ORCID Profile
0000-0001-8539-2784
Current Organisation
Helmholtz Institute for RNA-based Infection Research
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Publisher: Elsevier BV
Date: 04-2022
DOI: 10.1016/J.IMMUNI.2022.03.006
Abstract: Reinvigoration of exhausted CD8
Publisher: PeerJ
Date: 23-08-2019
DOI: 10.7287/PEERJ.PREPRINTS.27885V3
Abstract: The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis together, they give rise to the new realm of 'Single-Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single-Cell Data Science' for the coming years.
Publisher: Elsevier BV
Date: 10-2022
DOI: 10.1016/J.IMMUNI.2022.07.019
Abstract: Lymphatic transport of molecules and migration of myeloid cells to lymph nodes (LNs) continuously inform lymphocytes on changes in drained tissues. Here, using LN transplantation, single-cell RNA-seq, spectral flow cytometry, and a transgenic mouse model for photolabeling, we showed that tissue-derived unconventional T cells (UTCs) migrate via the lymphatic route to locally draining LNs. As each tissue harbored a distinct spectrum of UTCs with locally adapted differentiation states and distinct T cell receptor repertoires, every draining LN was thus populated by a distinctive tissue-determined mix of these lymphocytes. By making use of single UTC lineage-deficient mouse models, we found that UTCs functionally cooperated in interconnected units and generated and shaped characteristic innate and adaptive immune responses that differed between LNs that drained distinct tissues. Lymphatic migration of UTCs is, therefore, a key determinant of site-specific immunity initiated in distinct LNs with potential implications for vaccination strategies and immunotherapeutic approaches.
Publisher: PeerJ
Date: 06-08-2019
DOI: 10.7287/PEERJ.PREPRINTS.27885V1
Abstract: The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis together, they give rise to the new realm of 'Single Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single Cell Data Science' for the coming years.
Publisher: PeerJ
Date: 07-08-2019
DOI: 10.7287/PEERJ.PREPRINTS.27885V2
Abstract: The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis together, they give rise to the new realm of 'Single Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single Cell Data Science' for the coming years.
Location: Germany
No related grants have been discovered for Antoine-Emmanuel Saliba.