Digitalization is changing the landscape of infectious disease research. It not only enhances data collection and processing but brings together data, data-related resources, and diverse stakeholders, facilitating interdisciplinary collaboration. Building on the experiences of the international research network ESIDA (Epidemiological Surveillance of Infectious Diseases in Sub-Saharan Africa),...
Whole genome sequencing (WGS) has become the key approach for molecular surveillance of the foodborne pathogen Listeria monocytogenes (Lm). Genome comparison analysis can reveal transmission routes that cannot be found with classic epidemiology.
Widespread standard for use in genome comparison analysis is data from short read sequencing, generated on Illumina or Ion Torrent devices. To...
Hepatitis E virus (HEV) genotype 1 (gt1) infects only humans whereas genotype 3 (gt3) is zoonotic infecting various animal species and humans. For elucidation of determinants of host specificity, experiments using reverse genetics enabling targeted genome manipulations are needed. However, whereas a few reverse genetics systems exist for gt3, those for gt1 are still very limited, mainly...
Streptococcus suis is a respiratory commensal of pigs, with some lineages causing serious swine disease and zoonotic disease in humans. In recent years, S. suis has also been isolated from cats, dogs, cattle, sheep, wild boars, and different bird species, including chicken. It is generally assumed that, as in humans, these infections are due to “spillovers” from pigs, but no genomic...
Bovine mastitis is a highly prevalent disease plaguing the dairy industry. Streptococcus uberis is the most predominant pathogen for bovine mastitis and is frequently isolated from milk of infected quarters. This study aimed to identify the phenotypic and genotypic antimicrobial resistance (AMR). 80 S. uberis were isolated from milk samples of dairy cows with clinical mastitis in...
Changes in the microbiome can be an indicator of the onset of an infectious disease such as sepsis. The ability to distinguish these significant changes from naturally occurring fluctuations in the microbiome could aid in the early detection of potentially harmful diseases. We aim to take a step toward this prediction of microbial abundance trends based on analysis of 16S rRNA data. To this...