ABSTRACT
Hemophilia B is an ideal target for gene- and cell-based therapies because of its monogenic nature and broad therapeutic index. Here, we demonstrate the use of cell therapy as a potential long-term cure for hemophilia B in our FIX-deficient mouse model. We show that transplanted, cryopreserved, cadaveric human hepatocytes remain functional for more than a year and secrete FIX at therapeutic levels. Hepatocytes from different sources (companies and donors) perform comparably in curing the bleeding defect. We also generated induced pluripotent stem cells (iPSCs) from two hemophilia B patients and corrected the disease-causing mutations in them by two different approaches (mutation specific and universal). These corrected iPSCs were differentiated into hepatocyte-like cells (HLCs) and transplanted into hemophilic mice. We demonstrate these iPSC-HLCs to be viable and functional in mouse models for 9-12 months. This study aims to establish the use of cells from autologous and heterologous sources to treat hemophilia B.
Subject(s)
Cell Transplantation , Factor IX/metabolism , Hemophilia B/therapy , Hepatocytes/transplantation , Induced Pluripotent Stem Cells/transplantation , Animals , Disease Models, Animal , Hemophilia B/genetics , Hemophilia B/metabolism , Hemophilia B/pathology , Hepatocytes/metabolism , Hepatocytes/pathology , Heterografts , Induced Pluripotent Stem Cells/metabolism , Induced Pluripotent Stem Cells/pathology , Mice , Mice, KnockoutABSTRACT
SUMMARY: Analyzing the functional profile of a microbial community from unannotated shotgun sequencing reads is one of the important goals in metagenomics. Functional profiling has valuable applications in biological research because it identifies the abundances of the functional genes of the organisms present in the original sample, answering the question what they can do. Currently, available tools do not scale well with increasing data volumes, which is important because both the number and lengths of the reads produced by sequencing platforms keep increasing. Here, we introduce SUPER-FOCUS, SUbsystems Profile by databasE Reduction using FOCUS, an agile homology-based approach using a reduced reference database to report the subsystems present in metagenomic datasets and profile their abundances. SUPER-FOCUS was tested with over 70 real metagenomes, the results showing that it accurately predicts the subsystems present in the profiled microbial communities, and is up to 1000 times faster than other tools. AVAILABILITY AND IMPLEMENTATION: SUPER-FOCUS was implemented in Python, and its source code and the tool website are freely available at https://edwards.sdsu.edu/SUPERFOCUS. CONTACT: redwards@mail.sdsu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
