Mutation rate dynamics reflect ecological change in an emerging zoonotic pathogen

Mutation rates vary both within and between bacterial species, and understanding what drives this variation is essential for understanding the evolutionary dynamics of bacterial populations. In this study, we investigate two factors that are predicted to influence the mutation rate: ecology and genome size. We conducted mutation accumulation experiments on eight strains of the emerging zoonotic pathogen Streptococcus suis. Natural variation within this species allows us to compare tonsil carriage and invasive disease isolates, from both more and less pathogenic populations, with a wide range of genome sizes. We find that invasive disease isolates have repeatedly evolved mutation rates that are higher than those of closely related carriage isolates, regardless of variation in genome size. Independent of this variation in overall rate, we also observe a stronger bias towards G/C to A/T mutations in isolates from more pathogenic populations, whose genomes tend to be smaller and more AT-rich. Our results suggest that ecology is a stronger correlate of mutation rate than genome size over these timescales, and that transitions to invasive disease are consistently accompanied by rapid increases in mutation rate. These results shed light on the impact that ecology can have on the adaptive potential of bacterial pathogens.

Characterising the dynamics of cerebral metabolic dysfunction following traumatic brain injury: A microdialysis study in 619 patients

Traumatic brain injury (TBI) is a major cause of death and disability, particularly amongst young people. Current intensive care management of TBI patients is targeted at maintaining normal brain physiology and preventing secondary injury. Microdialysis is an invasive monitor that permits real-time assessment of derangements in cerebral metabolism and responses to treatment. We examined the prognostic value of microdialysis parameters, and the inter-relationships with other neuromonitoring modalities to identify interventions that improve metabolism. This was an analysis of prospective data in 619 adult TBI patients requiring intensive care treatment and invasive neuromonitoring at a tertiary UK neurosciences unit. Patients had continuous measurement of intracranial pressure (ICP), arterial blood pressure (ABP), brain tissue oxygenation (PbtO2), and cerebral metabolism and were managed according to a standardized therapeutic protocol. Microdialysate was assayed hourly for metabolites including glucose, pyruvate, and lactate. Cerebral perfusion pressure (CPP) and cerebral autoregulation (PRx) were derived from the ICP and ABP. Outcome was assessed with the Glasgow Outcome Score (GOS) at 6 months. Relationships between monitoring variables was examined with generalized additive mixed models (GAMM). Lactate/Pyruvate Ratio (LPR) over the first 3 to 7 days following injury was elevated amongst patients with poor outcome and was an independent predictor of ordinal GOS (p<0.05). Significant non-linear associations were observed between LPR and cerebral glucose, CPP, and PRx (p<0.001 to p<0.05). GAMM models suggested improved cerebral metabolism (i.e. reduced LPR with CPP >70mmHg, PRx <0.1, PbtO2 >18mmHg, and brain glucose >1mM. Deranged cerebral metabolism is an important determinant of patient outcome following TBI. Variations in cerebral perfusion, oxygenation and glucose supply are associated with changes in cerebral LPR and suggest therapeutic interventions to improve cerebral metabolism. Future prospective studies are required to determine the efficacy of these strategies.

Screening for type 2 diabetes: do screen-detected cases fare better?

AIMS/HYPOTHESIS

We aimed to investigate whether diabetes cases detected through screening have better health outcomes than clinically detected cases in a population-based cohort of adults who were eligible to be screened for diabetes at 10 year intervals.

METHODS

The Västerbotten Intervention Programme is a community- and individual-based public health programme in Västerbotten County, Sweden. Residents are invited to clinical examinations that include screening for diabetes by OGTTs at age 30, 40, 50 and 60 years (individuals eligible for screening, n = 142,037). Between 1992 and 2013, we identified 1024 screen-detected cases and 8642 clinically detected cases of diabetes using registry data. Clinically detected individuals were either prior screening participants (n = 4506) or people who did not participate in screening (non-participants, n = 4136). Study individuals with diabetes were followed from date of detection until end of follow-up, emigration, death or incident cardiovascular disease (CVD), renal disease or retinopathy event, and compared using Cox proportional hazard regression adjusted for calendar time, age at detection, year of detection, sex and socioeconomic status.

RESULTS

The average age at diabetes diagnosis was 4.6 years lower for screen-detected individuals compared with clinically detected individuals. Overall, those who were clinically detected had worse health outcomes than those who were screen-detected (HR for all-cause mortality 2.07 [95% CI 1.63, 2.62]). Compared with screen-detected study individuals, all-cause mortality was higher for clinically detected individuals who were screening non-participants (HR 2.31 [95% CI 1.82, 2.94]) than for those clinically detected who were prior screening participants (HR 1.70 [95% CI 1.32, 2.18]). Estimates followed a similar pattern for CVD, renal disease and retinopathy.

CONCLUSIONS/INTERPRETATION

Individuals with screen-detected diabetes were diagnosed earlier and appeared to fare better than those who were clinically detected with regard to all-cause mortality, CVD, renal disease and retinopathy. How much of these associations can be explained by earlier treatment because of screening rather than healthy user bias, lead time bias and length time bias warrants further investigation.