Yeast-based automated high-throughput screens to identify anti-parasitic lead compounds.

We have developed a robust, fully automated anti-parasitic drug-screening method that selects compounds specifically targeting parasite enzymes and not their host counterparts, thus allowing the early elimination of compounds with potential side effects. Our yeast system permits multiple parasite targets to be assayed in parallel owing to the strains' expression of different fluorescent proteins. A strain expressing the human target is included in the multiplexed screen to exclude compounds that do not discriminate between host and parasite enzymes.

The automation of science.

The basis of science is the hypothetico-deductive method and the recording of experiments in sufficient detail to enable reproducibility. We report the development of Robot Scientist "Adam," which advances the automation of both. Adam has autonomously generated functional genomics hypotheses about the yeast Saccharomyces cerevisiae and experimentally tested these hypotheses by using laboratory automation.

Nondestructive analysis of senescence in mesophyll cells by spectral resolution of protein synthesis-dependent pigment metabolism.

* Over 6 d of dark-induced senescence, leaf segments of wild-type Lolium temulentum lost > 96% chlorophyll a + b; leaves from plants containing a staygreen mutation introgressed from Festuca pratensis, which has a lesion in the senescence-associated fragmentation of pigment-proteolipid complexes, retained over 43% of total chlorophyll over the same period. * Mutant segments preferentially retained thylakoid membrane proteins (exemplified by LHCP II) but lost other cellular proteins at the same rate as wild-type tissue. The protein synthesis inhibitor D-MDMP inhibited chlorophyll degradation and partially prevented protein loss in both genotypes, but tissues treated with the ineffective L-stereoisomer were indistinguishable from water controls.

A general model of error-prone PCR.

In this paper, we generalize a previously-described model of the error-prone polymerase chain reaction (PCR) reaction to conditions of arbitrarily variable amplification efficiency and initial population size. Generalisation of the model to these conditions improves the correspondence to observed and expected behaviours of PCR, and restricts the extent to which the model may explore sequence space for a prescribed set of parameters. Error-prone PCR in realistic reaction conditions is predicted to be less effective at generating grossly divergent sequences than the original model.

Discrimination of modes of action of antifungal substances by use of metabolic footprinting.

Diploid cells of Saccharomyces cerevisiae were grown under controlled conditions with a Bioscreen instrument, which permitted the essentially continuous registration of their growth via optical density measurements. Some cultures were exposed to concentrations of a number of antifungal substances with different targets or modes of action (sterol biosynthesis, respiratory chain, amino acid synthesis, and the uncoupler). Culture supernatants were taken and analyzed for their "metabolic footprints" by using direct-injection mass spectrometry.

Fast automatic registration of images using the phase of a complex wavelet transform: application to proteome gels.

Image registration describes the process of manipulating a distorted version of an image such that its pixels overlay the equivalent pixels in a clean, master or reference image. The need for it has assumed particular prominence in the analysis of images of electrophoretic gels used in the analysis of protein expression levels in living cells, but also has fundamental applications in most other areas of image analysis. Much of the positional information of a data feature is carried in the phase of a complex transform, so a complex transform allows explicit specification of the phase, and hence of the position of features in the image.

Single-nucleotide polymorphism detection using nanomolar nucleotides and single-molecule fluorescence.

We have exploited three methods for discriminating single-nucleotide polymorphisms (SNPs) by detecting the incorporation or otherwise of labeled dideoxy nucleotides at the end of a primer chain using single-molecule fluorescence detection methods. Good discrimination of incorporated vs free nucleotide may be obtained in a homogeneous assay (without washing steps) via confocal fluorescence correlation spectroscopy or by polarization anisotropy obtained from confocal fluorescence intensity distribution analysis. Moreover, the ratio of the fluorescence intensities on each polarization channel may be used directly to discriminate the nucleotides incorporated.

High-throughput classification of yeast mutants for functional genomics using metabolic footprinting.

Many technologies have been developed to help explain the function of genes discovered by systematic genome sequencing. At present, transcriptome and proteome studies dominate large-scale functional analysis strategies. Yet the metabolome, because it is 'downstream', should show greater effects of genetic or physiological changes and thus should be much closer to the phenotype of the organism.

Monitoring of complex industrial bioprocesses for metabolite concentrations using modern spectroscopies and machine learning: application to gibberellic acid production.

Two rapid vibrational spectroscopic approaches (diffuse reflectance-absorbance Fourier transform infrared [FT-IR] and dispersive Raman spectroscopy), and one mass spectrometric method based on in vacuo Curie-point pyrolysis (PyMS), were investigated in this study. A diverse range of unprocessed, industrial fed-batch fermentation broths containing the fungus Gibberella fujikuroi producing the natural product gibberellic acid, were analyzed directly without a priori chromatographic separation. Partial least squares regression (PLSR) and artificial neural networks (ANNs) were applied to all of the information-rich spectra obtained by each of the methods to obtain quantitative information on the gibberellic acid titer.

Rapid and quantitative detection of the microbial spoilage of meat by fourier transform infrared spectroscopy and machine learning.

Fourier transform infrared (FT-IR) spectroscopy is a rapid, noninvasive technique with considerable potential for application in the food and related industries. We show here that this technique can be used directly on the surface of food to produce biochemically interpretable "fingerprints." Spoilage in meat is the result of decomposition and the formation of metabolites caused by the growth and enzymatic activity of microorganisms.