Ecological and genetic analysis of copper and streptomycin resistance in Pseudomonas syringae pv. syringae

Strains of Pseudomonas syringae pv. syringae resistant to copper, streptomycin, or both compounds were recovered from symptomless and diseased tissue of four woody hosts in three nurseries in Oklahoma. In strains resistant to copper and streptomycin (Cu^r Sm^r), resistance to both compounds was cotransferred with a single plasmid which was either 68, 190, or 220 kilobase pairs (kb). All Cu^s Sm^r strains contained a 68-kb conjugative plasmid. Cu^r Sm^s, strains contained one plasmid which varied in size from 60 to 73 kb. All conjugative plasmids which transferred streptomycin resistance contained sequences homologous to the strA and strB Sm^r genes from the broad-host-range plasmid RSF1010. The Sm^r determinant was subsequently cloned from a 68-kb Cu^r Sm^r plasmid designated pPSR1. A restriction map detailing the organization of the homologous Sm^r genes from pPSR1 and RSF1010 and cloned Sm^r genes from P. syringae pv. papulans and Xanthomonas campestris pv. vesicatoria revealed the conservation of all sites studied. The Cu^r genes cloned from P. syringae pv. tomato PT23 and X. campestris pv. vesicatoria XV10 did not hybridize to the Cu^r plasmids identified in the present study, indicating that copper resistance in these P. syringae pv. syringae strains may be conferred by a distinct genetic determinant.Peer reviewedPlant Patholog

Choosing what works for whom: towards a better use of mechanistic knowledge in clinical practice

Abstract Background Clinicians commonly try to use mechanism-based knowledge to make sense of the complexity and uncertainty of chronic pain treatments to create a rationale for their clinical decision-making. Although this seems intuitive, there are some problems with this approach. Discussion The widespread use of mechanism-based knowledge in clinical practice can be a source of confusion for clinicians, especially when complex interventions with different proposed mechanisms of action are equally effective. Although the available mechanistic evidence is still of very poor quality, in choosing from various treatment options for people with chronic pain, an approach that correctly incorporates mechanistic reasoning might aid clinical thinking and practice. Conclusion By explaining that not all evidence of mechanism is the same and by making a proposal to start using mechanism-based knowledge in clinical practice properly, we hope to help clinicians to incorporate mechanistic reasoning to prioritize and start choosing what may best work for whom