Fish microbiomics: Strengths and limitations of MinION sequencing of gilthead sea bream (Sparus aurata) intestinal microbiota

Signatures of dysbiosis in fish microbiomes in the context of aquaculture

“…We propose that in aquaculture settings, where disease and treatments are common and changes to water physio‐chemistry may occur frequently, fish homeostasis could be effectively monitored by regularly surveying bacterial community structure (beta diversity) in conjunction with the detection of increases in the abundance of potential pathogenic taxa. Although routine implementation of such monitoring programmes is still far from being easily achievable, next generation sequencing as well as analysis of entire communities in aquaculture settings are now feasible within a time frame of only a few days 150 . Additionally, our overview of published results is in line with previous findings, which demonstrate that microbial manipulation (e.g.…”

“…Although routine implementation of such monitoring programmes is still far from being easily achievable, next generation sequencing as well as analysis of entire communities in aquaculture settings are now feasible within a time frame of only a few days. 150 Additionally, our overview of published results is in line with previous findings, which demonstrate that microbial manipulation (e.g. through the delivery of probiotics) may be invaluable for aquaculture productivity by increasing microbiome resilience and stability and mitigating dysbiosis effects.…”

SAMBA: Structure-Learning of Aquaculture Microbiomes Using a Bayesian Approach

“…This “mock community” is composed of eight bacteria ( Listeria monocytogenes , Pseudomonas aeruginosa , Bacillus subtilis , Salmonella enterica , Escherichia coli , Lactobacillus fermentum , Enterococcus faecalis , and Staphylococcus aureus ) with known differential abundances, distributed on a log scale, ranging from 0.00001% ( S. aureus ) to 95.9% ( L. monocytogenes ). PCR conditions and sequencing procedures were performed as described by Toxqui-Rodriguez et al (2023) [ 45 ]. Briefly, eight replicates of the mock community were sequenced using the Oxford Nanopore Technologies MinION platform.…”

“…Taxonomy assignment and abundance quantification was performed using Minimap2 [ 49 ] aligning sequences against the SILVA database [ 50 ]. The two PCR conditions were optimized starting from the recommendations of the kit’s manufacturer: PCR1 (temperature of annealing 55 °C, 25 PCR cycles) and PCR2 (temperature of annealing 52 °C, 30 PCR cycles) [ 45 ]. The raw abundance counts (with the exception of S. aureus , which was not detected after taxonomic assignment) and the PCR conditions to sequence the mock community were used as input to SAMBA.…”

Exploring Multifunctional Markers of Biological Age in Farmed Gilthead Sea Bream (<em>Sparus aurata</em>). A Transcriptomic and Epigenetic Interplay for an Improved Fish Welfare Assessment Approach

“…The monitoring of the microorganisms living in or around the farmed animals is also a very promising aquaculture welfare indicator that can serve to plan corrective actions to mitigate an environmental issue, or to modulate the physiological state and the response of the organism from a holobiont perspective [17]. Thus, experimental evidence supports the use of some bacteria taxa as strong markers of thermal stress [18,19] or microplastic exposure [20,21] in both salmonid and nonsalmonid fish, which could be monitored in a real time and in a cost-effective manner with the advent of the 16S metabarcoding techniques based on the Nanopore technology [22,23], though we are far to establish references values for a wide spectrum of species and culture condition across the production cycle [24,25]. Other welfare indicators that can aid in developing an improved welfare assessment system are those based on age-related cellular and molecular modifications.…”