmarked using the highest quality annotations of the human proteome in the Gene Ontology. Precision associated with the Fisher scores was calculated as the ratio of cumulative TP/TP+FP at different prediction p-values, where TP (True Positives) is the rate of hits predicted as true protein binary associations in GO, and FP (False positive) is the average rate of hits predicted from 1000 random iterations.

3.2. Mapping functions on networks

All network analysis and visualization were done using Cytoscape (21). Mapping of the Gene Ontology (GO) categories statistically overrepresented in our networks were done with the BiNGO plugin (22) within Cytoscape, searching in the Biological Process and GO Full ontologies with the hypergeometric statistical test and a significance level of 0,05.

4. RESULTS

4.1. Lack of knowledge about H4R relationships

When using H4R as a bait to check the current knowledge about proteins associated with the receptor, we found virtually no output, that is there are no H4R interactors described and compiled in the major databases yet.

4.2. H3R and H4R predicted functional associations

Our PG analysis with the histamine H₃ receptor (H3R) yields 29 statistically significant interactions (p-val ≤ 0,014; 80% precision; Table 1). There are no homology inherited protein-protein interactions, but now we have domain fusion a gene co-expression signals in our functional relationships prediction. The overrepresented GO categories show the H3R function in neurotransmission. We found 188 statistically significant (p-val ≤ 0,014; 80% precision) functional interactions with H4R in the human proteome (Table 2). As with H3R there are no predicted physical interactions between the proteins in this highly reliable set and H4R, we have mainly predictions from gene co-expression signals and domain fusion. The Gene Ontology categories statistically overrepresented in this set of highly confiable H4R interactors, give us an overall picture of the cellular function H4R is involved in (Figure 1).

4.3. H3R and H4R interactors in the human brain

From the 29 H3R functional interactors predicted, 8 correspond to unknown proteins or unreviewed entries in UniProt (23). 11 out of the 21 characterized H3R predicted interactors are expressed in brain, offering a clear overview of the H3R role in the CNS.

We found 15 proteins predicted to have a functional relationship with H4R and expressed exclusively or mainly in the brain (Table 3). We obtain a strong co-expression signal between each interactor and H4R and no inherited physical protein-protein interaction. Most of them are proteins of unknown specific function or involved in elemental neuron biochemistry and development, but some of the proteins predicted to be co-expressed with H4R in the CNS play clear roles in important brain functions, they are highlighted in bold typeface in Table 3.

5. DISCUSSION

H3R is a well known pre-synaptic autoreceptor controlling histaminergic neuron activity (24) and a heteroreceptor regulating the release of important neurotransmitters, such as acetylcholine (25) and serotonine (26). We can see the involvement of the receptor in these functions from the analysis of the predicted interactions using the Predictogram. We also see its implications in neuronal diseases (27) such as epilepsy through gene co-expression and domain fusion signals with the Neuronal acetylcholine receptor subunit beta-2 (UniProt ID ACHB2_HUMAN); Alzheimer's disease through gene co-expression signal with Rab GTPase-activating protein 1-like (UniProt ID RBG1L_HUMAN). This indicates that we can obtain functional information for a protein from the analysis of its predicted functional interactors.

Our results do not include predicted protein-protein interactions (PPI) between H3R and proteins expressed by histaminergic neurons, Therefore we can not point to the role of H3R in the regulation of histamine release based on predictions. Coverage limitations are not only a shortcoming of the Predictogram methods, but it is a feature to any other experimental method able to obtain reliable PPI information, e.g. yeast two-hybrid experiments do not perform well on membrane-associated proteins and transient interactions tend to be under-reported (28). Besides, the data showing H3R as an autoreceptor in the regulation of histamine release is not even clear from the protein-protein associations described in the major databases using the Knowledgegram. We have also searched H3R protein associations with STRING (29) and iHOP (30); both powerful algorithms which uses text mining of literature, without clear outcomes in this direction (data not shown).

We address in this work the potential roles for H4R in the human brain from its predicted functional interactions in the human proteome. Its clear that the receptor is functionally expressed in the mammalian brain (10) but the receptor's role in the brain has not been established yet. Connelly et al. suggest H4R can complement histamine H₁ receptor (H1R) in the modulation of the circadian cycle (10), since H4R is much more sensitive sensors for histamine than H1R, H4R could act as the preferred histamine sensor during sleep when the histamine concentration is low. In this sense, we find a gene co-expression signal between H4R and the melatonin receptor type 1B (UniProt ID MTR1B_HUMAN) and with the enzyme serotonin N-acetyltransferase (Uniprot ID SNAT_HUMAN), both involved in the control of the night/day rhythm and circadian actions of melatonin.

Activation of H4R hyperpolarize cortical neurons (10), we find the subunit α of the glycine receptor (UniProt ID GLRA3_HUMAN) co-expressed with H4R which also inhibits neuronal firing, the glycine receptor can participate in the mechanism of this inhibitory response by H4R.

Relaxin-3 receptor 1 (UniProt ID RL3R1_HUMAN) is also co-expressed with H4R. This G protein-coupled receptor is present in the hypothalamic paraventricular nucleus, an area involved in the regulation of energy balance. Relaxin-3 is a peptide hormone belonging to the insulin superfamily that may act as signal to coordinate appetite, thyroid function and reproductive status (31). The potential coupling of this relaxin receptor and H4R functions, would imply an overlapping between H3R and H4R role in the brain, since loss of H3R function in knockout mice is associated with hyperphagia, obesity and increased insulin and leptin levels (32).

H4R could be involved in Alzheimer's disease. It is co-expressed with G protein-coupled receptor 3, an orphan receptor acting as a modulator of amyloid-β production. Overexpression of this GPCR stimulates amyloid-β production, while genetic ablation of the receptor prevented amyloid-β accumulation in an Alzheimer's disease mouse model (33). It is interesting to note that clobenpropit, a H3R antagonist with potential therapeutic application in conditions with memory deficits, like Alzheimer's disease (34) and clozapine, a H3R antagonist and antipsychotic drug with potential use in dementia (35) bind to H4R in the nanomolar range.

5.1. Concluding remarks

Histamine receptor 4, the newest member incorporated to the histamine receptors family may have an important role to play in the histaminergic system. From its predicted functional associations we obtained data supporting the probable H4R roles previously proposed, such as neuronal firing inhibition and its participation in circadian cycle modulation. Our data show that H4R and H3R could be involved together in processes, like sleep and homeostatic regulation, and allow us to hypothesize H4R participation in thyroid function and appetite coordination, as well as the histamine H₄ and glycine receptors in the mechanism of neuronal firing inhibition.

In summary, this work adds relevant information to the characterization of this G protein-coupled receptor, that can direct further research about its involvement in brain function and diseases.

6. ACKNOWLEDGMENTS

This work was supported by Grant SAF2008-2522 (Ministerio de Ciencia e Innovación, Spain), Grant BIO-267 from Junta de Andalucía and Funds from Fundación Ramón-Areces. Juan A. Garcia-Ranea acknowledges funding from SAF2009-09839 and the Ramon y Cajal program (RYC-2007-01649; Ministerio de Ciencia e Innovación, Spain). The authors acknowledge support from the European Cooperation in Science and Technology (COST) Action BM0806. CIBERER is an initiative of the ISCIII.

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Abbreviations: H4R: Histamine H₄ receptor; H3R: Histamine H₃ receptor; H1R: Histamine H₁ receptor; PG: Predictogram; KG: Knowledgegram; PDF: Probability Density Functions; TP: True Positive; FP: False Positive; PPI: Protein-Protein Interactions

Key Words: Histamine receptors, histamine, histamine receptor H4R, histamine receptor H3R,, human, network biology