Stem Cell Therapies for Hemophilia A

Hemophlia A (hemA), caused by a deficiency in coagulation factor VIII (FVIII), is the second most common hereditary bleeding disease and affects 1 in 5000 males at birth worldwide. Currently, treating hemophiliac patients requires constant prophylactic injections of FVIII which can be very expensive. As such, alternative ways to treat hemA have been studied including gene therapy and stem cell based therapy which could provide long term treatment for patients and dramatically reduce costs and other complications associated with giving constant FVIII injections. Though current animal models of hemA have similar mutations in their FVIII gene as humans, successful treatment of them has not translated to humans. This created a need for an animal model that recapitulates the human disease more closely. Subsequently, we developed a sheep model of hemA that seems to mimic the human disease more closely than other animal models and also discovered a mutation in the FVIII gene of HemA sheep that is not present in other animal models, but is similar to some human mutations. A stem cell-based therapy for hemA was then tested involving intraperitoneal (IP) transplant of FVIII-transduced mesenchymal stem cells (MSCs) into hemA sheep. The transplants resulted in a phenotypic improvement of those animals, but also caused an unexplained rise in inhibitory antibodies against FVIII. In order to facilitate the development of hematopoietic stem cell-based therapies for hemA in sheep, new antibodies against sheep CD34 were created and validated. Finally, a novel source of circulating FVIII in the human body was potentially identified, MSCs. The studies show that MSCs produce endogenous FVIII in vitro and may do the same in vivo. In conclusion, the sheep model of hemA may represent an improved preclinical model to test hemA therapies and human MSCs may be a novel cell type capable of producing FVIII in vivo. Future studies exploring the physiological role of MSCs producing FVIII are warranted as well as investigation into the etiology of inhibitor formation in hemA sheep upon transplant of FVIII transduced MSCs

Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-seq data

Systematic delineation of complex biological systems is an ever-challenging and resource-intensive process. Single-cell transcriptomics allows us to study cell-to-cell variability in complex tissues at an unprecedented resolution. Accurate modeling of gene expression plays a critical role in the statistical determination of tissue-specific gene expression patterns. In the past few years, considerable efforts have been made to identify appropriate parametric models for single-cell expression data. The zero-inflated version of Poisson/negative binomial and log-normal distributions have emerged as the most popular alternatives owing to their ability to accommodate high dropout rates, as commonly observed in single-cell data. Although the majority of the parametric approaches directly model expression estimates, we explore the potential of modeling expression ranks, as robust surrogates for transcript abundance. Here we examined the performance of the discrete generalized beta distribution (DGBD) on real data and devised a Wald-type test for comparing gene expression across two phenotypically divergent groups of single cells. We performed a comprehensive assessment of the proposed method to understand its advantages compared with some of the existing best-practice approaches. We concluded that besides striking a reasonable balance between Type I and Type II errors, ROSeq, the proposed differential expression test, is exceptionally robust to expression noise and scales rapidly with increasing sample size. For wider dissemination and adoption of the method, we created an R package called ROSeq and made it available on the Bioconductor platform.</p

Microfluidic live tracking and transcriptomics of cancer-immune cell doublets link intercellular proximity and gene regulation

Cell–cell communication and physical interactions play a vital role in cancer initiation, homeostasis, progression, and immune response. Here, we report a system that combines live capture of different cell types, co-incubation, time-lapse imaging, and gene expression profiling of doublets using a microfluidic integrated fluidic circuit that enables measurement of physical distances between cells and the associated transcriptional profiles due to cell–cell interactions. We track the temporal variations in natural killer—triple-negative breast cancer cell distances and compare them with terminal cellular transcriptome profiles. The results show the time-bound activities of regulatory modules and allude to the existence of transcriptional memory. Our experimental and bioinformatic approaches serve as a proof of concept for interrogating live-cell interactions at doublet resolution. Together, our findings highlight the use of our approach across different cancers and cell types.</p

Fluidic Logic Used in a Systems Approach to Enable Integrated Single-cell Functional Analysis

The study of single cells has evolved over the past several years to include expression and genomic analysis of an increasing number of single cells. Several studies have demonstrated wide-spread variation and heterogeneity within cell populations of similar phenotype. While the characterization of these populations will likely set the foundation for our understanding of genomic- and expression-based diversity, it will not be able to link the functional differences of a single cell to its underlying genomic structure and activity. Currently, it is difficult to perturb single cells in a controlled environment, monitor and measure the response due to perturbation, and link these response measurements to downstream genomic and transcriptomic analysis. In order to address this challenge, we developed a platform to integrate and miniaturize many of the experimental steps required to study single-cell function. The heart of this platform is an elastomer-based Integrated Fluidic Circuit (IFC) that uses fluidic logic to select and sequester specific single cells based on a phenotypic trait for downstream experimentation. Experiments with sequestered cells that have been performed include on-chip culture, exposure to a variety of stimulants, and post-exposure image-based response analysis, followed by preparation of the mRNA transcriptome for massively parallel sequencing analysis. The flexible system embodies experimental design and execution that enable routine functional studies of single cells

Induction of IL-33 expression and activity in central nervous system glia

IL-33 is a novel member of the IL-1 cytokine family and a potent inducer of type 2 immunity, as mast cells and Th2 CD4+ T cells respond to IL-33 with the induction of type 2 cytokines such as IL-13. IL-33 mRNA levels are extremely high in the CNS, and CNS glia possess both subunits of the IL-33R, yet whether IL-33 is produced by and affects CNS glia has not been studied. Here, we demonstrate that pathogen-associated molecular patterns (PAMPs) significantly increase IL-33 mRNA and protein expression in CNS glia. Interestingly, IL-33 was localized to the nucleus of astrocytes. Further, CNS glial and astrocyte-enriched cultures treated with a PAMP followed by an ATP pulse had significantly higher levels of supernatant IL-1β and IL-33 than cultures receiving any single treatment (PAMP or ATP). Supernatants from PAMP + ATP-treated glia induced the secretion of IL-6, IL-13, and MCP-1 from the MC/9 mast cell line in a manner similar to exogenous recombinant IL-33. Further, IL-33 levels and activity were increased in the brains of mice infected with the neurotropic virus Theiler’s murine encephalomyelitis virus. IL-33 also had direct effects on CNS glia, as IL-33 induced various innate immune effectors in CNS glia, and this induction was greatly amplified by IL-33-stimulated mast cells. In conclusion, these results implicate IL-33-producing astrocytes as a potentially critical regulator of innate immune responses in the CNS