Accelerating Innovation in the Creation of Biovalue : The Cell and Gene Therapy Catapult

The field of regenerative medicine (RM) has considerable therapeutic promise that is proving difficult to realize. As a result, governments have supported the establishment of intermediary agencies to “accelerate” innovation. This paper examines in detail one such agency, the UK's Cell and Gene Therapy Catapult (CGTC). We describe CGTC’s role as an accelerator agency and its value-narrative, which combines both “health and wealth.” Drawing on the notion of socio-technical imaginaries, we unpack the tensions within this narrative and its instantiation as the CGTC cell therapy infrastructure is built and engages with other agencies, some of which have different priorities and roles to play within the RM field

The Human Cell Atlas.

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community

Development of the Theta-Comparative-Cell-Scoring (TCCS) Method to Quantify Diverse Phenotypic Responses between Distinct Cell Types

In this article, we have developed novel data visualization tools and a Theta comparative cell scoring (TCCS) method, which supports high-throughput in vitro pharmacogenomic studies across diverse cellular phenotypes measured by multiparametric high-content analysis. The TCCS method provides a univariate descriptor of divergent compound-induced phenotypic responses between distinct cell types, which can be used for correlation with genetic, epigenetic, and proteomic datasets to support the identification of biomarkers and further elucidate drug mechanism-of-action. Application of these methods to compound profiling across high-content assays incorporating well-characterized cells representing known molecular subtypes of disease supports the development of personalized healthcare strategies without prior knowledge of a drug target. We present proof-of-principle data quantifying distinct phenotypic response between eight breast cancer cells representing four disease subclasses. Application of the TCCS method together with new advances in next-generation sequencing, induced pluripotent stem cell technology, gene editing, and high-content phenotypic screening are well placed to advance the identification of predictive biomarkers and personalized medicine approaches across a broader range of disease types and therapeutic classes

Author Correction: Genomic analysis finds no evidence of canonical eukaryotic DNA processing complexes in a free-living protist.

Funder: Canadian Institutes of Health Research (Grant: FRN-142349) Natural Sciences and Engineering Research Council of Canada (Grant: RGPIN 05871-2014)Abstract: Cells replicate and segregate their DNA with precision. Previous studies showed that these regulated cell-cycle processes were present in the last eukaryotic common ancestor and that their core molecular parts are conserved across eukaryotes. However, some metamonad parasites have secondarily lost components of the DNA processing and segregation apparatuses. To clarify the evolutionary history of these systems in these unusual eukaryotes, we generated a genome assembly for the free-living metamonad Carpediemonas membranifera and carried out a comparative genomics analysis. Here, we show that parasitic and free-living metamonads harbor an incomplete set of proteins for processing and segregating DNA. Unexpectedly, Carpediemonas species are further streamlined, lacking the origin recognition complex, Cdc6 and most structural kinetochore subunits. Carpediemonas species are thus the first known eukaryotes that appear to lack this suite of conserved complexes, suggesting that they likely rely on yet-to-be-discovered or alternative mechanisms to carry out these fundamental processes

A CEP104-CSPP1 Complex Is Required for Formation of Primary Cilia Competent in Hedgehog Signaling

CEP104 is an evolutionarily conserved centrosomal and ciliary tip protein. CEP104 loss-of-function mutations are reported in patients with Joubert syndrome, but their function in the etiology of ciliopathies is poorly understood. Here, we show that cep104 silencing in zebrafish causes cilia-related manifestations: shortened cilia in Kupffer's vesicle, heart laterality, and cranial nerve development defects. We show that another Joubert syndrome-associated cilia tip protein, CSPP1, interacts with CEP104 at microtubules for the regulation of axoneme length. We demonstrate in human telomerase reverse transcriptase-immortalized retinal pigmented epithelium (hTERT-RPE1) cells that ciliary translocation of Smoothened in response to Hedgehog pathway stimulation is both CEP104 and CSPP1 dependent. However, CEP104 is not required for the ciliary recruitment of CSPP1, indicating that an intra-ciliary CEP104-CSPP1 complex controls axoneme length and Hedgehog signaling competence. Our in vivo and in vitro analyses of CEP104 define its interaction with CSPP1 as a requirement for the formation of Hedgehog signaling-competent cilia, defects that underlie Joubert syndrome

EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data.

Droplet-based single-cell RNA sequencing protocols have dramatically increased the throughput of single-cell transcriptomics studies. A key computational challenge when processing these data is to distinguish libraries for real cells from empty droplets. Here, we describe a new statistical method for calling cells from droplet-based data, based on detecting significant deviations from the expression profile of the ambient solution. Using simulations, we demonstrate that EmptyDrops has greater power than existing approaches while controlling the false discovery rate among detected cells. Our method also retains distinct cell types that would have been discarded by existing methods in several real data sets

Cell-Free DNA and Active Rejection in Kidney Allografts

Histologic analysis of the allograft biopsy specimen is the standard method used to differentiate rejection from other injury in kidney transplants. Donor-derived cell-free DNA (dd-cfDNA) is a noninvasive test of allograft injury that may enable more frequent, quantitative, and safer assessment of allograft rejection and injury status. To investigate this possibility, we prospectively collected blood specimens at scheduled intervals and at the time of clinically indicated biopsies. In 102 kidney recipients, we measured plasma levels of dd-cfDNA and correlated the levels with allograft rejection status ascertained by histology in 107 biopsy specimens. The dd-cfDNA level discriminated between biopsy specimens showing any rejection (T cell-mediated rejection or antibody-mediated rejection [ABMR]) and controls (no rejection histologically), P1% indicate a probability of active rejection