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Article

Impact of Harvest Method on Development of European Sea Bass Skin Microbiome during Chilled Storage

by
Rafael Angelakopoulos
1,
Andreas Tsipourlianos
1,
Alexia E. Fytsili
1,
Themistoklis Giannoulis
2 and
Katerina A. Moutou
1,*
1
Laboratory of Genetics, Comparative and Evolutionary Biology, Department of Biochemistry and Biotechnology, School of Medical Sciences, University of Thessaly, Viopolis, Mezourlo, 41500 Larissa, Greece
2
Laboratory of Biology, Genetics and Bioinformatics, Department of Animal Science, University of Thessaly, Greece Gaiopolis, 41334 Larissa, Greece
*
Author to whom correspondence should be addressed.
Aquac. J. 2024, 4(4), 270-282; https://doi.org/10.3390/aquacj4040020
Submission received: 20 September 2024 / Revised: 4 October 2024 / Accepted: 14 October 2024 / Published: 16 October 2024
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Abstract

:
European sea bass (Dicentrarchus labrax) is one of the most significant species farmed in the Mediterranean, yet a very perishable product. Its quality deteriorates rapidly as a result of three mechanisms: microbial activity, chemical oxidation, and enzymatic degradation. Microbial spoilage is the mechanism that contributes most to the quality deterioration of fresh and non-processed fish. To this end, our study aims to identify for the first time the combined effect of aquatic environment and harvest method on the composition and trajectory at storage at 0 °C of the European sea bass skin microbiome. Sampling was performed in two commercial fish farms in Western (WG) and Central Greece (CG) where fish were harvested using different methods: direct immersion in ice water or a mixture of slurry ice; application of electro-stunning prior to immersion in ice water. Samples were collected on harvest day and one week post-harvest. To profile the bacterial communities in the fish skin, 16S ribosomal RNA gene sequencing was used. The results and the following analyses indicated that the aquatic environment shaped the original composition of the skin microbiome, with 815 ASVs identified in the WG farm as opposed to 362 ASVs in the CG farm. Moreover, Pseudomonas and Pseudoalteromonas dominated the skin microbiome in the WG farm, unlike the CG farm where Shewanella and Psychrobacter were the dominant genera. All these genera contain species such as Shewanella putrefaciens, Pseudomonas aeruginosa, Pseudoalteromonas spp., and Psychrobacter sp., all of which have been implicated in the deterioration and spoilage of the final product. The different harvest methods drove variations in the microbiome already shaped by the aquatic environment, with electro-stunning favoring more diversity in the skin microbiome. The aquatic environment in combination with the harvest method appeared to determine the skin microbiome trajectory at storage at 0 °C. Although Shewanella had dominated the skin microbiome in all samples one week post-harvest, the diversity and the relative abundance of genera were strongly influenced by the aquatic environment and the harvest method. This study sheds light on the hierarchy of the factors shaping the fish skin microbiome and their importance for controlling post-harvest quality of fresh fish.

1. Introduction

Fish farming is the fastest-growing sector of food production, with the potential to contribute to the nutritional needs of the global expanding population and to food security [1,2]. However, fresh fish is a highly perishable food product that degrades rapidly after death, resulting in large post-harvest losses [3]. It is estimated that over ten million tons of fresh fish are lost to post-harvest wastage per year [2], with a significant percentage being lost or wasted along the fish supply chain [4]. Fish handling, transportation, harvesting methods, and storage operations account for the majority of reported losses in the aquaculture industry [4].
Among the primary mechanisms of quality deterioration, microbial spoilage plays a predominant role [5,6]. The skin microbiome holds a key role in the post-harvest quality of fish, as the skin of the fish is known to be a breeding ground for spoilage bacteria like Pseudomonas spp. and Shewanella putrefaciens. The biogenic amines and volatile compounds that these bacteria produce, along with the off-odors, impair the fish’s sensory and safety qualities [7,8]. The inherent qualities of the product, combined with inevitable microbiological activity, result in a short shelf life for whole fresh fish. Fish species, storage temperature, initial microbial contamination, and packaging conditions are some of the elements that affect fish shelf life [9]. While the highest tolerable microbial load for fish has been generally accepted to be 107 CFU/g [10], sensory rejection has been generally observed at microbial levels between 106 and 109 cfu/g. This variation is largely due to the diversity of spoilage microorganisms, as not all microbes contribute equally to spoilage. Certain bacteria can produce off-odors, slime, or texture changes more rapidly than others, leading to spoilage and sensory rejection at lower microbial levels in a number of cases [8,11,12,13,14,15,16].
As bacteria develop, they utilize nutrients and produce by-products. According to Gram and Dalgaard [17], specific spoilage organisms (SSOs) usually make up a portion of the original microbiome, and their eventual expansion causes undesirable alterations in the product quality. Together with Gram-positive bacteria, psychrotrophic Gram-negative rod-shaped bacteria make up most of the microbiome in fresh marine fish [7]. The prevalence of SSOs over the initial microbiome depends on the type of fish, atmospheric conditions during storage, temperature, and the interactions between microorganisms leading to high concentrations of metabolites, which consecutively lead to product rejection.
The skin microbiome consists of bacteria, archaea, viruses, and eukaryotic microorganisms that inhabit animal mucosal surfaces as commensals, symbionts, or pathogens. Fish microbial communities are influenced by the dynamic environmental parameters, namely the physicochemical characteristics of the water (temperature, pH, oxygen content), the nutrient concentrations, and the microbiological characteristics of the water [18,19,20,21]. Farming practices also influence the microbial communities in the epidermal mucosa of fish. Overcrowding and low oxygen concentrations, common in fish farms, lead to host stress and dysbiosis in the skin microbiome, decreasing microbiome diversity and often promoting the proliferation of opportunistic pathogens [22,23].
European sea bass (Dicentrarchus labrax) is an emblematic species of Mediterranean aquaculture and the EU [24,25]. A product with high organoleptic characteristics, high levels of omega-3 fatty acids, and high-quality protein, it sustains substantial economic activity [2,26]. The most abundant taxa found in the gills and skin of healthy farmed sea bass belong to the phyla Proteobacteria, Bacteroidetes, and Verrucomicrobia. At the genus level, Rubritalea and Pseudomonas are highly abundant, followed by Polaribacter, Polynucleobacter, and Arcobacter [27,28].
Determining the post-harvest trajectory of the sea bass skin microbiome is essential to comprehending and preventing product deterioration. It is essential to identify important microbial species or communities linked to spoiling and to create focused control or mitigation methods towards maximizing shelf life and optimizing storage conditions. This study was designed to add on to previous work [29] that emphasizes the impact of environmental variations on the composition of the sea bass skin microbiome by comparing skin microbiome variations between farms located in Western and Central Greece. More importantly, this study investigates the combined effect of the farming environment and the harvest method on the trajectory of the sea bass skin microbiome over storage at 0 °C. Harvesting methods commonly used in Mediterranean aquaculture, such as net crowding and immersion in ice slurry, are recognized sources of stress for farmed fish. Advances such as slurry ice enhance cooling efficiency and minimize physical damage compared with the conventional ice water harvest [30,31], and innovations like the use of electrical stunning [32] provide a rapid and effective means to induce unconsciousness in fish, thereby ensuring minimal stress during the harvesting process. The effect of the various harvest methods on the sea bass skin microbiome is explored as a parameter that influences the microbiome trajectory at storage of the fresh product. Expanding our knowledge on the factors shaping the microbiome at storage can help identify strategies to improve product quality and shelf life, benefiting both producers and consumers.

2. Materials and Methods

2.1. Ethics Statement

All examined biological materials were derived from fish reared and harvested at commercial farms, registered for aquaculture production in EU countries. Animal sampling followed routine procedures and samples were collected by a qualified staff member from standard production cycles. The legislation and measures implemented by the commercial producers complied with existing national and EU (Directive 1998/58/EC) legislation (protection of animals kept for farming).

2.2. Fish Sampling and Sample Collection

Sampling of commercial-sized European sea bass (Dicentrarchus labrax), weighing between 300 and 500 g, was conducted on harvest days at two commercial fish farms located in Western (WG) and Central Greece (CG). The sea water temperatures at harvest were 20 °C and 21 °C, respectively. Fish were harvested using different methods. In the CG farm, ice water (IC) or 100% slurry ice (SI) or 1:1 slurry ice/ice flakes (S50) were used. In the WG farm, direct immersion in ice water (IC) was also used, while the alternative harvest methods included application of electrical stunning prior to immersion in ice water, with a high current (HC, electric field 1.8 V/cm and velocity 1.6 m/s) or low current (LC, electric field 1.5 V/cm and velocity 1.6 m/s). The first sampling was performed in situ on harvest day. Subsequently, fish were packed as a whole in polystyrene boxes filled with ice flakes and transported without bleeding to the Department of Biochemistry and Biotechnology, University of Thessaly. Upon arrival, the boxes were stored isothermally at 0 °C in high-precision (±0.2 °C) professional low-temperature incubators. A second sampling of the stored samples was performed one week post-harvest (week). In each case, a sterile scalpel blade was used to swab the right upper lateral part of each fish from head to tail multiple times. Skin along with scales and mucus were then transferred into sterile Eppendorf tubes and stored at −80 °C until further processing. Eight out of twenty-five individuals were selected from each condition.

2.3. DNA Extraction

DNA was extracted using the PureLink™ Genomic DNA Mini Kit (Invitrogen, Waltham, MA, USA-Catalog number: K182002), with modifications to optimize yield and purity. Briefly, 5M NaCl, 10 mg/μL of lysozyme, 20 mg/μL of proteinase K, and 350 μL of the kit lysis buffer were added to the samples, which were then incubated at 55 °C for 2 h. Following incubation, the samples were homogenized with glass beads using a Precellys tissue homogenizer (3 min at 8000 rpm). The manufacturer’s protocol was followed to complete the DNA purification process. DNA was quantified using a Qubit® fluorometer with a Quant-iT™ dsDNA broad range (BR) Assay Kit (Invitrogen, Waltham, MA, USA-Catalog number: Q32850).

2.4. Amplicon Sequencing

In total, 12 collective samples were created by pooling equimolarly DNA from 8 fish per condition. Microbial diversity analysis for total bacteria was performed via multiplex amplicon sequencing in a HiSeq 2500 System®—Rapid Mode (Illumina Inc., San Diego, CA, USA) 2 × 250 bp paired-end by BGI, Genomics Co Ltd (Hong Kong, China). The target region for sequencing was the hypervariable V3–V4 region of the 16S (small ribosomal subunit) gene. The V3–V4 regions, widely preferred for Illumina sequencing due to their comprehensive coverage and detection depth, facilitate the distinction between closely related bacterial taxa [33].

2.5. Bioinformatics Analysis

Sequence reads were quality trimmed at the first instance of Phred Q values ≤ 2 in the 3′ to 5′ direction. Sequences with unknown bases, a maximum error rate of 0.7 per 100 bp of reads, or lengths shorter than 225 bp post-trimming were removed from the dataset. The remaining sequences were dereplicated and error-corrected using the DADA2 machine learning and rare event removal algorithm. Passing read-pairs were assembled into amplicon sequence variants (ASVs) with the DADA2 read-pair assembler. Generated contigs were checked for chimeric amplicons using the native de novo approach [34].
For the classification of the V3-V4 16S rRNA amplicons, sequences were classified with the naïve Bayesian classifier [35] using the Silva v138 database [36] and an 80% bootstrap cutoff for total prokaryotes. After annotation, relational database objects were formed using the Phyloseq v1.38.0 R package [37], and off-target sequences were removed from the generated object. All analyses were performed in R Studio [38,39].

3. Results and Discussion

After high-throughput sequencing of 12 collective samples and quality control, clean data (Table 1) were used for further data cleaning and processing, and an average of 145,080 reads per sample were retained, ensuring high-quality data for subsequent analyses.
The analysis, after filtering out archaea, chloroplasts, and mitochondria, yielded 2571 amplicon sequence variants (ASVs) corresponding to 343 different genera, which belonged to 172 families (Supplementary Tables S1–S3).
The genera Shewanella, Psychrobacter, Pseudomonas, and Flavobacterium were present across all comparisons, indicating their widespread occurrence (Table 2, Figure 1). Microbial composition analysis revealed Proteobacteria and Bacteroidetes as the most abundant phyla (Table 3), in accordance with the current knowledge on the skin microbiome of European sea bass [28,29,40,41,42].
The Shannon and Simpson indices were used for comparing 16S bacterial samples because they provide complementary insights into the richness and evenness of bacterial communities, allowing for a more comprehensive assessment of diversity and community structure. Shannon and Simpson indices of alpha diversity revealed two main findings: (a) the CG farm demonstrated higher diversity compared with the WG farm, and (b) one week post-harvest, an increase in diversity was observed across all harvest methods, except for the IC group in the CG farm (Figure 2).
The analysis, conducted exclusively within the IC group due to it being the only common harvest method between the two farms, revealed distinct differences in dominant genera. In the WG farm, Pseudoalteromonas (44.46%) and Pseudomonas (25.05%) were the most prevalent, with Shewanella (13.73%) and Psychrobacter (7.82%) also present. In contrast, the CG farm was dominated by Shewanella (55.81%) and Psychrobacter (42.15%), with Pseudoalteromonas and Pseudomonas being nearly absent (<1%) (Table 4, Figure 1). Our results are in agreement with a previous study reporting the high presence of Pseudomonas and Pseudoalteromonas in gilthead seabream samples from the Ionian Sea as compared to samples from the Aegean Sea [29]. Pseudomonas may inhibit the growth of Shewanella and other microorganisms through the production of ferric compounds and antibiotics [43]. Pseudomonas is known for its ability to produce siderophores, which are iron-chelating compounds. These siderophores bind available iron, limiting the resources for competing bacteria like Shewanella, which rely on iron for growth and metabolism. Studies show that Pseudomonas strains with high siderophore production significantly inhibit the growth of Shewanella in fish extracts, particularly under low-iron conditions. Furthermore, some Pseudomonas strains may also produce other antibacterial compounds, such as phenazines or hydrogen cyanide, contributing to the suppression of Shewanella [43]. The high frequency of Shewanella in the Aegean samples is likely due to its high abundance in the Aegean Sea [44], and its presence in sea bass from fish farms in this region has also been reported elsewhere [45]. Thus, geographical origin appears to significantly influence the composition and development of the initial microbiome, potentially leading to different dominant spoilage microorganisms.
The initial/symbiotic microbiome is known to be highly dependent on the aquatic environment in which the fish dwell, as well as the handling and storage conditions during fish processing [46,47,48]. To this direction, this study also investigated how different harvest methods affect the skin microbiome of European sea bass. The harvest methods used were previously described [31,32]. Harvest method had a direct effect on the microbial composition post-harvest. On harvest day, samples from the IC, SC, and S50 groups showed a strong presence of Shewanella and Psychrobacter genera (Table 5). This is expected, as these bacteria are psychrotrophic and part of the core microbiome of European sea bass [28,29,49]. Differences in the distribution of Shewanella and Psychrobacter were observed, with comparable abundances in the IC and S50 groups. The highest relative abundance of Shewanella (89.48%) was observed in the SI group, while the highest abundance of Psychrobacter (42.15%) was found in the IC group. This difference is likely due to the physicochemical properties of slurry ice, a liquid with high viscosity comparable to ice water. Slurry ice reduces temperature more rapidly and to lower levels than ice water and results in a greater reduction in oxygen supply [30] (Figure 1, Table 5).
In fish harvested using electro-stunning prior to submersion in ice water, differences in the microbial community were observed (Table 6), consistent with findings by Papaharisis et al. (2019), who reported statistically significant differences in the Total Viable Count in whole European sea bass [12]. Predominant genera such as Pseudoalteromonas, Pseudomonas, and Shewanella, which are detected in high abundance with the ice water method (IC), were present in less than 3%. Conversely, genera like Methylococcus, Catenococcus, and Tenacibaculum were detected in higher percentages. Electrical stunning may affect mucus secretion [50], altering the fish’s physiological state and potentially creating conditions on the skin that favor the growth of certain genera. Changes in the composition and quantity of mucus, which serves as the primary substrate for microbial colonization, could influence the availability of nutrients or create a more hostile environment for certain bacteria while favoring others [51]. Furthermore, electrical stunning could cause minor disruptions to cellular membranes in both the fish and associated microbes. This can alter the permeability of the skin, potentially allowing different nutrients to be released [52,53,54]. Electro-stunning can affect the pH and temperature of the skin surface, creating microenvironmental changes that could favor different microbial species. Changes in these parameters can influence bacterial growth rates and competitiveness, potentially fostering a more diverse microbial ecosystem on the fish skin [55]. The combination of electro-stunning followed by immersion in ice water creates a unique set of environmental conditions that can lead to significant shifts in the skin microbiome. The transition from the physiological impact of electro-stunning to the cold environment of ice water may result in a restructuring of the microbial community. Additionally, competition between different species can lead to variations in microbial composition, with Methylococcus likely originating from plant feed used in farmed fish [56] (Figure 1, Table 6).
For the first time, the findings of this study provide critical insights into the microbiome profile and spoilage dynamics of European sea bass following different harvest methods and storage at 0 °C. In agreement with previous studies, one week post-harvest, samples harvested in ice water in the CG farm exhibited a high relative abundance of Shewanella, Psychrobacter, Pseudomonas, and Carnobacterium [46,57,58]. Shewanella was significantly abundant across all harvest methods, with the highest levels recorded in those using slurry ice. This bacterium is known for its rapid growth at 4 °C, which likely explains its higher abundance in samples treated with slurry ice. The rapid temperature reduction provided by slurry ice may create an optimal environment for Shewanella proliferation [58,59]. This is particularly important for the seafood industry, as Shewanella is a known spoilage organism in fish and frozen food.
Pseudomonas and Carnobacterium showed increased abundance in the IC group after one week of storage, whereas their levels were lower in slurry ice treatments (Table 5). Carnobacterium is a renowned spoilage microorganism that can cause product rejection if its levels exceed 107 CFU/g [10,60]. Psychrobacter levels remained unchanged in the IC group one week post-harvest, but showed a decline in both the SI and S50 groups (Table 5). The use of slurry ice presents a promising method to control these bacteria and enhance the shelf life of sea bass, aligning with the general understanding that rapid cooling can inhibit the growth of certain spoilage bacteria [30,58] (Figure 3, Table 5).
Interestingly, the use of electrical stunning methods did not significantly reduce the numbers of spoilage microorganisms, including Shewanella, Pseudomonas, Pseudoalteromonas, and Carnobacterium, over storage (Figure 3, Table 6). Although the initial abundance of these genera was low after electro-stunning, they exhibited a high growth rate during storage. Electrical stunning appeared to directly influence the microbiome diversity post-harvest; the initial shock likely reduced the abundance of certain genera such as Shewanella, Pseudomonas, and Pseudoalteromonas, while it might have affected other interacting genera, thereby influencing microbe–microbe interactions during storage at 4 °C [12]. This suggests that while electrical stunning may be beneficial for animal welfare and operational efficiency, it does not confer substantial microbiological benefits in terms of spoilage reduction.
When comparing the microbial communities within the IC group on harvest day, significant differences were observed between the WG and CG farms. Only 135 ASVs were shared, with the WG farm exhibiting 680 unique ASVs of lower abundance, emphasizing the distinct microbial profiles of each location (Figure 4).

4. Conclusions

This study provides valuable insights for aquaculture by highlighting the influence of the aquatic environment and harvesting methods on the skin microbiome of European sea bass, which is critical for extending shelf life. For the first time, variations in microbiome composition due to location and harvesting methods, following storage at 0 °C, were analyzed. Both factors significantly impacted the microbiome, with the initial composition shaped by the environment and later altered by harvesting methods, particularly electro-stunning. The use of slurry ice proved effective in controlling spoilage bacteria. Although the sample size was limited, understanding these effects is essential for improving fish immunity and shelf life through microbiome management in fish farming and post-harvest processes, thus preserving the value of sea bass products. A potential optimization of the harvest methods could involve combining the two methods. By summarizing all the above, we propose that the electro-stunning method followed by submersion in slurry ice may lead to the desired results by improving the shelf life of the products and the quality of the fillet. This could be achieved by reducing the microbial diversity and the fillet degradation rhythm and by minimizing the stress during harvest.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/aquacj4040020/s1: Table S1: Relative genus abundance; Table S2: Relative family abundance; Table S3: Relative phylum abundance.

Author Contributions

Conceptualization, K.A.M.; methodology, R.A., A.T., A.E.F. and T.G.; sampling, R.A. and A.T.; investigation, R.A., A.T. and A.E.F.; data curation, R.A., A.T., A.E.F. and T.G.; writing—original draft preparation, R.A., A.T. and A.E.F.; writing—review and editing, T.G. and K.A.M.; visualization, R.A. and A.T.; supervision, K.A.M.; project administration, K.A.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was co-financed by Greece and the European Union, European Maritime and Fisheries Fund in the context of the implementation of the Greek Operational Programme for Fisheries, Priority Axis “Innovation in Aquaculture”. 1. Project title: “Development and application of novel methods for fish harvesting and processing for quality improvement and shelf-life extension” (2018–2021) MIS 5010939. 2. Project title: “Development and industrial scale evaluation of an innovative humane slaughter system and assessment of welfare in aquaculture marine fish species” MIS 5010690.

Institutional Review Board Statement

The animals used in this study were reared in commercial installations registered for aquaculture production in EU countries, following certified procedures (GLOBAL GAP) of commercial production. The legislation and measures implemented by the commercial producers complied with existing national and EU (Directive 1998/58/EC) legislation (protection of animals kept for farming). The ultimate objective of the study was to avoid unnecessary pain and suffering during harvest.

Informed Consent Statement

Not applicable.

Data Availability Statement

All consensus sequences were submitted to the Short Read Archive (SRA) under Accession No PRJNA1136259.

Conflicts of Interest

The authors declare no conflicts of interest.

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Aquacj 04 00020 g001
Figure 1. Relative abundance (%) of all bacterial genera with a contribution higher than 3% detected in the European sea bass skin samples.
Figure 1. Relative abundance (%) of all bacterial genera with a contribution higher than 3% detected in the European sea bass skin samples.
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Figure 2. Shannon and Simpson indices of alpha diversity of European sea bass skin. Blue: WG farm, orange: CG farm.
Figure 2. Shannon and Simpson indices of alpha diversity of European sea bass skin. Blue: WG farm, orange: CG farm.
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Figure 3. Heatmap of the evolution of the skin microbiome one week post-harvest based on the relative abundance (%) of bacterial genera in European sea bass skin samples.
Figure 3. Heatmap of the evolution of the skin microbiome one week post-harvest based on the relative abundance (%) of bacterial genera in European sea bass skin samples.
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Figure 4. Number and percentage of abundance of distinct and shared bacterial amplicon sequence variants (ASVs) in European sea bass skin samples between the two farms, on harvest day.
Figure 4. Number and percentage of abundance of distinct and shared bacterial amplicon sequence variants (ASVs) in European sea bass skin samples between the two farms, on harvest day.
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Table 1. Number of raw and clean reads per sample.
Table 1. Number of raw and clean reads per sample.
GeographyDayHarvest MethodRaw ReadsClean ReadsRead Utilization Ratio (%)Reads Used for the Analysis
Western GreeceHarvest dayIC176,766168,49095.32142,586
Harvest dayHC175,402166,94295.18139,064
Harvest dayLC173,644166,44695.85141,201
One week post-harvestIC173,172165,80295.74143,016
One week post-harvestHC174,944166,38295.11151,340
One week post-harvestLC172,094164,59895.64149,879
Central GreeceHarvest dayIC170,766164,99696.62138,704
Harvest daySI171,372165,29496.45150,699
Harvest dayS50170,882165,22496.69145,253
One week post-harvestIC171,926166,16696.65148,649
One week post-harvestSI173,442166,48895.99145,874
One week post-harvestS50173,162166,78096.31144,691
Table 2. Relative abundance (%) of the genera shared among all European sea bass skin samples.
Table 2. Relative abundance (%) of the genera shared among all European sea bass skin samples.
GenusWestern GreeceCentral Greece
Harvest DayOne Week Post-HarvestHarvest DayOne Week Post-Harvest
ICHCLCICHCLCICSIS50ICSIS50
Shewanella13.73%0.44%0.26%43.63%72.61%56.44%55.81%89.48%67.13%34.89%81.27%82.03%
Psychrobacter7.82%9.07%26.64%3.47%0.66%10.62%42.15%8.69%30.60%40.73%4.33%4.89%
Pseudomonas25.05%0.14%0.15%6.32%8.48%3.58%0.18%0.54%0.06%12.93%1.57%1.67%
Flavobacterium1.24%2.25%0.30%0.04%7.84%0.20%0.49%0.01%0.67%0.02%3.13%2.04%
Other52.09%88.02%72.56%44.70%8.40%26.89%1.07%1.14%1.50%10.86%9.45%9.22%
Table 3. Relative abundance (%) of the phyla shared among all European sea bass skin samples.
Table 3. Relative abundance (%) of the phyla shared among all European sea bass skin samples.
PhylumWestern GreeceCentral Greece
Harvest DayOne Week Post-HarvestHarvest DayOne Week Post-Harvest
ICHCLCICHCLCICSIS50ICSIS50
Proteobacteria96.73%88.63%91.68%98.93%99.97%98.90%89.18%95.19%95.83%92.81%63.70%65.11%
Bacteroidota0.06%7.85%0.20%0.50%0.01%0.67%0.09%3.43%2.24%5.23%19.97%23.73%
Firmicutes3.18%3.46%8.11%0.57%0.01%0.43%10.68%0.84%1.41%0.91%9.67%7.38%
Other0.03%0.06%0.01%0.00%0.01%0.00%0.05%0.54%0.52%1.05%6.66%3.78%
Table 4. Relative abundance (%) of the common genera in European sea bass skin shared between farms in the IC group.
Table 4. Relative abundance (%) of the common genera in European sea bass skin shared between farms in the IC group.
GenusHarvest Day
IC
Western GreeceCentral Greece
Shewanella13.73%55.81%
Psychrobacter7.82%42.15%
Pseudoalteromonas44.46%0.49%
Pseudomonas25.05%0.18%
Aeromonas8.94%1.37%
Table 5. Relative abundance (%) of the highly abundant genera in the European sea bass skin microbiome trajectory in the CG farm.
Table 5. Relative abundance (%) of the highly abundant genera in the European sea bass skin microbiome trajectory in the CG farm.
GenusCentral Greece
ICSIS50
Harvest DayOne Week
Post-Harvest		Harvest DayOne Week
Post-Harvest		Harvest DayOne Week
Post-Harvest
Shewanella55.81%34.89%89.48%81.27%67.13%82.03%
Psychrobacter42.15%40.73%8.69%4.33%30.60%4.89%
Pseudoalteromonas0.49%0.00%0.99%0.05%1.05%4.05%
Pseudomonas0.18%12.93%0.54%1.57%0.06%1.67%
Carnobacterium0.38%10.45%0.01%0.02%0.25%0.10%
Flavobacterium0.49%0.02%0.01%3.13%0.67%2.04%
Vibrio0.00%0.00%0.00%5.34%0.00%0.04%
Other0.50%0.98%0.28%4.29%0.24%5.18%
Table 6. Relative abundance (%) of the highly abundant genera of the European sea bass skin microbiome trajectory in the Western Greek farm.
Table 6. Relative abundance (%) of the highly abundant genera of the European sea bass skin microbiome trajectory in the Western Greek farm.
GenusWestern Greece
ICLCHC
Harvest DayOne Week
Post-Harvest		Harvest DayOne Week
Post-Harvest		Harvest DayOne Week
Post-Harvest
Shewanella13.73%43.63%0.26%56.44%0.44%72.61%
Psychrobacter7.82%3.47%26.64%10.62%9.07%0.66%
Pseudoalteromonas44.46%41.41%1.07%18.72%2.62%4.85%
Pseudomonas25.05%6.32%0.15%3.58%0.14%8.48%
Catenococcus0.13%0.00%23.96%0.00%2.09%0.00%
Carnobacterium0.22%3.08%0.00%8.10%0.20%3.26%
Flavobacterium1.24%0.04%0.30%0.20%2.25%7.84%
Methylococcus0.00%0.00%0.00%0.00%13.64%0.00%
Weeksellaceae1.73%0.00%6.47%0.00%4.62%0.00%
Tenacibaculum0.56%0.00%5.73%0.00%6.29%0.01%
Vibrio0.08%0.00%0.67%0.00%2.55%0.00%
Aeromonas0.07%1.84%0.09%2.27%0.08%2.01%
Other4.91%0.21%34.66%0.07%56.01%0.28%
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Angelakopoulos, R.; Tsipourlianos, A.; Fytsili, A.E.; Giannoulis, T.; Moutou, K.A. Impact of Harvest Method on Development of European Sea Bass Skin Microbiome during Chilled Storage. Aquac. J. 2024, 4, 270-282. https://doi.org/10.3390/aquacj4040020

AMA Style

Angelakopoulos R, Tsipourlianos A, Fytsili AE, Giannoulis T, Moutou KA. Impact of Harvest Method on Development of European Sea Bass Skin Microbiome during Chilled Storage. Aquaculture Journal. 2024; 4(4):270-282. https://doi.org/10.3390/aquacj4040020

Chicago/Turabian Style

Angelakopoulos, Rafael, Andreas Tsipourlianos, Alexia E. Fytsili, Themistoklis Giannoulis, and Katerina A. Moutou. 2024. "Impact of Harvest Method on Development of European Sea Bass Skin Microbiome during Chilled Storage" Aquaculture Journal 4, no. 4: 270-282. https://doi.org/10.3390/aquacj4040020

APA Style

Angelakopoulos, R., Tsipourlianos, A., Fytsili, A. E., Giannoulis, T., & Moutou, K. A. (2024). Impact of Harvest Method on Development of European Sea Bass Skin Microbiome during Chilled Storage. Aquaculture Journal, 4(4), 270-282. https://doi.org/10.3390/aquacj4040020

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