First, PLG-containing tubes (Qiagen Sciences, MD) were used for phenol and chloroform extraction, since they allow clean separation of the top aqueous layer by decantation after centrifugation. Second, a final step of passing the DNA through DNeasy kit columns (Qiagen Sciences, MD) was included to obtain good quality DNA for real-time PCR. B. microti and A. phagocytophilum plasmid construction Thiamine pyrophosphokinase gene of C59 wnt manufacturer B. microti (BmTPK) and APH1387 gene of A. phagocytophilum were amplified from B. microti strain RM/NS and A. phagocytophilum strain HZ, respectively, using primers listed in Table 1, which are designed specifically for RM/NS and HZ

strains genes, respectively. Table 1 Sequence of PCR primers and molecular beacon probes PCR primers/Probes/Oligos Sequence* Length Tm (°C) Size of PCR amplicon Fluorophore/Quencher RecF primer 5’ GTG GAT CTA TTG TAT TAG ATG AGG CTC TCG 3’ 30

66.1 222 bp   RecR primer 5’ GCC AAA GTT CTG CAA CAT TAA CAC CTA AAG 3’ 30 67.3   RecF3 primer 5’ GCA AGA GTT CAA ATA GAA AA 3’ 20 53.7 287 bp   RecR3 primer 5’ AAA GCT TTT GCA TAA ACA G 3’ 19 54.7   RecA3 probe 5’ CTG GCG GAT ATC CTA GGG GG CGC CAG 3’ 26 CT99021 in vitro 67.9   FAM/ BHQ-1 5BmicrotiTPK primer 5’ AAT ATT GTT GAA TGG GGA TAT TTG TG 3’ 26 64.2 600 bp   3BmicrotiTPK primer 5’ AAT AAT ATA GCT TTT CCA AAA

TAT AAC TGA C 3’ 31 60.2   5BmTPK primer 5’ Phosphatidylinositol diacylglycerol-lyase TGA GAG GAA CGA CCA TAG C 3’ 19 61.4 141 bp   3BmTPK primer 5’ CCA TCA GGT AAA TCA CAC GAA A 3’ 22 61.6   BmTPK probe 5’ CGC GTC GGT GTT GTT GAC CAG CGG CCG CG GAC GCG 3’ 35 61.5   CAL Fluor Orange 560/ BHQ-1 5ApAPH1387 primer 5’ ATG TAT GGT ATA GAT ATA GAG CTA AGT GA 3’ 29 57.8 1737 bp   3ApAPH1387 primer 5’ CTA ATA ACT TAG AAC ATC TTC ATC GTC AG 3’ 29 62.2   5Aphagocyt primer 5’ ATG GCT ACT ACG AAG GAT 3’ 18 57.9 152 bp   3Aphagocyt primer 5’ CGA AGC AAC ATC TCT ACA T 3’ 19 58.0   Aph1387 probe 5’ CGG TGC GAC AAA GAT GCC AGC ACT AAT GCG GCA CCG 3’ 36 61.9   CAL Fluor Red 610/ BHQ-2 5ACTA1 primer 5’ AGA GCA AGA GAG GTA TCC 3’ 18 58.0 104 bp   3ACTA1 primer 5’ CTC GTT GTA GAA GGT GTG 3’ 18 57.7   ACTA1 probe 5’ CGC TGC CCT ATC GAG CAC GGC ATC ATC AC GCA GCG 3’ 35 62.4   Quasar 670/ BHQ-2 RecA3MB-com oligo 5’ ttG CGC CCC CTA GGA TAT CCG Ctt 3’ 24 67.9     TPKMB-com oligo 5’ tt tCG CGG CCG CTG GTC AAC AAC ACC ttt 3’ 29 61.5     AphMB-com oligo 5’ ttt CGC ATT AGT GCT GGC ATC TTT GTC ttt 3’ 30 61.9     ActinMB-com oligo 5’ tt tGT GAT GAT GCC GTG CTC GAT AGG ttt 3’ 29 62.4     *Italicized molecular beacon sequence depicts the arm sequences whereas the sequences marked by bold letters indicate probe region of molecular beacons complementary to the target sequence.

3 M 81 – + + + – - + + + 7/10 Died 4 M 74 + – - + – + – - – 4/10 Surv. 5 F 67 + + – - – - – + – 3/10 Surv. 6 M 55 – - – + + – - + – 3/10 Surv. 7 F 76 + + – + + + – + – 7/10 Died 8 M 56 – + – + + – - – - 3/10 Surv. 9 F drug discovery 73 + – + – - + + – - 5/10 Surv. 10 M 72 – + – - – + + – - 4/10 Surv. 11 M 78 + + + + – + + – + 8/10 Died 12 M 71 – - – - – - – + – 2/10 Surv. 13 M 64 – + – - + – - – - 2/10 Surv. 14 F 68 + + – - – - + – - 3/10 Surv. 15 F 74

+ – + + – - – - – 4/10 Surv. Elderly patients and history of COPD are present in the 67% of cases, cancer and sepsis in the 53,3% of cases. The presence of anemia, diabetes mellitus and the history of received chemotherapy or radiotherapy are 40% in iur patients. Malnutrition and obesity are present in one third of our patients. Only 20% of patients did receive treatment with steroids in the last 12 months. Concerning the surgical history and the postoperative

morbidity, the results are listed in table 3. Table 3 Patients surgical characteristics and postoperative outcome n Incision Wound closure Drain Postoperative Complication Wound dehiscence observed Postoperative day 1 Kocher Separate closure No No 6 2 Midline Separate closure Yes No 9 3 Midline Separate closure Yes Pneumonia 14 4 Midline Separate closure Yes No 9 5 Midline Separate closure Yes No 7 6 Midline Separate closure Yes No 8 7 Midline Continuous closure No Fistula 7 8 Kocher Separate closure No Intraabdominal Sepsis, Abscess 9 9 Mercedes Separate closure Yes No 16 10 Kocher Separate closure No No 14 11 Midline Continuous closure Yes No 7 12 Midline Separate closure Yes Catheter Sepsis 6 13 Belnacasan nmr Midline Continuous closure Yes No 9 14 Midline Continuous closure Yes Catheter Sepsis 9 15 Midline Continuous closure Yes Fossariinae Pneumonia 8 Wound dehiscence was more often observed on the 9,2 postoperative day (ranging from the 6th to 15th). Three patients (20%) developed wound dehiscence after their initial discharge and were readmitted to our hospital. Concerning the type of incision or the abdominal closure, only the presence of interrupted suturing of linea alba (10/14) patients plays a role in the wound dehiscence. This factor factor

is a hypoestimated parameter in he past as a possible risk factor. All patients are reoperated after the wound dehiscence diagnosis and three of them (20%) died due to postoperative complication of reoperation. In one of them recurrence of wound dehiscence was observed. Regarding the preoperative risk factors, three from four (75%) patients with 7 or more risk factors did die. The abdominal closure was performed using mesh in 4 cases, a flap in 2 cases and a continuous suturing in 9 cases. Retention suture were used in 2 cases. Discussion Wound dehiscence is a mechanical failure of wound healing, remains a problem and it can be affected by multiple factors. Pre-operative conditions especially in elective operations should be recommended to reduce or eliminate the risk.

Recently Kreider and colleagues studied the effect of a specific exercise program in overweight woman with a VLCKD or normal carbohydrate content diet [17], but only few papers that focus specifically on the influence of VLCKD on sports performance have been published, and with conflicting results: showing benefits [18, 19], no effect [20, 21] check details or impairment [22, 23]. The

present study set out to investigate if a VLCKD could be useful for athletes, especially for those engaged in sports involving weight categories where weight loss without negative changes in the body composition (i.e. loss of muscle mass) and performance is often needed. To the best of our knowledge no previous study has investigated the influence of a VLCKD on strength performance

and on explosive strength performance in competitive athletes. Methods Subjects Nine high-level male athletes (age 21 ± 5.5), elite artistic gymnasts, were recruited for this study. Subjects competed in the Italian premier league for the CorpoLibero Gymnastics Team ASD, Padova, Italy and include two athletes belonging to the Italian national team. The mean volume of weekly training was about 30 hours. During the VLCKD period (30 days) the athletes were asked to keep to their normal www.selleckchem.com/products/PF-2341066.html training schedule. During a preliminary meeting it was explained that during the first three weeks it was necessary to almost totally exclude carbohydrates and a detailed menu containing permitted and non-permitted foods was provided to each participant, along with the components of the ketogenic diet with phytoextracts diet described below. All gymnasts read and signed an informed consent with the testing procedures approved by the council of the Human Anatomy and Physiology Department, University of Padova. Experimental design Subject measurements were taken, according to the methodology described

below, before starting the VLCKD and repeated after thirty days of VLCKD. Since we chose a within subject design to strengthen the study (Subjects served as Osimertinib price their own control), the athletes were re-tested during a second training period comparable in terms of intensity and volume of training to the first one.. The work load between athletes was similar because the team training regimes are strictly controlled, and recorded, due to the elite nature of their competition. The protocol took place three months later to ensure a comparable training load and achieve this goal the intensity and volume of training during the two periods (hours of training, kind of exercises, etc.) was carefully measured. During the second experimental session the subjects followed their normal diet (WD) instead of the VLCKD. The test procedure before and after WD was the same as the first testing session (Figure 1).

These observations allowed us to rule out the participation of σT and σE in the control of sigF expression. To further verify if the promoter region upstream of sigF is controlled by σF, we overexpressed sigF in the parental strain from an additional plasmid-encoded copy of the gene under the control of a constitutive

promoter (construct pCM30) and measured β-galactosidase activity in these cells harboring either pCKlac53-1 or pCKlac53-2. Overexpression www.selleckchem.com/GSK-3.html of sigF in cells with the construct containing the complete sigF promoter (pCK53-1) led to an increase in β-galactosidase activity, whereas no difference was observed in cells harboring the promoterless construct pCKlac53-2 (Figure 3B). Similarly, higher β-galactosidase activity was observed in sigF overexpressing cells bearing the construct containing the promoter sequence motifs upstream from CC3254 (pCKlac54-1) when compared to the parental strain carrying the same construct or sigF overexpressing cells harboring the construct containing only the −10 motif of the promoter sequence of CC3254-CC3255-CC3256-CC3257 (pCKlac54-2) (Figure 3B). Therefore, these results confirm

that specific and highly similar promoter sequence motifs found upstream from sigF-CC3252 and CC3254-CC3255-CC3256-CC3257 are required for the control of these transcriptional units by σF. CC3252 negatively regulates σF regulon expression The chromosomal organization of CC3252 and Dabrafenib molecular weight sigF in a putative operon suggests that CC3252 could be involved in the same regulatory pathway of σF. To test the assumption that CC3252 could control σF activity, we monitored the expression of σF-dependent genes in parental cells overexpressing CC3252 from a plasmid-encoded copy of the gene under the control of the constitutive lacZ promoter present in vector pJS14. For that, cells overexpressing

CC3252 were stressed or not with dichromate and compared in qRT-PCR experiments with cells harboring the empty vector pJS14 or cells without this vector under the same conditions. According to qRT-PCR experiments, expression of genes GNA12 CC2906 and CC3255 was slightly reduced in cells overexpressing CC3252 under no stress conditions, when compared to cells with the empty vector pJS14 or cells without the vector (Figure 4). However, induction of CC2906 and CC3255 expression under dichromate stress was clearly absent in CC3252 overproducing cells, when compared to cells not overexpressing CC3252 (Figure 4). No difference could be found in the expression levels of two control genes (CC1039 and CC0566) when we compared cells overexpressing CC3252 or not (data not shown). This observation rules out a possible nonspecific effect due to overproduction of the protein. Taken together, these data indicate that CC3252, here denominated nrsF, acts as a negative regulator of σF function in C. crescentus.

These two subclusters correspond to sequence type ST26 [24], MLVA panel 1 genotype 24 (subcluster Navitoclax mw A1) and 77 (subcluster A2, Figure 1 and Figure 3), and together correspond to cluster A in [25] (Figure 3). The third

subcluster, from genotype 19 to 74 corresponds to MLST sequence type 23, MLVA-16 panel 1 genotypes 23, 69 and 70, and is cluster B in [25] (Figure 1 and Figure 3). This subcluster was composed of 78 strains. Sixty-four were obtained from porpoises, 12 from 4 species of dolphins (9 from Atlantic white sided dolphin (Lagenorhynchus acutus), one from a white-beaked dolphin (Lagenorhynchus albirostris), one from a bottlenose dolphin (Tursiops truncatus), one from a common dolphin (Delphinus delphis), and one from a minke whale (Balaenoptera acutorostrata) isolated in Norway in 1995 [10] (Figure 1). An exception was the bmar111 (strain number M490/95/1), with the genotype 20, isolated in Scotland from a harbour (or common) seal (Phoca vitulina) and which belongs to the B. ceti group (Figure 1). This is, however, in agreement with previous observations, either phenotypic

[26] or molecular, including MLVA typing [25]. This particular strain carries the two specific IRS-PCR fragments (II and III) of the B. ceti strains [11], and the PCR-RFLP pattern of the omp2 genes is similar to that of Brucella strains isolated Selisistat molecular weight from porpoises [8]. The 93 representative B. pinnipedialis strains presented 42 different genotypes (75–116) (Figure 2) corresponding to cluster C in [25]. This group of isolates could similarly be further divided in three major subclusters. The first subcluster

(genotype 75 to 101) was composed of several seal isolates Epothilone B (EPO906, Patupilone) (harbour seal and grey seal (Halichoerus grypus)) and the isolate from a European sea otter (Lutra lutra). It corresponds to MLST sequence type 25, MLVA panel 1 genotypes 25, 72, 73, and cluster C2 in [25]. The second subcluster (MLVA genotypes 102 to 107) corresponds to MLST sequence type 24, MLVA panel 1 genotypes 71 and 79 and is cluster C1 in [25]. Interestingly, the hooded seal isolates (15 strains) were exclusively clustered in 9 closely related genotypes, forming the third subcluster of the pinniped isolates (genotype 108 to 116) called C3 in [25]. Most of the hooded seal isolates analysed in this study were isolated in Norway in 2002 [27] and there were also 4 hooded seal isolates from Scotland that clustered with the Norwegian isolates. One of the 93 strains of the B. pinnipedialis group was obtained from a cetacean. This strain (M192/00/1), identified as bmar160 with the genotype107 in Figure 2, was isolated from a minke whale in Scotland in 2000. This strain was also demonstrated as a B. pinnipedialis strain by other molecular markers, as described by Maquart et al. [12] and Groussaud et al. [25].

16S rRNA Clone Library The amount of sampled material was limited due to little faeces in the rectum of the polar bears, and only three faeces samples gave sufficient DNA yield to make 16S rRNA gene clone libraries. A 16S rRNA gene clone library was made with DNA extracted from CYC202 faeces from bear no. 6, 7 and 8. Total genomic DNA was extracted using the QIAmp DNA stool kit (Qiagen, Solna, Sweden) according to the protocol provided by the producer, and DNA quantified using a NanoDrop® ND-1000 Spectrophotometer (260 nm) (Thermo Fisher Scientific, Waltham, USA). Two parallel 16S rRNA gene PCR amplifications on DNA from each of the three animals were performed,

using primers 16S-27F and 16S-1494R (Table 6), in a reaction mixture containing 1× HotStartTaq DNA master mix (Qiagen), 0.3 μM of each primer, and 20 ng of extracted DNA solution in a final volume of 50 μl. PCR amplification was initiated by denaturation at 95°C for 15 min and then 30 cycles of 94°C for 30 s, 50°C for 30 s, and 72°C for 2 min, with a final extension at 72°C for 10 min. The 16S rRNA gene amplicons were pooled and cloned using the TOPO TA Cloning® Kit for Sequencing (Invitrogen, California, USA), and transformed by heat-shock into One Shot® Competent Escherichia coli cells (Invitrogen). Positive clones were randomly selected and recombinant plasmids extracted using QIA prep spin miniprep kit (Qiagen). Extracted DNA was quantified using

a NanoDrop ND-1000 Spectrophotometer (260 Dorsomorphin nm), and sequenced on a 3130 Genetic analyzer (Applied Biosystems, Foster City, USA) using the ABI BigDye Terminator G protein-coupled receptor kinase chemistry. The sequencing primers (Invitrogen) used were M13 forward primer, M13 reverse primer, and the universal bacterial 16S

rRNA primer Bact338, corresponding to nucleotide position 338-355 of E. coli (Table 6). Table 6 Primers used for PCR and sequencing Name Primer sequence (5′-3′) Gene target Reference BlaF CATTTCCGTGTCGCCCTTATTCC bla TEM [52] BlaR GGCACCTATCTCAGCGATCTGTCTA bla TEM [52] TemI3 TGGTTTATTGCTGATAAATCTGGAG bla TEM [15] TemI5a TTAAAAGTGCTCATCATTGGAAAAC bla TEM [15] TemI5b CTGTTGAGATCCAGTTCGATGTA bla TEM [15] 16S-27F AGAGTTTGATCCTGGCTCAG 16S rRNA [53] 16S-1494R CTACGGCTACCTTGTTACGA 16S rRNA [53] Bact338 GCTGCCTCCCGTAGGAGT 16S rRNA [54] Sequence analysis The 16S rRNA gene sequences were assembled using the program Lasergene™ Seqman v. 7.1.0. (DNASTAR Inc.). Putative chimeric sequences were evaluated using the Chimera Detection Program which is part of the SimRank 2.7 package available through the Ribosomal Database Project (RDP) [42]. Sequences generated were first compared to sequences obtained from the RDP II (Classifier: Naive Bayesian rRNA Classifier Version 1.0, November 2003; The nomenclature taxonomy of Garrity and Lilburn, release 6.0) and then compared to GenBank sequences using BLAST (Basic Local Alignment Search Tool) [43]. The 16S rRNA gene sequences were automatically aligned by CLUSTAL-W in the software package BioEdit (v. 5.0.9) to give a uniform length.

coli or in Klebsiella spp. (Figure 1). Figure 1 Multi-step selection of resistance in E. coli (A) and Klebsiella spp. (B) at plasma concentration of fluoroquinolones. 1, 5, 10 step: number of passages on antibiotic BYL719 supplier gradient agar plates. 10 step free: passages on antibiotic free agar plates. Black bars: prulifloxacin; White bars: ciprofloxacin; Dotted bars: levofloxacin. Characterization of acquired resistance Strains of E. coli that were

selected by the multi-step assay and were able to maintain their resistance after 10 passages in antibiotic-free medium, were evaluated for acquired resistance. Among 16 resistant mutants, alterations in both gyrA and parC were found in 12 mutants for ciprofloxacin (n = 5) and prulifloxacin (n = 7), while only HER2 inhibitor alterations in gyrA were found for levofloxacin. As reported in table 4, the 4 strains resistant to levofloxacin showed changes in Ser83Leu and Asp87Asn; while in ciprofloxacin- and prulifloxacin-resistant mutants, the mutations identified were Ser83Leu in GyrA and Ser80Ile in ParC. The same mutations were

not found in the respective parent strains. Table 4 Amino acid changes encoded by mutations in gyrA, gyrB, parC, and parE in E. coli   Replacement in QRDR Drug GyrA GyrB ParC ParE LVX (n = 4) Ser83Leu (4) Asp87Asn (4) – - – CIP (n = 5) Ser83Leu (5) – Ser80Ile (5) – PRU (n = 7) Ser83Leu (7) – Ser80Ile (7) – Discussion Wild-type E. coli and K. pneumoniae clinical isolates are susceptible to quinolones, but resistance to these agents in Gram-negative bacteria has increased in recent years, probably caused by excessive and inappropriate use of Buspirone HCl these drugs [18]. Particularly, due to under-dosing and mono-therapy against moderately susceptible pathogens, FQ resistance has developed among common pathogens, like E. coli and Klebsiella spp., mainly conferred by ESBLs and AmpC enzymes [19]. ESBL production has been reported to be two times more common in infected patients who received ciprofloxacin than in those who did not (15% vs

7.4%) [8]. In a study performed over 5 years in Croatia on changes in susceptibility of E. coli from UTI, Moeal et al have shown a statistically significant change in antimicrobial resistance over that period only for ciprofloxacin [20]. This has been hypothesized to be related to the inappropriate use of quinolones for humans as well as in veterinary medicine [21]. Prolonged use (> 20 days) of low dose (250 mg twice a day) of the more potent fluoroquinolones such as ciprofloxacin or levofloxacin, has been shown to be the most significant risk factor for acquisition of resistance [22, 23]. Strategies to counteract bacterial resistances include use of the appropriate dosages of these molecules for the correct indication and/or use of synergistic combinations, particularly in the more complicated infections.

When the pristine resistive memory device is formed using positive polarity bias on the TE, it is termed as PF, while the negative voltage-formed device is termed GSI-IX ic50 as an NF device. PF devices with similar switching behavior are obtained using different high-κ oxide films of AlOx,

GdOx, HfOx, and TaOx. The switching mechanism is the formation/oxidation of oxygen vacancies in a conducting filament by controlling the migration of oxygen ions through the electrically formed interfacial layer. This unique phenomenon helps to design high-density cross-point memory using an IrOx/AlOx/W structure. This cross-point memory was forming-free, exhibiting 1,000 consecutive ‘dc’ cycles at a current compliance (CC) of <200 μA and a small operation voltage of ±2 V, highly uniform switching (yield >95%) with multilevel capability (at least four different levels of low resistance state (LRS)). The device can be switched even using a very small current of 10 μA, which makes it useful for low power applications. The surface

morphology and roughness of the structure were observed by atomic force microscopy (AFM). The device size and interfaces of layers were investigated by transmission electron microscopy (TEM). These observations show that the improved performance of this device structure can be attributed to the electrically formed O-rich https://www.selleckchem.com/products/Neratinib(HKI-272).html interfacial layer at the top electrode/filament interface. The devices have also shown good read endurance of >105 cycles and data retention at 85°C under a

low CC of 50 μA. Methods Resistive switching memory devices using high-κ oxides AlOx, GdOx, HfOx, and TaOx in a standard via-hole IrOx/high-κx/W structure (Device: S1) were fabricated. A W layer with a thickness of approximately 100 nm as a bottom electrode (BE) was deposited on SiO2 (200 nm)/Si substrates. Figure  1 shows an AFM image taken in tapping mode using an Innova Scanning Probe Microscope system (Bruker, Madison, WI, USA) of a deposited W film surface. The average and root mean square (RMS) roughness of the surface were 0.91 and 1.18 nm, respectively. An SiO2 layer with a thickness of approximately 150 old nm was then deposited at low temperature on each W BE. Photolithography and dry etching techniques were used to form holes of different sizes in the range of 0.4 to 8 μm in the structure. Then, AlOx and HfOx films were deposited by sputtering, and GdOx and TaOx films were deposited by electron beam evaporation. The thickness of each high-κ film was 10 to 15 nm. The top electrode (TE) of IrOx(approximately 200 nm thick) was deposited by reactive sputtering using a pure Ir target and O2 as the reactive gas. The final devices with a structure of IrOx/high-κx/W were obtained after a lift-off process. The structure of the memory devices and thicknesses of all deposited layers were observed by TEM at an energy of 200 keV.

Interestingly, reads assigned to Gardnerella were only identified in 3/8 urine samples, even though this genus was the 3rd most abundant group in the pooled sequence

MK-2206 order dataset for both the V1V2 and V6 regions (Figure 2A). Three other genera and a group of 5 genera were identified by reads belonging to 3 or 2 urine samples, respectively. 24 genera were only detected in 1 out of the 8 samples. Species richness and diversity estimates of the female urine microbiota Bacterial taxonomic richness and diversity varied greatly among urine samples investigated in this study. Community richness and diversity were determined using rarefaction plots, Chao1 and Shannon index estimations (Figure 3 and Table 2). Figure 3 Number of OTUs as function of the total number of sequences. A and B: Rarefaction curves of individual samples for the V1V2 (A) and the V6 datasets (B). Curves were generated at 3% genetic difference using MOTHUR v1.17.0 [39]. C and D: Rarefaction curves of the pooled dataset for both V1V2 reads (C) and V6 reads (D). OTUs with ≤3%, ≤6% and ≤10% pairwise sequence selleck products difference generated using MOTHUR v1.17.0 [39] are assumed to belong to the same species, genus and family, respectively. Rarefaction curves were generated for 3% genetic difference level (e.g., at the species level).

The number of OTUs calculated for the eight individual samples ranged from 20-504 and 63-499 OTUs for the V1V2 and V6 regions, respectively 4��8C (Figure 3A, B and Table 2). OTU numbers of the total bacterial

community in the female urine at 3% difference for the V1V2 sequence pool was calculated to 1209 OTUs and to 1435 OTUs for the V6 sequence pool (Figure 3C, D and Table 2). Furthermore, total unique OTUs for the V1V2 pooled reads were 1354 and for the V6 pooled reads 2069 (Table 2). To compare the diversity between the eight different urine samples, the Shannon diversity index was determined both with the original, and with normalized numbers of sequences (Table 2). There was no substantial difference between the two Shannon indices calculated for the same sample. Discussion In this work we sequenced two different variable regions of 16S rDNA isolated from eight culture-negative urine samples. Urine samples are at risk of contamination by the bacterial flora of the female urogenital system [82, 83], therefore sampling of mid-stream urine was performed by the clean catch method, under guidance of an experienced urotherapy nurse. To avoid further bacterial growth, which could skew the results, the samples were kept on ice and analyzed within an hour. Amplicon lengths used here exceed the typical fragment size (150-200 bp) of circulating cell-free DNA in urine [84], thus reducing the frequency of such DNA in our analyses.

This richness is considerably higher than the 34 to 72 phylotypes and the 6 to 30 genera previously described using conventional cloning and sequencing [15, 16]. The predominant taxa belonged to Firmicutes (genus Streptococcus, family Veillonellaceae, genus

Granulicatella), Proteobacteria (genus Neisseria, Haemophilus), Actinobacteria (genus Corynebacterium, Rothia, Actinomyces), Bacteroidetes (genus Prevotella, Capnocytophaga, Porphyromonas) and Fusobacteria (genus Fusobacterium) (Additional file 4). Figure 2 The relative abundance of OTUs per individual. Relative abundance of OTUs based on all unique sequences (0%, solid lines) and OTUs within genetic distances that do not exceed 3% difference (3%, dashed lines) per individual S1, S2 and S3, respectively. The x-axis indicates the individual OTUs, ranked according to their relative abundance (high BGB324 manufacturer to low). The y-axis indicates the cumulative abundance of the OTUs. About 100 “”species-level”" phylotypes (118, 97 and 112 phylotypes in the microbiome of individual S1, S2 and S3, respectively) belonged to abundant OTUs of the individual microbiome (Additional file 1). A phylotype was considered abundant if it contributed to at least 0.1% of the microbiome. These abundant phylotypes together contributed to 92 – 93% of each microbiome. As with a pooled oral microbiome [4] and

individually Selleckchem Luminespib sequenced gut microbiomes [13], each individual oral microbiome in this study was dominated by a few sequences while most sequences were rare and contributed to the “”long tail”" effect (Figure 2). Overlap of three individual oral microbiomes Unique sequences Twenty-six percent (1660 sequences) of the unique sequences were found in all three microbiomes and 65% in at least

two microbiomes (Figure 3A). Of all reads, 66% belonged to sequences that were shared by three microbiomes (Table 2). Nine sequences were highly abundant (0.5 – 5.8% of the reads) across all individuals: they contributed to 11%, 9% and 21% of the microbiome of individuals S1, S2 and S3, respectively (the full list of the taxonomy and abundance of the overlapping sequences is given in Additional file 5). Two of these sequences were assigned to the genus Streptococcus, two to the family Veillonellaceae, one each to the genera Granulicatella (Firmicutes), Corynebacterium, Rothia (Actinobacteria), Porphyromonas DOCK10 (Bacteroidetes) and Fusobacterium (Fusobacteria). Figure 3 The extent of overlap of oral microbiome between three individuals. The extent of overlap between subjects S1 (pink circle), S2 (light blue circle) and S3 (yellow circle) at the level of A) unique sequences, B) OTUs clustered at 3% difference and C) higher taxa (genus or more inclusive taxon). The data was obtained by combining all samples of the respective individual microbiome. The Venn Diagrams show that 26% of the unique sequences, 47% of the OTUs and 72% of the higher taxa were common (area in grey) to the three individuals.