An Optimized Tissue Dissociation Protocol for Single-Cell RNA Sequencing Analysis of Fresh and Cultured Human Skin Biopsies

Advances in long-read single-cell transcriptomics

Long-read single-cell transcriptomics (scRNA-Seq) is revolutionizing the way we profile heterogeneity in disease. Traditional short-read scRNA-Seq methods are limited in their ability to provide complete transcript coverage, resolve isoforms, and identify novel transcripts. The scRNA-Seq protocols developed for long-read sequencing platforms overcome these limitations by enabling the characterization of full-length transcripts. Long-read scRNA-Seq techniques initially suffered from comparatively poor accuracy compared to short read scRNA-Seq. However, with improvements in accuracy, accessibility, and cost efficiency, long-reads are gaining popularity in the field of scRNA-Seq. This review details the advances in long-read scRNA-Seq, with an emphasis on library preparation protocols and downstream bioinformatics analysis tools.

Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges

Single-cell RNA sequencing (scRNA-Seq) is a recent technology that allows for the measurement of the expression of all genes in each individual cell contained in a sample. Information at the single-cell level has been shown to be extremely useful in many areas. However, performing single-cell experiments is expensive. Although cellular deconvolution cannot provide the same comprehensive information as single-cell experiments, it can extract cell-type information from bulk RNA data, and therefore it allows researchers to conduct studies at cell-type resolution from existing bulk datasets. For these reasons, a great effort has been made to develop such methods for cellular deconvolution. The large number of methods available, the requirement of coding skills, inadequate documentation, and lack of performance assessment all make it extremely difficult for life scientists to choose a suitable method for their experiment. This paper aims to fill this gap by providing a comprehensive review of 53 deconvolution methods regarding their methodology, applications, performance, and outstanding challenges. More importantly, the article presents a benchmarking of all these 53 methods using 283 cell types from 30 tissues of 63 individuals. We also provide an R package named DeconBenchmark that allows readers to execute and benchmark the reviewed methods (https://github.com/tinnlab/DeconBenchmark).

Optimization of Tissue Digestion Methods for Characterization of Photoaged Skin by Single Cell RNA Sequencing Reveals Preferential Enrichment of T Cell Subsets

Healthy human skin tissue is often used as a control for comparison to diseased skin in patients with skin pathologies, including skin cancers or other inflammatory conditions such as atopic dermatitis or psoriasis. Although non-affected skin from these patients is a more appropriate choice for comparison, there is a paucity of studies examining such tissue. This lack is exacerbated by the difficulty of processing skin tissue for experimental analysis. In addition, choosing a processing protocol for skin tissue which preserves cell viability and identity while sufficiently dissociating cells for single-cell analysis is not a trivial task. Here, we compare three digestion methods for human skin tissue, evaluating the cell yield and viability for each protocol. We find that the use of a sequential dissociation method with multiple enzymatic digestion steps produces the highest cell viability. Using single-cell sequencing, we show this method results in a relative increase in the proportion of non-antigen-presenting mast cells and CD8 T cells as well as a relative decrease in the proportion of antigen-presenting mast cells and KYNU+ CD4 T cells. Overall, our findings support the use of this sequential digestion method on freshly processed human skin samples for optimal cell yield and viability.

Viable tendon neotissue from adult adipose-derived multipotent stromal cells

Background: Tendon healing is frequently prolonged, unpredictable, and results in poor tissue quality. Neotissue formed by adult multipotent stromal cells has the potential to guide healthy tendon tissue formation. Objectives: The objective of this study was to characterize tendon neotissue generated by equine adult adipose-derived multipotent stromal cells (ASCs) on collagen type I (COLI) templates under 10% strain in a novel bioreactor. The tested hypothesis was that ASCs assume a tendon progenitor cell-like morphology, express tendon-related genes, and produce more organized extracellular matrix (ECM) in tenogenic versus stromal medium with perfusion and centrifugal fluid motion. Methods: Equine ASCs on COLI sponge cylinders were cultured in stromal or tenogenic medium within bioreactors during combined perfusion and centrifugal fluid motion for 7, 14, or 21 days under 10% strain. Viable cell distribution and number, tendon-related gene expression, and micro- and ultra-structure were evaluated with calcein-AM/EthD-1 staining, resazurin reduction, RT-PCR, and light, transmission, and scanning electron microscopy. Fibromodulin was localized with immunohistochemistry. Cell number and gene expression were compared between culture media and among culture periods (p < 0.05). Results: Viable cells were distributed throughout constructs for up to 21 days of culture, and cell numbers were higher in tenogenic medium. Individual cells had a round or rhomboid shape with scant ECM in stromal medium in contrast to clusters of parallel, elongated cells surrounded by highly organized ECM in tenogenic medium after 21 days of culture. Transcription factor, extracellular matrix, and mature tendon gene expression profiles confirmed ASC differentiation to a tendon progenitor-like cell in tenogenic medium. Construct micro- and ultra-structure were consistent with tendon neotissue and fibromodulin was present in the ECM after culture in tenogenic medium. Conclusion: Long-term culture in custom bioreactors with combined perfusion and centrifugal tenogenic medium circulation supports differentiation of equine adult ASCs into tendon progenitor-like cells capable of neotissue formation.

Investigative needle core biopsies for multi-omics in Glioblastoma

Glioblastoma (GBM) is a primary brain cancer with an abysmal prognosis and few effective therapies. The ability to investigate the tumor microenvironment before and during treatment would greatly enhance both understanding of disease response and progression, as well as the delivery and impact of therapeutics. Stereotactic biopsies are a routine surgical procedure performed primarily for diagnostic histopathologic purposes. The role of investigative biopsies - tissue sampling for the purpose of understanding tumor microenvironmental responses to treatment using integrated multi-modal molecular analyses ('Multi-omics") has yet to be defined. Secondly, it is unknown whether comparatively small tissue samples from brain biopsies can yield sufficient information with such methods. Here we adapt stereotactic needle core biopsy tissue in two separate patients. In the first patient with recurrent GBM we performed highly resolved multi-omics analysis methods including single cell RNA sequencing, spatial-transcriptomics, metabolomics, proteomics, phosphoproteomics, T-cell clonotype analysis, and MHC Class I immunopeptidomics from biopsy tissue that was obtained from a single procedure. In a second patient we analyzed multi-regional core biopsies to decipher spatial and genomic variance. We also investigated the utility of stereotactic biopsies as a method for generating patient derived xenograft models in a separate patient cohort. Dataset integration across modalities showed good correspondence between spatial modalities, highlighted immune cell associated metabolic pathways and revealed poor correlation between RNA expression and the tumor MHC Class I immunopeptidome. In conclusion, stereotactic needle biopsy cores are of sufficient quality to generate multi-omics data, provide data rich insight into a patient's disease process and tumor immune microenvironment and can be of value in evaluating treatment responses.

One sentence summary

Integrative multi-omics analysis of stereotactic needle core biopsies in glioblastoma.

Methanol fixation is the method of choice for droplet-based single-cell transcriptomics of neural cells

The main critical step in single-cell transcriptomics is sample preparation. Several methods have been developed to preserve cells after dissociation to uncouple sample handling from library preparation. Yet, the suitability of these methods depends on the cell types to be processed. In this project, we perform a systematic comparison of preservation methods for droplet-based single-cell RNA-seq on neural and glial cells derived from induced pluripotent stem cells. Our results show that while DMSO provides the highest cell quality in terms of RNA molecules and genes detected per cell, it strongly affects the cellular composition and induces the expression of stress and apoptosis genes. In contrast, methanol fixed samples display a cellular composition similar to fresh samples and provide a good cell quality and little expression biases. Taken together, our results show that methanol fixation is the method of choice for performing droplet-based single-cell transcriptomics experiments on neural cell populations.

Decoding the Human Epidermal Complexity at Single-Cell Resolution

The epidermis is one of the largest tissues in the human body, serving as a protective barrier. The basal layer of the epidermis, which consists of epithelial stem cells and transient amplifying progenitors, represents its proliferative compartment. As keratinocytes migrate from the basal layer to the skin surface, they exit the cell cycle and initiate terminal differentiation, ultimately generating the suprabasal epidermal layers. A deeper understanding of the molecular mechanisms and pathways driving keratinocytes' organization and regeneration is essential for successful therapeutic approaches. Single-cell techniques are valuable tools for studying molecular heterogeneity. The high-resolution characterization obtained with these technologies has identified disease-specific drivers and new therapeutic targets, further promoting the advancement of personalized therapies. This review summarizes the latest findings on the transcriptomic and epigenetic profiling of human epidermal cells, analyzed from human biopsy or after in vitro cultivation, focusing on physiological, wound healing, and inflammatory skin conditions.

Revisiting the significance of keratin expression in complex epithelia

A large group of keratin genes (n=54 in the human genome) code for intermediate filament (IF)-forming proteins and show differential regulation in epithelial cells and tissues. Keratin expression can be highly informative about the type of epithelial tissue, differentiation status of constituent cells and biological context (e.g. normal versus diseased settings). The foundational principles underlying the use of keratin expression to gain insight about epithelial cells and tissues primarily originated in pioneering studies conducted in the 1980s. The recent emergence of single cell transcriptomics provides an opportunity to revisit these principles and gain new insight into epithelial biology. Re-analysis of single-cell RNAseq data collected from human and mouse skin has confirmed long-held views regarding the quantitative importance and pairwise regulation of specific keratin genes in keratinocytes of surface epithelia. Furthermore, such analyses confirm and extend the notion that changes in keratin gene expression occur gradually as progenitor keratinocytes commit to and undergo differentiation, and challenge the prevailing assumption that specific keratin combinations reflect a mitotic versus a post-mitotic differentiating state. Our findings provide a blueprint for similar analyses in other tissues, and warrant a more nuanced approach in the use of keratin genes as biomarkers in epithelia.