Bacterial diversity in the bulk soil and rhizosphere fractions of Lolium perenne and Trifolium repens as revealed by PCR restriction analysis of 16S rDNA

The rhizosphere of Trifolium repens and Lolium perenne was divided into three fractions: the bulk soil, the soil adhering to the roots and the washed roots (rhizoplane and endorhizosphere). After isolation and purification of DNA from these fractions, 16S rDNA was amplified by PCR and cloned to obtain a collection of 16S rRNA genes representative of the bacterial communities of these three fractions. The genes were then characterized by PCR restriction analysis. Each different profile was used to define an operational taxonomic unit (OTU). The numbers of OTUs and the numbers of clones among these OTUs allowed to calculate a diversity index. The number of OTUs decreased as root proximity increased and a few OTUs became dominant, resulting in a lower diversity index. In the root fraction of T. repens, the restriction profile of the dominant OTU matched the theoretical profile of the 16S rRNA gene of Rhizobium leguminosarum. This study showed that plant roots create a selective environment for microbial populations.     

In vivo differentiated cytokine-producing CD4(+) T cells express functional CCR7

Chemokines and their receptors fulfill specialized roles in inflammation and under homeostatic conditions. CCR7 and its ligands, CCL19 and CCL21, are involved in lymphocyte recirculation through secondary lymphoid organs and additionally navigate lymphocytes into distinct tissue compartments. The role of CCR7 in the migration of polarized T effector/memory cell subsets in vivo is still poorly understood. We therefore analyzed murine and human CD4(+) cytokine-producing cells developed in vivo for their chemotactic reactivity to CCR7 ligands. The responses of cells producing cytokines, such as IFN-gamma, IL-4, and IL-10, as well as of subsets defined by memory or activation markers were comparable to that of naive CD4(+) cells, with slightly lower reactivity in cells expressing IL-10 or CD69. This indicates that CCR7 ligands are able to attract naive as well as the vast majority of activated and effector/memory T cell stages. Chemotactic reactivity of these cells toward CCL21 was absent in CCR7-deficient cells, proving that effector cells do not use alternative receptors for this chemokine. Th1 cells generated from CCR7(-/-) mice failed to enter lymph nodes and Peyer's patches, but did enter a site of inflammation. These findings indicate that CD4(+) cells producing effector cytokines upon stimulation retain the capacity to recirculate through lymphoid tissues via CCR7.     

Response regulation in bacterial chemotaxis

The signal transduction system that mediates bacterial chemotaxis allows cells to moduate their swimming behavior in response to fluctuations in chemical stimuli. Receptors at the cell surface receive information from the surroundings. Signals are then passed from the receptors to cytoplasmic chemotaxis components: CheA, CheW, CheZ, CheR, and CheB. These proteins function to regulate the level of phosphorylation of a response regulator designated CheY that interacts with the flagellar motor switch complex to control swimming behavior. The structure of CheY has been determined. Magnesium ion is essential for activity. The active site contains highly conserved Asp residues that are required for divalent metal ion binding and CheY phosphorylation. Another residue-at the active site, Lys109, is important in the phosphorylation-induced conformational change that facilitates communication with the switch complex and another chemotaxis component, CheZ. CheZ facilitates the dephosphorylation of phospho-CheY. Defects in CheY and CheZ can be suppressed by mutations in the flagellar switch complex. CheZ is thought to modulate the switch bias by varying the level of phospho-CheY. © 1993 Wiley-Liss, Inc.     

The stationary state of epithelia

A tissue is a geometrical, space-filling, random cellular network; it remains in this steady state while individual cells divide. Cell division is a local, elementary topological transformation which establishes statistical equilibrium of the structure. We describe the physical conditions to maintain stationary the epidermis (of mammals or of the cucumber), in spite of the fact that cells constantly divide and die. Specifically, we study the statistical equilibrium of the basal layer, a corrugated surface filled with cells, constituting a two-dimensional topological froth. Cells divide and detach from the basal layer, and these two topological transformations are responsible for the stationary state of the epidermis. The topological froth is capable of responding rapidly and locally to external constraints, and is a good illustration of the plasticity of random cellular networks.Statistical equilibrium is controlled by entropy, both as a measure of disorder and as information, and is characterized by observable relations between average cell shapes and sizes. The technique can be applied to any random cellular network in dynamical equilibrium. Mitosis as the dominating topological transformation and the fact that the distribution of cell shapes is very narrow are the only inputs specific to biology.

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Resume Un tissu est, à première vue, un pavage aléatoire d'une surface ou d'un volume par des polygones (polyèdres) topologiques, les cellules. Ce pavage reste dans un état stationnaire alors que les cellules se divisent constamment. Nous décrivons les conditions physiques nécessaires à l'état stationnaire de l'épiderme (des mammifères et du concombre), en dépit du fait que ses cellules se divisent et meurent. En particulier, nous étudions l'équilibre statistique de la couche basale, une surface couverte de cellules constituant une mousse topologique aléatoire. Les cellules se divisent et se détachent de la couche basale, et ces transformations topologiques sont responsable de l'état stationnaire de l'épiderme. Cette mousse topologique est capable de répondre rapidement et localement à des contraintes externes. C'est un exemple de plasticité de structures cellulaires aléatoires.L'équilibre statistique est contrôlé par l'entropie qui est ici à la fois une mesure du désordre et une quantité d'information. Il est caractérisé par des relations facilement observables entre les formes des cellules et leurs dimensions. Les seuls éléments spécifiques aux tissus biologiques sont la mitose comme transformation topologique dominante, et l'étroitesse de la distribution des formes de cellules.

     

Spind: a package for computing spatially corrected accuracy measures

Using an appropriate accuracy measure is essential for assessing prediction accuracy in species distribution modelling. Therefore, model evaluation as an analytical uncertainty is a challenging problem. Although a variety of accuracy measures for the assessment of prediction errors in presence/absence models is available, there is a lack of spatial accuracy measures, i.e. measures that are sensitive to the spatial arrangement of the predictions. We present ‘spind’, a new software package (based on the R software program) that provides spatial performance measures for grid‐based models. These accuracy measures are generalized, spatially corrected versions of the classical ones, thus enabling comparisons between them. Our method for evaluation consists of the following steps: 1) incorporate additional autocorrelation until spatial autocorrelation in predictions and actuals is balanced, 2) cross‐classify predictions and adjusted actuals in a 4 × 4 contingency table, 3) use a refined weighting pattern for errors, and 4) calculate weighted Kappa, sensitivity, specificity and subsequently ROC, AUC, TSS to get spatially corrected indices. To illustrate the impact of our spatial method we present an example of simulated data as well as an example of presence/absence data of the plant species Dianthus carthusianorum across Germany. Our analysis includes a statistic for the comparison of spatial and classical (non‐spatial) indices. We find that our spatial indices tend to result in higher values than classical ones. These differences are statistically significant at medium and high autocorrelation levels. We conclude that these spatial accuracy measures may contribute to evaluate prediction errors in presence/absence models, especially in case of medium or high degree of similarity of adjacent data, i.e. aggregated (clumped) or continuous species distributions.