2 research outputs found
Effects of Digestion, Cell Culture Media, and Mucous on the Physical Properties, Cellular Effects, and Translocation of Polystyrene and Polymethacrylate Nanoparticles
No full textThe discovery of plastic and metal nanoparticles in organisms, foods, and beverages has generated numerous studies on the effects of these particles on the barrier cells and their subsequent absorption into the body. Following ingestion, nanoparticles travel down the gastrointestinal tract (GIT), and their physicochemical characteristics change in response to the change in proteins and pH during their digestion. We measured the translocation of digested nanoparticles across a co-culture monolayer of Caco-2 and various combinations (1:9, 5:5, and 9:1) of HT29-MTX-E12. The in vitro model of the intestine was used to determine the translocation of digested 20 nm polymethacrylate (PMA) particles and the accompanying monolayer barrier effects after a 72 h exposure. The in vitro digestion increased the agglomeration and hydrodynamic diameters and decreased the surface charge of the nanoparticles. For NH2-functionalized polymethacrylate nanoparticles (PMA-NH2), the diameters increased from 57 nm (water) to 3800 nm (media), or 2660 nm (chyme). These nanoparticles compromised the integrity of the monolayer (trans-epithelial electrical resistance, Lucifer yellow translocation) and translocated across all the cell ratio configurations. Digestion can have a large effect on nanoparticle agglomeration and surface charge. Excess mucous was not seen as a barrier to the translocation of PMA-NH2
Minority Gene Expression Profiling: Probing the Genetic Signatures of Pathogenesis Using Ribosome Profiling
No full textThis is a pre-copyedited, author-produced version of an article accepted for publication in The Journal of Infectious Diseases following peer review. The version of record is available online at https://doi.org/10.1093/infdis/jiz565[Abstract] Minority Gene Expression Profiling (MGEP) refers to a scenario where the expression profiles of specific genes of interest are concentrated in a small cellular pool that is embedded within a larger, non-expressive pool. An example of this is the analysis of disease-related genes within sub-populations of blood or biopsied tissues. These systems are characterized by low signal-to-noise ratios that make it difficult, if not impossible, to uncover the desired signatures of pathogenesis in the absence of lengthy, and often problematic, technical manipulations. We have adapted ribosome profiling (RP) workflows from the Illumina to the Ion Proton platform and used them to analyze signatures of pathogenesis in an MGEP model system consisting of human cells eliciting <3% productive dengue infection. We find that RP is powerful enough to identify relevant responses of differentially expressed genes, even in the presence of significant noise. We discuss how to deal with sources of unwanted variation, and propose ways to further improve this powerful approach to the study of pathogenic signatures within MGEP systems.The work was supported by an award to ML from the In-House Laboratory Independent Research Program of the Naval Medical Research Center (Project ID: ILIR-4514). This supplement is sponsored by WRAIR, LANL, USAMRIID, PUCP (Pontificia Universidad Catolica del Peru), USAFSAM, NIH.Estados Unidos. Naval Medical Research Center; ILIR-451
