Antoine-Emmanuel Saliba

Single-cell RNA-seq: advances and future challenges

Phenotypically identical cells can dramatically vary with respect to behavior during their lifespan and this variation is reflected in their molecular composition such as the transcriptomic landscape. Single-cell transcriptomics using next-generation transcript sequencing (RNA-seq) is now emerging as a powerful tool to profile cell-to-cell variability on a genomic scale. Its application has already greatly impacted our conceptual understanding of diverse biological processes with broad implications for both basic and clinical research. Different single-cell RNA-seq protocols have been introduced and are reviewed here—each one with its own strengths and current limitations. We further provide an overview of the biological questions single-cell RNA-seq has been used to address, the major findings obtained from such studies, and current challenges and expected future developments in this booming field.

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

We propose a unique method for cell sorting, “Ephesia,” using columns of biofunctionalized superparamagnetic beads self-assembled in a microfluidic channel onto an array of magnetic traps prepared by microcontact printing. It combines the advantages of microfluidic cell sorting, notably the application of a well controlled, flow-activated interaction between cells and beads, and those of immunomagnetic sorting, notably the use of batch-prepared, well characterized antibody-bearing beads. On cell lines mixtures, we demonstrated a capture yield better than 94%, and the possibility to cultivate in situ the captured cells. A second series of experiments involved clinical samples—blood, pleural effusion, and fine needle aspirates— issued from healthy donors and patients with B-cell hematological malignant tumors (leukemia and lymphoma). The immunophenotype and morphology of B-lymphocytes were analyzed directly in the microfluidic chamber, and compared with conventional flow cytometry and visual cytology data, in a blind test. Immunophenotyping results using Ephesia were fully consistent with those obtained by flow cytometry. We obtained in situ high resolution confocal three-dimensional images of the cell nuclei, showing intranuclear details consistent with conventional cytological staining. Ephesia thus provides a powerful approach to cell capture and typing allowing fully automated high resolution and quantitative immunophenotyping and morphological analysis. It requires at least 10 times smaller sample volume and cell numbers than cytometry, potentially increasing the range of indications and the success rate of microbiopsy-based diagnosis, and reducing analysis time and cost.

The systematic analysis of protein–lipid interactions comes of age

Lipids tailor membrane identities and function as molecular hubs in all cellular processes. However, the ways in which lipids modulate protein function and structure are poorly understood and still require systematic investigation. In this Innovation article, we summarize pioneering technologies, including lipid-overlay assays, lipid pull-down assays, affinity-purification lipidomics and the liposome microarray-based assay (LiMA), that will enable protein–lipid interactions to be deciphered on a systems level. We discuss how these technologies can be applied to the charting of system-wide networks and to the development of new pharmaceutical strategies.

A quantitative liposome microarray to systematically characterize protein-lipid interactions

Lipids have a role in virtually all biological processes, acting as structural elements, scaffolds and signaling molecules, but they are still largely under-represented in known biological networks. Here we describe a liposome microarray–based assay (LiMA), a method that measures protein recruitment to membranes in a quantitative, automated, multiplexed and high-throughput manner.

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

Intracellular bacterial pathogens can exhibit large heterogeneity in growth rate inside host cells, with major consequences for the infection outcome. If and how the host responds to this heterogeneity remains poorly understood. Here, we combined a fluorescent reporter of bacterial cell division with single-cell RNA-sequencing analysis to study the macrophage response to different intracellular states of the model pathogen Salmonella enterica serovar Typhimurium. The transcriptomes of individual infected macrophages revealed a spectrum of functional host response states to growing and non-growing bacteria. Intriguingly, macrophages harbouring non-growing Salmonella display hallmarks of the proinflammatory M1 polarization state and differ little from bystander cells, suggesting that non-growing bacteria evade recognition by intracellular immune receptors. By contrast, macrophages containing growing bacteria have turned into an anti-inflammatory, M2-like state, as if fast-growing intracellular Salmonella overcome host defence by reprogramming macrophage polarization. Additionally, our clustering approach reveals intermediate host functional states between these extremes. Altogether, our data suggest that gene expression variability in infected host cells shapes different cellular environments, some of which may favour a growth arrest of Salmonella facilitating immune evasion and the establishment of a long-term niche, while others allow Salmonella to escape intracellular antimicrobial activity and proliferate.

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

Many cellular processes involve the recruitment of proteins to specific membranes, which are decorated with distinctive lipids that act as docking sites. The phosphoinositides form signaling hubs, and we examine mechanisms underlying recruitment. We applied a physiological, quantitative, liposome microarray-based assay to measure the membrane-binding properties of 91 pleckstrin homology (PH) domains, the most common phosphoinositide-binding target. 10,514 experiments quantified the role of phosphoinositides in membrane recruitment. For most domains examined, the observed binding specificity implied cooperativity with additional signaling lipids. Analyses of PH domains with similar lipid-binding profiles identified a conserved motif, mutations in which-including some found in human cancers-induced discrete changes in binding affinities in vitro and protein mislocalization in vivo. The data set reveals cooperativity as a key mechanism for membrane recruitment and, by enabling the interpretation of disease-associated mutations, suggests avenues for the design of small molecules targeting PH domains.

New RNA-seq approaches for the study of bacterial pathogens

Understanding how bacteria cause disease requires knowledge of which genes are expressed and how they are regulated during infection. While RNA-seq is now a routine method for gene expression analysis in bacterial pathogens, the past years have also witnessed a surge of novel RNA-seq based approaches going beyond standard mRNA profiling. These include variations of the technique to capture post-transcriptional networks controlled by small RNAs and to discover associated RNA-binding proteins in the pathogen itself. Dual RNA-seq analyzing pathogen and host simultaneously has revealed roles of noncoding RNAs during infection and enabled the correlation of bacterial gene activity with specific host responses. Single-cell RNA-seq studies have addressed how heterogeneity among individual host cells may determine infection outcomes.

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

Rationale: It is assumed that atherosclerotic arteries contain several macrophage subsets endowed with specific functions. The precise identity of these subsets is poorly characterized as they have been defined by the expression of a restricted number of markers. Objective: We have applied single-cell RNA sequencing as an unbiased profiling strategy to interrogate and classify aortic macrophage heterogeneity at the single-cell level in atherosclerosis. Method and Results: We performed single-cell RNA sequencing of total aortic CD45+ cells extracted from the nondiseased (chow fed) and atherosclerotic (11 weeks of high-fat diet) aorta of low-density lipoprotein receptor–deficient (Ldlr−/−) mice. Unsupervised clustering singled out 13 distinct aortic cell clusters. Among the myeloid cell populations, resident-like macrophages with a gene expression profile similar to aortic resident macrophages were found in healthy and diseased aortas, whereas monocytes, monocyte-derived dendritic cells, and 2 populations of macrophages were almost exclusively detectable in atherosclerotic aortas, comprising inflammatory macrophages showing enrichment in Il1b and previously undescribed TREM2hi (triggered receptor expressed on myeloid cells 2) macrophages showing enrichment in Trem2. Differential gene expression and gene ontology enrichment analyses revealed specific gene expression patterns distinguishing these 3 macrophage subsets and monocyte-derived dendritic cells and uncovered putative functions of each cell type. Notably, TREM2hi macrophages seemed to be endowed with specialized functions in lipid metabolism and catabolism and presented a gene expression signature reminiscent of osteoclasts, suggesting a role in lesion calcification. TREM2 expression was moreover detected in human lesional macrophages. Importantly, these macrophage populations were present also in advanced atherosclerosis and in Apoe−/− aortas, indicating relevance of our findings in different stages of atherosclerosis and mouse models. Conclusions: These data unprecedentedly uncovered the transcriptional landscape and phenotypic heterogeneity of aortic macrophages and monocyte-derived dendritic cells in atherosclerotic and identified previously unrecognized macrophage populations and their gene expression signature, suggesting specialized functions. Our findings will open up novel opportunities to explore distinct myeloid cell populations and their functions in atherosclerosis.

[Circulating tumor cells and breast cancer: detection techniques and clinical results]

Due to recent technological progresses, Circulating Tumor Cells (CTC) are currently extensively studied in order to define their diagnostic, prognostic and predictive value. We review here the different detection techniques and their clinical results in breast cancer patients.

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

Rationale: Atherosclerosis is a chronic inflammatory disease that is driven by the interplay of pro- and anti-inflammatory leukocytes in the aorta. Yet, the phenotypic and transcriptional diversity of aortic leukocytes is poorly understood. Objective: We characterized leukocytes from healthy and atherosclerotic mouse aortas in-depth by single-cell RNA-sequencing and mass cytometry (cytometry by time of flight) to define an atlas of the immune cell landscape in atherosclerosis. Methods and Results: Using single-cell RNA-sequencing of aortic leukocytes from chow diet– and Western diet–fed Apoe−/− and Ldlr−/− mice, we detected 11 principal leukocyte clusters with distinct phenotypic and spatial characteristics while the cellular repertoire in healthy aortas was less diverse. Gene set enrichment analysis on the single-cell level established that multiple pathways, such as for lipid metabolism, proliferation, and cytokine secretion, were confined to particular leukocyte clusters. Leukocyte populations were differentially regulated in atherosclerotic Apoe−/− and Ldlr−/− mice. We confirmed the phenotypic diversity of these clusters with a novel mass cytometry 35-marker panel with metal-labeled antibodies and conventional flow cytometry. Cell populations retrieved by these protein-based approaches were highly correlated to transcriptionally defined clusters. In an integrated screening strategy of single-cell RNA-sequencing, mass cytometry, and fluorescence-activated cell sorting, we detected 3 principal B-cell subsets with alterations in surface markers, functional pathways, and in vitro cytokine secretion. Leukocyte cluster gene signatures revealed leukocyte frequencies in 126 human plaques by a genetic deconvolution strategy. This approach revealed that human carotid plaques and microdissected mouse plaques were mostly populated by macrophages, T-cells, and monocytes. In addition, the frequency of genetically defined leukocyte populations in carotid plaques predicted cardiovascular events in patients. Conclusions: The definition of leukocyte diversity by high-dimensional analyses enables a fine-grained analysis of aortic leukocyte subsets, reveals new immunologic mechanisms and cell-type–specific pathways, and establishes a functional relevance for lesional leukocytes in human atherosclerosis.