A sensitive bioassay for the mycotoxin aflatoxin B1, which also responds to the mycotoxins aflatoxin G1 and T-2 toxin, using engineered baker's yeast

A novel aflatoxin B(1) bioassay was created by introducing a Lipomyces kononenkoae alpha-amylase gene into a strain of S. cerevisiae capable of expressing the human cytochrome P450 3A4 (CYP3A4), and the cognate human CYP450 reductase. This strain and a dextranase-expressing strain were used in the development of a microtitre plate mycotoxin bioassay, which employed methanol as the solvent and polymyxin B nonapeptide as a permeation enhancer. Stable co-expression of the CYP3A4 gene system and of the dextranase and amylase genes in the two bioassay strains was demonstrated. The bioassay signalled toxicity as inhibition of secreted carbohydrase activity, using sensitive fluorimetric assays. The amylase-expressing strain could detect aflatoxin B(1) at 2 ng/ml, and was more sensitive than the dextranase-expressing strain. Aflatoxin G(1) could be detected at 2 microg/ml, and the trichothecene mycotoxin T-2 toxin was detectable at 100 ng/ml.

A multilevel algorithm for force-directed graph-drawing

We describe a heuristic method for drawing graphs which uses a multilevel framework combined with a force-directed placement algorithm. The multilevel technique matches and coalesces pairs of adjacent vertices to define a new graph and is repeated recursively to create a hierarchy of increasingly coarse graphs, G0, G1, …, GL. The coarsest graph, GL, is then given an initial layout and the layout is refined and extended to all the graphs starting with the coarsest and ending with the original. At each successive change of level, l, the initial layout for Gl is taken from its coarser and smaller child graph, Gl+1, and refined using force-directed placement. In this way the multilevel framework both accelerates and appears to give a more global quality to the drawing. The algorithm can compute both 2 & 3 dimensional layouts and we demonstrate it on examples ranging in size from 10 to 225,000 vertices. It is also very fast and can compute a 2D layout of a sparse graph in around 12 seconds for a 10,000 vertex graph to around 5-7 minutes for the largest graphs. This is an order of magnitude faster than recent implementations of force-directed placement algorithms.