Adenine nucleotide translocase is acetylated in vivo in human muscle: Modeling predicts a decreased ADP affinity and altered control of oxidative phosphorylation.

Proteomics techniques have revealed that lysine acetylation is abundant in mitochondrial proteins. This study was undertaken (1) to determine the relationship between mitochondrial protein acetylation and insulin sensitivity in human skeletal muscle, identifying key acetylated proteins, and (2) to use molecular modeling techniques to understand the functional consequences of acetylation of adenine nucleotide translocase 1 (ANT1), which we found to be abundantly acetylated. Eight lean and eight obese nondiabetic subjects had euglycemic clamps and muscle biopsies for isolation of mitochondrial proteins and proteomics analysis. A number of acetylated mitochondrial proteins were identified in muscle biopsies. Overall, acetylation of mitochondrial proteins was correlated with insulin action (r = 0.60; P < 0.05). Of the acetylated proteins, ANT1, which catalyzes ADP-ATP exchange across the inner mitochondrial membrane, was acetylated at lysines 10, 23, and 92. The extent of acetylation of lysine 23 decreased following exercise, depending on insulin sensitivity. Molecular dynamics modeling and ensemble docking simulations predicted the ADP binding site of ANT1 to be a pocket of positively charged residues, including lysine 23. Calculated ADP-ANT1 binding affinities were physiologically relevant and predicted substantial reductions in affinity upon acetylation of lysine 23. Insertion of these derived binding affinities as parameters into a complete mathematical description of ANT1 kinetics predicted marked reductions in adenine nucleotide flux resulting from acetylation of lysine 23. Therefore, acetylation of ANT1 could have dramatic physiological effects on ADP-ATP exchange. Dysregulation of acetylation of mitochondrial proteins such as ANT1 therefore could be related to changes in mitochondrial function that are associated with insulin resistance.

Modulation of function in a minimalist heme-binding membrane protein.

De novo designed heme-binding proteins have been used successfully to recapitulate features of natural hemoproteins. This approach has now been extended to membrane-soluble model proteins. Our group designed a functional hemoprotein, ME1, by engineering a bishistidine binding site into a natural membrane protein, glycophorin A (Cordova et al. in J Am Chem Soc 129:512-518, 2007). ME1 binds iron(III) protoporphyrin IX with submicromolar affinity, has a redox potential of -128 mV, and displays peroxidase activity. Here, we show the effect of aromatic residues in modulating the redox potential in the context of a membrane-soluble model system. We designed aromatic interactions with the heme through a single-point mutant, G25F, in which a phenylalanine is designed to dock against the porphyrin ring. This mutation results in roughly tenfold tighter binding to iron(III) protoporphyrin IX (K(d,app) = 6.5 × 10(-8) M), and lowers the redox potential of the cofactor to -172 mV. This work demonstrates that specific design features aimed at controlling the properties of bound cofactors can be introduced in a minimalist membrane hemoprotein model. The ability to modulate the redox potential of cofactors embedded in artificial membrane proteins is crucial for the design of electron transfer chains across membranes in functional photosynthetic devices.

Quantifying the Risk Continuum for Cardiovascular Death in Adults with Type 2 Diabetes.

OBJECTIVES: In type 2 diabetes (T2D), the most common causes of death are cardiovascular (CV) related, accounting for >50% of deaths in some reports. As novel diabetes therapies reduce CV death risk, identifying patients with T2D at highest CV death risk allows for cost-effective prioritization of these therapies. Accordingly, the primary goal of this study was to quantify the risk continuum for CV death in a real-world T2D population as a means to identify patients with the greatest expected benefit from cardioprotective antidiabetes therapies. METHODS: This retrospective study included patients with T2D receiving services through an integrated health-care system and used data generated through electronic medical records (EMRs). Quantifying the risk continuum entailed developing a prediction model for CV death, creating an integer risk score based on the final prediction model and estimating future CV death risk according to risk score ranking. RESULTS: Among 59,180 patients with T2D followed for an average of 7.5 years, 15,691 deaths occurred, 6,033 (38%) of which were CV related. The EMR-based prediction model included age, established CV disease and risk factors and glycemic indices (c statistic = 0.819). The 10% highest-risk patients according to prediction model elements had an annual CV death risk of ∼5%; the 25% highest-risk patients had an annual risk of ∼2%. CONCLUSIONS: This study incorporated a prediction modelling approach to quantify the risk continuum for CV death in T2D. Prospective application allows us to rank individuals with T2D according to their CV death risk, and may guide prioritization of novel diabetes therapies with cardioprotective properties.

A risk prediction model for heart failure hospitalization in type 2 diabetes mellitus.

BACKGROUND: Antidiabetic therapies have shown disparate effects on hospitalization for heart failure (HHF) in clinical trials. This study developed a prediction model for HHF in type 2 diabetes mellitus (T2DM) using real world data to identify patients at high risk for HHF. HYPOTHESIS: Type 2 diabetics at high risk for HHF can be identified using information generated during usual clinical care. METHODS: This electronic medical record- (EMR-) based retrospective cohort study included patients with T2DM free of HF receiving healthcare through a single, large integrated healthcare system. The primary endpoint was HHF, defined as a hospital admission with HF as the primary diagnosis. Cox regression identified the strongest predictors of HHF from 80 candidate predictors derived from EMRs. High risk patients were defined according to the 90th percentile of estimated risk. RESULTS: Among 54,452 T2DM patients followed on average 6.6 years, estimated HHF rates at 1, 3, and 5 years were 0.3%, 1.1%, and 2.0%. The final 9-variable model included: age, coronary artery disease, blood urea nitrogen, atrial fibrillation, hemoglobin A1c, blood albumin, systolic blood pressure, chronic kidney disease, and smoking history (c = 0.782). High risk patients identified by the model had a >5% probability of HHF within 5 years. CONCLUSIONS: The proposed model for HHF among T2DM demonstrated strong predictive capacity and may help guide therapeutic decisions.

Gene and MicroRNA Expression Responses to Exercise; Relationship with Insulin Sensitivity.

BACKGROUND: Healthy individuals on the lower end of the insulin sensitivity spectrum also have a reduced gene expression response to exercise for specific genes. The goal of this study was to determine the relationship between insulin sensitivity and exercise-induced gene expression in an unbiased, global manner. METHODS AND FINDINGS: Euglycemic clamps were used to measure insulin sensitivity and muscle biopsies were done at rest and 30 minutes after a single acute exercise bout in 14 healthy participants. Changes in mRNA expression were assessed using microarrays, and miRNA analysis was performed in a subset of 6 of the participants using sequencing techniques. Following exercise, 215 mRNAs were changed at the probe level (Bonferroni-corrected P<0.00000115). Pathway and Gene Ontology analysis showed enrichment in MAP kinase signaling, transcriptional regulation and DNA binding. Changes in several transcription factor mRNAs were correlated with insulin sensitivity, including MYC, r=0.71; SNF1LK, r=0.69; and ATF3, r= 0.61 (5 corrected for false discovery rate). Enrichment in the 5'-UTRs of exercise-responsive genes suggested regulation by common transcription factors, especially EGR1. miRNA species of interest that changed after exercise included miR-378, which is located in an intron of the PPARGC1B gene. CONCLUSIONS: These results indicate that transcription factor gene expression responses to exercise depend highly on insulin sensitivity in healthy people. The overall pattern suggests a coordinated cycle by which exercise and insulin sensitivity regulate gene expression in muscle.

Design of a functional membrane protein by engineering a heme-binding site in glycophorin A.

We have designed a functional model membrane protein by engineering a bis-Histidine heme-binding site into a natural membrane protein, glycophorin A (GpA), structurally characterized by the dimerization of a single transmembrane helix. Out of the 32 residues comprising the transmembrane helix of GpA, five amino acids were mutated; the resulting protein, ME1, has been characterized in dodecyl phosphocholin (DPC) micelles by UV-vis, CD spectroscopy, gel electrophoresis, and analytical ultracentrifugation. ME1 binds heme with sub-micromolar affinity and maintains the highly helical secondary structure and dimeric oligomerization state of GpA. The ME1-Heme complex exhibits a redox potential of -128 +/- 2 mV vs SHE, indicating that the heme resides in a hydrophobic environment and is well shielded from the aqueous phase. Moreover, ME1 catalyzes the hydrogen peroxide dependent oxidation of organic substrates such as TMB (2,2',5,5'-tetramethyl-benzidine). This protein may provide a useful framework to investigate how the protein matrix tunes the cofactor properties in membrane proteins.