Intracellular Absolute Quantification of Oligonucleotide Therapeutics by NanoSIMS

Abstract

Antisense oligonucleotide (ASO)-based therapeutics hold great potential for the treatment of a variety of diseases. Therefore, a better understanding of cellular delivery, uptake, and trafficking mechanisms of ASOs is highly important for early-stage drug discovery. In particular, understanding the biodistribution and quantifying the abundance of ASOs at the subcellular level are needed to fully characterize their activity. Here, we used a combination of electron microscopy and NanoSIMS to assess the subcellular concentrations of a 34 S-labeled GalNAc-ASO and a naked ASO in the organelles of primary human hepatocytes. We first cross-validated the method by including a 127 I-labeled ASO, finding that the absolute concentration of the lysosomal ASO using two independent labeling strategies gave matching results, demonstrating the strength of our approach. This work also describes the preparation of external standards for absolute quantification by NanoSIMS. For both the 34 S and 127 I approaches used for our quantification methodology, we established the limit of detection (5 and 2 μM, respectively) and the lower limit of quantification (14 and 5 μM, respectively).

Incorporation of Intracellular NanoSIMS Tracers to Oligonucleotide Conjugates via Strain Promoted Sydnone–Alkyne Cycloaddition

“…We have previously developed a methodology for absolute subcellular quantification of 13 C-labeled dopamine, 34 S-labeled GalNAc-ASO, and 127 I-labeled ASO with NanoSIMS. 9,25 The NanoSIMS quantification strategy is built on the fact that the carbon content of the Agar 100 resin (54 M) is homogeneously distributed and matches extremely well with the carbon content of the embedded cell as demonstrated by Thomen et al However, the abundance of rare isotopic or atomic labels in the resin is not known or is below the detection limit of elemental analysis. Thus, to quantify the bromide and iodide labeled ASO, it is necessary to rely on the use of a relative sensitivity factor (RSF) to transform the NanoSIMS ion counts into concentrations.…”

“…We have previously quantified the subcellular concentration of 34 S-labeled ASO conjugated to GalNAc using NanoSIMS. 9 Here we use a MALAT1 ASO labeled with bromides. Bromides give a stronger signal in NanoSIMS compared to 13 C and 34 S and an additional labeling strategy beyond 13 C, 34 S, and iodide.…”

“…No differences in 81 Br − / 13 C 12 C − or 127 I − / 13 C 12 C − ratios were observed between the two tested resins allowing us to use both batches of standards to produce robust standard curves. Our previously published iodide calibration curve was validated 9 and is reported together with the calibration curve for bromide in Figure 3A.…”

“…Hence, developing conjugation chemistries that can integrate NanoSIMS tracers would allow minimal disruption to activity. Designs that incorporate these tracers would, in turn, make it possible to combine the study of both the oligonucleotide component, as previously reported, − but also the dynamic of deconjugation and targeting ligand/linker fate upon cellular internalization using NanoSIMS. In addition, introduction of the imaging label on the linker as part as the conjugation step would be a broadly applicable approach which could circumvent the need for specific targeting ligand labeling/engineering.…”

“…We have synthesized a 34 S-labeled phosphorothioate ASO 8 and developed an analytical sulfur isotope labeling protocol using NanoSIMS imaging to study the distribution of GalNAc-34 S-ASO in hepatocyte spheroids. 9 We have labeled GLP1 peptide with 2,5-diiodotyrosine to explore the subcellular trafficking of both components of GLP1-34 S-ASO conjugate and the impact of conjugate stability on subcellular distribution. 10 However, introduction of imaging labels on the targeting ligand might impair receptor affinity and requires SAR exploration for optimal labeling of any new ligand.…”