Germline Variation in Cancer-Susceptibility Genes in a Healthy,Ancestrally Diverse Cohort: Implications for Individual Genome Sequencing

Technological advances coupled with decreasing costs are bringing whole genome and whole exome sequencing closer to routine clinical use. One of the hurdles to clinical implementation is the high number of variants of unknown significance. For cancer-susceptibility genes, the difficulty in interpreting the clinical relevance of the genomic variants is compounded by the fact that most of what is known about these variants comes from the study of highly selected populations, such as cancer patients or individuals with a family history of cancer. The genetic variation in known cancer-susceptibility genes in the general population has not been well characterized to date. To address this gap, we profiled the nonsynonymous genomic variation in 158 genes causally implicated in carcinogenesis using high-quality whole genome sequences from an ancestrally diverse cohort of 681 healthy individuals. We found that all individuals carry multiple variants that may impact cancer susceptibility, with an average of 68 variants per individual. Of the 2,688 allelic variants identified within the cohort, most are very rare, with 75% found in only 1 or 2 individuals in our population. Allele frequencies vary between ancestral groups, and there are 21 variants for which the minor allele in one population is the major allele in another. Detailed analysis of a selected subset of 5 clinically important cancer genes, BRCA1, BRCA2, KRAS, TP53, and PTEN, highlights differences between germline variants and reported somatic mutations. The dataset can serve a resource of genetic variation in cancer-susceptibility genes in 6 ancestry groups, an important foundation for the interpretation of cancer risk from personal genome sequences.     

Dynamic Conduction and Repolarisation Changes in Early Arrhythmogenic Right Ventricular Cardiomyopathy versus Benign Outflow Tract Ectopy Demonstrated by High Density Mapping & Paced Surface ECG Analysis

Aims

The concealed phase of arrhythmogenic right ventricular cardiomyopathy (ARVC) may initially manifest electrophysiologically. No studies have examined dynamic conduction/repolarization kinetics to distinguish benign right ventricular outflow tract ectopy (RVOT ectopy) from ARVC''s early phase. We investigated dynamic endocardial electrophysiological changes that differentiate early ARVC disease expression from RVOT ectopy.

Methods

22 ARVC (12 definite based upon family history and mutation carrier status, 10 probable) patients without right ventricular structural anomalies underwent high-density non-contact mapping of the right ventricle. These were compared to data from 14 RVOT ectopy and 12 patients with supraventricular tachycardias and normal hearts. Endocardial & surface ECG conduction and repolarization parameters were assessed during a standard S₁-S₂ restitution protocol.

Results

Definite ARVC without RV structural disease could not be clearly distinguished from RVOT ectopy during sinus rhythm or during steady state pacing. Delay in Activation Times at coupling intervals just above the ventricular effective refractory period (VERP) increased in definite ARVC (43±20 ms) more than RVOT ectopy patients (36±14 ms, p = 0.03) or Normals (25±16 ms, p = 0.008) and a progressive separation of the repolarisation time curves between groups existed. Repolarization time increases in the RVOT were also greatest in ARVC (definite ARVC: 18±20 ms; RVOT ectopy: 5±14, Normal: 1±18, p<0.05). Surface ECG correlates of these intracardiac measurements demonstrated an increase of greater than 48 ms in stimulus to surface ECG J-point pre-ERP versus steady state, with an 88% specificity and 68% sensitivity in distinguishing definite ARVC from the other groups. This technique could not distinguish patients with genetic predisposition to ARVC only (probable ARVC) from controls.

Conclusions

Significant changes in dynamic conduction and repolarization are apparent in early ARVC before detectable RV structural abnormalities, and were present to a lesser degree in probable ARVC patients. Investigation of dynamic electrophysiological parameters may be useful to identify concealed ARVC in patients without disease pedigrees by using endocardial electrogram or paced ECG parameters.     

In Vivo Inhibition of RIPK2 Kinase Alleviates Inflammatory Disease

The RIPK2 kinase transduces signaling downstream of the intracellular peptidoglycan sensors NOD1 and NOD2 to promote a productive inflammatory response. However, excessive NOD2 signaling has been associated with numerous diseases, including inflammatory bowel disease (IBD), sarcoidosis and inflammatory arthritis, making pharmacologic inhibition of RIPK2 an appealing strategy. In this work, we report the generation, identification, and evaluation of novel RIPK2 specific inhibitors. These compounds potently inhibit the RIPK2 tyrosine kinase activity in in vitro biochemical assays and cellular assays, as well as effectively reduce RIPK2-mediated effects in an in vivo peritonitis model. In conjunction with the development of these inhibitors, we have also defined a panel of genes whose expression is regulated by RIPK2 kinase activity. Such RIPK2 activation markers may serve as a useful tool for predicting settings likely to benefit from RIPK2 inhibition. Using these markers and the FDA-approved RIPK2 inhibitor Gefitinib, we show that pharmacologic RIPK2 inhibition drastically improves disease in a spontaneous model of Crohn Disease-like ileitis. Furthermore, using novel RIPK2-specific inhibitors, we show that cellular recruitment is inhibited in an in vivo peritonitis model. Altogether, the data presented in this work provides a strong rationale for further development and optimization of RIPK2-targeted pharmaceuticals and diagnostics.     

SeedQuant: a deep learning-based tool for assessing stimulant and inhibitor activity on root parasitic seeds

Witchweeds (Striga spp.) and broomrapes (Orobanchaceae and Phelipanche spp.) are root parasitic plants that infest many crops in warm and temperate zones, causing enormous yield losses and endangering global food security. Seeds of these obligate parasites require rhizospheric, host-released stimulants to germinate, which opens up possibilities for controlling them by applying specific germination inhibitors or synthetic stimulants that induce lethal germination in the host’s absence. To determine their effect on germination, root exudates or synthetic stimulants/inhibitors are usually applied to parasitic seeds in in vitro bioassays, followed by assessment of germination ratios. Although these protocols are very sensitive, the germination recording process is laborious, representing a challenge for researchers and impeding high-throughput screens. Here, we developed an automatic seed census tool to count and discriminate germinated seeds (GS) from non-GS. We combined deep learning, a powerful data-driven framework that can accelerate the procedure and increase its accuracy, for object detection with computer vision latest development based on the Faster Region-based Convolutional Neural Network algorithm. Our method showed an accuracy of 94% in counting seeds of Striga hermonthica and reduced the required time from approximately 5 min to 5 s per image. Our proposed software, SeedQuant, will be of great help for seed germination bioassays and enable high-throughput screening for germination stimulants/inhibitors. SeedQuant is an open-source software that can be further trained to count different types of seeds for research purposes.     

To breed or not to breed: past reproductive status and environmental cues drive current breeding decisions in a long-lived amphibian

Iteroparity is an adaptive response to uncertainty in reproductive success. However, spreading reproductive success over multiple reproduction events during a lifetime is constrained by adult mortality and the stochasticity associated with interactions between external factors and physiological states. The acquisition of information about environmental conditions during the growth of progeny and sufficient resources during the non-reproductive period are key factors for breeding success. Consequently, we hypothesized that long-lived animals may skip a breeding opportunity when information about unfavourable environmental conditions is available. In addition, nutritional constraints could prevent an animal from replenishing its reserves sufficiently to invest in the current breeding period. We investigated these questions using capture–recapture data from a 5-year study on a large population of yellow-bellied toads in a forest in north-eastern France. We took advantage of various advances in multi-state capture–recapture models (e.g. unobservable states and mixture models) to test our hypotheses. Our results show that the combined effects of rainfall deficit and the breeding/non-breeding state of individuals during the past breeding season affect breeding probability during the following breeding opportunity. We also found that females breed less frequently than males, suggesting that the overall energy cost of reproduction differs between genders. Finally, the results indicate that toad survival appears to be negatively influenced by rainfall deficits. We discuss the yellow-bellied toad’s reproductive behaviour in term of bet-hedging strategy and life history trait evolution.     

Validation of all-atom phosphatidylcholine lipid force fields in the tensionless NPT ensemble

A recently defined charge set, to be used in conjunction with the all-atom CHARMM27r force field, has been validated for a series of phosphatidylcholine lipids. The work of Sonne et al. successfully replicated experimental bulk membrane behaviour for dipalmitoylphosphatidylcholine (DPPC) under the isothermal-isobaric (NPT) ensemble. Previous studies using the defined CHARMM27r charge set have resulted in lateral membrane contraction when used in the tensionless NPT ensemble, forcing the lipids to adopt a more ordered conformation than predicted experimentally. The current study has extended the newly defined charge set to 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) and 1-palmitoyl-2-docosahexaenoyl-sn-glycero-3-phosphatidylcholine (PDPC). Molecular dynamics simulations were run for each of the lipids (including DPPC) using both the CHARMM27r charge set and the newly defined modified charge set. In all three cases a significant improvement was seen in both bulk membrane properties and individual atomistic effects. Membrane width, area per lipid and the depth of water penetration were all seen to converge to experimental values. Deuterium order parameters generated with the new charge set showed increased disorder across the width of the bilayer and reflected both results from experiment and similar simulations run with united atom models. These newly validated models can now find use in mixed biological simulations under the tensionless ensemble without concern for lateral contraction.     

The structure of FADD and its mode of interaction with procaspase-8

The structure of FADD has been solved in solution, revealing that the death effector domain (DED) and death domain (DD) are aligned with one another in an orthogonal, tail-to-tail fashion. Mutagenesis of FADD and functional reconstitution with its binding partners define the interaction with the intracellular domain of CD95 and the prodomain of procaspase-8 and reveal a self-association surface necessary to form a productive complex with an activated "death receptor." The identification of a procaspase-specific binding surface on the FADD DED suggests a preferential interaction with one, but not both, of the DEDs of procaspase-8 in a perpendicular arrangement. FADD self-association is mediated by a "hydrophobic patch" in the vicinity of F25 in the DED. The structure of FADD and its functional characterization, therefore, illustrate the architecture of key components in the death-inducing signaling complex.     

Overexpression of manganese or copper-zinc superoxide dismutase inhibits breast cancer growth

We have studied the effects of overexpression of superoxide dismutase (SOD), a tumor suppressor protein that dismutes superoxide radical to H2O2, on breast cancer cell growth in vitro and xenograft growth in vivo. No previous work has directly compared the growth-suppressive effects of manganese SOD (MnSOD) and copper-zinc SOD (CuZnSOD). We hypothesized that either adenoviral MnSOD (AdMnSOD) or adenoviral CuZnSOD (AdCuZnSOD) gene therapy would suppress the growth of human breast cancer cells. After determining the antioxidant profiles of three human breast cell lines, MCF 10A, MDA-MB231, and MCF-7, we measured the effects of MnSOD or CuZnSOD overexpression on cell growth and survival in vitro and in vivo. Results demonstrated that infection with AdMnSOD or AdCuZnSOD increased the activity of the respective enzyme in all three cell lines. In vitro, overexpression of MnSOD or CuZnSOD decreased not only cell growth but also clonogenic survival in a dose- and transgene-dependent manner. In vivo, treatment of tumors with AdMnSOD or AdCuZnSOD decreased xenograft growth compared to controls. The first direct comparison of MnSOD to CuZnSOD overexpression indicated that CuZnSOD and MnSOD were similarly effective at suppressing cancer cell growth.     

Efficient gene delivery and silencing of mouse and human pancreatic islets

Background  

In view of the importance of beta cells in glucose homeostasis and the profound repercussions of beta cell pathology on human health, the acquisition of tools to study pancreatic islet function is essential for the design of alternative novel therapies for diabetes. One promising approach toward this goal involves the modification of gene expression profile of beta cells.