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Abortion in cattle causes significant economic losses for cattle farmers worldwide. The diversity of abortifacients makes abortion diagnostics a complex and challenging discipline that additionally is restrained by time and economy. Microbial culture has traditionally been an important method for the identification of bacterial and mycotic abortifacients. However, it comes with the inherent bias of favoring the easy-to-culture species, e.g., those that do not require cell culture, pre-enrichment, a variety of selective growth media, or different oxygen levels for in vitro growth. Molecular methods such as polymerase chain reaction (PCR) and next-generation sequencing have been established as alternatives to traditional microbial culturing methods in several diagnostic fields including abortion diagnostics. Fluorescence in situ hybridization (FISH), a bridging microscopy technique that combines molecular accuracy with culture independence, and spatial resolution of the pathogen-lesion relation, is also gaining influence in several diagnostic fields. In this study, real-time quantitative PCR (qPCR), 16S rDNA amplicon sequencing, and FISH were applied separately and in combination in order to (i) identify potentially abortifacient bacteria without the bias of culturability, (ii) increase the diagnostic rate using combined molecular methods, (iii) investigate the presence of the difficult-to-culture zoonotic agents Coxiella burnetii, Chlamydia spp., and Leptospira spp. in bovine abortions in Denmark. Tissues from 162 aborted or stillborn bovine fetuses and placentas submitted for routine diagnostics were screened for pathogenic bacteria using 16S rDNA amplicon sequencing. Lesion association of fungal elements, as well as of selection of bacterial abortifacients, was assessed using specific FISH assays. The presence of Chlamydia spp. and chlamydia-like organisms was assessed using qPCR. The study focused on bacterial and fungal abortifacients, because Danish cattle is free from most viral abortifacients. The 16S rDNA amplicon sequencing–guided FISH approach was suitable for enhancing abortion diagnostics, i.e., the diagnostic rate for cases with tissue lesions (n = 115) was increased from 46 to 53% when compared to routine diagnostic methods. Identification of Bacillus licheniformis, Escherichia coli, and Trueperella pyogenes accounted for the majority of additional cases with an established etiology. No evidence for emerging or epizootic bacterial pathogens was found. The difficult-to-culture abortifacients were either not detected or not identified as abortifacients.

Vector-borne diseases such as Lyme disease and tick-borne encephalitis have become more common in recent decades and present a real health problem in many parts of Europe. Risk assessment, control, and prevention of these diseases require a better understanding of vector abundance as well as risk factors determining human exposure to ticks. There is a great need for analyses and models that can predict how vectors and their associated diseases are distributed and how this relates to high risk areas for human exposure.As a part of the ScandTick Innovation project, we surveyed ticks at approximately 30 sites (forests and meadows) in each of Denmark, southern Norway and south-eastern Sweden. At each site we measured presence/absence of ticks, and used the data obtained along with environmental satellite images to run Boosted Regression Tree machine learning algorithms to predict overall spatial distribution (probability of presence) in southern Scandinavia. Together with the predicted distribution maps, we used human density maps to determine areas with high risk of exposure to ticks. For nymphs, the predicted distribution found corresponded well with known distributions of ticks in Scandinavia, with more widespread distribution in Denmark compared to Norway and Sweden. In the Norwegian region, probability of presence was markedly higher nearer the coastline and the data shows a latitudinal boundary in the Swedish region above which probability of presence was low or close to zero. Presence of larvae was much more clustered in the observed data, which was also reflected in the predicted distribution maps for the region. Whereas the predicted distribution of larvae was mostly even throughout Denmark, larvae were primarily around the coastlines in Norway and Sweden. When combining these distribution maps with human population density maps and accounting for area accessibility, we could assess the proportion of the population living in areas where ticks were present. Our data showed that although ticks are found in a limited proportion of the total region area (particularly for Norway and Sweden), areas with high population densities tend to overlap with these zones.Machine learning techniques allow us to predict for larger areas without having to perform extensive sampling all over the region in question, and we were able to produce models and maps with high predictive value. The results from these models help us pinpoint areas with high risk of exposure to ticks and thus potentially tick-borne diseases.

Influenza A virus infections have great impact on human health and welfare and significant resources are linked to influenza epidemics due to excess hospitalizations and lost productivity. Up to 15% of the human population is affected when Influenza spreads around the world in seasonal epidemics (WHO). Animal models are essential in understanding the mechanisms involved in human infectious disease and for the development of effective prevention and treatment strategies. It is increasingly realized that large animal models like the pig are exceptionally human like and serve as an excellent model for disease and inflammation. Pigs are fully susceptible to human influenza, and have been demonstrated to be involved in influenza evolution and ecology. Pigs share many similarities with humans regarding lung physiology and innate immune cell infiltration of the respiratory system and thus seem to be an obvious large animal model for respiratory infections. This study aimed at providing a better understanding of the involvement of circulating non-coding RNA and innate immune factors in porcine blood leukocytes during influenza virus infection. By employing the pig as a model we were able to perform highly controlled experimental infections and to study changes of symptoms, viral titer, and expression of microRNAs/mRNAs as the influenza infection progresses in time, generating information that would be difficult to obtain from human patients. The Gram-negative bacterium Actinobacillus pleuropneumoniae causes pneumonia in pigs, a disease which is associated with high morbidity and mortality, as well as impaired animal welfare. The rapidly evolving pneumonia is characterized by large areas of lung necrosis resulting from the combined effect of tissue damage caused by the bacteria, and a strong proinflammatory immune response. To obtain in-depth understanding of this infection, concurrent gene expression of host and pathogen in lung samples collected from pigs experimentally infected with A. pleuropneumoniae was studied. We applied high-throughput RT-qPCR for the simultaneous analysis of host and pathogen gene expression. This parallel analysis was done in lung tissue samples as well as in the immediate surroundings of infection loci after laser capture microdissection. Regulation of gene expression of several immune factors was observed in agreement with protein levels of these factors in lung tissue, infection status and histopathological findings.

Aim: To obtain an increased understanding of how the porcine lung pathogen Actinobacillus pleuropneumoniae (Ap) establish infection in the host. Understanding the means by which a pathogen establishes and maintains infection in the host organism is the first step towards controlling disease. Methods: The local in vivo genetic response of Ap during the early phase of infection in porcine lungs was detailed using pangenomic microarray analysis. The global transcriptional patterns of Ap serotype 2 and 6 isolated from lung tissue biopsies of 25 experimentally infected pigs were compared at four time points between 6 and 48 hours post infection. Results: We identified 310 genes (p

Actinobacillus pleuropneumoniae (Ap) is a gram-negative bacterium that causes porcine pleuropneumonia, which is a widespread, highly contagious and often fatal respiratory disease in swine. A total of 44 pigs were experimentally inoculated with Ap serotype 2 or 6 and samples of liver and tracheobronchial lung lymph nodes were collected 6, 12, 24 and 48 hours after experimental inoculation, as well as from six non-inoculated control pigs. Transcriptional profiles of the liver samples have been generated by preparation of 12-plexed mRNA-Seq libraries followed by sequencing on an Illumina GAIIx (51+7 cycles) obtaining more than 200 million tag sequences. The 12-plexed mRNA-Seq libraries of the lung lymph node samples have presently (April 2010) been prepared and are to be sequenced. The PCR amplicons of the liver libraries were quantified using both a fluorometer and a qPCR assay, including the use of a sequence-titrated, in-house control library. The libraries were diluted to 6 pM based on the qPCR assay, except for a single library set which was duplicated and diluted based on the fluorometer measurements as well. Analysis of the obtained sequences revealed that the qPCR based quantifications reduced the cluster density variability as compared to fluorometer based quantifications. Furthermore, it was found that the fluorometer based measurements tended to deviate for dilute as well as for more concentrated libraries. Following the sequencing of the lung lymph node samples analyses are to be conducted to study the time and serotype dependent transcriptional response to Ap infection.

Recently, focus on tick-borne diseases has increased as diseases such as Lyme disease and tickborne encephalitis have become more widespread and represent a real health problem in many parts of Europe. Effective control and prevention of these diseases requires a better understanding of the factors affecting the vectors. There is a great need for analyses and models that can predict how vectors and their associated diseases are distributed now and possibly in the future. As a part of the ScandTick Innovation project, we surveyed and collected ticks at approximately 30 sites in each of Denmark, southern Norway and south-eastern Sweden. At each site we measured presence/absence and relative tick abundance using north- and east- facing line transect, where number of larvae, nymphs and adult females and males were counted at eight 50 m transects. We used the data obtained along with environmental satellite images to run Boosted Regression Tree machine learning algorithms to predict overall distribution (presence/absence of ticks) and relative tick abundance of nymphs and larvae in southern Scandinavia. For nymphs, the predicted abundance had a positive correlation with observed abundance and the spatial variation found corresponded well with known abundance and distributions of ticks in Scandinavia, with higher abundance and more widespread distribution in Denmark compared to Norway and Sweden. Because abundance was strongly correlated with forested habitats the risk areas were much larger in Sweden and Norway compared to Denmark. In both the Norwegian and Swedish regions, abundance was markedly higher nearer the coastline. Presence of larvae was much more clustered in the observed data, which was also reflected in the predicted abundance and distribution maps for the region. Whereas the predicted distribution of larvae was mostly even throughout Denmark, it was primarily around the coastlines in Norway and Sweden. Abundance was fairly low overall except in some fragmented patches corresponding to forested habitats in the region. Machine learning techniques allow us to predict for larger areas without having to perform extensive sampling all over the region in question. The results from these models can be used in epidemiological models and can help us determine areas under risk of disease transmission and help us interpret human incidence data. Next step will be to analyze the collected ticks for pathogens and using the same machine learning techniques to develop prevalence maps of the ScandTick region.

Since the end of the ice age, spring migrating birds from Africa and Europe and autumn migrating birds from Northern Scandinavia have entered Denmark, and recently a small wave of long migrating carnivores have started arriving in Denmark from Central Europe. Theoretically, migrating birds could introduce new tick species as well as tick-associated pathogens to Denmark. These migrating animals may also carry ticks and pathogens which already exist in native tick populations in Denmark. The potential supplement of native ticks and existing pathogens to the established high density tick populations in Danish forest and nature areas can be expected to be of little practical importance. However, some of the infected ticks, introduced by migrating birds, may be deposited in private gardens and public parks that are otherwise not able to sustain a viable tick population. Migrating birds may therefore introduce a low level risk of tick borne infections to urban areas. Also the recent unexpected wave of long migrating golden jackals (Canis aureus) and grey wolves (Canis lupus), arriving at the Danish peninsula of Jutland, constitutes an emerging risk of introduction of especially Dermacentor spp ticks and their associated pathogens from Germany and Central Europe. Here, we present the results of screening migrating birds and a golden jackal for ticks as well as ticks collected by flagging in selected urban areas in Denmark. The collected ticks were screened for exotic tick species and 38 different tick borne pathogens. We show that the risk is not just theoretical and we suggest that these introductions may have a practical public health impact.

In recent years, focus on tick-borne diseases has increased as diseases such as Lyme disease and tick-borne encephalitis have become more common and represent a health problem in many parts of Scandinavia. More effective prevention of infections requires a better understanding of the factors affecting the vector abundance as well as human exposure to the vectors. Hence, there is a great need for analyses and models that can predict how vectors and their associated diseases are distributed now and possibly in the future.As a part of the ScandTick Innovation project, we surveyed tick nymphs at 159 sites (forests and meadows) in Denmark, southern Norway and south-eastern Sweden. At each site we measured presence/absence, and used the data obtained along with environmental data from satellite images to run Boosted Regression Tree machine learning algorithms to predict overall distribution in southern Scandinavia. Together with the predicted distribution maps, we used human density maps to identify and plot areas with high risk of exposure to ticks. The predicted distribution and the spatial variation found corresponded well with known distributions of ticks in Scandinavia (sensitivity: 91%, specificity: 60%), and we found that the model was predominantly temperature-driven. Because presence was strongly correlated with forested habitats the risk areas were much larger in Sweden and Norway compared to Denmark. When combining these distribution maps with human population density maps, we were able to quantify the proportion of people living in areas with tick presence in Scandinavia. We found that although tick nymphs were restricted to a small proportion of the modelled area, high proportions of the human populations (67-79%) lived within these same areas. The model suggests that a potential future range expansion of I. ricinus in Scandinavia is likely but may only affect a relatively small additional proportion of the human population.

Large animal models are essential in understanding the mechanisms involved in human infectious disease. To study the expression of host and bacterial genes involved in defense and survival mechanisms, we analyzed lung tissue from pigs experimentally infected with the Gram-negative bacterium A. pleuropneumoniae. All steps including RNA extraction and high-throughput real-time qPCR were carried out simultaneously for the two organisms. By applying this dual-organism approach, we obtained unique insights into the host-pathogen interaction at the site of infection. Differential expression of host genes involved in innate immune responses towards Gram-negative infections, including pattern recognition receptors and cytokines concurrent with expression of bacterial genes involved in lipopolysaccharide biosynthesis and adhesion was demonstrated. We also studied the gene expression in blood leukocytes after experimental H1N2 virus infection of pigs, and found the regulation of several swine encoded miRNAs and cytokines to mimic key findings from influenza studies in human patients. By employing the pig as a model we were able to perform highly controlled experimental infections and to study changes of symptoms, viral titer, and expression of microRNAs/mRNAs as the influenza infection progressed in time, generating information that would be difficult to obtain from human patients.

Bovine digital dermatitis, the cause of lameness and wasting in cattle, was first reported in 1974. Today, this disease has considerable negative effects on animal welfare and production economy in many parts of the world. A bacterial etiology of digital dermatitis is now well documented, and the current view on this disease points towards a complicated etiology involving co-infection of more than one, and probably multiple species belonging to the genus Treponema. Still, the pathogenic role of each of the digital dermatitis-associated phylotypes remains unclear. The aim of this investigation was to obtain a better understanding of digital dermatitis in general, including possible predisposing skin alternations and the role of the bacteria Dichelobacter nodosus. Finally, we wanted to determine if any Treponema phylotypes could be singled out as having a particularly prominent role in the etiology of the disease.Here, a PCR-based approach targeting the 16S rRNA gene along with fluorescence in situ hybridization was used to determine the prevalence and diversity of 17 Treponema phylotypes in 85 digital dermatitis lesions from six Danish dairy herds as well as additional biopsies of healthy skin and previously examined digital dermatitis lesions. All skin samples were evaluated histopathologically for possible predisposing abnormalities. Furthermore, fluorescence in situ hybridization tests for Fusobacterium. necrophorum and D. nodosus was applied. All lesions revealed intermingled infections with multiple Treponema phylotypes (mean > 7). In six herds, the mean number of phylotypes identified varied between 12 and 15. D. nodosus was present in forty-nine (51%) of the lesions and in three of the apparently healthy skin samples. One “healthy” sample also contained Treponema spp. and D. nodosus, and were histopathologically categorized as subclinical digital dermatitis.We propose that external noxious stimuli allow D. nodosus to break down the epidermal barrier creating a suitable environment for the secondary invaders, Treponema species, which gradually take over the infection site. The variety and different distribution of treponemes in the digital dermatitis lesions observed in this study, suggests that most of the Treponema phylotypes have the potential to be pathogenic.

MicroRNAs are small non-coding RNA molecules (18-23 nt), that regulate the activity of other genes at the post-transcriptional level. Recently it has become evident that microRNA plays an important role in modulating and fine tuning innate and adaptive immune responses. Still, little is known about the impact of microRNAs in the development and pathogenesis of lung infections. Expression of microRNA known to be induced by bacterial (i.e., LPS) ligands and thus supposed to play a role in the regulation of antimicrobial defence, were studied in lung tissue and in blood from pigs experimentally infected with Actinobacillus pleuropneumoniae (AP). Expression differences of mRNA and microRNA were quantified at different time points (6h, 12h, 24h, 48h PI) using reverse transcription quantitative real-time PCR (Rotor-Gene and Fluidigm). Expression profiles of miRNA in blood of seven animals were further studied using miRCURY™ LNA arrays (Exiqon, Denmark). All AP infected animals had significantly higher levels of mRNA coding for inflammatory mediators as IL-6 and IL-8 as well as the acute phase protein SAA, in the lung compared to the control group. MiR-223 was found to be highly up regulated, followed by miR-146a and to a lesser degree miR- 155 in lung tissue of the AP infected animals. MiR-233 was also found to be up regulated in blood based on both microarray and real-time PCR. Mir-233 has been found to be a negative regulator of neutrophil proliferation and activation, and might act to limit the potentially harmful consequences of the accumulation of infiltrating neutrophils in AP infected lungs.

Bovine digital dermatitis (DD) is the most important infectious cause of lameness in dairy cattle, and a major contributing factor to welfare problems and economic losses in the dairy cattle industry worldwide. DD is a disease that involves chronic dermal inflammatory processes and destruction of collagenous and connective tissues. Multiple Treponema species, many of which are not-yet-cultivable, are strongly implicated in disease progression. Despite the economic and welfare importance of this disease, no effective vaccine is available; and there is presently very little knowledge concerning efficacious immunoprophylactic antigens against DD.It is highly likely that DD-associated treponemes possess considerable antigenic variation, as cows exhibit a variable humoral response against different isolates of Treponema. Hence, combinations of antigens from multiple Treponema species should be used for the development of disease prevention measures. As treponemes from DD lesions are extremely difficult to culture, identification of these antigens is challenging. To circumvent this problem, we studied the in situ gene expression patterns of the microbiome in DD-affected skin lesions and the host antibody response directed at the site of infection. By metatranscriptomics we measured the in situ genome-wide transcriptome of the bacterial population in DD-affected skin lesions from 21 dairy cows. From the transcriptome data, we identified a panel of Treponema genes that were highly expressed in multiple animals, and we monitored the host immune response to these target genes using high-density peptide microarrays. By this approach, we identified a small group of antigenic proteins, which were expressed in the majority of the samples, and demonstrated antigenicity when screened against sera from infected animal. Future studies will show if these proteins represent candidates for the development of novel biomarkers or vaccines

Endometritis is inflammation of the inner lining of the uterus, affecting up to 20% of the dairy cows after calving in Denmark. The disease causes reduced pregnancy rates, which often leads to culling of the cows and is costly for the farmer. Until now, investigations of which pathogens may cause the disease have been based on microbiological culturing, and no conclusive evidence has been found. Only a fraction of the bacterial flora is cultivable, and therefore more than 90% of the uterine microbiome has not been characterised. With incomplete knowledge of the pathogens, treatment is performed without an option for choosing the best suited antimicrobial agent, which may lead to unnecessary antibiotic resistance development. The present study is based on 16S rRNA PCR, which in combination with 454 next generation sequencing allows phylogenetic identification of the bacteria present in the sample. Not being limited to bacteria that are suited to growth under laboratory conditions, this study promises a more comprehensive insight into the microbiome of the dairy cow uterus than has previously been offered.Cows (n=40) on a Danish dairy herd were randomly selected on the basis of a uterine score indicating that the cows had uterine pathology. Uterine fluid was aspirated and if necessary the uterus was flushed with 30 ml sterile saline solution in order to retrieve uterine material. The fluid was placed in RNAlater. An endometrial biopsy was retrieved and the tissue placed in RNAlater. The cows were sampled on days 5-11 (week 1), days 26-32 (week 4), and on days 47-53 (week 7). This sampling schedule provided an opportunity to follow the development of any infection, and the combination of biopsy and uterine flush samples offered insights into whether tissue-invasive bacteria were present. The DNA was extracted with the Maxwell 16 LEV Blood kit (Promega), the 16S rRNA PCR was performed with primers targeting the V2 region, and the 454 next generation sequencing was performed by GATC.Previous papers based on culturing of endometrial swabs or biopsies point to Escherichia coli, Trueperella (Archanobacterium) pyogenes, and Fusobacterium necrophorum as the most likely pathogens, although some of them also seem to be present in healthy animals. We expect to find these bacteria in the samples from the diseased animals, and perhaps the detailed data from the sequencing will also reveal hitherto undiscovered pathogens.

Objective: To develop a fast and efficient method for measuring prevalence and gene expression of representatives from the three major groups of Treponema, most frequently identified in DD biopsies from cattle.

Recent years’ advance in sequencing technology has resulted in extensive new knowledge of the microbial ecology of different environments. We used the technology to investigate the causality of endometritis, which is an inflammation in the inner lining of the uterus affecting up to 20% of dairy cows in Denmark post partum. Endometritis is linked to reduced reproductive performance, which is costly for the farmer and often leads to culling of the affected cows. With incomplete knowledge of the bacteria involved, treatment is performed without an option for choosing the best suited antimicrobial agent, which may lead to unnecessary antibiotic resistance development. Slaughterhouse samples were analysed in order to obtain information on the uterine microbiota from both cows with endometritis and seemingly healthy cows from a variety of herds. We sampled uteri from cows (n=50) from a slaughterhouse in Holstebro, Denmark. An incision was made into the right uterine horn and an endometrial biopsy was taken with a pair of sterilised scissors. The endometrial surface was sampled with a cotton-swab through the same incision. All samples were immediately put in RNAlater. The DNA was extracted with the Maxwell 16 LEV Blood kit (Promega), the 16S rRNA PCR was performed with primers targeting the V2 region, and the 454 next generation sequencing was performed by GATC. Previous results have shown that Proteobacteria and Tenericutes are the most important bacteria phyla in the uterus of healthy cows (Machado et al. 2012 and Galvão et al. 2012) while Escherichia coli, Trueperella Pyogenes, Prevotella species and Fusobacterium necrophorum have commonly been associated with endometritis (Sheldon 2006). Preliminary results indicate that we often find bacteria from phylum Actinobacteria in the healthy cows and often bacteria from phyla Bacteroidetes and Fusobacteria in cows with endometritis.