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Phenotypic differences in intermediate generalized junctional epidermolysis bullosa with homozygous LAMC2 mutation and a potential genetic modifier.
No full textDeveloping Quality Workforce Training: Breaking with Traditional Scoring
No full textWhen thinking about grades, most of us naturally think of the numerical scoring system: a scale of 0-100% correct. While two trainees could have equivalent numerical scores, it is unlikely that they got the same questions correct. Identifying which types of questions they got correct could be more informative and demonstrate each trainee’s unique strengths and weaknesses
A cochlear progenitor pool influences patterning of the mammalian sensory epithelium via MYBL2.
Get PDFDuring embryonic development, Wnt signaling influences both proliferation and sensory formation in the cochlea. How this dual nature of Wnt signaling is coordinated is unknown. In this study, we define a novel role for a Wnt-regulated gene, Mybl2, which was already known to be important for proliferation, in determining the size and patterning of the sensory epithelium in the murine cochlea. Using a quantitative spatial analysis approach and analyzing Mybl2 loss-of-function, we show that Mybl2 promoted proliferation in the inner sulcus domain but limited the size of the sensory domain by influencing their adjoining boundary position via Jag1 regulation during development. Mybl2 loss-of-function simultaneously decreased proliferation in the inner sulcus and increased the size of the sensory domain, resulting in a wider sensory epithelium with ectopic inner hair cell formation during late embryonic stages. These data suggest that progenitor cells in the inner sulcus determine boundary formation and pattern the sensory epithelium via MYBL2
Amphiphilic shuttle peptide delivers base editor ribonucleoprotein to correct the CFTR R553X mutation in well-differentiated airway epithelial cells.
Get PDFBase editing could correct nonsense mutations that cause cystic fibrosis (CF), but clinical development is limited by the lack of delivery methods that efficiently breach the barriers presented by airway epithelia. Here, we present a novel amphiphilic shuttle peptide based on the previously reported S10 peptide that substantially improved base editor ribonucleoprotein (RNP) delivery. Studies of the S10 secondary structure revealed that the alpha-helix formed by the endosomal leakage domain (ELD), but not the cell penetrating peptide (CPP), was functionally important for delivery. By isolating and extending the ELD, we created a novel shuttle peptide, termed S237. While S237 achieved lower delivery of green fluorescent protein, it outperformed S10 at Cas9 RNP delivery to cultured human airway epithelial cells and to pig airway epithelia in vivo, possibly due to its lower net charge. In well-differentiated primary human airway epithelial cell cultures, S237 achieved a 4.6-fold increase in base editor RNP delivery, correcting up to 9.4% of the cystic fibrosis transmembrane conductance regulator (CFTR) R553X allele and restoring CFTR channel function close to non-CF levels. These findings deepen the understanding of peptide-mediated delivery and offer a translational approach for base editor RNP delivery for CF airway disease
Advancing stem cell technologies for conservation of wildlife biodiversity.
Get PDFWildlife biodiversity is essential for healthy, resilient and sustainable ecosystems. For biologists, this diversity also represents a treasure trove of genetic, molecular and developmental mechanisms that deepen our understanding of the origins and rules of life. However, the rapid decline in biodiversity reported recently foreshadows a potentially catastrophic collapse of many important ecosystems and the associated irreversible loss of many forms of life on our planet. Immediate action by conservationists of all stripes is required to avert this disaster. In this Spotlight, we draw together insights and proposals discussed at a recent workshop hosted by Revive & Restore, which gathered experts to discuss how stem cell technologies can support traditional conservation techniques and help protect animal biodiversity. We discuss reprogramming, in vitro gametogenesis, disease modelling and embryo modelling, and we highlight the prospects for leveraging stem cell technologies beyond mammalian species
A graph theoretical approach to experimental prioritization in genome-scale investigations.
Get PDFThe goal of systems biology is to gain a network level understanding of how gene interactions influence biological states, and ultimately inform upon human disease. Given the scale and scope of systems biology studies, resource constraints often limit researchers when validating genome-wide phenomena and potentially lead to an incomplete understanding of the underlying mechanisms. Further, prioritization strategies are often biased towards known entities (e.g. previously studied genes/proteins with commercially available reagents), and other technical issues that limit experimental breadth. Here, heterogeneous biological information is modeled as an association graph to which a high-performance minimum dominating set solver is applied to maximize coverage across the graph, and thus increase the breadth of experimentation. First, we tested our model on retrieval of existing gene functional annotations and demonstrated that minimum dominating set returns more diverse terms when compared to other computational methods. Next, we utilized our heterogenous network and minimum dominating set solver to assist in the process of identifying understudied genes to be interrogated by the International Mouse Phenotyping Consortium. Using an unbiased algorithmic strategy, poorly studied genes are prioritized from the remaining thousands of genes yet to be characterized. This method is tunable and extensible with the potential to incorporate additional user-defined prioritizing information. The minimum dominating set approach can be applied to any biological network in order to identify a tractable subset of features to test experimentally or to assist in prioritizing candidate genes associated with human disease
Pushing the boundaries of rare disease diagnostics with the help of the first Undiagnosed Hackathon.
No full textIn the first-ever Undiagnosed Hackathon, nearly 100 experts from 28 countries combined advanced phenotyping and genomic techniques for 48 hours, ultimately providing diagnoses to 40% of the previously undiagnosed families. This inspiring model demonstrates the power of multidisciplinary collaboration and patient partnership in precision diagnostics
In vivo models of subclonal oncogenesis and dependency in hematopoietic malignancy.
No full textCancer evolution is a multifaceted process leading to dysregulation of cellular expansion and differentiation through somatic mutations and epigenetic dysfunction. Clonal expansion and evolution is driven by cell-intrinsic and -extrinsic selective pressures, which can be captured with increasing resolution by single-cell and bulk DNA sequencing. Despite the extensive genomic alterations revealed in profiling studies, there remain limited experimental systems to model and perturb evolutionary processes. Here, we integrate multi-recombinase tools for reversible, sequential mutagenesis from premalignancy to leukemia. We demonstrate that inducible Flt3 mutations differentially cooperate with Dnmt3a, Idh2, and Npm1 mutant alleles, and that changing the order of mutations influences cellular and transcriptional landscapes. We next use a generalizable, reversible approach to demonstrate that mutation reversion results in rapid leukemic regression with distinct differentiation patterns depending upon co-occurring mutations. These studies provide a path to experimentally model sequential mutagenesis, investigate mechanisms of transformation and probe oncogenic dependency in disease evolution
The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species.
Get PDFBridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch\u27s APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch\u27s data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch\u27s analytic tools by developing a customized plugin for OpenAI\u27s ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app