High Frequency Ultrasound for In Vivo Pregnancy Diagnosis and Staging of Placental and Fetal Development in Mice

Background

Ultrasound is a valuable non-invasive tool used in obstetrics and gynecology to monitor the growth and well being of the human fetus. The laboratory mouse has recently emerged as an appropriate model for fetal and perinatal studies because morphogenetic processes in mice exhibit adequate homology to those in humans, and genetic manipulations are relatively simple to perform in mice. High-frequency ultrasound (HFUS) has recently become available for small animal preclinical imaging and can be used to study pregnancy and development in the mouse. The objective of the current study was to assess the main applications of HFUS in the evaluation of fetal growth and placental function and to better understand human congenital diseases.

Methodology/Principal Findings

On each gestational day, at least 5 dams were monitored with HFUS; a total of ∼200 embryos were examined. Because it is not possible to measure each variable for the entire duration of the pregnancy, the parameters were divided into three groups as a function of the time at which they were measured. Univariate analysis of the relationship between each measurement and the embryonic day was performed using Spearman’s rank correlation (Rs). Continuous linear regression was adopted for multivariate analysis of significant parameters. All statistical tests were two-sided, and a p value of 0.05 was considered statistically significant.

Conclusions/Significance

The study describes the main applications of HFUS to assess changes in phenotypic parameters in the developing CD1 mouse embryo and fetus during pregnancy and to evaluating physiological fetal and placental growth and the development of principal organs such as the heart, kidney, liver, brain and eyes in the embryonic mouse. A database of normal structural and functional parameters of mouse development will provide a useful tool for the better understanding of morphogenetic and cardiovascular anomalies in transgenic and mutant mouse models.     

A Novel Microtubule Inhibitor 4SC-207 with Anti-Proliferative Activity in Taxane-Resistant Cells

Microtubule inhibitors are invaluable tools in cancer chemotherapy: taxanes and vinca alkaloids have been successfully used in the clinic over the past thirty years against a broad range of tumors. However, two factors have limited the effectiveness of microtubule inhibitors: toxicity and resistance. In particular, the latter is highly unpredictable, variable from patient to patient and is believed to be the cause of treatment failure in most cases of metastatic cancers. For these reasons, there is an increasing demand for new microtubule inhibitors that can overcome resistance mechanisms and that, at the same time, have reduced side effects. Here we present a novel microtubule inhibitor, 4SC-207, which shows strong anti-proliferative activity in a large panel of tumor cell lines with an average GI₅₀ of 11nM. In particular, 4SC-207 is active in multi-drug resistant cell lines, such as HCT-15 and ACHN, suggesting that it is a poor substrate for drug efflux pumps. 4SC-207 inhibits microtubule growth in vitro and in vivo and promotes, in a dose dependent manner, a mitotic delay/arrest, followed by apoptosis or aberrant divisions due to chromosome alignment defects and formation of multi-polar spindles. Furthermore, preliminary data from preclinical studies suggest low propensity towards bone marrow toxicities at concentrations that inhibit tumor growth in paclitaxel-resistant xenograft models. In summary, our results suggest that 4SC-207 may be a potential anti-cancer agent.     

Identification of Pyrus Single Nucleotide Polymorphisms (SNPs) and Evaluation for Genetic Mapping in European Pear and Interspecific Pyrus Hybrids

We have used new generation sequencing (NGS) technologies to identify single nucleotide polymorphism (SNP) markers from three European pear (Pyrus communis L.) cultivars and subsequently developed a subset of 1096 pear SNPs into high throughput markers by combining them with the set of 7692 apple SNPs on the IRSC apple Infinium® II 8K array. We then evaluated this apple and pear Infinium® II 9K SNP array for large-scale genotyping in pear across several species, using both pear and apple SNPs. The segregating populations employed for array validation included a segregating population of European pear (‘Old Home’בLouise Bon Jersey’) and four interspecific breeding families derived from Asian (P. pyrifolia Nakai and P. bretschneideri Rehd.) and European pear pedigrees. In total, we mapped 857 polymorphic pear markers to construct the first SNP-based genetic maps for pear, comprising 78% of the total pear SNPs included in the array. In addition, 1031 SNP markers derived from apple (13% of the total apple SNPs included in the array) were polymorphic and were mapped in one or more of the pear populations. These results are the first to demonstrate SNP transferability across the genera Malus and Pyrus. Our construction of high density SNP-based and gene-based genetic maps in pear represents an important step towards the identification of chromosomal regions associated with a range of horticultural characters, such as pest and disease resistance, orchard yield and fruit quality.     

Mechanistic Phenotypes: An Aggregative Phenotyping Strategy to Identify Disease Mechanisms Using GWAS Data

A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF<0.1) non-synonymous SNPs (nsSNPs) associated with “mechanistic phenotypes”, comprised of collections of related diagnoses. We studied two mechanistic phenotypes: (1) thrombosis, evaluated in a population of 1,655 African Americans; and (2) four groupings of cancer diagnoses, evaluated in 3,009 white European Americans. We tested associations between nsSNPs represented on GWAS platforms and mechanistic phenotypes ascertained from electronic medical records (EMRs), and sought enrichment in functional ontologies across the top-ranked associations. We used a two-step analytic approach whereby nsSNPs were first sorted by the strength of their association with a phenotype. We tested associations using two reverse genetic models and standard additive and recessive models. In the second step, we employed a hypothesis-free ontological enrichment analysis using the sorted nsSNPs to identify functional mechanisms underlying the diagnoses comprising the mechanistic phenotypes. The thrombosis phenotype was solely associated with ontologies related to blood coagulation (Fisher''s p = 0.0001, FDR p = 0.03), driven by the F5, P2RY12 and F2RL2 genes. For the cancer phenotypes, the reverse genetics models were enriched in DNA repair functions (p = 2×10−5, FDR p = 0.03) (POLG/FANCI, SLX4/FANCP, XRCC1, BRCA1, FANCA, CHD1L) while the additive model showed enrichment related to chromatid segregation (p = 4×10−6, FDR p = 0.005) (KIF25, PINX1). We were able to replicate nsSNP associations for POLG/FANCI, BRCA1, FANCA and CHD1L in independent data sets. Mechanism-oriented phenotyping using collections of EMR-derived diagnoses can elucidate fundamental disease mechanisms.     

Sensitivity of Aspergillus nidulans to the Cellulose Synthase Inhibitor Dichlobenil: Insights from Wall-Related Genes’ Expression and Ultrastructural Hyphal Morphologies

The fungal cell wall constitutes an important target for the development of antifungal drugs, because of its central role in morphogenesis, development and determination of fungal-specific molecular features. Fungal walls are characterized by a network of interconnected glycoproteins and polysaccharides, namely α-, β-glucans and chitin. Cell walls promptly and dynamically respond to environmental stimuli by a signaling mechanism, which triggers, among other responses, modulations in wall biosynthetic genes’ expression. Despite the absence of cellulose in the wall of the model filamentous fungus Aspergillus nidulans, we found in this study that fungal growth, spore germination and morphology are affected by the addition of the cellulose synthase inhibitor dichlobenil. Expression analysis of selected genes putatively involved in cell wall biosynthesis, carried out at different time points of drug exposure (i.e. 0, 1, 3, 6 and 24 h), revealed increased expression for the putative mixed linkage β-1,3;1,4 glucan synthase celA together with the β-1,3-glucan synthase fksA and the Rho-related GTPase rhoA. We also compared these data with the response to Congo Red, a known plant/fungal drug affecting both chitin and cellulose biosynthesis. The two drugs exerted different effects at the cell wall level, as shown by gene expression analysis and the ultrastructural features observed through atomic force microscopy and scanning electron microscopy. Although the concentration of dichlobenil required to affect growth of A. nidulans is approximately 10-fold higher than that required to inhibit plant cellulose biosynthesis, our work for the first time demonstrates that a cellulose biosynthesis inhibitor affects fungal growth, changes fungal morphology and expression of genes connected to fungal cell wall biosynthesis.     

Transfer of the Nonmatch-to-Goal rule in Monkeys across Cognitive Domains

To solve novel problems, it is advantageous to abstract relevant information from past experience to transfer on related problems. To study whether macaque monkeys were able to transfer an abstract rule across cognitive domains, we trained two monkeys on a nonmatch-to-goal (NMTG) task. In the object version of the task (O-NMTG), the monkeys were required to choose between two object-like stimuli, which differed either only in shape or in shape and color. For each choice, they were required to switch from their previously chosen object-goal to a different one. After they reached a performance level of over 90% correct on the O-NMTG task, the monkeys were tested for rule transfer on a spatial version of the task (S-NMTG). To receive a reward, the monkeys had to switch from their previously chosen location to a different one. In both the O-NMTG and S-NMTG tasks, there were four potential choices, presented in pairs from trial-to-trial. We found that both monkeys transferred successfully the NMTG rule within the first testing session, showing effective transfer of the learned rule between two cognitive domains.     

Relative Effects of Road Risk,Habitat Suitability,and Connectivity on Wildlife Roadkills: The Case of Tawny Owls (Strix aluco)

Background

Despite its importance for reducing wildlife-vehicle collisions, there is still incomplete understanding of factors responsible for high road mortality. In particular, few empirical studies examined the idea that spatial variation in roadkills is influenced by a complex interplay between road-related factors, and species-specific habitat quality and landscape connectivity.

Methodology/Principal Findings

In this study we addressed this issue, using a 7-year dataset of tawny owl (Strix aluco) roadkills recorded along 37 km of road in southern Portugal. We used a multi-species roadkill index as a surrogate of intrinsic road risk, and we used a Maxent distribution model to estimate habitat suitability. Landscape connectivity was estimated from least-cost paths between tawny owl territories, using habitat suitability as a resistance surface. We defined 10 alternative scenarios to compute connectivity, based on variation in potential movement patterns according to territory quality and dispersal distance thresholds. Hierarchical partitioning of a regression model indicated that independent variation in tawny owl roadkills was explained primarily by the roadkill index (70.5%) and, to a much lesser extent, by landscape connectivity (26.2%), while habitat suitability had minor effects (3.3%). Analysis of connectivity scenarios suggested that owl roadkills were primarily related to short range movements (<5 km) between high quality territories. Tawny owl roadkills were spatially autocorrelated, but the introduction of spatial filters in the regression model did not change the type and relative contribution of environmental variables.

Conclusions

Overall, results suggest that road-related factors may have a dominant influence on roadkill patterns, particularly in areas like ours where habitat quality and landscape connectivity are globally high for the study species. Nevertheless, the study supported the view that functional connectivity should be incorporated whenever possible in roadkill models, as it may greatly increase their power to predict the location of roadkill hotspots.