Triku: a feature selection method based on nearest neighbors for single-cell data

Abstract BACKGROUND: Feature selection is a relevant step in the analysis of single-cell RNA sequencing datasets. Most of the current feature selection methods are based on general univariate descriptors of the data such as the dispersion or the percentage of zeros. Despite the use of correction methods, the generality of these feature selection methods biases the genes selected towards highly expressed genes, instead of the genes defining the cell populations of the dataset. RESULTS: Triku is a feature selection method that favors genes defining the main cell populations. It does so by selecting genes expressed by groups of cells that are close in the k-nearest neighbor graph. The expression of these genes is higher than the expected expression if the k-cells were chosen at random. Triku efficiently recovers cell populations present in artificial and biological benchmarking datasets, based on adjusted Rand index, normalized mutual information, supervised classification, and silhouette coefficient measurements. Additionally, gene sets selected by triku are more likely to be related to relevant Gene Ontology terms and contain fewer ribosomal and mitochondrial genes. CONCLUSION: Triku is developed in Python 3 and is available at https://github.com/alexmascension/triku.This work was supported by grants from Instituto de Salud Carlos III (AC17/00012 and PI19/01621), cofunded by the Euro- pean Union (European Regional Development Fund/European Sci- ence Foundation, Investing in your future) and the 4D-HEALING project (ERA-Net program EracoSysMed, JTC-2 2017); Diputación Foral de Gipuzkoa, and the Department of Economic Devel- opment and Infrastructures of the Basque Government (KK- 2019/00006, KK-2019/00093); European Union FET project Cir- cular Vision (H2020-FETOPEN, Project 899417), Ministry of Sci- ence and Innovation of Spain; and PID2020-119715GB-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe. A.M.A. was supported by a Basque Govern- ment Postgraduate Diploma fellowship (PRE_2020_2_0081), and O.I.S. was supported by a Postgraduate Diploma fellowship from la Caixa Foundation (identification document 100010434; code LCF/BQ/IN18/11660065)

Signal integration and transcriptional regulation of the inflammatory response mediated by the GM-/MCSF signaling axis in human monocytes

In recent years, the macrophage colony-stimulating factor (M-CSF) and granulocyte-macrophage CSF (GM-CSF) cytokines have been identified as opposing regulators of the inflammatory program. However, the two cytokines are simultaneously present in the inflammatory milieu, and it is not clear how cells integrate these signals. In order to understand the regulatory networks associated with the GM/M-CSF signaling axis, we analyzed DNA methylation in human monocytes. Our results indicate that GM-CSF induces activation of the inflammatory program and extensive DNA methylation changes, while M-CSF-polarized cells are in a less differentiated state. This inflammatory program is mediated via JAK2 associated with the GM-CSF receptor and the downstream extracellular signal-regulated (ERK) signaling. However, PI3K signaling is associated with a negative regulatory loop of the inflammatory program and M-CSF autocrine signaling in GM-CSF-polarized monocytes. Our findings describe the regulatory networks associated with the GM/M-CSF signaling axis and how they contribute to the establishment of the inflammatory program associated with monocyte activation.This work was supported by grants from the Plan Nacional de I+D+I 2013– 2016 ISCIII (Institute of Health Carlos III; PI16/01318, PI17/01244, PI17/ 0119, PI16/1900, and PI19/00184); the Gobierno del Principado de Asturias; the PCTI-Plan de Ciencia, Tecnologı´a e Innovacio´ n 2013-2017 (grant IDI/ 2018/144); FEDER ‘‘Funding Program of the European Union’’; the Red Española de Investigación Renal (REDinREN) (RD16/0009/0020, RD016/0009/002, and RD016/0009/001); the Agencia Estatal de Investigación (AEI) (ayuda Juan de la Cierva-Incorporaciόn; IJCI-2017-33347 to R.M.R.); and the Instituto de Salud Carlos III (Contratos Sara Borrell; CD16/00033 to C.H.). CIC bioGUNE support was provided by the Basque Department of Industry, Tourism and Trade (Etortek and Elkartek programs), the Innovation Technology Department of Bizkaia County, the CIBERehd Network, and Spanish MINECO, the Severo Ochoa Excellence Accreditation (SEV-2016-0644

Inflammation-mediated fibroblast activation and immune dysregulation in collagen VII-deficient skin

Inflammation is known to play a critical role in all stages of tumorigenesis; however, less is known about how it predisposes the tissue microenvironment preceding tumor formation. Recessive dystrophic epidermolysis bullosa (RDEB), a skin-blistering disease secondary to COL7A1 mutations and associated with chronic wounding, inflammation, fibrosis, and cutaneous squamous cell carcinoma (cSCC), models this dynamic. Here, we used single-cell RNA sequencing (scRNAseq) to analyze gene expression patterns in skin cells from a mouse model of RDEB. We uncovered a complex landscape within the RDEB dermal microenvironment that exhibited altered metabolism, enhanced angiogenesis, hyperproliferative keratinocytes, infiltration and activation of immune cell populations, and inflammatory fibroblast priming. We demonstrated the presence of activated neutrophil and Langerhans cell subpopulations and elevated expression of PD-1 and PD-L1 in T cells and antigen-presenting cells, respectively. Unsupervised clustering within the fibroblast population further revealed two differentiation pathways in RDEB fibroblasts, one toward myofibroblasts and the other toward a phenotype that shares the characteristics of inflammatory fibroblast subsets in other inflammatory diseases as well as the IL-1-induced inflammatory cancer-associated fibroblasts (iCAFs) reported in various cancer types. Quantitation of inflammatory cytokines indicated dynamic waves of IL-1α, TGF-β1, TNF, IL-6, and IFN-γ concentrations, along with dermal NF-κB activation preceding JAK/STAT signaling. We further demonstrated the divergent and overlapping roles of these cytokines in inducing inflammatory phenotypes in RDEB patients as well as RDEB mouse-derived fibroblasts together with their healthy controls. In summary, our data have suggested a potential role of inflammation, driven by the chronic release of inflammatory cytokines such as IL-1, in creating an immune-suppressed dermal microenvironment that underlies RDEB disease progression

Challenges and Opportunities for the Translation of Single-Cell RNA Sequencing Technologies to Dermatology

Skin is a complex and heterogeneous organ at the cellular level. This complexity is beginning to be understood through the application of single-cell genomics and computational tools. A large number of datasets that shed light on how the different human skin cell types interact in homeostasis—and what ceases to work in diverse dermatological diseases—have been generated and are publicly available. However, translation of these novel aspects to the clinic is lacking. This review aims to summarize the state-of-the-art of skin biology using single-cell technologies, with a special focus on skin pathologies and the translation of mechanistic findings to the clinic. The main implications of this review are to summarize the benefits and limitations of single-cell analysis and thus help translate the emerging insights from these novel techniques to the bedside

NaviSE: superenhancer navigator integrating epigenomics signal algebra

Abstract Background Superenhancers are crucial structural genomic elements determining cell fate, and they are also involved in the determination of several diseases, such as cancer or neurodegeneration. Although there are pipelines which use independent pieces of software to predict the presence of superenhancers from genome-wide chromatin marks or DNA-interaction protein binding sites, there is not yet an integrated software tool that processes automatically algebra combinations of raw data sequencing into a comprehensive final annotated report of predicted superenhancers. Results We have developed NaviSE, a user-friendly streamlined tool which performs a fully-automated parallel processing of genome-wide epigenomics data from sequencing files into a final report, built with a comprehensive set of annotated files that are navigated through a graphic user interface dynamically generated by NaviSE. NaviSE also implements an ‘epigenomics signal algebra’ that allows the combination of multiple activation and repression epigenomics signals. NaviSE provides an interactive chromosomal landscaping of the locations of superenhancers, which can be navigated to obtain annotated information about superenhancer signal profile, associated genes, gene ontology enrichment analysis, motifs of transcription factor binding sites enriched in superenhancers, graphs of the metrics evaluating the superenhancers quality, protein-protein interaction networks and enriched metabolic pathways among other features. We have parallelised the most time-consuming tasks achieving a reduction up to 30% for a 15 CPUs machine. We have optimized the default parameters of NaviSE to facilitate its use. NaviSE allows different entry levels of data processing, from sra-fastq files to bed files; and unifies the processing of multiple replicates. NaviSE outperforms the more time-consuming processes required in a non-integrated pipeline. Alongside its high performance, NaviSE is able to provide biological insights, predicting cell type specific markers, such as SOX2 and ZIC3 in embryonic stem cells, CDK5R1 and REST in neurons and CD86 and TLR2 in monocytes. Conclusions NaviSE is a user-friendly streamlined solution for superenhancer analysis, annotation and navigation, requiring only basic computer and next generation sequencing knowledge. NaviSE binaries and documentation are available at: https://sourceforge.net/projects/navise-superenhancer/

Inflammation-Mediated Fibroblast Activation and Immune Dysregulation in Collagen VII-Deficient Skin

Inflammation is known to play a critical role in all stages of tumorigenesis; however, less is known about how it predisposes the tissue microenvironment preceding tumor formation. Recessive dystrophic epidermolysis bullosa (RDEB), a skin-blistering disease secondary to mutations and associated with chronic wounding, inflammation, fibrosis, and cutaneous squamous cell carcinoma (cSCC), models this dynamic. Here, we used single-cell RNA sequencing (scRNAseq) to analyze gene expression patterns in skin cells from a mouse model of RDEB. We uncovered a complex landscape within the RDEB dermal microenvironment that exhibited altered metabolism, enhanced angiogenesis, hyperproliferative keratinocytes, infiltration and activation of immune cell populations, and inflammatory fibroblast priming. We demonstrated the presence of activated neutrophil and Langerhans cell subpopulations and elevated expression of PD-1 and PD-L1 in T cells and antigen-presenting cells, respectively. Unsupervised clustering within the fibroblast population further revealed two differentiation pathways in RDEB fibroblasts, one toward myofibroblasts and the other toward a phenotype that shares the characteristics of inflammatory fibroblast subsets in other inflammatory diseases as well as the IL-1-induced inflammatory cancer-associated fibroblasts (iCAFs) reported in various cancer types. Quantitation of inflammatory cytokines indicated dynamic waves of IL-1α, TGF-β1, TNF, IL-6, and IFN-γ concentrations, along with dermal NF-κB activation preceding JAK/STAT signaling. We further demonstrated the divergent and overlapping roles of these cytokines in inducing inflammatory phenotypes in RDEB patients as well as RDEB mouse-derived fibroblasts together with their healthy controls. In summary, our data have suggested a potential role of inflammation, driven by the chronic release of inflammatory cytokines such as IL-1, in creating an immune-suppressed dermal microenvironment that underlies RDEB disease progression

DataSheet_1_Inflammation-mediated fibroblast activation and immune dysregulation in collagen VII-deficient skin.zip

Inflammation is known to play a critical role in all stages of tumorigenesis; however, less is known about how it predisposes the tissue microenvironment preceding tumor formation. Recessive dystrophic epidermolysis bullosa (RDEB), a skin-blistering disease secondary to COL7A1 mutations and associated with chronic wounding, inflammation, fibrosis, and cutaneous squamous cell carcinoma (cSCC), models this dynamic. Here, we used single-cell RNA sequencing (scRNAseq) to analyze gene expression patterns in skin cells from a mouse model of RDEB. We uncovered a complex landscape within the RDEB dermal microenvironment that exhibited altered metabolism, enhanced angiogenesis, hyperproliferative keratinocytes, infiltration and activation of immune cell populations, and inflammatory fibroblast priming. We demonstrated the presence of activated neutrophil and Langerhans cell subpopulations and elevated expression of PD-1 and PD-L1 in T cells and antigen-presenting cells, respectively. Unsupervised clustering within the fibroblast population further revealed two differentiation pathways in RDEB fibroblasts, one toward myofibroblasts and the other toward a phenotype that shares the characteristics of inflammatory fibroblast subsets in other inflammatory diseases as well as the IL-1-induced inflammatory cancer-associated fibroblasts (iCAFs) reported in various cancer types. Quantitation of inflammatory cytokines indicated dynamic waves of IL-1α, TGF-β1, TNF, IL-6, and IFN-γ concentrations, along with dermal NF-κB activation preceding JAK/STAT signaling. We further demonstrated the divergent and overlapping roles of these cytokines in inducing inflammatory phenotypes in RDEB patients as well as RDEB mouse-derived fibroblasts together with their healthy controls. In summary, our data have suggested a potential role of inflammation, driven by the chronic release of inflammatory cytokines such as IL-1, in creating an immune-suppressed dermal microenvironment that underlies RDEB disease progression.</p

Ideal cardiovascular health and inflammation in European adolescents: The HELENA study

The HELENA study: et al.[Background and aims]: Inflammation plays a key role in atherosclerosis and this process seems to appear in childhood. The ideal cardiovascular health index (ICHI) has been inversely related to atherosclerotic plaque in adults. However, evidence regarding inflammation and ICHI in adolescents is scarce. The aim is to assess the association between ICHI and inflammation in European adolescents.[Methods and results]: As many as 543 adolescents (251 boys and 292 girls) from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study, a cross-sectional multi-center study including 9 European countries, were measured. C-reactive protein (CRP), complement factors C3 and C4, leptin and white blood cell counts were used to compute an inflammatory score. Multilevel linear models and multilevel logistic regression were used to assess the association between ICHI and inflammation controlling by covariates. Higher ICHI was associated with a lower inflammatory score, as well as with several individual components, both in boys and girls (p < 0.01). In addition, adolescents with at least 4 ideal components of the ICHI had significantly lower inflammatory score and lower levels of the study biomarkers, except CRP. Finally, the multilevel logistic regression showed that for every unit increase in the ICHI, the probability of having an inflammatory profile decreased by 28.1% in girls.[Conclusion]: Results from this study suggest that a better ICHI is associated with a lower inflammatory profile already in adolescence. Improving these health behaviors, and health factors included in the ICHI, could play an important role in CVD prevention.The HELENA Study was supported by the European Community Sixth RTD Framework Programme (Contract FOOD-CT-2005-007034). This analysis was also supported by the Spanish Ministry of Science and Innovation (JCI-2010-07055) and the European Regional Development Fund (FEDER). A grant from the Spanish Ministry of Economy and Competitiveness was received by JRR (grants RYC-2010-05957).Peer reviewe