Methylomirabilis oxyfera whole-cell extracts were separated (30 μg of protein per lane) on a 10% SDS-PAGE gel and transferred to a nitrocellulose membrane (Protran®, Germany) with a semi-dry transfer cell blotting system (Bio-Rad).

Blotting was performed Pexidartinib mw at 100 mA for 45 min with a transfer buffer containing 25 mM Tris, 192 mM glycine and 20% methanol. After blotting, the blots were air-dried and stored at 4 °C until further use. For immunoblotting, the stored blots were washed in distilled water for 30 min. Subsequently, the blots were (1) incubated in blocking buffer (1% BSA) in Tris-buffered saline (TBS; 10 mM Tris-HCL, 0.9% NaCl, pH 7.4) for 1 h; (2) incubated for 1 h in either blocking buffer or rabbit preimmune Erastin mw serum diluted 250-fold in blocking buffer (negative controls) or antiserum diluted 250-fold in blocking buffer; (3) washed tree times for 10 min in TBS containing 0.05% Tween20; (4) incubated for 1 h in monoclonal mouse α-rabbit IgG alkaline phosphatase conjugate (γ-chain specific;

Sigma, The Netherlands) diluted 1500-fold in blocking buffer; (5) washed two times for 10 min in TBS containing 0.05% Tween and three times for 10 min in TBS; and (6) incubated for 5 min in alkaline phosphatase substrate BCIP/NBT (Sigma), rinsed in distilled water and air-dried. Cells from the M. oxyfera enrichment culture were chemically fixed by immersion in 2% paraformaldehyde and 0.2% glutaraldehyde

in 0.1 M PHEM buffer (25 mM HEPES, 10 mM EGTA, 60 mM PIPES, 2 mM MgCl2, pH 6.9) for 1 h, at room temperature, followed by overnight fixation at 4 °C. Next, the samples were washed three times with 0.1 M PHEM buffer pH 6.9 and resuspended in 12% gelatin in 0.1 M PHEM buffer pH 6.9 at 37 °C. After 5 min at 37 °C, the samples were pelleted by a centrifugation step, half of the supernatant was removed, and the samples were placed on ice for 15 min. The gelatin-embedded cells were Carbohydrate cut into small cubes (1–2 mm3) under a stereo microscope, infiltrated overnight in rotating vials at 4 °C with 2.3 M sucrose in 0.1 M PHEM buffer pH 6.9 and frozen in liquid nitrogen. Cryosectioning was performed in a cryoultramicrotome (UCT/FCS or UC6/FCS; Leica Microsystems, Vienna, Austria). Ultrathin cryosections (about 70-nm) were picked up with a drop of 1% methylcellulose and 1.15 M sucrose in PHEM buffer and transferred to carbon-formvar-coated grids (copper, hexagonal 100-mesh) for immunogold localization. For single labelling, grids containing ultrathin sections of M.

Correlating pathogen prevalence in food surveillance to the risk of disease acquisition is difficult, and this study is unable to make definitive conclusions about human disease acquisition risk. A major hamper to drawing a definitive conclusion is that the pathogenicity of Arcobacter Fluorouracil mouse is still being elucidated. Arcobacter is a recently reclassified genera from the family Campylobacteracea, first identified in 1992. Arcobacter spp. differ from Campylobacter spp. by their ability to grow at lower temperatures and in air. Of the six Arcobacter spp., A butzleri has predominantly been

associated with human enteritis. The major focus of human acquisition risk is on raw meat products, specifically chicken.32,33 In 2000, Morita and colleagues34 identified A butzleri in 100% of retail chicken and canal water samples in Bangkok. Arcobacter as a human pathogen has not

been identified in TD etiology studies but has been described in five case series/case reports: two bacteremia cases in patients with underlying disease in Taiwan and Hong Kong, an outbreak among 10 patients in Italy, bacteremia in a newborn in the UK, and two cases of severe diarrhea in Germany.35–39 Taylor and colleagues40 isolated Campylobacter butzleri (now known as A butzleri) in 3% of 631 diarrheal stool samples collected from Thai children in 1991. Samie and colleagues41 compared the prevalence of A butzleri in 322 stool samples from patients with and without diarrhea in South Africa, and Protein Tyrosine Kinase inhibitor 70% of the 20 A butzleri isolates found were associated with diarrhea but the p value was not significant at 0.198. The most compelling evidence comes from Vendenberg and colleagues who compared the prevalence of Campylobacter and Arcobacter among 67,599 stool specimens (12,413 solid stools

and 55,186 diarrheal stools). Arcobacter butzleri was more frequently isolated in diarrheic stool [odds ratio (OR) 2.48, 95% confidence interval (CI) 1.10–5.86, p = 0.0175]. Clinical course was also compared, and A butzleri was more frequently associated with a persistent and watery diarrhea and less associated with bloody diarrhea.42 Because Arcobacter spp. prevalence is not routinely assessed and there is a lack of standard isolation methods, the true occurrence of this emerging pathogen is largely unknown. Arcobacter may be misclassified as Campylobacter Thiamet G in many studies due to their microbiologic similarities.32,33,40 This severely limits the ability to compare field data, and may partially explain why Campylobacter spp. was not identified in this study (ie, the Arcobacter isolated would have been misclassified as Campylobacter spp. if Arcobacter was not specifically assessed via the oxygen tolerance test which was not utilized in the previous Thailand TD etiology studies). The scientific community agrees current evidence points to Arcobacter spp. being pathogenic in humans, but further research is required to make conclusive assessments.

cerevisiae (Pagliuca et al., 2009). However, Spc7/Spc105 forms complex with Sos7, which has been identified recently as a KT protein in fission yeast S. pombe (Jakopec et al., 2012). Spc7 and Sos7 are interdependent for their KT localization (Jakopec et al., 2012). Both the proteins are dependent on Mis12 for their loading at the KT (Kerres et al., 2007; Jakopec et al., 2012). The Dam1 complex is essential for cell viability and localized at the KT throughout cell cycle in both budding yeasts, S. cerevisiae (Hofmann et al., 1998; Cheeseman et al., 2001a, b; Enquist-Newman et al., 2001) and C. albicans (Burrack et al., 2011;

Thakur & Sanyal, 2011). CENP-A influences the KT recruitment of this complex in both the budding yeasts (Collins et al., 2005; Burrack et al., 2011). In contrast to budding yeasts, the Dam1 complex Z-VAD-FMK mouse is nonessential for cell viability in fission selleck kinase inhibitor yeast S. pombe. Moreover, except Dad1, other subunits of this complex localize at the KT only during mitosis in S. pombe (Liu et al., 2005; Sanchez-Perez et al., 2005). The recruitment of

the Dam1 complex is affected by Ndc10, Mis12 and Ndc80 in S. cerevisiae (He et al., 2001; Li et al., 2002; Scharfenberger et al., 2003; Collins et al., 2005; Pagliuca et al., 2009), whereas localization of the Dam1 complex is controlled by the Mis6 complex proteins in S. pombe (Liu et al., 2005; Sanchez-Perez et al., 2005). In this review, we compared the process and sequence of events during KT assembly in three different PAK5 ascomycetous yeasts, each carrying a specific type of CEN. While similarities and differences in KT assembly in these organisms are evident, some key questions need to be experimentally addressed. Ndc10 is the key determinant in KT assembly in S. cerevisiae. Is there a functional homolog of Ndc10 in organisms (such as C. albicans and S. pombe) possessing sequence-independent regional CENs? The requirement of Scm3 for loading of CENP-A is found to be similar in S. cerevisiae and S. pombe but not yet studied in C. albicans. The localization dependence between Ndc80

and CENP-A has been examined in S. cerevisiae and C. albicans but not in S. pombe. The roles of an inner KT protein Mis6/Ctf3 and a middle KT protein Spc105/Spc7 in KT assembly have been studied in S. cerevisiae and S. pombe. The identification and characterization of the functional homologs of these proteins in C. albicans will improve our knowledge of KT assembly in this yeast. The requirement of the Dam1 complex for assembly of a KT also differs between two budding yeasts, S. cerevisiae and C. albicans. The Dam1 complex requires components of inner and middle KT for its KT localization in S. cerevisiae but not vice versa. In contrast, depletion of the Dam1 complex results in the disruption of KT architecture and destabilization of CENP-A in C. albicans (Thakur & Sanyal, 2012).

On the other hand, the association of Pdc2p with PDC5 was unaffected by thiamin. We also identified a DNA element in the upstream region of PDC5, which can bind to Pdc2p and is required for the expression of PDC5. The yeast Saccharomyces cerevisiae is able to synthesize thiamin pyrophosphate (TPP) de novo. In addition, it can efficiently http://www.selleckchem.com/products/dorsomorphin-2hcl.html utilize thiamin from the extracellular

environment to produce TPP. The expression of genes involved in the synthesis of TPP and in the utilization of extracellular thiamin (THI genes) is coordinated when the supply of thiamin is limited, a mechanism called the yeast THI regulatory system (Hohmann & Meacock, 1998; Nosaka, 2006; Kowalska & Kozik, 2007). This control occurs at the transcriptional level, and TPP serves as an intracellular negative signal. Conversely, three positive regulatory factors, Thi2p, Thi3p, and Pdc2p, have been identified. Thi2p has a Zn2-Cys6 DNA-binding motif of the N-terminus in common with several yeast transcriptional activators (Titz et al., 2006). The C-terminal part of Thi2p is rich in acidic amino acids. Harbison et al. (2004) identified the elements of S. cerevisiae

bound by transcriptional regulators, including Thi2p, using genome-wide chromatin immunoprecipitation technology. Several DNA sequences immunoprecipitated with an antibody specific for Thi2p were found upstream of the putative check details TATA box of THI genes, and one of these elements in PHO3, a THI gene which encodes a periplasmic acid phosphatase with high affinity for thiamin phosphates, had been demonstrated to be required for the induction in response to thiamin starvation

(Nosaka et al., 1992). Thi3p is a TPP-binding protein whose sequence is about 50% identical to that of yeast pyruvate decarboxylase isozymes (Pdc1p, Pdc5p, and Pdc6p). As THI genes are expressed even under thiamin-replete conditions when the TPP-binding site of Thi3p OSBPL9 is disrupted, Thi3p seems to act as a TPP sensor to exert transcriptional control (Nosaka et al., 2005). Pdc2p possesses putative DNA-binding domains similar to centromere binding protein B (Tanaka et al., 2001) and DDE superfamily endonuclease (Venclovas & Siksnys, 1995) at the N-terminus. The PDC2 gene is necessary for the expression of not only THI genes but also pyruvate decarboxylase structural genes (Hohmann, 1993). Thus, Pdc2p participates in the transcriptional regulation of TPP-synthesizing enzymes and TPP-dependent enzymes. The expression of PDC5 is also induced in response to thiamin starvation, whereas PDC1 is expressed abundantly in a thiamin-independent fashion (Muller et al., 1999). It is intriguing that Thi3p is not involved in the regulation of PDC5 in spite of being related to the intracellular level of TPP (Nosaka et al., 2005). We have previously demonstrated that Thi3p associates with Pdc2p directly, and to a lesser extent with Thi2p, and that these interactions are partially disturbed by TPP (Nosaka et al., 2008).

Here, we describe protozoan features that affect their DZNeP molecular weight ability to grow on secondary-metabolite-producing bacteria, and examine whether different bacterial secondary metabolites affect protozoa similarly. We investigated the growth of nine different soil protozoa on six different Pseudomonas strains, including the four secondary-metabolite-producing Pseudomonas fluorescens DR54 and CHA0, Pseudomonas chlororaphis MA342 and Pseudomonas sp. DSS73, as well as the two nonproducers P. fluorescens DSM50090T and P. chlororaphis ATCC43928. Secondary metabolite producers affected protozoan growth

differently. In particular, bacteria with extracellular secondary metabolites seemed more inhibiting than bacteria with membrane-bound metabolites. Interestingly, protozoan response seemed to correlate with high-level protozoan taxonomy, and amoeboid taxa tolerated a broader range of Pseudomonas strains than did the non-amoeboid

taxa. This stresses the importance of studying both protozoan and bacterial characteristics in order to understand bacterial defence mechanisms and potentially improve survival of bacteria introduced into the environment, for example for biocontrol purposes. Protozoan grazing increases bacterial turnover of organic matter and reduces bacterial biomass (Rønn et al., 2002; Bonkowski, 2004; Christensen et al., 2006). Furthermore, particular Dasatinib supplier protozoa consume different bacteria to different extents (Rønn et al., 2001, 2002; Mohapatra & Fukami, 2004; Pickup et al., 2007). Factors that presumably affect bacterial susceptibility to grazing include cell size, speed of movement, extent of biofilm production, and the composition of the bacterial envelope (Matz & Kjelleberg, 2005). Bacteria that produce secondary metabolites may likewise be less suitable as protozoan food (Rønn et al., Resminostat 2001; Andersen & Winding, 2004; Matz et al., 2004; Jousset et al., 2006; Pedersen et al., 2009). The genus

Pseudomonas is interesting in this context as it includes strains that produce a wide range of secondary metabolites (Haas & Défago, 2005). Protozoa can discriminate between different food items (e.g. Jürgens & DeMott, 1995; Boenigk et al., 2001; Jezbera et al., 2006; Pedersen et al., 2009) and therefore only ingest some bacterial strains. Hence, protozoa graze different taxonomic groups of bacteria differently (Matz et al., 2004). Still, we know only little about how protozoan features correlate with which bacteria they can ingest and hence digest. Here, we focus on protozoan characteristics; thus, we hypothesize that protozoan taxonomic affiliation (Adl et al., 2007) can be used to predict which bacteria they can subsist on, depending upon the bacterial production of secondary metabolites. Thus, we hope to find protozoan characteristics that correlate with their ability to grow on specific bacteria.

When grown in different media, this is mentioned. In all find more experiments, the strains were cultured from stocks kept at −80 °C. Double knockout mutants in mutM and mutY were constructed using the Cre-lox system for gene deletion and antibiotic resistance marker recycling. Combined sacB-based negative selection and

cre-lox antibiotic marker recycling for efficient gene deletion in P. aeruginosa were used (Quenee et al., 2005). Upstream and downstream PCR fragments (Primers listed in Table S1) of the wild-type mutM or mutY gene from P. aeruginosa strain PAO1 were digested with HindIII and either BamHI or EcoRI, and cloned by a three way ligation into pEX100Tlink deleted for the HindIII site and opened by EcoRI and BamHI. Eighty-four residues from position 268 were deleted, when the upstream and downstream mutM amplified fragments were joined in pEX100Tlink vector, and 76 residues from position 374 were deleted in mutY, respectively. The resulting plasmids (pEXTMM and pEXTMY) were transformed into E. coli XL1Blue strain, and transformants were ZD1839 in vitro selected in 30 mg L−1 ampicillin LB agar plates. The lox flanked gentamicin resistance cassette (aac1) obtained by HindIII restriction of plasmid pUCGmlox was cloned into the HindIII sites in pEXTMM and pEXTMY

formed by the ligation of the upstream and downstream PCR fragments. The resulting plasmids were transformed into E. coli XL1Blue strain, and transformants were selected on 30 mg L−1 ampicillin–5 mg L−1 gentamicin LB agar plates. The resulting plasmids (pEXTMMGm and pEXTMYgm) Flavopiridol (Alvocidib) were then transformed into the E. coli S17-1 helper strain. Single knockout mutants were generated by conjugation, followed by selection of double recombinants using 5% sucrose-1 mg L−1 cefotaxime-30 mg L−1 gentamicin LB agar plates. Double recombinants were checked by screening for ticarcillin (100 mg L−1)

susceptibility and afterwards by PCR amplification and sequencing. For the recycling of the gentamicin resistance cassettes, plasmid pCM157 was electroporated into different mutants. Transformants were selected in 250 mg L−1 tetracycline LB agar plates. One transformant for each mutant was grown overnight in 250 mg L−1 tetracycline LB broth to allow the expression of the cre recombinase. Plasmid pCM157 was then cured from the strains by successive passages on LB broth. Selected colonies were then screened for tetracycline (250 mg L−1) and gentamicin (30 mg L−1) susceptibility and checked by PCR amplification. The single knockout mutants obtained were named PAOMMgm and PAOMYgm. To obtain the double mutant, the conjugation experiments with pEXMMGm using PAOMY as recipients were performed as described above. MutY-mutM double mutant was named PAOMY-Mgm. The maximum growth rate was found to be the same for PAOMY-Mgm and PAO1 in LB (Philipsen et al., 2008).

For DXA, both Lunar (General Electric Company, Brussels, Belgium) and Hologic (Hologic Inc., Bedford, MA, USA) equipment was utilized. Calibration procedures selleck kinase inhibitor and quality control checks were performed daily. A special phantom was made available to each of the sites before study initiation to calibrate the DXA equipment for the assessment of lean and fat mass, in order to allow accurate centralized analysis of the data. Given that CT and DXA scanning had not been part of the SSAR 2004/0002 protocol, participants in that protocol were excluded from all body composition analyses. Glomerular filtration rate (GFR) was estimated using various equations: Cockcroft and Gault (C&G) [26], Modification of Diet

in Renal Disease (MDRD) formulas [27], the Cystatin C (CysC) equation [28] and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) estimate [29]. Patients from the SSAR 2004/0002 study

were excluded from the analyses of the estimated GFR (eGFR) estimated using the CysC and MDRD-6 equations, as cystatin C and urea levels were not available. Plasma HIV-1 RNA (lower limit of quantification this website 50 HIV-1 RNA copies/mL), CD4 T-cell count, routine haematology and chemistry were monitored at all visits. The latest version (version 1, December 2004) Adult Clinical Trials Group (ACTG) table for grading the severity of adverse events was used for the reporting of adverse events. The primary objective of this trial was to demonstrate noninferiority of an SQV/r-based regimen compared with an ATV/r-based regimen with respect to mean changes in TC. The sample size was calculated using results from the AI424-008 trial in which mean TC increased from 169 to 177 mg/dL Ribose-5-phosphate isomerase (with the standard deviation of the mean difference being 37.1) after 48 weeks of treatment [4]. Noninferiority is demonstrated when the upper limit of the 95% confidence interval of the difference between study arms is <10%. Setting alpha at 5%, a sample size of 60 subjects per study arm results in a power of more than 80% to

demonstrate noninferiority, assuming a true difference in TC between arms of 0%. The patient population used in the analyses included all randomized patients who received at least one dose of study medication. All analyses were performed on the intent-to-treat (ITT) population. For the ITT analysis, all missing values of the outcome measurements (other than the week 12 lipids in the SSAR 2004/0002 study) were imputed using a last observation carried forward (LOCF) approach. In addition, an on-treatment (OT) analysis was performed for blood lipids, glucose metabolism, body composition, virological and immunological responses. In the OT analysis, data from patients who prematurely discontinued study medication were censored at the time of study drug discontinuation, and no LOCF imputation was used. Changes in metabolic and renal parameters were assessed using linear mixed models incorporating repeated measurements.

Alexander’s Law (AL) states that slow-phase velocity Selleckchem Birinapant of SN is higher when looking in the direction of fast-phases of nystagmus and lower in the slow-phase direction. Earlier explanations for AL predict that during SN, slow-phase eye velocity is a linear function of eye position, increasing linearly as eye deviates towards the fast-phase direction. Recent observations, however, show that this is often not the case; eye velocity does not vary linearly with eye position. Such new findings necessitate a re-evaluation of our understanding of AL. As AL

may be an adaptive response of the vestibular system to peripheral lesions, understanding its mechanism could shed light on early adaptation strategies of the brain. Here, we propose a physiologically plausible mechanism for AL that explains recent experimental data. We use a dynamic control system model to simulate this mechanism and make testable predictions. This mechanism is based on the known effects of unilateral vestibular deficit on the response of the ipsi- and contralesional

vestibular nuclei (VN) of the brainstem. This hypothesis is based on the silencing of the majority of ipsilesional VN units, which creates an asymmetry between the responses of the ipsi- learn more and contralesional VN. Unlike former explanations, the new hypothesis does not rely on lesion detection strategies or signals originating in higher brain structures. The proposed model demonstrates possible consequences of acute peripheral deficits for the function of the velocity-to-position neural integrator of the ocular motor system and the vestibulo-ocular reflex. “
“Increasing evidence supports the involvement of inflammatory and immune processes in temporal lobe epilepsy (TLE). MicroRNAs (miRNA) represent small regulatory RNA molecules that have been shown to act as negative regulators of gene expression controlling different biological processes, including immune-system

homeostasis and function. We investigated the expression and cellular distribution of miRNA-146a (miR-146a) click here in a rat model of TLE as well as in human TLE. miR-146a analysis in rat hippocampus was performed by polymerase chain reaction and immunocytochemistry at 1 week and 3–4 months after induction of status epilepticus (SE). Prominent upregulation of miR-146a activation was evident at 1 week after SE and persisted in the chronic phase. The miR-146a expression was confirmed to be present in reactive astrocytes. In human TLE with hippocampal sclerosis, increased astroglial expression of miR-146a was observed mainly in regions where neuronal cell loss and reactive gliosis occurred. The increased and persistent expression of miR-146a in reactive astrocytes supports the possible involvement of miRNAs in the modulation of the astroglial inflammatory response occurring in TLE and provides a target for future studies aimed at developing strategies against pro-epileptogenic inflammatory signalling.

Three E. coli strains DH5α, Jm107 and BL21 (DE3) and three plasmids pGEM-T, pET-28a and pCAMBIA

with different sizes (3000, 5369 and 8428 bp, respectively) were Olaparib datasheet used to test the protocol. The results indicated a significant increase in number of transformed colonies compared with heat-shock method. Our findings also demonstrated the favourable impacts of glycerol on transformation of E. coli. “
“A novel thermophilic, anaerobic, keratinolytic bacterium designated KD-1 was isolated from grassy marshland. Strain KD-1 was a spore-forming rod with a Gram-positive type cell wall, but stained Gram-negative. The temperature, pH, and NaCl concentration range necessary for growth was 30–65 °C (optimum 55 °C), 6.0–10.5 (optimum 8.0–8.5), and 0–6% (optimum 0.2%) (w/v), respectively. Strain KD-1 possessed extracellular keratinase, and the optimum activity of the crude enzyme was pH 8.5 and 70 °C. The enzyme was identified as a thermostable serine-type protease. The strain was sensitive to rifampin, hypoxia-inducible factor pathway chloramphenicol, kanamycin, and tetracycline and was resistant to erythromycin, neomycin, penicillin, and streptomycin. The main cellular fatty acid was predominantly C15:0 iso (64%), and the G+C content was 28 mol%. Morphological and physiological characterization, together with phylogenetic analysis based

on 16S rRNA gene sequencing identified KD-1 as a new species of a novel genus of Clostridiaceae with 95.3%, 93.8% 16S rRNA gene sequence similarity to Clostridium ultunense BST (DSM 10521T) and Tepidimicrobium xylanilyticum PML14T (= JCM 15035T), respectively. We propose the name Keratinibaculum paraultunense gen. nov., sp. nov., with KD-1 (=JCM 18769T =DSM 26752T) as the type strain. “
“The

freshwater cyanobacterium Synechococcus elongatus PCC 7942 exhibits light-dependent growth. Although it has been reported that DNA replication also depends on light irradiation in S. elongatus 7942, the involvement of the light in the regulation of DNA replication remains unclear. IMP dehydrogenase To elucidate the regulatory pathway of DNA replication by light, we studied the effect of several inhibitors, including two electron transport inhibitors, 3-(3,4-dichlorophenyl)-1,1-dimethylurea (DCMU) and 2,5-dibromo-3-methyl-6-isopropyl-p-benzoquinone (DBMIB), on DNA replication in S. elongatus 7942. DCMU inhibited only DNA replication initiation, whereas DBMIB blocked both the initiation and progression of DNA replication. These results suggest that DNA replication depends on the photosynthetic electron transport activity and initiation and progression of DNA replication are regulated in different ways. “
“Most glycolipid antigens used for serological tests of Mycoplasma pneumoniae are not M. pneumonia-specific, and can cross-react with other microorganism antigens and body tissues, resulting in false positives. It is important to identify M. pneumonia-specific antigen(s) for serological testing and correct diagnosis.

When the σS levels in pgsA3ΔcpxA and pgsA3ΔcpxR double mutants were examined, the high level of σS in pgsA3 mutant cells was found to be considerably reduced (Fig. 2d), indicating that the activation of the Cpx system is one important cause for the high level of σS. In order to clarify how the system affects σS, we examined the activities of clpP′-lacZ and clpX′-lacZ in the double mutants. The activities of these transcriptional fusions recovered after disruption of the Cpx system from the very low levels in pgsA3 Apitolisib mutant cells as expected, although not completely (Fig. 2b). These results indicate that the activated Cpx system increases

σS levels by contributing to the repression of clpPX in pgsA3 mutant cells. Does the FK866 purchase Cpx system repress clpPX through rpoE, rpoH, and rpoD, and to what extent does it control their levels? Microarray analyses suggested that in pgsA mutant cells, the expressions of rpoE and rpoH genes and the genes under the control of σE and σH are reduced, but the level of σD is not (Nagahama et al., 2007). In fact, real-time PCR analysis of the mRNA levels of these sigma factors indicated that the mRNAs of rpoE and rpoH in pgsA3 mutant cells were reduced to 1/40 and 1/18 of those in pgsA+ cells,

respectively, whereas the mRNA level of rpoD was almost the same as in wild-type cells, supporting the results of the microarray analyses (Fig. 4). Further examination of the mRNA levels in ΔcpxR pgsA double mutant cells indicated that the low level of rpoE mRNA recovered to 1/10, but that rpoH mRNA was not much changed (to 1/14) (Fig. 4). These results indicate that the repression of rpoE in the NADPH-cytochrome-c2 reductase pgsA3 mutant cells can be partly attributed to the activated Cpx system (see Fig. 5). There must be an unknown component in the repression of rpoE, independent of the Cpx system. The results also imply that the repression of rpoH is independent of the

Cpx system. The transcription of clpPX from the σD promoter may also be repressed in the presence of increased σS, which probably contributes to the repression by competing with σD for RNA polymerase core enzyme, because σS has a high affinity for the core enzyme (Maeda et al., 2000). To elucidate the intriguing roles that these sigma factors play in the repression of clpPX in pgsA mutant cells, further analysis of the cellular levels of the sigma factors and of each promoter of clpPX will be required. Figure 5 summarizes our ideas about the regulatory pathways that lead to σS accumulation in pgsA mutant cells. In order to fully understand the molecular mechanism of the accumulation of σS in pgsA mutant cells, detailed examination of the signal transduction systems that respond to acidic phospholipid deficiency will also be necessary. We thank Drs Robert Simons, Michele Garsha, Christophe Merlin, Kouji Busujima, Koichi Inoue, and Hiroshi Matsuzaki for the gifts of bacterial strains and suggestions, and Dr Kan Tanaka for the antiserum against σS.