Cationic cholesterol-dependent LNP delivery to lung stem cells, the liver, and heart.

Adding a cationic helper lipid to a lipid nanoparticle (LNP) can increase lung delivery and decrease liver delivery. However, it remains unclear whether charge-dependent tropism is universal or, alternatively, whether it depends on the component that is charged. Here, we report evidence that cationic cholesterol-dependent tropism can differ from cationic helper lipid-dependent tropism. By testing how 196 LNPs delivered mRNA to 22 cell types, we found that charged cholesterols led to a different lung:liver delivery ratio than charged helper lipids. We also found that combining cationic cholesterol with a cationic helper lipid led to mRNA delivery in the heart as well as several lung cell types, including stem cell-like populations. These data highlight the utility of exploring charge-dependent LNP tropism.

Nanoparticle stereochemistry-dependent endocytic processing improves in vivo mRNA delivery.

Stereochemistry can alter small-molecule pharmacokinetics, safety and efficacy. However, it is unclear whether the stereochemistry of a single compound within a multicomponent colloid such as a lipid nanoparticle (LNP) can influence its activity in vivo. Here we report that LNPs containing stereopure 20α-hydroxycholesterol (20α) delivered mRNA to liver cells up to 3-fold more potently than LNPs containing a mixture of both 20α- and 20ß-hydroxycholesterols (20mix). This effect was not driven by LNP physiochemical traits. Instead, in vivo single-cell RNA sequencing and imaging revealed that 20mix LNPs were sorted into phagocytic pathways more than 20α LNPs, resulting in key differences between LNP biodistribution and subsequent LNP functional delivery. These data are consistent with the fact that nanoparticle biodistribution is necessary, but not sufficient, for mRNA delivery, and that stereochemistry-dependent interactions between LNPs and target cells can improve mRNA delivery.

The Transcriptional Response to Lung-Targeting Lipid Nanoparticles in Vivo.

Lipid nanoparticles (LNPs) have delivered RNA to hepatocytes in patients, underscoring the potential impact of nonliver delivery. Scientists can shift LNP tropism to the lung by adding cationic helper lipids; however, the biological response to these LNPs remains understudied. To evaluate the hypothesis that charged LNPs lead to differential cellular responses, we quantified how 137 LNPs delivered mRNA to 19 cell types in vivo. Consistent with previous studies, we observed helper lipid-dependent tropism. After identifying and individually characterizing three LNPs that targeted different tissues, we studied the in vivo transcriptomic response to these using single-cell RNA sequencing. Out of 835 potential pathways, 27 were upregulated in the lung, and of these 27, 19 were related to either RNA or protein metabolism. These data suggest that endogenous cellular RNA and protein machinery affects mRNA delivery to the lung in vivo.

Natural killer cell detection, quantification, and subpopulation identification on paper microfluidic cell chromatography using smartphone-based machine learning classification.

Natural killer (NK) cells are immune cells that defend against viral infections and cancer and are used in cancer immunotherapies. Subpopulations of NK cells include CD56dim and CD56bright which either produce cytokines or cytotoxically kill cells directly. The absolute number and proportion of these cells in peripheral blood are tied to proper immune function. Current methods of cytokine detection and proportion of NK cell subpopulations require fluorescent dyes and highly specialized equipment, e.g., flow cytometry, thus rapid cell quantification and subpopulation analysis are needed in the clinical setting. Here, a smartphone-based device and a two-component paper microfluidic chip were used towards identifying NK cell subpopulation and inflammatory markers. One unit measured flow velocity via smartphone-captured video, determining cytokine (IL-2) and total NK cell concentrations in undiluted buffy coat blood samples. The other, single flow lane unit performs spatial separation of CD56dim and CD56bright and cells over its length using differential binding of anti-CD56 nanoparticles. A smartphone microscope combined with cloud-based machine learning predictive modeling (utilizing a random forest classification algorithm) analyzed both flow data and NK cell subpopulation differentiation. Limits of detection for cytokine and cell concentrations were 98 IU/mL and 68 cells/mL, respectively, and cell subpopulation analysis showed 89% accuracy.

Microfluidic sample preparation for respiratory virus detection: A review.

Techniques used to prepare clinical samples have been perfected for use in diagnostic testing in a variety of clinical situations, e.g., to extract, concentrate, and purify respiratory virus particles. These techniques offer a high level of purity and concentration of target samples but require significant equipment and highly trained personnel to conduct, which is difficult to achieve in resource-limited environments where rapid testing and diagnostics are crucial for proper handling of respiratory viruses. Microfluidics has popularly been utilized toward rapid virus detection in resource-limited environments, where most devices focused on detection rather than sample preparation. Initial microfluidic prototypes have been hindered by their reliance on several off-chip preprocessing steps and external laboratory equipment. Recently, sample preparation methods have also been incorporated into microfluidics to conduct the virus detection in an all-in-one, automated manner. Extraction, concentration, and purification of viruses have been demonstrated in smaller volumes of samples and reagents, with no need for specialized training or complex machinery. Recent devices show the ability to function independently and efficiently to provide rapid, automated sample preparation as well as the detection of viral samples with high efficiency. In this review, methods of microfluidic sample preparation for the isolation and purification of viral samples are discussed, limitations of current systems are summarized, and potential advances are identified.

Plant-Based Scaffolds Modify Cellular Response to Drug and Radiation Exposure Compared to Standard Cell Culture Models.

Plant-based scaffolds present many advantages over a variety of biomaterials. Recent studies explored their potential to be repopulated with human cells and thus highlight a growing interest for their use in tissue engineering or for biomedical applications. However, it is still unclear if these in vitro plant-based scaffolds can modify cell phenotype or affect cellular response to external stimuli. Here, we report the characterization of the mechano-regulation of melanoma SK-MEL-28 and prostate PC3 cells seeded on decellularized spinach leaves scaffolds, compared to cells deposited on standard rigid cell culture substrate, as well as their response to drug and radiation treatment. The results showed that YAP/TAZ signaling was downregulated, cellular morphology altered and proliferation rate decreased when cells were cultured on leaf scaffold. Interestingly, cell culture on vegetal scaffold also affected cellular response to external stress. Thus, SK-MEL-28 cells phenotype is modified leading to a decrease in MITF activity and drug resistance, while PC3 cells showed altered gene expression and radiation response. These findings shed lights on the decellularization of vegetal materials to provide substrates that can be repopulated with human cells to better reproduce a soft tissue microenvironment. However, these complex scaffolds mediate changes in cell behavior and in order to exploit the capability of matching physical properties of the various plant scaffolds to diverse physiological functionalities of cells and human tissue constructs, additional studies are required to better characterize physical and biochemical cell-substrate interactions.

Smartphone based on-chip fluorescence imaging and capillary flow velocity measurement for detecting ROR1+ cancer cells from buffy coat blood samples on dual-layer paper microfluidic chip.

Diagnosis of hematological cancer requires complete white blood cell count, followed by flow cytometry with multiple markers, and cytology. It requires substantial time and specialized training. A dual-layer paper microfluidic chip was developed as a quicker, low-cost, and field-deployable alternative to detect ROR1+ (receptor tyrosine-like orphan receptor one) cancer cells from the undiluted and untreated buffy coat blood samples. The first capture layer consisted of a GF/D glass fiber substrate, preloaded with cancer specific anti-ROR1 conjugated fluorescent particles to its center for cancer cell capture and direct smartphone fluorescence imaging. The second flow layer was comprised of a grade 1 cellulose chromatography paper with wax-printed four channels for wicking and capillary flow-based detection. The flow velocity was used as measure of antigen concentration in the buffy coat sample. In this manner, intact cells and their antigens were separated and independently analyzed by both imaging and flow velocity analyses. A custom-made smartphone-based fluorescence microscope and automated image processing and particle counter software were developed to enumerate particles on paper, with the limit of detection of 1 cell/µL. Flow velocity analysis showed even greater sensitivity, with the limit of detection of 0.1 cells/µL in the first 6 s of assay. Comparison with capillary flow model revealed great alignment with experimental data and greater correlation to viscosity than interfacial tension. Our proposed device is able to capture and on-chip image ROR1+ cancer cells within a complex sample matrix (buffy coat) while simultaneously quantifying cell concentration in a point-of-care manner.