Geographic distribution and molecular diversity of Bartonella infections in moose, Alces alces, in Finland.

Moose, Alces alces (Artiodactyla: Cervidae) in Finland are heavily infested with deer keds, Lipoptena cervi (Diptera: Hippoboschidae). The deer ked, which carries species of the genus Bartonella, has been proposed as a vector for the transmission of bartonellae to animals and humans. Previously, bartonella DNA was found in deer keds as well as in moose blood collected in Finland. We investigated the prevalence and molecular diversity of Bartonella spp. infection from blood samples collected from free-ranging moose. Given that the deer ked is not present in northernmost Finland, we also investigated whether there were geographic differences in the prevalence of bartonella infection in moose. The overall prevalence of bartonella infection was 72.9% (108/148). Geographically, the prevalence was highest in the south (90.6%) and lowest in the north (55.9%). At least two species of bartonellae were identified by multilocus sequence analysis. Based on logistic regression analysis, there was no significant association between bartonella infection and either age or sex; however, moose from outside the deer ked zone were significantly less likely to be infected (P<0.015) than were moose hunted within the deer ked zone.

Standard genotyping overestimates transmission of Mycobacterium tuberculosis among immigrants in a low incidence country.

Immigrants from high tuberculosis (TB) incidence regions are a risk group for TB in low-incidence countries such as Switzerland. In a previous analysis of a nationwide collection of 520 Mycobacterium tuberculosis isolates from 2000-2008, we identified 35 clusters comprising 90 patients based on standard genotyping (24-loci MIRU-VNTR and spoligotyping). Here, we used whole genome sequencing (WGS) to revisit these transmission clusters. Genome-based transmission clusters were defined as isolate pairs separated by ≤12 single nucleotide polymorphisms (SNPs). WGS confirmed 17/35 (49%) MIRU-VNTR clusters; the other 18 clusters contained pairs separated by >12 SNPs. Most transmission clusters (3/4) of Swiss-born patients were confirmed by WGS, as opposed to 25% (4/16) of clusters involving only foreign-born patients. The overall clustering proportion using standard genotyping was 17% (90 patients, 95% confidence interval [CI]: 14-21%), but only 8% (43 patients, 95% CI: 6-11%) using WGS. The clustering proportion was 17% (67/401, 95% CI: 13-21%) using standard genotyping and 7% (26/401, 95% CI: 4-9%) using WGS among foreign-born patients, and 19% (23/119, 95% CI: 13-28%) and 14% (17/119, 95% CI: 9-22%), respectively, among Swiss-born patients. Using weighted logistic regression, we found weak evidence for an association between birth origin and transmission (aOR 2.2, 95% CI: 0.9-5.5, comparing Swiss-born patients to others). In conclusion, standard genotyping overestimated recent TB transmission in Switzerland when compared to WGS, particularly among immigrants from high TB incidence regions, where genetically closely related strains often predominate. We recommend the use of WGS to identify transmission clusters in low TB incidence settings.

An intercontinental comparison of chironomid palaeotemperature inference models: Europe vs North America

Chironomid-temperature inference models based on North American, European and combined surface sediment training sets were compared to assess the overall reliability of their predictions. Between 67 and 76 of the major chironomid taxa in each data set showed a unimodal response to July temperature, whereas between 5 and 22 of the common taxa showed a sigmoidal response. July temperature optima were highly correlated among the training sets, but the correlations for other taxon parameters such as tolerances and weighted averaging partial least squares (WA-PLS) and partial least squares (PLS) regression coefficients were much weaker. PLS, weighted averaging, WA-PLS, and the Modern Analogue Technique, all provided useful and reliable temperature inferences. Although jack-knifed error statistics suggested that two-component WA-PLS models had the highest predictive power, intercontinental tests suggested that other inference models performed better. The various models were able to provide good July temperature inferences, even where neither good nor close modern analogues for the fossil chironomid assemblages existed. When the models were applied to fossil Lateglacial assemblages from North America and Europe, the inferred rates and magnitude of July temperature changes varied among models. All models, however, revealed similar patterns of Lateglacial temperature change. Depending on the model used, the inferred Younger Dryas July temperature decrease ranged between 2.5 and 6°C.