scholarly journals Emergence of phytoplankton patchiness at small scales in mild turbulence

2018 ◽  
Vol 115 (48) ◽  
pp. 12112-12117 ◽  
Author(s):  
Rebekka E. Breier ◽  
Cristian C. Lalescu ◽  
Devin Waas ◽  
Michael Wilczek ◽  
Marco G. Mazza
Keyword(s):  
Continuum Theory ◽  
Cell Interaction ◽  
Cell Interactions ◽  
Three Dimensions ◽  
General Mechanism ◽  
Ecological Interactions ◽  
Dynamical Characteristics ◽  
Particle Simulations ◽  
General Physical ◽  
Cell Cell

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.

scholarly journals Physical confinement signals regulate the organization of stem cells in three dimensions

2016 ◽  
Vol 13 (123) ◽  
pp. 20160613 ◽  
Author(s):  
Sebastian V. Hadjiantoniou ◽  
David Sean ◽  
Maxime Ignacio ◽  
Michel Godin ◽  
Gary W. Slater ◽  
...  
Keyword(s):  
Stem Cells ◽  
Inner Cell Mass ◽  
Cell Mass ◽  
Three Dimensional ◽  
Embryonic Stem ◽  
Cell Interactions ◽  
Three Dimensions ◽  
Cell Substrate ◽  
Cell Cell

During embryogenesis, the spherical inner cell mass (ICM) proliferates in the confined environment of a blastocyst. Embryonic stem cells (ESCs) are derived from the ICM, and mimicking embryogenesis in vitro , mouse ESCs (mESCs) are often cultured in hanging droplets. This promotes the formation of a spheroid as the cells sediment and aggregate owing to increased physical confinement and cell–cell interactions. In contrast, mESCs form two-dimensional monolayers on flat substrates and it remains unclear if the difference in organization is owing to a lack of physical confinement or increased cell–substrate versus cell–cell interactions. Employing microfabricated substrates, we demonstrate that a single geometric degree of physical confinement on a surface can also initiate spherogenesis. Experiment and computation reveal that a balance between cell–cell and cell–substrate interactions finely controls the morphology and organization of mESC aggregates. Physical confinement is thus an important regulatory cue in the three-dimensional organization and morphogenesis of developing cells.

scholarly journals Transcriptional signatures of cell-cell interactions are dependent on cellular context

2021 ◽  
Author(s):  
Brendan T Innes ◽  
Gary D Bader
Keyword(s):  
Gene Expression ◽  
Gene Expression Signature ◽  
Cell Interaction ◽  
Cell Interactions ◽  
Receptor Interaction ◽  
Perturbation Data ◽  
Cellular Context ◽  
Transcriptomics Data ◽  
Downstream Gene Expression ◽  
Cell Cell

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.

Specification of ectodermal teloblast lineages in embryos of the oligochaete annelid Tubifex: involvement of novel cell-cell interactions

Development ◽  
2001 ◽  
Vol 128 (7) ◽  
pp. 1211-1219 ◽  
Author(s):  
A. Arai ◽  
A. Nakamoto ◽  
T. Shimizu
Keyword(s):  
Cell Interaction ◽  
Cell Interactions ◽  
Interaction Networks ◽  
Germ Band ◽  
Morphological Pattern ◽  
Cell Divisions ◽  
Cell Ablation ◽  
Oligochaete Annelid ◽  
Inductive Signal ◽  
Cell Cell

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.

Cell Interaction by Multiplet sequencing (CIM-seq) v2

2021 ◽  
Author(s):  
Nathanael Andrews ◽  
Jason T. Serviss ◽  
Natalie Geyer (Karolinska Institute Stockholm) ◽  
Agneta B. Andersson ◽  
Ewa Dzwonkowska ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cell Types ◽  
Cell Interaction ◽  
Cell Interactions ◽  
Cell Type ◽  
Single Cell Sequencing ◽  
High Throughput Method ◽  
Dissociated Cells ◽  
Specific Tissue ◽  
Cell Cell

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.

scholarly journals Flow Cytometric Evaluation of Yeast-Bacterial Cell-Cell Interactions

2021 ◽  
Author(s):  
Ming Lei ◽  
Vikas Trivedi ◽  
Nikhil Unni Nair ◽  
Kyongbum Lee ◽  
James A. Van Deventer
Keyword(s):  
Cell Interaction ◽  
Cell Interactions ◽  
Surface Binding ◽  
Bacterial Surface ◽  
E Coli ◽  
Flow Cytometric ◽  
Synthetic Cell ◽  
Antigen Interaction ◽  
Cell Cell

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.

Cell Interaction by Multiplet sequencing (CIM-seq) v1

2020 ◽  
Author(s):  
Nathanael Andrews ◽  
Jason T. Serviss ◽  
Natalie Geyer (Karolinska Institute Stockholm) ◽  
Agneta B. Andersson ◽  
Ewa Dzwonkowska ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cell Types ◽  
Cell Interaction ◽  
Cell Interactions ◽  
Cell Type ◽  
Single Cell Sequencing ◽  
High Throughput Method ◽  
Dissociated Cells ◽  
Specific Tissue ◽  
Cell Cell

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.

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 ◽  
...  
Keyword(s):  
Microfluidic Device ◽  
Cell Interaction ◽  
Cell Interactions ◽  
Cell Populations ◽  
Trapping Device ◽  
Flow Study ◽  
Cell Cell ◽  
Hydrodynamic Trapping

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.

scholarly journals Cdo Interacts with APPL1 and Activates AKT in Myoblast Differentiation

2010 ◽  
Vol 21 (14) ◽  
pp. 2399-2411 ◽  
Author(s):  
Gyu-Un Bae ◽  
Jae-Rin Lee ◽  
Bok-Geon Kim ◽  
Ji-Won Han ◽  
Young-Eun Leem ◽  
...  
Keyword(s):  
Myogenic Differentiation ◽  
Active Form ◽  
Surface Protein ◽  
Cell Interaction ◽  
Cell Interactions ◽  
Scaffold Proteins ◽  
Myoblast Differentiation ◽  
Akt Activation ◽  
Underlying Mechanisms ◽  
Cell Cell

Cell–cell interactions between muscle precursors are required for myogenic differentiation; however, underlying mechanisms are largely unknown. Promyogenic cell surface protein Cdo functions as a component of multiprotein complexes containing other cell adhesion molecules, Boc, Neogenin and N-cadherin, and mediates some of signals triggered by cell–cell interactions between muscle precursors. Cdo activates p38MAPK via interaction with two scaffold proteins JLP and Bnip-2 to promote myogenesis. p38MAPK and Akt signaling are required for myogenic differentiation and activation of both signaling pathways is crucial for efficient myogenic differentiation. We report here that APPL1, an interacting partner of Akt, forms complexes with Cdo and Boc in differentiating myoblasts. Both Cdo and APPL1 are required for efficient Akt activation during myoblast differentiation. The defective differentiation of Cdo-depleted cells is fully rescued by overexpression of a constitutively active form of Akt, whereas overexpression of APPL1 fails to do so. Taken together, Cdo activates Akt through association with APPL1 during myoblast differentiation, and this complex likely mediates some of the promyogenic effect of cell–cell interaction. The promyogenic function of Cdo involves a coordinated activation of p38MAPK and Akt via association with scaffold proteins, JLP and Bnip-2 for p38MAPK and APPL1 for Akt.

scholarly journals Effective mechanical potential of cell–cell interaction explains basic structures of three-dimensional morphogenesis

2019 ◽  
Author(s):  
Hiroshi Koyama ◽  
Hisashi Okumura ◽  
Atsushi M. Ito ◽  
Tetsuhisa Otani ◽  
Kazuyuki Nakamura ◽  
...  
Keyword(s):  
Mdck Cells ◽  
Three Dimensional ◽  
Cell Interaction ◽  
Fundamental Principle ◽  
Cell Interactions ◽  
Coarse Grained ◽  
Spherical Particles ◽  
Imaging Data ◽  
Effective Potentials ◽  
Cell Cell

AbstractMechanical properties of cell–cell interactions have been suggested to be critical for the emergence of diverse three-dimensional morphologies of multicellular organisms. Mechanical potential energy of cell–cell interactions has been theoretically assumed, however, whether such potential can be detectable in living systems remains poorly understood. In this study, we developed a novel framework for inferring mechanical forces of cell–cell interactions. First, by analogy to coarse-grained models in molecular and colloidal sciences, cells were approximately assumed to be spherical particles, where microscopic features of cells such as polarities and shapes were not explicitly incorporated and the mean forces (i.e. effective forces) of cell–cell interactions were considered. Then, the forces were statistically inferred from live imaging data, and subsequently, we successfully detected potentials of cell–cell interactions. Finally, computational simulations based on these potentials were performed to test whether these potentials can reproduce the original morphologies. Our results from various systems, including Madin-Darby canine kidney (MDCK) cells, C.elegans early embryos, and mouse blastocysts, suggest that the method can accurately infer the effective potentials and capture the diverse three-dimensional morphologies. Importantly, energy barriers were predicted to exist at the distant regions of the interactions, and this mechanical property of cell–cell interactions was essential for formation of cavities, tubes, cups, and two-dimensional sheets. Collectively, these structures constitute basic structures observed during morphogenesis and organogenesis. We propose that effective potentials of cell– cell interactions are parameters that can be measured from living organisms, and represent a fundamental principle underlying the emergence of diverse three-dimensional morphogenesis.

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