Modeling Pathogen Dispersal in Marine Fish and Shellfish

Assessments of epidemic spread in aquaculture: comparing different scenarios of infectious bacteria incursion through spatiotemporal hybrid modeling

The sustainable development of the aquaculture sector is at risk due to the significant challenges posed by many emerging infectious diseases. While disease prevention and control measures are becoming increasingly critical, there is a dearth of studies on the epidemiological aspects of disease transmission in aquatic ecosystems. This study aims to forecast the spread of a bacterial disease between fish farms in two regions, Romsdalsfjord in Norway and Gujwa in South Korea by applying a DTU-DADS-Aqua spatiotemporal hybrid simulation model. The simulation model assessed the pattern of disease transmission between fish farms under different degrees of transmission power based on the distance between farms (ScalingInf), host susceptibility (RelSusceptibility), the origin site of disease, and the capacity of culling fish. The distance between fish farms was found to have significant associations with disease transmission. In most simulation conditions, the disease transmission between different bay management areas (BMAs) was not evident in Romsdalsfjord. In the Guwja region, where there are relatively narrow distances between fish farms, the spread of infectious disease was greatly affected by ScalingInf. The impact of RelSusceptibility on disease transmission patterns is a critical factor to consider in simulation modeling. When RelSusceptibility ranges from 0.5-1, there is little impact on the likelihood of disease transmission. Conversely, lower ranges (0.2 and 0.05) of RelSusceptibility result in a significant decrease in the area affected by the spread of disease. Eradication measures could control the patterns of infectious disease transmission, but the effectiveness of the depopulation strategy can be dramatically changed depending on the geographical environment. In conclusion, through a comparative analysis of the disease transmission and management scenarios, this study demonstrates the potential use of existing simulation models in predicting the spread of infectious diseases under different epidemiological circumstances and quarantine actions.

Assigning cause for emerging diseases of aquatic organisms

Resolving the cause of disease (= aetiology) in aquatic organisms is a challenging but essential goal, heightened by increasing disease prevalence in a changing climate and an interconnected world of anthropogenic pathogen spread. Emerging diseases play important roles in evolutionary ecology, wildlife conservation, the seafood industry, recreation, cultural practices, and human health. As we emerge from a global pandemic of zoonotic origin, we must focus on timely diagnosis to confirm aetiology and enable response to diseases in aquatic ecosystems. Those systems' resilience, and our own sustainable use of seafood, depend on it. Synchronising traditional and recent advances in microbiology that span ecological, veterinary, and medical fields will enable definitive assignment of risk factors and causal agents for better biosecurity management and healthier aquatic ecosystems.

Phylodynamic analysis of the highly pathogenic avian influenza H5N8 epidemic in France, 2016-2017

In 2016-2017, France experienced a devastating epidemic of highly pathogenic avian influenza (HPAI) H5N8, with more than 400 outbreaks reported in poultry farms. We analyzed the spatiotemporal dynamics of the epidemic using a structured-coalescent-based phylodynamic approach that combined viral genomic data (n = 196; one viral genome per farm) and epidemiological data. In the process, we estimated viral migration rates between départements (French administrative regions) and the temporal dynamics of the effective viral population size (Ne) in each département. Viral migration rates quantify viral spread between départements and Ne is a population genetic measure of the epidemic size and, in turn, is indicative of the within-département transmission intensity. We extended the phylodynamic analysis with a generalized linear model to assess the impact of multiple factors-including large-scale preventive culling and live-duck movement bans-on viral migration rates and Ne. We showed that the large-scale culling of ducks that was initiated on 4 January 2017 significantly reduced the viral spread between départements. No relationship was found between the viral spread and duck movements between départements. The within-département transmission intensity was found to be weakly associated with the intensity of duck movements within départements. Together, these results indicated that the virus spread in short distances, either between adjacent départements or within départements. Results also suggested that the restrictions on duck transport within départements might not have stopped the viral spread completely. Overall, we demonstrated the usefulness of phylodynamics in characterizing the dynamics of a HPAI epidemic and assessing control measures. This method can be adapted to investigate other epidemics of fast-evolving livestock pathogens.

Identification of antibacterial metabolites produced by a marine bacterium Halobacillus marinus HMALI004

AIMS

This study examined and characterized the extract for metabolites of Halobacillus marinus HMALI004 to understand their antibacterial activities against opportunistic marine pathogens, i.e., Vibrio parahaemolyticus and Vibrio cholerae.

METHODS AND RESULTS

The bacterial strain HMALI004 was characterized as Halobacillus marinus, and an antibacterial spectral test revealed its inhibition against two opportunistic marine pathogens (V. parahaemolyticus and V. cholera). Fermentation broth of strain HMALI004 was subjected to column chromatography and high-performance liquid chromatography (HPLC) to separate antibacterial substances. Two compounds were successfully isolated and identified as 1H-pyrrole-2-carboxylic acid and 4-chloro-1H-pyrrole-2-carboxylic acid by mass spectrometry (MS) and nuclear magnetic resonance (NMR). The minimal inhibition concentration (MIC) values of 1H-pyrrole-2-carboxylic acid and 4-chloro-1H-pyrrole-2-carboxylic acid for V. parahaemolyticus were 25 μg/mL, while their MIC values for V. cholerae were 50 and 100 μg/mL, respectively. The reactive oxygen species (ROS) production of two pathogen strains treated with 1H-pyrrole-2-carboxylic acid and 4-chloro-1H-pyrrole-2-carboxylic acid were detected to investigate the antimicrobial mechanism. The results suggested that 4-chloro-1H-pyrrole-2-carboxylic acid exerted enhanced ROS production in V. parahaemolyticus, whereas 1H-pyrrole-2-carboxylic acid had a weaker effect. Both compounds caused a significant rise in ROS production in V. cholerae, causing severe damage to the cell wall and cytoplasm, leading to cell death.

CONCLUSIONS

The bacterium H. marinus HMALI004 was isolated from a shrimp pond and was found to produce antimicrobial compounds which could inhibit the growth of opportunistic marine pathogens V. parahaemolyticus and V. cholerae by increasing ROS.

SIGNIFICANCE AND IMPACT OF THE STUDY

Successfully isolated antibacterial-producing strain, H. marinus HMALI004, and its antimicrobial compounds could be used as biological control agents for marine pathogens.

Phytocompounds as an Alternative Antimicrobial Approach in Aquaculture

Despite culturing the fastest-growing animal in animal husbandry, fish farmers are often adversely economically affected by pathogenic disease outbreaks across the world. Although there are available solutions such as the application of antibiotics to mitigate this phenomenon, the excessive and injudicious use of antibiotics has brought with it major concerns to the community at large, mainly due to the rapid development of resistant bacteria. At present, the use of natural compounds such as phytocompounds that can be an alternative to antibiotics is being explored to address the issue of antimicrobial resistance (AMR). These phytocompounds are bioactive agents that can be found in many species of plants and hold much potential. In this review, we will discuss phytocompounds extracted from plants that have been evidenced to contain antimicrobial, antifungal, antiviral and antiparasitic activities. Further, it has also been found that compounds such as terpenes, phenolics, saponins and alkaloids can be beneficial to the aquaculture industry when applied. This review will focus mainly on compounds that have been identified between 2000 and 2021. It is hoped this review will shed light on promising phytocompounds that can potentially and effectively mitigate AMR.

Estimating the dispersal of Lepeophtheirus salmonis sea lice within and among Atlantic salmon sites of the Bay of Fundy, New Brunswick

The objective of this study was to estimate the impact of infestation pressures on the abundance of the parasitic sea louse, Lepeophtheirus salmonis, in the Bay of Fundy, New Brunswick (NB), Canada, using the Fish-iTrends database for the years 2009-2018. Infestation pressures were calculated as time-lagged weighted averages of the abundance of adult female (AF) sea lice within a site (internal infestation pressure: IIP) and among sites (external infestation pressure: EIP). The EIP weights were calculated from seaway distances among sites and a Gaussian kernel density for bandwidths of 5 to 60 km. The EIP with a bandwidth of 10 km had the best fit, as determined with Akaike's information criterion, and historical AF sea lice abundance. This estimated dispersal distance of 10 km was similar to previous studies in Norway, Scotland and in New Brunswick. The infestation pressures estimated from empirical AF sea lice abundance within and among sites significantly increased the abundance of AF sea lice (p < .001). This study concludes that sea lice burdens within Atlantic salmon farms in the Bay of Fundy, NB, are affected by within site management and could be improved by synchronizing treatments between sites.

The ecological impact of a bacterial weapon: microbial interactions and the Type VI secretion system

Bacteria inhabit all known ecological niches and establish interactions with organisms from all kingdoms of life. These interactions are mediated by a wide variety of mechanisms and very often involve the secretion of diverse molecules from the bacterial cells. The Type VI secretion system (T6SS) is a bacterial protein secretion system that uses a bacteriophage-like machinery to secrete a diverse array of effectors, usually translocating them directly into neighbouring cells. These effectors display toxic activity in the recipient cell, making the T6SS an effective weapon during inter-bacterial competition and interactions with eukaryotic cells. Over the last two decades, microbiology research has experienced a shift towards using systems-based approaches to study the interactions between diverse organisms and their communities in an ecological context. Here, we focus on this aspect of the T6SS. We consider how our perspective of the T6SS has developed and examine what is currently known about the impact that bacteria deploying the T6SS can have in diverse environments, including niches associated with plants, insects and mammals. We consider how T6SS-mediated interactions can affect host organisms by shaping their microbiota, as well as the diverse interactions that can be established between different microorganisms through the deployment of this versatile secretion system.

Lack of evidence for differences in the spread of classic (Lagovirus europaeus/GI.1) and novel (Lagovirus europaeus/GI.2) rabbit haemorrhagic disease viruses in Europe and North Africa

BACKGROUND

Fast-spreading diseases affecting wildlife populations threaten biodiversity. Two caliciviruses, Lagovirus europaeus/GI.1 and Lagovirus europaeus/GI.2, caused rabbit haemorrhagic disease virus (RHDV) in wild rabbits. Despite having different characteristics, these variants spread quickly, posing a threat to wild rabbit populations.

METHODS

In this study, we conducted a thorough review of the scientific literature and reports of international organisations of first detections of both variants of RHDV in the Euro-Mediterranean region. We concentrated on this area to avoid bias due to intentional human introductions.

RESULTS

The estimated mean spread rate of GI.2 was higher than that of GI.1 (GI.2: 479 km/year, range: 47-7346; GI.1: 330 km/year, 37-6248). These differences were not statistically significant. This lack of difference may be due to the interactions between each variant's virulence characteristics. Humans may have a dominant effect on their spread. Potential limitations associated with the observational process could have hindered our ability to identify statistical differences.

CONCLUSIONS

The lack of difference in the spread patterns of the two variants could be due to a biological cause, human facilitation or a lack of statistical power. Adapting protocols to detect diseases in wildlife using homogeneous criteria will be indispensable in the coming years.

Potential threat of SARS-CoV-2 in coastal waters

A novel coronavirus (SARS-CoV-2) has caused more than 150 million confirmed infections worldwide, while it is not clear whether it affects the coastal waters. This paper proposed a biophysical model based on 16 scenarios with different virus half-life parameters to assess potential viral contamination from 25 municipal sewage outfalls into the Bohai Sea. Viral concentration maps showing spatial and temporal changes are provided based on a biophysical model under multiple scenarios. Results demonstrate that adjacent sea areas can become exposed to SARS-CoV-2 via water-borne transport from outfalls, with a higher risk in winter, because SARS-CoV-2 can be highly stable at low temperature. As coastal waters are the ultimate sink for wastewater and the epidemic will last for long time, this work is of great importance to raise awareness, identify vulnerable areas for marine mammals, and avoid the risk of exposure of tourists at bathing beach.

Transmissible cancers in mammals and bivalves: How many examples are there?: Predictions indicate widespread occurrence

Transmissible cancers are elusive and understudied parasitic life forms caused by malignant clonal cells (nine lineages are known so far). They emerge by completing sequential steps that include breaking cell cooperation, evade anti-cancer defences and shedding cells to infect new hosts. Transmissible cancers impair host fitness, and their importance as selective force is likely largely underestimated. It is, therefore, crucial to determine how common they might be in the wild. Here, we draw a parallel between the steps required for a transmissible cancer to emerge and the steps required for an intelligent civilisation to emerge in the Milky Way using a modified Drake equation. Using numerical analyses, we estimate the potential number of extant marine and bivalve species in which transmissible cancers might exist. Our results suggest that transmissible cancers are more common than expected, and that new lineages can be found by screening a large number of species.

Classification of pathogens by Raman spectroscopy combined with generative adversarial networks

Rapid identification of marine pathogens is very important in marine ecology. Artificial intelligence combined with Raman spectroscopy is a promising choice for identifying marine pathogens due to its rapidity and efficiency. However, considering the cost of sample collection and the challenging nature of the experimental environment, only limited spectra are typically available to build a classification model, which hinders qualitative analysis. In this paper, we propose a novel method to classify marine pathogens by means of Raman spectroscopy combined with generative adversarial networks (GANs). Three marine strains, namely, Staphylococcus hominis, Vibrio alginolyticus, and Bacillus licheniformis, were cultured. Using Raman spectroscopy, we acquired 100 spectra of each strain, and we fitted them into GAN models for training. After 30,000 training iterations, the spectra generated by G were similar to the actual spectra, and D was used to test the accuracy of the spectra. Our results demonstrate that our method not only improves the accuracy of machine learning classification but also solves the problem of requiring a large amount of training data. Moreover, we have attempted to find potential identifying regions in the Raman spectra that can be used for reference in subsequent related work in this field. Therefore, this method has tremendous potential to be developed as a tool for pathogen identification.