Regulatory control and the costs and benefits of biochemical noise

Experiments in recent years have vividly demonstrated that gene expression can be highly stochastic. How protein concentration fluctuations affect the growth rate of a population of cells, is, however, a wide open question. We present a mathematical model that makes it possible to quantify the effect of protein concentration fluctuations on the growth rate of a population of genetically identical cells. The model predicts that the population's growth rate depends on how the growth rate of a single cell varies with protein concentration, the variance of the protein concentration fluctuations, and the correlation time of these fluctuations. The model also predicts that when the average concentration of a protein is close to the value that maximizes the growth rate, fluctuations in its concentration always reduce the growth rate. However, when the average protein concentration deviates sufficiently from the optimal level, fluctuations can enhance the growth rate of the population, even when the growth rate of a cell depends linearly on the protein concentration. The model also shows that the ensemble or population average of a quantity, such as the average protein expression level or its variance, is in general not equal to its time average as obtained from tracing a single cell and its descendants. We apply our model to perform a cost-benefit analysis of gene regulatory control. Our analysis predicts that the optimal expression level of a gene regulatory protein is determined by the trade-off between the cost of synthesizing the regulatory protein and the benefit of minimizing the fluctuations in the expression of its target gene. We discuss possible experiments that could test our predictions.Comment: Revised manuscript;35 pages, 4 figures, REVTeX4; to appear in PLoS Computational Biolog

A randomized controlled study of finerenone vs. eplerenone in patients with worsening chronic heart failure and diabetes mellitus and/or chronic kidney disease

AIMS: To evaluate oral doses of the non-steroidal mineralocorticoid receptor antagonist finerenone given for 90 days in patients with worsening heart failure and reduced ejection fraction and chronic kidney disease and/or diabetes mellitus. METHODS AND RESULTS: Miner Alocorticoid Receptor antagonist Tolerability Study-Heart Failure (ARTS-HF) was a randomized, double-blind, phase 2b multicentre study (ClinicalTrials.gov: NCT01807221). Of 1286 screened patients, 1066 were randomized. Patients received oral, once-daily finerenone (2.5, 5, 7.5, 10, or 15 mg, uptitrated to 5, 10, 15, 20, or 20 mg, respectively, on Day 30) or eplerenone (25 mg every other day, increased to 25 mg once daily on Day 30, and to 50 mg once daily on Day 60) for 90 days. The primary endpoint was the percentage of individuals with a decrease of >30% in plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) from baseline to Day 90. A key exploratory endpoint was a composite clinical endpoint of death from any cause, cardiovascular hospitalizations, or emergency presentation for worsening HF until Day 90. Mean age ranged from 69.2 to 72.5 years in different treatment groups (standard deviation 9.7–10.6 years). Decreases in NT-proBNP of >30% from baseline occurred in 37.2% of patients in the eplerenone group and 30.9, 32.5, 37.3, 38.8, and 34.2% in the 2.5→5, 5→10, 7.5→15, 10→20, and 15→20 mg finerenone groups, respectively (P = 0.42–0.88). Except for the 2.5→5 mg finerenone group, the composite clinical endpoint occurred numerically less frequently in finerenone-treated patients compared with eplerenone; this difference reached nominal statistical significance in the 10→20 mg group (hazard ratio 0.56, 95% confidence interval, CI, 0.35; 0.90; nominal P = 0.02), despite the fact that this phase 2 study was not designed to detect statistical significant differences. A potassium level increase to ≥5.6 mmol/L at any time point occurred in 4.3% of patients, with a balanced distribution among all treatment groups. CONCLUSION: Finerenone was well tolerated and induced a 30% or greater decrease in NT-proBNP levels in a similar proportion of patients to eplerenone. The finding of reduced clinical events in the finerenone 10→20 mg group should be further explored in a large outcomes trial

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Specificities of three tight-binding Lac repressors.

Tight binding mutants of Lac repressor exhibit complex repression phenomena. In this work, in vivo Lac operator binding of three such mutants of E. coli Lac repressor (X86: ser 61-leu, l12: pro 3-tyr and the double mutant l12X86: pro 3-tyr, ser 61-leu) was analyzed. Repression of beta-galactosidase synthesis controlled by ideal lac operator and its 27 symmetric operator variants containing each possible base-pair at each single half-operator position in the presence of the tight-binding Lac repressor mutants was determined. The average increase of repression with all operator variants was about 3 fold with the X86 mutant. It was about 4 fold with the l12 mutant and about 2 fold with the double mutant l12X86 as compared to wildtype Lac repressor. The X86 mutant showed the same increase of affinity to all operator variants, whereas the l12 and l12X86 mutants exhibited lower repression with some variants than with most others. These results suggest that the X86 mutant has gained no additional specificity. In contrast the l12 mutant and the l12X86 mutant exhibit a relaxed specificity for certain base pairs in positions 1 and 3 of lac operator. This suggests that the extreme N-terminus of Lac repressor may interact with the inner base-pairs in the minor groove

Steroidal and novel non-steroidal mineralocorticoid receptor antagonists in heart failure and cardiorenal diseases: Comparison at bench and bedside

Characterization of mice with cell-specific deletion or overexpression of the mineralocorticoid receptor (MR) shed a new light on its role in health and disease. Pathophysiological MR activation contributes to a plethora of deleterious molecular mechanisms in the development of cardiorenal diseases like chronic kidney disease (CKD) and heart failure (HF). Accordingly, the available steroidal MR antagonists (MRAs) spironolactone (first generation MRA) and eplerenone (second generation MRA) have been shown to be effective in reducing cardiovascular (CV) mortality and morbidity in patients with chronic HF and a reduced left ventricular ejection fraction (HFrEF). However, they remain underutilized, in large part owing to the risk inducing severe adverse events including hyperkalemia and worsening of kidney function, particularly when given on top of inhibitors of the renin angiotensin system (RAS) to patients with concomitant kidney dysfunction. Novel, potent, and selective non-steroidal MRAs (third generation) were identified in drug discovery campaigns and a few entered clinical development recently. One of these is finerenone with different physicochemical, pharmacokinetics, and pharmacological properties in comparison with the steroidal MRAs. Available data from five clinical phase II trials with finerenone in more than 2,000 patients with HF and additional CKD and/or diabetes as well as in patients with diabetic kidney disease demonstrated that neither hyperkalemia nor reductions in kidney function were limiting factors to its use. Moreover, finerenone demonstrated a nominally improved outcome compared to eplerenone in a phase IIb trial with 1,066 patients with HFrEF and concomitant type 2 diabetes mellitus (T2DM) and/or CKD. © 2016, Springer International Publishing Switzerland

Predicting gene expression level in E. coli from mRNA sequence information

The accurate characterization of the translational mechanism is crucial for enhancing our understanding of the relationship between genotype and phenotype. In particular, predicting the impact of the genetic variants on gene expression will allow to optimize specific pathways and functions for engineering new biological systems. In this context, the development of accurate methods for predicting the translation efficiency and/or protein expression from the nucleotide sequence is a key challenge in computational biology. In this work we present PGExpress, a new regression method for predicting the log2-fold-change of the translation efficiency of an mRNA sequence in E. coli. PGExpress algorithm takes as input 12 features corresponding to the predicted RNA secondary structure and anti-Shine-Dalgarno hybridization free energies. The method was trained on a set of 1,772 sequence variants (WT-High)of 137 essential E. coli genes. For each gene, we considered 13 sequence variants of the first 33 nucleotides encoding for the same amino acids followed by the superfolder GFP. Each gene variant is represented sequence blocks that include the Ribosome Binding Site (RBS), the first 33 nucleotides of the coding region (C33), the remaining part of the coding region (CC), and their combinations. Our gradient-boosting-based tool (PGExpress) was trained using a 10-fold gene-based cross-validation procedure on the WT-High dataset. In this test PGExpress achieved a correlation coefficient of 0.60, with a Root Mean Square Error (RMSE)of 1.3. When the regression task is cast as a classification problem, PGExpress reached an overall accuracy of 0.74 a Matthews correlation coefficient 0.48 and an Area Under the Receiver Operating Characteristic Curve (AUC)of 0.81. In the regression task, PGExpress results in better performance than RBSCalculator in the prediction of the log2-fold-change of the translational efficiency and its variation on the WT-High dataset. Finally, we validated our method by performing in-house experiments on five newly generated mRNA sequence variants. The predictions of the expression level of the new variants are in agreement with our experimental results in E. coli