Biology subjects

Hart, T.

Publications and source records attributed to Hart, T..

7 recordsLinked to original sources

bioRxiv2018

Mobility in Osteogenesis Imperfecta: A Multicenter North American Study

BackgroundOsteogenesis imperfecta (OI) is a genetic connective tissue disorder characterized by increased bone fragility and recurrent fractures. The phenotypic severity of OI has a significant influence on the ability to walk but little is known about the ambulatory characteristics, strength, or functional abilities in individuals with OI, especially in the more severe forms. To advance clinical research in OI, the Linked Clinical Research Centers, network of clinical centers in North America with significant experience in treating patients with OI, was established in 2009. The purpose of this work was to characterize mobility in OI using standard clinical assessment tools. and determine if any patient characteristics could be used to predict mobility outcomes.\n\nMethodsData were collected at five clinical sites and included age, gender, ethnicity, height, weight, use of assistive device, and bisphosphonate use and mobility metrics (age at first walk, Gillette Functional Assessment Questionnaire, Functional Mobility Scale, and distance walked in the 6 minute walk test). Linear mixed models were developed to explore the relationships between subject demographics and mobility metrics.\n\nResultsThe study identified 491 individuals age 3 and older. In general, the results showed minor limitations in the type I group while the more severe types showed more significant limitations in all mobility metrics analyzed. Height and weight were shown to be the most significant predictors of mobility metrics. Relationships with mobility and bisphosphonates varied with OI type and whether oral or IV was used.\n\nConclusionThis paper is the most comprehensive report of mobility in individuals with OI to date. These results are vital to understanding the mobility limitations of specific types of OI and beneficial when developing rehabilitation protocols for this population. It is important for physicians, patients, and caregivers to gain insight into severity and classification of the disease and the influence of disease-related characteristics on the prognosis for mobility.

bioengineering↗

bioRxiv2018

The functional genomic circuitry of human glioblastoma stem cells

SummarySuccessful glioblastoma (GBM) therapies have remained elusive due to limitations in understanding mechanisms of growth and survival of the tumorigenic population. Using CRISPR-Cas9 approaches in patient-derived GBM stem cells to interrogate function of the coding genome, we identify diverse actionable pathways responsible for growth that reveal the gene-essential circuitry of GBM stemness. In particular, we describe the Sox developmental transcription factor family; H3K79 methylation by DOT1L; and ufmylation stress responsiveness programs as essential for GBM stemness. Additionally, we find mechanisms of temozolomide resistance and sensitivity that could lead to combination strategies with this standard of care treatment. By reaching beyond static genome analysis of bulk tumors, with a genome wide functional approach, we dive deep into a broad range of biological processes to provide new understanding of GBM growth and treatment resistance.\n\nSignificanceGlioblastoma (GBM) remains an incurable disease despite an increasingly thorough depth of knowledge of the genomic and epigenomic alterations of bulk tumors. Evidence from multiple approaches support that GBM reflects an aberrant developmental hierarchy, with GBM stem cells (GSCs), fueling tumor growth and invasion. The properties of this tumor subpopulation may also in part explain treatment resistance and disease recurrence. Unfortunately, we still have a limited knowledge of the molecular circuitry of these cells and progress has been slow as we have not been able, until recently, to interrogate function at the genome-wide scale. Here, using parallel genome-wide CRISPR-Cas9 screens, we identify the essential genes for GSC growth. Further, by screening in the presence of low and high dose temozolomide, we identify mechanisms of drug resistance and sensitivity. These functional screens in patient derived cells reveal new aspects of GBM biology and identify a diversity of actionable targets such as genes governing stem cell traits, epigenome regulation and the response to stress stimuli.

cancer biology↗

bioRxiv2018

Reactive Initiation Training is more effective than Shuttle Run to improve the on-court agility of novice badminton players

PurposeDespite its well-known importance in sports, agility is ambiguously defined and lack of research. Shuttle Run (SR) is commonly used to improve the on-court agility of badminton players. Reactive Initiation Training (RIT) contrasts SR in that it only demands rapid generation of initiation step toward the direction of shuttlecock. The current study compared SR with RIT to determine which one is more effective for improving on-court agility of novice badminton players.\n\nMethod20 novice badminton players were split in half to receive either RIT or SR on court for five days. Before and after training, participants were assessed on their ability to intercept the shuttlecocks randomly thrown by a coach to six corners of the court with and without visual occlusion of the coach. All trials of interception were recorded for video analysis of initiation time, running time and total time.\n\nResultsThe mean total times were greater with visual occlusion and varied systematically with the position of interception. Both training methods shortened the mean running time, however, only RIT additionally reduced the initiation time and its proportion on those time-consuming positions in the occluded condition.\n\nConclusionRIT is more effective than SR to improve the on-court agility of novice badminton players.

physiology↗

bioRxiv2018

Hierarchical organization of the human cell from a cancer coessentiality network

Genetic interactions mediate the emergence of phenotype from genotype. Systematic survey of genetic interactions in yeast showed that genes operating in the same biological process have highly correlated genetic interaction profiles, and this observation has been exploited to infer gene function in model organisms. Systematic surveys of digenic perturbations in human cells are also highly informative, but are not scalable, even with CRISPR-mediated methods. As an alternative, we developed an indirect method of deriving functional interactions. We show that genes having correlated knockout fitness profiles across diverse, non-isogenic cell lines are analogous to genes having correlated genetic interaction profiles across isogenic query strains, and similarly implies shared biological function. We constructed a network of genes with correlated fitness profiles across 400 CRISPR knockout screens in cancer cell lines into a \"coessentiality network,\" with up to 500-fold enrichment for co-functional gene pairs, enabling strong inference of human gene function. Modules in the network are connected in a layered web that gives insight into the hierarchical organization of the cell.

systems biology↗

bioRxiv2017

Identifying drug-gene interactions from CRISPR knockout screens with drugZ

Chemogenetic profiling enables the identification of gene mutations that enhance or suppress the activity of small molecules. This knowledge provides insights into drug mechanism-of-action, genetic vulnerabilities, and resistance mechanisms, all of which may help stratify patient populations. We present drugZ, an algorithm for identifying both synergistic and suppressor chemogenetic interactions from highly sensitive CRISPR screens, available at github.com/hart-lab/drugz. In screens for interactions with a poly(ADP-ribose) polymerase (PARP) inhibitor, DrugZ identifies a greater fraction of the homologous recombination repair pathway than contemporary methods, and confirms KEAP1 loss as a resistance factor for ERK inhibitors.

bioinformatics↗

bioRxiv2017

Coessentiality And Cofunctionality: A Network Approach To Learning Genetic Vulnerabilities From Cancer Cell Line Fitness Screens

Genetic interaction networks are a powerful approach for functional genomics, and the synthetic lethal interactions that comprise these networks offer a compelling strategy for identifying candidate cancer targets. As the number of published shRNA and CRISPR perturbation screens in cancer cell lines expands, there is an opportunity for integrative analysis that goes further than pairwise synthetic lethality and discovers genetic vulnerabilities of related sets of cell lines. We re-analyze over 100 high-quality, genome-scale shRNA screens in human cancer cell lines and derive a quantitative fitness score for each gene that accurately reflects genotype-specific gene essentiality. We identify pairs of genes with correlated essentiality profiles and merge them into a cancer coessentiality network, where shared patterns of genetic vulnerability in cell lines give rise to clusters of functionally related genes in the network. Network clustering discriminates among all three defined subtypes of breast cancer cell lines (basal, luminal, and Her2-amplified), and further identifies novel subsets of Her2+ and ovarian cancer cells. We demonstrate the utility of the network as a platform for both hypothesis-driven and data-driven discovery of context-specific essential genes and their associated biomarkers.

genomics↗

bioRxiv2017

Evaluation and Design of Genome-wide CRISPR/Cas9 Knockout Screens

The adaptation of CRISPR/Cas9 technology to mammalian cell lines is transforming the study of human functional genomics. Pooled libraries of CRISPR guide RNAs (gRNAs), targeting human protein-coding genes and encoded in viral vectors, have been used to systematically create gene knockouts in a variety of human cancer and immortalized cell lines, in an effort to identify whether these knockouts cause cellular fitness defects. Previous work has shown that CRISPR screens are more sensitive and specific than pooled library shRNA screens in similar assays, but currently there exists significant variability across CRISPR library designs and experimental protocols. In this study, we re-analyze 17 genome-scale knockout screens in human cell lines from three research groups using three different genome-scale gRNA libraries, using the Bayesian Analysis of Gene Essentiality (BAGEL) algorithm to identify essential genes, to refine and expand our previously defined set of human core essential genes, from 360 to 684 genes. We use this expanded set of reference Core Essential Genes (CEG2), plus empirical data from six CRISPR knockout screens, to guide the design of a sequence-optimized gRNA library, the Toronto KnockOut version 3.0 (TKOv3) library. We demonstrate the high effectiveness of the library relative to reference sets of essential and nonessential genes as well as other screens using similar approaches. The optimized TKOv3 library, combined with the CEG2 reference set, provide an efficient, highly optimized platform for performing and assessing gene knockout screens in human cell lines.

systems biology↗