Growth hormone response to a growth hormone-releasing hormone stimulation test in a population-based study following cranial irradiation of childhood brain tumors

Children with brain tumors are at high risk of developing growth hormone deficiency (GHD) after cranial irradiation (CI) if the hypothalamus/pituitary (HP) axis falls within the fields of irradiation. The biological effective dose (BED) of irradiation to the HP region was determined, since BED gives a means of expressing the biological effect of various irradiation treatment schedules in a uniform way. Hypothalamic versus pituitary damage as cause of GHD was distinguished in 62 patients by comparing the growth hormone (GH) peak response to an insulin tolerance test (ITT)/arginine stimulation test and the GH response to a growth hormone-releasing hormone (GHRH) stimulation test. Peak GH response to a GHRH test was significantly higher (median 7.3 mU/l; range: 0.5--79.0 mU/l) than that of an ITT/arginine test (median 4.7 mU/l; range: 0.01--75.0 mU/l) (p = 0.017). Peak GH after a GHRH test was significantly inversely correlated to follow-up time (r(s) = -0.46, p < 0.0001) and to BED (R(s) = -0.28, p = 0.03), and both were found to be of significance in a multivariante regression analysis. We speculate that a significant number of patients developed hypothalamic radiation-induced damage to the GHRH secreting neurons, and secondary to this the pituitary gland developed decreased responsiveness to GHRH following CI in childhood.     

Octaplex PCR and fluorescence-based capillary electrophoresis for identification of human diarrheagenic Escherichia coli and Shigella spp

A multiplex PCR assay, amplifying seven specific virulence genes and one internal control gene in a single reaction, was developed to identify the five main pathotypes of diarrheagenic Escherichia coli and Shigella spp. The virulence genes selected for each category were Stx1, Stx2, and eaeA for enterohemorrhagic E. coli (EHEC), eaeA for enteropathogenic E. coli (EPEC), STIb and LTI for enterotoxigenic E. coli (ETEC), ipaH for enteroinvasive E. coli (EIEC) and Shigella spp., and aggR for enteroaggregative E. coli (EAEC). Each forward primer was labelled with a fluorochrome and the PCR products were separated by multicolour capillary electrophoresis on an ABI PRISM310 Genetic Analyzer (Applied Biosystems). If present, several gene variants of each virulence gene were identified. The internal control gene rrs, encoding 16S rRNA, was amplified in all 110 clinical strains analyzed. Virulence genes were demonstrated in 103 (94%) of these strains. In the majority of the cases (98/103, 95%), classification obtained by the novel multiplex PCR assay was in agreement with that previously determined by phenotypic assays combined with other molecular genetic approaches. Numerous multiplex PCR assays have been published, but only a few of them detect all five E. coli pathotypes within a single reaction, and none of them has used multicolour capillary electrophoresis to separate the PCR products. The octaplex PCR assay followed by capillary electrophoresis presented in the present paper provides a simple, reliable, and rapid procedure that in a single reaction identifies the five main pathotypes of E. coli, and Shigella spp. This assay will replace the previous molecular genetic methods used in our laboratory and work as an important supplement to the more time-consuming phenotypic assays.     

An alteration in ATG16L1 stability in Crohn disease

Individuals who harbor a common coding polymorphism (Thr300Ala) within a structurally unclassified region of ATG16L1 are at increased risk for the development of Crohn disease. Recently, we reported on the generation and characterization of knockin mice carrying the ATG16L1 T300A variant. We demonstrate that multiple cell types from T300A knock-in mice exhibit reduced selective autophagy, and we mechanistically link this phenotype with an increased susceptibility of ATG16L1 T300A to CASP3- and CASP7-mediated cleavage. These findings demonstrate how a single polymorphism can result in cell type- and pathway-specific disruptions of selective autophagy and alterations in the inflammatory milieu that can contribute to disease.     

Engineering of Phytase for Improved Activity at Low pH

For industrial applications in animal feed, a phytase of interest must be optimally active in the pH range prevalent in the digestive tract. Therefore, the present investigation describes approaches to rationally engineer the pH activity profiles of Aspergillus fumigatus and consensus phytases. Decreasing the negative surface charge of the A. fumigatus Q27L phytase mutant by glycinamidylation of the surface carboxy groups (of Asp and Glu residues) lowered the pH optimum by ca. 0.5 unit but also resulted in 70 to 75% inactivation of the enzyme. Alternatively, detailed inspection of amino acid sequence alignments and of experimentally determined or homology modeled three-dimensional structures led to the identification of active-site amino acids that were considered to correlate with the activity maxima at low pH of A. niger NRRL 3135 phytase, A. niger pH 2.5 acid phosphatase, and Peniophora lycii phytase. Site-directed mutagenesis confirmed that, in A. fumigatus wild-type phytase, replacement of Gly-277 and Tyr-282 with the corresponding residues of A. niger phytase (Lys and His, respectively) gives rise to a second pH optimum at 2.8 to 3.4. In addition, the K68A single mutation (in both A. fumigatus and consensus phytase backbones), as well as the S140Y D141G double mutation (in A. fumigatus phytase backbones), decreased the pH optima with phytic acid as substrate by 0.5 to 1.0 unit, with either no change or even a slight increase in maximum specific activity. These findings significantly extend our tools for rationally designing an optimal phytase for a given purpose.     

Large-Scale metabolomics: Predicting biological age using 10,133 routine untargeted LC–MS measurements

Untargeted metabolomics is the study of all detectable small molecules, and in geroscience, metabolomics has shown great potential to describe the biological age—a complex trait impacted by many factors. Unfortunately, the sample sizes are often insufficient to achieve sufficient power and minimize potential biases caused by, for example, demographic factors. In this study, we present the analysis of biological age in ~10,000 toxicologic routine blood measurements. The untargeted screening samples obtained from ultra-high pressure liquid chromatography-quadruple time of flight mass spectrometry (UHPLC- QTOF) cover + 300 batches and + 30 months, lack pooled quality controls, lack controlled sample collection, and has previously only been used in small-scale studies. To overcome experimental effects, we developed and tested a custom neural network model and compared it with existing prediction methods. Overall, the neural network was able to predict the chronological age with an rmse of 5.88 years (r² = 0.63) improving upon the 6.15 years achieved by existing normalization methods. We used the feature importance algorithm, Shapley Additive exPlanations (SHAP), to identify compounds related to the biological age. Most importantly, the model returned known aging markers such as kynurenine, indole-3-aldehyde, and acylcarnitines along with a potential novel aging marker, cyclo (leu-pro). Our results validate the association of tryptophan and acylcarnitine metabolism to aging in a highly uncontrolled large-s cale sample. Also, we have shown that by using robust computational methods it is possible to deploy large LC-MS datasets for metabolomics studies to reduce the risk of bias and empower aging studies.     

An approximate multitrait model for genetic evaluation in dairy cattle with a robust estimation of genetic trends (Open Access publication)

In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.