Cell Elasticity Is Regulated by the Tropomyosin Isoform Composition of the Actin Cytoskeleton

The actin cytoskeleton is the primary polymer system within cells responsible for regulating cellular stiffness. While various actin binding proteins regulate the organization and dynamics of the actin cytoskeleton, the proteins responsible for regulating the mechanical properties of cells are still not fully understood. In the present study, we have addressed the significance of the actin associated protein, tropomyosin (Tpm), in influencing the mechanical properties of cells. Tpms belong to a multi-gene family that form a co-polymer with actin filaments and differentially regulate actin filament stability, function and organization. Tpm isoform expression is highly regulated and together with the ability to sort to specific intracellular sites, result in the generation of distinct Tpm isoform-containing actin filament populations. Nanomechanical measurements conducted with an Atomic Force Microscope using indentation in Peak Force Tapping in indentation/ramping mode, demonstrated that Tpm impacts on cell stiffness and the observed effect occurred in a Tpm isoform-specific manner. Quantitative analysis of the cellular filamentous actin (F-actin) pool conducted both biochemically and with the use of a linear detection algorithm to evaluate actin structures revealed that an altered F-actin pool does not absolutely predict changes in cell stiffness. Inhibition of non-muscle myosin II revealed that intracellular tension generated by myosin II is required for the observed increase in cell stiffness. Lastly, we show that the observed increase in cell stiffness is partially recapitulated in vivo as detected in epididymal fat pads isolated from a Tpm3.1 transgenic mouse line. Together these data are consistent with a role for Tpm in regulating cell stiffness via the generation of specific populations of Tpm isoform-containing actin filaments.     

Preclinical Assessment of Adjunctive tPA and DNase for Peritoneal Dialysis Associated Peritonitis

A major complication of peritoneal dialysis is the development of peritonitis, which is associated with reduced technique and patient survival. The inflammatory response elicited by infection results in a fibrin and debris-rich environment within the peritoneal cavity, which may reduce the effectiveness of antimicrobial agents and predispose to recurrence or relapse of infection. Strategies to enhance responses to antimicrobial agents therefore have the potential to improve patient outcomes. This study presents pre-clinical data describing the compatibility of tPA and DNase in combination with antimicrobial agents used for the treatment of PD peritonitis. tPA and DNase were stable in standard dialysate solution and in the presence of antimicrobial agents, and were safe when given intraperitoneally in a mouse model with no evidence of local or systemic toxicity. Adjunctive tPA and DNase may have a role in the management of patients presenting with PD peritonitis.     

Accuracy of predicting genomic breeding values for carcass merit traits in Angus and Charolais beef cattle

Accuracy of predicting genomic breeding values for carcass merit traits including hot carcass weight, longissimus muscle area (REA), carcass average backfat thickness (AFAT), lean meat yield (LMY) and carcass marbling score (CMAR) was evaluated based on 543 Angus and 400 Charolais steers genotyped on the Illumina BovineSNP50 Beadchip. For the genomic prediction within Angus, the average accuracy was 0.35 with a range from 0.32 (LMY) to 0.37 (CMAR) across different training/validation data‐splitting strategies and statistical methods. The within‐breed genomic prediction for Charolais yielded an average accuracy of 0.36 with a range from 0.24 (REA) to 0.46 (AFAT). The across‐breed prediction had the lowest accuracy, which was on average near zero. When the data from the two breeds were combined to predict the breeding values of either breed, the prediction accuracy averaged 0.35 for Angus with a range from 0.33 (REA) to 0.39 (CMAR) and averaged 0.33 for Charolais with a range from 0.18 (REA) to 0.46 (AFAT). The prediction accuracy was slightly higher on average when the data were split by animal's birth year than when the data were split by sire family. These results demonstrate that the genetic relationship or relatedness of selection candidates with the training population has a great impact on the accuracy of predicting genomic breeding values under the density of the marker panel used in this study.     

Rare species habitat suitability assessment and reliability evaluation of an expert-based model: A case study of the insectivorous plant Pinguicula crystallina Sibth. et Smith subsp. hirtiflora (Ten.) Strid (Lentibulariaceae)

The development of habitat suitability models requires a large amount of data which are rarely available. In this case, researchers need to get information on the ecological features of the studied species, based on the opinion of experts or on the literature, to construct a qualitative model. However, such models cannot be rigorously evaluated, as in most cases absence points are not available. In this paper, we assess the habitat suitability for a vulnerable insectivorous plant, Pinguicula crystallina Sibth. et Smith subsp. hirtiflora (Ten.) Strid (Lentibulariaceae) in the Campania region. Our aim was to develop an expert-based, presence-only model in support of possible conservation actions. Topographic and geological features of this species suggested by the literature were used in our model. Both the Boyce index and field surveys were chosen to evaluate the model's reliability. During field surveys, 31 absence sites and 1 new presence site were identified, and differences between sites with regard to water chemistry and quality were investigated, water being an element in the species habitat. Factors that affect reliability of the model, such as the lack of a large amount of information on the species and the limited spatial resolution of geographical information system data, are discussed.     

DBA/2J Genetic Background Exacerbates Spontaneous Lethal Seizures but Lessens Amyloid Deposition in a Mouse Model of Alzheimer’s Disease

Alzheimer’s disease (AD) is a leading cause of dementia in the elderly and is characterized by amyloid plaques, neurofibrillary tangles (NFTs) and neuronal dysfunction. Early onset AD (EOAD) is commonly caused by mutations in amyloid precursor protein (APP) or genes involved in the processing of APP including the presenilins (e.g. PSEN1 or PSEN2). In general, mouse models relevant to EOAD recapitulate amyloidosis, show only limited amounts of NFTs and neuronal cell dysfunction and low but significant levels of seizure susceptibility. To investigate the effect of genetic background on these phenotypes, we generated APP^swe and PSEN1^de9 transgenic mice on the seizure prone inbred strain background, DBA/2J. Previous studies show that the DBA/2J genetic background modifies plaque deposition in the presence of mutant APP but the impact of PSEN1^de9 has not been tested. Our study shows that DBA/2J.APP^swePSEN1^de9 mice are significantly more prone to premature lethality, likely to due to lethal seizures, compared to B6.APP^swePSEN1^de9 mice—70% of DBA/2J.APP^swePSEN1^de9 mice die between 2-3 months of age. Of the DBA/2J.APP^swePSEN1^de9 mice that survived to 6 months of age, plaque deposition was greatly reduced compared to age-matched B6.APP^swePSEN1^de9 mice. The reduction in plaque deposition appears to be independent of microglia numbers, reactive astrocytosis and complement C5 activity.     

Exploring the Gastrointestinal “Nemabiome”: Deep Amplicon Sequencing to Quantify the Species Composition of Parasitic Nematode Communities

Parasitic helminth infections have a considerable impact on global human health as well as animal welfare and production. Although co-infection with multiple parasite species within a host is common, there is a dearth of tools with which to study the composition of these complex parasite communities. Helminth species vary in their pathogenicity, epidemiology and drug sensitivity and the interactions that occur between co-infecting species and their hosts are poorly understood. We describe the first application of deep amplicon sequencing to study parasitic nematode communities as well as introduce the concept of the gastro-intestinal “nemabiome”. The approach is analogous to 16S rDNA deep sequencing used to explore microbial communities, but utilizes the nematode ITS-2 rDNA locus instead. Gastro-intestinal parasites of cattle were used to develop the concept, as this host has many well-defined gastro-intestinal nematode species that commonly occur as complex co-infections. Further, the availability of pure mono-parasite populations from experimentally infected cattle allowed us to prepare mock parasite communities to determine, and correct for, species representation biases in the sequence data. We demonstrate that, once these biases have been corrected, accurate relative quantitation of gastro-intestinal parasitic nematode communities in cattle fecal samples can be achieved. We have validated the accuracy of the method applied to field-samples by comparing the results of detailed morphological examination of L3 larvae populations with those of the sequencing assay. The results illustrate the insights that can be gained into the species composition of parasite communities, using grazing cattle in the mid-west USA as an example. However, both the technical approach and the concept of the ‘nemabiome’ have a wide range of potential applications in human and veterinary medicine. These include investigations of host-parasite and parasite-parasite interactions during co-infection, parasite epidemiology, parasite ecology and the response of parasite populations to both drug treatments and control programs.