scholarly journals Single-Cell Sequencing: Biological Insight and Potential Clinical Implications in Pediatric Leukemia

Cancers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 5658
Author(s):  
Donát Alpár ◽  
Bálint Egyed ◽  
Csaba Bödör ◽  
Gábor T. Kovács
Keyword(s):  
High Resolution ◽  
Single Cell ◽  
Childhood Leukemia ◽  
Clinical Decision Making ◽  
Cellular Heterogeneity ◽  
Therapeutic Interventions ◽  
Cell Populations ◽  
Pediatric Leukemia ◽  
Single Cell Sequencing ◽  
Wide Range

Single-cell sequencing (SCS) provides high-resolution insight into the genomic, epigenomic, and transcriptomic landscape of oncohematological malignancies including pediatric leukemia, the most common type of childhood cancer. Besides broadening our biological understanding of cellular heterogeneity, sub-clonal architecture, and regulatory network of tumor cell populations, SCS can offer clinically relevant, detailed characterization of distinct compartments affected by leukemia and identify therapeutically exploitable vulnerabilities. In this review, we provide an overview of SCS studies focused on the high-resolution genomic and transcriptomic scrutiny of pediatric leukemia. Our aim is to investigate and summarize how different layers of single-cell omics approaches can expectedly support clinical decision making in the future. Although the clinical management of pediatric leukemia underwent a spectacular improvement during the past decades, resistant disease is a major cause of therapy failure. Currently, only a small proportion of childhood leukemia patients benefit from genomics-driven therapy, as 15–20% of them meet the indication criteria of on-label targeted agents, and their overall response rate falls in a relatively wide range (40–85%). The in-depth scrutiny of various cell populations influencing the development, progression, and treatment resistance of different disease subtypes can potentially uncover a wider range of driver mechanisms for innovative therapeutic interventions.

scholarly journals The Development of an Effective Bacterial Single-Cell Lysis Method Suitable for Whole Genome Amplification in Microfluidic Platforms

Micromachines ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 367 ◽  
Author(s):  
Yuguang Liu ◽  
Dirk Schulze-Makuch ◽  
Jean-Pierre de Vera ◽  
Charles Cockell ◽  
Thomas Leya ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Bacterial Species ◽  
Cell Manipulation ◽  
Microfluidic Platforms ◽  
Gram Positive ◽  
Gram Negative ◽  
Genome Amplification ◽  
Single Cell Sequencing ◽  
Wide Range

Single-cell sequencing is a powerful technology that provides the capability of analyzing a single cell within a population. This technology is mostly coupled with microfluidic systems for controlled cell manipulation and precise fluid handling to shed light on the genomes of a wide range of cells. So far, single-cell sequencing has been focused mostly on human cells due to the ease of lysing the cells for genome amplification. The major challenges that bacterial species pose to genome amplification from single cells include the rigid bacterial cell walls and the need for an effective lysis protocol compatible with microfluidic platforms. In this work, we present a lysis protocol that can be used to extract genomic DNA from both gram-positive and gram-negative species without interfering with the amplification chemistry. Corynebacterium glutamicum was chosen as a typical gram-positive model and Nostoc sp. as a gram-negative model due to major challenges reported in previous studies. Our protocol is based on thermal and chemical lysis. We consider 80% of single-cell replicates that lead to >5 ng DNA after amplification as successful attempts. The protocol was directly applied to Gloeocapsa sp. and the single cells of the eukaryotic Sphaerocystis sp. and achieved a 100% success rate.

scholarly journals rCASC: reproducible classification analysis of single-cell sequencing data

GigaScience ◽  
2019 ◽  
Vol 8 (9) ◽  
Author(s):  
Luca Alessandrì ◽  
Francesca Cordero ◽  
Marco Beccuti ◽  
Maddalena Arigoni ◽  
Martina Olivero ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cellular Heterogeneity ◽  
Cell Subpopulation ◽  
Integrated Analysis ◽  
Specific Gene ◽  
Sequencing Data ◽  
Single Cell Sequencing ◽  
Cell Stability ◽  
Reproducible Analysis

Abstract Background Single-cell RNA sequencing is essential for investigating cellular heterogeneity and highlighting cell subpopulation-specific signatures. Single-cell sequencing applications have spread from conventional RNA sequencing to epigenomics, e.g., ATAC-seq. Many related algorithms and tools have been developed, but few computational workflows provide analysis flexibility while also achieving functional (i.e., information about the data and the tools used are saved as metadata) and computational reproducibility (i.e., a real image of the computational environment used to generate the data is stored) through a user-friendly environment. Findings rCASC is a modular workflow providing an integrated analysis environment (from count generation to cell subpopulation identification) exploiting Docker containerization to achieve both functional and computational reproducibility in data analysis. Hence, rCASC provides preprocessing tools to remove low-quality cells and/or specific bias, e.g., cell cycle. Subpopulation discovery can instead be achieved using different clustering techniques based on different distance metrics. Cluster quality is then estimated through the new metric "cell stability score" (CSS), which describes the stability of a cell in a cluster as a consequence of a perturbation induced by removing a random set of cells from the cell population. CSS provides better cluster robustness information than the silhouette metric. Moreover, rCASC's tools can identify cluster-specific gene signatures. Conclusions rCASC is a modular workflow with new features that could help researchers define cell subpopulations and detect subpopulation-specific markers. It uses Docker for ease of installation and to achieve a computation-reproducible analysis. A Java GUI is provided to welcome users without computational skills in R.

scholarly journals Synovial single-cell heterogeneity, zonation, and interactions: a patchwork of effectors in arthritis

Rheumatology ◽  
2021 ◽  
Author(s):  
Barbora Schonfeldova ◽  
Kristina Zec ◽  
Irina A Udalova
Keyword(s):  
Rheumatoid Arthritis ◽  
Single Cell ◽  
Cell Signalling ◽  
Synovial Cell ◽  
Cellular Heterogeneity ◽  
Cell Populations ◽  
Single Cell Level ◽  
Cell Heterogeneity ◽  
Cell Level ◽  
Peripheral Neurons

Abstract Despite extensive research, there is still no treatment that would lead to remission in all patients with rheumatoid arthritis as our understanding of the affected site, the synovium, is still incomplete. Recently, single-cell technologies helped to decipher the cellular heterogeneity of the synovium; however, certain synovial cell populations, such as endothelial cells or peripheral neurons, remain to be profiled on a single-cell level. Furthermore, associations between certain cellular states and inflammation were found; whether these cells cause the inflammation remains to be answered. Similarly, cellular zonation and interactions between individual effectors in the synovium are yet to be fully determined. A deeper understanding of cell signalling and interactions in the synovium is crucial for a better design of therapeutics with the goal of complete remission in all patients.

scholarly journals Cellular heterogeneity during mouse pancreatic ductal adenocarcinoma progression at single-cell resolution

2019 ◽  
Author(s):  
Abdel Nasser Hosein ◽  
Huocong Huang ◽  
Zhaoning Wang ◽  
Kamalpreet Parmar ◽  
Wenting Du ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Genetically Engineered ◽  
Cellular Heterogeneity ◽  
Ductal Adenocarcinoma ◽  
Cell Populations ◽  
Specific Cell ◽  
Cell Heterogeneity ◽  
Mesenchymal Transition

AbstractBackground & AimsPancreatic ductal adenocarcinoma (PDA) is a major cause of cancer-related death with limited therapeutic options available. This highlights the need for improved understanding of the biology of PDA progression. The progression of PDA is a highly complex and dynamic process featuring changes in cancer cells and stromal cells; however, a comprehensive characterization of PDA cancer cell and stromal cell heterogeneity during disease progression is lacking. In this study, we aimed to profile cell populations and understand their phenotypic changes during PDA progression.MethodsWe employed single-cell RNA sequencing technology to agnostically profile cell heterogeneity during different stages of PDA progression in genetically engineered mouse models.ResultsOur data indicate that an epithelial-to-mesenchymal transition of cancer cells accompanies tumor progression. We also found distinct populations of macrophages with increasing inflammatory features during PDA progression. In addition, we noted the existence of three distinct molecular subtypes of fibroblasts in the normal mouse pancreas, which ultimately gave rise to two distinct populations of fibroblasts in advanced PDA, supporting recent reports on intratumoral fibroblast heterogeneity. Our data also suggest that cancer cells and fibroblasts are dynamically regulated by epigenetic mechanisms.ConclusionThis study systematically outlines the landscape of cellular heterogeneity during the progression of PDA. It strongly improves our understanding of the PDA biology and has the potential to aid in the development of therapeutic strategies against specific cell populations of the disease.

scholarly journals The single-cell epigenetic regulatory landscape in mammalian perinatal testis development

2021 ◽  
Author(s):  
Jinyue Liao ◽  
Hoi Ching Suen ◽  
Shitao Rao ◽  
Alfred Chun Shui Luk ◽  
Ruoyu Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Fate ◽  
Germ Cells ◽  
Somatic Cells ◽  
Cell Types ◽  
Regulatory Elements ◽  
Cellular Heterogeneity ◽  
Cell Populations ◽  
Cell Type

AbstractSpermatogenesis depends on an orchestrated series of developing events in germ cells and full maturation of the somatic microenvironment. To date, the majority of efforts to study cellular heterogeneity in testis has been focused on single-cell gene expression rather than the chromatin landscape shaping gene expression. To advance our understanding of the regulatory programs underlying testicular cell types, we analyzed single-cell chromatin accessibility profiles in more than 25,000 cells from mouse developing testis. We showed that scATAC-Seq allowed us to deconvolve distinct cell populations and identify cis-regulatory elements (CREs) underlying cell type specification. We identified sets of transcription factors associated with cell type-specific accessibility, revealing novel regulators of cell fate specification and maintenance. Pseudotime reconstruction revealed detailed regulatory dynamics coordinating the sequential developmental progressions of germ cells and somatic cells. This high-resolution data also revealed putative stem cells within the Sertoli and Leydig cell populations. Further, we defined candidate target cell types and genes of several GWAS signals, including those associated with testosterone levels and coronary artery disease. Collectively, our data provide a blueprint of the ‘regulon’ of the mouse male germline and supporting somatic cells.

scholarly journals Heterogeneity of Circulating Tumor Cell Neoplastic Subpopulations Outlined by Single-Cell Transcriptomics

Cancers ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 4885
Author(s):  
Christine M. Pauken ◽  
Shelby Ray Kenney ◽  
Kathryn J. Brayer ◽  
Yan Guo ◽  
Ursa A. Brown-Glaberman ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Single Cell ◽  
Immune Cell ◽  
Metastatic Breast ◽  
Gene Expression Signature ◽  
Circulating Tumor Cell ◽  
Therapeutic Interventions ◽  
Cell Populations ◽  
Breast Cancer Patients ◽  
The Common

Fatal metastasis occurs when circulating tumor cells (CTCs) disperse through the blood to initiate a new tumor at specific sites distant from the primary tumor. CTCs have been classically defined as nucleated cells positive for epithelial cell adhesion molecule and select cytokeratins (EpCAM/CK/DAPI), while negative for the common lymphocyte marker CD45. The enumeration of CTCs allows an estimation of the overall metastatic burden in breast cancer patients, but challenges regarding CTC heterogeneity and metastatic propensities persist, and their decryption could improve therapies. CTCs from metastatic breast cancer (mBC) patients were captured using the RareCyteTM Cytefinder II platform. The Lin− and Lin+ (CD45+) cell populations isolated from the blood of three of these mBC patients were analyzed by single-cell transcriptomic methods, which identified a variety of immune cell populations and a cluster of cells with a distinct gene expression signature, which includes both cells expressing EpCAM/CK (“classic” CTCs) and cells possessing an array of genes not previously associated with CTCs. This study put forward notions that the identification of these genes and their interactions will promote novel areas of analysis by dissecting properties underlying CTC survival, proliferation, and interaction with circulatory immune cells. It improves upon capabilities to measure and interfere with CTCs for impactful therapeutic interventions.

scholarly journals scTriangulate: Decision-level integration of multimodal single-cell data

2021 ◽  
Author(s):  
Guangyuan Li ◽  
Song Baobao ◽  
H. L Grimes ◽  
V. B. Surya Prasath ◽  
Nathan L Salomonis
Keyword(s):  
Single Cell ◽  
Cooperative Game Theory ◽  
Cellular Heterogeneity ◽  
Cell Populations ◽  
Multimodal Analysis ◽  
Distinct Cell ◽  
Cell Data ◽  
Mix And Match ◽  
Computational Strategy ◽  
Statistical Metrics

Hundreds of bioinformatics approaches now exist to define cellular heterogeneity from single-cell genomics data. Reconciling conflicts between diverse methods, algorithm settings, annotations or modalities have the potential to clarify which populations are real and establish reusable reference atlases. Here, we present a customizable computational strategy called scTrianguate, which leverages cooperative game theory to intelligently mix-and-match clustering solutions from different resolutions, algorithms, reference atlases, or multi-modal measurements. This algorithm relies on a series of robust statistical metrics for cluster stability that work across molecular modalities to identify high-confidence integrated annotations. When applied to annotations from diverse competing cell atlas projects, this approach is able to resolve conflicts and determine the validity of controversial cell population predictions. Tested with scRNA-Seq, CITE-Seq (RNA + surface ADT), multiome (RNA + ATAC), and TEA-Seq (RNA + surface ADT + ATAC), this approach identifies highly stable and reproducible, known and novel cell populations, while excluding clusters defined by technical artifacts (i.e., doublets). Importantly, we find that distinct cell populations are frequently attributed with features from different modalities (RNA, ATAC, ADT) in the same assay, highlighting the importance of multimodal analysis in cluster determination. As it is flexible, this approach can be updated with new user-defined statistical metrics to alter the decision engine and customized to new measures of stability for different measures of cellular activity.

scholarly journals Single-Cell RNA Sequencing Defines the Regulation of Spermatogenesis by Sertoli-Cell Androgen Signaling

2021 ◽  
Vol 9 ◽  
Author(s):  
Congcong Cao ◽  
Qian Ma ◽  
Shaomei Mo ◽  
Ge Shu ◽  
Qunlong Liu ◽  
...  
Keyword(s):  
Single Cell ◽  
Sertoli Cells ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Cell Populations ◽  
Wild Type ◽  
Cellular Processes ◽  
Transcriptomic Sequencing ◽  
Transcriptional Changes

Androgen receptor (AR) signaling is essential for maintaining spermatogenesis and male fertility. However, the molecular mechanisms by which AR acts between male germ cells and somatic cells during spermatogenesis have not begun to be revealed until recently. With the advances obtained from the use of transgenic mice lacking AR in Sertoli cells (SCARKO) and single-cell transcriptomic sequencing (scRNA-seq), the cell specific targets of AR action as well as the genes and signaling pathways that are regulated by AR are being identified. In this study, we collected scRNA-seq data from wild-type (WT) and SCARKO mice testes at p20 and identified four somatic cell populations and two male germ cell populations. Further analysis identified that the distribution of Sertoli cells was completely different and uncovered the cellular heterogeneity and transcriptional changes between WT and SCARKO Sertoli cells. In addition, several differentially expressed genes (DEGs) in SCARKO Sertoli cells, many of which have been previously implicated in cell cycle, apoptosis and male infertility, have also been identified. Together, our research explores a novel perspective on the changes in the transcription level of various cell types between WT and SCARKO mice testes, providing new insights for the investigations of the molecular and cellular processes regulated by AR signaling in Sertoli cells.

scholarly journals Reference-based annotation of single cell transcriptomes identifies a profibrotic macrophage niche after tissue injury

2018 ◽  
Author(s):  
Dvir Aran ◽  
Agnieszka P. Looney ◽  
Leqian Liu ◽  
Valerie Fong ◽  
Austin Hsu ◽  
...  
Keyword(s):  
Single Cell ◽  
Lung Fibrosis ◽  
Tissue Injury ◽  
Granular Cell ◽  
Cellular Heterogeneity ◽  
Trophic Effect ◽  
Peripheral Tissues ◽  
Wide Range

AbstractMyeloid cells localize to peripheral tissues in a wide range of pathologic contexts. However, appreciation of distinct myeloid subtypes has been limited by the signal averaging inherent to bulk sequencing approaches. Here we applied single-cell RNA sequencing (scRNA-seq) to map cellular heterogeneity in lung fibrosis induced by bleomycin injury in mice. We first developed a computational framework that enables unbiased, granular cell-type annotation of scRNA-seq. This approach identified a macrophage subpopulation that was specific to injured lung and notable for high expression of Cx3cr1+ and MHCII genes. We found that these macrophages, which bear a gene expression profile consistent with monocytic origin, progressively acquire alveolar macrophage identity and localize to sites of fibroblast accumulation. Probing their functional role, in vitro studies showed a trophic effect of these cells on fibroblast activation, and ablation of Cx3cr1-expressing cells suppressed fibrosis in vivo. We also found by gene set analysis and immunofluorescence that markers of these macrophages were upregulated in samples from patients with lung fibrosis compared with healthy controls. Taken together, our results uncover a specific pathologic subgroup of macrophages with markers that could enable their therapeutic targeting for fibrosis.

scholarly journals Intratumoral molecular genetic heterogeneity of glioblastomas

2020 ◽  
Vol 9 (4) ◽  
pp. 5-11
Author(s):  
P.V. Nikitin ◽  
◽  
M.V. Ryzhova ◽  
A.A. Potapov ◽  
S.A. Galstyan ◽  
...  
Keyword(s):  
Single Cell ◽  
Genetic Heterogeneity ◽  
Tumor Therapy ◽  
Molecular Genetic ◽  
Experimental Treatment ◽  
Intratumoral Heterogeneity ◽  
Cell Populations ◽  
Malignant Neoplasms ◽  
Single Cell Sequencing

Intratumoral molecular genetic heterogeneity is not a less significant challenge in modern oncology than the intertumoral. The presence of cell populations within the same tumor, differing in their molecular properties, translated into phenotypic features of the cells, is one of the reasons for the inefficiency of many developments in the field of tumor therapy and the basis for the progression of malignant neoplasms. The issue under consideration is very relevant for glioblastoma (GBM) – being one of the deadliest human tumors; it practically does not lend itself to even promising experimental treatment methods. Therefore, this paper reviews intratumoral heterogeneity. The review in this aspect examines new experimental data, including those obtained using single-cell technologies, in particular, the key cell populations that make up the pool of tumor cells in glioblastoma, and their molecular metamodules, the presumptive role of some cell populations and their subpopulations in providing tumor malignancy properties. A promising groundwork for fundamentally new approaches to creating personalized diagnostic and therapeutic methods is indicated. Keywords: glioblastoma, intratumoral heterogeneity, glioblastoma genetics, single-cell sequencing

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