Journal Description
Fishes
Fishes
is an international, peer-reviewed, scientific, open access journal published monthly online by MDPI. It covers fishes and aquatic animals research. The Iberian Society of Ichthyology (SIBIC) and the Brazilian Society of Aquaculture and Aquatic Biology (Aquabio) are affiliated with Fishes and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubAg, FSTA, and other databases.
- Journal Rank: JCR - Q2 (Marine and Freshwater Biology)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 18.2 days after submission; acceptance to publication is undertaken in 2.4 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about Fishes.
- Companion Journal: Aquaculture Journal
Impact Factor:
2.1 (2023);
5-Year Impact Factor:
2.4 (2023)
Latest Articles
Molecular Barcoding Identification of the Invasive Blue Crabs Along Tunisian Coast
Fishes 2024, 9(12), 485; https://doi.org/10.3390/fishes9120485 (registering DOI) - 28 Nov 2024
Abstract
Crabs are the most widely studied marine crustaceans due to their high economic value, ecological significance, and worldwide range in the subtropics and tropics zones. In this study, we adopted a molecular barcoding approach for rapid identification of blue crab species by sequencing
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Crabs are the most widely studied marine crustaceans due to their high economic value, ecological significance, and worldwide range in the subtropics and tropics zones. In this study, we adopted a molecular barcoding approach for rapid identification of blue crab species by sequencing the mitochondrial cytochrome c oxidase subunit I gene (COI), which has previously been used for phylogenetic analysis in wide taxonomic groups, and particularly for Crustaceans. The results indicated the evidence of Callinectes sapidus and Portunus pelagicus in different localities along Tunisian coast. Data were confirmed by BLAST analysis (Basic Local Alignment Tool) and phylogenetic trees. The molecular identification showed the ability of the COI region to differentiate between two similar blue crab species, Portunus segnis and Portunus pelagicus, which were confused by morphological analysis. The adoption of this protocol may be useful in revealing the biogeography of these invasive species across Mediterranean and to support the authentication of crab-meat processed products, according to the normative control.
Full article
(This article belongs to the Special Issue Genetics and Evolutionary Biology of Aquatic Invasive Organisms)
Open AccessReview
Antibiotic Residues in Cultured Fish: Implications for Food Safety and Regulatory Concerns
by
Dragana Ljubojević Pelić, Vladimir Radosavljević, Miloš Pelić, Milica Živkov Baloš, Nikola Puvača, Jurica Jug-Dujaković and Ana Gavrilović
Fishes 2024, 9(12), 484; https://doi.org/10.3390/fishes9120484 - 28 Nov 2024
Abstract
Antibiotics are widely recognized as significant chemical pollutants that enter the environment and ultimately the food chain. They are extensively used in both aquaculture and terrestrial animal breeding. Antibiotic residues in cultured fish pose significant public health risks, including the potential for antimicrobial
[...] Read more.
Antibiotics are widely recognized as significant chemical pollutants that enter the environment and ultimately the food chain. They are extensively used in both aquaculture and terrestrial animal breeding. Antibiotic residues in cultured fish pose significant public health risks, including the potential for antimicrobial resistance and adverse health outcomes. This review examines the widespread use of antibiotics in aquaculture, highlighting key challenges such as the lack of reliable data on antibiotic consumption in many regions as well as variability in regulatory enforcement. While strict regulations in European countries help to mitigate risks, the growing, often unregulated use of antibiotics in low- and middle-income countries exacerbates concerns over food safety. This paper provides an in-depth analysis of global regulatory frameworks and the impact of antibiotic residues on public health, and it offers recommendations for improving the monitoring, regulation, and responsible use of antibiotics in aquaculture in order to ensure safer food products from farmed fish. It contributes to a deeper understanding of the global scope of antibiotic misuse in aquaculture and points to an urgent need for more effective management practices.
Full article
(This article belongs to the Special Issue Pharmacokinetic in Aquatic Animals)
Open AccessArticle
Comprehensive Transcriptome Sequencing and Analysis of Euspira gilva: Insights into Aquaculture and Conservation
by
Zhixing Su, Jiayuan Xu, Xiaokang Lv, Xuefeng Song, Yanming Sui, Benjian Wang, Xiaoshan Wang, Bianbian Zhang, Baojun Tang and Liguo Yang
Fishes 2024, 9(12), 483; https://doi.org/10.3390/fishes9120483 - 28 Nov 2024
Abstract
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Euspira gilva, a member of the family Naticidae, is predominantly found in intertidal soft mud, sandy soil, and sandy seabeds along the coast of China, where it is valued for its nutritional richness and significant economic value. This study presents a comprehensive
[...] Read more.
Euspira gilva, a member of the family Naticidae, is predominantly found in intertidal soft mud, sandy soil, and sandy seabeds along the coast of China, where it is valued for its nutritional richness and significant economic value. This study presents a comprehensive transcriptome sequencing and analysis of E. gilva specimens from the Lianyungang area, yielding 3385 high-quality isoform sequences and 3310 non-redundant transcripts. Annotation against various databases, including NR, Swiss-Prot, KEGG, KOG, eggNOG, GO, and Pfam, successfully annotated a significant number of transcripts. A total of 7929 simple sequence repeat (SSR) loci were identified, with single nucleotide repeats predominating at 85.0%. Predictive analysis of coding DNA sequences (CDS) resulted in 1340 BLAST comparisons, while ESTScan predicted 840. Further, 530 long non-coding RNAs (lncRNAs) were identified through the application of the CPC2, CNCI, Pfam, and PLEK algorithms. The highest overall sequence similarity in the NR database was observed with Pomacea canaliculata, a freshwater species, but with a similarity of only 36.6%, indicating a unique genetic makeup of E. gilva. The KEGG database annotation revealed a predominance of signal transduction pathways, particularly the PI3K-Akt signaling pathway, with 29 non-redundant transcripts encoding key genes such as IGH (immunoglobulin heavy chain), PCK (phosphoenolpyruvate carboxykinase), COL2A (collagen, type II, alpha), ITGB1 (integrin beta 1), and GNG7 (guanine nucleotide-binding protein G(I)/G(S)/G(O) subunit gamma-7). These genes play crucial roles in cellular processes, including cell growth, transcription, translation, proliferation, movement, and glycogen metabolism. The findings of this research elucidate the full-length transcriptome profile of E. gilva, thereby establishing a foundational dataset and providing valuable insights for the species’ aquaculture, health management, conservation efforts, and future molecular biological investigations.
Full article
Figure 1
Figure 1
<p>Distribution of sequence lengths of non-redundant transcripts in the transcriptome of <span class="html-italic">E. gilva</span>. The abscissa represents the sequence length distribution interval, and the ordinate represents the sequence counts.</p> Full article ">Figure 2
<p>Top 10 homologous species distribution within the NR database. Pie slices in different colors represent the proportion of each species noted.</p> Full article ">Figure 3
<p>KEGG annotation statistics chart at Level 2. The horizontal axis represents the number of genes, the vertical axis represents the name of the Level 2 pathway, and the number on the right side of the column represents the number of genes annotated to the Level 2 pathway.</p> Full article ">Figure 4
<p>GO function classification statistics map. The horizontal axis represents the GO function classification, the left vertical axis represents the proportion of genes annotated to this category, and the right vertical axis represents the number of genes annotated to this category.</p> Full article ">Figure 5
<p>TF family Unigene distribution map. The abscissa represents the transcription factor family, and the ordinate represents the number of transcription factors contained in the transcription factor family.</p> Full article ">Figure 6
<p>CDS sequence length distribution map. The abscissa represents the CDS length distribution interval, and the ordinate represents the number of CDS sequences.</p> Full article ">Figure 7
<p>Venn diagram of lncRNA transcripts identified from CNCI, Pfam, PLEK, and CPC.</p> Full article ">Figure 8
<p>SSR type statistical results. The abscissa is the type of repeat, and the ordinate is the number of repeats of each type. (For example, 1 bp is a single-base repeat, 2 bp is a two-base repeat, the number of repetitions range from 5 to >11, and the ordinate is the sum of their corresponding frequencies).</p> Full article ">
<p>Distribution of sequence lengths of non-redundant transcripts in the transcriptome of <span class="html-italic">E. gilva</span>. The abscissa represents the sequence length distribution interval, and the ordinate represents the sequence counts.</p> Full article ">Figure 2
<p>Top 10 homologous species distribution within the NR database. Pie slices in different colors represent the proportion of each species noted.</p> Full article ">Figure 3
<p>KEGG annotation statistics chart at Level 2. The horizontal axis represents the number of genes, the vertical axis represents the name of the Level 2 pathway, and the number on the right side of the column represents the number of genes annotated to the Level 2 pathway.</p> Full article ">Figure 4
<p>GO function classification statistics map. The horizontal axis represents the GO function classification, the left vertical axis represents the proportion of genes annotated to this category, and the right vertical axis represents the number of genes annotated to this category.</p> Full article ">Figure 5
<p>TF family Unigene distribution map. The abscissa represents the transcription factor family, and the ordinate represents the number of transcription factors contained in the transcription factor family.</p> Full article ">Figure 6
<p>CDS sequence length distribution map. The abscissa represents the CDS length distribution interval, and the ordinate represents the number of CDS sequences.</p> Full article ">Figure 7
<p>Venn diagram of lncRNA transcripts identified from CNCI, Pfam, PLEK, and CPC.</p> Full article ">Figure 8
<p>SSR type statistical results. The abscissa is the type of repeat, and the ordinate is the number of repeats of each type. (For example, 1 bp is a single-base repeat, 2 bp is a two-base repeat, the number of repetitions range from 5 to >11, and the ordinate is the sum of their corresponding frequencies).</p> Full article ">
Open AccessArticle
Potential Exposure of Aquatic Organisms to Dynamic Visual Cues Originating from Aerial Wind Turbine Blades
by
Benjamin J. Williamson, Lonneke Goddijn-Murphy, Jason McIlvenny and Alan Youngson
Fishes 2024, 9(12), 482; https://doi.org/10.3390/fishes9120482 - 26 Nov 2024
Abstract
For many aquatic species, vision is important for detecting prey, predators, and conspecifics; however, the potential impacts of visual cues from offshore wind turbines have not been investigated in these crucial contexts. There is the possibility of visual cues, originating from moving wind
[...] Read more.
For many aquatic species, vision is important for detecting prey, predators, and conspecifics; however, the potential impacts of visual cues from offshore wind turbines have not been investigated in these crucial contexts. There is the possibility of visual cues, originating from moving wind turbine blades, propagating through the air–water interface to impact visually sensitive species. Two classes of visual cues are possible: direct motion cues originating as light reflected from moving turbine blades and indirect cues resulting from an interruption of direct sunlight causing dynamic shadowing when the sun, blade, and receptor are aligned. In both cases, the propagation of cues across the air–water interface is governed by physical principles but modulated in potentially complex ways by the aspects of the local environment that vary with time. Evidence for the extent of the exposure of aquatic organisms to the visual cues arising from moving turbine blades and for the potential response of receptor organisms is sparse. This study considers the physics involved to support the formulation and testing of robust biological hypotheses. Marine migratory salmonid species are considered as an example species because their behaviour in the marine environment is relatively well documented. This study concludes that the aquatic receptor organisms present in the uppermost layer of the sea in the vicinity of wind turbines are potentially exposed to direct motion cues originating from moving turbine blades and also, when the sun elevation angle is greater than ca. 20°, to dynamic shadowing cues.
Full article
(This article belongs to the Section Environment and Climate Change)
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Figure 1
Figure 1
<p>Diagram showing the composition of natural daylight and Fresnel reflection and the refraction of direct light (the solar beam) at a smooth water surface with solar elevation angle ‘<span class="html-italic">h</span>’, angle of incidence ‘<span class="html-italic">i</span>’, and angle of refraction ‘<span class="html-italic">j</span>’ defined as being in the same plane.</p> Full article ">Figure 2
<p>Diagram showing Fresnel reflectance. For <span class="html-italic">i</span> = 0° to 70°, Fresnel reflectance increases from 0.02 to 0.13 (and ultimately to 1 for grazing incidence, <span class="html-italic">i</span> = 90°, when all light is reflected).</p> Full article ">Figure 3
<p>(<b>Left</b>)—diagram showing Fresnel refraction of light from the upper hemisphere into water; the dashed line indicates the critical angle (48.5°). (<b>Right</b>)—optics of Snell’s window for flat water. Image taken from Lynch [<a href="#B9-fishes-09-00482" class="html-bibr">9</a>].</p> Full article ">Figure 4
<p>Diagram showing how light reflected from a point in the air (red line, here the tip of a wind turbine blade, with the wind turbine shown oblique to the page) transmitted across a smooth water surface appears closer to an aquatic receptor organism (green dashed line) due to refraction of light.</p> Full article ">Figure 5
<p>Visuals of a wind turbine from beneath the water’s surface with increasing roughening of the water surface from a to d, created using Blender [<a href="#B14-fishes-09-00482" class="html-bibr">14</a>]. The figures show (<b>a</b>) no ripples, calm conditions, (<b>b</b>) 5 cm high ripples, (<b>c</b>) 10 cm high ripples, and (<b>d</b>) 25 cm high ripples. Viewpoint placed at 2 m water depth. The 60-m high wind turbine is approximately 250 m from the viewpoint position.</p> Full article ">Figure 6
<p>Shadow rays (in yellow) from a wind turbine blade traveling across a smooth water surface, with the wind turbine shown oblique to the page.</p> Full article ">Figure 7
<p>Transmission coefficient of light leaving a point at distance x and height z through an air–water interface for an underwater receptor organism at different depths (calculated using the Fresnel equations).</p> Full article ">Figure 8
<p>Attenuated light calculated as exp(-cL) with the light attenuation coefficient c (m<sup>−1</sup>) and path length in water L (m).</p> Full article ">
<p>Diagram showing the composition of natural daylight and Fresnel reflection and the refraction of direct light (the solar beam) at a smooth water surface with solar elevation angle ‘<span class="html-italic">h</span>’, angle of incidence ‘<span class="html-italic">i</span>’, and angle of refraction ‘<span class="html-italic">j</span>’ defined as being in the same plane.</p> Full article ">Figure 2
<p>Diagram showing Fresnel reflectance. For <span class="html-italic">i</span> = 0° to 70°, Fresnel reflectance increases from 0.02 to 0.13 (and ultimately to 1 for grazing incidence, <span class="html-italic">i</span> = 90°, when all light is reflected).</p> Full article ">Figure 3
<p>(<b>Left</b>)—diagram showing Fresnel refraction of light from the upper hemisphere into water; the dashed line indicates the critical angle (48.5°). (<b>Right</b>)—optics of Snell’s window for flat water. Image taken from Lynch [<a href="#B9-fishes-09-00482" class="html-bibr">9</a>].</p> Full article ">Figure 4
<p>Diagram showing how light reflected from a point in the air (red line, here the tip of a wind turbine blade, with the wind turbine shown oblique to the page) transmitted across a smooth water surface appears closer to an aquatic receptor organism (green dashed line) due to refraction of light.</p> Full article ">Figure 5
<p>Visuals of a wind turbine from beneath the water’s surface with increasing roughening of the water surface from a to d, created using Blender [<a href="#B14-fishes-09-00482" class="html-bibr">14</a>]. The figures show (<b>a</b>) no ripples, calm conditions, (<b>b</b>) 5 cm high ripples, (<b>c</b>) 10 cm high ripples, and (<b>d</b>) 25 cm high ripples. Viewpoint placed at 2 m water depth. The 60-m high wind turbine is approximately 250 m from the viewpoint position.</p> Full article ">Figure 6
<p>Shadow rays (in yellow) from a wind turbine blade traveling across a smooth water surface, with the wind turbine shown oblique to the page.</p> Full article ">Figure 7
<p>Transmission coefficient of light leaving a point at distance x and height z through an air–water interface for an underwater receptor organism at different depths (calculated using the Fresnel equations).</p> Full article ">Figure 8
<p>Attenuated light calculated as exp(-cL) with the light attenuation coefficient c (m<sup>−1</sup>) and path length in water L (m).</p> Full article ">
Open AccessArticle
Population Genetics and Gene Flow in Cyphotilapia frontosa and Cyphotilapia gibberosa Along the East Coast of Lake Tanganyika
by
George D. Jackson, Timothy Standish, Ortaç Çetintaş, Oleksandr Zinenko, Asilatu H. Shechonge and Alexey Yanchukov
Fishes 2024, 9(12), 481; https://doi.org/10.3390/fishes9120481 - 26 Nov 2024
Abstract
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The radiation of cichlid species in the East African Great Lakes is remarkable and rapid. The population genetics of two deep-water Cyphotilapia species along the east coast of Lake Tanganyika from Burundi to southern Tanzania was determined using ddRAD-seq. A combination of ADMIXTURE,
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The radiation of cichlid species in the East African Great Lakes is remarkable and rapid. The population genetics of two deep-water Cyphotilapia species along the east coast of Lake Tanganyika from Burundi to southern Tanzania was determined using ddRAD-seq. A combination of ADMIXTURE, PCA, genome polarization, and 2D site frequency spectrum analyses confirmed the presence of two species, C. frontosa in the north and C. gibberosa in the south, as documented in other studies. We also found evidence of a potential hybrid zone connecting the two species at a sharp genetic cline centered in the middle of the lake and apparent introgression in both directions, but predominantly from ‘gibberosa’ into ‘frontosa’. The highest proportion of introgressed ‘gibberosa’ ancestry was present in the southernmost populations of C. frontosa collected near Karilani Island and Cape Kabogo. At the intra-specific level, there was support for between 1 and 3 populations of C. frontosa, whereas the results indicated only a single homogeneous population of C. gibberosa. The presence of different morphs in the lake despite the low levels of heterozygosity suggests that a small number of loci may be involved in the morphological variation and/or that there is a more complex interplay between genetics and the environment in different locations.
Full article
Graphical abstract
Graphical abstract
Full article ">Figure 1
<p><span class="html-italic">Cyphotilapia</span> from this study: (<b>A</b>) juvenile near Lupita island around 15–20 m in depth. (<b>B</b>,<b>C</b>) Catch in fisherman’s boats between Kipili on the mainland and Lupita Island. (<b>D</b>) Mwamgongo morphs showing variety in bar patterns. (<b>E</b>) Burundi morph. (<b>F</b>) Juvenile near Lupita Island around 15–20 m in depth. (<b>G</b>) Kigoma 7-bar morph. (<b>H</b>) Collection locations of fish for this study.</p> Full article ">Figure 2
<p>PCA and hierarchical genetic clustering analysis. (<b>A</b>) Principal component analysis: the vertical arrow indicates geographic positions of the localities, north to south. (<b>B</b>) ADMIXTURE plots for the range of values of K (2–6). The individuals on each plot are aligned according to their inferred ancestry proportions of two clusters at K = 2. The inset on the plot with K = 2 shows the respective cross-validation errors (CV) over K (lower values of CV translate into better statistical support).</p> Full article ">Figure 3
<p>Co-ancestry matrix of <span class="html-italic">Cyphotilapia</span> populations in Lake Tanganyika, produced in RADpainter [<a href="#B24-fishes-09-00481" class="html-bibr">24</a>]. The values in the heatmap cells indicate the contributions of inferred genetic ancestry from the individuals listed in columns (“donors”) to the individuals listed in rows (“recipients”). Note the presence of two main clusters (‘<span class="html-italic">gibberosa</span>’ in the bottom left and ‘<span class="html-italic">frontosa</span>’ in the top right), as well as the higher genetic affinity of Cape Kabogo and Karalani Island individuals to the ‘<span class="html-italic">gibberosa</span>’ cluster, likely caused by gene flow.</p> Full article ">Figure 4
<p>Genetic barrier between <span class="html-italic">C. frontosa</span> and <span class="html-italic">C. gibberosa</span> visualized using SNP polarization in diemr. (<b>A</b>,<b>B</b>) Hybrid index (h) showing a sharp transition between two species, as well as possible traces of admixture on both sides of the barrier: (<b>A</b>) individuals ordered by h; (<b>B</b>) average h per sampling location across the geographic distance (centered at the mid-point between the most distant locations Burundi and Kabwimba) along Lake Tanganyika shore.</p> Full article ">Figure 5
<p>Introgression between <span class="html-italic">C. frontosa</span> and <span class="html-italic">C. gibberosa</span> visualized using SNP polarization in diemr. (<b>A</b>) The top 30% diagnostic individual SNP genotypes (<span class="html-italic">n</span> = 3624) ordered in rows by their genomic location and colored as follows: teal—homozygotes for <span class="html-italic">frontosa</span> alleles; light blue—homozygotes for <span class="html-italic">gibberosa</span> alleles; red—heterozygotes; and yellow—missing genotypes. (<b>B</b>) Frequency distribution of the diemr per-SNP diagnostic index (d) for the dataset on (<b>A</b>). (<b>C</b>) The distribution of the lower 5% confidence interval boundary of the cline parameter v (cline gradient) among the 330 SNPs included in the bgchm analysis.</p> Full article ">Figure 6
<p>Asymmetric introgression between two <span class="html-italic">Cyphotilapia</span> species. (<b>A</b>) A 2D site frequency spectrum constructed in <span class="html-italic">snpR</span>. The <span class="html-italic">x</span> and <span class="html-italic">y</span> axes show the projected number of gene copies in <span class="html-italic">frontosa</span> and <span class="html-italic">gibberosa</span> individuals: a small fraction of SNPs with high prevalence in <span class="html-italic">gibberosa</span> but <span class="html-italic">also</span> present at low frequencies in <span class="html-italic">frontosa</span>, indicated by an arrow. (<b>B</b>) Triangular plot of the mixed interspecific individual ancestry vs. hybrid index (=proportion of <span class="html-italic">frontosa</span> alleles), inferred for 330 SNPs in <span class="html-italic">bgchm</span>. Arrow indicates a small number of <span class="html-italic">frontosa</span> individuals with slightly higher values of interspecific ancestry, possibly caused by distant introgression.</p> Full article ">
Full article ">Figure 1
<p><span class="html-italic">Cyphotilapia</span> from this study: (<b>A</b>) juvenile near Lupita island around 15–20 m in depth. (<b>B</b>,<b>C</b>) Catch in fisherman’s boats between Kipili on the mainland and Lupita Island. (<b>D</b>) Mwamgongo morphs showing variety in bar patterns. (<b>E</b>) Burundi morph. (<b>F</b>) Juvenile near Lupita Island around 15–20 m in depth. (<b>G</b>) Kigoma 7-bar morph. (<b>H</b>) Collection locations of fish for this study.</p> Full article ">Figure 2
<p>PCA and hierarchical genetic clustering analysis. (<b>A</b>) Principal component analysis: the vertical arrow indicates geographic positions of the localities, north to south. (<b>B</b>) ADMIXTURE plots for the range of values of K (2–6). The individuals on each plot are aligned according to their inferred ancestry proportions of two clusters at K = 2. The inset on the plot with K = 2 shows the respective cross-validation errors (CV) over K (lower values of CV translate into better statistical support).</p> Full article ">Figure 3
<p>Co-ancestry matrix of <span class="html-italic">Cyphotilapia</span> populations in Lake Tanganyika, produced in RADpainter [<a href="#B24-fishes-09-00481" class="html-bibr">24</a>]. The values in the heatmap cells indicate the contributions of inferred genetic ancestry from the individuals listed in columns (“donors”) to the individuals listed in rows (“recipients”). Note the presence of two main clusters (‘<span class="html-italic">gibberosa</span>’ in the bottom left and ‘<span class="html-italic">frontosa</span>’ in the top right), as well as the higher genetic affinity of Cape Kabogo and Karalani Island individuals to the ‘<span class="html-italic">gibberosa</span>’ cluster, likely caused by gene flow.</p> Full article ">Figure 4
<p>Genetic barrier between <span class="html-italic">C. frontosa</span> and <span class="html-italic">C. gibberosa</span> visualized using SNP polarization in diemr. (<b>A</b>,<b>B</b>) Hybrid index (h) showing a sharp transition between two species, as well as possible traces of admixture on both sides of the barrier: (<b>A</b>) individuals ordered by h; (<b>B</b>) average h per sampling location across the geographic distance (centered at the mid-point between the most distant locations Burundi and Kabwimba) along Lake Tanganyika shore.</p> Full article ">Figure 5
<p>Introgression between <span class="html-italic">C. frontosa</span> and <span class="html-italic">C. gibberosa</span> visualized using SNP polarization in diemr. (<b>A</b>) The top 30% diagnostic individual SNP genotypes (<span class="html-italic">n</span> = 3624) ordered in rows by their genomic location and colored as follows: teal—homozygotes for <span class="html-italic">frontosa</span> alleles; light blue—homozygotes for <span class="html-italic">gibberosa</span> alleles; red—heterozygotes; and yellow—missing genotypes. (<b>B</b>) Frequency distribution of the diemr per-SNP diagnostic index (d) for the dataset on (<b>A</b>). (<b>C</b>) The distribution of the lower 5% confidence interval boundary of the cline parameter v (cline gradient) among the 330 SNPs included in the bgchm analysis.</p> Full article ">Figure 6
<p>Asymmetric introgression between two <span class="html-italic">Cyphotilapia</span> species. (<b>A</b>) A 2D site frequency spectrum constructed in <span class="html-italic">snpR</span>. The <span class="html-italic">x</span> and <span class="html-italic">y</span> axes show the projected number of gene copies in <span class="html-italic">frontosa</span> and <span class="html-italic">gibberosa</span> individuals: a small fraction of SNPs with high prevalence in <span class="html-italic">gibberosa</span> but <span class="html-italic">also</span> present at low frequencies in <span class="html-italic">frontosa</span>, indicated by an arrow. (<b>B</b>) Triangular plot of the mixed interspecific individual ancestry vs. hybrid index (=proportion of <span class="html-italic">frontosa</span> alleles), inferred for 330 SNPs in <span class="html-italic">bgchm</span>. Arrow indicates a small number of <span class="html-italic">frontosa</span> individuals with slightly higher values of interspecific ancestry, possibly caused by distant introgression.</p> Full article ">
Open AccessArticle
Shelf Life Study of Chilled Mullet (Mugil cephalus): Histamine Formation and Quality Degradation at Constant and Dynamic Storage Conditions
by
Athina Ntzimani, Eirini Papamichail, Efimia Dermesonlouoglou, Theofania Tsironi and Petros Taoukis
Fishes 2024, 9(12), 480; https://doi.org/10.3390/fishes9120480 - 26 Nov 2024
Abstract
The present work aimed to evaluate and mathematically model the effect of temperature on Morganella morganii growth and histamine formation in farmed mullet (Mugil cephalus) during refrigerated storage (at constant temperatures, T = 0, 2.5, 5, 10, and 15 °C) and
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The present work aimed to evaluate and mathematically model the effect of temperature on Morganella morganii growth and histamine formation in farmed mullet (Mugil cephalus) during refrigerated storage (at constant temperatures, T = 0, 2.5, 5, 10, and 15 °C) and to validate the developed models at non-constant temperature conditions (effective temperature Teff = 7.4 °C). Shelf life evaluation of chilled mullet was also carried out based on microbial spoilage, sensory degradation, and total volatile nitrogen (TVB-N) determination. Spoilage of mullet during refrigerated storage was co-dominated by Pseudomonas spp. and Enterobacteriaceae growth. Sensory rejection (score 5 for overall impression) and the end of shelf life coincided with a total microbial load of 8 log cfu/g. The shelf life of chilled mullet was estimated at 15, 11, 7, 3, and 1.5 days at 0, 2.5, 5, 10, and 15 °C, respectively. At T 0–5 °C, the time of sensory rejection coincided with TVB-N concentrations of 10.2–12.3 mg·100 g−1, and at 10–15 °C, the samples were sensorially rejected before TVB-N development. At storage temperatures < 5 °C, sensory rejection was observed well before histamine levels reached a concentration of 50 mg/kg fish flesh. However, when abusive temperatures prevail, histamine should be considered as a risk factor for the human consumption of mullet.
Full article
(This article belongs to the Special Issue Trends and Advances in Seafood Quality: Processing, Preservation and Safety Processes to Guarantee Food Value)
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Figure 1
Figure 1
<p><span class="html-italic">M. morganii</span> growth in aerobically packed mullet flesh during isothermal storage at ▲ 0 °C, ○ 5 °C, ■ 10 °C, △ 15 °C, and □ 20 °C (experimental points and predictions are based on the Baranyi Growth Model).</p> Full article ">Figure 2
<p><span class="html-italic">M. morganii</span> growth in aerobically packed mullet stored at dynamic conditions (<span class="html-italic">T<sub>eff</sub></span> = 7.4 °C) (<span class="html-italic">A<sub>f</sub></span> = 1.0462, <span class="html-italic">B<sub>f</sub></span> = 1.0042, <span class="html-italic">RE</span> = −9.00 to 10.81).</p> Full article ">Figure 3
<p>Histamine formation in aerobically packed mullet flesh during isothermal storage at ▲ 0 °C, ○ 5 °C, ■ 10 °C, △ 15 °C, and □ 20 °C (experimental points and predictions are based on the Baranyi Growth Model).</p> Full article ">Figure 4
<p>Histamine formation in aerobically packed mullet stored at dynamic conditions (<span class="html-italic">T<sub>eff</sub></span> = 7.4 °C) (<span class="html-italic">A<sub>f</sub></span> = 1.1419, <span class="html-italic">B<sub>f</sub></span> = 0.8866, <span class="html-italic">RE</span> = −1.22 to 18.79).</p> Full article ">Figure 5
<p>Development of (<b>a</b>) total viable count, (<b>b</b>) <span class="html-italic">Pseudomonas</span> spp., and (<b>c</b>) Enterobacteriaceae spp. in aerobically packed mullet slices during isothermal storage at ● 0 °C, △ 2.5 °C, ○ 5 °C, □ 10 °C, and ▲ 15 °C (experimental points and predictions based on the Baranyi Growth Model).</p> Full article ">Figure 6
<p>Sensory scoring: (<b>a</b>) appearance, (<b>b</b>) odor, and (<b>c</b>) overall impression of aerobically packed mullet slices during isothermal storage at ● 0 °C, △ 2.5 °C, ○ 5 °C, □ 10 °C, and ▲ 15 °C.</p> Full article ">Figure 7
<p>Development pattern of the volatile base (TVB-N) during storage of aerobically packed mullet slices during isothermal storage at ▲ 0 °C, □ 2.5 °C, ○ 5 °C, △ 10 °C, and ● 15 °C.</p> Full article ">Figure 8
<p>Time required to reach a histamine concentration of 50 mg/kg in mullet flesh and the shelf life of aerobically packed mullet slices during isothermal storage at 0–20 °C.</p> Full article ">Figure 9
<p>(<b>a</b>) Total viable count (TVC) growth (log cfu/g) and (<b>b</b>) histamine concentration (ppm) in aerobically stored mullet under a theoretical time–temperature scenario for transportation and storage with temperature fluctuations.</p> Full article ">
<p><span class="html-italic">M. morganii</span> growth in aerobically packed mullet flesh during isothermal storage at ▲ 0 °C, ○ 5 °C, ■ 10 °C, △ 15 °C, and □ 20 °C (experimental points and predictions are based on the Baranyi Growth Model).</p> Full article ">Figure 2
<p><span class="html-italic">M. morganii</span> growth in aerobically packed mullet stored at dynamic conditions (<span class="html-italic">T<sub>eff</sub></span> = 7.4 °C) (<span class="html-italic">A<sub>f</sub></span> = 1.0462, <span class="html-italic">B<sub>f</sub></span> = 1.0042, <span class="html-italic">RE</span> = −9.00 to 10.81).</p> Full article ">Figure 3
<p>Histamine formation in aerobically packed mullet flesh during isothermal storage at ▲ 0 °C, ○ 5 °C, ■ 10 °C, △ 15 °C, and □ 20 °C (experimental points and predictions are based on the Baranyi Growth Model).</p> Full article ">Figure 4
<p>Histamine formation in aerobically packed mullet stored at dynamic conditions (<span class="html-italic">T<sub>eff</sub></span> = 7.4 °C) (<span class="html-italic">A<sub>f</sub></span> = 1.1419, <span class="html-italic">B<sub>f</sub></span> = 0.8866, <span class="html-italic">RE</span> = −1.22 to 18.79).</p> Full article ">Figure 5
<p>Development of (<b>a</b>) total viable count, (<b>b</b>) <span class="html-italic">Pseudomonas</span> spp., and (<b>c</b>) Enterobacteriaceae spp. in aerobically packed mullet slices during isothermal storage at ● 0 °C, △ 2.5 °C, ○ 5 °C, □ 10 °C, and ▲ 15 °C (experimental points and predictions based on the Baranyi Growth Model).</p> Full article ">Figure 6
<p>Sensory scoring: (<b>a</b>) appearance, (<b>b</b>) odor, and (<b>c</b>) overall impression of aerobically packed mullet slices during isothermal storage at ● 0 °C, △ 2.5 °C, ○ 5 °C, □ 10 °C, and ▲ 15 °C.</p> Full article ">Figure 7
<p>Development pattern of the volatile base (TVB-N) during storage of aerobically packed mullet slices during isothermal storage at ▲ 0 °C, □ 2.5 °C, ○ 5 °C, △ 10 °C, and ● 15 °C.</p> Full article ">Figure 8
<p>Time required to reach a histamine concentration of 50 mg/kg in mullet flesh and the shelf life of aerobically packed mullet slices during isothermal storage at 0–20 °C.</p> Full article ">Figure 9
<p>(<b>a</b>) Total viable count (TVC) growth (log cfu/g) and (<b>b</b>) histamine concentration (ppm) in aerobically stored mullet under a theoretical time–temperature scenario for transportation and storage with temperature fluctuations.</p> Full article ">
Open AccessArticle
Evaluating Silvering Stages in European Eels: A Study on Biological and Morphometric Variations in the Asi River, Türkiye
by
Aydın Demirci
Fishes 2024, 9(12), 479; https://doi.org/10.3390/fishes9120479 - 26 Nov 2024
Abstract
The European eel (Anguilla anguilla) undergoes significant morphological and physiological changes during its transition from the yellow to the silver stage, which are critical for its long-distance spawning migration. This study aimed to investigate these changes in European eels from the
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The European eel (Anguilla anguilla) undergoes significant morphological and physiological changes during its transition from the yellow to the silver stage, which are critical for its long-distance spawning migration. This study aimed to investigate these changes in European eels from the Asi River, located in Hatay, Türkiye, during their silvering process. A total of 96 eels were sampled in February 2019, and various morphometric measurements, including total length, body weight, eye dimensions and height, and pectoral fin lengths, were taken. Liver and gonad weights were also measured to assess the hepatosomatic index (HSI). The length–weight relationship for silver eels was described by the equation, W = 0.0072 × L2.732, with silver-stage eels showing a higher growth rate compared to yellow-stage eels, which had a relationship of W = 0.0184 × L2.397. The average total length of silver eels (431.2 ± 16.7 mm) was significantly greater than that of yellow eels (382.4 ± 11.9 mm). Additionally, pectoral fin length was significantly longer in silver eels (20.8 ± 1.1 mm) compared to yellow eels (14.8 ± 0.9 mm). The hepatosomatic index (HSI) for silver eels was also found to be higher than for yellow eels, indicating increased liver size as an adaptation for energy storage during migration. Eye height, a key indicator of silvering, showed a substantial increase during the transition, with silver-stage eels having an average eye height of 5.3 ± 0.2 mm compared to 4.2 ± 0.1 mm in yellow-stage eels.
Full article
(This article belongs to the Section Biology and Ecology)
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<p>General view of the Asi River and the sampling locality of European eels collected from the Turkish part of the Asi River in February 2019 (modified from Şimşek and Kale [<a href="#B32-fishes-09-00479" class="html-bibr">32</a>]).</p> Full article ">Figure 2
<p>Distribution of yellow- and silver-stage eels by weight (g) and total length (mm) from the Asi River (February 2019).</p> Full article ">Figure 3
<p>Sex distribution of European eels in yellow and silver stages in the Asi River (February 2019).</p> Full article ">Figure 4
<p>Length–weight relationship of silver-stage eels in the Asi River (February 2019).</p> Full article ">Figure 5
<p>Length–weight relationship of yellow-stage eels in the Asi River (February 2019).</p> Full article ">Figure 6
<p>Comparison of pectoral fin length, eye diameter, and eye height between silver and yellow eels in the Asi River (February 2019).</p> Full article ">Figure 7
<p>Receiver operating characteristic (ROC) curve for the analysis of morphometric differences in silvering stage eels: a predictive model based on length, weight, pectoral fin length, eye width, and eye height (Area under the curve = 0.84).</p> Full article ">Figure 8
<p>Relationship between liver weight and body weight in silver- and yellow-stage eels from the Asi River (February 2019).</p> Full article ">
<p>General view of the Asi River and the sampling locality of European eels collected from the Turkish part of the Asi River in February 2019 (modified from Şimşek and Kale [<a href="#B32-fishes-09-00479" class="html-bibr">32</a>]).</p> Full article ">Figure 2
<p>Distribution of yellow- and silver-stage eels by weight (g) and total length (mm) from the Asi River (February 2019).</p> Full article ">Figure 3
<p>Sex distribution of European eels in yellow and silver stages in the Asi River (February 2019).</p> Full article ">Figure 4
<p>Length–weight relationship of silver-stage eels in the Asi River (February 2019).</p> Full article ">Figure 5
<p>Length–weight relationship of yellow-stage eels in the Asi River (February 2019).</p> Full article ">Figure 6
<p>Comparison of pectoral fin length, eye diameter, and eye height between silver and yellow eels in the Asi River (February 2019).</p> Full article ">Figure 7
<p>Receiver operating characteristic (ROC) curve for the analysis of morphometric differences in silvering stage eels: a predictive model based on length, weight, pectoral fin length, eye width, and eye height (Area under the curve = 0.84).</p> Full article ">Figure 8
<p>Relationship between liver weight and body weight in silver- and yellow-stage eels from the Asi River (February 2019).</p> Full article ">
Open AccessArticle
The Effects of Predominantly Chemoautotrophic Versus Heterotrophic Biofloc Systems on Nitrifying Bacteria, Planktonic Microorganisms, and Growth of Penaeus vannamei, and Oreochromis niloticus in an Integrated Multitrophic Culture
by
Raysa Pâmela Oliveira Sena, Dariano Krummenauer, Wilson Wasielesky, Jr., Otávio Augusto Lacerda Ferreira Pimentel, Aline Bezerra, Jorge Renato Tagliaferro dos Santos Junior, Andrezza Carvalho, Elisa Ravagnan, Andrea Bagi and Luis H. S. Poersch
Fishes 2024, 9(12), 478; https://doi.org/10.3390/fishes9120478 - 26 Nov 2024
Abstract
The aim of this study was to evaluate the effect of predominantly chemoautotrophic and heterotrophic biofloc systems on ammonia-oxidizing bacteria (AOB), nitrite-oxidizing bacteria (NOB), and planktonic microorganisms in an integrated Penaeus vannamei and Oreochromis niloticus integrated multitrophic culture. Shrimp and tilapia were stocked
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The aim of this study was to evaluate the effect of predominantly chemoautotrophic and heterotrophic biofloc systems on ammonia-oxidizing bacteria (AOB), nitrite-oxidizing bacteria (NOB), and planktonic microorganisms in an integrated Penaeus vannamei and Oreochromis niloticus integrated multitrophic culture. Shrimp and tilapia were stocked at a density of 400 shrimp m−2 and 45 fish m−3, respectively. The trial consisted of two biofloc treatments, with three replicates each: chemoautotrophic and heterotrophic. The identification and quantification of the planktonic microorganisms (ciliates, flagellates, microalgae, and total bacteria) and nitrifying bacteria were carried out through direct counting and fluorescence in situ hybridization, respectively. At the end of the trial, heterotrophic treatment had resulted in higher total abundance of bacteria. The relative abundance of AOB and NOB in relation to the total abundance was less than 0.1% for both treatments. The system was dominated by flagellates in both treatment groups. The abundance of microalgae and ciliates was higher with chemoautotrophic treatment. After 43 days, the shrimp weights were higher in the chemoautotrophic group, while the final weights of the tilapia were not significantly different between the two treatments. The type of biofloc system (Chemoautotrophic vs. Heterotrophic) did not significantly alter the establishment of AOB and NOB in a Penaeus vannamei and Oreochromis niloticus integrated multitrophic culture. The two treatments proved to be equally efficient for maintaining good water quality, but the chemoautotrophic treatment resulted in better shrimp growth. Thus, our study demonstrated that chemoautotrophic biofloc is a promising approach in integrated multitrophic aquaculture.
Full article
(This article belongs to the Special Issue Biofloc Technology in Aquaculture)
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<p>Scheme of the multitrophic culture system of <span class="html-italic">Penaeus vannamei</span> and <span class="html-italic">Oreochromis niloticus</span> with a predominantly chemoautotrophic or heterotrophic biofloc system.</p> Full article ">Figure 2
<p>Total abundance of bacteria (organisms mL<sup>−1</sup>, mean ± standard deviation) (<b>a</b>), ammonia-oxidizing bacteria (AOB, (<b>b</b>)), nitrite-oxidizing bacteria (NOB, (<b>c</b>)), microalgae (<b>d</b>), flagellates (<b>e</b>), and ciliates (<b>f</b>) in a <span class="html-italic">Penaeus vannamei</span> and <span class="html-italic">Oreochromis niloticus</span> multitrophic culture with a predominantly chemoautotrophic or heterotrophic biofloc system.</p> Full article ">Figure 3
<p>Spearman correlation matrix among water quality variables and microbial community components in a <span class="html-italic">Penaeus vannamei</span> and <span class="html-italic">Oreochromis niloticus</span> multitrophic culture with a predominantly chemoautotrophic or heterotrophic biofloc system. Numbers inside the boxes correspond to the correlation coefficient. * Significant correlations (<span class="html-italic">p</span>-value < 0.05). TAN: total ammonia nitrogen, DO: dissolved oxygen; TSS: total suspended solids; SS: settleable solids; TA: total abundance of bacteria.</p> Full article ">
<p>Scheme of the multitrophic culture system of <span class="html-italic">Penaeus vannamei</span> and <span class="html-italic">Oreochromis niloticus</span> with a predominantly chemoautotrophic or heterotrophic biofloc system.</p> Full article ">Figure 2
<p>Total abundance of bacteria (organisms mL<sup>−1</sup>, mean ± standard deviation) (<b>a</b>), ammonia-oxidizing bacteria (AOB, (<b>b</b>)), nitrite-oxidizing bacteria (NOB, (<b>c</b>)), microalgae (<b>d</b>), flagellates (<b>e</b>), and ciliates (<b>f</b>) in a <span class="html-italic">Penaeus vannamei</span> and <span class="html-italic">Oreochromis niloticus</span> multitrophic culture with a predominantly chemoautotrophic or heterotrophic biofloc system.</p> Full article ">Figure 3
<p>Spearman correlation matrix among water quality variables and microbial community components in a <span class="html-italic">Penaeus vannamei</span> and <span class="html-italic">Oreochromis niloticus</span> multitrophic culture with a predominantly chemoautotrophic or heterotrophic biofloc system. Numbers inside the boxes correspond to the correlation coefficient. * Significant correlations (<span class="html-italic">p</span>-value < 0.05). TAN: total ammonia nitrogen, DO: dissolved oxygen; TSS: total suspended solids; SS: settleable solids; TA: total abundance of bacteria.</p> Full article ">
Open AccessArticle
Ease and Limitations in Using Environmental DNA to Track the Spread of Invasive Host–Parasite Complexes: A Case Study of the Freshwater Fish Pseudorasbora parva and the Cryptic Fungal Parasite Sphaerothecum destruens
by
Théo Deremarque, Rodolphe Elie Gozlan, Ravo Ravaozafindrasoa, Giuliano Mucci, Lucie Delalex, Jean-Michel Foissy, Michaël Cagnant, Mathieu Clair, Justina Givens, Fabienne Justy, Alice Valentini, Delphine Nicolas, Pascal Contournet, Claire Tetrel, Marc Thibault and Marine Combe
Fishes 2024, 9(12), 477; https://doi.org/10.3390/fishes9120477 - 26 Nov 2024
Abstract
The spread of non-native species threatens biodiversity and exacerbates societal challenges like food security. To address this, effective conservation programs require detection methods that are easy to implement, accurate, and non-invasive. Over the past 15 years, environmental DNA (eDNA) techniques have gained popularity,
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The spread of non-native species threatens biodiversity and exacerbates societal challenges like food security. To address this, effective conservation programs require detection methods that are easy to implement, accurate, and non-invasive. Over the past 15 years, environmental DNA (eDNA) techniques have gained popularity, surpassing traditional sampling methods. In this context, our study focused on tracking the invasive host–pathogen complex Pseudorasbora parva and Sphaerothecum destruens using eDNA metabarcoding. We collected water samples from freshwater canals over five months in the Camargue region, and once in Corsica Island, both in southern France. Total DNA was extracted from filtered water samples, and PCR-amplicons were sequenced using Illumina or Nanopore technologies. Our results revealed a high detection rate of P. parva in lentic ecosystems, aligning with habitat preferences of this small freshwater fish. Additionally, the detection rate in Camargue increased in May and June, likely due to the peak of the spawning season, which leads to more DNA being released into the environment (i.e., concentration and interaction of individuals). While eDNA successfully detected this invasive fish, we were unable to detect its cryptic fungal parasite, S. destruens, highlighting the challenges of identifying intracellular and cryptic fungal pathogens through eDNA methods.
Full article
(This article belongs to the Special Issue Detection and Monitoring of Aquatic Pathogens by Using Environmental DNA (eDNA))
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<p>Map of the sampling sites sampled from January to June 2023 and located in 4 areas of the Camargue region. For each area, 3 aquatic sites were sampled.</p> Full article ">Figure 2
<p>Map of the sampling sites sampled in April 2023 located in the Golo River and Lake Calacuccia in Corsica Island.</p> Full article ">Figure 3
<p>Detection rate of <span class="html-italic">P. parva</span> in four areas in the Camargue for each month studied.</p> Full article ">Figure 4
<p>Box plot of the percentage of reads generated by Nanopore sequencing and mapping the mtDNA 16S gene of <span class="html-italic">P. parva</span> in the Camargue region. * <span class="html-italic">p</span>-value < 0.05.</p> Full article ">Figure 5
<p>Clades detected in Camargue (data pooled for February, March, and June) by Illumina sequencing of amplicons obtained by PCR with the ChF2-ChR2 primers. For each clade the number of reads mapping its genome is indicated. (<b>A</b>) Pebre canal; (<b>B</b>) Fumemorte canal; (<b>C</b>) Grandes Cabanes Domain; (<b>D</b>) Belugue canal.</p> Full article ">
<p>Map of the sampling sites sampled from January to June 2023 and located in 4 areas of the Camargue region. For each area, 3 aquatic sites were sampled.</p> Full article ">Figure 2
<p>Map of the sampling sites sampled in April 2023 located in the Golo River and Lake Calacuccia in Corsica Island.</p> Full article ">Figure 3
<p>Detection rate of <span class="html-italic">P. parva</span> in four areas in the Camargue for each month studied.</p> Full article ">Figure 4
<p>Box plot of the percentage of reads generated by Nanopore sequencing and mapping the mtDNA 16S gene of <span class="html-italic">P. parva</span> in the Camargue region. * <span class="html-italic">p</span>-value < 0.05.</p> Full article ">Figure 5
<p>Clades detected in Camargue (data pooled for February, March, and June) by Illumina sequencing of amplicons obtained by PCR with the ChF2-ChR2 primers. For each clade the number of reads mapping its genome is indicated. (<b>A</b>) Pebre canal; (<b>B</b>) Fumemorte canal; (<b>C</b>) Grandes Cabanes Domain; (<b>D</b>) Belugue canal.</p> Full article ">
Open AccessArticle
Potential Probiotic Bacillus Strains with Antioxidant and Antimutagenic Activity Increased Weight Gain and Altered hsp70, cxc, tnfα, il1β, and lysC Gene Expression in Clarias gariepinus
by
Radomir Viktorovich Skripnichenko, Daria Sergeevna Chelombitskaya, Evgeniya Valer’evna Prazdnova, Maxim Pavlovich Kulikov, Alexey Mikhailovich Neurov, Anna Andreevna Zaikina, Vadim Alekseevich Grigoryev, Marina Nikolaevna Sorokina, Vladimir Anatolievich Chistyakov, Michael Leonidas Chikindas and Dmitriy Vladimirovich Rudoy
Fishes 2024, 9(12), 476; https://doi.org/10.3390/fishes9120476 - 25 Nov 2024
Abstract
The potential probiotic properties of three Bacillus strains were studied. A probiotic supplement for the African catfish Clarias gariepinus was produced via the solid-state fermentation protocol and incorporated into the fish feed for a period of seven weeks. Since the 36th day of
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The potential probiotic properties of three Bacillus strains were studied. A probiotic supplement for the African catfish Clarias gariepinus was produced via the solid-state fermentation protocol and incorporated into the fish feed for a period of seven weeks. Since the 36th day of the experiment, all experimental groups had a statistically significant increase in their weight gain than the control group. The maximum weight gain observed in fish fed the probiotic-supplemented feed was 29.16% higher than that of the control group, and the maximum feed conversion rate improvement was 24%. Cell-free extracts from these strains showed antioxidant (11.55–27.40%) and DNA-protective (45.33–61.83%) activity in a series of in vitro biosensor tests. Further investigation into the antimutagenic activity of the strains revealed that two of them reduced the level of induced mutagenesis in an Escherichia coli model (by 33.58% and 54.35%, respectively). We also assessed the impact of probiotic strains on the expression of several key genes in the host (C. gariepinus), including hsp70, cxc, tnfα, il1β, and lysC. More than a 10-fold increase in expression rates was observed for hsp70 in gonads and liver; for cxc in muscles and gonads; for tnfα in brain, gills, and liver; for il1β in the brain, gills, gonads, and liver; and for lysC in gills, gonads, liver, and muscles. This study provides evidence that probiotics exhibiting antioxidant and antimutagenic properties can provide significant benefits in vivo within aquaculture systems. The molecular effects of these probiotics appear to be complex and tissue-specific, with both upregulation and downregulation of immune system genes observed. Nevertheless, at the organismal level, the impact was unequivocally positive in terms of aquaculture objectives, manifested as enhanced body weight gain in the fish. Consequently, these Bacillus strains warrant serious consideration as potential probiotics for this species.
Full article
(This article belongs to the Special Issue The Effects of Feed on the Growth Immunity and Metabolism of Fishes)
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<p>Antioxidant and DNA-protective activity of potential probiotic strains. All effects were statistically significant (<span class="html-italic">p</span> < 0.05). Tocopherol was used as a standard antioxidant.</p> Full article ">Figure 2
<p>Frequencies of spontaneous and dioxidine-induced mutagenesis in <span class="html-italic">E. coli</span> MG1655 under the action of preparations of the studied strains. * These experimental data have a statistically significant difference from the control (<span class="html-italic">p</span> < 0.05).</p> Full article ">Figure 3
<p>Relative mRNA expression of the <span class="html-italic">hsp70</span> gene in different tissues of <span class="html-italic">C. gariepinus</span> (<span class="html-italic">p</span>-values for the brain, gill, gonad, liver, and muscle tissues were 0.007937, 0.07276, 0.09663, 0.01015, and 0.01889 (for <span class="html-italic">B. subtilis</span> R1); 0.5476, 0.06088, 0.125, 0.07507, and 0.02579 (for <span class="html-italic">B. subtilis</span> R4); and 0.15, 0.08589, 0.1718, 0.02247, and 1.1157 (for <span class="html-italic">B. velezensis</span> R5), respectively). Thick lines inside the boxes indicate the medians; circles outside the boxes indicate the outliers.</p> Full article ">Figure 4
<p>Relative mRNA expression of the <span class="html-italic">cxc</span> gene in different tissues of <span class="html-italic">C. gariepinus</span> (<span class="html-italic">p</span>-values for the brain, gill, gonad, liver, and muscle tissues were 0.9802, 0.08762, 0.1558, 0.003346 (for <span class="html-italic">B. subtilis</span> R1); 0.6268, 0.09122, 0.207, 0.09524, and 0.1676 (for <span class="html-italic">B. subtilis</span> R4); and 0.2877, 0.2723, 0.004556, 0.01587, and 0.466 (for <span class="html-italic">B. velezensis</span> R5), respectively). Thick lines inside the boxes indicate the medians; circles outside the boxes indicate the outliers.</p> Full article ">Figure 5
<p>Relative expression of mRNA of the <span class="html-italic">tnfa</span> gene in different tissues of <span class="html-italic">C. gariepinus</span> (<span class="html-italic">p</span>-values for the brain, gill, gonad, liver, and muscle tissues were 0.5445, 0.1272, 0.774, 0.007937, and 0.1091 (for <span class="html-italic">B. subtilis</span> R1); 0.01978, 0.008842, 0.4466, 0.09524, and 0.3561 (for <span class="html-italic">B. subtilis</span> R4); and 0.01753, 0.04634, 0.1412, 0.007937, 0.6802 (for <span class="html-italic">B. velezensis</span> R5), respectively). Thick lines inside the boxes indicate the medians; circles outside the boxes indicate the outliers.</p> Full article ">Figure 6
<p>Relative expression of mRNA of the <span class="html-italic">il1β</span> gene in different tissues of <span class="html-italic">C. gariepinus</span> (<span class="html-italic">p</span>-values for the brain, gill, gonad, liver, and muscle tissues were 0.1005, 0.005556, 0.03175, 0.07213, and 0.3931 (for <span class="html-italic">B. subtilis</span> R1); 0.07737, 0.007937, 0.8413, 0.02697, and 0.07423 (for <span class="html-italic">B. subtilis</span> R4); and 0.1121, 0.1508, 0.03175, 0.2175, and 0.615 (for <span class="html-italic">B. velezensis</span> R5), respectively). Thick lines inside the boxes indicate the medians; circles outside the boxes indicate the outliers.</p> Full article ">Figure 7
<p>Relative expression of mRNA of the <span class="html-italic">lysC</span> gene in different tissues of <span class="html-italic">C. gariepinus</span> (<span class="html-italic">p</span>-values for the brain, gill, gonad, liver, and muscle tissues was 0.1149, 0.003685, 0.02024, 0.007937, 0.8413 (for <span class="html-italic">B. subtilis</span> R1); 0.8046, 0.0006603, 0.03012, 0.09524, and 0.01587 (for <span class="html-italic">B. subtilis</span> R4); and 0.01873, 0.01638, 0.001216, 0.007937, and 0.007937 (for <span class="html-italic">B. velezensis</span> R5), respectively). Thick lines inside the boxes indicate the medians; circles outside the boxes indicate the outliers.</p> Full article ">Figure 8
<p>Weight gain dynamic throughout the experiment. Since Day 36, all groups have a statistically significant difference from the control (<span class="html-italic">p</span> < 0.05).</p> Full article ">Figure 9
<p>Effect of potential probiotic <span class="html-italic">Bacillus</span> strains on weight gain. All groups have a statistically significant difference from the control (<span class="html-italic">p</span> < 0.05).</p> Full article ">
<p>Antioxidant and DNA-protective activity of potential probiotic strains. All effects were statistically significant (<span class="html-italic">p</span> < 0.05). Tocopherol was used as a standard antioxidant.</p> Full article ">Figure 2
<p>Frequencies of spontaneous and dioxidine-induced mutagenesis in <span class="html-italic">E. coli</span> MG1655 under the action of preparations of the studied strains. * These experimental data have a statistically significant difference from the control (<span class="html-italic">p</span> < 0.05).</p> Full article ">Figure 3
<p>Relative mRNA expression of the <span class="html-italic">hsp70</span> gene in different tissues of <span class="html-italic">C. gariepinus</span> (<span class="html-italic">p</span>-values for the brain, gill, gonad, liver, and muscle tissues were 0.007937, 0.07276, 0.09663, 0.01015, and 0.01889 (for <span class="html-italic">B. subtilis</span> R1); 0.5476, 0.06088, 0.125, 0.07507, and 0.02579 (for <span class="html-italic">B. subtilis</span> R4); and 0.15, 0.08589, 0.1718, 0.02247, and 1.1157 (for <span class="html-italic">B. velezensis</span> R5), respectively). Thick lines inside the boxes indicate the medians; circles outside the boxes indicate the outliers.</p> Full article ">Figure 4
<p>Relative mRNA expression of the <span class="html-italic">cxc</span> gene in different tissues of <span class="html-italic">C. gariepinus</span> (<span class="html-italic">p</span>-values for the brain, gill, gonad, liver, and muscle tissues were 0.9802, 0.08762, 0.1558, 0.003346 (for <span class="html-italic">B. subtilis</span> R1); 0.6268, 0.09122, 0.207, 0.09524, and 0.1676 (for <span class="html-italic">B. subtilis</span> R4); and 0.2877, 0.2723, 0.004556, 0.01587, and 0.466 (for <span class="html-italic">B. velezensis</span> R5), respectively). Thick lines inside the boxes indicate the medians; circles outside the boxes indicate the outliers.</p> Full article ">Figure 5
<p>Relative expression of mRNA of the <span class="html-italic">tnfa</span> gene in different tissues of <span class="html-italic">C. gariepinus</span> (<span class="html-italic">p</span>-values for the brain, gill, gonad, liver, and muscle tissues were 0.5445, 0.1272, 0.774, 0.007937, and 0.1091 (for <span class="html-italic">B. subtilis</span> R1); 0.01978, 0.008842, 0.4466, 0.09524, and 0.3561 (for <span class="html-italic">B. subtilis</span> R4); and 0.01753, 0.04634, 0.1412, 0.007937, 0.6802 (for <span class="html-italic">B. velezensis</span> R5), respectively). Thick lines inside the boxes indicate the medians; circles outside the boxes indicate the outliers.</p> Full article ">Figure 6
<p>Relative expression of mRNA of the <span class="html-italic">il1β</span> gene in different tissues of <span class="html-italic">C. gariepinus</span> (<span class="html-italic">p</span>-values for the brain, gill, gonad, liver, and muscle tissues were 0.1005, 0.005556, 0.03175, 0.07213, and 0.3931 (for <span class="html-italic">B. subtilis</span> R1); 0.07737, 0.007937, 0.8413, 0.02697, and 0.07423 (for <span class="html-italic">B. subtilis</span> R4); and 0.1121, 0.1508, 0.03175, 0.2175, and 0.615 (for <span class="html-italic">B. velezensis</span> R5), respectively). Thick lines inside the boxes indicate the medians; circles outside the boxes indicate the outliers.</p> Full article ">Figure 7
<p>Relative expression of mRNA of the <span class="html-italic">lysC</span> gene in different tissues of <span class="html-italic">C. gariepinus</span> (<span class="html-italic">p</span>-values for the brain, gill, gonad, liver, and muscle tissues was 0.1149, 0.003685, 0.02024, 0.007937, 0.8413 (for <span class="html-italic">B. subtilis</span> R1); 0.8046, 0.0006603, 0.03012, 0.09524, and 0.01587 (for <span class="html-italic">B. subtilis</span> R4); and 0.01873, 0.01638, 0.001216, 0.007937, and 0.007937 (for <span class="html-italic">B. velezensis</span> R5), respectively). Thick lines inside the boxes indicate the medians; circles outside the boxes indicate the outliers.</p> Full article ">Figure 8
<p>Weight gain dynamic throughout the experiment. Since Day 36, all groups have a statistically significant difference from the control (<span class="html-italic">p</span> < 0.05).</p> Full article ">Figure 9
<p>Effect of potential probiotic <span class="html-italic">Bacillus</span> strains on weight gain. All groups have a statistically significant difference from the control (<span class="html-italic">p</span> < 0.05).</p> Full article ">
Open AccessArticle
A Deep Dive into the Trophic Ecology of Engraulis ringens: Assessing Diet Through Stomach Content and Stable Isotope Analysis
by
Carolina Cárcamo, Eric T. Schultz, Francisco Leiva, Alvaro Saavedra and Sebastian A. Klarian
Fishes 2024, 9(12), 475; https://doi.org/10.3390/fishes9120475 - 25 Nov 2024
Abstract
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Our study investigates the trophic ecology of the anchoveta (Engraulis ringens). The anchoveta plays a key role in the Greater Humboldt Ecosystem and is extensively exploited by countries from the south-eastern Pacific Ocean. For a comprehensive study of trophic ecology, we
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Our study investigates the trophic ecology of the anchoveta (Engraulis ringens). The anchoveta plays a key role in the Greater Humboldt Ecosystem and is extensively exploited by countries from the south-eastern Pacific Ocean. For a comprehensive study of trophic ecology, we employed a combined approach that included stomach content analysis, stable isotope analysis, and scaled mass index of body condition. Our results showed that the multivariate composition of the diet varies significantly between life stage and fishing zones in Chile. Copepods and euphausiids emerged as the dominant prey found in the stomachs across all fisheries zones. Stable isotope analysis revealed significant differences among different zones. The scaled mass index values were higher in the northern zone compared to the southern zones, for both juveniles and adults. This research carries significant implications for fisheries management and conservation efforts, such as the development of targeted management strategies that address variations in the trophic structure of anchoveta across different life stages and fishing zones.
Full article
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<p>Study area and sampling locations off the coast of Chile. Samples were collected during three separate hydroacoustic surveys for Pacific small pelagic fishes conducted aboard the research vessel B/C Abate Molina, operated by the Instituto de Fomento Pesquero (IFOP). The sea surface temperature (SST) is represented by the mean value observed during the sampling period. The data were obtained from <a href="https://giovanni.gsfc.nasa.gov" target="_blank">https://giovanni.gsfc.nasa.gov</a>, accessed on 17 June 2024.</p> Full article ">Figure 2
<p>Estimation of the proportion of main prey items (copepods and euphausiids) in (<b>a</b>) juvenile and (<b>b</b>) adult anchovetas in fishing zones, based on Bayesian analysis of stomach contents.</p> Full article ">Figure 3
<p>Biplot of stable isotopes <span class="html-italic">δ<sup>13</sup>C</span> and <span class="html-italic">δ<sup>15</sup>N</span> for anchovetas in zones A, B, and C and their main prey items.</p> Full article ">
<p>Study area and sampling locations off the coast of Chile. Samples were collected during three separate hydroacoustic surveys for Pacific small pelagic fishes conducted aboard the research vessel B/C Abate Molina, operated by the Instituto de Fomento Pesquero (IFOP). The sea surface temperature (SST) is represented by the mean value observed during the sampling period. The data were obtained from <a href="https://giovanni.gsfc.nasa.gov" target="_blank">https://giovanni.gsfc.nasa.gov</a>, accessed on 17 June 2024.</p> Full article ">Figure 2
<p>Estimation of the proportion of main prey items (copepods and euphausiids) in (<b>a</b>) juvenile and (<b>b</b>) adult anchovetas in fishing zones, based on Bayesian analysis of stomach contents.</p> Full article ">Figure 3
<p>Biplot of stable isotopes <span class="html-italic">δ<sup>13</sup>C</span> and <span class="html-italic">δ<sup>15</sup>N</span> for anchovetas in zones A, B, and C and their main prey items.</p> Full article ">
Open AccessArticle
Effects of Transport Stress (Duration and Density) on the Physiological Conditions of Marbled Rockfish (Sebastiscus marmoratus, Cuvier 1829) Juveniles and Water Quality
by
Jiahao Wang, Kaida Xu, Xinyi Chen, Haoxue Wang and Zhe Li
Fishes 2024, 9(12), 474; https://doi.org/10.3390/fishes9120474 - 22 Nov 2024
Abstract
Live transportation is a critical component of fish farming and hatchery release. To optimize hatchery-release techniques and improve the survival rate of marbled rockfish (Sebastiscus marmoratus, Cuvier 1829) juveniles, the effects of varying transport durations (2, 4, 6, and 8 h)
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Live transportation is a critical component of fish farming and hatchery release. To optimize hatchery-release techniques and improve the survival rate of marbled rockfish (Sebastiscus marmoratus, Cuvier 1829) juveniles, the effects of varying transport durations (2, 4, 6, and 8 h) and densities (60, 90, 120, and 150 kg m−3) on the physiological indicators of the fish and water quality were investigated under controlled laboratory conditions. We found that as transport duration and density increased, water quality significantly deteriorated, with ammonia nitrogen levels rising and dissolved oxygen content and pH levels decreasing. Physiological indicators including levels of lactate, cortisol, and malondialdehyde and activities of superoxide dismutase, alkaline phosphatase, and glutamate oxaloacetate transaminase notably increased, indicating that the fish experienced heightened stress during transport. Additionally, the mortality rate of juveniles increased significantly with increasing density and transport duration. The high mortality rate might be associated with sustained elevated cortisol levels and liver damage. Our results are helpful for determining the optimal transport conditions for S. marmoratus juveniles and also provide valuable insights for improving transport techniques for other aquatic animal species.
Full article
(This article belongs to the Special Issue Biodiversity and Spatial Distribution of Fishes, Second Edition)
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<p>Water quality parameters including (<b>a</b>) NH<sub>4</sub><sup>+</sup>-N (unit: mg L<sup>−1</sup>), (<b>b</b>) pH, and (<b>c</b>) DO (mg L<sup>−1</sup>) for different density groups (60, 90, 120, and 150 kg m<sup>−3</sup> represented by the red, reddish brown, light yellow, and light blue bars, respectively) after different transport durations (0, 2, 4, 6, and 8 h). Different uppercase letters indicate significant differences between different transport durations within the same density group (<span class="html-italic">p</span> < 0.05). Different lowercase letters indicate significant differences between different density groups at the same transport duration (<span class="html-italic">p</span> < 0.05). The same is true for subsequent figures.</p> Full article ">Figure 1 Cont.
<p>Water quality parameters including (<b>a</b>) NH<sub>4</sub><sup>+</sup>-N (unit: mg L<sup>−1</sup>), (<b>b</b>) pH, and (<b>c</b>) DO (mg L<sup>−1</sup>) for different density groups (60, 90, 120, and 150 kg m<sup>−3</sup> represented by the red, reddish brown, light yellow, and light blue bars, respectively) after different transport durations (0, 2, 4, 6, and 8 h). Different uppercase letters indicate significant differences between different transport durations within the same density group (<span class="html-italic">p</span> < 0.05). Different lowercase letters indicate significant differences between different density groups at the same transport duration (<span class="html-italic">p</span> < 0.05). The same is true for subsequent figures.</p> Full article ">Figure 2
<p>Physiological indicators including (<b>a</b>) lactate (µmol g<sup>−1</sup>), (<b>b</b>) MDA (nmol mL<sup>−1</sup>), (<b>c</b>) cortisol (ng L<sup>−1</sup>), (<b>d</b>) SOD (IU mL<sup>−1</sup>), (<b>e</b>) ALP (IU L<sup>−1</sup>), and (<b>f</b>) GOT (U L<sup>−1</sup>) in each density groups (60, 90, 120, and 150 kg m<sup>−3</sup> represented by the red, reddish brown, light yellow, and light blue bar) after different transport duration (0, 2, 4, 6, and 8 h).</p> Full article ">Figure 3
<p>Mortality rates (%) of the samples under different transport durations (2, 4, 6, and 8 h) and densities (0, 60, 90, 120, and 150 kg m<sup>−3</sup>).</p> Full article ">Figure 4
<p>Results of correlation analysis between mortality rate and physiological indicators. The right bar shows the correlation closeness between 0.6 represented by red and −0.4 represented by light blue.</p> Full article ">
<p>Water quality parameters including (<b>a</b>) NH<sub>4</sub><sup>+</sup>-N (unit: mg L<sup>−1</sup>), (<b>b</b>) pH, and (<b>c</b>) DO (mg L<sup>−1</sup>) for different density groups (60, 90, 120, and 150 kg m<sup>−3</sup> represented by the red, reddish brown, light yellow, and light blue bars, respectively) after different transport durations (0, 2, 4, 6, and 8 h). Different uppercase letters indicate significant differences between different transport durations within the same density group (<span class="html-italic">p</span> < 0.05). Different lowercase letters indicate significant differences between different density groups at the same transport duration (<span class="html-italic">p</span> < 0.05). The same is true for subsequent figures.</p> Full article ">Figure 1 Cont.
<p>Water quality parameters including (<b>a</b>) NH<sub>4</sub><sup>+</sup>-N (unit: mg L<sup>−1</sup>), (<b>b</b>) pH, and (<b>c</b>) DO (mg L<sup>−1</sup>) for different density groups (60, 90, 120, and 150 kg m<sup>−3</sup> represented by the red, reddish brown, light yellow, and light blue bars, respectively) after different transport durations (0, 2, 4, 6, and 8 h). Different uppercase letters indicate significant differences between different transport durations within the same density group (<span class="html-italic">p</span> < 0.05). Different lowercase letters indicate significant differences between different density groups at the same transport duration (<span class="html-italic">p</span> < 0.05). The same is true for subsequent figures.</p> Full article ">Figure 2
<p>Physiological indicators including (<b>a</b>) lactate (µmol g<sup>−1</sup>), (<b>b</b>) MDA (nmol mL<sup>−1</sup>), (<b>c</b>) cortisol (ng L<sup>−1</sup>), (<b>d</b>) SOD (IU mL<sup>−1</sup>), (<b>e</b>) ALP (IU L<sup>−1</sup>), and (<b>f</b>) GOT (U L<sup>−1</sup>) in each density groups (60, 90, 120, and 150 kg m<sup>−3</sup> represented by the red, reddish brown, light yellow, and light blue bar) after different transport duration (0, 2, 4, 6, and 8 h).</p> Full article ">Figure 3
<p>Mortality rates (%) of the samples under different transport durations (2, 4, 6, and 8 h) and densities (0, 60, 90, 120, and 150 kg m<sup>−3</sup>).</p> Full article ">Figure 4
<p>Results of correlation analysis between mortality rate and physiological indicators. The right bar shows the correlation closeness between 0.6 represented by red and −0.4 represented by light blue.</p> Full article ">
Open AccessArticle
Correlation Between Sensory Characteristics and Physicochemical Properties of Wild and Farmed Frozen Southern Bluefin Tuna (Thunnus maccoyii)
by
Hiroki Kashikura, Masafumi Yagi, Yusa Nakamura, Akira Sakai, Kigen Takahashi, Seiichi Hiratsuka and Keiichi Goto
Fishes 2024, 9(12), 473; https://doi.org/10.3390/fishes9120473 - 22 Nov 2024
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In this study, to investigate the quality of wild and farmed frozen southern bluefin tuna, physicochemical analyses and sensory evaluations were conducted. Principal component analysis was then performed using the results obtained to examine the correlation between the bluefin tuna’s taste characteristics and
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In this study, to investigate the quality of wild and farmed frozen southern bluefin tuna, physicochemical analyses and sensory evaluations were conducted. Principal component analysis was then performed using the results obtained to examine the correlation between the bluefin tuna’s taste characteristics and physicochemical properties. The sensory evaluation suggested differences in texture and acidity between wild and farmed fish, whereas the principal component analysis indicated differences in fatty acid and amino acid composition. Wild fish contained higher levels of docosahexaenoic acid and monounsaturated fatty acids, while farmed fish had higher levels of saturated fatty acids. Regarding free amino acids and dipeptides, wild fish had higher levels of anserine and alanine, whereas farmed fish showed higher levels of glutamine and histidine, and acidity was observed in farmed fish. Furthermore, based on the results of the principal component analysis, it was inferred that the content of inosinic acid, which is considered an umami component in fish, may have a low impact on palatability. These factors were suggested to influence the differences between wild and farmed tuna.
Full article
Figure 1
Figure 1
<p>Principal component analysis chart with cumulative contribution rate of 50.2%. Sample names show abbreviation, sample number, and part of fish (A: <span class="html-italic">Akami</span>; C: <span class="html-italic">Chu-toro</span>; and O: <span class="html-italic">O-toro</span>, respectively). Red vectors correspond to <a href="#fishes-09-00473-t002" class="html-table">Table 2</a>. Thick line: Wild, farm-raised; Dashed line: <span class="html-italic">Akami</span> group; Dotted line: <span class="html-italic">Chu-toro</span> and <span class="html-italic">O-toro</span> groups.</p> Full article ">Figure 2
<p>Principal component analysis chart with cumulative contribution rate of 60.9%. Sample name shows abbreviation, sample number, and part of fish (A: <span class="html-italic">Akami</span>; C: <span class="html-italic">Chu-toro</span>; and O: <span class="html-italic">O-toro</span>, respectively). Red vectors correspond to <a href="#fishes-09-00473-t002" class="html-table">Table 2</a>. Thick line: Wild, farm-raised; Dashed line: <span class="html-italic">Akami</span> group; Dotted line: <span class="html-italic">Chu-toro</span> and <span class="html-italic">O-toro</span> groups.</p> Full article ">Figure 3
<p>Principal component analysis chart with cumulative contribution rate of 70.1%. Sample name shows abbreviation, sample number, and part of fish (A: <span class="html-italic">Akami</span>; C: <span class="html-italic">Chu-toro</span>; and O: <span class="html-italic">O-toro</span>, respectively). Red vector corresponds to <a href="#fishes-09-00473-t002" class="html-table">Table 2</a>. Thick line: Wild, farm-raised; Dashed line: <span class="html-italic">Akami</span> group; Dotted line: <span class="html-italic">Chu-toro</span> and <span class="html-italic">O-toro</span> groups.</p> Full article ">
<p>Principal component analysis chart with cumulative contribution rate of 50.2%. Sample names show abbreviation, sample number, and part of fish (A: <span class="html-italic">Akami</span>; C: <span class="html-italic">Chu-toro</span>; and O: <span class="html-italic">O-toro</span>, respectively). Red vectors correspond to <a href="#fishes-09-00473-t002" class="html-table">Table 2</a>. Thick line: Wild, farm-raised; Dashed line: <span class="html-italic">Akami</span> group; Dotted line: <span class="html-italic">Chu-toro</span> and <span class="html-italic">O-toro</span> groups.</p> Full article ">Figure 2
<p>Principal component analysis chart with cumulative contribution rate of 60.9%. Sample name shows abbreviation, sample number, and part of fish (A: <span class="html-italic">Akami</span>; C: <span class="html-italic">Chu-toro</span>; and O: <span class="html-italic">O-toro</span>, respectively). Red vectors correspond to <a href="#fishes-09-00473-t002" class="html-table">Table 2</a>. Thick line: Wild, farm-raised; Dashed line: <span class="html-italic">Akami</span> group; Dotted line: <span class="html-italic">Chu-toro</span> and <span class="html-italic">O-toro</span> groups.</p> Full article ">Figure 3
<p>Principal component analysis chart with cumulative contribution rate of 70.1%. Sample name shows abbreviation, sample number, and part of fish (A: <span class="html-italic">Akami</span>; C: <span class="html-italic">Chu-toro</span>; and O: <span class="html-italic">O-toro</span>, respectively). Red vector corresponds to <a href="#fishes-09-00473-t002" class="html-table">Table 2</a>. Thick line: Wild, farm-raised; Dashed line: <span class="html-italic">Akami</span> group; Dotted line: <span class="html-italic">Chu-toro</span> and <span class="html-italic">O-toro</span> groups.</p> Full article ">
Open AccessBrief Report
When Mediterranean Artisanal Fishers Protect Coastal Ecosystems
by
Cornelia E. Nauen
Fishes 2024, 9(12), 472; https://doi.org/10.3390/fishes9120472 - 22 Nov 2024
Abstract
According to EuroStat data, the recorded landings of fisheries products from European waters were estimated at about 6 million tons in 2001, down to 3.2 million tons in 2022. This gradual decline slowed after the entering into force of the reform of the
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According to EuroStat data, the recorded landings of fisheries products from European waters were estimated at about 6 million tons in 2001, down to 3.2 million tons in 2022. This gradual decline slowed after the entering into force of the reform of the European Common Fisheries Policy (CFP) at the end of 2013, but was followed by a steeper decline after 2018. This is reflected in the last assessment of the Scientific Technical and Economic Committee for Fisheries (STEPF), noting that despite progress in the NE Atlantic management, 41% of the assessed stocks in 2022 were outside safe biological limits, down from 80% in 2003. Improvements in the Mediterranean are significantly slower. A warming ocean provokes the measurable poleward migration of species and adds stress to predator–prey relations in all European seas. Within this general picture, the broad-brush landscape is influenced by policy applications more in favour of industrial exploitation and regulatory and market environments, making it very hard for many small-scale fishers (SSFs) to remain in business, let alone attract younger successors for generational transition. In crowded marine spaces, it is a challenge to allocate access rights fairly between fisheries, exclusion zones for resource and habitat protection and much-needed ecosystem recovery, platforms for fossil exploitation, wind farms, underwater cables and recreational uses. Two examples of local initiatives with faunal recovery potential in the Mediterranean are briefly presented as a bottom-up complement to more top-down management approaches. They are spearheaded by artisanal fishers, who seek to restore spawning grounds and other coastal habitats as a way to procure enough fish and other complementary activities to secure their livelihoods in the future. They are supported by local scientists and nature conservation organisations. While promising, this is still rather the exception. Here, it is argued that trust-building between artisanal fishers, conservationists and scientists, and greater systemic support to SSFs by governments, increase chances for the urgently needed structural shifts that deliver the reversal in the ongoing decline in biodiversity and ocean productivity that all aspire to, to ensure sustained social and economic benefits.
Full article
(This article belongs to the Special Issue Fisheries Policies and Management)
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Open AccessArticle
Identification of SNPs and Candidate Genes Associated with Growth Using GWAS and Transcriptome Analysis in Portuguese Oyster (Magallana angulata)
by
Jingyi Xie, Yue Ning, Yi Han, Caiyuan Su, Xiaoyan Zhou, Qisheng Wu, Xiang Guo, Jianfei Qi, Hui Ge, Yizou Ke and Mingyi Cai
Fishes 2024, 9(12), 471; https://doi.org/10.3390/fishes9120471 - 22 Nov 2024
Abstract
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Portuguese oyster (Magallana angulata) is one of the most important shellfish species worldwide. Although significant improvements in growth have been achieved through artificial selection breeding, the genetic basis underlying these traits remains unclear. Thus, this study aimed to (i) estimate variation
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Portuguese oyster (Magallana angulata) is one of the most important shellfish species worldwide. Although significant improvements in growth have been achieved through artificial selection breeding, the genetic basis underlying these traits remains unclear. Thus, this study aimed to (i) estimate variation and heritability for growth-related traits and (ii) identify SNPs and candidate genes associated with growth traits in Portuguese oyster. Five growth-related traits, including shell height (SH), shell length (SL), shell width (SW), whole weight (WW), and soft tissue weight (STW), were measured and analyzed in 114 one-year-old individuals from a cultivated population in Fujian Province, China. Through whole-genome sequencing and genotyping, we obtained 8,183,713 high-quality SNPs. Based on the genomic relationship matrix, heritability for the five traits was estimated, ranging from 0.071 to 0.695. Through genome-wide association analysis (GWAS), a total of nine SNPs were identified as significantly or suggestively associated with one of the growth-related traits, each explaining phenotypic variation ranging from 14.13% to 18.56%. Differentially expressed genes (DEGs) between individuals with extreme phenotypes were identified using comparative transcriptome analysis, ranging from 868 to 2274 for each trait. By combining GWAS and comparative transcriptome analysis, a total of seven candidate genes were identified, with biological functions related to growth inhibition, stress response, cell cycle regulation, and immune defense. The associations between the candidate genes and the growth-related traits were validated by using single-marker association analysis in other populations. Based on SNPs in these candidate genes, 16 haplotypes associated with growth-related traits were obtained. This study contributes to a deeper understanding of the genetic mechanisms of growth traits, and provides a theoretical basis and genetic markers for the breeding of fast-growing strains of the Portuguese oyster.
Full article
Figure 1
Figure 1
<p>(<b>A</b>) Identification of shell sizes of Portuguese oyster. (<b>B</b>) Pearson correlation between each pair of studied traits.</p> Full article ">Figure 2
<p>Comparison of growth traits between male and female individuals. **** indicates <span class="html-italic">p</span> < 0.0001; ns indicates not significant.</p> Full article ">Figure 3
<p>GWAS of growth traits in Portuguese oyster, including SH, SL, SW, WW, and STW. The dashed lines at −log10 (<span class="html-italic">p</span>) = 6.91 and 8.20 correspond to the suggestive and significant association levels, respectively.</p> Full article ">Figure 4
<p>DEGs between extreme phenotypes for five growth-related traits. (<b>A</b>) Volcano plot of DEGs for the SH trait. Red and blue dots represent significantly upregulated and downregulated genes (|log 2 FC| ≥ 1 and <span class="html-italic">p</span> < 0.05), respectively. Gray dots represent genes with no significant differential expression between individuals with the largest and smallest phenotypes. (<b>B</b>) Volcano plot of DEGs for SL trait. (<b>C</b>) Volcano plot of DEGs for SW trait. (<b>D</b>) Volcano plot of DEGs for WW trait. (<b>E</b>) Volcano plot of DEGs for STW trait.</p> Full article ">Figure 5
<p>Venn diagrams of DEGs obtained from RNA-seq based on the extreme phenotypes of 5 growth traits. (<b>A</b>) Downregulated DEGs. (<b>B</b>) Upregulated DEGs. Green represents SH trait, blue represents SL trait, pink represents SW trait, yellow represents WW trait, and orange represents STW trait.</p> Full article ">Figure 6
<p>Variation analysis of two candidate genes in the population. (<b>A</b>) NJ phylogenetic tree of the <span class="html-italic">sstr2</span> gene region. According to the branches of the NJ phylogenetic tree, all individuals were divided into three groups: G1, G2, and G3. (<b>B</b>) Comparison of genotype heatmaps of different branches of <span class="html-italic">sstr2</span> gene NJ tree. (<b>C</b>) Comparison of SH trait of different branches of <span class="html-italic">sstr2</span> gene NJ tree. (<b>D</b>) NJ phylogenetic tree of the <span class="html-italic">crfr2</span> gene region. According to the branches of the NJ phylogenetic tree, all individuals were divided into four groups: G1, G2, G3, and G4. (<b>E</b>) Comparison of genotype heatmaps of different branches of <span class="html-italic">crfr2</span> gene NJ tree. (<b>F</b>) Comparison of STW trait of different branches of <span class="html-italic">crfr2</span> gene NJ tree. * indicates <span class="html-italic">p</span> < 0.05, ** indicates <span class="html-italic">p</span> < 0.01, *** indicates <span class="html-italic">p</span> < 0.001, **** indicates <span class="html-italic">p</span> < 0.0001, and ns indicates not significant.</p> Full article ">
<p>(<b>A</b>) Identification of shell sizes of Portuguese oyster. (<b>B</b>) Pearson correlation between each pair of studied traits.</p> Full article ">Figure 2
<p>Comparison of growth traits between male and female individuals. **** indicates <span class="html-italic">p</span> < 0.0001; ns indicates not significant.</p> Full article ">Figure 3
<p>GWAS of growth traits in Portuguese oyster, including SH, SL, SW, WW, and STW. The dashed lines at −log10 (<span class="html-italic">p</span>) = 6.91 and 8.20 correspond to the suggestive and significant association levels, respectively.</p> Full article ">Figure 4
<p>DEGs between extreme phenotypes for five growth-related traits. (<b>A</b>) Volcano plot of DEGs for the SH trait. Red and blue dots represent significantly upregulated and downregulated genes (|log 2 FC| ≥ 1 and <span class="html-italic">p</span> < 0.05), respectively. Gray dots represent genes with no significant differential expression between individuals with the largest and smallest phenotypes. (<b>B</b>) Volcano plot of DEGs for SL trait. (<b>C</b>) Volcano plot of DEGs for SW trait. (<b>D</b>) Volcano plot of DEGs for WW trait. (<b>E</b>) Volcano plot of DEGs for STW trait.</p> Full article ">Figure 5
<p>Venn diagrams of DEGs obtained from RNA-seq based on the extreme phenotypes of 5 growth traits. (<b>A</b>) Downregulated DEGs. (<b>B</b>) Upregulated DEGs. Green represents SH trait, blue represents SL trait, pink represents SW trait, yellow represents WW trait, and orange represents STW trait.</p> Full article ">Figure 6
<p>Variation analysis of two candidate genes in the population. (<b>A</b>) NJ phylogenetic tree of the <span class="html-italic">sstr2</span> gene region. According to the branches of the NJ phylogenetic tree, all individuals were divided into three groups: G1, G2, and G3. (<b>B</b>) Comparison of genotype heatmaps of different branches of <span class="html-italic">sstr2</span> gene NJ tree. (<b>C</b>) Comparison of SH trait of different branches of <span class="html-italic">sstr2</span> gene NJ tree. (<b>D</b>) NJ phylogenetic tree of the <span class="html-italic">crfr2</span> gene region. According to the branches of the NJ phylogenetic tree, all individuals were divided into four groups: G1, G2, G3, and G4. (<b>E</b>) Comparison of genotype heatmaps of different branches of <span class="html-italic">crfr2</span> gene NJ tree. (<b>F</b>) Comparison of STW trait of different branches of <span class="html-italic">crfr2</span> gene NJ tree. * indicates <span class="html-italic">p</span> < 0.05, ** indicates <span class="html-italic">p</span> < 0.01, *** indicates <span class="html-italic">p</span> < 0.001, **** indicates <span class="html-italic">p</span> < 0.0001, and ns indicates not significant.</p> Full article ">
Open AccessEditorial
Monitoring and Conservation of Freshwater and Marine Fishes: Synopsis
by
Robert L. Vadas, Jr. and Robert M. Hughes
Fishes 2024, 9(12), 470; https://doi.org/10.3390/fishes9120470 - 21 Nov 2024
Abstract
Globally, native migratory and resident fishes are declining from aquatic and terrestrial ecosystem degradation resulting from physicochemical habitat alteration, migration barriers, over-exploitation, hatchery supplementation, non-native species introductions, and the climate crisis [...]
Full article
(This article belongs to the Special Issue Biomonitoring and Conservation of Freshwater & Marine Fishes)
Open AccessArticle
Validation of a Health Characterization Model for Tilapia Farming in a Brazilian Federative Unit
by
Ricardo da Silva Raposo, Nádia Valesca Biral de Oliveira, Marina Karina de Veiga Cabral Delphino, Carlos Augusto Gomes Leal, Ana Lourdes Arrais de Alencar Mota and Fabiano José Ferreira de Sant’Ana
Fishes 2024, 9(11), 469; https://doi.org/10.3390/fishes9110469 - 20 Nov 2024
Abstract
Brasília, Distrito Federal, is among the Brazilian cities with the highest number of tilapia farms, with around 660 farms, of which 112 are commercial. The aim of this study was to validate a health characterization model for commercial tilapia production using the production
[...] Read more.
Brasília, Distrito Federal, is among the Brazilian cities with the highest number of tilapia farms, with around 660 farms, of which 112 are commercial. The aim of this study was to validate a health characterization model for commercial tilapia production using the production chain in the Distrito Federal (DF), one of Brazil’s 27 federative units, by applying a semi-structured questionnaire. A total of 112 farms were categorized according to the degree of vulnerability to the introduction of pathogens and the risk of dissemination using two weighted scorecard tables that evaluated 15 items each. After calculating the mean between the two variables, the farms were classified from A (insignificant risk) to D (high risk). Most of the commercial tilapia farms in the Distrito Federal were categorized as B (39; 34.8%) and C (53; 47.3%), representing low and medium risk, respectively. When comparing the different commercial groups, a significant difference (p < 0.05) was observed in the mean scores between closed-system fattening farms and both semi-closed fattening farms and pay-to-fish farms. Closed-system fattening farms, such as those using biofloc, aquaponics, and recirculation aquaculture systems, showed the lowest vulnerability to pathogen entry and the lowest risk of disease spread. The study’s findings provide valuable health information for the official veterinary service of the DF, enabling the categorization of farms, identification of production units, and determination of the most vulnerable strata. Furthermore, the model can be easily applied by private companies and by official veterinary services in other states or countries with significant tilapia production that need to implement risk-based surveillance programs for tilapia farms.
Full article
(This article belongs to the Special Issue Safety Management in Fish Farming: Challenges and Further Trends)
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Figure 1
Figure 1
<p>Spatial distribution of commercial tilapia farms in the Distrito Federal, according to the purpose of production and the national river basins in the territory of the DF.</p> Full article ">Figure 2
<p>Perception of mortality of the tilapia farmers participating in the study presented by absolute number and percentage.</p> Full article ">Figure 3
<p>Graphical representation of the boxplots of the mean VL, RD, and BL scores of the farms in the 4 strata, separated by color according to the image legend.</p> Full article ">
<p>Spatial distribution of commercial tilapia farms in the Distrito Federal, according to the purpose of production and the national river basins in the territory of the DF.</p> Full article ">Figure 2
<p>Perception of mortality of the tilapia farmers participating in the study presented by absolute number and percentage.</p> Full article ">Figure 3
<p>Graphical representation of the boxplots of the mean VL, RD, and BL scores of the farms in the 4 strata, separated by color according to the image legend.</p> Full article ">
Open AccessArticle
Integrate Analysis of Eyestalk Proteome and Metabolome in Precocious and Formal Juvenile Female Eriocheir sinensis
by
Tingshuang Pan, Min Yang, Tong Li, He Jiang and Jun Ling
Fishes 2024, 9(11), 468; https://doi.org/10.3390/fishes9110468 - 18 Nov 2024
Abstract
The Chinese mitten crab (Eriocheir sinensis) is an economically important crustacean. With the development of the E. sisnensis industry, precocity has become a significant challenge in juvenile crab culturing. In this study, the eyestalks of female E. sinensis from precocious (PE)
[...] Read more.
The Chinese mitten crab (Eriocheir sinensis) is an economically important crustacean. With the development of the E. sisnensis industry, precocity has become a significant challenge in juvenile crab culturing. In this study, the eyestalks of female E. sinensis from precocious (PE) and normal juvenile (NE) groups were used for proteome and metabolome analyses. In total, 731 up-regulated and 657 down-regulated differentially expressed proteins (DEPs) were identified in the PE and NE groups. In addition, 110 differentially expressed metabolites (DMs) were up-regulated and 256 were down-regulated in the PE group. An integrated analysis showed 5667 significant correlations between the metabolites and proteins and 109 common pathways in the proteome and metabolome. The proteins were mostly associated with the mechanistic target of rapamycin (mTOR) pathway, longevity regulation, autophagy, and the pyrimidine and purine metabolism pathways. The metabolites were primarily enriched in amino acid and lipid metabolisms. These results demonstrated the differences in the PE and NE groups at two omics levels and will be useful for the E. sinensis industry.
Full article
(This article belongs to the Special Issue Interactions between Fish and Pathogens in Aquaculture—2nd Edition)
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Figure 1
Figure 1
<p>Principle component analysis of proteome abundance in the precocious and normal juvenile groups. Green plot (PE) indicates the precocious Chinese mitten crab; blue plot (NE) indicates the normal juvenile Chinese mitten crab.</p> Full article ">Figure 2
<p>Gene ontology terms for DEPs between the precocious group and the normal juvenile group.</p> Full article ">Figure 3
<p>Top 30 KEGG pathways of DEPs.</p> Full article ">Figure 4
<p>Orthogonal partial least squares (OPLS-DA) score plots for precocious (blue) and normal juvenile (red) groups.</p> Full article ">Figure 5
<p>Volcano plots of DMs for the precocious group and normal juvenile group. The <span class="html-italic">x</span>-axis and <span class="html-italic">y</span>-axis represent fold change and −log10(<span class="html-italic">p</span>-value), respectively. In the volcano plot, red dots, blue dots, tawny dots, and grey dots represent significant up-regulated, significant down-regulated, non-significant different metabolites, and fitered metabolites, respectively.</p> Full article ">Figure 6
<p>KEGG enrichment analysis of different metabolites in the precocious group and normal juvenile group.</p> Full article ">
<p>Principle component analysis of proteome abundance in the precocious and normal juvenile groups. Green plot (PE) indicates the precocious Chinese mitten crab; blue plot (NE) indicates the normal juvenile Chinese mitten crab.</p> Full article ">Figure 2
<p>Gene ontology terms for DEPs between the precocious group and the normal juvenile group.</p> Full article ">Figure 3
<p>Top 30 KEGG pathways of DEPs.</p> Full article ">Figure 4
<p>Orthogonal partial least squares (OPLS-DA) score plots for precocious (blue) and normal juvenile (red) groups.</p> Full article ">Figure 5
<p>Volcano plots of DMs for the precocious group and normal juvenile group. The <span class="html-italic">x</span>-axis and <span class="html-italic">y</span>-axis represent fold change and −log10(<span class="html-italic">p</span>-value), respectively. In the volcano plot, red dots, blue dots, tawny dots, and grey dots represent significant up-regulated, significant down-regulated, non-significant different metabolites, and fitered metabolites, respectively.</p> Full article ">Figure 6
<p>KEGG enrichment analysis of different metabolites in the precocious group and normal juvenile group.</p> Full article ">
Open AccessArticle
Effects of Carnosine Addition in Low-Fishmeal Feed on the Growth Performance, Muscle Antioxidant Capacity and Flesh Quality of Orange-Spotted Grouper (Epinephelus coioides)
by
Dong Li, Weijun Chen, Yanxia Yin, Lulu Yang, Mingfan Chen, Yunzhang Sun and Jidan Ye
Fishes 2024, 9(11), 467; https://doi.org/10.3390/fishes9110467 - 18 Nov 2024
Abstract
Carnosine is a natural dipeptide made up of L-histidine and β-alanine which is rich in muscle tissues and has multiple physiological functions. The current research aimed to investigate the effects of varied carnosine concentrations in low-fishmeal feed on the growth, muscle antioxidant capacity
[...] Read more.
Carnosine is a natural dipeptide made up of L-histidine and β-alanine which is rich in muscle tissues and has multiple physiological functions. The current research aimed to investigate the effects of varied carnosine concentrations in low-fishmeal feed on the growth, muscle antioxidant capacity and flesh quality of orange-spotted grouper. Carnosine was supplemented at doses of 0, 10, 20, 40, 80, 160, and 320 mg/kg in low-fishmeal feed. Seven groups with three tanks of fish (11.4 ± 0.1 g/fish) were allotted one of the diets during the 8-week feeding trial. The growth rate, body protein content, muscle activities of superoxide dismutase and catalase, and muscle adhesiveness showed positive linear response and/or an open upward parabola with increasing carnosine concentrations, with a peak at 160 mg/kg of carnosine. Feed utilization, serum total protein content, gut trypsin activity, muscle glutathione peroxidase, total antioxidant capacity, muscle hardness, gumminess, chewiness and resilience followed the same pattern as the growth rate, reaching a peak at 320 mg/kg of carnosine; while the opposite trend was observed, reaching a minimum at 320 mg/kg for muscle malondialdehyde and 160 mg/kg for muscle liquid and water loss. The results indicated that appropriate carnosine addition could improve growth performance, muscle antioxidant capacity and flesh quality of grouper. The suitable inclusion concentration was estimated to be 195.14 mg/kg to achieve the best percent weight gain.
Full article
(This article belongs to the Special Issue Growth, Metabolism, and Flesh Quality in Aquaculture Nutrition)
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Open AccessArticle
Effects of Dietary Protein and Lipid Levels on the Growth Performance and Serum Biochemical Indices of Juvenile Furong Crucian Carp
by
Zhigang He, Xing Tian, Jinlong Li, Jiarong Guo, Xiaofei Cheng and Dongwu Wang
Fishes 2024, 9(11), 466; https://doi.org/10.3390/fishes9110466 - 16 Nov 2024
Abstract
The impact of dietary protein and lipid levels on the growth performance, feed utilization, and serum biochemical indices of Furong crucian carp was examined. Five hundred and forty carp (2.35 ± 0.08 g) were randomly assigned to nine groups and fed diets with
[...] Read more.
The impact of dietary protein and lipid levels on the growth performance, feed utilization, and serum biochemical indices of Furong crucian carp was examined. Five hundred and forty carp (2.35 ± 0.08 g) were randomly assigned to nine groups and fed diets with three different protein levels (30.0, 35.0, and 40.0%) and three different lipid levels (4.0, 7.0, and 10.0%) for 60 days. The current findings revealed that the interaction effect between dietary lipid and protein levels exhibited significance for the final average weight (FAW), weight gain rate (WGR), specific growth rate (SGR), feed efficiency (FE), energy deposition rate (EDR), whole-fish energy, ash, and fat content (p < 0.05). Specifically, there was a significant reduction in FAW, WGR, and SGR with increasing dietary fat supplementation. Conversely, FE, EDR, and protein efficiency ratios were significantly decreased with increasing dietary protein levels (p < 0.05). Furthermore, serum albumin and globulin levels exhibited significant increases in response to dietary lipid inclusion (p < 0.05). The findings collectively indicate that Furong crucian carp fed a diet comprising 4% lipid and 30% protein exhibited the optimal growth and feed utilization. Conversely, excessive protein and lipid supplementation were detrimental to growth and resulted in the aggravation of metabolic disorders.
Full article
(This article belongs to the Special Issue Development of Low-Crop, Low-Fishmeal or Low-Fish Oil Feeds for Aquaculture)
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Graphical abstract
Graphical abstract
Full article ">Figure 1
<p>Potential regulatory patterns in Furong crucian carp. (<b>A</b>) Correlation analysis based on the Spearman coefficient was used for the interactions between the module eigengenes extracted from the matrix of the main and interaction effects of dietary lipid and protein inclusion levels and the secondary module eigenvectors extracted from the phenotype matrix. The presence of ‘*, **, ***’ indicated the significant difference level at 0.05, 0.01, and 0.001, respectively. The different size of diamond represented that the number of significant pairwise comparison in each row of the heat map. The arrow stated that at least one significant pairwise comparison was observed in the corresponding row; (<b>B</b>) structural equation model. The structural equation model explains as much variance as possible in the variables in the model while understanding the covariance between the variables.</p> Full article ">
Full article ">Figure 1
<p>Potential regulatory patterns in Furong crucian carp. (<b>A</b>) Correlation analysis based on the Spearman coefficient was used for the interactions between the module eigengenes extracted from the matrix of the main and interaction effects of dietary lipid and protein inclusion levels and the secondary module eigenvectors extracted from the phenotype matrix. The presence of ‘*, **, ***’ indicated the significant difference level at 0.05, 0.01, and 0.001, respectively. The different size of diamond represented that the number of significant pairwise comparison in each row of the heat map. The arrow stated that at least one significant pairwise comparison was observed in the corresponding row; (<b>B</b>) structural equation model. The structural equation model explains as much variance as possible in the variables in the model while understanding the covariance between the variables.</p> Full article ">
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