Thymus and Bursa Dependence of Lymphocyte Mitogenic Factor in the Chicken

AMONG the soluble products generated during activation of rodent or human lymphocytes¹, lymphocyte-stimulating (‘mitogenic’) factors are detected by their ability to accelerate DNA metabolism of freshly cultured allogeneic or syngeneic lymphocytes^2–8. If such lymphocyte activation products function as mediators of cellular immunity^1,9–11, their activities will be generated independently of the antibody-forming system. In the chicken, antigen-stimulation of sensitized lymphocytes in vitro involves both thymus (T-) and bursa-(B-)-dependent cells^12–14. If antigen-induced lymphocyte transformations are generally mediated by lymphocyte mitogenic factors, both T-cells and B-cells should produce lymphocyte mitogenic factors when stimulated by specific antigen. We have therefore determined whether antigen-stimulated chicken lymphocytes generate a lymphocyte mitogenic factor and whether this response is affected by neonatal thymectomy or bursectomy.     

An experimental design and procedures for testing putative controls against naturally-occurring take-all in the field

In experiments during 1983–86 take-all was more severe and eyespot and sharp eyespot less frequent in 2nd-4th crops of winter wheat at Woburn (Beds.) than at Rothamsted (Herts.). Third crops had most take-all and yielded least grain. Against this background, small plots, 37 cm × 31 cm, in which all plants were sampled, were tried as a means of increasing experimental precision. They were arranged in fours in incomplete blocks and blocks with complementary treatments (putative controls of take-all) were paired. Thirty of these block-pairs were distributed throughout each experimental site in each year to provide one replicate of the design for each of three sampling times: April, June and August. Unattributed variation in disease and plant growth for plots within blocks was compared to that in other strata (block-pairs and blocks within block-pairs) of the experiment. The variability amongst block-pairs scattered throughout the site was nearly always greater than that for blocks within block-pairs (98% of take-all assessments, 71% of soil infectivity estimates, 94% of eyespot and sharp eyespot assessments and 86% of all plant measurements). The variability of blocks within block-pairs exceeded that of plots much less frequently (56% and 69% of take-all assessments, 33% and 25% of soil infectivity measurements, 63% and 56% of eyespot and sharp eyespot assessments and 50% and 63% of plant measurements; Rothamsted and Woburn, respectively). Small plots were judged mostly on this last comparison, where a variance ratio in excess of 1 indicated that the small plots had decreased variability and increased precision. Variance ratios for different assessments of take-all indicates that small plots: i) most consistently decreased disease variability during the years of maximum disease, ii) were slightly less effective at Rothamsted than at Woburn, and iii) were usually less effective in fourth crops than in previous crops. Soil infectivity was most uniform after crops with most disease and blocks were rarely more variable than plots. hxcept when disease was severe, soil infectivity in August tended to be positively associated with the yield of the crop just harvested. These findings reveal changes in the scale of disease patterns, both during the crop sequence and within individual crops, and suggest more than one scale of pattern in take-all-infested fields. This is discussed in relation to field experimentation and take-all decline.     

Beyond aflatoxin: four distinct expression patterns and functional roles associated with Aspergillus flavus secondary metabolism gene clusters

Species of Aspergillus produce a diverse array of secondary metabolites, and recent genomic analysis has predicted that these species have the capacity to synthesize many more compounds. It has been possible to infer the presence of 55 gene clusters associated with secondary metabolism in Aspergillus flavus ; however, only three metabolic pathways—aflatoxin, cyclopiazonic acid (CPA) and aflatrem—have been assigned to these clusters. To gain an insight into the regulation of and to infer the ecological significance of the 55 secondary metabolite gene clusters predicted in A. flavus, we examined their expression over 28 diverse conditions. Variables included culture medium and temperature, fungal development, colonization of developing maize seeds and misexpression of laeA , a global regulator of secondary metabolism. Hierarchical clustering analysis of expression profiles allowed us to categorize the gene clusters into four distinct clades. Gene clusters for the production of aflatoxins, CPA and seven other unknown compound(s) were identified as belonging to one clade. To further explore the relationships found by gene expression analysis, aflatoxin and CPA production were quantified under five different cell culture environments known to be conducive or nonconducive for aflatoxin biosynthesis and during the colonization of developing maize seeds. Results from these studies showed that secondary metabolism gene clusters have distinctive gene expression profiles. Aflatoxin and CPA were found to have unique regulation, but are sufficiently similar that they would be expected to co-occur in substrates colonized with A. flavus .     

Ethirimol-sensitivity in populations of Erysiphe graminis from plots of spring barley

Barley plots, cv. Proctor were sown with either ethirimol-treated or untreated seed. At seedling emergence, plots were inoculated with isolates of Erysiphe graminis either sensitive or insensitive to ethirimol, or left uninoculated. Mildew samples taken from the coleoptile leaves of seedlings, and later from leaf 6 (next but one to the flag leaf) were compared for ethirimol sensitivity using probit analysis. Probit lines were derived using ‘Wadley's analysis’. This analysis uses the number of survivors to estimate the total number of individuals originally present. In the test for ethirimol sensitivity a count of colonies on inoculated test leaves was taken to represent survivors. Microscopic counting of the original inoculum was thus avoided. The analyses snowed that the initial leaf inoculation treatments established mildew populations in the plots, which differed considerably in ethirimol sensitivity. Some 6 wk after inoculation the levels of sensitivity in these populations remained unchanged even though inoculum coming into the experiment from external sources was often much more insensitive than the mildew in some plots. Probit lines of response to ethirimol had shallow slopes, showing that large variability exists in the pathogen for this character.