Amaral, L. | Search bioRxiv

bioRxiv2020

Subcutaneous nanotherapy repurposes the immunosuppressive mechanism of rapamycin to enhance allogeneic islet graft viability

Oral rapamycin administration rapamycin is plagued by poor bioavailability and wide biodistribution. Thus, this pleotropic mTOR inhibitor has a narrow therapeutic window, numerous side effects and provides inadequate transplantation protection. Parental formulation was not possible due to rapamycins hydrophobicity (log P 4.3). Here, we demonstrate that subcutaneous rapamycin delivery via poly(ethylene glycol)-b-poly(propylene sulfide)(PEG-b-PPS) polymersome (PS) nanocarriers modulates cellular biodistribution of rapamycin to change its immunosuppressive mechanism for enhanced efficacy while minimizing side effects. While oral rapamycin inhibits naive T cell proliferation directly, subcutaneously administered rapamycin-loaded polymersomes (rPS) instead modulated Ly-6Clow monocytes and tolerogenic semi-mature dendritic cells, with immunosuppression mediated by CD8+ Tregs and rare CD4+ CD8+ double-positive T cells. As PEG-b-PPS PS are uniquely non-inflammatory, background immunostimulation from the vehicle was avoided, allowing immunomodulation to be primarily attributed to rapamycins cellular biodistribution. Repurposing mTOR inhibition significantly improved maintenance of normoglycemia in a clinically relevant, MHC-mismatched, allogeneic, intraportal (liver) islet transplantation model. These results demonstrate the ability of engineered nanocarriers to repurpose drugs for alternate routes of administration by rationally controlling cellular biodistribution.

bioengineering↗

bioRxiv2019

Fly-QMA: Automated analysis of mosaic imaginal discs in Drosophila

Mosaic analysis provides a means to probe developmental processes in situ by generating loss-of-function mutants within otherwise wildtype tissues. Combining these techniques with quantitative microscopy enables researchers to rigorously compare RNA or protein expression across the resultant clones. However, visual inspection of mosaic tissues remains common in the literature because quantification demands considerable labor and computational expertise. Practitioners must segment cell membranes or cell nuclei from a tissue and annotate the clones before their data are suitable for analysis. Here, we introduce Fly-QMA, a computational framework that automates each of these tasks for confocal microscopy images of Drosophila imaginal discs. The framework includes an unsupervised annotation algorithm that incorporates spatial context to inform the genetic identity of each cell. We use a combination of real and synthetic validation data to survey the performance of the annotation algorithm across a broad range of conditions. By contributing our framework to the open-source software ecosystem, we aim to contribute to the current move toward automated quantitative analysis among developmental biologists.\n\nAuthor summaryBiologists use mosaic tissues to compare the behavior of genetically distinct cells within an otherwise equivalent context. The ensuing analysis is often limited to qualitative insight. However, it is becoming clear that quantitative models are needed to unravel the complexities of many biological systems. In this manuscript we introduce Fly-QMA, an open-source software framework that automates the quantification of mosaic analysis for Drosophila imaginal discs, a common setting for studies of developmental processes. The software automatically extracts quantitative measurements from confocal images of mosaic tissues, rectifies any cross-talk between fluorescent reporters, and identifies clonally-related subpopulations of cells. Together, these functions allow users to rigorously ascribe changes in gene expression to the presence or absence of particular genes. We validate the performance of our framework using both real and synthetic data. Through its publication, we aim to contribute to the current move toward automated quantitative analysis among biologists.

systems biology↗