3 Analysis of antioxidants A) Activity of SOD; B)


3 Analysis of antioxidants. A) Activity of SOD; B) GSH-GPx and C) CAT. The results are expressed as the mean + S.E. of 10 animals per group. TCr Angiogenesis inhibitor = Trained Creatine; T = Trained; CCr = Control Creatine; C = Control not trained. * different C; † different CCr; ‡ different T/C. Concentration of reduced glutathione (GSH), oxidized glutathione (GSSG) and ratio between reduced glutathione and oxidized glutathione (GSH/GSSG) in liver Rat liver values for GSH, GSSG and GSH/GSSG ratio at the end of the experiment showed no differences between groups (Figure 4). Figure 4 Concentration of reduced glutathione, oxidized glutathione and ratio reduced glutathione/oxidized glutathione in the liver the animals at the end of the experiment. The results are expressed as the mean + S.E. of 10 animals per group. TCr = Trained Creatine; T = Trained; CCr = Control Creatine; C = Control not trained. Discussion In recent years the use of creatine supplementation (CrS) whith antioxidant function has increased. Several studies have confirmed these effects and pointed to creatine as a new alternative in the prevention of oxidative stress in which creatine appears to play a crucial role in reducing the toxic effects of endogenous production of reactive oxygen species (ROS) [5, 26–28]. The literature indicates that 2% CrS in animal feed JQEZ5 purchase is able to

trigger a significant increase in phosphocreatine (PCr) and creatine levels in rat tissues [29, 30]. Using this amount of creatine, McMillen et al. [30] observed a significant increase in the total creatine content of rat gastrocnemius muscle in two weeks of supplementation. In the present study, significant increase in the hepatic creatine concentrations were demonstrated in CCr and TCr rats compared to the non-supplemented control groups, which supports prior findings in the literature [30, 31]. After confirming that dietary supplementation increased creatine concentration in rat liver, this study aimed to evaluate the possible

antioxidant effects of CrS in vivo. The results demonstrate that Mannose-binding protein-associated serine protease creatine exerts indirect antioxidant activity in rat liver, i.e., creatine increased the activity of antioxidant enzymes GSH-GPx and CAT. However, CrS was not effective in normalizing the increased concentrations of H2O2 triggered by exercise. In addition, no significant differences were observed in the concentration of TBARS between groups. H2O2 plays an important role in homeostasis. It participates in cellular induction of gene expression, among which are those genes responsible for antioxidant enzyme synthesis [32–34]. In the present study, we demonstrated that exercise-trained rats (T and TCr) had higher concentrations of H2O2 than sedentary rats (C and CCr). These data reinforce the observations of several authors that indicate that creatine appears to exert selective antioxidant effects [26, 27]. Lawler et al.

However, 51% of the sequences (14,667 of 28,451) were divided bet

However, 51% of the sequences (14,667 of 28,451) were divided between five different isolates in roughly equal numbers. GBV-C is known to vary extensively between isolates and the large diversity revealed here indicates that these four affected twins were infected by different isolates and that different variants are present in each individual. Hepatitis C virus A standard diagnostic serology test confirmed previously unrecognized hepatitis C infection in one affected twin. This discovery provides a plausible medical explanation for chronic

fatigue in this individual. Discussion We used an “”unbiased”" genomic technology to Proteases inhibitor search for the presence of known and novel viruses that correlate with the clinical presence or absence of chronic fatiguing illness. Such searches have proven powerful for respiratory infections selleck chemicals llc [14, 15], and complement studies targeting specific infectious agents [13]. The general hypothesis we tested was that chronic fatigue was associated with on-going viremia. As we have argued elsewhere [12], the study of discordant monozygotic twins was optimal in controlling for potential biases particularly as samples were obtained from both twins

at the same place and time. The deep Roche 454 sequencing, combined with the efficient enrichment of virus particles, makes it likely that most viruses present in the serum of these individuals were detected. However, we did not detect any clear-cut signatures of novel viruses. For known viruses, the predominant finding was a slight but significant excess of detection of nucleic acid from GBV-C in 8.9% of affected twins

and 0% of their unaffected co-twins (p = 0.019). Previously undetected hepatitis C virus infection was discovered in one affected twin. This individual was kept in these analyses as this is conservative and conforms to our prior intentions. GBV-C (also known as hepatitis G virus) is an RNA virus and member of the Flaviviridae family with greatest homology O-methylated flavonoid to hepatitis C virus. It is transmitted via multiple modalities (e.g., vertically, sexually, and parenterally) [17]. GBV-C viremia is present in ~2% of healthy blood donors and 17% show evidence of past infection [18]. GBV-C infection is not known to cause any human disease [19] and co-infection might improve the course of HIV-1 disease [20]. A prior small study of 12 CFS cases and 21 controls concluded that chronic GBV-C infection was not associated with CFS [21]. The lack of GBV-C positive individuals among the unaffected twins is could at first glance be seen as surprising. However, we would statistically expect that one or two individuals would be positive, based on chance, and the result we obtained is therefore not unlikely. There are several reasons why a chronic infection important to the etiology of chronic fatiguing illness could have escaped detection.

PLoS One 2009,4(3):e4969 CrossRefPubMed 65 Duron O, Bouchon D, B

PLoS One 2009,4(3):e4969.CrossRefPubMed 65. Duron O, Bouchon D, Boutin S, Bellamy L, Zhou L, Engelstadter J, Hurst GD: The diversity of reproductive parasites among arthropods: Wolbachia do not walk alone. BMC Biol 2008,6(1):27.CrossRefPubMed 66. Baldo L, Werren JH: Revisiting Wolbachia supergroup typing based on WSP: Spurious lineages and discordance with MLST. Curr Microbiol 2007, 55:81–87.CrossRefPubMed 67. Casiraghi M, Bordenstein SR, Baldo L, Lo N, Beninati T, Wernegreen JJ, Werren JH, Bandi C: Phylogeny of Wolbachia pipientis based on gltA, groEL and

ftsZ gene sequences: clustering of arthropod and nematode symbionts in the F supergroup, and evidence for further diversity in the Wolbachia tree. Microbiology-Sgm 2005, 151:4015–4022.CrossRef 68. Werren JH:Arsenophonus. Bergey’s Manual of Systematic Bacteriology (Edited by: Garrity GM). New York: Springer-Verlag 2004., 2: 69. Hall TA: BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nuc Acid Symp Series 1999, 41:95–98. 70. Castresana J: Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol 2000, 17:540–552.PubMed

71. Posada D, Crandall KA: MODELTEST: testing the model of DNA substitution. Bioinformatics 1998, 14:817–818.CrossRefPubMed 72. Goloboff Nutlin-3a mouse PA, Farris JS, Nixon KC: TNT. Cladistics-the International Journal of the Willi Hennig Society 2004, 20:84–84. 73. Guindon S, Gascuel O: A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol 2003, 52:696–704.CrossRefPubMed STK38 74. Galtier N, Gouy M, Gautier C: SEAVIEW and PHYLO_WIN: Two graphic tools for sequence alignment and molecular phylogeny. Comput Appl Biosci 1996, 12:543–548.PubMed 75. Drummond AJ, Nicholls GK, Rodrigo AG, Solomon W: Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data.

Genetics 2002, 161:1307–1320.PubMed Authors’ contributions EN obtained the sequence data, compiled alignments and participated in the study design, phylogenetic inference, interpretation of the results, and preparation of the manuscript. VH conceived of the study and participated in conduction of the phylogenetic inference. Both, VH and NAM participated in the study design, evolutionary interpretation of the results and preparation of the manuscript. All authors read and approved the final manuscript.”
“Background Brucellae are Gram-negative, facultative, intracellular bacteria that can infect many species of animals and man. Six species were classically recognized within the genus Brucella: B. abortus, B. melitensis, B. suis, B. ovis, B. canis, and B. neotomae [1, 2]. This classification is mainly based on differences in pathogenicity, host preference, and phenotypic characteristics [1–3].

The cutoff was set at 2 times Secondly, genes designated present

The cutoff was set at 2 times. Secondly, genes designated present in treated samples but see more absent in controls, or vice versa, were determined, as these could be genes induced from or repressed to background expression levels, respectively, after treatment. From these genes, those discriminating between treated and control samples

were again selected with a two-sample t-test (p < 0.001), combined with the requirement of an at least two-fold difference of the mean intensities for a given gene. Scatter plot, gene tree Scatter plots were used to visually examine the expressional level of genes between the control and DEN-exposed groups. Hierarchical dendrograms were drawn with the Cluster (2.0). It was created by clustering the genes according to their expression in response to the carcinogenic agent. Genes sharing similar expression profiles tended to be clustered together, and the Belinostat clinical trial location of a branch containing the genes can be considered a measure of how similar the gene expression was. Genes were selected for the construction of gene tree if the expression of the gene was two-fold

greater or less in the treatments, relative to that in the corresponding control. The horizontal axis shows the clustering of the genes according to their expression across treatments; while the vertical axis showed the clustering according to their expression profile in the treatment. Statistical analysis The genechip probe array system only allows comparison of one treatment hybridizing with the probe set. In a comparison analysis, two samples were hybridized to two genechip probe arrays of the same type, they were compared against each other in order to detect and quantify changes in gene expression. One genechip was for baseline (control) and the other was

for the experiment (treatment). Two sets of algorithms were generated and they were used to generate change significance and change quantity metrics for every probe set using Microarray Suite (MAS) version 5.0 (Affymetrix, CA). The change algorithm generated a Change p value and an associated Ribose-5-phosphate isomerase fold-change value. The second algorithm gave a quantitative estimate of the change in gene expression in the form of Signal Log Ratio. In the present study, the level of gene expression can be regarded as increased if its Change p-value was less than 0.002 and the gene expression would be considered to be decreased if its Change p-value was greater than 0.997. This method has been used by other investigators. Fold change could be calculated with the following formula: fold change = 2(signal log ratio). Validation of differential expression of genes by real-time RT-PCR The differential expression of selected genes was further validated by real-time PCR with SYBR green-based detection (ABI) using gene-specific primer pairs that were run on an ABI 7000 fluorescent sequence detection system (Perkin-Elmer, Foster City, CA).

As shown in Table 4, the detection limit of the test varied from

As shown in Table 4, the detection limit of the test varied from 0.5 to 0.125 HA units/200 ul of sample. The detection limit of the commercial kit for influenza A virus detection (Rockeby) was determined to be 200 ul of sample containing at least 1.5 HA titer of virus. Performance of H5 dot ELISA in the detection of variant

H5N1 Indonesia strains in poultry samples relative to RT-PCR The dot ELISA test was further evaluated with poultry Ilomastat clinical trial samples. The swabs from birds infected with H5N1 virus can secrete virus of titer higher than l08 EID50/ml. Samples were serially diluted 10 times from 10-1 to 10-4 with PBS and tested by the dot ELISA kit to determine the detection limit for swabs. The sensitivity test indicated that the dot ELISA kit

was able to detect the presence of virus at a concentration down to 105 EID50/ml in swabs, suggesting the test can be used for the detection of H5 infection in sick birds. From 150 samples taken from clinically healthy birds, one sample was found to be positive with the test. The same sample this website was confirmed to be the only positive swab among the 150 samples in RT-PCR with H5 specific primers. 50 tracheal swabs obtained from sick birds were also tested with both dot ELISA and RT-PCR (Table 7). The results with the dot ELISA showed that nine samples were positive for H5 infection. The same result was observed from the verification with RT-PCR. Table 7 Results of detection

of H5 virus in random tracheal swabs using the dot ELISA kit and RT-PCR Source of sample (area) Source of animal Clinically condition of animal Number of samples Result of test using Sensitivity (%)         Dot ELISA RT-PCR primer H5   Makasar Native chicken Healthy 50 1 1 100 Bogor Layer chicken Healthy 50 1 1 100 Bogor Broiler chicken Healthy 50 selleck compound 1 1 100 Bogor Chicken and duck Sick 50 9 9 100 As shown in Table 8, specificity test using various H5N1 viruses from several years and areas in Indonesia showed that the ELISA kit is 90% specific compared with RT-PCR using H5 primers, but 100% specific compared to HA2 primer. This indicates that the dot ELISA kit is able to detect H5N1 as long as the virus did not undergo a genetic mutation in their HA genes. Taken together, these findings indicate that the dot ELISA kit is suitable for specific early detection of H5 virus infection in avian species.

SS carried out the overexpression of Obg and its biochemical anal

SS carried out the overexpression of Obg and its biochemical analysis. VLS

read the manuscript critically, participated in interpretation of the data, and worked with the other authors to prepare the final version of the paper. SD conceived the study, participated in its design and interpretation of results and wrote the manuscript. All authors read and approved the manuscript.”
“Background The two major porins of Escherichia coli, namely OmpF and OmpC, form non-specific transport channels selleck products and allow for the passive diffusion of small, polar molecules (such as water, ions, amino acids, and other nutrients, as well as waste products) across the cell membrane. High and low levels of OmpF and OmpC are respectively expressed at low osmolarities in E. coli; as the medium osmolarity increases, OmpF expression is repressed, while OmpC is activated [1, 2]. OmpF forms a larger pore (hence a faster flux) than OmpC

[3]. OmpC expression is favored when the enteric bacteria, such as E. coli, live in the mammalian gut where a high osmolarity (300 mM of NaCl or higher) is observed; in addition, the smaller pore size of OmpC can aid in the exclusion of harmful molecules in the gut. OmpF can predominate in the aqueous habitats, and its larger pore size can assist in scavenging for scarce nutrients from the external aqueous environments. OmpX represents the smallest known channel protein. OmpX expression in Enterobacter is inducible under high osmolarity, selleckchem which is accompanied by the repressed expressions of OmpF and OmpC [4–6]. The over-expression of OmpX can balance the decreased expression of non-specific porins, OmpF and OmpC, for the exclusion of small harmful molecules. However, whether or not OmpX functions as a porin to modulate the membrane permeability is still unclear. The osmosensor Lck histidine protein kinase EnvZ can phosphorylate the response regulator OmpR, which constitutes a two-component signal transduction

and regulatory system. The reciprocal regulation of OmpF and OmpC in E. coli is mediated by phosphorylated OmpR (OmpR-P) [2, 7, 8] (Figure 1). OmpR-P binds to four (F4, F1, F2, and F3 from the 5′ to 3′ direction) and three (C1, C2, and C3) sites within the upstream regions of ompF and ompC, respectively, with each containing two tandem 10 bp subsites (‘a’ and ‘b’) bound by two OmpR-P molecules. At low osmolarity, OmpR-P tandemly binds to F1 and F2 (and somewhat loosely to F3) in order to activate the transcription of ompF; meanwhile OmpR-P occupies C1 but not C2 and C3, which is not sufficient to stimulate the transcription of ompC. With increasing osmolarity, the cellular levels of OmpR-P elevate, and OmpR-P binds to C2 and C3 cooperatively, allowing for the transcription of ompC. At high osmolarity, OmpR-P is also capable of binding to F4, which is a weak site upstream F1-F2-F3.

The other side of Ag particle facing the Si would works as the ca

The other side of Ag particle facing the Si would works as the catalyst to oxidize Si and generate electron, which generate H+ and electrons (reaction 6). The reactions at cathode (Ag facing the electrolyte) and the anode (Si contacting with Ag) sites are outlined as follow [14]. (4) (5) (6) (7) The potential of the cathode site (EH2O2 = 1.77 V vs. SHE) is higher than that of the anode site (ESi =1.2 V vs. SHE), thus a local corrosion current would flow from the cathode site to the anode site. In this case, the catalytic Ag particle would work as a redox center and act as a short-circuited VX-680 supplier galvanic cell with an

electron flow inside the Ag particle, while H+ would migrate outside the Ag particle from the anode site to the cathode site. The H+ gradient across the Ag particle from the anode site to cathode site would build-up of an electric field which would propel Ag particles (with negative charge) toward the anode site, thus, the Ag particles deposited on the surface and side of SiNWs would migrate in a vertical or horizontal direction, respectively, as shown by the yellow arrows in Figure 6. It can satisfactorily explain the perpendicular longitudinal and lateral etching pore channel in Figure 5C. Figure 6 Ag particle migration in bulk Si Crenolanib supplier driven by self-electrophoresis mode. An electric field is

built with the presence of H+ gradient across the Ag particle from the anode site to cathode site, which can propel Ag particles toward the anode site. The formation process of mesoporous structures

within the SiNWs may be consistent with that of macroporous structures, both are caused by the lateral etching of silicon, i.e., lateral motility of Ag particles. The four steps are proposed to describe the PSiNWs formation in the HF/AgNO3/H2O2 etching system. When silicon wafers were Liothyronine Sodium immersed into the etchant, Ag nanoparticles were deposited on silicon surface, as depicted in Figure 7A. According to the self-electrophoresis mode, the nucleated Ag particles would migrate down and form the SiNWs, the duration of the redox reaction couple of reactions 4 and 6 lead to the growth of SiNWs. In addition, the reaction of silver ion deposition (Ag+ + e− → Ag) is still present during the growth of SiNWs. Thus, some of the silver particles would grow into dendrite and cover the surface of SiNWs, just as Ag dendrite form in the one-step MACE [28]. As the standard reduction potential of H2O2 (1.77 eV) is larger than that of Ag (0.78 eV), the growing Ag dendritic layer can simultaneously be oxidized into Ag+ ions by H2O2 (reaction 2). The generated Ag+ ions could renucleate throughout the nanowires, as shown in Figure 7B. The horizontal and vertical migrations of Ag particles driven by self-electrophoresis finally induce perpendicular pore channels (Figure 7C).

The chemokine CXCL12, also called stromal-derived factor (SDF-1),

The chemokine CXCL12, also called stromal-derived factor (SDF-1), is the sole

ligand for CXCR4 [6]. Unlike other chemokines and their receptors, CXCR4 and SDF-1 are constitutively expressed in a variety of tissues, including the brain, heart, liver, lung, spleen and kidney [1, 7, 8]. SDF-1 is expressed in hematopoietic and non-hematopoietic tissues and was originally identified from bone marrow stromal cells as a pre-B cell growth factor, which is essential for heart, nervous system and blood vessel development. Mice with a targeted deletion of the CXCL12 gene die perinatally, whereas the CXCR4 protein is expressed mainly in neutrophilic granulocytes, macrophages and dendritic cells. The interaction between CXCR4 and SDF-1 plays an important role in the formation of embryos, the development of blood vessels and this website the heart, the homing of hematopoietic stem cells after

transplant, the transmembrane migration of inflammatory cells, T lymphocyte proliferation and the inflammatory response. After further research on the receptor, investigators found that CXCR4 is one of the most comprehensive cytokine receptors expressed in tissue, playing an important role in the growth and metastasis of a variety of malignant tumors [9]. In this article, through in vitro primary culture methods, we obtained an HCC cell line derived from the human hepatoma portal vein, which provided the experimental materials for a functional study of the role of CXCR4 in tumor cell invasiveness. To confirm

the novel role of CXCR4 in hepatocarcinogenesis, the expression levels of CXCR4 in tumor tissue, adjacent hepatic tissue and PVTT tissue selleck compound were measured. Finally, the mutual effects of CXCR4 expression and clinical pathology characteristics were discussed [10]. To further investigate the role of CXCR4 in HCC tumorigenesis and metastasis, a migration assay was performed on PVTT cells following the suppression of CXCR4 expression by the lentivirus-mediated expression of enough small hairpin RNA (shRNA). Methods Patients Patient sample exhibiting HCC with PVTT A total of 23 cases originated from the resected sample of HCC of active hepatitis combined with PVTT in the Eastern Hepatobiliary Surgery Hospital from May 2007 to May 2008. Of all of the cases, 14 cases were male and 9 were female, and the ages ranged from 28 to 66 years, with an average age of 42. The detection of hepatitis B DNA in all patients was greater than 104 (104-107) copies/ml. Nineteen of the patients had HbsAg (+), HbeAg (+) and HbcAg (+), which accounted for 82.6% of the patients; 4 cases were HbsAg (+), HbeAb (+), HbcAg (+), which accounted for 17.4%. There were 7 cases with complicating lesser tubercle hepatic cirrhosis, 10 cases with tuberculum majus liver cirrhosis, and 6 cases with mixed tuberculum liver cirrhosis. Seventeen cases had serum alpha-fetoprotein levels of greater than 20 μg/L (upper normal level), which accounts for 73.9%.

J Clin Oncol 2006, 24: 5034–5042 PubMedCrossRef 18 Coombs NJ, Go

J Clin Oncol 2006, 24: 5034–5042.PubMedCrossRef 18. Coombs NJ, Gough AC, Primrose

JN: Optimisation of DNA and RNA extraction from archival formalin-fixed learn more tissue. Nucleic Acids Res 1999, 27: e12.PubMedCrossRef 19. Board RE, Ellison G, Orr MC, Kemsley KR, McWalter G, Blockley LY, Dearden SP, Morris C, Ranson M, Cantarini MV, et al.: Detection of BRAF mutations in the tumour and serum of patients enrolled in the AZD6244 (ARRY-142886) advanced melanoma phase II study. Br J Cancer 2009, 101: 1724–1730.PubMedCrossRef 20. Kimura H, Suminoe M, Kasahara K, Sone T, Araya T, Tamori S, Koizumi F, Nishio K, Miyamoto K, Fujimura M, et al.: Evaluation of epidermal growth factor receptor mutation status in serum DNA as a predictor of response to gefitinib (IRESSA). Br J Cancer 2007, 97: 778–784.PubMedCrossRef 21. Horiike A, Kimura H, Nishio K, Ohyanagi F, Satoh Y, Okumura S, Ishikawa Y, Nakagawa K, Horai T, Nishio M: Detection of epidermal growth factor receptor mutation in transbronchial needle aspirates of non-small cell lung cancer. Chest 2007, 131: 1628–1634.PubMedCrossRef 22. Kimura H, Fujiwara Y, Sone T, Kunitoh H, Tamura T, Kasahara K, Nishio K: High sensitivity detection of epidermal

growth factor receptor mutations in the pleural effusion of non-small cell lung cancer patients. Cancer Sci 2006, 97: 642–648.PubMedCrossRef Competing interests GE, ED, GM, LF, JS, MC, MO and GS are employees and shareholders of AstraZeneca. LK is a former employee of AstraZeneca and has no additional competing interests to declare. Authors’ contributions GE carried out the molecular Navitoclax order genetic studies and drafted the manuscript. ED, GM, LK, LF and JS carried out the molecular analysis. MC, MO and GS participated in the design and coordination of the study. JM drafted the manuscript. All authors reviewed the draft manuscript and read and approved the final version for submission.”
“Introduction Dickkopf-1(DKK-1) gene was first discovered in 1998 as a head formation inducer and an antagonist of Wnt signaling pathway [1]. In normal

tissues of human body, DKK-1 mRNA was highly expressed in placenta and at a very low level in prostate only [2, 3]. Recent studies have revealed the involvement of DKK-1 protein in tumorigenesis. Its exact role in tumorigenesis, Carbohydrate however, still remains unclear. Several studies reported that the expression level of DKK-1 in different tumors was different and its biological functions were different as well [4–8]. DDK-1 expression was confirmed in several cancer cell lines derived from breast and other common cancers. DDK-1 protein secretion was documented in breast, prostate and lung cancers, but was negligible in melanoma [9]. The DKK-1 concentration was significantly higher in the serum of lung cancer patients than in that of other malignant tumor patients or healthy people.

1), M leprae TN (AL450380 1), M marinum M (CP000854 1), M para

1), M. leprae TN (AL450380.1), M. marinum M (CP000854.1), M. parascrofulaceum BAA-614 (ADNV00000000), M. smegmatis MC2 155 (CP000480.1), Mycobacterium sp. JLS (CP000580.1), Mycobacterium sp. KMS (CP000518.1), Mycobacterium sp. MCS (CP000384.1), M. tuberculosis CDC1551 (AE000516.2), M. tuberculosis H37Ra (CP000611.1), M. tuberculosis H37Rv (AL123456.2), M. tuberculosis KZN 1435 (CP001658.1), M. ulcerans Agy99 (CP000325.1) and M. vanbaalenii PYR-1 (CP000511.1). (PDF 1 MB) Additional file 3: DNA sequence alignment Selleck GSK3 inhibitor of conserved proteins in mycobacterial genomes. Sequences are from genomes of M. abscessus ATCC 19977 (CU458896.1), M. avium 104 (CP000479.1), M. avium subsp. paratuberculosis K10 (AE016958.1), M.

bovis subsp. bovis AF2122/97 (BX248333.1), M. bovis BCG Pasteur 1173P2 (AM408590.1), M. bovis BCG Tokyo 172 (AP010918.1), M. gilvum PYR-GCK (CP000656.1), M. intracellulare ATCC 13950 (ABIN00000000), M. kansasii ATCC 12478 (ACBV00000000), M. leprae Br4923 (FM211192.1), M. leprae TN (AL450380.1), M. marinum Proteasome inhibitor M (CP000854.1), M. parascrofulaceum BAA-614 (ADNV00000000),

M. smegmatis MC2 155 (CP000480.1), Mycobacterium sp. JLS (CP000580.1), Mycobacterium sp. KMS (CP000518.1), Mycobacterium sp. MCS (CP000384.1), M. tuberculosis CDC1551 (AE000516.2), M. tuberculosis H37Ra (CP000611.1), M. tuberculosis H37Rv (AL123456.2), M. tuberculosis KZN 1435 (CP001658.1), M. ulcerans Agy99 (CP000325.1) and M. vanbaalenii PYR-1 (CP000511.1). (PDF 3 MB) References 1. Kazda J: The chronology of mycobacteria and the development of mycobacterial ecology. In The ecology of mycobacteria: Impact on animal’s and human’s health. Volume 1. Edited by: Kazda J, Pavlik I, Falkinham JO, Hruska K. Dordrecht Heidelberg London New York: Springer; 2009:1–11.CrossRef 2. Radomski N, Cambau E, Moulin L, Haenn S, Moilleron R, Lucas FS: Comparison of culture methods for isolation of nontuberculous

mycobacteria from surface waters. Appl Environ Etofibrate Microbiol 2010,76(11):3514–3520.PubMedCentralPubMedCrossRef 3. Adékambi T, Drancourt M: Dissection of phylogenetic relationships among 19 rapidly growing Mycobacterium species by 16S rRNA, hsp65, sodA, recA and rpoB gene sequencing. Int J Syst Evol Microbiol 2004,54(6):2095–2105.PubMedCrossRef 4. Gomila M, Ramirez A, Lalucat J: Diversity of environmental Mycobacterium isolates from hemodialysis water as shown by a multigene sequencing approach. Appl Environ Microbiol 2007,73(12):3787–3797.PubMedCentralPubMedCrossRef 5. Mendum TA, Chilima BZ, Hirsch PR: The PCR amplification of non-tuberculous mycobacterial 16S rRNA sequences from soil. FEMS Microbiol Lett 2000,185(2):189–192.PubMedCrossRef 6. Garcia-Quintanilla A, Gonzalez-Martin J, Tudo G, Espasa M, Jiménez de Anta MT: Simultaneous identification of Mycobacterium genus and Mycobacterium tuberculosis complex in clinical samples by 5′-exonuclease fluorogenic PCR. J Clin Microbiol 2002,40(12):4646–4651.PubMedCentralPubMedCrossRef 7.