scholarly journals Microfluidic device performing on flow study of serial cell–cell interactions of two cell populations

RSC Advances ◽  
2019 ◽  
Vol 9 (70) ◽  
pp. 41066-41073 ◽  
Author(s):  
Margaux Duchamp ◽  
Thamani Dahoun ◽  
Clarisse Vaillier ◽  
Marion Arnaud ◽  
Sara Bobisse ◽  
...  

In this study we present a novel microfluidic hydrodynamic trapping device to probe the cell–cell interaction between all cell samples of two distinct populations.

2018 ◽  
Vol 115 (48) ◽  
pp. 12112-12117 ◽  
Author(s):  
Rebekka E. Breier ◽  
Cristian C. Lalescu ◽  
Devin Waas ◽  
Michael Wilczek ◽  
Marco G. Mazza

Phytoplankton often encounter turbulence in their habitat. As most toxic phytoplankton species are motile, resolving the interplay of motility and turbulence has fundamental repercussions on our understanding of their own ecology and of the entire ecosystems they inhabit. The spatial distribution of motile phytoplankton cells exhibits patchiness at distances of decimeter to millimeter scales for numerous species with different motility strategies. The explanation of this general phenomenon remains challenging. Furthermore, hydrodynamic cell–cell interactions, which grow more relevant as the density in the patches increases, have been so far ignored. Here, we combine particle simulations and continuum theory to study the emergence of patchiness in motile microorganisms in three dimensions. By addressing the combined effects of motility, cell–cell interaction, and turbulent flow conditions, we uncover a general mechanism: The coupling of cell–cell interactions to the turbulent dynamics favors the formation of dense patches. Identification of the important length and time scales, independent from the motility mode, allows us to elucidate a general physical mechanism underpinning the emergence of patchiness. Our results shed light on the dynamical characteristics necessary for the formation of patchiness and complement current efforts to unravel planktonic ecological interactions.


2021 ◽  
Author(s):  
Mattias Malaguti ◽  
Rosa Portero Migueles ◽  
Jennifer Annoh ◽  
Daina Sadurska ◽  
Guillaume Blin ◽  
...  

ABSTRACTCell-cell interactions govern differentiation and cell competition in pluripotent cells during early development, but the investigation of such processes is hindered by a lack of efficient analysis tools. Here we introduce SyNPL: clonal pluripotent stem cell lines which employ optimised Synthetic Notch (SynNotch) technology to report cell-cell interactions between engineered “sender” and “receiver” cells in cultured pluripotent cells and chimaeric mouse embryos. A modular design makes it straightforward to adapt the system for programming differentiation decisions non-cell-autonomously in receiver cells in response to direct contact with sender cells. We demonstrate the utility of this system by enforcing neuronal differentiation at the boundary between two cell populations. In summary, we provide a new tool which could be used to identify cell interactions and to profile changes in gene or protein expression that result from direct cell-cell contact with defined cell populations in culture and in early embryos, and which can be adapted to generate synthetic patterning of cell fate decisions.


2021 ◽  
Author(s):  
Brendan T Innes ◽  
Gary D Bader

Cell-cell interactions are often predicted from single-cell transcriptomics data based on observing receptor and corresponding ligand transcripts in cells. These predictions could theoretically be improved by inspecting the transcriptome of the receptor cell for evidence of gene expression changes in response to the ligand. It is commonly expected that a given receptor, in response to ligand activation, will have a characteristic downstream gene expression signature. However, this assumption has not been well tested. We used ligand perturbation data from both the high-throughput Connectivity Map resource and published transcriptomic assays of cell lines and purified cell populations to determine whether ligand signals have unique and generalizable transcriptional signatures across biological conditions. Most of the receptors we analyzed did not have such characteristic gene expression signatures - instead these signatures were highly dependent on cell type. Cell context is thus important when considering transcriptomic evidence of ligand signaling, which makes it challenging to build generalizable ligand-receptor interaction signatures to improve cell-cell interaction predictions.


Development ◽  
2001 ◽  
Vol 128 (7) ◽  
pp. 1211-1219 ◽  
Author(s):  
A. Arai ◽  
A. Nakamoto ◽  
T. Shimizu

In embryos of clitellate annelids (i.e. oligochaetes and leeches), four ectodermal teloblasts (ectoteloblasts N, O, P and Q) are generated on either side through a stereotyped sequence of cell divisions of a proteloblast, NOPQ. The four ectoteloblasts assume distinct fates and produce bandlets of smaller progeny cells, which join together to form an ectodermal germ band. The pattern of the germ band, with respect to the ventrodorsal order of the bandlets, has been highly preserved in clitellate annelids. We show that specification of ectoteloblast lineages in the oligochaete annelid Tubifex involves cell interaction networks distinct from those in leeches. Cell ablation experiments have shown that fates of teloblasts N, P and Q in Tubifex embryos are determined rigidly as early as their birth. In contrast, the O teloblast and its progeny are initially pluripotent and their fate becomes restricted to the O fate through an inductive signal emanating from the P lineage. In the absence of this signal, the O lineage assumes the P fate. These results differ significantly from those obtained in embryos of the leech Helobdella, suggesting the diversity of patterning mechanisms that give rise to germ bands with similar morphological pattern.


2021 ◽  
Author(s):  
Nathanael Andrews ◽  
Jason T. Serviss ◽  
Natalie Geyer (Karolinska Institute Stockholm) ◽  
Agneta B. Andersson ◽  
Ewa Dzwonkowska ◽  
...  

Single cell sequencing methods facilitate the study of tissues at high resolution, revealing rare cell types with varying transcriptomes or genomes, but so far have been lacking the capacity to investigate cell-cell interactions. Here, we introduce CIM-seq, an unsupervised and high-throughput method to analyze direct physical cell-cell interactions between every cell type in a given tissue. CIM-seq is based on RNA sequencing of incompletely dissociated cells, followed by computational deconvolution of these into their constituent cell types using machine learning. CIM-seq is broadly applicable to studies that aim to simultaneously investigate the constituent cell types and the global interaction profile in a specific tissue.


2014 ◽  
Vol 8 (4) ◽  
pp. 044105 ◽  
Author(s):  
K. Hockemeyer ◽  
C. Janetopoulos ◽  
A. Terekhov ◽  
W. Hofmeister ◽  
A. Vilgelm ◽  
...  

2021 ◽  
Author(s):  
Ming Lei ◽  
Vikas Trivedi ◽  
Nikhil Unni Nair ◽  
Kyongbum Lee ◽  
James A. Van Deventer

Synthetic cell-cell interaction systems can be useful for understanding multicellular communities or for screening binding molecules. We adapt a previously characterized set of synthetic cognate nanobody-antigen pairs to a yeast-bacteria coincubation format and use flow cytometry to evaluate cell-cell interactions mediated by binding between surface-displayed molecules. We further use fluorescence-activated cell sorting (FACS) to enrich for a specific yeast-displayed nanobody within a mixed yeast-display population. Finally, we demonstrate that this system supports characterization of a therapeutically relevant nanobody-antigen interaction: a previously discovered nanobody that binds to the intimin protein expressed on the surface of enterohemorrhagic E. coli. Overall, our findings indicate that the yeast-bacteria format supports efficient evaluation of ligand-target interactions. With further development, this format may facilitate systematic characterization and high throughput discovery of bacterial surface-binding molecules.


2020 ◽  
Author(s):  
Nathanael Andrews ◽  
Jason T. Serviss ◽  
Natalie Geyer (Karolinska Institute Stockholm) ◽  
Agneta B. Andersson ◽  
Ewa Dzwonkowska ◽  
...  

Single cell sequencing methods facilitate the study of tissues at high resolution, revealing rare cell types with varying transcriptomes or genomes, but so far have been lacking the capacity to investigate cell-cell interactions. Here, we introduce CIM-seq, an unsupervised and high-throughput method to analyze direct physical cell-cell interactions between every cell type in a given tissue. CIM-seq is based on RNA sequencing of incompletely dissociated cells, followed by computational deconvolution of these into their constituent cell types using machine learning. CIM-seq is broadly applicable to studies that aim to simultaneously investigate the constituent cell types and the global interaction profile in a specific tissue.


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