High level production, characterization and structural analysis of neuronal calcium-activated potassium channels

Kaliumkanäle vermitteln als reguliertes Porenprotein den selektiven Transport von Kaliumionen durch die Zellmembran. Sie sind für physiologische Prozesse wie Neurosekretion und Tonus der glatten Muskulatur von Bedeutung. Eine Familie stellen die Calcium-aktivierten Kaliumkanäle dar, welche wiederum in drei Unterfamilien aufgeteilt werden können: SK-Kanäle (geringe Leitfähigkeit), BK-Kanäle (hohe Leitfähigkeit) und IK-Kanäle (mittlere Leitfähigkeit). Sie werden durch ein Ansteigen der intrazellulären Ca2+-Konzentration, wie sie während eines Aktionspotentials auftritt, aktiviert und zeigen keine Spannungsabhängigkeit der Aktivierung. SK-Kanäle sind in physiologische Prozesse wie Lernen, Erinnerungsvermögen, Regulation des Tagesrhytmus und Unterbrechung des normalen Schlafmusters involviert. Das SK2-Protein der Ratte (rSK2) wurde in Pichia pastoris-Zellen überexprimiert, um das Protein zu reinigen und genügend Material für strukturelle Studien zu erhalten. Dazu wurde die rSK2-cDNA in das Pichia Pastoris-Expressionssystem kloniert. Elektronenmikroskopische Lokalisationsstudien wie Immunogold-Markierung und Gefrierbruch-Analyse zeigten, daß der SK2-Kanal hauptsächlich an der Oberfläche des Endoplasmatischen Retikulums oder andersartigen internen Membranstrukturen lokalisiert ist. Dies steht im Gegensatz zu neuronalen Zellen, in denen das Protein eher in der Plasmamembran zu finden ist. Die Solubilisierung des Kanalproteins mit Detergentien war besonders schwierig zu erreichen. Von 15 getesteten Detergentien konnte das Kanalprotein nur mit Digitonin aus der Membran gelöst werden. Verschiedene chromatographische Verfahren wurden zur Reinigung des Kanals eingesetzt, aber das Protein wurde nur teilweise gereinigt und die Ausbeute war gering. Eine Gelfiltrationsanalyse zeigte, daß der gereinigte SK2-Kanal wie andere Kaliumkanäle als Homotetramer vorlag (MacKinnon 1991). Um einen verbesserten Einbau in die Plasmamembran zu erreichen, wurde versucht, ein weiteres SK2-Konstrukt zu exprimieren. Dieses verfügte über eine zusätzliche sechs Aminosäuren umfassende Sequenz (FCYENE), welche sich als bedeutsam für die Membranlokalisation anderer Kaliumkanäle herausgestellt hatte (Ma et al. 2001). Die Sequenz war an den Carboxyterminus angefügt. Der Effekt dieser Sequenz auf die SK2-Expression in Pichia pastoris wurde untersucht. Dies zeigte, daß die FCYENE-Sequenz keinen Effekt auf den gesamt-Expressionslevel bindungskompetenter Kanäle hatte. Digitonin, TritonX-100, n-Dodecyl-beta-D-maltosid (DDM) und Octyl-glycosid erlaubten eine Solubilisierung des SK2-FCYENE-Proteins. Dies zeigte, daß die FCYENE-Sequenz einen bemerkenswerten Effekt auf die Löslichkeit des SK2-Proteins hatte. Im Gegensatz zum Wildtyp zeigte das SK2-FCYENE-Protein auch eine veränderte Verteilung innerhalb der Hefezellen. Es lag nicht nur im Endoplasmatischen Retikulum, sondern auch konzentriert in Vesikeln vor. Trotzdem waren wie zuvor nur geringe Mengen an Protein in der Plasmamembran zu finden. Offenbar kann die FCYENE-Sequenz zwar den Austritt aus dem Endoplasmatischen Retikulum fördern, aber die Kanäle werden nicht in die Plasmamembran translokiert. Trotz der erhöhten Menge an löslichem Ausgangsmaterial wurde die Menge an gereinigtem Kanalprotein nicht nennenswert erhöht. Die Calcium-Sensitivität der SK-Kanäle wird durch eine Wechselwirkung mit Calmodulin hervorgerufen (Xia et al. 1998; Schumacher et al. 2001). Die Bindung zwischen Calmodulin und SK2-Protein ist nicht nur für das Öffnen, sondern auch für den Transport des Kanals essentiell (Lee et al. 2003). Deshalb wurde das SK2-Protein in tandem mit Calmodulin kloniert (SK2-q-CaM), wobei ein Verbindungsstück aus zehn Glutaminresten die beiden Proteine verband. Das Calmodulin veränderte dramatisch die Verteilung des Kanalproteins in der Zelle. Dies zeigte die Immunogold-Markierung des SK2-q-CaM-Proteins in den Pichia pastoris-Zellen. Einige der SK2-q-CaM-Chimären waren in der Plasmamembran lokalisiert. Ferner war die Effektivität der Solubilisierung mit Detergenz weitaus höher als für das wildtyp- und das SK2-FCYENE-Protein. Trotz der enormen Verbesserung der Löslichkeit war die Ausbeute an SK2-q-CaM-Protein geringer als für die beiden anderen Konstrukte, was vermutlich auf eine veränderte Verfügbarkeit der His-Sequenz durch die Wechselwirkung mit Calmodulin zurückzuführen war. Das SK2-Protein wurde zudem in der Säugerzelllinie BHK (Baby Hamster Kidney) unter Verwendung des Semliki Forest Virus-Systems exprimiert. Das Protein erreichte 24 h nach Virusinfektion einen hohen Expressionslevel. Eine Immunogold-Markierung bestätigte, daß das SK-Protein in die Plasmamembran eingebaut wurde, wenngleich ein Großteil des Proteins in den Membranen des Endoplasmatischen Retikulums verblieb. Apamin band mit hoher Affinität an das Kanalprotein, wobei die Daten der Sättigungskurven auf eine einzelne Bindungstelle hinwiesen. Diese Werte und Daten aus kompetitiven Verdrängungs-Experimenten waren mit jenen Werten, die mit nativen Hirnmembranen gemessen wurden, vergleichbar (Marqueze, Seagar et al. 1989; Wadsworth, Doorty et al. 1994; Wadsworth, Torelli et al. 1997). Das Kanalprotein ließ sich erfolgreich mit verschiedenen Detergentien, vor allem mit DDM, aus der Membran lösen. Mittels Ionenaustausch-Chromatographie konnten 0,1-0,2 mg/ml reines SK-Protein erhalten werden. Gelfiltrations-Chromatographie und Blau-Nativ Gelelektrophorese (BN-PAGE) zeigten, daß das reine Kanalprotein wie erwartet als Tetramer vorlag. Bis heute gibt es keine weiteren Berichte von gereinigtem SK2-Protein aus natürlicher oder rekombinanter Quelle. Trotz der relativ geringen Proteinausbeute ist die gelungene Reinigung des Proteins daher eine zentrale Erkenntnis für die Charakterisierung von SK-Kanälen.Calcium-activated potassium channels are fundamental regulators of neuron excitability. SK channels are activated by an intracellular increase of Ca++ (such as occurs during an action potential). They have a small single channel conductance (less than 20pS) and show no voltage dependence of activation. To date, there are only a few examples of high-resolution structures of eukaryotic membrane proteins. All of them were purified from natural sources. Since no abundant natural sources of eukaryotic K+ channels are available we overexpressed rSK2 in order to produce the quantities necessary for structural analysis. Unfortunately the Pichia pastoris expression system did not yield sufficient amount of pure protein, mainly because most of the protein was retained by in the ER and was only partially soluble. Subsequently, two constructs were expressed: SK2-FCYENE (containing a specific sequence that promotes surface expression), and SK2-q-CaM a concatamer of SK2 and calmodulin. Although these proved an improvement in terms of solubilisation, little improvement was found in terms of amounts of purified material obtained. For this reason we tested the Semliki Forest virus expression system, since the protein is expressed in a mammalian system where we hoped that it would be trafficked in the same way as in vivo. Using this system it was possible to express rSK2 and solubilise it with several detergents and to achieve much better purification. However, the levels were still not sufficient for high-resolution structural studies, although sufficient for single particle electron microscopy analysis

A Resource to Infer Molecular Paths Linking Cancer Mutations to Perturbation of Cell Metabolism

Some inherited or somatically-acquired gene variants are observed significantly more frequently in the genome of cancer cells. Although many of these cannot be confidently classified as driver mutations, they may contribute to shaping a cell environment that favours cancer onset and development. Understanding how these gene variants causally affect cancer phenotypes may help developing strategies for reverting the disease phenotype. Here we focus on variants of genes whose products have the potential to modulate metabolism to support uncontrolled cell growth. Over recent months our team of expert curators has undertaken an effort to annotate in the database SIGNOR 1) metabolic pathways that are deregulated in cancer and 2) interactions connecting oncogenes and tumour suppressors to metabolic enzymes. In addition, we refined a recently developed graph analysis tool that permits users to infer causal paths leading from any human gene to modulation of metabolic pathways. The tool grounds on a human signed and directed network that connects similar to 8400 biological entities such as proteins and protein complexes via causal relationships. The network, which is based on more than 30,000 published causal links, can be downloaded from the SIGNOR website. In addition, as SIGNOR stores information on drugs or other chemicals targeting the activity of many of the genes in the network, the identification of likely functional paths offers a rational framework for exploring new therapeutic strategies that revert the disease phenotype

SIGNOR 3.0, the SIGnaling network open resource 3.0: 2022 update

The SIGnaling Network Open Resource (SIGNOR 3.0, ) is a public repository that captures causal information and represents it according to an 'activity-flow' model. SIGNOR provides freely-accessible static maps of causal interactions that can be tailored, pruned and refined to build dynamic and predictive models. Each signaling relationship is annotated with an effect (up/down-regulation) and with the mechanism (e.g. binding, phosphorylation, transcriptional activation, etc.) causing the regulation of the target entity. Since its latest release, SIGNOR has undergone a significant upgrade including: (i) a new website that offers an improved user experience and novel advanced search and graph tools; (ii) a significant content growth adding up to a total of approx. 33,000 manually-annotated causal relationships between more than 8900 biological entities; (iii) an increase in the number of manually annotated pathways, currently including pathways deregulated by SARS-CoV-2 infection or involved in neurodevelopment synaptic transmission and metabolism, among others; (iv) additional features such as new model to represent metabolic reactions and a new confidence score assigned to each interaction

The landscape of microRNA interaction annotation: analysis of three rare disorders as a case study

In recent years, a huge amount of data on ncRNA interactions has been described in scientific papers and databases. Although considerable effort has been made to annotate the available knowledge in public repositories, there are still significant discrepancies in how different resources capture and interpret data on ncRNA functional and physical associations. In the present paper, we present a collection of microRNA-mRNA interactions annotated from the scientific literature following recognized standard criteria and focused on microRNAs, which regulate genes associated with rare diseases as a case study. The list of protein-coding genes with a known role in specific rare diseases was retrieved from the Genome England PanelApp, and associated microRNA-mRNA interactions were annotated in the IntAct database and compared with other datasets. RNAcentral identifiers were used for unambiguous, stable identification of ncRNAs. The information about the interaction was enhanced by a detailed description of the cell types and experimental conditions, providing a computer-interpretable summary of the published data, integrated with the huge amount of protein interactions already gathered in the database. Furthermore, for each interaction, the binding sites of the microRNA are precisely mapped on a well-defined mRNA transcript of the target gene. This information is crucial to conceive and design optimal microRNA mimics or inhibitors to interfere in vivo with a deregulated process. As these approaches become more feasible, high-quality, reliable networks of microRNA interactions are needed to help, for instance, in the selection of the best target to be inhibited and to predict potential secondary off-target effects. Database URL https://www.ebi.ac.uk/intact

Curation of causal interactions mediated by genes associated with autism accelerates the understanding of gene-phenotype relationships underlying neurodevelopmental disorders

Autism spectrum disorder (ASD) comprises a large group of neurodevelopmental conditions featuring, over a wide range of severity and combinations, a core set of manifestations (restricted sociality, stereotyped behavior and language impairment) alongside various comorbidities. Common and rare variants in several hundreds of genes and regulatory regions have been implicated in the molecular pathogenesis of ASD along a range of causation evidence strength. Despite significant progress in elucidating the impact of few paradigmatic individual loci, such sheer complexity in the genetic architecture underlying ASD as a whole has hampered the identification of convergent actionable hubs hypothesized to relay between the vastness of risk alleles and the core phenotypes. In turn this has limited the development of strategies that can revert or ameliorate this condition, calling for a systems-level approach to probe the cross-talk of cooperating genes in terms of causal interaction networks in order to make convergences experimentally tractable and reveal their clinical actionability. As a first step in this direction, we have captured from the scientific literature information on the causal links between the genes whose variants have been associated with ASD and the whole human proteome. This information has been annotated in a computer readable format in the SIGNOR database and is made freely available in the resource website. To link this information to cell functions and phenotypes, we have developed graph algorithms that estimate the functional distance of any protein in the SIGNOR causal interactome to phenotypes and pathways. The main novelty of our approach resides in the possibility to explore the mechanistic links connecting the suggested gene-phenotype relations

MINT and IntAct contribute to the Second BioCreative challenge: serving the text-mining community with high quality molecular interaction data

In the absence of consolidated pipelines to archive biological data electronically, information dispersed in the literature must be captured by manual annotation. Unfortunately, manual annotation is time consuming and the coverage of published interaction data is therefore far from complete. The use of text-mining tools to identify relevant publications and to assist in the initial information extraction could help to improve the efficiency of the curation process and, as a consequence, the database coverage of data available in the literature. The 2006 BioCreative competition was aimed at evaluating text-mining procedures in comparison with manual annotation of protein-protein interactions

The landscape of cancer-rewired GPCR signaling axes.

We explored the dysregulation of G-protein-coupled receptor (GPCR) ligand systems in cancer transcriptomics datasets to uncover new therapeutics opportunities in oncology. We derived an interaction network of receptors with ligands and their biosynthetic enzymes. Multiple GPCRs are differentially regulated together with their upstream partners across cancer subtypes and are associated to specific transcriptional programs and to patient survival patterns. The expression of both receptor-ligand (or enzymes) partners improved patient stratification, suggesting a synergistic role for the activation of GPCR networks in modulating cancer phenotypes. Remarkably, we identified many such axes across several cancer molecular subtypes, including many involving receptor-biosynthetic enzymes for neurotransmitters. We found that GPCRs from these actionable axes, including, e.g., muscarinic, adenosine, 5-hydroxytryptamine, and chemokine receptors, are the targets of multiple drugs displaying anti-growth effects in large-scale, cancer cell drug screens, which we further validated. We have made the results generated in this study freely available through a webapp (gpcrcanceraxes.bioinfolab.sns.it)

Resources and tools for rare disease variant interpretation

: Collectively, rare genetic disorders affect a substantial portion of the world's population. In most cases, those affected face difficulties in receiving a clinical diagnosis and genetic characterization. The understanding of the molecular mechanisms of these diseases and the development of therapeutic treatments for patients are also challenging. However, the application of recent advancements in genome sequencing/analysis technologies and computer-aided tools for predicting phenotype-genotype associations can bring significant benefits to this field. In this review, we highlight the most relevant online resources and computational tools for genome interpretation that can enhance the diagnosis, clinical management, and development of treatments for rare disorders. Our focus is on resources for interpreting single nucleotide variants. Additionally, we present use cases for interpreting genetic variants in clinical settings and review the limitations of these results and prediction tools. Finally, we have compiled a curated set of core resources and tools for analyzing rare disease genomes. Such resources and tools can be utilized to develop standardized protocols that will enhance the accuracy and effectiveness of rare disease diagnosis

MINT, the molecular interaction database: 2009 update

MINT (http://mint.bio.uniroma2.it/mint) is a public repository for molecular interactions reported in peer-reviewed journals. Since its last report, MINT has grown considerably in size and evolved in scope to meet the requirements of its users. The main changes include a more precise definition of the curation policy and the development of an enhanced and user-friendly interface to facilitate the analysis of the ever-growing interaction dataset. MINT has adopted the PSI-MI standards for the annotation and for the representation of molecular interactions and is a member of the IMEx consortium

The IntAct database:Efficient access to fine-grained molecular interaction data

The IntAct molecular interaction database (https://www.ebi.ac.uk/intact) is a curated resource of molecular interactions, derived from the scientific literature and from direct data depositions. As of August 2021, IntAct provides more than one million binary interactions, curated by twelve global partners of the International Molecular Exchange consortium, for which the IntAct database provides a shared curation and dissemination platform. The IMEx curation policy has always emphasised a fine-grained data and curation model, aiming to capture the relevant experimental detail essential for the interpretation of the provided molecular interaction data. Here, we present recent curation focus and progress, as well as a completely redeveloped website which presents IntAct data in a much more user-friendly and detailed way