BackgroundIn humans, Streptococcus agalactiae or group B streptococcus (GBS) is a frequent coloniser of the rectovaginal tract, a major cause of neonatal infectious disease and an emerging cause of disease in non-pregnant adults. In addition, Streptococcus agalactiae causes invasive disease in fish, compromising food security and posing a zoonotic hazard. We studied the molecular epidemiology of S. agalactiae in fish and other aquatic species to assess potential for pathogen transmission between aquatic species and humans.MethodsIsolates from fish (n = 26), seals (n = 6), a dolphin and a frog were characterized by pulsed-field gel electrophoresis, multilocus sequence typing and standardized 3-set genotyping, i.e. molecular serotyping and profiling of surface protein genes and mobile genetic elements.ResultsFour subpopulations of S. agalactiae were identified among aquatic isolates. Sequence type (ST) 283 serotype III-4 and its novel single locus variant ST491 were detected in fish from Southeast Asia and shared a 3-set genotype identical to that of an emerging ST283 clone associated with invasive disease of adult humans in Asia. The human pathogenic strain ST7 serotype Ia was also detected in fish from Asia. ST23 serotype Ia, a subpopulation that is normally associated with human carriage, was found in all grey seals, suggesting that human effluent may contribute to microbial pollution of surface water and exposure of sea mammals to human pathogens. The final subpopulation consisted of non-haemolytic ST260 and ST261 serotype Ib isolates, which belong to a fish-associated clonal complex that has never been reported from humans.ConclusionsThe apparent association of the four subpopulations of S. agalactiae with specific groups of host species suggests that some strains of aquatic S. agalactiae may present a zoonotic or anthroponotic hazard. Furthermore, it provides a rational framework for exploration of pathogenesis and host-associated genome content of S. agalactiae strains.

1. Marine aquaculture relies on coastal habitats that will be affected by climate change. This review assesses current knowledge of the threats and opportunities of climate change for aquaculture in the UK and Ireland, focusing on the most commonly farmed species, blue mussels (Mytilus edulis) and Atlantic salmon (Salmo salar). 2. There is sparse evidence to indicate that climate change is affecting aquaculture in the UK and Ireland. Impacts to date have been difficult to discern from natural environmental variability, and the pace of technological development in aquaculture overshadows effects of climatic change. However, this review of broader aquaculture literature and the likely effects of climate change suggests that over the next century, climate change has the potential to directly impact the industry. 3. Impacts are related to the industry's dependence on the marine environment for suitable biophysical conditions. For instance, changes in the frequency and strength of storms pose a risk to infrastructure, such as salmon cages. Sea-level rise will shift shoreline morphology, reducing the areal extent of some habitats that are suitable for the industry. Changes in rainfall patterns will increase the turbidity and nutrient loading of rivers, potentially triggering harmful algal blooms and negatively affecting bivalve farming. In addition, ocean acidification may disrupt the early developmental stages of shellfish. 4. Some of the most damaging but least predictable effects of climate change relate to the emergence, translocation and virulence of diseases, parasites and pathogens, although parasites and diseases in finfish aquaculture may be controlled through intervention. The spread of nuisance and non-native species is also potentially damaging. 5. Rising temperatures may create the opportunity to rear warmer water species in theUKand Ireland. Market forces, rather than technical feasibility, are likely to determine whether existing farmed species are displaced by new ones

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Farmed and wild salmonids are affected by a variety of skin conditions, some of which have significant economic and welfare implications. In many cases, the causes are not well understood, and one example is cold water strawberry disease of rainbow trout, also called red mark syndrome, which has been recorded in the UK since 2003. To date, there are no internationally agreed methods for describing these conditions, which has caused confusion for farmers and health professionals, who are often unclear as to whether they are dealing with a new or a previously described condition. This has resulted, inevitably, in delays to both accurate diagnosis and effective treatment regimes. Here, we provide a standardized methodology for the description of skin conditions of rainbow trout of uncertain aetiology. We demonstrate how the approach can be used to develop case definitions, using coldwater strawberry disease as an example.

This is the peer reviewed version of the following article: Lyons, P. P., Turnbull, J. In this study, high throughput 16S rRNA sequencing was used to investigate the effect of a 171Samples were allowed to settle, and total genomic DNA was extracted and purified using the 192Illumina libraries were prepared following the method described by Caporaso, Lauber, Walters, All fish consumed both diets readily and upon conclusion of the trial, the weighed individuals 273 from the treatment group had a higher mean weight and condition factor than the control group. 274The final mean weight and condition factor (± SE) for the treatment group was 136.6 ± 12.1g 275 and 1.44 ± 0.06 whereas these values for the control group were 116.5 ± 9.3g and 1.33 ± 0.04 276 respectively ( Figure S1). A t-test was performed using the Minitab 15 statistical software to 277 test for significant differences between the performance parameters for both groups, however 278 no such differences were found (p = 0.107). Sequence data and diversity analyses 280After quality filtering of sequences, a total of 18,282,541 sequences remained for analysis, The overall microbial community composition was similar in both the control and treatment 296 populations of fish. The distribution of OTU's at the phylum level of both the control and 297 treatment libraries is illustrated below (Figure 1). The vast majority of reads were assigned to 298 nine separate bacterial phyla, although an overall total of 13 phyla were recorded. Within these 299 phyla, 13 microbial classes dominated (Figure 2 is still yet to be fully characterized. 329Principal coordinate analyses, when visualized based on the thetaYC distance matrix 330 comparing similarities in community structure, showed that samples were broadly 412The Tenericutes were the dominant microbial phylum in the vast majority of samples, followed