[http://​www.​repeatmasker.​org] 53. House CH, Runnegar B, Fitz-Gibbon ST: Geobiological analysis using whole genome-based tree building applied to the bacteria, archaea, and eukarya. Geobiology 2003, 1:15–26.CrossRef 54. Huse SM, Huber JA, Morrison HG, Sogin ML, Welch DM: Accuracy and quality of massively parallel DNA pyrosequencing. Genome find more Biol 2007,8(7):R143.PubMedCrossRef 55. Kunin V, Engelbrektson A, Ochman H, Hugenholtz P: Wrinkles in the rare biosphere: pyrosequencing

errors can lead to artificial inflation of diversity estimates. Environ Microbiol 2010,12(1):118–123.PubMedCrossRef 56. Niu B, Fu L, Sun S, Li W: Artificial and natural duplicates in pyrosequencing reads of metagenomic data. BMC Bioinforma 2010,11(1):187.CrossRef 57. Gilbert MTP, Binladen J, Miller W, Wiuf C, Willerslev E, Poinar H, Carlson JE, Leebens-Mack JH, Schuster SC: Recharacterization of ancient DNA miscoding lesions: insights in the era of sequencing-by-synthesis. Nucleic Acids LEE011 Res 2007,35(1):1–10.PubMedCrossRef 58. Quince C, Lanzen A, Davenport RJ, Turnbaugh PJ: Removing noise from pyrosequenced amplicons. BMC Bioinforma 2011, 12:38.CrossRef 59. Kitts CL: Terminal restriction fragment patterns: a tool for comparing microbial communities and assessing community dynamics. Curr Issues Intest Microbiol 2001,2(1):17–25.PubMed 60. Bukovska P, Jelinkova M, Hrselova H, Sykorova Z, Gryndler M: Terminal restriction fragment length measurement errors are affected mainly

by fragment length, G plus C nucleotide content and secondary structure melting point. J Microbiol Methods 2010,82(3):223–228.PubMedCrossRef 61. Kaplan CW, Kitts CL: Variation between observed and true terminal restriction fragment length is dependent on true TRF

length and purine content. J Microbiol Methods 2003,54(1):121–125.PubMedCrossRef 62. Osborn AM, Moore ERB, Timmis KN: An evaluation of terminal-restriction fragment length polymorphism (T-RFLP) analysis for the study of microbial community structure and dynamics. Environ Microbiol 2000,2(1):39–50.PubMedCrossRef 63. Clement BG, Kehl LE, DeBord KL, Kitts CL: Terminal restriction fragment patterns (TRFPs), a rapid, PCR-based method for the comparison of complex bacterial communities. J Microbiol Methods 1998,31(3):135–142.CrossRef 64. Egert M, Friedrich MW: Formation of pseudo-terminal GSK-3 inhibitor restriction fragments, a PCR-related bias affecting terminal restriction fragment length polymorphism analysis of microbial community structure. Appl Environ Microbiol 2003,69(5):2555–2562.PubMedCrossRef 65. Pilloni G, von Netzer F, Engel M, Lueders T: Electron acceptor-dependent identification of key anaerobic toluene degraders at a tar-oil-contaminated aquifer by pyro-SIP. FEMS Microbiol Ecol 2011,78(1):165–175.PubMedCrossRef 66. Meyer F, Paarmann D, D′Souza M, Olson R, Glass EM, Kubal M, Paczian T, Rodriguez A, Stevens R, Wilke A, et al.: The metagenomics RAST server – a public resource for the automatic phylogenetic and functional analysis of metagenomes.

ShRNA inhibit gene expression of HBV strains with different genotypes in vitro The levels of cytoplasmic HBV pg/pc RNA (3.5 kb) and HBV DNA in cultured supernatants were

determined by realtime RT-PCR/PCR and presented in Figure 3. The pg/pc RNA level of five HBV strains with different genotypes were reduced by 58%~93% in B245(69%~93%), B376(59%~91%), B1581(67%~90%) and B1789(58%~88%) treatments, while the HBV DNA level observed in supernatants was decreased by 77%~99% in these shRNA plasmid treatments (B245: 83%~99%, B376: 79%~99%, B1581:88%~98%, B1789: 77%~99%). Figure 3 SiRNAs inhibit RNA and DNA expression of HBV strains with different genotypes in Huh7 cells. The histogram show the cytoplasmic HBV pg/pc RNA levels (A, B, C, D, E) and extracellular Obeticholic Acid manufacturer HBV DNA (F, G, H, I, J) of five HBV strains with genotypes Ae(N10), Ba(C4371), C1(Y1021), D1(Y10) and I1(W29) in treated shRNA plasmids, treated pSUPER vector, and non-treated Huh7 cells. In addition, the extracellular and intracellular antigen levels in Huh7 cells that were co-transfected with HBV and shRNA plasmids were also determined (Figure 4). In the shRNA-treated Huh7 cells, the average extracellular HBsAg expression level of all five HBV strains decreased by 1.66 ± 0.36 logs. The average intracellular HBsAg expression level decreased by 1.47 ± 0.33 logs, while the extracellular HBeAg levels decreased by 1.04 ± 0.23 logs, and the intracellular HBcAg levels by 1.71 ±

0.49 logs. The effect of the siRNA treatment on HBeAg levels was weaker than that on the HBsAg or HBcAg levels (P < 0.001, Figure 5). RO4929097 Figure 4 SiRNAs inhibit viral antigens expression of HBV strains with different genotypes in Huh7 cells. (A, B, C, D) Extracellular HBsAg, intracellular HBsAg, extracellular HBeAg, and intracellular HBcAg expression levels of HBV N10(Ae), respectively. (E, F, G, H) Extracellular HBsAg, intracellular

HBsAg, extracellular HBeAg, and intracellular HBcAg expression 3-mercaptopyruvate sulfurtransferase levels of HBV C4371(Ba), respectively. (I, J, K, L) Extracellular HBsAg, intracellular HBsAg, extracellular HBeAg, and intracellular HBcAg expression levels of HBV Y1021(C1), respectively. (M, N, O, P) Extracellular HBsAg, intracellular HBsAg, extracellular HBeAg, and intracellular HBcAg expression levels of HBV Y10(D1), respectively. (Q, R, S, T) Extracellular HBsAg, intracellular HBsAg, extracellular HBeAg and intracellular HBcAg expression levels of HBV W29(I1), respectively. Figure 5 Comparing the RNAi-induced silencing effect on different viral markers. Data were displayed the average antigen level of the 4 siRNAs reduced for five HBV strains. “”Ex”" = Extracellular and “”In”" = Intracellular. The Mann-Whitney test was used to assess the difference. An asterisk represents a statistical difference of P < 0.01 in comparison with the other markers (Ex HBeAg vs. Others P < 0.001, Ex HBsAg vs. In HBsAg P = 0.05, Ex HBsAg vs. In HBcAg P = 0.82, In HBsAg vs. In HBcAg P = 0.10.

2% of the SW collection); poultry strains predominate in PG #302 (N = 84 i.e. 63.1% of

the P collection), LY2835219 molecular weight while all quinolone-sensitive mammal strains were assigned to PG #301A (N = 33 i.e. 71.7% of the DM collection). The seven strains harboring a “C. jejuni-like allele” all originate from poultry (Table 2). Genotype diversity within the C. jejuni collection All the strains from this study were further characterized by MLST. For the C. jejuni isolates, a total of 170 different STs were identified. Combining MLST with gyrA yielded 191 distinct genotypes. The Simpson’s Index of Diversity (SID) was 0.911 (95% confidence intervals (CI) 0.899–0.923) for gyrA alleles only, 0.979 (95% CI 0.974–0.984) for MLST only and 0.984 (95% CI 0.979-0.988) for the combination of MLST and gyrA. The indexes of association IA calculated for each source using a single representative of each genotype,

appeared low and fairly similar, suggesting that each of these populations was highly diverse by recombining to some degree: 0.22 (SW), 0.28 (DM) and 0.19 (P). Population differentiation estimated by the F ST values was highest between SW and DM (0.07787, P <0.00001), followed by DM and P (0.04074, Poziotinib P <0.00001) and lowest for SW and P (0.03476, P <0.00001). Nearly half of the strains from the DM set (43.4%), 18.9% of the SW set and 23.2% of the P set had genotypes identified in all three sources (Figure 3A). In the same way, 60.2%, 22.2% and 52.8% of the strains had genotypes specific to SW, DM and P origins, respectively. Finally, 14.6% and 6.3% of the environmental (SW) collection had genotypes common to DM and P sets, respectively. Genotypes not recovered from SW and common to both animal sets represented 15.1% and 10.4% of the DM

and P collections, respectively. Figure 3 Distribution of genotypes (ST +  gyrA ) by source. (A) C. jejuni collection, (B) C. coli collection. SW = Surface waters, DM = Domesticated Mammals, P = Poultry. Genotype diversity within the C. coli collection Among the C. coli isolates, a total of 146 STs were identified and yielded 194 distinct genotypes when combined with the gyrA locus. The SID value for the combined methods was of 0.994 (0.992 – 0.996) versus 0.987 (0.984 – 0.991) for MLST alone or 0.945 (0.936 – 0.953) for the gyrA Farnesyltransferase data alone. The IA determined from the SW collection had a value similar to those previously calculated from the C. jejuni sets (0.26). In contrast, the IA values from each of the animal population displayed a trend closer to zero indicating a random association between alleles of the 8 loci (i.e. in proximity to linkage equilibrium) by freely recombining (IA for DM = 0.03 and IA for P = 0.05). The population pairwise F STs approach generated 3 similar values for each pair combination: SW/DM (0.16295, P <0.00001); SW/P (0.16455, P <0.00001) and DM/P (0.

Similarly in E. coli, stationary phase induced thermotolerance has been shown to depend upon the rpoS regulated expression of the otsAB genes for trehalose synthesis, but the levels of trehalose synthesized on entry into stationary phase were very LEE011 molecular weight much lower than in osmotically stressed cells [26]. There is now a large body of evidence

showing that the mechanisms for trehalose-mediated protection against heat and desiccation stress are different from those involved in osmoprotection, i.e., as a counteracting osmolyte. Thus, studies in vitro have shown that trehalose preserves structure and function in biomolecules and molecular assemblages, such as membranes, during drying and heat stress [63]. Strains of R. leguminosarum bv trifolii[7] and R. etli (this work) deficient in trehalose synthesis are more sensitive to the effects of drying, and show impaired survival upon storage. Thus, desiccation tolerance in R. etli cells was dependent of high trehalose production by osmotic pre-conditioned cells. Indeed, desiccation stress is much more harmful than heat stress for microorganisms, as it produces the accumulation of salt and solutes, hyperosmotic stress, metabolism impairment, and damage to macromolecules MK-2206 chemical structure upon removing the aqueous monolayer [64]. This may explain why high trehalose content is necessary for survival of R. etli cells to drying, in order

to cope with so many stresses. In agreement with this, E. coli[65], S. meliloti[55], and desert-isolated rhizobial strains nodulating acacia [56] that were osmotically induced to accumulate trehalose (and also mannosucrose, in desert-isolated rhizobia), showed increased tolerance to drying and storage. Interestingly, transcriptomic analyses revealed that desiccation stress per se, if performed under controlled conditions, also induced trehalose synthesis by B. japonicum[24], the soil actinomycete Rhodococcus jostii[66] and the yeast Saccharomyces cerevisiae[67]. It

is worth mentioning that desiccation tolerance by R. etli was not improved by an increase in drying temperature. This lack of correlation has been also found in many other rhizobia [64] and could be attributed, at least in R. etli, to the low induction of trehalose synthesis under high temperature. On Oxymatrine the other hand, the survival rate of R. etli wild type strain after the vacuum-drying treatments was below 40%, and rapidly decreased after 4 days storage (see Figure 6). This differs from the high survival rates found for S. meliloti on nitrocellulose filters [55] or R. leguminosarum bv trifolii on glass beads [7]. Rather than intrinsic tolerance to desiccation, we suggest that these differences may be related to the experimental conditions used for drying. In rhizobia, the relationship between inactivation of a given trehalose metabolic pathway (and the resulting trehalose accumulation) and the observed symbiotic performance, seems to vary among species (see Introduction). The R.

Table 2 Biochemical properties of the three enzymes Enzyme Temperature range(°C) Optimal temperature Thermal Stability① pH range Optimal pH Acid stability② Alkali Stability③ Specific activity Epigenetics Compound Library PdcDE 20-70 40°C 35% 3.0-10.0 6.0 20% 60% ND④ PdcG 20-70 50°C 65% 5.0-10.0 8.0 18% 75% 0.44 U/mg PdcF 20-70 40°C 10% 5.0-9.0 7.0 20% 58% 446.97 U/mg ①Relative activity of purified protein when it was treated in 60°C for 20 min; ②Relative activity of purified protein when it was treated in pH 3.0 for 30 min; ③Relative activity of purified protein when it was treated in pH 10.0 for 30 min; ④Not detectedEach value

represents the mean of at least three independent replicates. Autophagy Compound Library Table 3 Effect of various metal ions and chemical agent on the activity of the three enzymes Metal ion or chemical agent (5 mM)   Relative activity (%)     PdcDE PdcG PdcF No addition 100 100 100 K + (KCl) 113.04 ± 10.80 95.79 ± 16.49 129.00 ± 27.32 Na + (NaCl) 113.42 ± 2.27 88.22 ± 17.76 123.91 ± 25.82 Ba 2+ (BaCl 2 ) 99.19 ± 6.29 123.34 ± 7.79 129.02 ± 6.46 Mg 2+ (MgCl 2 ) 95.41 ± 5.96 138.06 ± 8.46 129.79 ± 18.11 Zn 2+ (ZnCl 2 ) 87.44 ± 8.68 145.95 ± 5.13 21.44 ± 3.71 Cu 2+ (CuCl 2 ) 22.46 ± 6.83 110.18 ± 11.17 59.23 ± 12.57 Ni 2+ (NiCl 2 ) 111.05 ± 2.61 183.93 ± 30.68 35.25 ± 16.67 Co 2+ (CoCl 2 ) 104.15 ± 6.79 147.08 ± 17.51 79.14 ± 13.21 Mn 2+ (MnCl 2 ) 77.45 ± 2.93

186.12 ± 9.99 136.59 ± 3.65 Cd 2 + (CdSO 4 ) 63.24 ± 3.61 58.93 ± 3.88 39.52 ± 7.01 Fe 2+ (FeCl 2 ) 82.13 ± 13.46 39.47 ± 9.49 118.90 ± 21.53 Fe 3+ (FeCl 3 ) 78.33 ±

10.74 187.37 ± 15.37 134.89 ± 28.19 EDTA 62.44 ± 3.90 83.17 ± 8.32 112.93 ± 40.43 SDS 97.47 ± 1.65 81.58 ± 24.05 136.59 ± 3.66 Each value represents the mean of at least three independent replicates. Enzymatic www.selleck.co.jp/products/cobimetinib-gdc-0973-rg7420.html assays of 4-HS dehydrogenase activity The catalysis of 4-HS to MA by 4-HS dehydrogenase (His6-PdcG) was determined by monitoring the spectral changes at 320 nm. His6-PdcG thus catalyzed the oxidation of 4-HS to MA, confirming that PdcG was the enzyme downstream of PdcDE in the PNP degradation pathway in strain 1-7. Figure 7 Enzyme activity assay of PdcG. (a) Absorbance from 270 nm to 320 nm in the absence of His6-PdcG; (b) Spectral changes during oxidation of 4-HS by His6-PdcDE. The spectra were recorded a total of five times over a five minute period (marked 1-5). The arrow indicates the direction of spectral changes. (c) Spectral changes at 320 nm during metabolism of HQ by purified His6-PdcDE and oxidation of 4-HS by purified His6-PdcG. The arrow indicates when NAD+ was added. The specific activity of PdcG was calculated to be 0.44 Umg-1 (Table 2).

On the other hand, with one exception, all identified mutations were heterozygous in fluconazole-susceptible isolates; the finding supports the contention that loss of heterozygosity Gefitinib supplier in a diploid species such as C. albicans is a step in the development of the azole-resistant phenotype [3, 20, 29]. It is also possible that many ERG11 polymorphisms whilst not conferring resistance per se, may play a role in increasing the level of resistance [12, 21]. Conversely, the absence of substitutions G307S, G448E, G464S, Y132H, S405F and R467K, in susceptible isolates strongly suggests they have

contributed to the resistant phenotype. This hypothesis can be tested by site-directed mutagenesis and expression studies of specific ERG11 alleles in Saccharomyces cerevisiae. Using this approach, Sanglard and co-workers demonstrated that the substitutions G464S, Y132H, S405F and R467K were linked to azole resistance among their collection of isolates [12]; similar studies

are warranted to determine if the new substitution G450V is associated LY2157299 ic50 with resistance. Testing matched, susceptible and resistant, isolates from the same patient for ERG11 mutations may also assist in determining if particular mutations impact on azole resistance; unfortunately, matched isolates were not available in the present study. In general, neither the type or number of mutations in isolates sequentially obtained from the same patient correlated with azole MICs (Table 2), emphasising the need to assess additional genes

to understand the contribution of each to the resistance phenotype. As such, methods that detect polymorphisms are well-placed to screen large numbers of isolates from different sources for mutations and to guide functional testing of these isolates for resistance. This study demonstrates a new application of a simple RCA-based technique for the rapid and accurate detection of SNPs in the ERG11 gene as potential markers of resistance and for the tracking of resistant strains. Other sequencing-independent cAMP methods include conventional real time PCR and/or other probe-based technologies eg. molecular beacons or TaqMan probes [30, 31]. Results using conventional real time PCR are well-known to be highly-dependent on the physical characteristics of the platform. Molecular beacons and TaqMan probe methods are conveniently available in the form of commercial kits. Although able to detect SNPs with good sensitivity [30, 31], strict attention to the Tm of the probes is required to ensure adequate specificity. The RCA-based method described here offers several advantages over other amplification techniques in that ligation of the probe ends by DNA ligase requires perfectly-matched target-probe complexes preventing nonspecific amplification generated by conventional PCR and resulting in very high specificity. It is also rapid (2 h compared to 1–2 days for DNA sequencing following DNA extraction).

For example, blood loss and fluid shifts needing immediate replacement can quickly induce hemodynamic instability, electrolyte disturbance, oxygen supply and demand imbalances that can lead to acute organ dysfunction such as unstable arrhythmias. This process is commonly misinterpreted by non-anaesthesiologists as an evaluation Vismodegib purchase of fitness

for anaesthesia, assuming the anaesthesia is the most life-threatening process to the patient. On the contrary, when performed carefully with appropriate monitoring and timely interventions, the period of anaesthesia represents a period of relative stability for the patient in the vast majority of time. Rather, preoperative risk assessment evaluates the capacity of the patient to withstand the acute physiological perturbations resulting from the entire operative period that extends well into the recovery phase. The critical element is to estimate whether the patient can meet the increased oxygen demand due to the acute stress response to surgery. Therefore, the assessment tends to focus upon the cardiac and respiratory system as these are critical determinants of oxygen selleck compound supply to tissues. Another point of focus of the examination is conditions affecting the level of consciousness, whether it involves the central nervous system or secondary to metabolic disturbances. Acute delirium

is associated with high perioperative morbidity and mortality. Delayed emergence from anaesthesia may occur in Glutathione peroxidase patients suffering from preoperative delirium. Alternatively, the effects of general anaesthesia may further contribute to the delirious state, complicating the clinical picture. Pulmonary risk stratification Risk factors for developing postoperative pulmonary complications In a systematic review of more than 100 studies, the authors identified

patient, procedure and laboratory related risk factors for the development of postoperative pulmonary complications in non-cardiothoracic surgery that were supported by good evidence. Those of interest to the fracture hip population include advanced age, American Society of Anesthesiologists class 2 or higher, functional dependence, chronic obstructive pulmonary disease and congestive heart failure, emergency surgery, general anaesthesia, prolonged surgery and serum albumin level less than 30 g/L. Interestingly, for the study population there was insufficient evidence to support preoperative spirometry as a tool to stratify risk [4]. Similar risk factors have also been incorporated into a respiratory failure risk index [5].The presence of any of these conditions should alert the primary treating doctors to request for an early anaesthetic consultation. Postoperative pulmonary complications: why does it occur? Severe factors can individually or in combination precipitate respiratory failure should the patient fail to increase and sustain the necessary minute ventilation.

Thus, even though permeating and non-permeating solutes had the same effect on specific growth rates (Figure 1), these solutes affect cells in fundamentally different ways. Future work is now needed to test whether the responses to permeating and non-permeating solutes accurately simulate the responses to the solute and matric components of the total water potential, respectively, and to connect these responses with those observed in more realistic scenarios of soil desiccation.

Acknowledgements and funding We thank the European Community program FP7 (grant KBBE-211684) (http://​cordis.​europa.​eu/​fp7/​home_​en.​html) for financial support of this project. We thank Regina-Michaela Wittich for kindly providing strain RW1 and Jacques Schrenzel for helpful advice about cDNA labeling protocols. We thank the DNA Array Facility at the University of Lausanne for assistance with learn more microarray analyses. Electronic supplementary

material Additional file 1: Complete list of genes whose expression levels responded to short-term perturbation with sodium chloride or PEG8000 (FDR < 0.05, fold difference > 2.0). (XLSX 53 KB) Additional MDV3100 file 2: Complete list of genes whose expression levels responded to short-term perturbation with sodium chloride but not PEG8000 (FDR < 0.05, fold difference > 2.0). (XLSX 59 KB) Additional file 3: Complete list of genes whose expression levels responded to short-term perturbation with PEG8000 but not sodium chloride (FDR < 0.05, fold difference > 2.0). (XLSX 56 KB) Additional file 4: Complete list of genes whose expression levels

responded D-malate dehydrogenase to long-term perturbation with PEG8000 (FDR < 0.05, fold difference > 2.0). (XLSX 57 KB) References 1. Hiraishi A: Biodiversity of dioxin-degrading microorganisms and potential utilization in bioremediation. Microbes Environ 2003, 18:105–125.CrossRef 2. Wittich RM, Wilkes H, Sinnwell V, Francke W, Fortnagel P: Metabolism of dibenzo- p -dioxin by Sphingomonas sp. strain RW1. Appl Environ Microbiol 1992, 58:1005–1010.PubMed 3. Wilkes H, Wittich R, Timmis KN, Fortnagel P, Francke W: Degradation of chlorinated dibenzofurans and dibenzo- p -dioxins by Sphingomonas sp. strain RW1. Appl Environ Microbiol 1996, 62:367–371.PubMed 4. Armengaud J, Happe B, Timmis KN: Genetic analysis of dioxin dioxygenase of Sphingomonas sp. strain RW1: catabolic genes dispersed on the genome. J Bacteriol 1998, 180:3954–3966.PubMed 5. Wittich RM: Degradation of dioxin-like compounds by microorganisms. Appl Microbiol Biotechnol 1998, 49:489–499.PubMedCrossRef 6. Halden RU, Halden BG, Dwyer DF: Removal of dibenzofuran, dibenzo-p-dioxin, and 2-chlorodibenzo-p-dioxin from soils inoculated with Sphingomonas sp strain RW1. Appl Environ Microbiol 1999, 65:2246–2249.PubMed 7. Harris RF: Effect of water potential on microbial growth and activity. In Water Potential Relations in Soil Microbiology. SSA Special Publication Number 9. Edited by: Parr JF, Gardner WR, Elliot LF.

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Low pH usually accelerates acid consumption and proton export [51], and increases production of oxygen radicals, thus inducing a partial oxidative stress response. In this work, the expression of genes coding for ATP transporters that can work as proton pumps and proteins involved in osmotic stress response seem to be at least partially dependent on RpoH1. Likewise, the RpoH sigma factor has already been implicated in the oxidative stress response in other rhizobia [9, 11]. Moreover, our study revealed patterns of pH response and clarified the overlap of pH stress with heat shock response. The heat shock response in bacteria is characterized by the induction of a number of proteins

in response to change in temperature. Since many of these proteins are also induced by a variety of other environmental stress conditions, it can be concluded

that such response is a stress response and not only a heat shock response. RpoH1 has been described click here in S. meliloti as the heat shock response sigma factor [23–25]. The group of proteins shown to be involved in the heat shock response under the transcriptional control of RpoH1 includes chaperones, proteases, and regulatory factors. In the present study, we have seen that those groups of proteins are also involved in pH stress response. Hence, the pH stress response in S. meliloti, characterized in this work, is likewise not specific for pH stress, but also likely to be a response to other types of environmental stress. Three groups of S. meliloti genes were found to be transcriptionally regulated upon pH stress in an RpoH1-independent, check details in an RpoH1-dependent and in a complex

manner Overall, gene expression following rapid acid shift revealed several patterns of acid stress response, characterized by the induction of heat shock regulons and exopolysaccharide production and the repression of energy-expensive flagellar and chemotaxis regulons. The observed response of the S. meliloti wild type following acid shift is in agreement with that described by Hellweg et al. [30]. Though the nomenclature adopted in this manuscript is similar to that found in Hellweg et al., cluster distribution differs in that Hellweg divided the dataset in eight clusters and in the present study the dataset was divided into six clusters. Three classes of transcriptionally regulated S. meliloti genes Phosphoprotein phosphatase could be identified: genes which were regulated in an RpoH1-independent, an RpoH1-dependent or in a complex manner upon pH stress. The first class of genes, which were regulated in an RpoH1-independent manner, comprises exopolysaccharide I biosynthesis genes, like exoQ, exoP, exoN and exoY, and also the group of genes involved in motility and flagellar biosynthesis like the flagellar genes flgA, flgL and mcpT [35]. Those expression patterns further confirm the notion of an induced exopolysaccharide production and a hampered motility activity of S.