Classical cadherins control nucleus and centrosome position and cell polarity

Control of cell polarity is crucial during tissue morphogenesis and renewal, and depends on spatial cues provided by the extracellular environment. Using micropatterned substrates to impose reproducible cell–cell interactions, we show that in the absence of other polarizing cues, cell–cell contacts are the main regulator of nucleus and centrosome positioning, and intracellular polarized organization. In a variety of cell types, including astrocytes, epithelial cells, and endothelial cells, calcium-dependent cadherin-mediated cell–cell interactions induce nucleus and centrosome off-centering toward cell–cell contacts, and promote orientation of the nucleus–centrosome axis toward free cell edges. Nucleus and centrosome off-centering is controlled by N-cadherin through the regulation of cell interactions with the extracellular matrix, whereas the orientation of the nucleus–centrosome axis is determined by the geometry of N-cadherin–mediated contacts. Our results demonstrate that in addition to the specific function of E-cadherin in regulating baso-apical epithelial polarity, classical cadherins control cell polarization in otherwise nonpolarized cells.     

Direct measurement of protein–protein interactions by FLIM-FRET at UV laser-induced DNA damage sites in living cells

Protein–protein interactions are essential to ensure timely and precise recruitment of chromatin remodellers and repair factors to DNA damage sites. Conventional analyses of protein–protein interactions at a population level may mask the complexity of interaction dynamics, highlighting the need for a method that enables quantification of DNA damage-dependent interactions at a single-cell level. To this end, we integrated a pulsed UV laser on a confocal fluorescence lifetime imaging (FLIM) microscope to induce localized DNA damage. To quantify protein–protein interactions in live cells, we measured Förster resonance energy transfer (FRET) between mEGFP- and mCherry-tagged proteins, based on the fluorescence lifetime reduction of the mEGFP donor protein. The UV-FLIM-FRET system offers a unique combination of real-time and single-cell quantification of DNA damage-dependent interactions, and can distinguish between direct protein–protein interactions, as opposed to those mediated by chromatin proximity. Using the UV-FLIM-FRET system, we show the dynamic changes in the interaction between poly(ADP-ribose) polymerase 1, amplified in liver cancer 1, X-ray repair cross-complementing protein 1 and tripartite motif containing 33 after DNA damage. This new set-up complements the toolset for studying DNA damage response by providing single-cell quantitative and dynamic information about protein–protein interactions at DNA damage sites.     

Integrin–ECM interactions and membrane-associated Catalase cooperate to promote resilience of the Drosophila intestinal epithelium

Balancing cellular demise and survival constitutes a key feature of resilience mechanisms that underlie the control of epithelial tissue damage. These resilience mechanisms often limit the burden of adaptive cellular stress responses to internal or external threats. We recently identified Diedel, a secreted protein/cytokine, as a potent antagonist of apoptosis-induced regulated cell death in the Drosophila intestinal midgut epithelium during aging. Here, we show that Diedel is a ligand for RGD-binding Integrins and is thus required for maintaining midgut epithelial cell attachment to the extracellular matrix (ECM)-derived basement membrane. Exploiting this function of Diedel, we uncovered a resilience mechanism of epithelial tissues, mediated by Integrin–ECM interactions, which shapes cell death spreading through the regulation of cell detachment and thus cell survival. Moreover, we found that resilient epithelial cells, enriched for Diedel–Integrin–ECM interactions, are characterized by membrane association of Catalase, thus preserving extracellular reactive oxygen species (ROS) balance to maintain epithelial integrity. Intracellular Catalase can relocalize to the extracellular membrane to limit cell death spreading and repair Integrin–ECM interactions induced by the amplification of extracellular ROS, which is a critical adaptive stress response. Membrane-associated Catalase, synergized with Integrin–ECM interactions, likely constitutes a resilience mechanism that helps balance cellular demise and survival within epithelial tissues.

A key feature of the resilience mechanisms that underlie the control of epithelial tissue damage is the balance between cell death and survival. This study shows that the anti-oxidant enzyme catalase can relocate to membranes in order to promote the resilience of the Drosophila midgut epithelium, synergizing with integrin-ECM interactions to prevent the spread of cell death.     

Single-cell genomics-based analysis of virus–host interactions in marine surface bacterioplankton

Viral infections dynamically alter the composition and metabolic potential of marine microbial communities and the evolutionary trajectories of host populations with resulting feedback on biogeochemical cycles. It is quite possible that all microbial populations in the ocean are impacted by viral infections. Our knowledge of virus–host relationships, however, has been limited to a minute fraction of cultivated host groups. Here, we utilized single-cell sequencing to obtain genomic blueprints of viruses inside or attached to individual bacterial and archaeal cells captured in their native environment, circumventing the need for host and virus cultivation. A combination of comparative genomics, metagenomic fragment recruitment, sequence anomalies and irregularities in sequence coverage depth and genome recovery were utilized to detect viruses and to decipher modes of virus–host interactions. Members of all three tailed phage families were identified in 20 out of 58 phylogenetically and geographically diverse single amplified genomes (SAGs) of marine bacteria and archaea. At least four phage–host interactions had the characteristics of late lytic infections, all of which were found in metabolically active cells. One virus had genetic potential for lysogeny. Our findings include first known viruses of Thaumarchaeota, Marinimicrobia, Verrucomicrobia and Gammaproteobacteria clusters SAR86 and SAR92. Viruses were also found in SAGs of Alphaproteobacteria and Bacteroidetes. A high fragment recruitment of viral metagenomic reads confirmed that most of the SAG-associated viruses are abundant in the ocean. Our study demonstrates that single-cell genomics, in conjunction with sequence-based computational tools, enable in situ, cultivation-independent insights into host–virus interactions in complex microbial communities.     

Accounting for Errors in Data Improves Divergence Time Estimates in Single-cell Cancer Evolution

Single-cell sequencing provides a new way to explore the evolutionary history of cells. Compared to traditional bulk sequencing, where a population of heterogeneous cells is pooled to form a single observation, single-cell sequencing isolates and amplifies genetic material from individual cells, thereby preserving the information about the origin of the sequences. However, single-cell data are more error-prone than bulk sequencing data due to the limited genomic material available per cell. Here, we present error and mutation models for evolutionary inference of single-cell data within a mature and extensible Bayesian framework, BEAST2. Our framework enables integration with biologically informative models such as relaxed molecular clocks and population dynamic models. Our simulations show that modeling errors increase the accuracy of relative divergence times and substitution parameters. We reconstruct the phylogenetic history of a colorectal cancer patient and a healthy patient from single-cell DNA sequencing data. We find that the estimated times of terminal splitting events are shifted forward in time compared to models which ignore errors. We observed that not accounting for errors can overestimate the phylogenetic diversity in single-cell DNA sequencing data. We estimate that 30–50% of the apparent diversity can be attributed to error. Our work enables a full Bayesian approach capable of accounting for errors in the data within the integrative Bayesian software framework BEAST2.     

Enhancing biological signals and detection rates in single-cell RNA-seq experiments with cDNA library equalization

Considerable effort has been devoted to refining experimental protocols to reduce levels of technical variability and artifacts in single-cell RNA-sequencing data (scRNA-seq). We here present evidence that equalizing the concentration of cDNA libraries prior to pooling, a step not consistently performed in single-cell experiments, improves gene detection rates, enhances biological signals, and reduces technical artifacts in scRNA-seq data. To evaluate the effect of equalization on various protocols, we developed Scaffold, a simulation framework that models each step of an scRNA-seq experiment. Numerical experiments demonstrate that equalization reduces variation in sequencing depth and gene-specific expression variability. We then performed a set of experiments in vitro with and without the equalization step and found that equalization increases the number of genes that are detected in every cell by 17–31%, improves discovery of biologically relevant genes, and reduces nuisance signals associated with cell cycle. Further support is provided in an analysis of publicly available data.     

Biological control in a disturbed environment

Most ecological and epidemiological models describe systems with continuous uninterrupted interactions between populations. Many systems, though, have ecological disturbances, such as those associated with planting and harvesting of a seasonal crop. In this paper, we introduce host–parasite–hyperparasite systems as models of biological control in a disturbed environment, where the host–parasite interactions are discontinuous. One model is a parasite–hyperparasite system designed to capture the essence of biological control and the other is a host–parasite–hyperparasite system that incorporates many more features of the population dynamics. Two types of discontinuity are included in the models. One corresponds to a pulse of new parasites at harvest and the other reflects the discontinuous presence of the host due to planting and harvesting. Such discontinuities are characteristic of many ecosystems involving parasitism or other interactions with an annual host. The models are tested against data from an experiment investigating the persistent biological control of the fungal plant parasite of lettuce Sclerotinia minor by the fungal hyperparasite Sporidesmium sclerotivorum, over successive crops. Using a combination of mathematical analysis, model fitting and parameter estimation, the factors that contribute the observed persistence of the parasite are examined. Analytical results show that repeated planting and harvesting of the host allows the parasite to persist by maintaining a quantity of host tissue in the system on which the parasite can reproduce. When the host dynamics are not included explicitly in the model, we demonstrate that homogeneous mixing fails to predict the persistence of the parasite population, while incorporating spatial heterogeneity by allowing for heterogeneous mixing prevents fade-out. Including the host''s dynamics lessens the effect of heterogeneous mixing on persistence, though the predicted values for the parasite population are closer to the observed values. An alternative hypothesis for persistence involving a stepped change in rates of infection is also tested and model fitting is used to show that changes in some environmental conditions may contribute to parasite persistence. The importance of disturbances and periodic forcing in models for interacting populations is discussed.     

Topographic Factor Analysis: A Bayesian Model for Inferring Brain Networks from Neural Data

The neural patterns recorded during a neuroscientific experiment reflect complex interactions between many brain regions, each comprising millions of neurons. However, the measurements themselves are typically abstracted from that underlying structure. For example, functional magnetic resonance imaging (fMRI) datasets comprise a time series of three-dimensional images, where each voxel in an image (roughly) reflects the activity of the brain structure(s)–located at the corresponding point in space–at the time the image was collected. FMRI data often exhibit strong spatial correlations, whereby nearby voxels behave similarly over time as the underlying brain structure modulates its activity. Here we develop topographic factor analysis (TFA), a technique that exploits spatial correlations in fMRI data to recover the underlying structure that the images reflect. Specifically, TFA casts each brain image as a weighted sum of spatial functions. The parameters of those spatial functions, which may be learned by applying TFA to an fMRI dataset, reveal the locations and sizes of the brain structures activated while the data were collected, as well as the interactions between those structures.     

Precocious Mammary Gland Development in P-Cadherin–deficient Mice

To investigate the functions of P-cadherin in vivo, we have mutated the gene encoding this cell adhesion receptor in mice. In contrast to E- and N-cadherin– deficient mice, mice homozygous for the P-cadherin mutation are viable. Although P-cadherin is expressed at high levels in the placenta, P-cadherin–null females are fertile. P-cadherin expression is localized to the myoepithelial cells surrounding the lumenal epithelial cells of the mammary gland. The role of the myoepithelium as a contractile tissue necessary for milk secretion is clear, but its function in the nonpregnant animal is unknown. The ability of the P-cadherin mutant female to nurse and maintain her litter indicates that the contractile function of the myoepithelium is not dependent on the cell adhesion molecule P-cadherin. The virgin P-cadherin–null females display precocious differentiation of the mammary gland. The alveolar-like buds in virgins resemble the glands of an early pregnant animal morphologically and biochemically (i.e., milk protein synthesis). The P-cadherin mutant mice develop hyperplasia and dysplasia of the mammary epithelium with age. In addition, abnormal lymphocyte infiltration was observed in the mammary glands of the mutant animals. These results indicate that P-cadherin–mediated adhesion and/or signals derived from cell–cell interactions are important determinants in negative growth control in the mammary gland. Furthermore, the loss of P-cadherin from the myoepithelium has uncovered a novel function for this tissue in maintaining the undifferentiated state of the underlying secretory epithelium.