Acinetobacter baumannii, a pathogen for humans and animals, possesses a tremendous potential to survive under hostile conditions. We studied the effect of temperature, nutrient deprivation, and desiccation on the survival of A. baumannii ATCC 19606T by monitoring variations in cellular counts and in cell length and analyzing cell envelope subproteome during the survival process. Nutrient deprivation alone does not appear to have a negative effect on A. baumannii survival, but incubation at 37 °C in an aqueous solution provoked loss of culturability, as well as a marked increase in cell length. Although a high stability of the membrane subproteome was observed, even under environmental conditions that promote morphological changes and loss of culturability, the expression of some membrane proteins did change upon exposure to the stress. Signal peptidase I and fimbrial protein became undetectable in almost all the conditions examined, while EF-Tu (in all conditions) and MinD (in populations incubated at 37 °C) were overexpressed. The great capacity for survival displayed by A. baumannii under adverse conditions may be explained, at least in part, by its capacity to maintain the expression levels of most of its cell envelope proteins and regulate a few others.

Global warming and acidification of the global ocean are two important manifestations of the ongoing climate change. To characterize their joint impact on Vibrio adaptation and fitness, we analyzed the temperature-dependent adaptation of Vibrio harveyi at different pHs (7.0, 7.5, 8.0, 8.3 and 8.5) that mimic the pH of the world ocean in the past, present and future. Comparison of V. harveyi growth at 20, 25 and 30 °C show that higher temperature per se facilitates the logarithmic growth of V. harveyi in nutrient-rich environments in a pH-dependent manner. Further survival tests carried out in artificial seawater for 35 days revealed that cell culturability declined significantly upon incubation at 25 °C and 30 °C but not at 20 °C. Moreover, although acidification displayed a negative impact on cell culturability at 25 °C, it appeared to play a minor role at 30 °C, suggesting that elevated temperature, rather than pH, was the key player in the observed reduction of cell culturability. In addition, analyses of the stressed cell morphology and size distribution by epifluorescent microscopy indicates that V. harveyi likely exploits different adaptation strategies (e.g., acquisition of coccoid-like morphology) whose roles might differ depending on the temperature-pH combination.

In a non-linear system, such as a biological system, the change of the output (e.g., behaviour) is not proportional to the change of the input (e.g., exposure to stressors). In addition, biological systems also change over time, i.e., they are dynamic. Non-linear dynamical analyses of biological systems have revealed hidden structures and patterns of behaviour that are not discernible by classical methods. Entropy analyses can quantify their degree of predictability and the directionality of individual interactions, while fractal dimension (FD) analyses can expose patterns of behaviour within apparently random ones. The incorporation of these techniques into the architecture of precision fish farming (PFF) and intelligent aquaculture (IA) is becoming increasingly necessary to understand and predict the evolution of the status of farmed fish. This review summarizes recent works on the application of entropy and FD techniques to selected individual and collective fish behaviours influenced by the number of fish, tagging, pain, preying/feed search, fear/anxiety (and its modulation) and positive emotional contagion (the social contagion of positive emotions). Furthermore, it presents an investigation of collective and individual interactions in shoals, an exposure of the dynamics of inter-individual relationships and hierarchies, and the identification of individuals in groups. While most of the works have been carried out using model species, we believe that they have clear applications in PFF. The review ends by describing some of the major challenges in the field, two of which are, unsurprisingly, the acquisition of high-quality, reliable raw data and the construction of large, reliable databases of non-linear behavioural data for different species and farming conditions.

Analysis of fish behaviour is an effective way to indirectly identify the presence of environmental pollutants that negatively affect fish life, its production and quality. Monitoring individual and collective behaviours produces large amounts of non-linear data that require tailor-suited computational methods to interpret and manage the information. Fractal dimension (FD) and entropy are two groups of such non-linear analysing methods that serve as indicators of the complexity (FD) and predictability (entropy) of the behaviours. Since behavioural complexity and predictability may be modulated by contaminants, the changes in its FD and entropy values have a clear potential to be embedded in a biological early warning system (BEWS), which may be particularly useful in Precision Fish Farming settings and to monitor wild populations. This work presents a review of the effects of a wide range of environmental contaminants, including toxic compounds, cleaning and disinfecting agents, stimulant (caffeine), anaesthetics and antibiotics, heavy metals (lead, cupper, and mercury), selenium, pesticides and persistent environmental pollutants, on the FD and entropy values of collective and individual behavioural responses of different fish species. All the revised studies demonstrate the usefulness of both FD and entropy to indicate the presence of pollutants and underline the need to consider early changes in the trend of the evolution of their values prior to them becoming significantly different from the control values, i.e., while it is still possible to identify the contaminant and preserve the health and integrity of the fish.

Feeding 3.9 and 6.7 mg Hg/kg (Se/Hg molar ratios of 0.8 and 0.4, respectively) for 14 days negatively affected Dicentrarchus labrax growth and total DNTB- and thioredoxin-reductase (TrxR) activities and the transcription of four redox genes (txn1, gpx1, txnrd3, and txnrd2) in the liver, but a diet with 0.5 mg Hg/kg (Se/Hg molar ratio 6.6) slightly increased both reductase activities and the transcription of txn1, gpx1, and txnrd2. Feeding 6.7 mg Hg/kg for 53 days downregulated the genes of the thioredoxin system (txn1, txnrd3, and txnrd2) but upregulated gpx1, confirming the previously proposed complementarity among the antioxidant systems. Substitution of 20% of the feed by thawed white fish (hake) slightly counteracted the negative effects of Hg. The effects were not statistically significant and were dependent, in a non-linear manner, on the Se/Hg molar ratio of the feed but not on its Hg concentration. These results stress the need to consider the Se/Hg molar ratio of the feed/food when evaluating the toxicity of Hg.

This review presents some applications of proteomics and selected spectroscopic methods to validate certain aspects of seafood traceability. After a general introduction to traceability and the initial applications of proteomics to authenticate traceability information, it addresses the application of proteomics to trace seafood exposure to some increasingly abundant emergent health hazards with the potential to indicate the geographic/environmental origin, such as microplastics, triclosan and human medicinal and recreational drugs. Thereafter, it shows the application of vibrational spectroscopy (Fourier-Transform Infrared Spectroscopy (FTIR) and Fourier-Transform Raman Spectroscopy (FT Raman)) and Low Field Nuclear Magnetic Resonance (LF-NMR) relaxometry to discriminate frozen fish from thawed fish and to estimate the time and temperature history of frozen fillets by monitoring protein modifications induced by processing and storage. The review concludes indicating near future trends in the application of these techniques to ensure seafood safety and traceability.

This review presents the primary applications of various proteomic strategies to evaluate the impact of farming conditions on food quality and safety in aquaculture products. Aquaculture is a quickly growing sector that represents 47% of total fish production. Food quality, dietary management, fish welfare, the stress response, food safety, and antibiotic resistance, which are covered by this review, are among the primary topics in which proteomic techniques and strategies are being successfully applied. The review concludes by outlining future directions and potential perspectives.

The present study aims at identifying the lowest number of fish (European seabass) that could be used for monitoring and/or experimental purposes in small-scale fish facilities by quantifying the effect that the number of individuals has on the Shannon entropy (SE) of the trajectory followed by the shoal's centroid. Two different experiments were performed: (i) one starting with 50 fish and decreasing to 25, 13, and 1 fish, and (ii) a second experiment starting with one fish, adding one new fish per day during 5 days, ending up with five fish in the tank. The fish were recorded for 1h daily, during which time a stochastic event (a hit in the tank) was introduced. The SE values were calculated from the images corresponding to three arbitrary basal (shoaling) periods of 3.5 min prior to the event, and to the 3.5 min period immediately after the event (schooling response). Taking both experiments together, the coefficient of variation (CV) of the SE among measurements was largest for one fish systems (CV 37.12 and 17.94% for the daily average basal and response SE, respectively) and decreased concomitantly with the number of fish (CV 8.6-10% for the basal SE of 2 to 5 fish systems and 5.86, 2.69, and 2.31% for the basal SE of 13, 25, and 50 fish, respectively). The SE of the systems kept a power relationship with the number of fish (basal: R-2 = 0.93 and response: R-2 = 0.92). Thus, 5-13 individuals should be the lowest number for a compromise between acceptable variability (< 10%) in the data and reduction in the number of fish. We believe this to be the first scientific work made to estimate the minimum number of individuals to be used in subsequent experimental (including behavioral) studies using shoaling fish species that reaches a compromise between the reduction in number demanded by animal welfare guidelines and a low variability in the fish system's response.

The present study investigates the suitability of a machine vision-based method to detect deviations in the Shannon entropy (SE) of a European seabass (Dicentrarchus labrax) biological system fed with different selenium:mercury (Se:Hg) molar ratios. Four groups of fish were fed during 14 days with commercial feed (control) and with the same feed spiked with 0.5, 5 and 10 mg of MeHg per kg, giving Se:Hg molar ratios of 29.5 (control-C1); 6.6, 0.8 and 0.4 (C2, C3 and C4). The basal SE of C1 and C2 (Se:Hg > 1) tended to increase during the experimental period, while that of C3 and C4 (Se:Hg < 1) tended to decrease. In addition, the differences in the SE of the four systems in response to a stochastic event minus that of the respective basal states were less pronounced in the systems fed with Se:Hg molar ratios lower than one (C3 and C4). These results indicate that the SE may be a suitable indicator for the prediction of seafood safety and fish health (i.e., the Se:Hg molar ratio and not the Hg concentration alone) prior to the displaying of pathological symptoms. We hope that this work can serve as a first step for further investigations to confirm and validate the present results prior to their potential implementation in practical settings.

The present work explores the capacity of a machine vision system to detect deviations in the Shannon entropy (SE) of a European seabass (Dicentrarchus labrax) biological system in response to MeHg contaminated feed. Three groups of fish were exposed for 2 weeks to 0.5, 5 and 10 ppm of methylmercury (MeHg) in the feed and compared to a group whose feed was not artificially contaminated. No mortality was observed during the 2 weeks experimental period. The SE of the experimental cases was modified by the presence of MeHg, confirming our previous works. However, no clear dosedependent responses of the systems' SE to MeHg administration were detected during the 2 weeks period, although there was a different tendency in the evolution of SE during the experimental period between the non-exposed group and the exposed ones.

Burnt tuna (BT), or yake-niku, is a quality flaw of the muscle characterised by a pale colour and grainy and exudative texture. Cathepsin-L, water soluble and total protein components from normal and BT muscles, from three tropical tuna species – yellowfin (YFT, Thunnus albacares), bigeye (BET, Thunnus obesus) and skipjack (SKJ, Katsuwonus pelamis) – were compared by electrophoretic and western blot analyses to identify biomarkers for BT. As expected, SDS–PAGE patterns were species-specific but differences, due to BT, were observed only between some low ionic strength extracts of BET and YFT. Protein oxidation and cell proliferation analysed by immunoblotting did not show differences between BT and normal muscles. Gelatine zymography revealed different gelatinase activity patterns that, although not linked to BT, may affect the final texture of the muscle. A 43 kDa band, identified as creatine kinase by proteomic analysis, showed the potential to be a good indicator for BT in BET and YFT.

This article introduces the application of proteomics to food and nutrition studies. It contains a brief description of what proteomics is and the main laboratory requirements to perform the analyses followed by a technical part that includes the main applications of proteomics (protein identification and characterization, differential proteomics, and functional proteomics), the proteomic workflow, and mass spectrometric analysis. Then, proteomic studies applied to food groups are illustrated using cereals and fruits, dairy products, eggs, meat, seafood, and bioactive compounds as examples. Finally, the concept of systems biology and its application to nutritional studies is introduced to the reader.

Methylmercury (MeHg) is an environmental contaminant of increasing relevance as a seafood safety hazard that affects the health and welfare of fish. Non-invasive, on-line methodologies to monitor and evaluate the behavior of a fish system in aquaculture may make the identification of altered systems feasible—for example, due to the presence of agents that compromise their welfare and wholesomeness—and find a place in the implementation of Hazard Analysis and Critical Control Points and Fish Welfare Assurance Systems. The Shannon entropy (SE) of a European seabass (Dicentrarchus labrax) system has been shown to differentiate MeHg-treated from non-treated fish, the former displaying a lower SE value than the latter. However, little is known about the initial evolution of the system after removal of the toxicant. To help to cover this gap, the present work aims at providing information about the evolution of the SE of a European seabass system during a recuperation period of 11 days following a two-week treatment with 4 µg·MeHg/L. The results indicate that the SE of the system did not show a recovery trend during the examined period, displaying erratic responses with daily fluctuations and lacking a tendency to reach the initial SE values.

The development of non-invasive methods for fish welfare and contaminant monitoring is of high relevance for the production of high quality and safe farmed fish. We have recently shown the suitability of the Shannon entropy (SE) in a commercially relevant fish system (European seabass, Dicentrarchus labrax) to differentiate methylmercury (MeHg) treated fish from non-treated fish. The present work examines the evolution of the SE of a European seabass system during an 11 days recuperation period immediately after a 2 weeks treatment with 4 μg MeHg/L (Case C2) and compares it to that of a control group not treated with MeHg (Case 1). While the SE of the C1 increased during the recuperation period, that of C2 showed erratic responses with a very modest decreasing trend.

The objective of the work was to investigate the potential of low-field nuclear magnetic resonance of protons (1H LF NMR) relaxometry to produce indicators useful in the estimation of the quality and shelf life of frozen hake (Merluccius merluccius L.) muscle as affected by storage temperature and time. 1H low-field NMR T 2 transverse relaxation measurements were performed from fillets of a total of 145 hakes that had been stored at −10, −20, −30, or −80 °C for up to 150 weeks. The principal component (PC) scores from the 1H LF NMR distribution of T 2 relaxation times were adjusted to zero-order kinetics and the reaction rates followed an Arrhenius-type pattern. Kinetic modeling using the PC scores of the 12–400-ms range resulted in the best model corresponding to both T 21 and T 22 regions. The temperature dependency of the rate of reactions, measured by B values, was similar to that previously found for shear resistance and for the hydrolysis of phospholipids, well-known markers related to the sensory quality in this species. Thus, our results suggest that this methodology has a great potential to evaluate the frozen storage time and temperature in hake as well as to provide an indication of the expected quality of the fillet.

The annual global increase in the production, particularly from aquaculture, and consumption of seafood is expected to continue in the future. One of the main worldwide concerns from the point of view of seafood safety is the increasing number of novel and unexpected chemical substances that contaminate the aquatic environment. Currently, there is a lack of cost effective, user-friendly methods to detect many of these contaminants and there is no method to detect unknown contaminants. A paradigm shift is necessary in the seafood production industry from contaminant detection only, to monitoring the effects of the contaminants as well. This can be achieved by introducing a systems approach and using a biological warning system (BWS) specifically adapted to fish farming. In this manner, it would be possible to develop affordable, on-line identification of production units displaying atypical responses or behaviour and therefore potentially contaminated regardless of whether the contaminant is an identified or an unknown substance. Once developed, the BWS should be implemented within the HACCP plans and the results accompany the traceability documentation of the products.

In light of the Marine Strategy Framework Directive (MSFD) and the EU Thematic Strategy on the Sustainable Use of Natural Resources, environmental biotechnology could make significant contributions in the exploitation of marine resources and addressing key marine environmental problems. In this paper 14 propositions are presented focusing on (i) the contamination of the marine environment, and more particularly how to optimize the use of biotechnology-related tools and strategies for predicting and monitoring contamination and developing mitigation measures; (ii) the exploitation of the marine biological and genetic resources to progress with the sustainable, eco-compatible use of the maritime space (issues are very diversified and include, for example, waste treatment and recycling, anti-biofouling agents; bio-plastics); (iii) environmental/marine biotechnology as a driver for a sustainable economic growth.

The objective of the work was to develop a non-invasive methodology for image acquisition, processing and nonlinear trajectory analysis of the collective fish response to a stochastic event. Object detection and motion estimation were performed by an optical flow algorithm in order to detect moving fish and simultaneously eliminate background, noise and artifacts. The Entropy and the Fractal Dimension (FD) of the trajectory followed by the centroids of the groups of fish were calculated using Shannon and permutation Entropy and the Katz, Higuchi and Katz-Castiglioni’s FD algorithms respectively. The methodology was tested on three case groups of European sea bass (Dicentrarchus labrax), two of which were similar (C1 control and C2 tagged fish) and very different from the third (C3, tagged fish submerged in methylmercury contaminated water). The results indicate that Shannon entropy and Katz-Castiglioni were the most sensitive algorithms and proved to be promising tools for the non-invasive identification and quantification of differences in fish responses. In conclusion, we believe that this methodology has the potential to be embedded in online/real time architecture for contaminant monitoring programs in the aquaculture industry.