The Influence of Reactive Oxygen Species on the Adhesion of Pancreatic Carcinoma Cells to the Peritoneum

Postoperative peritoneal carcinomatosis is a significant clinical problem after “curative” resection of pancreatic carcinoma. Preoperative surgical trauma activates a cascade of peritoneal defense mechanisms responsible for postoperative intra-abdominal tumor recurrence. Reactive oxygen species (ROS) play a pivotal role in this postoperative inflammatory reaction. This study explores the influence of ROS on adhesion of human pancreatic carcinoma cells to human mesothelial cells. Furthermore this study explores the influence of ROS on the presentation of adhesion molecules on Panc-1 and mesothelial cells. ROS were produced using the enzymatic reaction of xanthine with xanthine oxidase (X/XO). A reproducible in vitro assay to study adhesion of human Panc-1 carcinoma tumor cells to a mesothelial cell monolayer of primary human mesothelial cells was used. Mesothelial monolayers were incubated with ROS produced prior to adhesion of the tumor cells. Incubation of the mesothelial cells with X/XO resulted in a significant increase (69.5%) in adhesion of Panc-1 in all patients. SOD/catalase, anti-oxidants, could reduce this increase by 56.7%. ROS significantly influenced the expression of the adhesion molecules ICAM-1, VCAM-1 and CD44h on mesothelial cells, but did not influence adhesion molecule expression on Panc-1. The ROS released during the post-operative inflammatory reaction may play an important role in the adhesion of pancreatic tumor cells to the mesothelium-possibly by influencing adhesion molecule expression on mesothelial cells. Therefore ROS can partly be responsible for the enhanced post-operative intra-abdominal tumor recurrence.Key words: reactive oxygen species, mesothelium, Panc-1     

Creatine kinase isoenzyme activity during and after an ultra-distance (200 km) run

It is commonly assumed that creatine kinase (CK) activity in plasma is related to the state of an inflammatory response at 24-48 h, and also it has shown biphasic patterns after a marathon run. No information is available on CK isoenzymes after an ultra-marathon run. The purpose of the present study is to examine the CK isoenzymes after a 200 km ultra-marathon run and during the subsequent recovery. Blood samples were obtained during registration 1 2 h before the 200-km race and during the race at 100 km, 150 km and at the end of 200 km, as well as after a 24 h period of recovery. Thirty-two male ultra-distance runners participated in the study. Serum CPK showed a marked increase throughout the race and 24 h recovery period (p < 0.001). Serum CK during the race occurs mostly in the CK-MM isoform and only minutely in the CK-MB isoform and is unchanged in the CK-BB isoform. High-sensitivity C-reactive protein (hs-CRP), oestradiol, AST and ALT increased significantly from the pre-race value at 100 km and a further increase took place by the end of the 200 km run. The results of our study demonstrate a different release pattern of creatine kinase after an ultra-distance (200 km) run compared to the studies of marathon running and intense eccentric exercise, and changes in several biomarkers, indicative of muscle damage during the race, were much more pronounced during the latter half (100–200 km) of the race. However, the increases in plasma concentration of muscle enzymes may reflect not only structural damage, but also their rate of clearance.     

Strategies providing success in a variable habitat: I. Relationships of environmental factors and dominance of Cladophora glomerata

Dominance of macrophytes and their response to environmental factors were studied in the river Ilm, Thuringia/ Germany with special reference to Cladophora glomerata (L.) Kütz. Macroalgae showed a growth peak in spring with C. glomerata, Ulothrix zonata Kütz., Lemanea fluviatilis (L.) C. Agardh and Audouinella sp. being the dominant species. Shortly after this peak, a rapid decline of macrophyte substrate coverage was observed. Only C. glomerata revealed a second growth peak in late summer/early autumn. Frequent disturbances of the macrophyte assemblage by floods resulted repeatedly in an almost complete wash out of benthic organisms. After summer floods C. glomerata was the species that recolonized the substrate. At high‐light sites, faster recovery of C. glomerata was observed as compared to low‐light sites. This is discussed in relation to the life cycle of C. glomerata. Among the physical and chemical parameters that were analysed, irradiance, current velocity, pH, soluble reactive phosphorus and ammonia‐nitrogen accounted for most of the observed patterns of dominance of C. glomerata.     

A MademoiseLLE domain binding platform links the key RNA transporter to endosomes

Spatiotemporal expression can be achieved by transport and translation of mRNAs at defined subcellular sites. An emerging mechanism mediating mRNA trafficking is microtubule-dependent co-transport on shuttling endosomes. Although progress has been made in identifying various components of the endosomal mRNA transport machinery, a mechanistic understanding of how these RNA-binding proteins are connected to endosomes is still lacking. Here, we demonstrate that a flexible MademoiseLLE (MLLE) domain platform within RNA-binding protein Rrm4 of Ustilago maydis is crucial for endosomal attachment. Our structure/function analysis uncovered three MLLE domains at the C-terminus of Rrm4 with a functionally defined hierarchy. MLLE3 recognises two PAM2-like sequences of the adaptor protein Upa1 and is essential for endosomal shuttling of Rrm4. MLLE1 and MLLE2 are most likely accessory domains exhibiting a variable binding mode for interaction with currently unknown partners. Thus, endosomal attachment of the mRNA transporter is orchestrated by a sophisticated MLLE domain binding platform.     

A Retroelement Modifies Pre-mRNA Splicing: THE MURINE Glrbspa ALLELE IS A SPLICING SIGNAL POLYMORPHISM AMPLIFIED BY LONG INTERSPERSED NUCLEAR ELEMENT INSERTION

The glycine receptor-deficient mutant mouse spastic carries a full-length long interspersed nuclear element (LINE1) retrotransposon in intron 6 of the glycine receptor β subunit gene, Glrb(spa). The mutation arose in the C57BL/6J strain and is associated with skipping of exon 6 or a combination of the exons 5 and 6, thus resulting in a translational frameshift within the coding regions of the GlyR β subunit. The effect of the Glrb(spa) LINE1 insertion on pre-mRNA splicing was studied using a minigene approach. Sequence comparison as well as motif prediction and mutational analysis revealed that in addition to the LINE1 insertion the inactivation of an exonic splicing enhancer (ESE) within exon 6 is required for skipping of exon 6. Reconstitution of the ESE by substitution of a single residue was sufficient to prevent exon skipping. In addition to the ESE, two regions within the 5' and 3' UTR of the LINE1 were shown to be critical determinants for exon skipping, indicating that LINE1 acts as efficient modifier of subtle endogenous splicing phenotypes. Thus, the spastic allele of the murine glycine receptor β subunit gene is a two-hit mutation, where the hypomorphic alteration in an ESE is amplified by the insertion of a LINE1 element in the adjacent intron. Conversely, the LINE1 effect on splicing may be modulated by individual polymorphisms, depending on the insertional environment within the host genome.     

A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation

Background

Efficient, robust, and accurate genotype imputation algorithms make large-scale application of genomic selection cost effective. An algorithm that imputes alleles or allele probabilities for all animals in the pedigree and for all genotyped single nucleotide polymorphisms (SNP) provides a framework to combine all pedigree, genomic, and phenotypic information into a single-stage genomic evaluation.

Methods

An algorithm was developed for imputation of genotypes in pedigreed populations that allows imputation for completely ungenotyped animals and for low-density genotyped animals, accommodates a wide variety of pedigree structures for genotyped animals, imputes unmapped SNP, and works for large datasets. The method involves simple phasing rules, long-range phasing and haplotype library imputation and segregation analysis.

Results

Imputation accuracy was high and computational cost was feasible for datasets with pedigrees of up to 25 000 animals. The resulting single-stage genomic evaluation increased the accuracy of estimated genomic breeding values compared to a scenario in which phenotypes on relatives that were not genotyped were ignored.

Conclusions

The developed imputation algorithm and software and the resulting single-stage genomic evaluation method provide powerful new ways to exploit imputation and to obtain more accurate genetic evaluations.     

The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes

Background

The theory of genomic selection is based on the prediction of the effects of genetic markers in linkage disequilibrium with quantitative trait loci. However, genomic selection also relies on relationships between individuals to accurately predict genetic value. This study aimed to examine the importance of information on relatives versus that of unrelated or more distantly related individuals on the estimation of genomic breeding values.

Methods

Simulated and real data were used to examine the effects of various degrees of relationship on the accuracy of genomic selection. Genomic Best Linear Unbiased Prediction (gBLUP) was compared to two pedigree based BLUP methods, one with a shallow one generation pedigree and the other with a deep ten generation pedigree. The accuracy of estimated breeding values for different groups of selection candidates that had varying degrees of relationships to a reference data set of 1750 animals was investigated.

Results

The gBLUP method predicted breeding values more accurately than BLUP. The most accurate breeding values were estimated using gBLUP for closely related animals. Similarly, the pedigree based BLUP methods were also accurate for closely related animals, however when the pedigree based BLUP methods were used to predict unrelated animals, the accuracy was close to zero. In contrast, gBLUP breeding values, for animals that had no pedigree relationship with animals in the reference data set, allowed substantial accuracy.

Conclusions

An animal''s relationship to the reference data set is an important factor for the accuracy of genomic predictions. Animals that share a close relationship to the reference data set had the highest accuracy from genomic predictions. However a baseline accuracy that is driven by the reference data set size and the overall population effective population size enables gBLUP to estimate a breeding value for unrelated animals within a population (breed), using information previously ignored by pedigree based BLUP methods.     

Accuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validation

Background

Genomic predictions can be applied early in life without impacting selection candidates. This is especially useful for meat quality traits in sheep. Carcass and novel meat quality traits were predicted in a multi-breed sheep population that included Merino, Border Leicester, Polled Dorset and White Suffolk sheep and their crosses.

Methods

Prediction of breeding values by best linear unbiased prediction (BLUP) based on pedigree information was compared to prediction based on genomic BLUP (GBLUP) and a Bayesian prediction method (BayesR). Cross-validation of predictions across sire families was used to evaluate the accuracy of predictions based on the correlation of predicted and observed values and the regression of observed on predicted values was used to evaluate bias of methods. Accuracies and regression coefficients were calculated using either phenotypes or adjusted phenotypes as observed variables.

Results and conclusions

Genomic methods increased the accuracy of predicted breeding values to on average 0.2 across traits (range 0.07 to 0.31), compared to an average accuracy of 0.09 for pedigree-based BLUP. However, for some traits with smaller reference population size, there was no increase in accuracy or it was small. No clear differences in accuracy were observed between GBLUP and BayesR. The regression of phenotypes on breeding values was close to 1 for all methods, indicating little bias, except for GBLUP and adjusted phenotypes (regression = 0.78). Accuracies calculated with adjusted (for fixed effects) phenotypes were less variable than accuracies based on unadjusted phenotypes, indicating that fixed effects influence the latter. Increasing the reference population size increased accuracy, indicating that adding more records will be beneficial. For the Merino, Polled Dorset and White Suffolk breeds, accuracies were greater than for the Border Leicester breed due to the smaller sample size and limited across-breed prediction. BayesR detected only a few large marker effects but one region on chromosome 6 was associated with large effects for several traits. Cross-validation produced very similar variability of accuracy and regression coefficients for BLUP, GBLUP and BayesR, showing that this variability is not a property of genomic methods alone. Our results show that genomic selection for novel difficult-to-measure traits is a feasible strategy to achieve increased genetic gain.