Anders Blomberg

The proteomes of three industrial lager beer strains, CMBS33, OG2252 and A15, were analysed under standardised laboratory growth conditions. Protein spots in the 2‐DE pattern of the lager strains were subjected to MS/MS to identify protein variants. We found the protein composition of the three lager strains to be qualitatively rather similar, while being substantially different from the Saccharomyces cerevisiae strain BY4742. Database searches using several fully sequenced genomes from the Saccharomyces genera indicated that the non‐cerevisiae proteins in the 2‐D pattern of lager strains were most closely related to S. bayanus. For many proteins the regulation of the bayanus‐like protein and its cerevisiae counterpart varied in a strain‐dependent manner, e.g. the bayanus‐like form of Tdh3p was roughly eight‐fold more abundant than the cerevisiae form in the OG2252 strain. We also found differential regulation of cerevisiae‐ and bayanus‐like proteins during various stress conditions like low temperature growth, and adaptation to high temperatures or high salinity, e.g. for Arg1p, Sti1p and Pdc1p. Our data on the differential regulation of the two genomes in these hybrid strains may have important industrial implications for strain improvement and strain protection.

Connecting genotype to phenotype is fundamental in biomedical research and in our understanding of disease. Phenomics--the large-scale quantitative phenotypic analysis of genotypes on a genome-wide scale--connects automated data generation with the development of novel tools for phenotype data integration, mining and visualization. Our yeast phenomics database PROPHECY is available at http://prophecy.lundberg.gu.se. Via phenotyping of 984 heterozygous diploids for all essential genes the genotypes analysed and presented in PROPHECY have been extended and now include all genes in the yeast genome. Further, phenotypic data from gene overexpression of 574 membrane spanning proteins has recently been included. To facilitate the interpretation of quantitative phenotypic data we have developed a new phenotype display option, the Comparative Growth Curve Display, where growth curve differences for a large number of mutants compared with the wild type are easily revealed. In addition, PROPHECY now offers a more informative and intuitive first-sight display of its phenotypic data via its new summary page. We have also extended the arsenal of data analysis tools to include dynamic visualization of phenotypes along individual chromosomes. PROPHECY is an initiative to enhance the growing field of phenome bioinformatics.

To investigate Saccharomyces cerevisiae physiology during growth on the conditionally toxic triose dihydroxyacetone (DHA), protein expression was studied in strains overexpressing either of the two dihydroxyacetone kinase isogenes, DAK1 or DAK2, that grow well utilizing DHA as a carbon and energy source. DHA metabolism was found mostly similar to ethanol utilization, involving a strong component of glucose derepression, but also involved DHA-specific regulatory changes. A specific and strong (10- to 30-fold induction of formaldehyde dehydrogenase, Fdhlp, indicated activation of the formaldehyde dissimilation pathway in DHA medium. The importance of this pathway was further supported by impaired adaptation to DHA growth and DHA survival in a glutathione-dependent formaldehyde dehydrogenase (SFA1) deletion mutant. Glutathione synthase (GSH1) deletion led to decreased DHA survival in agreement with the glutathione cofactor requirement for the SFA1-encoded activity. DHA toxicity did, however, not solely appear related to formaldehyde accumulation, because SFA1 overexpression only enhanced formaldehyde but not DHA tolerance. In further agreement with a low DHA-to-formaldehyde flux, GSH supplements in the low microM range also fully suppressed the DHA sensitivity of a gsh1Delta strain. Under growth reduction on high (100 mM) DHA medium we report increased levels of advanced glycation end-product (AGE) formation on total protein. Under these high-DHA conditions expression of several stress-related proteins, e.g. a heat-shock protein (Hsp104p) and the oxidative stress indicator, alkyl hydroperoxide reductase (Ahp1p) was also found induced. However, hallmark determinants of oxidative stress tolerance (e.g. YAP1, SKN7, HYR1/GPX3 and SOD2) were redundant for DHA tolerance, thus indicating mechanisms of DHA toxicity largely independent of central oxidative stress defence mechanisms. We conclude that mechanisms for DHA growth and detoxification appear complex and that the evolutionary strive to minimize detrimental effects of this intracellular metabolite links to both formaldehyde and glutathione metabolism.

Genetic pleiotropy, the ability of a mutation in a single gene to give rise to multiple phenotypic outcomes, constitutes an important but incompletely understood biological phenomenon. We used a high-resolution and high-precision phenotypic profiling approach to quantify the fitness contribution of genes on the five smallest yeast chromosomes during different forms of environmental stress, selected to probe a wide diversity of physiological features. We found that the extent of pleiotropy is much higher than previously claimed; 17% of the yeast genes were pleiotropic whereof one-fifth were hyper-pleiotropic. Pleiotropic genes preferentially participate in functions related to determination of protein fate, cell growth and morphogenesis, signal transduction and transcription. Contrary to what has earlier been proposed we did not find experimental evidence for slower evolutionary rate of pleiotropic genes/proteins. We also refute the existence of phenotypic islands along chromosomes but report on a remarkable loss both of pleiotropy and of phenotypic penetrance towards chromosomal ends. Thus, the here reported features of pleiotropy both have implications on our understanding of evolutionary processes as well as the mechanisms underlying disease.

The N-terminal acetyltransferase NatB in Saccharomyces cerevisiae consists of the catalytic subunit Nat3p and the associated subunit Mdm20p. We here extend our present knowledge about the physiological role of NatB by a combined proteomics and phenomics approach. We found that strains deleted for either NAT3 or MDM20 displayed different growth rates and morphologies in specific stress conditions, demonstrating that the two NatB subunits have partly individual functions. Earlier reported phenotypes of the nat3Δ strain have been associated with altered functionality of actin cables. However, we found that point mutants of tropomyosin that suppress the actin cable defect observed in nat3Δ only partially restores wild-type growth and morphology, indicating the existence of functionally important acetylations unrelated to actin cable function. Predicted NatB substrates were dramatically overrepresented in a distinct set of biological processes, mainly related to DNA processing and cell cycle progression. Three of these proteins, Cac2p, Pac10p, and Swc7p, were identified as true NatB substrates. To identify N-terminal acetylations potentially important for protein function, we performed a large-scale comparative phenotypic analysis including nat3Δ and strains deleted for the putative NatB substrates involved in cell cycle regulation and DNA processing. By this procedure we predicted functional importance of the N-terminal acetylation for 31 proteins.

Despite a strong evolutionary pressure to reduce genome size, proteins vary in length over a surprisingly wide range also in very compact genomes. Here we investigated the evolutionary forces that act on protein size in the yeast Saccharomyces cerevisiae utilizing a system-wide bioinformatics approach. Data on yeast protein size was compared to global experimental data on protein expression, phenotypic pleiotropy, protein-protein interactions, protein evolutionary rate and biochemical classification. Comparing the experimentally determined abundance of individual proteins, highly expressed proteins were found to be consistently smaller than lowly expressed proteins, in accordance with the biosynthetic cost minimization hypothesis. Yeast proteins able to maintain a high expression level despite a large size tended to belong to a very distinct set of protein families, notably nuclear transport and translation initiation/elongation. Large proteins have significantly more protein-protein interactions than small proteins, suggesting that a requirement for multiple interaction domains may constitute a positive selective pressure for large protein size in yeast. The higher frequency of protein-protein interactions in large proteins was not accompanied by a higher phenotypic pleiotropy. Hence, the increase in interactions may not reflect an increase in function differentiation. Proteins of different sizes also evolved at similar rates. Finally, whereas the biological process involved was found to have little influence on protein size the biochemical activity exerted by the protein represented a dominant factor. More than one third of all biochemical activity classes were enriched in one or more size intervals. In yeast, there is an inverse relationship between protein size and protein expression such that highly expressed proteins tend to be of smaller size. Also, protein size is moderately affected by protein connectivity and strongly affected by biochemical activity. Phenotypic pleiotropy does not seem to affect protein size.

The rapid recent evolution of the field phenomics—the genome-wide study of gene dispensability by quantitative analysis of phenotypes—has resulted in an increasing demand for new data analysis and visualization tools. Following the introduction of a novel approach for precise, genome-wide quantification of gene dispensability in Saccharomyces cerevisiae we here announce a public resource for mining, filtering and visualizing phenotypic data—the PROPHECY database. PROPHECY is designed to allow easy and flexible access to physiologically relevant quantitative data for the growth behaviour of mutant strains in the yeast deletion collection during conditions of environmental challenges. PROPHECY is publicly accessible at http://prophecy.lundberg.gu.se.

A methodology for large‐scale automated phenotypic profiling utilizing quantitative changes in yeast growth has been tested and applied to the analysis of some commonly used laboratory strains. This yeast‐adjusted methodology is based on microcultivation in 350 µl liquid medium, where growth is frequently optically recorded, followed by automated extraction of relevant variables from obtained growth curves. We report that cultivation at this micro‐scale displayed overall growth features and protein expression pattern highly similar to growth in well aerated medium‐scale (10 ml) culture. However, differences were also encountered, mainly relating to the respiratory potential and the production of stress‐induced proteins. Quantitative phenotypic profiles for the laboratory yeast strains W303, FY1679 and CEN‐PK.2 were screened for in environmental arrays, including 98 different conditions composed of low, medium and high concentrations of 33 growth inhibitors. We introduce the concepts phenotypic index_rate and phenotypic index_stationary, which relate to changes in rate of growth and the stationary phase optical density increment, respectively, in a particular environment relative a reference strain. The laboratory strains presented selective phenotypic profiles in both phenotypic indexes and the two features appeared in many cases to be independent characteristics. We propose the utilization of this methodology in large‐scale screening of the complete collection of yeast deletion mutants. Copyright © 2002 John Wiley & Sons, Ltd.