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Unbiased classification of mosquito blood cells by single-cell genomics and high-content imaging

Mosquito blood cells are immune cells that help control infection by vector-borne pathogens. Despite their importance, little is known about mosquito blood cell biology beyond morphological and functional criteria used for their classification. Here, we combined the power of single-cell RNA sequenci...

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Autores principales: Severo, Maiara S., Landry, Jonathan J. M., Lindquist, Randall L., Goosmann, Christian, Brinkmann, Volker, Collier, Paul, Hauser, Anja E., Benes, Vladimir, Henriksson, Johan, Teichmann, Sarah A., Levashina, Elena A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6094101/
https://www.ncbi.nlm.nih.gov/pubmed/30038005
http://dx.doi.org/10.1073/pnas.1803062115
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author Severo, Maiara S.
Landry, Jonathan J. M.
Lindquist, Randall L.
Goosmann, Christian
Brinkmann, Volker
Collier, Paul
Hauser, Anja E.
Benes, Vladimir
Henriksson, Johan
Teichmann, Sarah A.
Levashina, Elena A.
author_facet Severo, Maiara S.
Landry, Jonathan J. M.
Lindquist, Randall L.
Goosmann, Christian
Brinkmann, Volker
Collier, Paul
Hauser, Anja E.
Benes, Vladimir
Henriksson, Johan
Teichmann, Sarah A.
Levashina, Elena A.
author_sort Severo, Maiara S.
collection PubMed
description Mosquito blood cells are immune cells that help control infection by vector-borne pathogens. Despite their importance, little is known about mosquito blood cell biology beyond morphological and functional criteria used for their classification. Here, we combined the power of single-cell RNA sequencing, high-content imaging flow cytometry, and single-molecule RNA hybridization to analyze a subset of blood cells of the malaria mosquito Anopheles gambiae. By demonstrating that blood cells express nearly half of the mosquito transcriptome, our dataset represents an unprecedented view into their transcriptional program. Analyses of differentially expressed genes identified transcriptional signatures of two cell types and provide insights into the current classification of these cells. We further demonstrate the active transfer of a cellular marker between blood cells that may confound their identification. We propose that cell-to-cell exchange may contribute to cellular diversity and functional plasticity seen across biological systems.
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spelling pubmed-60941012018-08-17 Unbiased classification of mosquito blood cells by single-cell genomics and high-content imaging Severo, Maiara S. Landry, Jonathan J. M. Lindquist, Randall L. Goosmann, Christian Brinkmann, Volker Collier, Paul Hauser, Anja E. Benes, Vladimir Henriksson, Johan Teichmann, Sarah A. Levashina, Elena A. Proc Natl Acad Sci U S A PNAS Plus Mosquito blood cells are immune cells that help control infection by vector-borne pathogens. Despite their importance, little is known about mosquito blood cell biology beyond morphological and functional criteria used for their classification. Here, we combined the power of single-cell RNA sequencing, high-content imaging flow cytometry, and single-molecule RNA hybridization to analyze a subset of blood cells of the malaria mosquito Anopheles gambiae. By demonstrating that blood cells express nearly half of the mosquito transcriptome, our dataset represents an unprecedented view into their transcriptional program. Analyses of differentially expressed genes identified transcriptional signatures of two cell types and provide insights into the current classification of these cells. We further demonstrate the active transfer of a cellular marker between blood cells that may confound their identification. We propose that cell-to-cell exchange may contribute to cellular diversity and functional plasticity seen across biological systems. National Academy of Sciences 2018-08-07 2018-07-23 /pmc/articles/PMC6094101/ /pubmed/30038005 http://dx.doi.org/10.1073/pnas.1803062115 Text en Copyright © 2018 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle PNAS Plus
Severo, Maiara S.
Landry, Jonathan J. M.
Lindquist, Randall L.
Goosmann, Christian
Brinkmann, Volker
Collier, Paul
Hauser, Anja E.
Benes, Vladimir
Henriksson, Johan
Teichmann, Sarah A.
Levashina, Elena A.
Unbiased classification of mosquito blood cells by single-cell genomics and high-content imaging
title Unbiased classification of mosquito blood cells by single-cell genomics and high-content imaging
title_full Unbiased classification of mosquito blood cells by single-cell genomics and high-content imaging
title_fullStr Unbiased classification of mosquito blood cells by single-cell genomics and high-content imaging
title_full_unstemmed Unbiased classification of mosquito blood cells by single-cell genomics and high-content imaging
title_short Unbiased classification of mosquito blood cells by single-cell genomics and high-content imaging
title_sort unbiased classification of mosquito blood cells by single-cell genomics and high-content imaging
topic PNAS Plus
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6094101/
https://www.ncbi.nlm.nih.gov/pubmed/30038005
http://dx.doi.org/10.1073/pnas.1803062115
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