scholarly journals Short-range interactions govern cellular dynamics in microbial multi-genotype systems

2019 ◽  
Author(s):  
A. Dal Co ◽  
S. van Vliet ◽  
D. J. Kiviet ◽  
S. Schlegel ◽  
M. Ackermann
Keyword(s):  
Microbial Communities ◽  
Single Cell ◽  
Spatial Organization ◽  
Single Cell Analysis ◽  
Spatial Interaction ◽  
Interaction Network ◽  
Spatial Arrangement ◽  
Emergent Properties ◽  
Interaction Range ◽  
Microbial Systems

AbstractEcosystem processes result from interaction between organisms. When interactions are local, the spatial organization of organisms defines their network of interactions, and thus influences the system’s functioning. This can be especially relevant for microbial systems, which often consist of spatially structured communities of cells connected by a dense interaction network. Here we measured the spatial interaction network between cells in microbial systems and identify the factors that determine it. Combining quantitative single-cell analysis of synthetic bacterial communities with mathematical modeling, we find that cells only interact with other cells in their immediate neighbourhood. This short interaction range impacts the functioning of the whole system by reducing its ability to perform metabolic processes collectively. Our experiments and models demonstrate that the spatial scale of cell-to-cell interaction plays a fundamental role in understanding and controlling natural communities, and in engineering microbial systems for specific purposes.Significance StatementCommunities of interacting microbes perform fundamental processes on earth. We do not understand well how these processes emerge from the interactions between individual microbial cells. Our work investigates how strongly individual cells interact and how the strength of the interaction depends on the distance between cells. The discovery that individual cells ‘live in a small world’, i.e. they only interact with a small number of cells around them, changes our understanding of how cells in natural microbial communities are metabolically coupled and how their spatial arrangement determines emergent properties at the community level. Our quantitative single-cell approach allows to address central questions on systems composed of interacting genotypes and to increase our understanding and ability to control microbial communities.

scholarly journals Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data

2020 ◽  
Vol 3 (11) ◽  
pp. e202000867 ◽  
Author(s):  
Jovan Tanevski ◽  
Thin Nguyen ◽  
Buu Truong ◽  
Nikos Karaiskos ◽  
Mehmet Eren Ahsen ◽  
...  
Keyword(s):  
Single Cell ◽  
Spatial Organization ◽  
Gene Selection ◽  
Spatial Information ◽  
Spatial Clustering ◽  
Spatial Location ◽  
Spatial Arrangement ◽  
Fish Embryo ◽  
Hybridization Data ◽  
Silver Standard

Single-cell RNA-sequencing (scRNAseq) technologies are rapidly evolving. Although very informative, in standard scRNAseq experiments, the spatial organization of the cells in the tissue of origin is lost. Conversely, spatial RNA-seq technologies designed to maintain cell localization have limited throughput and gene coverage. Mapping scRNAseq to genes with spatial information increases coverage while providing spatial location. However, methods to perform such mapping have not yet been benchmarked. To fill this gap, we organized the DREAM Single-Cell Transcriptomics challenge focused on the spatial reconstruction of cells from the Drosophila embryo from scRNAseq data, leveraging as silver standard, genes with in situ hybridization data from the Berkeley Drosophila Transcription Network Project reference atlas. The 34 participating teams used diverse algorithms for gene selection and location prediction, while being able to correctly localize clusters of cells. Selection of predictor genes was essential for this task. Predictor genes showed a relatively high expression entropy, high spatial clustering and included prominent developmental genes such as gap and pair-rule genes and tissue markers. Application of the top 10 methods to a zebra fish embryo dataset yielded similar performance and statistical properties of the selected genes than in the Drosophila data. This suggests that methods developed in this challenge are able to extract generalizable properties of genes that are useful to accurately reconstruct the spatial arrangement of cells in tissues.

scholarly journals Neutral mechanisms and niche differentiation in steady-state insular microbial communities revealed by single cell analysis

2018 ◽  
Vol 21 (1) ◽  
pp. 164-181 ◽  
Author(s):  
Zishu Liu ◽  
Nicolas Cichocki ◽  
Thomas Hübschmann ◽  
Christine Süring ◽  
Irina Dana Ofiţeru ◽  
...  
Keyword(s):  
Steady State ◽  
Microbial Communities ◽  
Single Cell ◽  
Single Cell Analysis ◽  
Niche Differentiation ◽  
Cell Analysis

scholarly journals Single-cell analysis of EphA clustering phenotypes to probe cancer cell heterogeneity

2019 ◽  
Author(s):  
Andrea Ravasio ◽  
Myint Zu Myaing ◽  
Shumei Chia ◽  
Aditya Arora ◽  
Aneesh Sathe ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Cancer Cell ◽  
Cancer Progression ◽  
Tyrosine Kinases ◽  
Spatial Organization ◽  
Single Cell Analysis ◽  
Cell Populations ◽  
Eph Receptors ◽  
Effective Manner

Abstract Eph receptors, a family of receptor tyrosine kinases, play a crutial role in the assembly and maintenance of healthy tissues. Dysfunction in Eph signaling are causally and correlatively associated with cancer progression. In breast cancer cells, dysregulated Eph signaling has been largely linked to alterations in receptor clustering abilities. In the present study, we implemented a single-cell assay and a scoring scheme to systematically probe the spatial organization of activated EphA receptor in carcinoma cells of different origin. Using this assay, we found that cancer cells retained EphA clustering phenotype upon cell division for several generations and degree of clustering reported for population as well as single-cell migration potential. Finally, using patient-derived cancer cell lines, we probed the evolution of EphA signalling in cancer cell populations that underwent metastatic transformation and acquisition of drug resistance. Taken together, our simple and scalable approach provides a reliable quantitation of EphA associated gene expression and phenotypes in multiple carcinomas and can assay the heterogeneity of cancer cell populations in a cost- and time-effective manner.

scholarly journals Single-cell analysis of EphA clustering phenotypes to probe cancer cell heterogeneity

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Andrea Ravasio ◽  
Myint Z. Myaing ◽  
Shumei Chia ◽  
Aditya Arora ◽  
Aneesh Sathe ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Cancer Cell ◽  
Cancer Progression ◽  
Tyrosine Kinases ◽  
Spatial Organization ◽  
Single Cell Analysis ◽  
Cell Populations ◽  
Effective Manner ◽  
Migration Potential

AbstractThe Eph family of receptor tyrosine kinases is crucial for assembly and maintenance of healthy tissues. Dysfunction in Eph signaling is causally associated with cancer progression. In breast cancer cells, dysregulated Eph signaling has been linked to alterations in receptor clustering abilities. Here, we implemented a single-cell assay and a scoring scheme to systematically probe the spatial organization of activated EphA receptors in multiple carcinoma cells. We show that cancer cells retain EphA clustering phenotype over several generations, and the degree of clustering reported for migration potential both at population and single-cell levels. Finally, using patient-derived cancer lines, we probed the evolution of EphA signalling in cell populations that underwent metastatic transformation and acquisition of drug resistance. Taken together, our scalable approach provides a reliable scoring scheme for EphA clustering that is consistent over multiple carcinomas and can assay heterogeneity of cancer cell populations in a cost- and time-effective manner.

scholarly journals Dissecting the chromatin interactome of microRNA genes

2013 ◽  
Vol 42 (5) ◽  
pp. 3028-3043 ◽  
Author(s):  
Dijun Chen ◽  
Liang-Yu Fu ◽  
Zhao Zhang ◽  
Guoliang Li ◽  
Hang Zhang ◽  
...  
Keyword(s):  
Rna Polymerase Ii ◽  
Spatial Organization ◽  
Spatial Interaction ◽  
Interaction Network ◽  
Cell Types ◽  
Disease Category ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Interacting Networks ◽  
Microrna Genes

Abstract Our knowledge of the role of higher-order chromatin structures in transcription of microRNA genes (MIRs) is evolving rapidly. Here we investigate the effect of 3D architecture of chromatin on the transcriptional regulation of MIRs. We demonstrate that MIRs have transcriptional features that are similar to protein-coding genes. RNA polymerase II–associated ChIA-PET data reveal that many groups of MIRs and protein-coding genes are organized into functionally compartmentalized chromatin communities and undergo coordinated expression when their genomic loci are spatially colocated. We observe that MIRs display widespread communication in those transcriptionally active communities. Moreover, miRNA–target interactions are significantly enriched among communities with functional homogeneity while depleted from the same community from which they originated, suggesting MIRs coordinating function-related pathways at posttranscriptional level. Further investigation demonstrates the existence of spatial MIR–MIR chromatin interacting networks. We show that groups of spatially coordinated MIRs are frequently from the same family and involved in the same disease category. The spatial interaction network possesses both common and cell-specific subnetwork modules that result from the spatial organization of chromatin within different cell types. Together, our study unveils an entirely unexplored layer of MIR regulation throughout the human genome that links the spatial coordination of MIRs to their co-expression and function.

Computational Micrograph Registration with Sieve Processes

1996 ◽  
Vol 54 ◽  
pp. 440-441
Author(s):  
P.J. Phillips ◽  
J. Huang ◽  
S. M. Dunn
Keyword(s):  
Planar Graph ◽  
Efficient Algorithm ◽  
Spatial Organization ◽  
Spatial Arrangement ◽  
Stereo Image ◽  
Image Model ◽  
Geometric Invariants ◽  
Point Set

In this paper we present an efficient algorithm for automatically finding the correspondence between pairs of stereo micrographs, the key step in forming a stereo image. The computation burden in this problem is solving for the optimal mapping and transformation between the two micrographs. In this paper, we present a sieve algorithm for efficiently estimating the transformation and correspondence.In a sieve algorithm, a sequence of stages gradually reduce the number of transformations and correspondences that need to be examined, i.e., the analogy of sieving through the set of mappings with gradually finer meshes until the answer is found. The set of sieves is derived from an image model, here a planar graph that encodes the spatial organization of the features. In the sieve algorithm, the graph represents the spatial arrangement of objects in the image. The algorithm for finding the correspondence restricts its attention to the graph, with the correspondence being found by a combination of graph matchings, point set matching and geometric invariants.

Author response for "Immunocyte single cell analysis of vaccine‐induced narcolepsy"

2020 ◽  
Author(s):  
Alexander Lind ◽  
Falastin Salami ◽  
Anne‐Marie Landtblom ◽  
Lars Palm ◽  
Åke Lernmark ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Author Response ◽  
Cell Analysis

ЛАНДШАФТНАЯ ОРГАНИЗАЦИЯ БЕРЕГОВОЙ ГЕОСТРУКТУРЫ ОСТРОВА ШКОТА (ЗАЛИВ ПЕТРА ВЕЛИКОГО)

2019 ◽  
Author(s):  
K.S. Ganzei ◽  
V.V. Zharikov ◽  
N.F. Pshenichnikova ◽  
A.M. Lebedev ◽  
A.G. Kiselyova ◽  
...  
Keyword(s):  
Spatial Organization ◽  
Peter The Great Bay ◽  
Spatial Arrangement ◽  
Water Area ◽  
Marine Spatial Planning ◽  
Landscape Approach ◽  
Important Condition ◽  
Statistical Comparison ◽  
Peter The Great ◽  
Comprehensive Study

Важнейшим условием достижения устойчивого развития прибрежноморского природопользования в заливе Петра Великого системы является морское пространственное планирование. Основой для этого является информация о природных комплексах территории и акватории, полученная на основе ландшафтного подхода. Ключевым районом для изучения пространственной организации ландшафтов прибрежных геоструктур стала территория острова Шкота и его подводных склонов. Для наземных ландшафтов было описано 49 наблюдательных пунктов, 4 профиля были заложены для подводных ландшафтов описано 64 наблюдательных пункта, проложено 18 профилей. Выделено 22 вида ландшафтов, из них 16 наземных, 6 подводных. Берега острова сформированы преобладанием абразивноденудационного и абразивного типов. В результате всестороннего изучения показаны особенности пространственной организации воздушных и водных природных комплексов. Особенностью исследуемой территории является экспозиция дифференциации ландшафтов между юговосточной и северозападной частями острова, обусловленная муссонной природой климата. Результаты полевых и картографических работ послужили основой для выбора зон интенсивного, умеренного и ослабленного взаимодействия наземных и подводных ландшафтов. Пространственное расположение зон взаимодействия четко иллюстрируется значительными различиями экспозиции. Результаты статистического сравнения ландшафтов суши и мелководья, окружающего остров, на основе картометрических характеристик указывают на неоднородность геоструктуры острова, обусловленную, прежде всего, сочетанием ландшафтообразующих факторов. The most important condition for achieving sustainable development of coastalmarine environmental management in Peter the Great Bay is marine spatial planning. The basis for this is information about the natural complexes of the territory and water area, obtained based on the landscape approach. The main area for studying the spatial organization of landscapes of coastal geostructures was the territory of the island of Shkota and its underwater slopes. For terrestrial landscapes, 49 observation points were described, 4 profiles were laid 64 observation points were described for underwater landscapes, 18 profiles were laid. 22 species of landscapes have been identified, of which 16 are terrestrial, 6 are underwater. The shores of the island are formed by the predominance of abrasivedenudation and abrasive types. Because of a comprehensive study, features of the spatial organization of air and aquatic natural complexes are shown. A special feature of the study area is the exposure of the differentiation of landscapes between the southeastern and northwestern parts of the island, due to the monsoon nature of the climate. The results of field and cartographic works served as the basis for selecting areas of intense, moderate and weakened interaction of land and underwater landscapes. The spatial arrangement of the interaction zones is clearly illustrated by significant differences in exposure. The results of a statistical comparison of the land and shallow water landscapes surrounding the island, based on the cartometric characteristics, indicate the heterogeneity of the islands geostructure, primarily due to the combination of landscapeforming factors.

Sign in / Sign up

Export Citation Format

Share Document