An Optimized Enzyme-Nucleobase Pair Enables In Vivo RNA Metabolic Labeling with Improved Cell-Specificity.

Current transcriptome-wide analyses have identified a growing number of regulatory RNA with expression that is characterized in a cell-type-specific manner. Herein, we describe RNA metabolic labeling with improved cell-specificity utilizing the in vivo expression of an optimized uracil phosphoribosyltransferase (UPRT) enzyme. We demonstrate improved selectivity for metabolic incorporation of a modified nucleobase (5-vinyuracil) into nascent RNA, using a battery of tests. The selective incorporation of vinyl-U residues was demonstrated in 3xUPRT LM2 cells through validation with dot blot, qPCR, LC-MS/MS and microscopy analysis. We also report using this approach in a metastatic human breast cancer mouse model for profiling cell-specific nascent RNA.

Spatial transcriptomics using combinatorial fluorescence spectral and lifetime encoding, imaging and analysis.

Multiplexed mRNA profiling in the spatial context provides new information enabling basic research and clinical applications. Unfortunately, existing spatial transcriptomics methods are limited due to either low multiplexing or complexity. Here, we introduce a spatialomics technology, termed Multi Omic Single-scan Assay with Integrated Combinatorial Analysis (MOSAICA), that integrates in situ labeling of mRNA and protein markers in cells or tissues with combinatorial fluorescence spectral and lifetime encoded probes, spectral and time-resolved fluorescence imaging, and machine learning-based decoding. We demonstrate MOSAICA's multiplexing scalability in detecting 10-plex targets in fixed colorectal cancer cells using combinatorial labeling of five fluorophores with facile error-detection and removal of autofluorescence. MOSAICA's analysis is strongly correlated with sequencing data (Pearson's r = 0.96) and was further benchmarked using RNAscopeTM and LGC StellarisTM. We further apply MOSAICA for multiplexed analysis of clinical melanoma Formalin-Fixed Paraffin-Embedded (FFPE) tissues. We finally demonstrate simultaneous co-detection of protein and mRNA in cancer cells.

An ultrasensitive test for profiling circulating tumor DNA using integrated comprehensive droplet digital detection.

Current cancer detection systems lack the required sensitivity to reliably detect minimal residual disease (MRD) and recurrence at the earliest stages when treatment would be most effective. To address this issue, we present a novel liquid biopsy approach that utilizes an integrated comprehensive droplet digital detection (IC3D) digital PCR system which combines microfluidic droplet partitioning, fluorescent multiplex PCR chemistry, and our rapid 3D, large-volume droplet counting technology. The IC3D ddPCR assay can detect cancer-specific, ultra-rare genomic targets due to large sample input and high degree of partitioning. We first demonstrate our droplet digital PCR assay can robustly detect common cancer mutants including KRAS G12D spiked in wild-type genomic background or isolated from patient samples with 100% specificity. We then demonstrate that the IC3D ddPCR system can detect oncogenic KRAS G12D mutant alleles against a background of wild-type genomes at a sensitivity of 0.00125-0.005% with a false positive rate of 0% which is 50 to 1000× more sensitive than existing commercial liquid biopsy ddPCR and qPCR platforms, respectively. In addition, our technology can uniquely enable detection of circulating tumor cells using their genetic markers without a pre-enrichment step, and analysis of total tumor DNA isolated from blood samples, which will increase clinical sensitivity and specificity, and minimize inter-assay variability. Therefore, our technology holds the potential to provide clinicians with a powerful decision-making tool to monitor and treat MRD with unprecedented sensitivity for earlier stage intervention.

Programming in situ immunofluorescence intensities through interchangeable reactions of dynamic DNA complexes.

The regulation of antibody reporting intensities is critical to various in situ fluorescence-imaging analyses. Although such control is often necessary to visualize sparse molecular targets, the ability to tune marker intensities is also essential for highly multiplexed imaging strategies in which marker reporting levels must be tuned both to optimize dynamic detection ranges and to minimize crosstalk between different signals. Existing chemical amplification approaches generally lack such control. Here, we demonstrate that linear and branched DNA complexes can be designed to function as interchangeable building blocks that can be assembled into organized, fluorescence-reporting complexes. We show that the ability to program DNA-strand-displacement reactions between these complexes offers new opportunities to deterministically tune the number of dyes that are coupled to individual antibodies in order both to increase and controllably balance marker reporting levels within fixed cells.

Theoretical investigation of the role of the RANK-RANKL-OPG system in bone remodeling.

The RANK-RANKL-OPG system is an essential signaling pathway involved in bone cell-cell communication, with ample evidence that modification of the RANK-RANKL-OPG signaling pathway has major effects on bone remodeling. The first focus of this paper is to demonstrate that a theoretical model of bone cell-cell interactions is capable of qualitatively reproducing changes in bone associated with RANK-RANKL-OPG signaling. To do this we consider either biological experiments or bone diseases related to receptor and/or ligand deficiencies, including RANKL over-expression, ablation of OPG production and/or RANK receptor modifications. The second focus is to investigate a wide range of possible therapeutic strategies for re-establishing bone homeostasis for various pathologies of the RANK-RANKL-OPG pathway. These simulations indicate that bone diseases associated with the RANK-RANKL-OPG pathway are very effective in triggering bone resorption compared to bone formation. These results align with Hofbauer's "convergence hypothesis", which states that catabolic bone diseases most effectively act through the RANK-RANKL-OPG system. Additionally, we demonstrate that severity of catabolic bone diseases strongly depends on how many components of this pathway are affected. Using optimization algorithms and the theoretical model, we identify a variety of successful "virtual therapies" for different disease states using both single and dual therapies.

Model structure and control of bone remodeling: a theoretical study.

It is generally accepted that RANKL is highly expressed in osteoblast precursor cells while OPG is highly expressed in mature osteoblasts, but to date no functional utility to the BMU has been proposed for this particular ligand-decoy-receptor expression profile. As discovered in the mid 90s, the RANK-RANKL-OPG signaling cascade is a major signaling pathway regulating bone remodeling. In this paper we study theoretically the functional implications of particular RANKL/OPG expression profiles on bone volume. For this purpose we formulate an extended bone-cell dynamics model describing functional behaviour of basic multicellular units (BMUs) responsible for bone resorption and formation. This model incorporates the RANK-RANKL-OPG signaling together with the regulating action of TGF-beta on bone cells. The bone-cell population model employed here builds on the work of Lemaire et al. (2004) [1], but incorporates the following significant modifications: (i) addition of a rate equation describing changes in bone volume with time as the key 'output function' tracking functional behaviour of BMUs, (ii) a rate equation describing release of TGF-beta from the bone matrix, (iii) expression of OPG and RANKL on both osteoblastic cell lines, and (iv) modified activator/repressor functions. Using bone volume as a functional selection criterion, we find that there is a preferred arrangement for ligand expression on particular cell types, and further, that this arrangement coincides with biological observations. We then investigate the model parameter space combinatorially, searching for preferred 'groupings' of changes in differentiation rates of various cell types. Again, a criterion of bone volume change is employed to identify possible ways of optimally controlling BMU responses. While some combinations of changes in differentiation rates are clearly unrealistic, other combinations of changes in differentiation rates are potentially functionally significant. Most importantly, the combination of parameter changes representing the signaling pathway for TGF-beta gives a unique result that appears to have a clear biological rationale. The methodological approach for the investigation of model structure described here offers a theoretical explanation as to why TGF-beta has its particular suite of biological effects on bone-cell differentiation rates.