Biocompatibility and application of carbon fibres in heart valve tissue engineering

The success of tissue engineered heart valves relies on a balance between polymer degradation, appropriate cell repopulation and ECM deposition, in order for the valves to continue their vital function. However, the process of remodelling is highly dynamic and species dependent. Carbon fibres have been well used in the construction industry for their high tensile strength and flexibility, and therefore might be relevant to support tissue engineered hearts valve during this transition in the mechanically demanding environment of the circulation. The aim of this study was to assess the suitability of carbon fibres to be incorporated into tissue engineered heart valves, with respect to optimising their cellular interaction and mechanical flexibility during valve opening and closure. The morphology and surface oxidation of the carbon fibres was characterised by scanning electron microscopy (SEM). Their ability to interact with human adipose derived stem cells (hADSCs) was assessed with respect to cell attachment and phenotypic changes. hADSCs attached and maintained their expression of stem cell markers with negligible differentiation to other lineages. Incorporation of carbon fibres into a stand-alone tissue engineered aortic root, comprised of jet-sprayed poly-caprolactone aligned fibres had no negative effects on the opening and closure characteristics of the valve when simulated in a pulsatile bioreactor. In conclusion, carbon fibres were found to be conducive to hADSC attachment and maintaining their phenotype. Carbon fibres were sufficiently flexible for full motion of valvular opening and closure. This study provides a proof of concept for the incorporation of carbon fibres into tissue engineered heart valves to continue their vital function during scaffold degradation

Ethnicity, consanguinity, and genetic architecture of hypertrophic cardiomyopathy

AIMS: Hypertrophic cardiomyopathy (HCM) is characterized by phenotypic heterogeneity that is partly explained by the diversity of genetic variants contributing to disease. Accurate interpretation of these variants constitutes a major challenge for diagnosis and implementing precision medicine, especially in understudied populations. The aim is to define the genetic architecture of HCM in North African cohorts with high consanguinity using ancestry-matched cases and controls. METHODS AND RESULTS: Prospective Egyptian patients (n = 514) and controls (n = 400) underwent clinical phenotyping and genetic testing. Rare variants in 13 validated HCM genes were classified according to standard clinical guidelines and compared with a prospective HCM cohort of majority European ancestry (n = 684). A higher prevalence of homozygous variants was observed in Egyptian patients (4.1% vs. 0.1%, P = 2 × 10-7), with variants in the minor HCM genes MYL2, MYL3, and CSRP3 more likely to present in homozygosity than the major genes, suggesting these variants are less penetrant in heterozygosity. Biallelic variants in the recessive HCM gene TRIM63 were detected in 2.1% of patients (five-fold greater than European patients), highlighting the importance of recessive inheritance in consanguineous populations. Finally, rare variants in Egyptian HCM patients were less likely to be classified as (likely) pathogenic compared with Europeans (40.8% vs. 61.6%, P = 1.6 × 10-5) due to the underrepresentation of Middle Eastern populations in current reference resources. This proportion increased to 53.3% after incorporating methods that leverage new ancestry-matched controls presented here. CONCLUSION: Studying consanguineous populations reveals novel insights with relevance to genetic testing and our understanding of the genetic architecture of HCM

Dissociation of Infectivity from Seeding Ability in Prions with Alternate Docking Mechanism

Previous studies identified two mammalian prion protein (PrP) polybasic domains that bind the disease-associated conformer PrPSc, suggesting that these domains of cellular prion protein (PrPC) serve as docking sites for PrPSc during prion propagation. To examine the role of polybasic domains in the context of full-length PrPC, we used prion proteins lacking one or both polybasic domains expressed from Chinese hamster ovary (CHO) cells as substrates in serial protein misfolding cyclic amplification (sPMCA) reactions. After ∼5 rounds of sPMCA, PrPSc molecules lacking the central polybasic domain (ΔC) were formed. Surprisingly, in contrast to wild-type prions, ΔC-PrPSc prions could bind to and induce quantitative conversion of all the polybasic domain mutant substrates into PrPSc molecules. Remarkably, ΔC-PrPSc and other polybasic domain PrPSc molecules displayed diminished or absent biological infectivity relative to wild-type PrPSc, despite their ability to seed sPMCA reactions of normal mouse brain homogenate. Thus, ΔC-PrPSc prions interact with PrPC molecules through a novel interaction mechanism, yielding an expanded substrate range and highly efficient PrPSc propagation. Furthermore, polybasic domain deficient PrPSc molecules provide the first example of dissociation between normal brain homogenate sPMCA seeding ability from biological prion infectivity. These results suggest that the propagation of PrPSc molecules may not depend on a single stereotypic mechanism, but that normal PrPC/PrPSc interaction through polybasic domains may be required to generate prion infectivity

Strain-Dependent Effect of Macroautophagy on Abnormally Folded Prion Protein Degradation in Infected Neuronal Cells

Prion diseases are neurodegenerative disorders caused by the accumulation of abnormal prion protein (PrPSc) in the central nervous system. With the aim of elucidating the mechanism underlying the accumulation and degradation of PrPSc, we investigated the role of autophagy in its degradation, using cultured cells stably infected with distinct prion strains. The effects of pharmacological compounds that inhibit or stimulate the cellular signal transduction pathways that mediate autophagy during PrPSc degradation were evaluated. The accumulation of PrPSc in cells persistently infected with the prion strain Fukuoka-1 (FK), derived from a patient with Gerstmann-Straussler-Scheinker syndrome, was significantly increased in cultures treated with the macroautophagy inhibitor 3-methyladenine (3MA) but substantially reduced in those treated with the macroautophagy inducer rapamycin. The decrease in FK-derived PrPSc levels was mediated, at least in part, by the phosphatidylinositol 3-kinase/MEK signalling pathway. By contrast, neither rapamycin nor 3MA had any apparently effect on PrPSc from either the 22L or the Chandler strain, indicating that the degradation of PrPSc in host cells might be strain-dependent

Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions

Funder: Science and Technology Development Fund; doi: https://doi.org/10.13039/Funder: Al-Alfi FoundationFunder: Magdi Yacoub Heart FoundationFunder: Rosetrees and Stoneygate Imperial College Research FellowshipFunder: National Health and Medical Research Council (Australia)Abstract: Purpose: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene–disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. We hypothesized that incorporating disease-specific information would improve tool performance. Methods: We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We assessed CardioBoost’s ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. Results: CardioBoost has high global discrimination accuracy (precision recall area under the curve [AUC] 0.91 for cardiomyopathies; 0.96 for arrhythmias), outperforming existing tools (4–24% improvement). CardioBoost obtains excellent accuracy (cardiomyopathies 90.2%; arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval [CI] 11–29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. Conclusions: A disease-specific variant classifier outperforms state-of-the-art genome-wide tools for rare missense variants in inherited cardiac conditions (https://www.cardiodb.org/cardioboost/), highlighting broad opportunities for improved pathogenicity prediction through disease specificity

Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions

Funder: Science and Technology Development Fund; doi: https://doi.org/10.13039/Funder: Al-Alfi FoundationFunder: Magdi Yacoub Heart FoundationFunder: Rosetrees and Stoneygate Imperial College Research FellowshipFunder: National Health and Medical Research Council (Australia)Abstract: Purpose: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene–disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. We hypothesized that incorporating disease-specific information would improve tool performance. Methods: We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We assessed CardioBoost’s ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. Results: CardioBoost has high global discrimination accuracy (precision recall area under the curve [AUC] 0.91 for cardiomyopathies; 0.96 for arrhythmias), outperforming existing tools (4–24% improvement). CardioBoost obtains excellent accuracy (cardiomyopathies 90.2%; arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval [CI] 11–29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. Conclusions: A disease-specific variant classifier outperforms state-of-the-art genome-wide tools for rare missense variants in inherited cardiac conditions (https://www.cardiodb.org/cardioboost/), highlighting broad opportunities for improved pathogenicity prediction through disease specificity

Advanced fluorescence microscopy techniques for the life sciences

The development of super-resolved fluorescence microscopy, for which the Nobel Prize was awarded in 2014, has been a topic of interest to physicists and biologists alike. It is inevitable that numerous questions in biomedical research cannot be answered by means other than direct observation. In this review, advances to fluorescence microscopy are covered in a widely accessible fashion to facilitate its use in decisions related to its acquisition and utilization in biomedical research