Functional Characterization of MODY2 Mutations Highlights the Importance of the Fine-Tuning of Glucokinase and Its Role in Glucose Sensing

BackgroundThe detection of significant compensatory mutation signals in multiple sequence alignments (MSAs) is often complicated by noise. A challenging problem in bioinformatics is remains the separation of significant signals between two or more non-conserved residue sites from the phylogenetic noise and unrelated pair signals. Determination of these non-conserved residue sites is as important as the recognition of strictly conserved positions for understanding of the structural basis of protein functions and identification of functionally important residue regions. In this study, we developed a new method, the Coupled Mutation Finder (CMF) quantifying the phylogenetic noise for the detection of compensatory mutations.ResultsTo demonstrate the effectiveness of this method, we analyzed essential sites of two human proteins: epidermal growth factor receptor (EGFR) and glucokinase (GCK). Our results suggest that the CMF is able to separate significant compensatory mutation signals from the phylogenetic noise and unrelated pair signals. The vast majority of compensatory mutation sites found by the CMF are related to essential sites of both proteins and they are likely to affect protein stability or functionality.ConclusionsThe CMF is a new method, which includes an MSA-specific statistical model based on multiple testing procedures that quantify the error made in terms of the false discovery rate and a novel entropy-based metric to upscale BLOSUM62 dissimilar compensatory mutations. Therefore, it is a helpful tool to predict and investigate compensatory mutation sites of structural or functional importance in proteins. We suggest that the CMF could be used as a novel automated function prediction tool that is required for a better understanding of the structural basis of proteins. The CMF server is freely accessible at http://cmf.bioinf.med.uni-goettingen.de.

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“…16 of these significant residue positions are related to disease associated nsSNP positions [29-31,34,35] (see Figure 3). …”

Section: Resultsmentioning

confidence: 99%

Coupled mutation finder: A new entropy-based method quantifying phylogenetic noise for the detection of compensatory mutations

et al. 2012

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“…We next applied our computational model to examine the role of electrical coupling in the presence of specific GCK mutations that cause NDM or MODY. We simulated the islet in the presence of electrical coupling and included altered GK kinetics based upon the biochemical characterization of a set of GCK mutations that cause MODY or PNDM (Table S1) [36,[45][46][47][48][49][50][51][52][53][54][55][56][57][58]. The majority of PNDM GCK mutations (4/5) fully suppressed [Ca 2+ ] at elevated glucose (Fig.…”

Section: Figure 4: Experimentally Demonstrating How Heterogeneity In mentioning

confidence: 99%

How heterogeneity in glucokinase and gap junction coupling determines the islet electrical response

Dwulet

Ludin

Piscopio

et al. 2019

Preprint

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Understanding how cell sub-populations in a tissue impact the function of the overall system is often challenging. There is extensive heterogeneity among insulin-secreting β-cells within islets of Langerhans, including their insulin secretory response and gene expression profile; and this heterogeneity can be altered in diabetes. Several studies have identified variations in nutrient sensing between β-cells, including glucokinase (GK) levels, mitochondrial function or expression of genes important for glucose metabolism. Sub-populations of β-cells with defined electrical properties can disproportionately influence islet-wide free-calcium activity ([Ca2+]) and insulin secretion, via gap junction electrical coupling. However, it is poorly understood how sub-populations of β-cells with altered glucose metabolism may impact islet function. To address this, we utilized a multicellular computational model of the islet in which a population of cells deficient in GK activity and glucose metabolism was imposed on the islet, or where β-cells were heterogeneous in glucose metabolism and GK kinetics were altered. This included simulating Glucokinase gene (GCK) mutations that cause monogenic diabetes. We combined these approaches with experimental models in which gck was genetically deleted in a population of cells or GK was pharmacologically inhibited. In each case we modulated gap junction electrical coupling. Both the simulated islet and the experimental system required 30-50% of the cells to have near-normal glucose metabolism. Below this number, the islet lacked any glucose-stimulated [Ca2+] elevations. In the absence of electrical coupling the change in [Ca2+] was more gradual. As such, given heterogeneity in glucose metabolism, electrical coupling allows a large minority of cells with normal glucose metabolism to promote glucose-stimulated [Ca2+]. If insufficient numbers of cells are present, which we predict can be caused by a subset of GCK mutations that cause monogenic diabetes, electrical coupling exacerbates [Ca2+] suppression. This demonstrates precisely how heterogeneous β-cell populations interact to impact islet function.SIGNIFICANCEBiological tissues contain heterogeneous populations of cells. Insulin-secreting β-cells within the islets of Langerhans are critical for regulating blood glucose homeostasis. β-cells are heterogeneous but it is unclear how the islet response is impacted by different cell populations and their interactions. We use a multicellular computational model and experimental systems to predict and quantify how cellular populations defined by varied glucose metabolism interact via electrical communication to impact islet function. When glucose metabolism is heterogeneous, electrical coupling is critical to promote electrical activity. However, when cells deficient in glucose metabolism are in the majority, electrical activity is completely suppressed. Thus modulating electrical communication can promotes islet electrical activity, following dysfunction caused by gene mutations that impact glucose metabolism.

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“…The relative activity index was normalised to 5 mmol/ L basal blood glucose (Christesen et al 2002). GCK activator LY2121260 (Elli Lilly and Co) was prepared as described (García-Herrero et al 2012).…”

Section: Enzymatic Analysis Of Wild-type and Mutant Gckmentioning

confidence: 99%

Lack of Glibenclamide Response in a Case of Permanent Neonatal Diabetes Caused by Incomplete Inactivation of Glucokinase

et al. 2014

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Functional Characterization of MODY2 Mutations Highlights the Importance of the Fine-Tuning of Glucokinase and Its Role in Glucose Sensing

Cited by 24 publications

References 37 publications

Coupled mutation finder: A new entropy-based method quantifying phylogenetic noise for the detection of compensatory mutations

Coupled mutation finder: A new entropy-based method quantifying phylogenetic noise for the detection of compensatory mutations

How heterogeneity in glucokinase and gap junction coupling determines the islet electrical response

Lack of Glibenclamide Response in a Case of Permanent Neonatal Diabetes Caused by Incomplete Inactivation of Glucokinase

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