LUTHOR HD: Pushing the Boundaries of Single Cell Transcriptome Analysis by in vitro mRNA Amplification
Challenges in Single Cell Transcriptome Analysis
Since its establishment in 2009 , single cell transcriptome experiments became a cornerstone to advance modern biomedical research, drug discovery and developmental biology. A typical single cell transcriptome analysis experiment consists of isolating single cells, followed by library generation and sequencing. The sensitivity of sc-RNA sequencing approaches is limited by the amount of the RNA that can be extracted from single cells, which is typically between 1-50 pg depending on the cell type. Unfortunately, low input RNA, combined with multiple library preparation steps, can cause dropouts: transcripts that are not detected in the sequencing data owing to a failure to capture/amplify them .
Figure 1: Schematic illustration of the THOR amplification method. 
These limitations are caused by the overrepresentation of high copy number transcripts that decreases sequencing resolution and thereby masking low-copy number transcripts. This in turn makes it challenging to fully capture subtypes or intermediate cell states  as these require the detection of more subtle differences in expression patterns, which are often masked by overrepresentation of highly expressed transcripts. The LUTHOR HD technology is a 3’mRNA-seq library preparation method, that can overcome these sensitivity limitations by relying on in vitro mediated RNA amplification of poly(T)-tagged mRNA right at the start of the amplification step .
LUTHOR HD Technology
The LUTHOR HD technology is based on the proprietary THOR amplification method. Traditional sc-RNA-seq library preparation methods are based on transcribing RNA first to cDNA followed by an exponential amplification by PCR. In contrast to traditional approaches, LUTHOR HD amplifies RNA copies directly from the mRNA templates that were isolated from the cell of interest. Through this approach, the amplification process is more linear and manages to capture low copy number transcripts more accurately. In the first step, a primer containing a poly(T), library specific tags (UMI), adaptor and a T7 promoter is annealed to the 3’ end of single stranded RNA. Subsequently, antisense RNA copies are generated using a T7 RNA polymerase. This enables the faithful selection and amplification of polyA tail mRNA without the need of previous enrichment or ribosomal RNA depletion.
Next, the antisense mRNA copies are transcribed into cDNA using random primers containing a 5’ adaptor ensuring strand-specific conversion. The resulting single stranded cDNA library is amplified by PCR thereby introducing Illumina-compatible sequence adaptors and unique indices for next-generation sequencing  (Illustrated in Figure 1).
The sensitivity of the LUTHOR HD kit was tested on a dilution series of total RNA (1-40pg) from DU-145 cells and FACS isolated single DU-145 cells. At a read-depth of 1 mio reads per sample, LUTHOR HD was able to detect transcripts from 12 000 genes at the single cell level and 2000-3000 genes from only 1pg of RNA! Therefore, LUTHOR HD provides the required information depth to perform high-definition gene expression profiling from a minimum amount of input RNA. This addresses the shortcomings of current methods and will reduce the number of drop-out transcripts and increases the resolution of gene expression.
Overall, the LUTHOR HD approach will provide high definition of sc-RNA sequencing experiments, thereby enabling progress in high confidence discovery of cellular heterogeneity.
Figure 2: Gene detection sensitivity at different sequencing depths. At 1 mio reads, 12 000 genes were detected from single cells and approximately 3000 genes from 1pg of purified total RNA. 
Combining the LUTHOR HD approach with Live-seq
Live-seq is a novel scRNA-seq method that enables time-resolved transcriptomics by extracting cytoplasmic biopsies from individual cells while keeping them alive, and thereby enabling repeated sampling from the SAME cell . The Biopsy solution on the FluidFM OMNIUM Platform provides this workflow. The platform enables selection of specific individual cells based on their phenotype and performs cytoplasmic extractions for downstream transcriptome analysis, without requiring cell lysis. Therefore, it is possible to link a cell’s physical appearance with the underlying transcriptome. Current challenges of this approach are to faithfully generate high quality transcriptomics data from approximately 1pg of total RNA. By combining Live-seq with the LUTHOR HD kit, we expect that the current detection capability of Live-seq of 1000-1500 genes could be increased significantly, enabling further applications of both technologies in biomedical research. Meanwhile, it is already feasible to use the OMNIUM Platform to isolate rare cells based on their phenotype.
In combination with the LUTHOR HD kit, researchers can start to explore the transcriptome from rare cells obtained from liquid biopsies or based on phenotypic appearance of individual cells from a heterogeneous culture. Lexogen and Cytosurge are collaborating to adapt the LUTHOR HD approach to cytoplasmic biopsies to increase the robustness and sensitivity to enable a streamlined end-to-end workflow to support live-seq. We expect first results confirming the hypothesis that the LUTHOR HD kit will indeed increase the sensitivity and resolution of Live-seq biopsies at the end of Q1 2024.
 Tang, F. et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 6, 377–382 (2009).
 Kharchenko, P. V. The triumphs and limitations of computational methods for scRNA-seq. Nat Methods 18, 723–732 (2021).
 Haque, A., Engel, J., Teichmann, S. A. & Lönnberg, T. A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications. Genome Med 9, 1–12 (2017).
 Mantas Survila, Pamela Moll, Michael Moldaschl, A. & Reda, T. Application note LUTHOR HD : High-definition single-cell gene expression analyses. Nat Methods 5–7 (2023).
 Chen, W. et al. Live-seq enables temporal transcriptomic recording of single cells. Nature 608, 733–740 (2022).