Hans Geir Eiken

Senior Research Scientist

(+47) 996 29 966
hansgeir.eiken@nibio.no

Place
Bergen

Visiting address
Thormøhlensgate 55, 5006 Bergen

To document

Abstract

Despite the high density of brown bears (Ursus arctos piscator) on the Kamchatka peninsula their genetic variation has not been studied by STR analysis. Our aim was, therefore, to provide population data from the Kamchatka brown bear population applying a validated DNA profiling system. Twelve dinucleotide STRs commonly used in Western-European (WE) populations and four additional ones (G10C, G10J, G10O, G10X), were included. Template input ≥ 0.2 ng was successfully amplified. Measurements of precision, stutter and heterozygous balance showed that markers could be reliably genotyped applying the thresholds used for genotyping WE brown bears. However, locus G10X revealed an ancient allele-specific polymorphism that led to suboptimal amplification of all 174 bp alleles (Kamchatka and WE). Allele frequency estimates and forensic genetic parameters were obtained from 115 individuals successfully identified by genotyping 434 hair samples. All markers met the Hardy-Weinberg and linkage equilibrium expectations, and the power of discrimination ranged from 0.667 to 0.962. The total average probability of identity from the 15 STRs was 1.4 ×10−14 (FST = 0.05) while the total average probability of sibling identity was 6.0 ×10−6. Relationship tests revealed several parent-cub and full sibling pairs demonstrating that the marker set would be valuable for the study of family structures. The population data is the first of its kind from the Kamchatka brown bear population. Population pairwise FST`s revealed moderate genetic differentiation that mirrored the geographic distances to WE populations. The DNA profiling system, providing individual-specific profiles from non-invasive samples, will be useful for future monitoring and conservation purposes

To document

Abstract

The abundance and diversity of antimicrobial-resistant bacteria (ARB) and antimicrobial resistance genes (ARGs) in agricultural landscapes may be important for the spread of antimicrobial resistance (AMR) in the environment. The aim of this study was to apply screening methods for ARB and ARGs to investigate the impact of farming on the prevalence of AMR in a country with low antibiotic usage. We have analyzed samples (n = 644) from soil and wild terrestrial animals and plants (slugs, snails, mice, shrews, earthworms, and red clover) collected over two years in agricultural fields accompanied by nearby control areas with low human activity. All samples were investigated for the occurrence of 35 different ARGs using high-throughput quantitative PCR (HT-qPCR) on a newly developed DNA array. In addition, samples from the first year (n = 415) were investigated with a culture-based approach combined with whole-genome sequencing (WGS) to identify antimicrobial-resistant E. coli (AREC). ARGs were detected in 59.5% of all samples (2019 + 2020). AREC, which was only investigated in the 2019 samples, was identified in 1.9% of these. Samples collected in the autumn showed more ARGs and AREC than spring samples, and this was more pronounced for organic fields than for conventional fields. Control areas with low human activity showed lower levels of ARGs and a lack of AREC. The use of livestock manure was correlated with a higher level of ARG load than other farming practices. None of the soil samples contained antibiotics, and no association was found between AMR and the levels of metals or pesticides. High qualitative similarity between HT-qPCR and WGS, together with the positive controls to the validation of our 35 ARG assays, show that the microfluid DNA array may be an efficient screening tool on environmental samples. In conclusion, even in a country with a very low consumption of antimicrobials by production animals, our results support the hypothesis of these animals being a source of AREC and ARGs in agricultural environments, primarily through the use of manure.