PCR-based prescreening for clones with DNA imports in strain 26695 uvrA Due to the low recombination frequency in 26695 uvrA, it was necessary to screen the Rif resistant clones after transformation in order to distinguish recombinants from spontaneous mutants. This was accomplished by allele-specific PCR using the primers HPrpoB-IscrX and HPrpoB-4, which specifically detect the Rif resistance mediating point mutation in strain J99-R3 [12, 46]. PCR positive clones were used for sequencing as described above. UV irradiation of mutant

strains Bacteria were cultured on blood agar plates for find more 24 h as described above. Cells were then suspended in phosphate buffered saline (PBS) and appropriate dilutions to obtain ~100, 500 and 1,000 colonies were plated on blood agar plates in two triplicate batches. As a control, the

first batch was not exposed to UV light to obtain the total cell number. The plates of the second batch were placed under a UV-C lamp (OSRAM HNS 30 W OFR, wavelength 254 nm) for two seconds at click here a distance of 40 cm, corresponding to approximately 100 J/m2. All plates were incubated for 72 h as previously described, colonies were counted and the percentage of surviving cells was calculated. Growth properties of H. pylori strains Growth curves were monitored in liquid cultures (BHI broth including 10% horse serum and antibiotics). Strains were grown for

<24 h on blood agar plates and then harvested in BHI broth. The OD600 of the suspension was measured and diluted to a starting concentration of 2.1 × 107 bacteria/ml. Cultures were then incubated at 37°C in a rotary shaker (175 rpm) under microaerobic conditions. The optical density was measured at regular intervals. Statistical methodology Statistical analysis was performed using Bayesian model comparison, where two competing hypotheses are weighted against each other by computing the ratio of probabilities of the observed data under the two hypotheses. This ratio is called a Bayes Factor (see refs. [47, 48] for reviews). A benefit of this approach is that it accounts for the relative Orotic acid complexity of the hypotheses, so that the more complex one is validated only if the data justifies it. Interpretation of the Bayes Factor was done following the scale of Jeffreys [49]: Negative (<1); Barely worth mentioning (1–3); Substantial (3–10); Strong (10–30); Very strong (30–100); Decisive (>100). When the Bayes Factor could not be analytically computed, the Bayes Information Criterion (BIC; refs. [47, 50] was used as an estimate: (1) where l 1 and l 2 are the maximized value of the log-likelihood under the two models, k 1 and k 2 the number of parameters in the two models, and n the number of observations.