Large-Scale Screening of Pharmaceutical Compounds to Explore the Application Space of On-Tissue MALDI and MALDI-2 Mass Spectrometry.

The successful application of matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) in pharmaceutical research is strongly dependent on the detection of the drug of interest at physiologically relevant concentrations. Here we explored how insufficient sensitivity due to low ionization efficiency and/or the interaction of the drug molecule with the local biochemical environment of the tissue can be mitigated for many compound classes using the recently introduced MALDI-MSI coupled with laser-induced postionization, known as MALDI-2-MSI. Leveraging a MALDI-MSI screen of about 1,200 medicines/drug-like compounds from a broad range of medicinal application areas, we demonstrate a significant improvement in drug detection and the degree of sensitivity uplift by using MALDI-2 versus traditional MALDI. Our evaluation was made under simulated imaging conditions using liver homogenate sections as substrate, onto which the compounds were spotted to mimic biological conditions to the first order. To enable an evaluable detection by both MALDI and MALDI-2 for the majority of employed compounds, we spotted 1 µL of a 10 mM solution using a spotting robot and performed our experiments with a Bruker timsTOF fleX MALDI-2 instrument in both positive and negative ion modes. Specifically, we demonstrate using a large cohort of drug-like compounds that ∼60% of the tested compounds showed a more than 10-fold increase in signal intensity and ∼16% showed a more than 100-fold increase upon use of MALDI-2 postionization. Such increases in sensitivity could help advance pharmaceutical MALDI-MSI applications toward the single-cell level.

Cellular uptake and fate of cationic polymer-coated nanodiamonds delivering siRNA: a mechanistic study.

Gene silencing using small interfering RNAs (siRNAs) is a selective and promising approach for treatment of numerous diseases. However, broad applications of siRNAs are compromised by their low stability in a biological environment and limited ability to penetrate cells. Nanodiamonds (NDs) coated with cationic polymers can enable cellular delivery of siRNAs. Recently, we developed a new type of ND coating based on a random copolymer consisting of (2-dimethylaminoethyl) methacrylate (DMAEMA) and N-(2-hydroxypropyl) methacrylamide (HPMA) monomers. These hybrid ND-polymer particles (Cop+-FND) provide near-infrared fluorescence, form stable complexes with siRNA in serum, show low toxicity, and effectively deliver siRNA into cells in vitro and in vivo. Here, we present data on the mechanism of cellular uptake and cell trafficking of Cop+-FND : siRNA complexes and their ability to selectively suppress mRNA levels, as well as their cytotoxicity, viability and colloidal stability. We identified clathrin-mediated endocytosis as the predominant entry mechanism for Cop+-FND : siRNA into U-2 OS human bone osteosarcoma cells, with a substantial fraction of Cop+-FND : siRNA following the lysosome pathway. Cop+-FND : siRNA potently inhibited the target GAPDH gene with negligible toxicity and sufficient colloidal stability. Based on our results, we suggest that Cop+-FND : siRNA can serve as a suitable in vivo delivery system for siRNA.

Weakly Supervised Identification and Localization of Drug Fingerprints Based on Label-Free Hyperspectral CARS Microscopy.

Understanding drug fingerprints in complex biological samples is essential for the development of a drug. Hyperspectral coherent anti-Stokes Raman scattering (HS-CARS) microscopy, a label-free nondestructive chemical imaging technique, can profile biological samples based on their endogenous vibrational contrast. Here, we propose a deep learning-assisted HS-CARS imaging approach for the investigation of drug fingerprints and their localization at single-cell resolution. To identify and localize drug fingerprints in complex biological systems, an attention-based deep neural network, hyperspectral attention net (HAN), was developed. By formulating the task to a multiple instance learning problem, HAN highlights informative regions through the attention mechanism when being trained on whole-image labels. Using the proposed technique, we investigated the drug fingerprints of a hepatitis B virus therapy in murine liver tissues. With the increase in drug dosage, higher classification accuracy was observed, with an average area under the curve (AUC) of 0.942 for the high-dose group. Besides, highly informative tissue structures predicted by HAN demonstrated a high degree of similarity with the drug localization shown by the in situ hybridization staining results. These results demonstrate the potential of the proposed deep learning-assisted optical imaging technique for the label-free profiling, identification, and localization of drug fingerprints in biological samples, which can be extended to nonperturbative investigations of complex biological systems under various biological conditions.

Quantification of Drugs in Brain and Liver Mimetic Tissue Models Using Raman Spectroscopy.

Quantitative analysis of drug delivery with in biological systems is an integral challenge in drug development. Analytical techniques are important for assessing both drug target delivery, target action, and drug toxicology. Using mimetic tissue models, we have investigated the efficacy of Raman spectroscopy in quantitative detection of alkyne group and deuterated drugs in rat brain and rat liver tissue models. Lasers with 671 nm and 785 nm wavelengths were assessed for their feasibility in this application due to opposing relative benefits and disadvantages. Thin tissue sections have been tested as a practical means of reducing autofluorescent background by minimizing out-of-focus tissue and therefore maximizing photobleaching rates. Alkyne-tagged drugs were quantitatively measured at 18 ± 5 µg/g drug/tissue mass ratio in rat brain and at 34 ± 6 µg/g in rat liver. Quantification calibration curves were generated for a range of concentrations from 0-500 µg/g. These results show the potential of Raman spectroscopy as a diffraction-limited spatially resolved imaging technique for assessing drug delivery in tissue applications.