Mol Ecol 15:1519–1534PubMedCrossRef AZD6244 Manni F, Guérard E, Hever E (2004) Geographic patterns of (Genetic, Morphologic, Linguistic) variation: how barriers can be detected by using Monmonier’s algorithm. Hum Biol 76:173–190PubMedCrossRef McCusker MR, Bentzen P (2010) Positive relationships between genetic diversity and abundance in fishes. Mol Ecol 19:4852–4862PubMedCrossRef Nielsen EE, Hansen MM, Ruzzante DE, Meldrup D, Grønkjaer

P (2003) Evidence of a hybrid-zone in Atlantic cod (Gadus morhua) in the Baltic and the Danish Belt Sea revealed by individual admixture analysis. Mol Ecol 12:1479–1508 Ojaveer H, Jaanus A, MacKenzie BR, Martin G, Olenin S, Radziejewska T, Telesh I, Zettler ML, Zaiko A (2010) Status of biodiversity in the Baltic Sea. PLoS ONE 5:e12467PubMedCrossRef Olsson J, Mo K, Florin A-B, Aho T, Ryman N (2011) Genetic population structure of perch Perca fluviatilis along the Swedish coast of the Baltic Sea. J Fish Biol 79:122–137PubMedCrossRef Olsson J, Florin AB, Mo K, Aho T, Ryman N (2012a) Genetic structure of whitefish (Coregonus maraena) in the Baltic Sea. Estuar Coast Shelf S 97:104–113CrossRef Olsson J, Bergström L, Gårdmark A (2012b) Abiotic drivers of coastal fish community change during four decades in the Baltic Sea. ICES J Mar Sci 68:961–970CrossRef Østbye K, Bernatchez L, Naesje TF, Himberg K-JM, Hindar K (2005) Evolutionary

history of the European whitefish Coregonus lavaretus species complex as inferred from mtDNA phylogeography and gill-raker numbers. Mol Ecol 14:4371–4387PubMedCrossRef Palumbi SR (2003) Population genetics, demographic www.selleckchem.com/products/jnj-64619178.html connectivity, and the design of marine reserves. Ecol Appl 13:146–158CrossRef Papakostas S, Vasemägi A, Vähä J-P, Himberg M, Peil L, Primmer CR (2012) A proteomics approach reveals divergent molecular responses to salinity in populations of European whitefish (Coregonus lavaretus). Mol Ecol 21:3516–3530PubMedCrossRef Park SDE (2001) The Excel microsatellite toolkit, version 3.1. Animal Genomics Laboratory, University College Dublin. (http://​animalgenomics.​ucd.​ie/​sdepark/​ms-toolkit/​)

Bumetanide Patarnello T, Volckaert FAMJ, Avapritinib Castilho R (2007) Pollars of Hercules: is the Atlantic-Mediterranean transition a phylogeographical break? Mol Ecol 16:4426–4444PubMedCrossRef Pelc RA, Warner RR, Gaines SD (2009) Geographical patterns of genetic structure in marine species with contrasting life histories. J Biogeogr 36:1881–1890CrossRef Pereyra R, Bergström L, Kautsky L, Johannesson K (2009) Rapid speciation in a newly opened postglacial marine environment. BMC Evol Biol 9:70. doi:10.​1186/​1471-2148-9-70 PubMedCrossRef Petit R, Mousadik A, Pons O (1998) Identifying populations for conservation on the basis of genetic markers. Conserv Biol 12:844–855CrossRef Raymond M, Rousset F (1995) GENEPOP Version 1.

Nevertheless, current knowledge (both laboratory observations and

theoretical analyses) does not justify any assumptions regarding their interaction with bacteriophages. Some of the above surface particles interact via beta(3)-integrin subunits; for example, L1-CAM mediates melanoma cell/melanoma cell and melanoma cell/endothelial cell interactions [24]. Therefore, L1-CAM can be indirectly engaged in the studied effect. We consider the problem of molecular mechanisms of phage-melanoma interaction still open and believe selleck kinase inhibitor that further Ferrostatin-1 price investigations are needed. Models of in vitro studies allow investigating the direct effects of preparations on migrating cells. This brings us closer to understanding previously observed in vivo antimetastatic effects [13, 14]. The in vivo anticancer effects may result from an impact of the investigated preparations DNA Damage inhibitor on immunological systems, which has to be seriously considered. In vitro migration excludes the effect of complex mammalian immunology. Observations of the “”antimigratory”" effect of bacteriophages suggest that they are able to influence (at

least some) cancer cells directly. Previously we investigated the interactions of bacteriophage T4 with mammalian cells, observing an unexpected ability of the bacteriophage to bind weakly to melanoma cells in vitro. We selected bacteriophage HAP1, which was able to bind cancer cells more strongly. Importantly, HAP1 was also much more effective against melanoma metastases in vivo [13]. A mutation in the hoc gene that differentiates bacteriophage HAP1 and its parental strain T4 was found [14]. Nevertheless, in these studies we did not find any difference in the effects of T4 and HAP1 on melanoma migration in vitro. This may suggest that some immunological components are engaged in the activity of HAP1. This phage is different acetylcholine (from

T4 phage) in, among other properties, the time and means of clearance from a mammalian organism, which may contribute to these observations. On the other hand, the difference between T4 and HAP1 interactions with melanomas may simply be undetectable in the types of tests conducted. We believe that our observations are of importance for any further attempts to use bacteriophage preparations in antibacterial treatment. To the best of our knowledge, there are no published data on the effect of bacteriophages on macrophage or lymphocyte (normal cell) migration in vitro. We also work on this issue and we hope to be able to present data in the future. It should be pointed out that bacteriophages constitute a strongly diversified group of microorganisms and our observations apply to T4-like phages. Other types of bacteriophages (with different genetics and protein construction) must be investigated and analysed independently. As the risk of antibiotic-resistant hospital infections strongly affects cancer patients, we consider that such investigations are greatly needed.

v. every 3 months, and 2 mg i.v. every 2 months) were compared to ACE doses ≤7.2 mg (100 mg oral monthly, 50/50 mg monthly, and 2.5 mg oral daily) and to low 5.5 mg ACE dose (oral

2.5 mg daily). A dose–response effect on nonvertebral fractures was observed when comparing high with low ACE doses. The comparison resulted in a 0.62 RR (95% CI, 0.396–0.974; p = 0.038) for ACE doses ≥10.8 mg see more vs. to 5.5 mg ACE doses and in a 0.64 RR (95% CI, 0.43–0.94) for ≥10.8 mg ACE doses vs. ≤7.2 mg ACE doses, leading to the conclusion that higher ibandronate dose levels (150 mg monthly or 3 mg i.v. quarterly) significantly reduced nonvertebral fracture risk in postmenopausal women. In a similar analysis, Harris et al. compared reduction in fracture risk for high (≥10.8 mg), mid (7.2–5.5 mg), and low (≤4.0 mg) ACE relative to placebo [74]. It was observed that doses of ibandronate resulting in ACEs ≥10.8 mg, including the marketed oral 150 mg monthly and i.v. 3 mg thrice monthly, significantly reduce the risk of all clinical, vertebral, and nonvertebral fractures with a 0.712 RR (95% CI, 0.55–0.92; p = 0.01). The risk of nonvertebral fractures was also significantly reduced with a 0.701 RR (95% CI, 0.50–0.99; p = 0.04). Data from the four phase III clinical trials of ibandronate (8,710 patients) were pooled in a meta-analysis to assess the relationship between ibandronate dose, BMD changes, and rates of both clinical and

nonvertebral fractures [75]. It was observed that both lumbar spine and total hip BMD increased with increasing ibandronate dose. A statistically significant inverse linear IWR1 SPTLC1 relationship has been reported between percent change in lumbar spine BMD and the rate of clinical fractures (p = 0.005). There is no evidence, from placebo-controlled trials, for a reduction of nonvertebral fracture with ibandronate,

but data from the MOBILE bridging study, from meta-analysis and from ACE evaluations, suggest a significant effect of the marketed oral 150 and the 3 mg i.v. ibandronate on the risk reduction of nonvertebral fractures. Hip, nonvertebral, or clinical fracture rates were not statistically different between patients receiving monthly oral ibandronate, weekly oral alendronate, or risedronate in a 12-month observational study, but patients on oral ibandronate had a significantly 64% lower risk of vertebral fractures than patients on weekly bisphosphonates (RR, 0.36; 95% CI, 0.18–0.75; p = 0.006) [76]. Both oral 2.5 mg daily and intermittent oral ibandronate dosage (20 mg every other day for 12 doses every 3 months) were well tolerated with an incidence of adverse events similar to placebo in the BONE trial [69]. Once-monthly oral ibandronate was well tolerated, with a similar safety profile to placebo in a 3-month, double-blind, placebo-controlled, phase I study (Monthly Oral Pilot Study) [77] and with a similar incidence of adverse events across Sepantronium molecular weight groups (oral 50 + 50, 100, and 150 mg) in the MOBILE study [70].

05 for

all PCR comparisons, including target gene mRNA relative to β-actin or GAPDH mRNA; data shown for normalization to β-actin expression, only). These findings indicate that APF induces changes in GSK3β phosphorylation via CKAP4, but further suggest that APF does not mediate its antiproliferative activity in T24 cells merely by inhibiting canonical Wnt/frizzled signaling. Figure 4 GSK3β tyr216 phosphorylation activity in bladder cancer cells. A, Western blot analysis of GSK3β protein CBL0137 expression and phosphorylation in cells electroporated in the presence of no siRNA (Lanes 1 and 2), CKAP4 siRNA (Lanes 3 and 4), or scrambled non-target (NT) siRNA (Lanes 5 and 6), and treated with as -APF (APF) or its inactive control peptide (Pep). β-actin served as a standard control. B, Quantitative real time RT-PCR analysis of GSK3β mRNA expression in T24 cells electroporated SIS3 cell line with no siRNA, C, CKAP4 siRNA, or D, non-target siRNA, and then treated with as -APF (APF) or its inactive control peptide (Pep). Each experiment was performed in duplicate on at least three

separate occasions. Data are expressed as mean ± SEM. We therefore proceeded to examine the effects of as -APF on β-catenin and β-catenin phosphorylation in T24 cells. As shown in Figure 5A, although subtle Navitoclax increases in β-catenin phosphorylation were apparent following APF treatment of nontransfected cells when antibodies against phosphoserine 33, 37 and threonine 41 (ser33,37/thr41) sites were used, there was no apparent change in total cell β-catenin protein. In addition, decreased phosphorylation was apparent following APF treatment when antibodies that recognized phosphoserine 45 (ser45) and phosphothreonine 41 (thr41) were used. Again, these changes in phosphorylation were abrogated by CKAP4 knockdown, and there were no significant differences in β-catenin mRNA levels regardless of transfection status (Figure 5B-D) (p >.05 for all PCR comparisons, including AMP deaminase target gene mRNA relative to β-actin or GAPDH mRNA; data

shown for normalization to β-actin expression, only). Although these findings suggest subtle changes in β-catenin phosphorylation in response to APF, they also provide additional evidence that APF may mediate its profound effects on cell proliferation and gene expression via means other than (or in addition to) regulation of canonical Wnt/frizzled signaling pathways. Figure 5 β-catenin phosphorylation in T24 bladder cancer cells. A, Western blot analysis of β-catenin protein expression and phosphorylation activity in cells electroporated in the presence of no siRNA (Lanes 1 and 2), CKAP4 siRNA (Lanes 3 and 4), or scrambled non-target (NT) siRNA (Lanes 5 and 6), and treated with as -APF (APF) or its inactive control peptide (Pep). β-actin served as a standard control.

All termite feeding groups were positively associated BKM120 clinical trial with axis 1 (i.e. with low disturbance levels), with dead wood/leaf litter feeders (Group II) and organic soil feeders (Group III) being strongly so, dead wood/feeders (Group I) and fungus-growing termites (Group IIF) being more weakly associated, and true soil feeders (Group IV) having the weakest association of all (note, there

were very few Group IV occurrences) (Fig. 2b). Axis 2 accounted for only 2.5 % of assemblage variation. Group IIF and Group I showed stronger associations with axis 2 than axis 1, being positively and negatively associated with bare ground cover, respectively (Fig. 2b). Discussion Both ants and termites inhabiting soil and dead wood varied in occurrence and functional group composition with habitat disturbance. However, the results selleck screening library differed greatly between the two taxa. All termite feeding groups showed fewer occurrences in more disturbed sites, whereas ant functional groups showed more idiosyncratic patterns. Variation in functional group occurrence was related to habitat treatment for both ants and termites, but the strength of associations with other variables differed between the taxa. Ants were well

represented in disturbed habitats, with occurrences highest in logged forest. Studies in Amazonia have also found high ant abundances in moderately disturbed habitats such as re-growth forest and fragment edges (Didham 1997; Vasconcelos Tacrolimus (FK506) 1999). Andersen (2000) considers low temperature, lack of nest sites (e.g. rotting logs), poor food supply, and high structural complexity of foraging surfaces to be the main stressors limiting ant populations. Logged forests may offer intermediate conditions that favour greater ant abundance, in which nest sites are available, but surfaces are not too complex to limit foraging, with temperatures slightly higher on average than in old growth forest. However, more highly disturbed forests, such as secondary regrowth following clearance, support fewer species due to differences in tree density, diversity and size distribution (Klimes et al. 2012). In contrast, termites

were more common in old growth forest than in the other two habitats. Many termites require a closed canopy to buffer microclimate and avoid desiccation, as well as relatively clayey soils rich in organic material for colony building and food (Eggleton et al. 1997, Hassall et al. 2006). Logging, habitat clearance and conversion to oil palm plantation lead to hotter and drier microclimate (Turner and Foster 2006), and the disruption of soil structure by logging FHPI tracks (Malmer and Grip 1990). These differences may have been accentuated by a drought that was just ending during the sampling period (see http://​www.​searrp.​org/​danum-valley/​the-conservation-area/​climate/​), because disturbed forests may be less able to buffer microclimate (Ewers and Banks-Leite 2013).

This took longer to become apparent in the cyanobacterial species (48 h, Figure 2C) where significant differences from the control also occurred in the sulfite and cysteine treatments. The latter was not the case for Chlamydomonas or Cyanidioschyzon. Here again, this could be accounted for by sulfur metabolism differences between cyanobacteria

and algae, or possibly distinct tolerances to the toxic effects of these metabolites. High rates of sulfite assimilation into amino acids [34] and high expression of SSU1, mTOR phosphorylation a sulfite efflux gene [35], are known to result in lower toxicity to sulfite in yeast. Similar mechanisms may also occur in Synechococcus. The thermophilic red microalga, Cyanidioschyzon, was capable of biotransforming approximately three times as much Cd(II) into metal sulfide as the mesophilic green alga, Chlamydomonas, when both were grown in 100 μM Cd(II). This ability may be accounted for by its adaptation to sulfur-rich hot springs [36]. In fact, the Cyanidium medium [37] used to grow Cyanidioschyzon contains over an order SRT1720 concentration of magnitude

more sulfate than the high salt medium conventionally used for Chlamydomonas. The sensitivity of Synechococcus to Cd(II) is much higher than in the eukaryotic species. Nevertheless, metal biotransformation into sulfide by this species was only about half of that for Chlamydomonas, indicating that although sensitive to cadmium, it was able to transform a high proportion of the Cd(II)

into metal sulfide. The fact that Synechococcus can convert a relatively high amount of Cd(II) into metal sulfide while remaining very sensitive to Cd(II), might be attributed to a relatively high susceptibility to displacement of metals by Cd as cofactors in photosynthetic and other metabolic enzymes, and to disruption of membrane function [4]. Similarly, this could account for the differences between the algal species. The first report of acid labile sulfide in living organisms was in association with metallothioneins and phytochelatins in fission yeast [38], and it is known that metallothionein gene amplification can confer resistance to Ion Channel Ligand Library cell assay cadmium in Synechococcus PCC 6301 [39]. Algal phytochelatins bind cadmium in relatively low metal to peptide amounts [40] and it is likely that CdS Fossariinae formed in the organisms in the present study are mainly in the form of precipitated nanoparticles, examples of which have been reported in as diverse organisms as Klebsiella[41], marine microalgae [33], tomatoes [42] and mustard plants [43]. This, however, remains to be confirmed. Sulfate assimilation Most organisms absorb sulfur from the environment in the form of inorganic sulfate and active transport systems for sulfate uptake have been investigated extensively in algae [44–46], bacteria [47], yeast [48], and higher plants [49, 50]. Algae and cyanobacteria appear to undergo sulfur assimilation in a similar manner [51, 52].

As shown in Fig 4A, on day 22 after tumor cell inoculation, PEDF level in AZD8186 chemical structure Ad-PEDF group was significantly higher than control groups, 77.36 ± 3.78 ng/ml vs 33.62 ± 2.79 ng/ml in Ad-null and 36.87 RSL3 manufacturer ± 3.35 ng/ml in NS

groups, respectively (p < 0.05). This result indicates that Ad-PEDF successfully transferred PEDF to mice and produced secretory PEDF proteins. Figure 4 Serum PEDF and viral distribution in mice after Ad-PEDF treatment. A. Serum collected from mice bearing B16-F10 melanoma on day 22 after tumor inoculation was processed and subjected to an ELISA analysis to measure PEDF concentration. Compared to Ad-null or NS treated mice, serum PEDF concentration significantly increased in mice treated with Ad-PEDF (ANOVA, *, p < 0.05). B. The distribution of i.v. injected virus. The luciferase content represents the amount of virus. n = 2. Next, we determined the source of PEDF by analyzing the distribution of i.v. injected virus. As shown in Fig 4B, using the luciferase reporting system, we found that the viruses mainly distributed in the liver, in agreement with many adenovirus infection models. This result suggests that while Ad-PEDF infected multiple organs, including the tumor, the liver click here is the major organ that adenovirus targeted and likely is the significant source of

the serum PEDF. Ad-PEDF treatment increased apoptosis and decreased MVD in tumor tissue In the proceeding experiments, we observed the reduced tumor volume and increased serum PEDF after Ad-PEDF treatment, in comparison to control, however, the majority of the virus was entrapped in liver and did not target the tumor tissue. It is important to demonstrate crotamiton whether serum PEDF indeed acts on tumor tissue and causes histological change. To address this question, we determined apoptosis in tumor tissue after Ad-PEDF treatment

using TUNEL staining. As shown in Fig 5A, within a similar field of view, may more apoptotic cells (with green nuclei) in tumor tissues were observed in Ad-PEDF treated mice than in Ad-null or NS treated mice. For the quantitative comparison, the apoptosis index in each group was calculated. The apoptosis index was significantly higher in Ad-PEDF group than in Ad-Null and NS groups with values of 26.3% ± 3.3% v.s. 6.3% ± 4.7% and 5.6% ± 1.9%, respectively (p < 0.05, Fig 5B). These data suggest that decreased tumor volumes after Ad-PEDF may be caused by increased apoptosis. Figure 5 TUNEL, CD31 and histological staining for tumor tissue. On day 24 following inoculation, tumor tissue from tumor-bearing mice treated with NS (a), Ad-Null (b), or Ad-PEDF (c) were sectioned and stained with FITC-dUTP, CD31 mAb or H&E. A. Apoptotic cells (green) were identified by TUNEL and examined under a fluorescence microscope (Original magnification, ×200). B. ANOVA analysis detected significant differences in the apoptotic index between Ad-PEDF group and control groups (p < 0.05). C.

All authors read and approved the final selleck chemical manuscript.”
“Background Accurate, reproducible isolate characterization

data helps epidemiologists, scientists, physicians, public health officials, and many other professions, better monitor and manage endemic and epidemic infectious disease trends [1]. Historically, bacterial typing schemes have been based on immunological and electrophoretic approaches [2]. Immunological based schemes classify strains on the specificity of antibodies raised against antigenic bacterial components. This approach has been widely applied in the form of capsular serotyping, whereby the antigenic specificity of different intra-species capsule types are used to classify the bacteria [3, 4]. However, many globally significant bacterial pathogens such as Streptococcus pneumoniae and Neisseria meningitidis are readily able to incorporate environmental genetic material into their genomes allowing for rapid genetic variation and interchange of immunogenic components; including those on which serotyping is based [5]. This phenomenon has been observed recently with S. pneumoniae capsular typing following the introduction of the seven-valent pneumococcal conjugate vaccine (PCV7) [6]. As a result of the histone deacetylase activity component specificity of immunological

based typing methods, it has become well recognized that strains possessing the same serotype are not necessarily clonally related, nor expected to possess the same repertoire of virulence factors. Immunogenic approaches are now used in more focused ways to explore specific factors, particularly those relevant to guiding vaccine evaluation and development, as GANT61 purchase was demonstrated with a recent serotype B meningococcal vaccine investigation Tacrolimus (FK506) [7]. Multi-locus enzyme electrophoresis (MLEE) is another typing method, and is based on the relative electrophoretic mobility of a set of ubiquitously present bacterial enzymes [8]. This approach is not dependent on a single immunogenic component and as such is less influenced by horizontal exchange or positive selection

events. However, it is complicated to perform and it is difficult to compare the resulting electrophoretic types between different groups [2]. Similar to the MLEE, pulse field gel electrophoresis (PFGE) classifies individual strains based on the gel electrophoretic mobility of bacterial components: in this case the relative mobility of DNA fragments which have been obtained through restriction enzyme digestion [9]. PFGE has been widely used for typing and has been considered a gold standard for some epidemiological studies, however, there have been challenges in standardizing protocols between different research groups [10]. Multi-locus sequence typing (MLST) is a classification scheme whereby isolates are typed based on the nucleotide sequences from a set of housekeeping genes that are necessary for the maintenance of basic cellular functions.

FEMS Microbiol Lett 1991, 65:123–128.PubMedCrossRef 38. Kieser T, Bibb MJ, Buttner MJ, Chater KF, Hopwood DA: Practical Streptomyces Genetics. 2e edition. Norwich, England: John Innes Foundation; 2000. 39. Duary RK, Batish VK, Grover S: Expression of the atpD gene in probiotic Lactobacillus plantarum strains under in vitro acidic conditions using RT-qPCR. Res Microbiol 2010, 161:399–405.PubMedCrossRef 40. Fernandez A, Thibessard A, Borges F, Gintz B, Decaris B, Leblond-Bourget N: Characterization of oxidative stress-resistant mutants of Streptococcus thermophilus CNRZ368. Arch Microbiol 2004, 182:364–372.PubMedCrossRef Authors’ contributions Conceived and designed the experiments:

NC VL FCB PL GG. Performed the experiments: NC VL CM. Analyzed the data: NC VL FCB PL BD GG. Wrote the

paper: Belinostat NC VL FCB GG. All authors read and approved the final manuscript.”
“Background Dampness or mold in buildings are positively associated with several allergic and respiratory effects [1]. Based on a meta-analysis of relevant literature, a 30-50% increase in Epigenetics Compound Library variety of respiratory and asthma-related health outcomes was summarized by Fisk et al. [2]. It has also been estimated that 21% (4.6 million cases) of total asthma cases in the United States may be attributable to residential dampness and mold [3]. Due to the strong epidemiological association between observed dampness or mold and adverse health Poziotinib ic50 effects, it is hypothesized that excessive microbial proliferation in building materials manifests itself as increased or altered levels of microbe-derived compounds in the indoor air, which individually or in combination reach sufficient levels to affect human health. The elimination

of growth by remediation is intended to normalize these levels, usually resulting in decreased symptoms [4–10]. However, alleviation is not always L-NAME HCl seen, especially if remediation has been partial [5, 11, 12]. At present, the agents that contribute to the development of the reported building-related health effects are still only partially understood, and no internationally accepted guidelines are available for monitoring the success of mold remediation [13]. This is due largely to the complex and compound nature of indoor exposures and the varying extent of population susceptibility, further complicated by traditional methodological deficiencies in the identification and enumeration of biological agents. Fungi are major colonizers and degraders of building materials; they possess vast bioactive potential, and have the capacity to spread spores and smaller fragments from the site of proliferation to the surrounding air. The capacity to induce symptoms in the non-sensitized population at concentrations typical of indoor environments depends on species-specific traits, such as allergenicity, pathogenicity and mycotoxin production. Thus, the accurate identification of microbes is a prerequisite for the assessment of their potential health effects [14, 15].

The posterior probabilities were then summarized as a consensus tree with MrBayes. Thirdly, the consensus tree was rooted by paralog CUDC-907 price rooting [33] based on the phylogeny of the repetitive elements from the first step, producing the final phylogenetic hypothesis. Lastly, to check for conflicting signals and possible patterns of recombination, a recombination network of the sequences was computed using SplitsTree 4.10 [34]. Acknowledgements We would like to thank Gilbert Greub for supplying us with the hctB sequence of Protochlamydia naegleriophila and

Garry Myers for giving us the hctB sequence of Chlamydophila psittaci. This study has been supported by The Swedish Board of Health and Welfare and The Uppsala-Örebro Regional Research Council. The work of this manuscript is part of the goals described in the European Framework Programme 6 (FP6) funded EpiGenChlamydia Consortium (EU FP6 LSHG-CT-2007-037837) a Co-ordination Action, in functional genomics research entitled: Contribution of molecular epidemiology and host-pathogen genomics to understand Chlamydia trachomatis disease (see additional information at http://​www.​EpiGenChlamydia.​EU). Electronic supplementary

material Additional file 1: Appendix 1. List of the 378 sequences in the MLST database included in this study. (XLS 56 KB) Additional file 2: Appendix 2. Sequence variants of the MLST target that include hctB in Chlamydia trachomatis with corresponding accession number.

Each sequence variant is named after the allele number and the serotypes in which that variant has been found. (DOC 44 KB) Additional file 3: Appendix 3. Hc2 amino acid SGC-CBP30 order sequences in Chlamydiales and Hc2-like sequences in other genera. (DOC 82 KB) References 1. Hackstadt T, Baehr W, Ying Y: Chlamydia trachomatis developmentally regulated protein is homologous to eukaryotic histone H1. Proceedings of the National Academy of Sciences of the Cilengitide United States of America 1991,88(9):3937–3941.PubMedCrossRef 2. Perara E, Ganem D, Engel JN: A developmentally regulated chlamydial gene with apparent homology to eukaryotic histone H1. Proceedings of the National Academy of Sciences of the United States of America Y27632 1992,89(6):2125–2129.PubMedCrossRef 3. Belland RJ, Zhong G, Crane DD, Hogan D, Sturdevant D, Sharma J, Beatty WL, Caldwell HD: Genomic transcriptional profiling of the developmental cycle of Chlamydia trachomatis. Proceedings of the National Academy of Sciences of the United States of America 2003,100(14):8478–8483.PubMedCrossRef 4. Barry CE, Hayes SF, Hackstadt T: Nucleoid condensation in Escherichia coli that express a chlamydial histone homolog. Science 1992,256(5055):377–379.PubMedCrossRef 5. Brickman TJ, Barry CE, Hackstadt T: Molecular cloning and expression of hctB encoding a strain-variant chlamydial histone-like protein with DNA-binding activity. J Bacteriol 1993,175(14):4274–4281.PubMed 6.