Maps of variability in cell lineage trees

New approaches to lineage tracking have allowed the study of differentiation in multicellular organisms over many generations of cells. Understanding the phenotypic variability observed in these lineage trees requires new statistical methods. Whereas an invariant cell lineage, such as that for the nematode Caenorhabditis elegans, can be described by a lineage map, defined as the pattern of phenotypes overlaid onto the binary tree, a traditional lineage map is static and does not describe the variability inherent in the cell lineages of higher organisms. Here, we introduce lineage variability maps which describe the pattern of second-order variation in lineage trees. These maps can be undirected graphs of the partial correlations between every lineal position, or directed graphs showing the dynamics of bifurcated patterns in each subtree. We show how to infer these graphical models for lineages of any depth from sample sizes of only a few pedigrees. This required developing the generalized spectral analysis for a binary tree, the natural framework for describing tree-structured variation. When tested on pedigrees from C. elegans expressing a marker for pharyngeal differentiation potential, the variability maps recover essential features of the known lineage map. When applied to highly-variable pedigrees monitoring cell size in T lymphocytes, the maps show that most of the phenotype is set by the founder naive T cell. Lineage variability maps thus elevate the concept of the lineage map to the population level, addressing questions about the potency and dynamics of cell lineages and providing a way to quantify the progressive restriction of cell fate with increasing depth in the tree.

Imaging Asymmetric T Cell Division

Asymmetric cell division (ACD) controls cell fate decisions in model organisms such as Drosophila and C. elegans and has recently emerged as a mediator of T cell fate and hematopoiesis. The most appropriate methods for assessing ACD in T cells are still evolving. Here we describe the methods currently applied to monitor and measure ACD of developing and activated T cells. We provide an overview of approaches for capturing cells in the process of cytokinesis in vivo, ex vivo, or during in vitro culture. We provide methods for in vitro fixed immunofluorescent staining and for time-lapse analysis. We provide an overview of the different approaches for quantification of ACD of lymphocytes, discuss the pitfalls and concerns in interpretation of these analyses, and provide detailed methods for the quantification of ACD in our group.

Explosive cell lysis as a mechanism for the biogenesis of bacterial membrane vesicles and biofilms

Many bacteria produce extracellular and surface-associated components such as membrane vesicles (MVs), extracellular DNA and moonlighting cytosolic proteins for which the biogenesis and export pathways are not fully understood. Here we show that the explosive cell lysis of a sub-population of cells accounts for the liberation of cytosolic content in Pseudomonas aeruginosa biofilms. Super-resolution microscopy reveals that explosive cell lysis also produces shattered membrane fragments that rapidly form MVs. A prophage endolysin encoded within the R- and F-pyocin gene cluster is essential for explosive cell lysis. Endolysin-deficient mutants are defective in MV production and biofilm development, consistent with a crucial role in the biogenesis of MVs and liberation of extracellular DNA and other biofilm matrix components. Our findings reveal that explosive cell lysis, mediated through the activity of a cryptic prophage endolysin, acts as a mechanism for the production of bacterial MVs.

Asymmetric cell division during T cell development controls downstream fate

T cell precursors undergo asymmetric cell division after T cell receptor genomic recombination, with stromal cell cues controlling the differential inheritance of fate determinants Numb and α-Adaptin by the daughters of a dividing DN3a T cell precursor.

During mammalian T cell development, the requirement for expansion of many individual T cell clones, rather than merely expansion of the entire T cell population, suggests a possible role for asymmetric cell division (ACD). We show that ACD of developing T cells controls cell fate through differential inheritance of cell fate determinants Numb and α-Adaptin. ACD occurs specifically during the β-selection stage of T cell development, and subsequent divisions are predominantly symmetric. ACD is controlled by interaction with stromal cells and chemokine receptor signaling and uses a conserved network of polarity regulators. The disruption of polarity by deletion of the polarity regulator, Scribble, or the altered inheritance of fate determinants impacts subsequent fate decisions to influence the numbers of DN4 cells arising after the β-selection checkpoint. These findings indicate that ACD enables the thymic microenvironment to orchestrate fate decisions related to differentiation and self-renewal.

CellTracker (not only) for dummies

MOTIVATION

Time-lapse experiments play a key role in studying the dynamic behavior of cells. Single-cell tracking is one of the fundamental tools for such analyses. The vast majority of the recently introduced cell tracking methods are limited to fluorescently labeled cells. An equally important limitation is that most software cannot be effectively used by biologists without reasonable expertise in image processing. Here we present CellTracker, a user-friendly open-source software tool for tracking cells imaged with various imaging modalities, including fluorescent, phase contrast and differential interference contrast (DIC) techniques.

AVAILABILITY AND IMPLEMENTATION

CellTracker is written in MATLAB (The MathWorks, Inc., USA). It works with Windows, Macintosh and UNIX-based systems. Source code and graphical user interface (GUI) are freely available at: http://celltracker.website/

CONTACT

horvath.peter@brc.mta.hu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Normalized polarization ratios for the analysis of cell polarity

The quantification and analysis of molecular localization in living cells is increasingly important for elucidating biological pathways, and new methods are rapidly emerging. The quantification of cell polarity has generated much interest recently, and ratiometric analysis of fluorescence microscopy images provides one means to quantify cell polarity. However, detection of fluorescence, and the ratiometric measurement, is likely to be sensitive to acquisition settings and image processing parameters. Using imaging of EGFP-expressing cells and computer simulations of variations in fluorescence ratios, we characterized the dependence of ratiometric measurements on processing parameters. This analysis showed that image settings alter polarization measurements; and that clustered localization is more susceptible to artifacts than homogeneous localization. To correct for such inconsistencies, we developed and validated a method for choosing the most appropriate analysis settings, and for incorporating internal controls to ensure fidelity of polarity measurements. This approach is applicable to testing polarity in all cells where the axis of polarity is known.

The actin-driven spatiotemporal organization of T-cell signaling at the system scale

T cells are activated through interaction with antigen-presenting cells (APCs). During activation, receptors and signaling intermediates accumulate in diverse spatiotemporal distributions. These distributions control the probability of signaling interactions and thus govern information flow through the signaling system. Spatiotemporally resolved system-scale investigation of signaling can extract the regulatory information thus encoded, allowing unique insight into the control of T-cell function. Substantial technical challenges exist, and these are briefly discussed herein. While much of the work assessing T-cell spatiotemporal organization uses planar APC substitutes, we focus here on B-cell APCs with often stark differences. Spatiotemporal signaling distributions are driven by cell biologically distinct structures, a large protein assembly at the interface center, a large invagination, the actin-supported interface periphery as extended by smaller individual lamella, and a newly discovered whole-interface actin-driven lamellum. The more than 60 elements of T-cell activation studied to date are dynamically distributed between these structures, generating a complex organization of the signaling system. Signal initiation and core signaling prefer the interface center, while signal amplification is localized in the transient lamellum. Actin dynamics control signaling distributions through regulation of the underlying structures and drive a highly undulating T-cell/APC interface that imposes substantial constraints on T-cell organization. We suggest that the regulation of actin dynamics, by controlling signaling distributions and membrane topology, is an important rheostat of T-cell signaling.