Comprehensive phenotypic analysis for identification of genes affecting growth under ethanol stress in Saccharomyces cerevisiae

We quantified the growth behavior of all available single gene deletion strains of budding yeast under ethanol stress. Genome-wide analyses enabled the extraction of the genes and determination of the functional categories required for growth under this condition. Statistical analyses revealed that the growth of 446 deletion strains under stress induced by 8% ethanol was defective. We classified these deleted genes into known functional categories, and found that many were important for growth under ethanol stress including several categories that have not been characterized, such as peroxisome. We also performed genome-wide screening under osmotic stress and identified 329 osmotic-sensitive strains. We excluded these strains from the 446 ethanol-sensitive strains to extract the genes whose deletion caused sensitivity to ethanol-specific (359 genes), osmotic-specific (242 genes), and both stresses (87 genes). We also extracted the functional categories that are specifically important for growth under ethanol stress. The genes and functional categories identified in the analysis might provide clues to improving ethanol stress tolerance among yeast cells.     

Construction of physical map and mapping of chromosomal virulence genes of the biovar 3 Agrobacterium (Rhizobium vitis) strain K-Ag-1

Most plant pathogenic Agrobacterium strains have been classified into three biovars, "biovar 1 (A. tumefaciens; Rhizobium radiobacter), biovar 2 (A. rhizogenes; R. rhizogenes) and biovar 3 (A. vitis; R. vitis)". The bacteria possess diverse types of genomic organization depending on the biovar. Previous genomic physical maps indicated difference in location of rDNA and chromosomally-coded virulence genes between biovar 1 and 2 genomes. In order to understand biovar 3 genome and its evolution in relation to the biovar 1, 2 and 3 genomes, we constructed physical map of a pathogenic biovar 3 strain K-Ag-1 in this study. Its genome consisted of two circular chromosomes (3.6 and 1.1 Mbp in length), and three plasmids (560, 230 and 70 kbp). Gene mapping based on the physical map showed presence of two rDNA loci in the larger chromosome and at least one rDNA locus in the smaller chromosome. Six chromosomal virulence genes, namely chvA, chvD, chvE, glgP, exoC and ros were found in the larger chromosome and not in the smaller chromosome. The location of rDNA loci is similar with that of biovar 1 genome, whereas the location of chromosomal virulence genes is similar with that of biovar 2 genome despite of the closer 16S-rRNA based phylogenetic relation of biovar 3 with biovar 1 than with biovar 2. Genomic PFGE RFLP analysis revealed that the K-Ag-1 strain, which was isolated on a kiwifruit plant in Japan, has the closest intra-species relation with two strains isolated from grapevine plants in Japan among eight biovar 3 strains examined. This datum suggests that the line of the strain is a major one in biovar 3 in Japan. Evolution of the genome of the strain is discussed based on the data.     

A novel approach and protocol for discovering extremely low-abundance proteins in serum

The proteomic analysis of serum (plasma) has been a major approach to determining biomarkers essential for early disease diagnoses and drug discoveries. The determination of these biomarkers, however, is analytically challenging since the dynamic concentration range of serum proteins/peptides is extremely wide (more than 10 orders of magnitude). Thus, the reduction in sample complexity prior to proteomic analyses is essential, particularly in analyzing low-abundance protein biomarkers. Here, we demonstrate a novel approach to the proteomic analyses of human serum that uses an originally developed serum protein separation device and a sequentially linked 3-D-LC-MS/MS system. Our hollow-fiber-membrane-based serum pretreatment device can efficiently deplete high-molecular weight proteins and concentrate low-molecular weight proteins/peptides automatically within 1 h. Four independent analyses of healthy human sera pretreated using this unique device, followed by the 3-D-LC-MS/MS successfully produced 12 000-13 000 MS/MS spectra and hit around 1800 proteins (>95% reliability) and 2300 proteins (>80% reliability). We believe that the unique serum pretreatment device and proteomic analysis protocol reported here could be a powerful tool for searching physiological biomarkers by its high throughput (3.7 days per one sample analysis) and high performance of finding low abundant proteins from serum or plasma samples.     

Structure of the N-terminal domain of PEX1 AAA-ATPase. Characterization of a putative adaptor-binding domain

Peroxisomes are responsible for several pathways in primary metabolism, including beta-oxidation and lipid biosynthesis. PEX1 and PEX6 are hexameric AAA-type ATPases, both of which are indispensable in targeting over 50 peroxisomal resident proteins from the cytosol to the peroxisomes. Although the tandem AAA-ATPase domains in the central region of PEX1 and PEX6 are highly similar, the N-terminal sequences are unique. To better understand the distinct molecular function of these two proteins, we analyzed the unique N-terminal domain (NTD) of PEX1. Extensive computational analysis revealed weak similarity (<10% identity) of PEX1 NTD to the N-terminal domains of other membrane-related type II AAA-ATPases, such as VCP (p97) and NSF. We have determined the crystal structure of mouse PEX1 NTD at 2.05-A resolution, which clearly demonstrated that the domain belongs to the double-psi-barrel fold family found in the other AAA-ATPases. The N-domains of both VCP and NSF are structural neighbors of PEX1 NTD with a 2.7- and 2.1-A root mean square deviation of backbone atoms, respectively. Our findings suggest that the supradomain architecture, which is composed of a single N-terminal domain followed by tandem AAA domains, is a common feature of organellar membrane-associating AAA-ATPases. We propose that PEX1 functions as a protein unfoldase in peroxisomal biogenesis, using its N-terminal putative adaptor-binding domain.     

The polyphosphate kinase gene of Escherichia coli. Isolation and sequence of the ppk gene and membrane location of the protein.

Polyphosphate kinase (PPK) catalyzes the reversible transfer of the terminal phosphate of ATP to form a long-chain polyphosphate (polyP) (Ahn, K., and Kornberg, A. (1990) J. Biol. Chem. 265, 11734-11739). The Escherichia coli gene (ppk) encoding PPK has been cloned, sequenced, and overexpressed (about 100-fold). The gene possesses an open reading frame for 687 amino acids (mass of 80,278 Da). PPK has been purified from overproducing cells after release from attachment to the cell outer membrane; the purified soluble PPK reassociate with cell membrane fractions. About 850 molecules of PPK are found in a wild type cell.     

Interaction with IQGAP1 links APC to Rac1, Cdc42, and actin filaments during cell polarization and migration

Rho family GTPases, particularly Rac1 and Cdc42, are key regulators of cell polarization and directional migration. Adenomatous polyposis coli (APC) is also thought to play a pivotal role in polarized cell migration. We have found that IQGAP1, an effector of Rac1 and Cdc42, interacts directly with APC. IQGAP1 and APC localize interdependently to the leading edge in migrating Vero cells, and activated Rac1/Cdc42 form a ternary complex with IQGAP1 and APC. Depletion of either IQGAP1 or APC inhibits actin meshwork formation and polarized migration. Depletion of IQGAP1 or APC also disrupts localization of CLIP-170, a microtubule-stabilizing protein that interacts with IQGAP1. Taken together, these results suggest a model in which activation of Rac1 and Cdc42 in response to migration signals leads to recruitment of IQGAP1 and APC which, together with CLIP-170, form a complex that links the actin cytoskeleton and microtubule dynamics during cell polarization and directional migration.     

The Fission Yeast Minichromosome Maintenance (MCM)-binding Protein (MCM-BP), Mcb1, Regulates MCM Function during Prereplicative Complex Formation in DNA Replication

The minichromosome maintenance (MCM) complex is a replicative helicase, which is essential for chromosome DNA replication. In recent years, the identification of a novel MCM-binding protein (MCM-BP) in most eukaryotes has led to numerous studies investigating its function and its relationship to the MCM complex. However, the mechanisms by which MCM-BP functions and associates with MCM complexes are not well understood; in addition, the functional role of MCM-BP remains controversial and may vary between model organisms. The present study aims to elucidate the nature and biological function of the MCM-BP ortholog, Mcb1, in fission yeast. The Mcb1 protein continuously interacts with MCM proteins during the cell cycle in vivo and can interact with any individual MCM subunit in vitro. To understand the detailed characteristics of mcb1⁺, two temperature-sensitive mcb1 gene mutants (mcb1^ts) were isolated. Extensive genetic analysis showed that the mcb1^ts mutants were suppressed by a mcm5⁺ multicopy plasmid and displayed synthetic defects with many S-phase-related gene mutants. Moreover, cyclin-dependent kinase modulation by Cig2 repression or Rum1 overproduction suppressed the mcb1^ts mutants, suggesting the involvement of Mcb1 in pre-RC formation during DNA replication. These data are consistent with the observation that Mcm7 loading onto replication origins is reduced and S-phase progression is delayed in mcb1^ts mutants. Furthermore, the mcb1^ts mutation led to the redistribution of MCM subunits to the cytoplasm, and this redistribution was dependent on an active nuclear export system. These results strongly suggest that Mcb1 promotes efficient pre-RC formation during DNA replication by regulating the MCM complex.     

Dynamical systems analysis of arterial blood pressure signals in relation to heart rate fluctuations in chick embryos

We attempted a new approach based on a modern dynamical system theory to reconstruct the arterial blood pressure signals in relation to heart rate fluctuations of developing chick embryos. The dynamical systems approach in general is to model a phenomenon that is presented by a single time series record and approximate the dynamical property (e.g. heart rate fluctuations) of a system based only on information contained in a single-variable (arterial blood pressure) of the system. The time-series data of the arterial blood pressure was reconstructed in 3-dimensional space to draw characteristic orbits. Since the reconstructed orbits of the blood pressure should retain information contained in the pressure signals, we attempted to derive instantaneous heart rate (IHR) from the reconstructed orbits. The derived IHR presenting HR fluctuations coincided well with the IHR obtained conventionally from the peak-to-peak time intervals of the maximum blood pressure. Movements of the reconstructed orbits of the arterial blood pressure in 3-dimensional space reflected HR fluctuations (i.e. transient decelerations and accelerations).