Sphingosine-1-Phosphate Lyase Deficient Cells as a Tool to Study Protein Lipid Interactions

Cell membranes contain hundreds to thousands of individual lipid species that are of structural importance but also specifically interact with proteins. Due to their highly controlled synthesis and role in signaling events sphingolipids are an intensely studied class of lipids. In order to investigate their metabolism and to study proteins interacting with sphingolipids, metabolic labeling based on photoactivatable sphingoid bases is the most straightforward approach. In order to monitor protein-lipid-crosslink products, sphingosine derivatives containing a reporter moiety, such as a radiolabel or a clickable group, are used. In normal cells, degradation of sphingoid bases via action of the checkpoint enzyme sphingosine-1-phosphate lyase occurs at position C2-C3 of the sphingoid base and channels the resulting hexadecenal into the glycerolipid biosynthesis pathway. In case the functionalized sphingosine looses the reporter moiety during its degradation, specificity towards sphingolipid labeling is maintained. In case degradation of a sphingosine derivative does not remove either the photoactivatable or reporter group from the resulting hexadecenal, specificity towards sphingolipid labeling can be achieved by blocking sphingosine-1-phosphate lyase activity and thus preventing sphingosine derivatives to be channeled into the sphingolipid-to-glycerolipid metabolic pathway. Here we report an approach using clustered, regularly interspaced, short palindromic repeats (CRISPR)-associated nuclease Cas9 to create a sphingosine-1-phosphate lyase (SGPL1) HeLa knockout cell line to disrupt the sphingolipid-to-glycerolipid metabolic pathway. We found that the lipid and protein compositions as well as sphingolipid metabolism of SGPL1 knock-out HeLa cells only show little adaptations, which validates these cells as model systems to study transient protein-sphingolipid interactions.     

All-Cause and Cause-Specific Mortality among Users of Basal Insulins NPH,Detemir, and Glargine

Background

Insulin therapy in type 2 diabetes may increase mortality and cancer incidence, but the impact of different types of basal insulins on these endpoints is unclear. Compared to the traditional NPH insulin, the newer, longer-acting insulin analogues detemir and glargine have shown benefits in randomized controlled trials. Whether these advantages translate into lower mortality among users in real life is unknown.

Objective

To estimate the differences in all-cause and cause-specific mortality rates between new users of basal insulins in a population-based study in Finland.

Methods

23 751 individuals aged ≥40 with type 2 diabetes, who initiated basal insulin therapy in 2006–2009 were identified from national registers, with comprehensive data for mortality, causes of death, and background variables. Propensity score matching was performed on characteristics. Follow-up time was up to 4 years (median 1.7 years).

Results

2078 deaths incurred. With NPH as reference, the adjusted HRs for all-cause mortality were 0.39 (95% CI, 0.30–0.50) for detemir, and 0.55 (95% CI, 0.44–0.69) for glargine. As compared to glargine, the HR was 0.71 (95% CI, 0.54–0.93) among detemir users. Compared to NPH, the mortality risk for both cardiovascular causes as well as cancer were also significantly lower for glargine, and especially for detemir in adjusted analysis. Furthermore, the results were robust in various sensitivity analyses.

Conclusion

In real clinical practice, mortality was substantially higher among users of NPH insulin as compared to insulins detemir or glargine. Considering the large number of patients who require insulin therapy, this difference in risk may have major clinical and public health implications. Due to limitations of the observational study design, further investigation using an interventional study design is warranted.     

A Novel Glutamyl (Aspartyl)-Specific Aminopeptidase A from Lactobacillus delbrueckii with Promising Properties for Application

Lactic acid bacteria (LAB) are auxotrophic for a number of amino acids. Thus, LAB have one of the strongest proteolytic systems to acquit their amino acid requirements. One of the intracellular exopeptidases present in LAB is the glutamyl (aspartyl) specific aminopeptidase (PepA; EC 3.4.11.7). Most of the PepA enzymes characterized yet, belonged to Lactococcus lactis sp., but no PepA from a Lactobacillus sp. has been characterized so far. In this study, we cloned a putative pepA gene from Lb. delbrueckii ssp. lactis DSM 20072 and characterized it after purification. For comparison, we also cloned, purified and characterized PepA from Lc. lactis ssp. lactis DSM 20481. Due to the low homology between both enzymes (30%), differences between the biochemical characteristics were very likely. This was confirmed, for example, by the more acidic optimum pH value of 6.0 for Lb-PepA compared to pH 8.0 for Lc-PepA. In addition, although the optimum temperature is quite similar for both enzymes (Lb-PepA: 60°C; Lc-PepA: 65°C), the temperature stability after three days, 20°C below the optimum temperature, was higher for Lb-PepA (60% residual activity) than for Lc-PepA (2% residual activity). EDTA inhibited both enzymes and the strongest activation was found for CoCl₂, indicating that both enzymes are metallopeptidases. In contrast to Lc-PepA, disulfide bond-reducing agents such as dithiothreitol did not inhibit Lb-PepA. Finally, Lb-PepA was not product-inhibited by L-Glu, whereas Lc-PepA showed an inhibition.     

MobiSeq: De novo SNP discovery in model and non‐model species through sequencing the flanking region of transposable elements

In recent years, the availability of reduced representation library (RRL) methods has catalysed an expansion of genome‐scale studies to characterize both model and non‐model organisms. Most of these methods rely on the use of restriction enzymes to obtain DNA sequences at a genome‐wide level. These approaches have been widely used to sequence thousands of markers across individuals for many organisms at a reasonable cost, revolutionizing the field of population genomics. However, there are still some limitations associated with these methods, in particular the high molecular weight DNA required as starting material, the reduced number of common loci among investigated samples, and the short length of the sequenced site‐associated DNA. Here, we present MobiSeq, a RRL protocol exploiting simple laboratory techniques, that generates genomic data based on PCR targeted enrichment of transposable elements and the sequencing of the associated flanking region. We validate its performance across 103 DNA extracts derived from three mammalian species: grey wolf (Canis lupus), red deer complex (Cervus sp.) and brown rat (Rattus norvegicus). MobiSeq enables the sequencing of hundreds of thousands loci across the genome and performs SNP discovery with relatively low rates of clonality. Given the ease and flexibility of MobiSeq protocol, the method has the potential to be implemented for marker discovery and population genomics across a wide range of organisms—enabling the exploration of diverse evolutionary and conservation questions.     

Demographic history has influenced nucleotide diversity in European Pinus sylvestris populations

To infer the role of natural selection in shaping standing genetic diversity, it is necessary to assess the genomewide impact of demographic history on nucleotide diversity. In this study we analyzed sequence diversity of 16 nuclear loci in eight Pinus sylvestris populations. Populations were divided into four geographical groups on the basis of their current location and the geographical history of the region: northern Europe, central Europe, Spain, and Turkey. There were no among-group differences in the level of silent nucleotide diversity, which was approximately 0.005/bp in all groups. There was some evidence that linkage disequilibrium extended further in northern Europe than in central Europe: the estimates of the population recombination rate parameter, rho, were 0.0064 and 0.0294, respectively. The summary statistics of nucleotide diversity in central and northern European populations were compatible with an ancient bottleneck rather than the standard neutral model.     

Genome wide association (GWA) study for early onset extreme obesity supports the role of fat mass and obesity associated gene (FTO) variants

Background

Obesity is a major health problem. Although heritability is substantial, genetic mechanisms predisposing to obesity are not very well understood. We have performed a genome wide association study (GWA) for early onset (extreme) obesity.

Methodology/Principal Findings

a) GWA (Genome-Wide Human SNP Array 5.0 comprising 440,794 single nucleotide polymorphisms) for early onset extreme obesity based on 487 extremely obese young German individuals and 442 healthy lean German controls; b) confirmatory analyses on 644 independent families with at least one obese offspring and both parents. We aimed to identify and subsequently confirm the 15 SNPs (minor allele frequency ≥10%) with the lowest p-values of the GWA by four genetic models: additive, recessive, dominant and allelic. Six single nucleotide polymorphisms (SNPs) in FTO (fat mass and obesity associated gene) within one linkage disequilibrium (LD) block including the GWA SNP rendering the lowest p-value (rs1121980; log-additive model: nominal p = 1.13×10⁻⁷, corrected p = 0.0494; odds ratio (OR)_CT 1.67, 95% confidence interval (CI) 1.22–2.27; OR_TT 2.76, 95% CI 1.88–4.03) belonged to the 15 SNPs showing the strongest evidence for association with obesity. For confirmation we genotyped 11 of these in the 644 independent families (of the six FTO SNPs we chose only two representing the LD bock). For both FTO SNPs the initial association was confirmed (both Bonferroni corrected p<0.01). However, none of the nine non-FTO SNPs revealed significant transmission disequilibrium.

Conclusions/Significance

Our GWA for extreme early onset obesity substantiates that variation in FTO strongly contributes to early onset obesity. This is a further proof of concept for GWA to detect genes relevant for highly complex phenotypes. We concurrently show that nine additional SNPs with initially low p-values in the GWA were not confirmed in our family study, thus suggesting that of the best 15 SNPs in the GWA only the FTO SNPs represent true positive findings.