Application Of Single-cell Technology Research Articles

A transfer learning framework to elucidate the clinical relevance of altered proximal tubule cell states in kidney disease

The application of single-cell technologies in clinical nephrology remains elusive. We generated an atlas of transcriptionally defined cell types and cell states of human kidney disease by integrating single-cell signatures reported in the literature with newly generated signatures obtained from 5 patients with acute kidney injury. We used this information to develop kidney-specific cell-level information ExtractoR (K-CLIER), a transfer learning approach specifically tailored to evaluate the role of cell types/states on bulk RNAseq data. We validated the K-CLIER as a reliable computational framework to obtain a dimensionality reduction and to link clinical data with single-cell signatures. By applying K-CLIER on cohorts of patients with different kidney diseases, we identified the most relevant cell types associated with fibrosis and disease progression. This analysis highlighted the central role of altered proximal tubule cells in chronic kidney disease. Our study introduces a new strategy to exploit the power of single-cell technologies toward clinical applications.

#3186 INVESTIGATING TREM2 MACROPHAGES IN CHRONIC KIDNEY DISEASE

Abstract Background and Aims Kidney macrophages have been implicated in interstitial fibrosis and inflammation in various forms of chronic kidney disease (CKD), but subsets with different markers and putative functions have been identified through the application of single cell technologies. A recent study from the Greka Lab revealed distinct macrophage populations in the human kidney bearing lymphatic endothelium hyaluronan receptor-1 (LYVE1) and triggering receptor expressed on myeloid cells-2 (TREM2). Notably, TREM2+ macrophages, which have been implicated in limiting metabolic toxicity in chronic diseases, were enriched in diabetic mouse kidneys and human kidneys from obese individuals (Subramanian et al. BioRvix 2021). To support these findings, we aimed at characterizing LYVE1+ and TREM2+ macrophages in kidney samples taken from subjects with CKD-associated co-morbidities, including hypertension, diabetes mellitus and obesity. Method We performed immunofluorescence microscopy of samples collected from the cortex of kidneys donated for transplantation but deemed unsuitable for implantation. Each sample was stained with anti-CD163, -LYVE1, and -TREM2 antibodies, plus Hoechst to stain nuclei. Two identically sized fields of view were imaged in each sample. Macrophages were identified based on CD163 expression and the expression of the LYVE1 and TREM2 in macrophages delineated. Macrophage subsets were compared according to age, BMI, eGFR and the presence of hypertension, obesity and diabetes. Results of 49 donors assessed, 19 (39%) were “healthy”, six (12%) “hypertensive” without obesity or diabetes, 16 (33%) “obese” with no evidence of diabetes, and 8 (16%) “diabetic” (all had type 2 diabetes and 6/8 were also obese) The median eGFR at donation was 95 mL/min/1.73 m2 and none of the donors had a history of CKD. Gender, median age and cause of death were not significantly different as well (Table 1). “Healthy”, “hypertensive” and “obese” donors had similar numbers of total macrophages, LYVE1+ and TREM2+ macrophages per region of interest. In contrast, “diabetic” subjects had a tendency towards a higher macrophage count (P = .10) and significantly higher numbers of LYVE1+ (P = .02) and TREM2+ macrophages (P = .002), compared to “healthy” ones (see Figure 1). The median LYVE1+/CD163+ ratio was 0.69 and did not differ substantially between the groups (P = .18), while the TREM2+/CD163+ ratio was higher among “diabetic” compared to “healthy” donors (0.43 vs 0.34, P = .06). Conclusion Diabetes is associated with an increase in kidney macrophages, particularly in those expressing TREM2. Further investigation is required to determine the role these cells may play in CKD progression.

Corticogenesis across species at single-cell resolution.

The neocortex (or pallium) consists of diverse cell types that are organized in a highly species-specific manner under strict spatiotemporal control during development. Many of the cell types are present transiently throughout development but contribute to permanent species-specific cortical features that are acquired through evolution. Therefore, capturing cell type-specific biological information has always been an important quest in the field of neurodevelopment. The progress in achieving fine cellular resolution has been slow due to technical challenges. However, with recent advancements in single-cell and multi-omics technologies, many laboratories have begun to successfully interrogate cellular and molecular mechanisms driving corticogenesis at single-cell resolution. In this review, we provide summarized results from many primary publications and several in-depth review articles that utilize or address single-cell genomics techniques to understand important topics, such as cellular and molecular mechanisms governing cortical progenitor proliferation, cell lineage progression, neuronal specification, and arealization, across multiple gyrencephalic (i.e., human and non-human primates) and lissencephalic species (i.e., mouse, reptiles, and songbirds). We also examine findings from recent studies involving epigenomic and posttranscriptional regulation of corticogenesis. In the discussion section, we provide our insights on the challenges the field currently faces as well as promising future applications of single cell technologies.

Single-Cell Transcriptional Analysis Deciphers the Inflammatory Response of Skin-Resident Stromal Cells.

The skin is the outermost barrier of the body. It has developed a sophisticated system against the ever-changing environment. The application of single-cell technologies has revolutionized dermatology research and unraveled the changes and interactions across skin resident cells in the healthy and inflamed skin. Single-cell technologies have revealed the critical roles of stromal cells in an inflammatory response and explained a series of plausible previous findings concerning skin immunity. Here, we summarized the functional diversity of skin stromal cells defined by single-cell analyses and how these cells orchestrated events leading to inflammatory diseases, including atopic dermatitis, psoriasis, vitiligo, and systemic lupus erythematosus.

Characterization of cell-cell communication in autistic brains with single-cell transcriptomes

BackgroundAutism spectrum disorder is a neurodevelopmental disorder, affecting 1–2% of children. Studies have revealed genetic and cellular abnormalities in the brains of affected individuals, leading to both regional and distal cell communication deficits.MethodsRecent application of single-cell technologies, especially single-cell transcriptomics, has significantly expanded our understanding of brain cell heterogeneity and further demonstrated that multiple cell types and brain layers or regions are perturbed in autism. The underlying high-dimensional single-cell data provides opportunities for multilevel computational analysis that collectively can better deconvolute the molecular and cellular events altered in autism. Here, we apply advanced computation and pattern recognition approaches on single-cell RNA-seq data to infer and compare inter-cell-type signaling communications in autism brains and controls.ResultsOur results indicate that at a global level, there are cell-cell communication differences in autism in comparison with controls, largely involving neurons as both signaling senders and receivers, but glia also contribute to the communication disruption. Although the magnitude of changes is moderate, we find that excitatory and inhibitor neurons are involved in multiple intercellular signaling that exhibits increased strengths in autism, such as NRXN and CNTN signaling. Not all genes in the intercellular signaling pathways show differential expression, but genes in the affected pathways are enriched for axon guidance, synapse organization, neuron migration, and other critical cellular functions. Furthermore, those genes are highly connected to and enriched for genes previously associated with autism risks.ConclusionsOverall, our proof-of-principle computational study using single-cell data uncovers key intercellular signaling pathways that are potentially disrupted in the autism brains, suggesting that more studies examining cross-cell type effects can be valuable for understanding autism pathogenesis.

The Application of Single-Cell Technologies in Cardiovascular Research.

Cardiovascular diseases (CVDs) are the leading cause of deaths in the world. The intricacies of the cellular composition and tissue microenvironment in heart and vasculature complicate the dissection of molecular mechanisms of CVDs. Over the past decade, the rapid development of single-cell omics technologies generated vast quantities of information at various biological levels, which have shed light on the cellular and molecular dynamics in cardiovascular development, homeostasis and diseases. Here, we summarize the latest single-cell omics techniques, and show how they have facilitated our understanding of cardiovascular biology. We also briefly discuss the clinical value and future outlook of single-cell applications in the field.

Current Insights and Advancements in Head and Neck Cancer: Emerging Biomarkers and Therapeutics with Cues from Single Cell and 3D Model Omics Profiling.

Head and neck cancer (HNC) is among the ten leading malignancies worldwide, with India solely contributing one-third of global oral cancer cases. The current focus of all cutting-edge strategies against this global malignancy are directed towards the heterogeneous tumor microenvironment that obstructs most treatment blueprints. Subsequent to the portrayal of established information, the review details the application of single cell technology, organoids and spheroid technology in relevance to head and neck cancer and the tumor microenvironment acknowledging the resistance pattern of the heterogeneous cell population in HNC. Bioinformatic tools are used for study of differentially expressed genes and further omics data analysis. However, these tools have several challenges and limitations when analyzing single-cell gene expression data that are discussed briefly. The review further examines the omics of HNC, through comprehensive analyses of genomics, transcriptomics, proteomics, metabolomics, and epigenomics profiles. Patterns of alterations vary between patients, thus heterogeneity and molecular alterations between patients have driven the clinical significance of molecular targeted therapies. The analyses of potential molecular targets in HNC are discussed with connotation to the alteration of key pathways in HNC followed by a comprehensive study of protein kinases as novel drug targets including its ATPase and additional binding pockets, non-catalytic domains and single residues. We herein review, the therapeutic agents targeting the potential biomarkers in light of new molecular targeted therapies. In the final analysis, this review suggests that the development of improved target-specific personalized therapies can combat HNC’s global plight.

Biomarkers for Precision Urothelial Carcinoma Diagnosis: Current Approaches and the Application of Single-Cell Technologies.

Simple SummaryUrothelial carcinoma (UC) is the most frequently diagnosed cancer of the urinary tract and is ranked the sixth most diagnosed cancer in men worldwide. About 70–75% of newly diagnosed UCs are non-invasive or low grade. Different tests such as urine cytology and cystoscopy are used to detect UC. If abnormal tissue is found during cystoscopy, then a biopsy will be performed. Cytology has low sensitivity for low-grade cancer while cystoscopy is invasive and costly. Detecting UC early improves the chances of treatment success. Therefore, many researchers have painstakingly identified urine biological markers for non-invasive UC diagnosis. In this review, we summarize some of the latest and most promising biological markers (including FDA-approved and investigational markers). We also discuss some new technologies that can aid research efforts in biological marker discovery for early UC detection.Urothelial carcinoma (UC) is the most frequent malignancy of the urinary system and is ranked the sixth most diagnosed cancer in men worldwide. Around 70–75% of newly diagnosed UC manifests as the non-muscle invasive bladder cancer (NMIBC) subtype, which can be treated by a transurethral resection of the tumor. However, patients require life-long monitoring due to its high rate of recurrence. The current gold standard for UC diagnosis, prognosis, and disease surveillance relies on a combination of cytology and cystoscopy, which is invasive, costly, and associated with comorbidities. Hence, there is considerable interest in the development of highly specific and sensitive urinary biomarkers for the non-invasive early detection of UC. In this review, we assess the performance of current diagnostic assays for UC and highlight some of the most promising biomarkers investigated to date. We also highlight some of the recent advances in single-cell technologies that may offer a paradigm shift in the field of UC biomarker discovery and precision diagnostics.

Overview of Trends in Global Single Cell Research Based on Bibliometric Analysis and LDA Model (2009–2019)

Abstract Purpose This article aims to describe the global research profile and the development trends of single cell research from the perspective of bibliometric analysis and semantic mining. Design/methodology/approach The literatures on single cell research were extracted from Clarivate Analytic's Web of Science Core Collection between 2009 and 2019. Firstly, bibliometric analyses were performed with Thomson Data Analyzer (TDA). Secondly, topic identification and evolution trends of single cell research was conducted through the LDA topic model. Thirdly, taking the post-discretized method which is used for topic evolution analysis for reference, the topics were also be dispersed to countries to detect the spatial distribution. Findings The publication of single cell research shows significantly increasing tendency in the last decade. The topics of single cell research field can be divided into three categories, which respectively refers to single cell research methods, mechanism of biological process, and clinical application of single cell technologies. The different trends of these categories indicate that technological innovation drives the development of applied research. The continuous and rapid growth of the topic strength in the field of cancer diagnosis and treatment indicates that this research topic has received extensive attention in recent years. The topic distributions of some countries are relatively balanced, while for the other countries, several topics show significant superiority. Research limitations The analyzed data of this study only contain those were included in the Web of Science Core Collection. Practical implications This study provides insights into the research progress regarding single cell field and identifies the most concerned topics which reflect potential opportunities and challenges. The national topic distribution analysis based on the post-discretized analysis method extends topic analysis from time dimension to space dimension. Originality/value This paper combines bibliometric analysis and LDA model to analyze the evolution trends of single cell research field. The method of extending post-discretized analysis from time dimension to space dimension is distinctive and insightful.

Application of single-cell RNA sequencing methodologies in understanding haematopoiesis and immunology.

The blood and immune system are characterised by utmost diversity in its cellular components. This heterogeneity can solely be resolved with the application of single-cell technologies that enable precise examination of cell-to-cell variation. Single-cell transcriptomics is continuously pushing forward our understanding of processes driving haematopoiesis and immune responses in physiological settings as well as in disease. Remarkably, in the last five years, a number of studies involving single-cell RNA sequencing (scRNA-seq) allowed the discovery of new immune cell types and revealed that haematopoiesis is a continuous rather than a stepwise process, thus challenging the classical haematopoietic lineage tree model. This review summarises the most recent studies which applied scRNA-seq to answer outstanding questions in the fields of haematology and immunology and discusses the present challenges and future directions.

Application of Single Cell Sequencing in Cancer.

Cancer is a heterogenetic disease at both the level of clinical manifestation and the level of the genome. Single-cell sequencing provides an unprecedented means of characterizing the intra-tumor heterogeneity and detecting and analyzing the genomes of cancer cells. These data will help to reconstruct the understanding of the evolutionary lineage of cancer cells. In the future, single-cell technology is believed to be a useful tool in diagnostic and prognostic application in oncology. The application of single cell technology in clinics will make it possible to detect cancer non-invasively at early stages and to develop precision medicine. In this chapter, we review the research and application status of the single cell technology in cancer.

Single-cell technologies to study the immune system.

The immune system is composed of a variety of cells that act in a coordinated fashion to protect the organism against a multitude of different pathogens. The great variability of existing pathogens corresponds to a similar high heterogeneity of the immune cells. The study of individual immune cells, the fundamental unit of immunity, has recently transformed from a qualitative microscopic imaging to a nearly complete quantitative transcriptomic analysis. This shift has been driven by the rapid development of multiple single-cell technologies. These new advances are expected to boost the detection of less frequent cell types and transient or intermediate cell states. They will highlight the individuality of each single cell and greatly expand the resolution of current available classifications and differentiation trajectories. In this review we discuss the recent advancement and application of single-cell technologies, their limitations and future applications to study the immune system.