Dissociation of solid tumor tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

NBAtlas: A harmonized single-cell transcriptomic reference atlas of human neuroblastoma tumors

Neuroblastoma, a rare embryonic tumor arising from neural crest development, is responsible for 15% of pediatric cancer-related deaths. Recently, several single-cell transcriptome studies were performed on neuroblastoma patient samples to investigate the cell of origin and tumor heterogeneity. However, these individual studies involved a small number of tumors and cells, limiting the conclusions that could be drawn. To overcome this limitation, we integrated seven single-cell or single-nucleus datasets into a harmonized cell atlas covering 362,991 cells across 61 patients. We use this atlas to decipher the transcriptional landscape of neuroblastoma at single-cell resolution, revealing associations between transcriptomic profiles and clinical outcomes within the tumor compartment. In addition, we characterize the complex immune-cell landscape and uncover considerable heterogeneity among tumor-associated macrophages. Finally, we showcase the utility of our atlas as a resource by expanding it with additional data and using it as a reference for data-driven cell-type annotation.

Community assessment of methods to deconvolve cellular composition from bulk gene expression

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics

Single-cell transcriptomics has broadened our understanding of cellular diversity and gene expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has emerged as a tool to contextualize single cells in multicellular neighbourhoods and to identify spatially recurrent phenotypes, or ecotypes. These technologies have generated vast datasets with targeted-transcriptome and whole-transcriptome profiles of hundreds to millions of cells. Such data have provided new insights into developmental hierarchies, cellular plasticity and diverse tissue microenvironments, and spurred a burst of innovation in computational methods for single-cell analysis. In this Review, we discuss recent advancements, ongoing challenges and prospects in identifying and characterizing cell states and multicellular neighbourhoods. We discuss recent progress in sample processing, data integration, identification of subtle cell states, trajectory modelling, deconvolution and spatial analysis. Furthermore, we discuss the increasing application of deep learning, including foundation models, in analysing single-cell and spatial transcriptomics data. Finally, we discuss recent applications of these tools in the fields of stem cell biology, immunology, and tumour biology, and the future of single-cell and spatial transcriptomics in biological research and its translation to the clinic.

Dissection of triple-negative breast cancer microenvironment and identification of potential therapeutic drugs using single-cell RNA sequencing analysis

Breast cancer remains a leading cause of mortality in women worldwide. Triple-negative breast cancer (TNBC) is a particularly aggressive subtype characterized by rapid progression, poor prognosis, and lack of clear therapeutic targets. In the clinic, delineation of tumor heterogeneity and development of effective drugs continue to pose considerable challenges. Within the scope of our study, high heterogeneity inherent to breast cancer was uncovered based on the landscape constructed from both tumor and healthy breast tissue samples. Notably, TNBC exhibited significant specificity regarding cell proliferation, differentiation, and disease progression. Significant associations between tumor grade, prognosis, and TNBC oncogenes were established via pseudotime trajectory analysis. Consequently, we further performed comprehensive characterization of the TNBC microenvironment. A crucial epithelial subcluster, E8, was identified as highly malignant and strongly associated with tumor cell proliferation in TNBC. Additionally, epithelial-mesenchymal transition (EMT)-associated fibroblast and M2 macrophage subclusters exerted an influence on E8 through cellular interactions, contributing to tumor growth. Characteristic genes in these three cluster cells could therefore serve as potential therapeutic targets for TNBC. The collective findings provided valuable insights that assisted in the screening of a series of therapeutic drugs, such as pelitinib. We further confirmed the anti-cancer effect of pelitinib in an orthotopic 4T1 tumor-bearing mouse model. Overall, our study sheds light on the unique characteristics of TNBC at single-cell resolution and the crucial cell types associated with tumor cell proliferation that may serve as potent tools in the development of effective anti-cancer drugs.

Pan-cancer profiling of tumor-infiltrating natural killer cells through transcriptional reference mapping

The functional diversity of natural killer (NK) cell repertoires stems from differentiation, homeostatic, receptor-ligand interactions and adaptive-like responses to viral infections. In the present study, we generated a single-cell transcriptional reference map of healthy human blood- and tissue-derived NK cells, with temporal resolution and fate-specific expression of gene-regulatory networks defining NK cell differentiation. Transfer learning facilitated incorporation of tumor-infiltrating NK cell transcriptomes (39 datasets, 7 solid tumors, 427 patients) into the reference map to analyze tumor microenvironment (TME)-induced perturbations. Of the six functionally distinct NK cell states identified, a dysfunctional stressed CD56bright state susceptible to TME-induced immunosuppression and a cytotoxic TME-resistant effector CD56dim state were commonly enriched across tumor types, the ratio of which was predictive of patient outcome in malignant melanoma and osteosarcoma. This resource may inform the design of new NK cell therapies and can be extended through transfer learning to interrogate new datasets from experimental perturbations or disease conditions.

Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

BACKGROUND

The encoding of cell intrinsic drug resistance states in breast cancer reflects the contributions of genomic and non-genomic variations and requires accurate estimation of clonal fitness from co-measurement of transcriptomic and genomic data. Somatic copy number (CN) variation is the dominant mutational mechanism leading to transcriptional variation and notably contributes to platinum chemotherapy resistance cell states. Here, we deploy time series measurements of triple negative breast cancer (TNBC) single-cell transcriptomes, along with co-measured single-cell CN fitness, identifying genomic and transcriptomic mechanisms in drug-associated transcriptional cell states.

RESULTS

We present scRNA-seq data (53,641 filtered cells) from serial passaging TNBC patient-derived xenograft (PDX) experiments spanning 2.5 years, matched with genomic single-cell CN data from the same samples. Our findings reveal distinct clonal responses within TNBC tumors exposed to platinum. Clones with high drug fitness undergo clonal sweeps and show subtle transcriptional reversion, while those with weak fitness exhibit dynamic transcription upon drug withdrawal. Pathway analysis highlights convergence on epithelial-mesenchymal transition and cytokine signaling, associated with resistance. Furthermore, pseudotime analysis demonstrates hysteresis in transcriptional reversion, indicating generation of new intermediate transcriptional states upon platinum exposure.

CONCLUSIONS

Within a polyclonal tumor, clones with strong genotype-associated fitness under platinum remained fixed, minimizing transcriptional reversion upon drug withdrawal. Conversely, clones with weaker fitness display non-genomic transcriptional plasticity. This suggests CN-associated and CN-independent transcriptional states could both contribute to platinum resistance. The dominance of genomic or non-genomic mechanisms within polyclonal tumors has implications for drug sensitivity, restoration, and re-treatment strategies.

Substantive Similarities Between Synovial Fluid and Synovial Tissue T cells in Inflammatory Arthritis Via Single-Cell RNA and T cell Receptor Sequencing

OBJECTIVE

Synovial fluid (SF)-derived T cells are frequently studied as a proxy for investigating the synovial tissue (ST) T cell infiltrate in inflammatory arthritis. However, because ST is the primary site of inflammatory activity, there is debate as to whether SF provides a true reflection of the ST T cell population.

METHODS

In this study, we used single-cell RNA sequencing paired with single-cell T cell receptor (TCR) sequencing to directly compare memory T cells from paired samples of SF and ST from six patients with inflammatory arthritis to investigate their similarity in terms of TCR repertoire and T cell subset composition.

RESULTS

The TCR repertoires of SF and ST T cells were strikingly similar, particularly for CD8+ T cells. A median of 49% of the total CD8+ TCR repertoire in SF was shared with ST, compared with 20% shared with blood. Similarly, 47% of the ST CD8+ TCR repertoire was shared with SF compared to 25% with blood. Furthermore, once the effect of collagenase digestion on gene expression by ST T cells had been accounted for, the frequencies of specific CD8+ and CD4+ T cell subsets were, in general, similar in SF and ST and were distinct from blood.

CONCLUSION

Our results suggest that T cells migrate and equilibrate between the SF and ST and maintain similar phenotypes in both sites. We conclude that SF is an appropriate proxy for investigating the T cell infiltrate in inflamed synovium, particularly in terms of investigating the TCR repertoire.

Identification of New Markers of Angiogenic Sprouting Using Transcriptomics: New Role for RND3

BACKGROUND

New blood vessel formation requires endothelial cells to transition from a quiescent to an invasive phenotype. Transcriptional changes are vital for this switch, but a comprehensive genome-wide approach focused exclusively on endothelial cell sprout initiation has not been reported.

METHODS

Using a model of human endothelial cell sprout initiation, we developed a protocol to physically separate cells that initiate the process of new blood vessel formation (invading cells) from noninvading cells. We used this model to perform multiple transcriptomics analyses from independent donors to monitor endothelial gene expression changes.

RESULTS

Single-cell population analyses, single-cell cluster analyses, and bulk RNA sequencing revealed common transcriptomic changes associated with invading cells. We also found that collagenase digestion used to isolate single cells upregulated the Fos proto-oncogene transcription factor. Exclusion of Fos proto-oncogene expressing cells revealed a gene signature consistent with activation of signal transduction, morphogenesis, and immune responses. Many of the genes were previously shown to regulate angiogenesis and included multiple tip cell markers. Upregulation of SNAI1 (snail family transcriptional repressor 1), PTGS2 (prostaglandin synthase 2), and JUNB (JunB proto-oncogene) protein expression was confirmed in invading cells, and silencing JunB and SNAI1 significantly reduced invasion responses. Separate studies investigated rounding 3, also known as RhoE, which has not yet been implicated in angiogenesis. Silencing rounding 3 reduced endothelial invasion distance as well as filopodia length, fitting with a pathfinding role for rounding 3 via regulation of filopodial extensions. Analysis of in vivo retinal angiogenesis in Rnd3 heterozygous mice confirmed a decrease in filopodial length compared with wild-type littermates.

CONCLUSIONS

Validation of multiple genes, including rounding 3, revealed a functional role for this gene signature early in the angiogenic process. This study expands the list of genes associated with the acquisition of a tip cell phenotype during endothelial cell sprout initiation.

Single-cell and single-nucleus RNA-sequencing from paired normal-adenocarcinoma lung samples provide both common and discordant biological insights

Whether single-cell RNA-sequencing (scRNA-seq) captures the same biological information as single-nucleus RNA-sequencing (snRNA-seq) remains uncertain and likely to be context-dependent. Herein, a head-to-head comparison was performed in matched normal-adenocarcinoma human lung samples to assess biological insights derived from scRNA-seq versus snRNA-seq and better understand the cellular transition that occurs from normal to tumoral tissue. Here, the transcriptome of 160,621 cells/nuclei was obtained. In non-tumor lung, cell type proportions varied widely between scRNA-seq and snRNA-seq with a predominance of immune cells in the former (81.5%) and epithelial cells (69.9%) in the later. Similar results were observed in adenocarcinomas, in addition to an overall increase in cell type heterogeneity and a greater prevalence of copy number variants in cells of epithelial origin, which suggests malignant assignment. The cell type transition that occurs from normal lung tissue to adenocarcinoma was not always concordant whether cells or nuclei were examined. As expected, large differential expression of the whole-cell and nuclear transcriptome was observed, but cell-type specific changes of paired normal and tumor lung samples revealed a set of common genes in the cells and nuclei involved in cancer-related pathways. In addition, we showed that the ligand-receptor interactome landscape of lung adenocarcinoma was largely different whether cells or nuclei were evaluated. Immune cell depletion in fresh specimens partly mitigated the difference in cell type composition observed between cells and nuclei. However, the extra manipulations affected cell viability and amplified the transcriptional signatures associated with stress responses. In conclusion, research applications focussing on mapping the immune landscape of lung adenocarcinoma benefit from scRNA-seq in fresh samples, whereas snRNA-seq of frozen samples provide a low-cost alternative to profile more epithelial and cancer cells, and yield cell type proportions that more closely match tissue content.

Dissociation protocols influence the phenotypes of lymphocyte and myeloid cell populations isolated from the neonatal lymph node

Frequencies and phenotypes of immune cells differ between neonates and adults in association with age-specific immune responses. Lymph nodes (LN) are critical tissue sites to quantify and define these differences. Advances in flow cytometry have enabled more multifaceted measurements of complex immune responses. Tissue processing can affect the immune cells under investigation that influence key findings. To understand the impact on immune cells in the LN after processing for single-cell suspension, we compared three dissociation protocols: enzymatic digestion, mechanical dissociation with DNase I treatment, and mechanical dissociation with density gradient separation. We analyzed cell yields, viability, phenotypic and maturation markers of immune cells from the lung-draining LN of neonatal and adult mice two days after intranasal respiratory syncytial virus (RSV) infection. While viability was consistent across age groups, the protocols influenced the yield of subsets defined by important phenotypic and activation markers. Moreover, enzymatic digestion did not show higher overall yields of conventional dendritic cells and macrophages from the LN. Together, our findings show that the three dissociation protocols have similar impacts on the number and viability of cells isolated from the neonatal and adult LN. However, enzymatic digestion impacts the mean fluorescence intensity of key lineage and activation markers that may influence experimental findings.

Evolution of chromosome-arm aberrations in breast cancer through genetic network rewiring

The basal breast cancer subtype is enriched for triple-negative breast cancer (TNBC) and displays consistent large chromosomal deletions. Here, we characterize evolution and maintenance of chromosome 4p (chr4p) loss in basal breast cancer. Analysis of The Cancer Genome Atlas data shows recurrent deletion of chr4p in basal breast cancer. Phylogenetic analysis of a panel of 23 primary tumor/patient-derived xenograft basal breast cancers reveals early evolution of chr4p deletion. Mechanistically we show that chr4p loss is associated with enhanced proliferation. Gene function studies identify an unknown gene, C4orf19, within chr4p, which suppresses proliferation when overexpressed-a member of the PDCD10-GCKIII kinase module we name PGCKA1. Genome-wide pooled overexpression screens using a barcoded library of human open reading frames identify chromosomal regions, including chr4p, that suppress proliferation when overexpressed in a context-dependent manner, implicating network interactions. Together, these results shed light on the early emergence of complex aneuploid karyotypes involving chr4p and adaptive landscapes shaping breast cancer genomes.

Single-cell RNA sequencing of cells from fresh or frozen tissue reveals a signature of freezing marked by heightened stress and activation

Thawing of viably frozen human tissue T cells, ILCs, and NK cells and subsequent single-cell RNA sequencing reveals that recovery of cellular subclusters is variably impacted. While freeze-thawing does not alter the transcriptional profiles of cells, it upregulates genes and gene pathways associated with stress and activation.

FixNCut: single-cell genomics through reversible tissue fixation and dissociation

The use of single-cell technologies for clinical applications requires disconnecting sampling from downstream processing steps. Early sample preservation can further increase robustness and reproducibility by avoiding artifacts introduced during specimen handling. We present FixNCut, a methodology for the reversible fixation of tissue followed by dissociation that overcomes current limitations. We applied FixNCut to human and mouse tissues to demonstrate the preservation of RNA integrity, sequencing library complexity, and cellular composition, while diminishing stress-related artifacts. Besides single-cell RNA sequencing, FixNCut is compatible with multiple single-cell and spatial technologies, making it a versatile tool for robust and flexible study designs.

Microfluidic platform for omics analysis on single cells with diverse morphology and size: A review

BACKGROUND

Microfluidic techniques have emerged as powerful tools in single-cell research, facilitating the exploration of omics information from individual cells. Cell morphology is crucial for gene expression and physiological processes. However, there is currently a lack of integrated analysis of morphology and single-cell omics information. A critical challenge remains: what platform technologies are the best option to decode omics data of cells that are complex in morphology and size?

RESULTS

This review highlights achievements in microfluidic-based single-cell omics and isolation of cells based on morphology, along with other cell sorting methods based on physical characteristics. Various microfluidic platforms for single-cell isolation are systematically presented, showcasing their diversity and adaptability. The discussion focuses on microfluidic devices tailored to the distinct single-cell isolation requirements in plants and animals, emphasizing the significance of considering cell morphology and cell size in optimizing single-cell omics strategies. Simultaneously, it explores the application of microfluidic single-cell sorting technologies to single-cell sequencing, aiming to effectively integrate information about cell shape and size.

SIGNIFICANCE AND NOVELTY

The novelty lies in presenting a comprehensive overview of recent accomplishments in microfluidic-based single-cell omics, emphasizing the integration of different microfluidic platforms and their implications for cell morphology-based isolation. By underscoring the pivotal role of the specialized morphology of different cells in single-cell research, this review provides robust support for delving deeper into the exploration of single-cell omics data.

Rebuilding the microenvironment of primary tumors in humans: a focus on stroma

Conventional tumor models have critical shortcomings in that they lack the complexity of the human stroma. The heterogeneous stroma is a central compartment of the tumor microenvironment (TME) that must be addressed in cancer research and precision medicine. To fully model the human tumor stroma, the deconstruction and reconstruction of tumor tissues have been suggested as new approaches for in vitro tumor modeling. In this review, we summarize the heterogeneity of tumor-associated stromal cells and general deconstruction approaches used to isolate patient-specific stromal cells from tumor tissue; we also address the effect of the deconstruction procedure on the characteristics of primary cells. Finally, perspectives on the future of reconstructed tumor models are discussed, with an emphasis on the essential prerequisites for developing authentic humanized tumor models.

Applications of single-cell omics for chimeric antigen receptor T cell therapy

Chimeric antigen receptor (CAR) T cell therapy is a promising cancer treatment modality. The breakthroughs in CAR T cell therapy were, in part, possible with the help of cell analysis methods, such as single-cell analysis. Bulk analyses have provided invaluable information regarding the complex molecular dynamics of CAR T cells, but their results are an average of thousands of signals in CAR T or tumour cells. Since cancer is a heterogeneous disease where each minute detail of a subclone could change the outcome of the treatment, single-cell analysis could prove to be a powerful instrument in deciphering the secrets of tumour microenvironment for cancer immunotherapy. With the recent studies in all aspects of adoptive cell therapy making use of single-cell analysis, a comprehensive review of the recent preclinical and clinical findings in CAR T cell therapy was needed. Here, we categorized and summarized the key points of the studies in which single-cell analysis provided insights into the genomics, epigenomics, transcriptomics and proteomics as well as their respective multi-omics of CAR T cell therapy.

Single-cell transcriptomics dissects premalignant progression in proliferative verrucous leukoplakia

OBJECTIVE

Proliferative verrucous leukoplakia (PVL) is characterized by a spectrum of clinicopathological features and a high risk of malignant transformation. In this study, we aimed to delineate the dynamic changes in molecular signature during PVL progression and identify the potential cell subtypes that play a key role in the premalignant evolution of PVL.

METHODS

We performed single-cell RNA sequencing on three biopsy samples from a large PVL lesion. These samples exhibited a histopathological continuum of PVL progression.

RESULTS

By analyzing the transcriptome profiles of 27,611 cells from these samples, we identified ten major cell lineages and revealed that cellular remodeling occurred during the progression of PVL lesions, including epithelial, stromal, and immune cells. Epithelial cells are shifted to tumorigenic states and secretory patterns at the premalignant stage. Immune cells showed growing immunosuppressive phenotypes during PVL progression. Remarkably, two novel cell subtypes INSR+ endothelial cells and ASPN+ fibroblasts, were discovered and may play vital roles in microenvironment remodeling, such as angiogenesis and stromal fibrosis, which are closely involved in malignant transformation.

CONCLUSION

Our work is the first to depict the cellular landscape of PVL and speculate that disease progression may be driven by functional remodeling of multiple cell subtypes.

A human stomach cell type transcriptome atlas

BACKGROUND

The identification of cell type-specific genes and their modification under different conditions is central to our understanding of human health and disease. The stomach, a hollow organ in the upper gastrointestinal tract, provides an acidic environment that contributes to microbial defence and facilitates the activity of secreted digestive enzymes to process food and nutrients into chyme. In contrast to other sections of the gastrointestinal tract, detailed descriptions of cell type gene enrichment profiles in the stomach are absent from the major single-cell sequencing-based atlases.

RESULTS

Here, we use an integrative correlation analysis method to predict human stomach cell type transcriptome signatures using unfractionated stomach RNAseq data from 359 individuals. We profile parietal, chief, gastric mucous, gastric enteroendocrine, mitotic, endothelial, fibroblast, macrophage, neutrophil, T-cell, and plasma cells, identifying over 1600 cell type-enriched genes.

CONCLUSIONS

We uncover the cell type expression profile of several non-coding genes strongly associated with the progression of gastric cancer and, using a sex-based subset analysis, uncover a panel of male-only chief cell-enriched genes. This study provides a roadmap to further understand human stomach biology.

The activator protein-1 complex governs a vascular degenerative transcriptional programme in smooth muscle cells to trigger aortic dissection and rupture

BACKGROUND AND AIMS

Stanford type A aortic dissection (AD) is a degenerative aortic remodelling disease marked by an exceedingly high mortality without effective pharmacologic therapies. Smooth muscle cells (SMCs) lining tunica media adopt a range of states, and their transformation from contractile to synthetic phenotypes fundamentally triggers AD. However, the underlying pathomechanisms governing this population shift and subsequent AD, particularly at distinct disease temporal stages, remain elusive.

METHODS

Ascending aortas from nine patients undergoing ascending aorta replacement and five individuals undergoing heart transplantation were subjected to single-cell RNA sequencing. The pathogenic targets governing the phenotypic switch of SMCs were identified by trajectory inference, functional scoring, single-cell regulatory network inference and clustering, regulon, and interactome analyses and confirmed using human ascending aortas, primary SMCs, and a β-aminopropionitrile monofumarate-induced AD model.

RESULTS

The transcriptional profiles of 93 397 cells revealed a dynamic temporal-specific phenotypic transition and marked elevation of the activator protein-1 (AP-1) complex, actively enabling synthetic SMC expansion. Mechanistically, tumour necrosis factor signalling enhanced AP-1 transcriptional activity by dampening mitochondrial oxidative phosphorylation (OXPHOS). Targeting this axis with the OXPHOS enhancer coenzyme Q10 or AP-1-specific inhibitor T-5224 impedes phenotypic transition and aortic degeneration while improving survival by 42.88% (58.3%-83.3% for coenzyme Q10 treatment), 150.15% (33.3%-83.3% for 2-week T-5224), and 175.38% (33.3%-91.7% for 3-week T-5224) in the β-aminopropionitrile monofumarate-induced AD model.

CONCLUSIONS

This cross-sectional compendium of cellular atlas of human ascending aortas during AD progression provides previously unappreciated insights into a transcriptional programme permitting aortic degeneration, highlighting a translational proof of concept for an anti-remodelling intervention as an attractive strategy to manage temporal-specific AD by modulating the tumour necrosis factor-OXPHOS-AP-1 axis.

Cancer Cell Silicification and Surface Functionalization to Create Microbial Mimetic Cancer Vaccines

As cancer progresses, tumor cells adapt to evade immune cells. To counter this, cancer cells can be silicified ex vivo, creating surface masks that can be decorated with microbial-associated molecules that are readily recognized by antigen-presenting cells (APCs). The transformation process renders the tumor cells nonviable and preserves the integrity of the cell and associated tumor antigens. The resulting personalized cancer vaccine, when returned to the patient, engages molecules on the surface of APC, activating signaling pathways that lead to immune cell activation, vaccine internalization, processing of tumor antigens, and major histocompatibility complex peptide presentation to T cells. The cancer-specific T cells then circulate throughout the body, killing tumor cells. This chapter presents detailed methods for the cryogenic precipitation of silica on cellular structures (cryo-silicification), creating vaccines that are potent immune activators. Further, silicified cells can be dehydrated for shelf storage, eliminating the need for costly cryogenic storage.

Protocol to dissociate epithelia from non-pregnant and pregnant mouse cervical tissue for single-cell RNA-sequencing

A challenge in studying cervical epithelial cell biology at the single-cell level is that differentiated subtypes, in particular mucus-secreting goblet cells, are sensitive to disassociating enzymes making isolation of all epithelial subpopulations difficult. Here we present a protocol to dissociate epithelia from non-pregnant and pregnant mouse cervical tissue for single-cell RNA-sequencing. We describe steps for harvesting cervices, preparing cervical tissue, dissociation of cervical cells, and viability checks. We then detail library preparation, sequencing, and procedure for data analysis. For complete details on the use and execution of this protocol, please refer to Cooley et al. (2023).1.

Single-cell RNA sequencing in osteoarthritis

Osteoarthritis is a progressive and heterogeneous joint disease with complex pathogenesis. The various phenotypes associated with each patient suggest that better subgrouping of tissues associated with genotypes in different phases of osteoarthritis may provide new insights into the onset and progression of the disease. Recently, single-cell RNA sequencing was used to describe osteoarthritis pathogenesis on a high-resolution view surpassing traditional technologies. Herein, this review summarizes the microstructural changes in articular cartilage, meniscus, synovium and subchondral bone that are mainly due to crosstalk amongst chondrocytes, osteoblasts, fibroblasts and endothelial cells during osteoarthritis progression. Next, we focus on the promising targets discovered by single-cell RNA sequencing and its potential applications in target drugs and tissue engineering. Additionally, the limited amount of research on the evaluation of bone-related biomaterials is reviewed. Based on the pre-clinical findings, we elaborate on the potential clinical values of single-cell RNA sequencing for the therapeutic strategies of osteoarthritis. Finally, a perspective on the future development of patient-centred medicine for osteoarthritis therapy combining other single-cell multi-omics technologies is discussed. This review will provide new insights into osteoarthritis pathogenesis on a cellular level and the field of applications of single-cell RNA sequencing in personalized therapeutics for osteoarthritis in the future.

Divergent molecular networks program functionally distinct CD8+ skin-resident memory T cells

Skin-resident CD8+ T cells include distinct interferon-γ-producing [tissue-resident memory T type 1 (TRM1)] and interleukin-17 (IL-17)-producing (TRM17) subsets that differentially contribute to immune responses. However, whether these populations use common mechanisms to establish tissue residence is unknown. In this work, we show that TRM1 and TRM17 cells navigate divergent trajectories to acquire tissue residency in the skin. TRM1 cells depend on a T-bet-Hobit-IL-15 axis, whereas TRM17 cells develop independently of these factors. Instead, c-Maf commands a tissue-resident program in TRM17 cells parallel to that induced by Hobit in TRM1 cells, with an ICOS-c-Maf-IL-7 axis pivotal to TRM17 cell commitment. Accordingly, by targeting this pathway, skin TRM17 cells can be ablated without compromising their TRM1 counterparts. Thus, skin-resident T cells rely on distinct molecular circuitries, which can be exploited to strategically modulate local immunity.

Molecular traces of Drosophila hemocytes reveal transcriptomic conservation with vertebrate myeloid cells

Drosophila hemocytes serve as the primary defense system against harmful threats, allowing the animals to thrive. Hemocytes are often compared to vertebrate innate immune system cells due to the observed functional similarities between the two. However, the similarities have primarily been established based on a limited number of genes and their functional homologies. Thus, a systematic analysis using transcriptomic data could offer novel insights into Drosophila hemocyte function and provide new perspectives on the evolution of the immune system. Here, we performed cross-species comparative analyses using single-cell RNA sequencing data from Drosophila and vertebrate immune cells. We found several conserved markers for the cluster of differentiation (CD) genes in Drosophila hemocytes and validated the role of CG8501 (CD59) in phagocytosis by plasmatocytes, which function much like macrophages in vertebrates. By comparing whole transcriptome profiles in both supervised and unsupervised analyses, we showed that Drosophila hemocytes are largely homologous to vertebrate myeloid cells, especially plasmatocytes to monocytes/macrophages and prohemocyte 1 (PH1) to hematopoietic stem cells. Furthermore, a small subset of prohemocytes with hematopoietic potential displayed homology with hematopoietic progenitor populations in vertebrates. Overall, our results provide a deeper understanding of molecular conservation in the Drosophila immune system.

Microglia promote anti-tumour immunity and suppress breast cancer brain metastasis

Breast cancer brain metastasis (BCBM) is a lethal disease with no effective treatments. Prior work has shown that brain cancers and metastases are densely infiltrated with anti-inflammatory, protumourigenic tumour-associated macrophages, but the role of brain-resident microglia remains controversial because they are challenging to discriminate from other tumour-associated macrophages. Using single-cell RNA sequencing, genetic and humanized mouse models, we specifically identify microglia and find that they play a distinct pro-inflammatory and tumour-suppressive role in BCBM. Animals lacking microglia show increased metastasis, decreased survival and reduced natural killer and T cell responses, showing that microglia are critical to promote anti-tumour immunity to suppress BCBM. We find that the pro-inflammatory response is conserved in human microglia, and markers of their response are associated with better prognosis in patients with BCBM. These findings establish an important role for microglia in anti-tumour immunity and highlight them as a potential immunotherapy target for brain metastasis.

Automatic quality control of single-cell and single-nucleus RNA-seq using valiDrops

Single-cell and single-nucleus RNA-sequencing (sxRNA-seq) measures gene expression in individual cells or nuclei enabling comprehensive characterization of cell types and states. However, isolation of cells or nuclei for sxRNA-seq releases contaminating RNA, which can distort biological signals, through, for example, cell damage and transcript leakage. Thus, identifying barcodes containing high-quality cells or nuclei is a critical analytical step in the processing of sxRNA-seq data. Here, we present valiDrops, an automated method to identify high-quality barcodes and flag dead cells. In valiDrops, barcodes are initially filtered using data-adaptive thresholding on community-standard quality metrics, and subsequently, valiDrops uses a novel clustering-based approach to identify barcodes with distinct biological signals. We benchmark valiDrops and show that biological signals from cell types and states are more distinct, easier to separate and more consistent after filtering by valiDrops compared to existing tools. Finally, we show that valiDrops can predict and flag dead cells with high accuracy. This novel classifier can further improve data quality or be used to identify dead cells to interrogate the biology of cell death. Thus, valiDrops is an effective and easy-to-use method to improve data quality and biological interpretation. Our method is openly available as an R package at www.github.com/madsen-lab/valiDrops.

Virus-specific TRM cells of both donor and recipient origin reside in human kidney transplants

Tissue-resident lymphocytes (TRLs) are critical for local protection against viral pathogens in peripheral tissue. However, it is unclear if TRLs perform a similar role in transplanted organs under chronic immunosuppressed conditions. In this study, we aimed to characterize the TRL compartment in human kidney transplant nephrectomies and examine its potential role in antiviral immunity. The TRL compartment of kidney transplants contained diverse innate, innate-like, and adaptive TRL populations expressing the canonical residency markers CD69, CD103, and CD49a. Chimerism of donor and recipient cells was present in 43% of kidney transplants and occurred in all TRL subpopulations. Paired single-cell transcriptome and T cell receptor (TCR) sequencing showed that donor and recipient tissue-resident memory T (TRM) cells exhibit striking similarities in their transcriptomic profiles and share numerous TCR clonotypes predicted to target viral pathogens. Virus dextramer staining further confirmed that CD8 TRM cells of both donor and recipient origin express TCRs with specificities against common viruses, including CMV, EBV, BK polyomavirus, and influenza A. Overall, the study results demonstrate that a diverse population of TRLs resides in kidney transplants and offer compelling evidence that TRM cells of both donor and recipient origin reside within this TRL population and may contribute to local protection against viral pathogens.

Rapid single-cell physical phenotyping of mechanically dissociated tissue biopsies

During surgery, rapid and accurate histopathological diagnosis is essential for clinical decision making. Yet the prevalent method of intra-operative consultation pathology is intensive in time, labour and costs, and requires the expertise of trained pathologists. Here we show that biopsy samples can be analysed within 30 min by sequentially assessing the physical phenotypes of singularized suspended cells dissociated from the tissues. The diagnostic method combines the enzyme-free mechanical dissociation of tissues, real-time deformability cytometry at rates of 100-1,000 cells s-1 and data analysis by unsupervised dimensionality reduction and logistic regression. Physical phenotype parameters extracted from brightfield images of single cells distinguished cell subpopulations in various tissues, enhancing or even substituting measurements of molecular markers. We used the method to quantify the degree of colon inflammation and to accurately discriminate healthy and tumorous tissue in biopsy samples of mouse and human colons. This fast and label-free approach may aid the intra-operative detection of pathological changes in solid biopsies.

Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors

BACKGROUND

Single-cell gene expression profiling provides unique opportunities to understand tumor heterogeneity and the tumor microenvironment. Because of cost and feasibility, profiling bulk tumors remains the primary population-scale analytical strategy. Many algorithms can deconvolve these tumors using single-cell profiles to infer their composition. While experimental choices do not change the true underlying composition of the tumor, they can affect the measurements produced by the assay.

RESULTS

We generated a dataset of high-grade serous ovarian tumors with paired expression profiles from using multiple strategies to examine the extent to which experimental factors impact the results of downstream tumor deconvolution methods. We find that pooling samples for single-cell sequencing and subsequent demultiplexing has a minimal effect. We identify dissociation-induced differences that affect cell composition, leading to changes that may compromise the assumptions underlying some deconvolution algorithms. We also observe differences across mRNA enrichment methods that introduce additional discrepancies between the two data types. We also find that experimental factors change cell composition estimates and that the impact differs by method.

CONCLUSIONS

Previous benchmarks of deconvolution methods have largely ignored experimental factors. We find that methods vary in their robustness to experimental factors. We provide recommendations for methods developers seeking to produce the next generation of deconvolution approaches and for scientists designing experiments using deconvolution to study tumor heterogeneity.

Spatial transcriptomics in glioblastoma: is knowing the right zip code the key to the next therapeutic breakthrough?

Spatial transcriptomics, the technology of visualizing cellular gene expression landscape in a cells native tissue location, has emerged as a powerful tool that allows us to address scientific questions that were elusive just a few years ago. This technological advance is a decisive jump in the technological evolution that is revolutionizing studies of tissue structure and function in health and disease through the introduction of an entirely new dimension of data, spatial context. Perhaps the organ within the body that relies most on spatial organization is the brain. The central nervous system's complex microenvironmental and spatial architecture is tightly regulated during development, is maintained in health, and is detrimental when disturbed by pathologies. This inherent spatial complexity of the central nervous system makes it an exciting organ to study using spatial transcriptomics for pathologies primarily affecting the brain, of which Glioblastoma is one of the worst. Glioblastoma is a hyper-aggressive, incurable, neoplasm and has been hypothesized to not only integrate into the spatial architecture of the surrounding brain, but also possess an architecture of its own that might be actively remodeling the surrounding brain. In this review we will examine the current landscape of spatial transcriptomics in glioblastoma, outline novel findings emerging from the rising use of spatial transcriptomics, and discuss future directions and ultimate clinical/translational avenues.

Single-cell dissection of tumor microenvironmental response and resistance to cancer therapy

Cancer treatment strategies have evolved significantly over the years, with chemotherapy, targeted therapy, and immunotherapy as major pillars. Each modality leads to unique treatment outcomes by interacting with the tumor microenvironment (TME), which imposes a fundamental selective pressure on cancer progression. The advent of single-cell profiling technologies has revolutionized our understanding of the intricate and heterogeneous nature of the TME at an unprecedented resolution. This review delves into the commonalities and differential manifestations of how cancer therapies reshape the microenvironment in diverse cancer types. We highlight how groundbreaking immune checkpoint blockade (ICB) strategies alone or in combination with tumor-targeting treatments are endowed with comprehensive mechanistic insights when decoded at the single-cell level, aiming to drive forward future research directions on personalized treatments.

Lung tumor-infiltrating Treg have divergent transcriptional profiles and function linked to checkpoint blockade response

Regulatory T cells (Treg) are conventionally viewed as suppressors of endogenous and therapy-induced antitumor immunity; however, their role in modulating responses to immune checkpoint blockade (ICB) is unclear. In this study, we integrated single-cell RNA-seq/T cell receptor sequencing (TCRseq) of >73,000 tumor-infiltrating Treg (TIL-Treg) from anti-PD-1-treated and treatment-naive non-small cell lung cancers (NSCLC) with single-cell analysis of tumor-associated antigen (TAA)-specific Treg derived from a murine tumor model. We identified 10 subsets of human TIL-Treg, most of which have high concordance with murine TIL-Treg subsets. Only one subset selectively expresses high levels of TNFRSF4 (OX40) and TNFRSF18 (GITR), whose engangement by cognate ligand mediated proliferative programs and NF-κB activation, as well as multiple genes involved in Treg suppression, including LAG3. Functionally, the OX40hiGITRhi subset is the most highly suppressive ex vivo, and its higher representation among total TIL-Treg correlated with resistance to PD-1 blockade. Unexpectedly, in the murine tumor model, we found that virtually all TIL-Treg-expressing T cell receptors that are specific for TAA fully develop a distinct TH1-like signature over a 2-week period after entry into the tumor, down-regulating FoxP3 and up-regulating expression of TBX21 (Tbet), IFNG, and certain proinflammatory granzymes. Transfer learning of a gene score from the murine TAA-specific TH1-like Treg subset to the human single-cell dataset revealed a highly analogous subcluster that was enriched in anti-PD-1-responding tumors. These findings demonstrate that TIL-Treg partition into multiple distinct transcriptionally defined subsets with potentially opposing effects on ICB-induced antitumor immunity and suggest that TAA-specific TIL-Treg may positively contribute to antitumor responses.

Bestrophin3 Deficiency in Vascular Smooth Muscle Cells Activates MEKK2/3-MAPK Signaling to Trigger Spontaneous Aortic Dissection

BACKGROUND

Aortic dissection (AD) is a fatal cardiovascular disorder without effective medications due to unclear pathogenic mechanisms. Bestrophin3 (Best3), the predominant isoform of bestrophin family in vessels, has emerged as critical for vascular pathological processes. However, the contribution of Best3 to vascular diseases remains elusive.

METHODS

Smooth muscle cell-specific and endothelial cell-specific Best3 knockout mice (Best3SMKO and Best3ECKO, respectively) were engineered to investigate the role of Best3 in vascular pathophysiology. Functional studies, single-cell RNA sequencing, proteomics analysis, and coimmunoprecipitation coupled with mass spectrometry were performed to evaluate the function of Best3 in vessels.

RESULTS

Best3 expression in aortas of human AD samples and mouse AD models was decreased. Best3SMKO but not Best3ECKO mice spontaneously developed AD with age, and the incidence reached 48% at 72 weeks of age. Reanalysis of single-cell transcriptome data revealed that reduction of fibromyocytes, a fibroblast-like smooth muscle cell cluster, was a typical feature of human ascending AD and aneurysm. Consistently, Best3 deficiency in smooth muscle cells decreased the number of fibromyocytes. Mechanistically, Best3 interacted with both MEKK2 and MEKK3, and this interaction inhibited phosphorylation of MEKK2 at serine153 and MEKK3 at serine61. Best3 deficiency induced phosphorylation-dependent inhibition of ubiquitination and protein turnover of MEKK2/3, thereby activating the downstream mitogen-activated protein kinase signaling cascade. Furthermore, restoration of Best3 or inhibition of MEKK2/3 prevented AD progression in angiotensin II-infused Best3SMKO and ApoE-/- mice.

CONCLUSIONS

These findings unveil a critical role of Best3 in regulating smooth muscle cell phenotypic switch and aortic structural integrity through controlling MEKK2/3 degradation. Best3-MEKK2/3 signaling represents a novel therapeutic target for AD.

Dynamic thresholding and tissue dissociation optimization for CITE-seq identifies differential surface protein abundance in metastatic melanoma

Multi-omics profiling by CITE-seq bridges the RNA-protein gap in single-cell analysis but has been largely applied to liquid biopsies. Applying CITE-seq to clinically relevant solid biopsies to characterize healthy tissue and the tumor microenvironment is an essential next step in single-cell translational studies. In this study, gating of cell populations based on their transcriptome signatures for use in cell type-specific ridge plots allowed identification of positive antibody signals and setting of manual thresholds. Next, we compare five skin dissociation protocols by taking into account dissociation efficiency, captured cell type heterogeneity and recovered surface proteome. To assess the effect of enzymatic digestion on transcriptome and epitope expression in immune cell populations, we analyze peripheral blood mononuclear cells (PBMCs) with and without dissociation. To further assess the RNA-protein gap, RNA-protein we perform codetection and correlation analyses on thresholded protein values. Finally, in a proof-of-concept study, using protein abundance analysis on selected surface markers in a cohort of healthy skin, primary, and metastatic melanoma we identify CD56 surface marker expression on metastatic melanoma cells, which was further confirmed by multiplex immunohistochemistry. This work provides practical guidelines for processing and analysis of clinically relevant solid tissue biopsies for biomarker discovery.

spinDrop: a droplet microfluidic platform to maximise single-cell sequencing information content

Droplet microfluidic methods have massively increased the throughput of single-cell sequencing campaigns. The benefit of scale-up is, however, accompanied by increased background noise when processing challenging samples and the overall RNA capture efficiency is lower. These drawbacks stem from the lack of strategies to enrich for high-quality material or specific cell types at the moment of cell encapsulation and the absence of implementable multi-step enzymatic processes that increase capture. Here we alleviate both bottlenecks using fluorescence-activated droplet sorting to enrich for droplets that contain single viable cells, intact nuclei, fixed cells or target cell types and use reagent addition to droplets by picoinjection to perform multi-step lysis and reverse transcription. Our methodology increases gene detection rates fivefold, while reducing background noise by up to half. We harness these properties to deliver a high-quality molecular atlas of mouse brain development, despite starting with highly damaged input material, and provide an atlas of nascent RNA transcription during mouse organogenesis. Our method is broadly applicable to other droplet-based workflows to deliver sensitive and accurate single-cell profiling at a reduced cost.

Microbial energy metabolism fuels an intestinal macrophage niche in solitary isolated lymphoid tissues through purinergic signaling

Maintaining macrophage (MΦ) heterogeneity is critical to ensure intestinal tissue homeostasis and host defense. The gut microbiota and host factors are thought to synergistically guide intestinal MΦ development, although the exact nature, regulation, and location of such collaboration remain unclear. Here, we report that microbial biochemical energy metabolism promotes colony-stimulating factor 2 (CSF2) production by group 3 innate lymphoid cells (ILC3s) within solitary isolated lymphoid tissues (SILTs) in a cell-extrinsic, NLRP3/P2X7R-dependent fashion in the steady state. Tissue-infiltrating monocytes accumulating around SILTs followed a spatially constrained, distinct developmental trajectory into SILT-associated MΦs (SAMs). CSF2 regulated the mitochondrial membrane potential and reactive oxygen species production of SAMs and contributed to the antimicrobial defense against enteric bacterial infections. Collectively, these findings identify SILTs and CSF2-producing ILC3s as a microanatomic niche for intestinal MΦ development and functional programming fueled by the integration of commensal microbial energy metabolism.

Preparation of a Single-Cell Suspension from Tumor Biopsy Samples for Single-Cell RNA Sequencing

An essential requirement for single-cell RNA sequencing in cancer is the preparation of high-quality single-cell suspensions from the tumor tissue. In this work, various methods of dissociation of tumor biopsy specimens were analyzed and developed to obtain a cell suspension with at least 80% viability. It was found that the optimal conditions for sample preparation are mechanical dissociation followed by incubation with a collagenase/hyaluronidase mixture with addition of DNAase I for 60 min. Thus, we optimize the approach for preparing single-cell suspensions from the tumor biopsy tissue for single-cell RNA sequencing.

The effect of matrices on the gene expression profile of patient-derived head and neck carcinoma cells for in vitro therapy testing

OBJECTIVE

Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive tumor with a 5-year mortality rate of ~ 50%. New in vitro methods are needed for testing patients' cancer cell response to anti-cancer treatments. We aimed to investigate how the gene expression of fresh carcinoma tissue samples and freshly digested single cancer cells change after short-term cell culturing on plastic, Matrigel or Myogel. Additionally, we studied the effect of these changes on the cancer cells' response to anti-cancer treatments.

MATERIALS/METHODS

Fresh tissue samples from HNSCC patients were obtained perioperatively and single cells were enzymatically isolated and cultured on either plastic, Matrigel or Myogel. We treated the cultured cells with cisplatin, cetuximab, and irradiation; and performed cell viability measurement. RNA was isolated from fresh tissue samples, freshly isolated single cells and cultured cells, and RNA sequencing transcriptome profiling and gene set enrichment analysis were performed.

RESULTS

Cancer cells obtained from fresh tissue samples changed their gene expression regardless of the culturing conditions, which may be due to the enzymatic digestion of the tissue. Myogel was more effective than Matrigel at supporting the upregulation of pathways related to cancer cell proliferation and invasion. The impacts of anti-cancer treatments varied between culturing conditions.

CONCLUSIONS

Our study showed the challenge of in vitro cancer drug testing using enzymatic cell digestion. The upregulation of many targeted pathways in the cultured cells may partially explain the common clinical failure of the targeted cancer drugs that pass the in vitro testing.

SiftCell: A robust framework to detect and isolate cell-containing droplets from single-cell RNA sequence reads

Single-cell RNA sequencing (scRNA-seq) massively profiles transcriptomes of individual cells encapsulated in barcoded droplets in parallel. However, in real-world scRNA-seq data, many barcoded droplets do not contain cells, but instead, they capture a fraction of ambient RNAs released from damaged or lysed cells. A typical first step to analyze scRNA-seq data is to filter out cell-free droplets and isolate cell-containing droplets, but distinguishing them is often challenging; incorrect filtering may mislead the downstream analysis substantially. We propose SiftCell, a suite of software tools to identify and visualize cell-containing and cell-free droplets in manifold space via randomization (SiftCell-Shuffle) to classify between the two types of droplets (SiftCell-Boost) and to quantify the contribution of ambient RNAs for each droplet (SiftCell-Mix). By applying our method to datasets obtained by various single-cell platforms, we show that SiftCell provides a streamlined way to perform upstream quality control of scRNA-seq, which is more comprehensive and accurate than existing methods.

Single-cell transcriptome atlas of Drosophila gastrula 2.0

During development, positional information directs cells to specific fates, leading them to differentiate with their own transcriptomes and express specific behaviors and functions. However, the mechanisms underlying these processes in a genome-wide view remain ambiguous, partly because the single-cell transcriptomic data of early developing embryos containing accurate spatial and lineage information are still lacking. Here, we report a single-cell transcriptome atlas of Drosophila gastrulae, divided into 77 transcriptomically distinct clusters. We find that the expression profiles of plasma-membrane-related genes, but not those of transcription-factor genes, represent each germ layer, supporting the nonequivalent contribution of each transcription-factor mRNA level to effector gene expression profiles at the transcriptome level. We also reconstruct the spatial expression patterns of all genes at the single-cell stripe level as the smallest unit. This atlas is an important resource for the genome-wide understanding of the mechanisms by which genes cooperatively orchestrate Drosophila gastrulation.

Pan-cancer T cell atlas links a cellular stress response state to immunotherapy resistance

Tumor-infiltrating T cells offer a promising avenue for cancer treatment, yet their states remain to be fully characterized. Here we present a single-cell atlas of T cells from 308,048 transcriptomes across 16 cancer types, uncovering previously undescribed T cell states and heterogeneous subpopulations of follicular helper, regulatory and proliferative T cells. We identified a unique stress response state, TSTR, characterized by heat shock gene expression. TSTR cells are detectable in situ in the tumor microenvironment across various cancer types, mostly within lymphocyte aggregates or potential tertiary lymphoid structures in tumor beds or surrounding tumor edges. T cell states/compositions correlated with genomic, pathological and clinical features in 375 patients from 23 cohorts, including 171 patients who received immune checkpoint blockade therapy. We also found significantly upregulated heat shock gene expression in intratumoral CD4/CD8+ cells following immune checkpoint blockade treatment, particularly in nonresponsive tumors, suggesting a potential role of TSTR cells in immunotherapy resistance. Our well-annotated T cell reference maps, web portal and automatic alignment/annotation tool could provide valuable resources for T cell therapy optimization and biomarker discovery.

Approaches for single-cell RNA sequencing across tissues and cell types

Single-cell sequencing of RNA (scRNA-seq) has advanced our understanding of cellular heterogeneity and signaling in developmental biology and disease. A large number of complementary assays have been developed to profile transcriptomes of individual cells, also in combination with other readouts, such as chromatin accessibility or antibody-based analysis of protein surface markers. As scRNA-seq technologies are advancing fast, it is challenging to establish robust workflows and up-to-date protocols that are best suited to address the large range of research questions. Here, we review scRNA-seq techniques from mRNA end-counting to total RNA in relation to their specific features and outline the necessary sample preparation steps and quality control measures. Based on our experience in dealing with the continuously growing portfolio from the perspective of a central single-cell facility, we aim to provide guidance on how workflows can be best automatized and share our experience in coping with the continuous expansion of scRNA-seq techniques.

Transitioning single-cell genomics into the clinic

The use of genomics is firmly established in clinical practice, resulting in innovations across a wide range of disciplines such as genetic screening, rare disease diagnosis and molecularly guided therapy choice. This new field of genomic medicine has led to improvements in patient outcomes. However, most clinical applications of genomics rely on information generated from bulk approaches, which do not directly capture the genomic variation that underlies cellular heterogeneity. With the advent of single-cell technologies, research is rapidly uncovering how genomic data at cellular resolution can be used to understand disease pathology and mechanisms. Both DNA-based and RNA-based single-cell technologies have the potential to improve existing clinical applications and open new application spaces for genomics in clinical practice, with oncology, immunology and haematology poised for initial adoption. However, challenges in translating cellular genomics from research to a clinical setting must first be overcome.

Cellular mechanisms of oligoclonal vascular smooth muscle cell expansion in cardiovascular disease

AIMS

Quiescent, differentiated adult vascular smooth muscle cells (VSMCs) can be induced to proliferate and switch phenotype. Such plasticity underlies blood vessel homeostasis and contributes to vascular disease development. Oligoclonal VSMC contribution is a hallmark of end-stage vascular disease. Here, we aim to understand cellular mechanisms underpinning generation of this VSMC oligoclonality.

METHODS AND RESULTS

We investigate the dynamics of VSMC clone formation using confocal microscopy and single-cell transcriptomics in VSMC-lineage-traced animal models. We find that activation of medial VSMC proliferation occurs at low frequency after vascular injury and that only a subset of expanding clones migrate, which together drives formation of oligoclonal neointimal lesions. VSMC contribution in small atherosclerotic lesions is typically from one or two clones, similar to observations in mature lesions. Low frequency (<0.1%) of clonal VSMC proliferation is also observed in vitro. Single-cell RNA-sequencing revealed progressive cell state changes across a contiguous VSMC population at onset of injury-induced proliferation. Proliferating VSMCs mapped selectively to one of two distinct trajectories and were associated with cells showing extensive phenotypic switching. A proliferation-associated transitory state shared pronounced similarities with atypical SCA1+ VSMCs from uninjured mouse arteries and VSMCs in healthy human aorta. We show functionally that clonal expansion of SCA1+ VSMCs from healthy arteries occurs at higher rate and frequency compared with SCA1- cells.

CONCLUSION

Our data suggest that activation of proliferation at low frequency is a general, cell-intrinsic feature of VSMCs. We show that rare VSMCs in healthy arteries display VSMC phenotypic switching akin to that observed in pathological vessel remodelling and that this is a conserved feature of mouse and human healthy arteries. The increased proliferation of modulated VSMCs from healthy arteries suggests that these cells respond more readily to disease-inducing cues and could drive oligoclonal VSMC expansion.

Cold-Adapted Proteases: An Efficient and Energy-Saving Biocatalyst

The modern biotechnology industry has a demand for macromolecules that can function in extreme environments. One example is cold-adapted proteases, possessing advantages such as maintaining high catalytic efficiency at low temperature and low energy input during production and inactivation. Meanwhile, cold-adapted proteases are characterised by sustainability, environmental protection, and energy conservation; therefore, they hold significant economic and ecological value regarding resource utilisation and the global biogeochemical cycle. Recently, the development and application of cold-adapted proteases have gained gaining increasing attention; however, their applications potential has not yet been fully developed, which has seriously restricted the promotion and application of cold-adapted proteases in the industry. This article introduces the source, related enzymology characteristics, cold resistance mechanism, and the structure-function relationship of cold-adapted proteases in detail. This is in addition to discussing related biotechnologies to improve stability, emphasise application potential in clinical medical research, and the constraints of the further developing of cold-adapted proteases. This article provides a reference for future research and the development of cold-adapted proteases.

Single-nucleus RNA sequencing of human pancreatic islets identifies novel gene sets and distinguishes β-cell subpopulations with dynamic transcriptome profiles

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) provides valuable insights into human islet cell types and their corresponding stable gene expression profiles. However, this approach requires cell dissociation that complicates its utility in vivo. On the other hand, single-nucleus RNA sequencing (snRNA-seq) has compatibility with frozen samples, elimination of dissociation-induced transcriptional stress responses, and affords enhanced information from intronic sequences that can be leveraged to identify pre-mRNA transcripts.

METHODS

We obtained nuclear preparations from fresh human islet cells and generated snRNA-seq datasets. We compared these datasets to scRNA-seq output obtained from human islet cells from the same donor. We employed snRNA-seq to obtain the transcriptomic profile of human islets engrafted in immunodeficient mice. In both analyses, we included the intronic reads in the snRNA-seq data with the GRCh38-2020-A library.

RESULTS

First, snRNA-seq analysis shows that the top four differentially and selectively expressed genes in human islet endocrine cells in vitro and in vivo are not the canonical genes but a new set of non-canonical gene markers including ZNF385D, TRPM3, LRFN2, PLUT (β-cells); PTPRT, FAP, PDK4, LOXL4 (α-cells); LRFN5, ADARB2, ERBB4, KCNT2 (δ-cells); and CACNA2D3, THSD7A, CNTNAP5, RBFOX3 (γ-cells). Second, by integrating information from scRNA-seq and snRNA-seq of human islet cells, we distinguish three β-cell sub-clusters: an INS pre-mRNA cluster (β3), an intermediate INS mRNA cluster (β2), and an INS mRNA-rich cluster (β1). These display distinct gene expression patterns representing different biological dynamic states both in vitro and in vivo. Interestingly, the INS mRNA-rich cluster (β1) becomes the predominant sub-cluster in vivo.

CONCLUSIONS

In summary, snRNA-seq and pre-mRNA analysis of human islet cells can accurately identify human islet cell populations, subpopulations, and their dynamic transcriptome profile in vivo.

User-Controlled 4D Biomaterial Degradation with Substrate-Selective Sortase Transpeptidases for Single-Cell Biology

Stimuli-responsive biomaterials show great promise for modeling disease dynamics ex vivo with spatiotemporal control over the cellular microenvironment. However, harvesting cells from such materials for downstream analysis without perturbing their state remains an outstanding challenge in 3/4-dimensional (3D/4D) culture and tissue engineering. In this manuscript, a fully enzymatic strategy for hydrogel degradation that affords spatiotemporal control over cell release while maintaining cytocompatibility is introduced. Exploiting engineered variants of the sortase transpeptidase evolved to recognize and selectively cleave distinct peptide sequences largely absent from the mammalian proteome, many limitations implicit to state-of-the-art methods to liberate cells from gels are sidestepped. It is demonstrated that evolved sortase exposure has minimal impact on the global transcriptome of primary mammalian cells and that proteolytic cleavage proceeds with high specificity; incorporation of substrate sequences within hydrogel crosslinkers permits rapid and selective cell recovery with high viability. In composite multimaterial hydrogels, it is shown that sequential degradation of hydrogel layers enables highly specific retrieval of single-cell suspensions for phenotypic analysis. It is expected that the high bioorthogonality and substrate selectivity of the evolved sortases will lead to their broad adoption as an enzymatic material dissociation cue and that their multiplexed use will enable newfound studies in 4D cell culture.

Isolation of human cutaneous immune cells for single-cell RNA sequencing

Single-cell RNA sequencing (scRNA-seq) allows for high-resolution analysis of transcriptionally dysregulated cell subpopulations in inflammatory diseases. However, it can be challenging to properly isolate viable immune cells from human skin for scRNA-seq due to its barrier properties. Here, we present a protocol to isolate high-viability human cutaneous immune cells. We describe steps for obtaining and enzymatically dissociating a skin biopsy specimen and isolating immune cells using flow cytometry. We then provide an overview of downstream computational techniques to analyze sequencing data. For complete details on the use and execution of this protocol, please refer to Cook et al. (2022)1 and Liu et al. (2022).2.

Multi-omic single cell sequencing: Overview and opportunities for kidney disease therapeutic development

Single cell sequencing technologies have rapidly advanced in the last decade and are increasingly applied to gain unprecedented insights by deconstructing complex biology to its fundamental unit, the individual cell. First developed for measurement of gene expression, single cell sequencing approaches have evolved to allow simultaneous profiling of multiple additional features, including chromatin accessibility within the nucleus and protein expression at the cell surface. These multi-omic approaches can now further be applied to cells in situ, capturing the spatial context within which their biology occurs. To extract insights from these complex datasets, new computational tools have facilitated the integration of information across different data types and the use of machine learning approaches. Here, we summarize current experimental and computational methods for generation and integration of single cell multi-omic datasets. We focus on opportunities for multi-omic single cell sequencing to augment therapeutic development for kidney disease, including applications for biomarkers, disease stratification and target identification.

Femtosecond laser microdissection for isolation of regenerating C. elegans neurons for single-cell RNA sequencing

Our understanding of nerve regeneration can be enhanced by delineating its underlying molecular activities at single-neuron resolution in model organisms such as Caenorhabditis elegans. Existing cell isolation techniques cannot isolate neurons with specific regeneration phenotypes from C. elegans. We present femtosecond laser microdissection (fs-LM), a single-cell isolation method that dissects specific cells directly from living tissue by leveraging the micrometer-scale precision of fs-laser ablation. We show that fs-LM facilitates sensitive and specific gene expression profiling by single-cell RNA sequencing (scRNA-seq), while mitigating the stress-related transcriptional artifacts induced by tissue dissociation. scRNA-seq of fs-LM isolated regenerating neurons revealed transcriptional programs that are correlated with either successful or failed regeneration in wild-type and dlk-1 (0) animals, respectively. This method also allowed studying heterogeneity displayed by the same type of neuron and found gene modules with expression patterns correlated with axon regrowth rate. Our results establish fs-LM as a spatially resolved single-cell isolation method for phenotype-to-genotype mapping.