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1.
Nature ; 598(7879): 111-119, 2021 10.
Artículo en Inglés | MEDLINE | ID: mdl-34616062

RESUMEN

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch-seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.


Asunto(s)
Corteza Motora/citología , Neuronas/clasificación , Análisis de la Célula Individual , Animales , Atlas como Asunto , Callithrix/genética , Epigénesis Genética , Epigenómica , Femenino , Neuronas GABAérgicas/citología , Neuronas GABAérgicas/metabolismo , Perfilación de la Expresión Génica , Glutamatos/metabolismo , Humanos , Hibridación Fluorescente in Situ , Masculino , Ratones , Persona de Mediana Edad , Corteza Motora/anatomía & histología , Neuronas/citología , Neuronas/metabolismo , Especificidad de Órganos , Filogenia , Especificidad de la Especie , Transcriptoma
3.
BMC Genomics ; 19(Suppl 6): 569, 2018 Aug 13.
Artículo en Inglés | MEDLINE | ID: mdl-30367575

RESUMEN

BACKGROUND: Single cell transcriptomics is critical for understanding cellular heterogeneity and identification of novel cell types. Leveraging the recent advances in single cell RNA sequencing (scRNA-Seq) technology requires novel unsupervised clustering algorithms that are robust to high levels of technical and biological noise and scale to datasets of millions of cells. RESULTS: We present novel computational approaches for clustering scRNA-seq data based on the Term Frequency - Inverse Document Frequency (TF-IDF) transformation that has been successfully used in the field of text analysis. CONCLUSIONS: Empirical experimental results show that TF-IDF methods consistently outperform commonly used scRNA-Seq clustering approaches.


Asunto(s)
Perfilación de la Expresión Génica/métodos , Análisis de Secuencia de ARN/métodos , Algoritmos , Análisis por Conglomerados , Análisis de la Célula Individual
4.
J Comput Biol ; 28(8): 820-841, 2021 08.
Artículo en Inglés | MEDLINE | ID: mdl-34115950

RESUMEN

Single-cell RNA-Seq (scRNA-Seq) is critical for studying cellular function and phenotypic heterogeneity as well as the development of tissues and tumors. In this study, we present SC1 a web-based highly interactive scRNA-Seq data analysis tool publicly accessible at https://sc1.engr.uconn.edu. The tool presents an integrated workflow for scRNA-Seq analysis, implements a novel method of selecting informative genes based on term-frequency inverse-document-frequency scores, and provides a broad range of methods for clustering, differential expression analysis, gene enrichment, interactive visualization, and cell cycle analysis. The tool integrates other single-cell omics data modalities such as T-cell receptor (TCR)-Seq and supports several single-cell sequencing technologies. In just a few steps, researchers can generate a comprehensive analysis and gain powerful insights from their scRNA-Seq data.


Asunto(s)
Biología Computacional/métodos , Perfilación de la Expresión Génica/métodos , Análisis de la Célula Individual/métodos , Regulación de la Expresión Génica , Humanos , Internet , Análisis de Secuencia de ARN , Programas Informáticos
5.
Nat Commun ; 12(1): 6423, 2021 11 05.
Artículo en Inglés | MEDLINE | ID: mdl-34741035

RESUMEN

High-affinity MHC I-peptide interactions are considered essential for immunogenicity. However, some neo-epitopes with low affinity for MHC I have been reported to elicit CD8 T cell dependent tumor rejection in immunization-challenge studies. Here we show in a mouse model that a neo-epitope that poorly binds to MHC I is able to enhance the immunogenicity of a tumor in the absence of immunization. Fibrosarcoma cells with a naturally occurring mutation are edited to their wild type counterpart; the mutation is then re-introduced in order to obtain a cell line that is genetically identical to the wild type except for the neo-epitope-encoding mutation. Upon transplantation into syngeneic mice, all three cell lines form tumors that are infiltrated with activated T cells. However, lymphocytes from the two tumors that harbor the mutation show significantly stronger transcriptional signatures of cytotoxicity and TCR engagement, and induce greater breadth of TCR reactivity than those of the wild type tumors. Structural modeling of the neo-epitope peptide/MHC I pairs suggests increased hydrophobicity of the neo-epitope surface, consistent with higher TCR reactivity. These results confirm the in vivo immunogenicity of low affinity or 'non-binding' epitopes that do not follow the canonical concept of MHC I-peptide recognition.


Asunto(s)
Epítopos de Linfocito T/genética , Epítopos de Linfocito T/inmunología , Neoplasias/inmunología , Linfocitos T CD8-positivos/metabolismo , Linfocitos T CD8-positivos/fisiología , Mutación/genética , Neoplasias/genética , Neoplasias/metabolismo
6.
J Clin Invest ; 131(3)2021 02 01.
Artículo en Inglés | MEDLINE | ID: mdl-33320837

RESUMEN

Identification of neoepitopes that are effective in cancer therapy is a major challenge in creating cancer vaccines. Here, using an entirely unbiased approach, we queried all possible neoepitopes in a mouse cancer model and asked which of those are effective in mediating tumor rejection and, independently, in eliciting a measurable CD8 response. This analysis uncovered a large trove of effective anticancer neoepitopes that have strikingly different properties from conventional epitopes and suggested an algorithm to predict them. It also revealed that our current methods of prediction discard the overwhelming majority of true anticancer neoepitopes. These results from a single mouse model were validated in another antigenically distinct mouse cancer model and are consistent with data reported in human studies. Structural modeling showed how the MHC I-presented neoepitopes had an altered conformation, higher stability, or increased exposure to T cell receptors as compared with the unmutated counterparts. T cells elicited by the active neoepitopes identified here demonstrated a stem-like early dysfunctional phenotype associated with effective responses against viruses and tumors of transgenic mice. These abundant anticancer neoepitopes, which have not been tested in human studies thus far, can be exploited for generation of personalized human cancer vaccines.


Asunto(s)
Antígenos de Neoplasias , Vacunas contra el Cáncer , Epítopos de Linfocito T , Inmunoterapia , Neoplasias , Animales , Antígenos de Neoplasias/inmunología , Antígenos de Neoplasias/farmacología , Vacunas contra el Cáncer/inmunología , Vacunas contra el Cáncer/farmacología , Línea Celular Tumoral , Epítopos de Linfocito T/inmunología , Epítopos de Linfocito T/farmacología , Femenino , Ratones , Neoplasias/inmunología , Neoplasias/terapia
7.
Sci Immunol ; 5(51)2020 09 11.
Artículo en Inglés | MEDLINE | ID: mdl-32917793

RESUMEN

Sympathetic nerves that innervate lymphoid organs regulate immune development and function by releasing norepinephrine that is sensed by immune cells via their expression of adrenergic receptors. Here, we demonstrate that ablation of sympathetic nervous system (SNS) signaling suppresses tumor immunity, and we dissect the mechanism of such immune suppression. We report that disruption of the SNS in mice removes a critical α-adrenergic signal required for maturation of myeloid cells in normal and tumor-bearing mice. In tumor-bearing mice, disruption of the α-adrenergic signal leads to the accumulation of immature myeloid-derived suppressor cells (MDSCs) that suppress tumor immunity and promote tumor growth. Furthermore, we show that these SNS-responsive MDSCs drive expansion of regulatory T cells via secretion of the alarmin heterodimer S100A8/A9, thereby compounding their immunosuppressive activity. Our results describe a regulatory framework in which sympathetic tone controls the development of innate and adaptive immune cells and influences their activity in health and disease.


Asunto(s)
Células Supresoras de Origen Mieloide/inmunología , Sistema Nervioso Simpático/inmunología , Antagonistas Adrenérgicos/uso terapéutico , Animales , Calgranulina A/sangre , Calgranulina B/sangre , Línea Celular Tumoral , Femenino , Linfocitos Infiltrantes de Tumor/inmunología , Ratones Endogámicos BALB C , Neoplasias/sangre , Neoplasias/tratamiento farmacológico , Neoplasias/inmunología , Neoplasias/patología , Receptores Adrenérgicos/inmunología , Linfocitos T Reguladores/inmunología
8.
J Comput Biol ; 26(8): 822-835, 2019 08.
Artículo en Inglés | MEDLINE | ID: mdl-30785309

RESUMEN

One of the most notable challenges in single cell RNA-Seq data analysis is the so called drop-out effect, where only a fraction of the transcriptome of each cell is captured. The random nature of dropouts, however, makes it possible to consider imputation methods as means of correcting for dropouts. In this article, we study some existing single cell RNA sequencing (scRNA-Seq) imputation methods and propose a novel iterative imputation approach based on efficiently computing highly similar cells. We then present the results of a comprehensive assessment of existing and proposed methods on real scRNA-Seq data sets with varying per cell sequencing depth.


Asunto(s)
Bases de Datos de Ácidos Nucleicos , RNA-Seq , Análisis de la Célula Individual , Programas Informáticos
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