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Dr Antoine-Emmanuel Saliba

Single-cell Analysis

The research of Antoine-Emmanuel Saliba and his group is dedicated to using single-cell RNA-seq approaches to study heterogeneity in host responses to infections and its impact on disease outcome.

Our research and approach

Pathogenic bacteria can reside in a mammalian host for a life-long period and chronic carriers form a reservoir leading to recurrent infections. Despite the importance of chronic infections for public health, how subsets of pathogens escape the host’s immune surveillance and how the host contains the spread of bacteria are still poorly understood. Scientists within the Single-cell Analysis group develop and use single-cell transcriptomics and computational approaches to decipher the microenvironments of individual pathogens and ultimately their functional consequences on infection outcome.

Team members

Research projects

Persistent bacterial infections are caused by a minor subpopulation of intracellular pathogens, called ‘persisters’, that reside in different cell types and tissue locations for years asymptomatically. These subpopulations establish a specific cellular organization, which enables them to evade immune surveillance and chemotherapeutic treatment. Histological studies have described complex tissue remodelling during the infection and emerging in vivo studies at the single-cell level have begun to reveal the heterogeneity of infection foci. 

However, the cellular architecture of the infection foci and the identification of favoured niches within this complex tissue landscape that impact disease outcome remain open questions. For example, Salmonella are believed to reside in a large variety of cells including macrophages, neutrophils, dendritic cells and epithelial cells. These large cell types exist as a myriad of different sub-classes, which were - until recently - not appreciated. Similarly, within an infected tissue such as the spleen many infected cells escape inflammatory lesions and disseminate into tissues. Therefore, single-cell studies in an in vivo context are necessary to understand the heterogeneity inherent in infected cells, their microenvironment and their function. The Single-cell Analysis group develops and combines in vitro and in vivo single-cell transcriptomics to decipher the cellular organization of infection foci and their functional consequences for infection outcome.

The recent emergence of single-cell genome-wide transcriptomics is proving to be a powerful approach to decipher both cellular identities and function making it possible to study heterogeneity. This is being facilitated by the development of automated platforms that enable the processing of hundreds and thousands of single-cells in parallel. In the context of infection we have pioneered the use of single-cell RNA-seq to investigate heterogeneity in the response of mouse bone marrow-derived macrophages to Salmonella focusing on bacteria with different growth status including non-growing ‘persisters’ that have been linked to recurrent infections. We have described how Salmonella impact the wide spectrum of host polarization and revealed the existence of a subset of macrophages that escape inflammatory and immune activation programs. While providing new insights into the host response, the study was limited to analyzing infected cells from in vitro cultures. The next step is now to decipher the response of single cells of infected tissues, which remains an unmet challenge.

Moreover, the Single-cell Analysis group is fully committed to developing the full potential of single-cell RNA-seq for addressing fundamental scientific questions of infection biology in general, at the HIRI as well as at other locations of the HZI.

Publications

2020

Eleven grand challenges in single-cell data science

Lähnemann D, Köster J, Szczurek E, McCarthy D, Hicks S, Robinson M, Vallejos C, Campbell K, Beerenwinkel N, Mahfouz A, …, Shah S, Schönhuth A (2020)

Genome Biology, 21 (1): 31DOI: 10.1186/s13059-020-1926-6

2019

scSLAM-seq reveals core features of transcription dynamics in single cells

Erhard F, Baptista M, Krammer T, Hennig T, Lange M, Arampatzi P, Jürges C, Theis F, Saliba A, Dölken L (2019)

Nature, 571 (7765): 419-423DOI: 10.1038/s41586-019-1369-y

2018

Salmonella persisters undermine host immune defenses during antibiotic treatment

Stapels D, Hill P, Westermann A, Fisher R, Thurston T, Saliba A, Blommestein I, Vogel J, Helaine S (2018)

Science, 362 (6419): 1156-1160DOI: 10.1126/science.aat7148

Neonatally imprinted stromal cell subsets induce tolerogenic dendritic cells in mesenteric lymph nodes

Pezoldt J, Pasztoi M, Zou M, Wiechers C, Beckstette M, Thierry G, Vafadarnejad E, Floess S, Arampatzi P, Buettner M, …, Saliba A, Huehn J (2018)

Nature Communications, 9 (1): 3903DOI: 10.1038/s41467-018-06423-7

Single-Cell RNA-Seq Reveals the Transcriptional Landscape and Heterogeneity of Aortic Macrophages in Murine Atherosclerosis

Cochain C, Vafadarnejad E, Arampatzi P, Pelisek J, Winkels H, Ley K, Wolf D, Saliba A, Zernecke A (2018)

Circulation Research, 122 (12): 1661-1674DOI: 10.1161/CIRCRESAHA.117.312509

Atlas of the Immune Cell Repertoire in Mouse Atherosclerosis Defined by Single-Cell RNA-Sequencing and Mass Cytometry

Winkels H, Ehinger E, Vassallo M, Buscher K, Dinh H, Kobiyama K, Hamers A, Cochain C, Vafadarnejad E, Saliba A, …, Ley K, Wolf D (2018)

Circulation Research, 122 (12): 1675-1688DOI: 10.1161/CIRCRESAHA.117.312513

Genome organization and DNA accessibility control antigenic variation in trypanosomes

Müller L, Cosentino R, Förstner K, Guizetti J, Wedel C, Kaplan N, Janzen C, Arampatzi P, Vogel J, Steinbiss S, …, Sebra R, Siegel T (2018)

Nature, 563 (7729): 121-125DOI: 10.1038/s41586-018-0619-8

2017

Einzelzell-RNA-Sequenzierung beleuchtet den Infektionsprozess

Saliba A, Westermann A, Vogel J (2017)

BIOspektrum, 23 (5): 525-528DOI: 10.1007/s12268-017-0836-y

New RNA-seq approaches for the study of bacterial pathogens

Saliba A, C Santos S, Vogel J (2017)

Current Opinion In Microbiology, 35: 78-87DOI: 10.1016/j.mib.2017.01.001

2016

A protocol for the systematic and quantitative measurement of protein-lipid interactions using the liposome-microarray-based assay

Saliba A, Vonkova I, Deghou S, Ceschia S, Tischer C, Kugler K, Bork P, Ellenberg J, Gavin A (2016)

Nature Protocols, 11 (6): 1021-38DOI: 10.1038/nprot.2016.059

Single-cell RNA-seq ties macrophage polarization to growth rate of intracellular Salmonella

Saliba A, Li L, Westermann A, Appenzeller S, Stapels D, Schulte L, Helaine S, Vogel J (2016)

Nature Microbiology, 2: 16206DOI: 10.1038/nmicrobiol.2016.206

2015

Lipid Cooperativity as a General Membrane-Recruitment Principle for PH Domains

Vonkova I, Saliba A, Deghou S, Anand K, Ceschia S, Doerks T, Galih A, Kugler K, Maeda K, Rybin V, …, Bork P, Gavin A (2015)

Cell Reports, 12 (9): 1519-30DOI: 10.1016/j.celrep.2015.07.054

The systematic analysis of protein-lipid interactions comes of age

Saliba A, Vonkova I, Gavin A (2015)

Nature Reviews Molecular Cell biology, 16 (12): 753-61DOI: 10.1038/nrm4080

2014

A quantitative liposome microarray to systematically characterize protein-lipid interactions

Saliba A, Vonkova I, Ceschia S, Findlay G, Maeda K, Tischer C, Deghou S, van Noort V, Bork P, Pawson T, Ellenberg J, Gavin A (2014)

Nature Methods, 11 (1): 47-50DOI: 10.1038/nmeth.2734

Single-cell RNA-seq: advances and future challenges

Saliba A, Westermann A, Gorski S, Vogel J (2014)

Nucleic Acids Research, 42 (14): 8845-60DOI: 10.1093/nar/gku555

2010

Microfluidic sorting and multimodal typing of cancer cells in self-assembled magnetic arrays

Saliba A, Saias L, Psychari E, Minc N, Simon D, Bidard F, Mathiot C, Pierga J, Fraisier V, Salamero J, …, Malaquin L, Viovy J (2010)

Proceedings Of The National Academy Of Sciences Of The United States Of America, 107 (33): 14524-9DOI: 10.1073/pnas.1001515107

2009

Cellules tumorales circulantes et cancer du sein : méthodes de détection et résultats cliniques

Bidard F, Saliba A, Saias L, Degeorges A, Cremoux P, Viovy J, Vincent-Salomon A, Mathiot C, Pierga J, Gramont A (2009)

Bulletin du Cancer, 96 (1): 73-86DOI: 10.1684/bdc.2008.0797

2004

Nanotechnology serving biochips – The Toulouse example

Vieu C, Malaquin L, Thibault C, Saliba Antoine-Emmanuel, Daran E, Dildan M, Carcenac F, Leberre V, Trevisiol E, François JM (2004)

Biofutur (250): 41-45

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