We established two mouse interspecific backcross DNA panels, one containing 94 N2 animals from the cross (C57BL/6J x Mus spretus)F1 x C57BL/6J, and another from 94 N2 animals from the reciprocal backcross (C57BL/6J x SPRET/Ei)F1 x SPRET/Ei. We prepared large quantities of DNA from most tissues of each animal to create a community resource of interspecific backcross DNA for use by laboratories interested in mapping loci in the mouse. Initial characterization of the genetic maps of both panels has been completed. We used MIT SSLP markers, proviral loci, and several other sequence-defined genes to anchor our maps to other published maps. The BSB panel map (from the backcross to C57BL/6J) contains 215 loci and is anchored by 45 SSLP and 32 gene sequence loci. The BSS panel map (from the backcross to SPRET/Ei) contains 451 loci and is anchored by 49 SSLP loci, 43 proviral loci, and 60 gene sequence loci. To obtain a high density of markers, we used motif-primed PCR to "fingerprint" the panel DNAs. We constructed two maps, each representing one of the two panels. All new loci can be located with a high degree of certainty on the maps at current marker density. Segregation patterns in these data reveal several examples of transmission ratio distortion and permit analysis of the distribution of crossovers on individual chromosomes.
Background Prevalence and load of airway bacteria in stable and exacerbated chronic obstructive pulmonary disease (COPD) has been previously studied using microbiological culture. Molecular techniques, such as quantitative PCR (qPCR), may be more informative. Methods In this study, 373 sputum samples from 134 COPD outpatients were assessed for prevalence and load of typical airway bacteria (Haemophilus influenzae, Streptococcus pneumoniae, Moraxella catarrhalis) by multiplex qPCR, with 176 samples analysed for atypical bacteria. Paired stable and exacerbation typical bacteria data were compared in 52 patients. We compared routine culture with qPCR in 177/373 samples. Results Typical bacteria were more prevalent in exacerbation than stable-state paired samples: 30/52 (57.7%) vs. 14/52 (26.9%); p¼0.001. In patients who were bacteria-positive at both time points, mean (61 SEM) load was significantly higher at exacerbation than stable state ( vs. cfu/ml), constituting a 20-fold increase (p¼0.011). qPCR was more discriminatory at detecting typical bacteria than microbiological culture (prevalence 59.3% vs. 24.3%; p<0.001). At stable state, higher airway bacterial load correlated with more severe airflow limitation (FEV 1 % predicted) (r¼À0.299; p¼0.033) and higher inhaled corticosteroid dosage (r¼0.382; p¼0.008). Mean C-reactive protein was higher in bacterial-associated exacerbations (35.0 Vs 25.1 mg/L; p¼0.032). Conclusions Airway bacterial prevalence and load increase at COPD exacerbations and are an aetiological factor. qPCR is more discriminatory than culture, identifying higher airway bacterial prevalence. Exacerbations associated with bacterial detection showed a higher mean C-reactive protein level. In the stable state, airway bacterial load is related to more severe airflow limitation and higher inhaled corticosteroid dosage used.
BackgroundSputum and blood eosinophil counts predict corticosteroid effects in COPD patients. Bacterial infection causes increased airway neutrophilic inflammation. The relationship of eosinophil counts with airway bacterial load in COPD patients is uncertain. We tested the hypothesis that bacterial load and eosinophil counts are inversely related.MethodsCOPD patients were seen at stable state and exacerbation onset. Sputum was processed for quantitative polymerase chain reaction detection of the potentially pathogenic microorganisms (PPM) H. influenzae, M. catarrhalis and S. pneumoniae. PPM positive was defined as total load ≥1 × 104copies/ml. Sputum and whole blood were analysed for differential cell counts.ResultsAt baseline, bacterial counts were not related to blood eosinophils, but sputum eosinophil % was significantly lower in patients with PPM positive compared to PPM negative samples (medians: 0.5% vs. 1.25% respectively, p = 0.01). Patients with PPM positive samples during an exacerbation had significantly lower blood eosinophil counts at exacerbation compared to baseline (medians: 0.17 × 109/L vs. 0.23 × 109/L respectively, p = 0.008), while no blood eosinophil change was observed with PPM negative samples.ConclusionsThese findings indicate an inverse relationship between bacterial infection and eosinophil counts. Bacterial infection may influence corticosteroid responsiveness by altering the profile of neutrophilic and eosinophilic inflammation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12931-017-0570-5) contains supplementary material, which is available to authorized users.
The complete 184,457-bp sequence of the aromatic catabolic plasmid, pNL1, from Sphingomonas aromaticivorans F199 has been determined. A total of 186 open reading frames (ORFs) are predicted to encode proteins, of which 79 are likely directly associated with catabolism or transport of aromatic compounds. Genes that encode enzymes associated with the degradation of biphenyl, naphthalene,m-xylene, and p-cresol are predicted to be distributed among 15 gene clusters. The unusual coclustering of genes associated with different pathways appears to have evolved in response to similarities in biochemical mechanisms required for the degradation of intermediates in different pathways. A putative efflux pump and several hypothetical membrane-associated proteins were identified and predicted to be involved in the transport of aromatic compounds and/or intermediates in catabolism across the cell wall. Several genes associated with integration and recombination, including two group II intron-associated maturases, were identified in the replication region, suggesting that pNL1 is able to undergo integration and excision events with the chromosome and/or other portions of the plasmid. Conjugative transfer of pNL1 to another Sphingomonas sp. was demonstrated, and genes associated with this function were found in two large clusters. Approximately one-third of the ORFs (59 of them) have no obvious homology to known genes.
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