Maintenance of the cellobiose utilization genes of Escherichia coli in a cryptic state

The genes for cellobiose utilization are normally cryptic in Escherichia coli. The cellobiose system was used as a model to understand the process by which silent genes are maintained in microbial populations. Previously reported was (1) the isolation of a mutant strain that expresses the cellobiose-utilization (Cel) genes and (2) that expression of those genes allows utilization of three beta- glucoside sugars: cellobiose, arbutin, and salicin. The Cel gene cluster has now been cloned from that mutant strain. In the course of locating the Cel genes within the cloned DNA segment, it was discovered that inactivation of the Cel-encoded hydrolase rendered the host strain sensitive to all three beta-glucosides as potent inhibitors. This sensitivity arises from the accumulation of the phosphorylated beta- glucosides. Because even the fully active genes conferred some degree of beta-glucoside sensitivity, the effects of cellobiose on a series of five Cel+ mutants of independent origin were investigated. Although each of those strains utilizes cellobiose as a sole carbon and energy source, cellobiose also acts as a potent inhibitor that reduces the growth rate on glycerol 2.5-16.5-fold. On the other hand, wild-type strains that cannot utilize cellobiose are not inhibited. The observation that the same compound can serve either as a nutrient or as an inhibitor suggests that, under most conditions in which cellobiose will be present together with other resources, there is a strong selective advantage to having the cryptic (Cel0) allele. In those environments in which cellobiose is the sole, or the best, resource, mutants that express the genes (Cel+) will have a strong selective advantage. It is suggested that temporal alternation between these two conditions is a major factor in the maintenance of these genes in E. coli populations. This alternation of environments and fitnesses was predicted by the model for cryptic-gene maintenance that was previously published.      

The Kinetochore-Microtubule Coupling Machinery Is Repurposed in Sensory Nervous System Morphogenesis

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Type 2 diabetes TCF7L2 risk genotypes alter birth weight: a study of 24,053 individuals

The role of genes in normal birth-weight variation is poorly understood, and it has been suggested that the genetic component of fetal growth is small. Type 2 diabetes genes may influence birth weight through maternal genotype, by increasing maternal glycemia in pregnancy, or through fetal genotype, by altering fetal insulin secretion. We aimed to assess the role of the recently described type 2 diabetes gene TCF7L2 in birth weight. We genotyped the polymorphism rs7903146 in 15,709 individuals whose birth weight was available from six studies and in 8,344 mothers from three studies. Each fetal copy of the predisposing allele was associated with an 18-g (95% confidence interval [CI] 7-29 g) increase in birth weight (P=.001) and each maternal copy with a 30-g (95% CI 15-45 g) increase in offspring birth weight (P=2.8x10-5). Stratification by fetal genotype suggested that the association was driven by maternal genotype (31-g [95% CI 9-48 g] increase per allele; corrected P=.003). Analysis of diabetes-related traits in 10,314 nondiabetic individuals suggested the most likely mechanism is that the risk allele reduces maternal insulin secretion (disposition index reduced by ~0.15 standard deviation; P=1x10-4), which results in increased maternal glycemia in pregnancy and hence increased offspring birth weight. We combined information with the other common variant known to alter fetal growth, the -30G-->A polymorphism of glucokinase (rs1799884). The 4% of offspring born to mothers carrying three or four risk alleles were 119 g (95% CI 62-172 g) heavier than were the 32% born to mothers with none (for overall trend, P=2x10-7), comparable to the impact of maternal smoking during pregnancy. In conclusion, we have identified the first type 2 diabetes-susceptibility allele to be reproducibly associated with birth weight. Common gene variants can substantially influence normal birth-weight variation.     

Fracture prevention in COPD patients; a clinical 5-step approach

Although osteoporosis and its related fractures are common in patients with COPD, patients at high risk of fracture are poorly identified, and consequently, undertreated. Since there are no fracture prevention guidelines available that focus on COPD patients, we developed a clinical approach to improve the identification and treatment of COPD patients at high risk of fracture. We organised a round-table discussion with 8 clinical experts in the field of COPD and fracture prevention in the Netherlands in December 2013. The clinical experts presented a review of the literature on COPD, osteoporosis and fracture prevention. Based on the Dutch fracture prevention guideline, they developed a 5-step clinical approach for fracture prevention in COPD. Thereby, they took into account both classical risk factors for fracture (low body mass index, older age, personal and family history of fracture, immobility, smoking, alcohol intake, use of glucocorticoids and increased fall risk) and COPD-specific risk factors for fracture (severe airflow obstruction, pulmonary exacerbations and oxygen therapy). Severe COPD (defined as postbronchodilator FEV₁ < 50% predicted) was added as COPD-specific risk factor to the list of classical risk factors for fracture. The 5-step clinical approach starts with case finding using clinical risk factors, followed by risk evaluation (dual energy X-ray absorptiometry and imaging of the spine), differential diagnosis, treatment and follow-up. This systematic clinical approach, which is evidence-based and easy-to-use in daily practice by pulmonologists, should contribute to optimise fracture prevention in COPD patients at high risk of fracture.     

Quantifying the improvement of surrogate indices of hepatic insulin resistance using complex measurement techniques

We evaluated the ability of simple and complex surrogate-indices to identify individuals from an overweight/obese cohort with hepatic insulin-resistance (HEP-IR). Five indices, one previously defined and four newly generated through step-wise linear regression, were created against a single-cohort sample of 77 extensively characterised participants with the metabolic syndrome (age 55.6 ± 1.0 years, BMI 31.5 ± 0.4 kg/m(2); 30 males). HEP-IR was defined by measuring endogenous-glucose-production (EGP) with [6-6(2)H(2)] glucose during fasting and euglycemic-hyperinsulinemic clamps and expressed as EGP*fasting plasma insulin. Complex measures were incorporated into the model, including various non-standard biomarkers and the measurement of body-fat distribution and liver-fat, to further improve the predictive capability of the index. Validation was performed against a data set of the same subjects after an isoenergetic dietary intervention (4 arms, diets varying in protein and fiber content versus control). All five indices produced comparable prediction of HEP-IR, explaining 39-56% of the variance, depending on regression variable combination. The validation of the regression equations showed little variation between the different proposed indices (r(2) = 27-32%) on a matched dataset. New complex indices encompassing advanced measurement techniques offered an improved correlation (r = 0.75, P<0.001). However, when validated against the alternative dataset all indices performed comparably with the standard homeostasis model assessment for insulin resistance (HOMA-IR) (r = 0.54, P<0.001). Thus, simple estimates of HEP-IR performed comparable to more complex indices and could be an efficient and cost effective approach in large epidemiological investigations.     

EDTA improves stability of whole blood C-Peptide and insulin to over 24 hours at room temperature

Introduction

C-peptide and insulin measurements in blood provide useful information regarding endogenous insulin secretion. Conflicting evidence on sample stability and handling procedures continue to limit the widespread clinical use of these tests. We assessed the factors that altered the stability of insulin and C-peptide in blood.

Methods

We investigated the impact of preservative type, time to centrifugation, storage conditions and duration of storage on the stability of C-peptide and insulin on three different analytical platforms.

Results

C-peptide was stable for at least 24 hours at room temperature in both centrifuged and whole blood collected in K⁺-EDTA and serum gel tubes, with the exception of whole blood serum gel, which decreased to 78% of baseline at 24 hours, (p = 0.008). Insulin was stable at room temperature for 24 hours in both centrifuged and whole blood collected in K⁺-EDTA tubes. In contrast insulin levels decreased in serum gel tubes both centrifuged and whole blood (66% of baseline, p = 0.01 and 76% of baseline p = 0.01, by 24 hours respectively). C-peptide and insulin remained stable after 6 freeze-thaw cycles.

Conclusions

The stability of C-peptide and insulin in whole blood K⁺-EDTA tubes negates the need to conform to strict sample handling procedures for these assays, greatly increasing their clinical utility.