Biocomputational exploration of intestinal keystone taxa and digesta versus mucus-associated markers in intensively reared hybrid African catfish (Clarias gariepinus × Heterobranchus longifilis)

Abstract Microbiome-governed probiotic selection is widely accepted approach to host disease mitigation. It is contingent upon both proper identification of putative disease-associated taxa and the ability to induce sustainable correction in their abundance. This might be challenging in case of disease-causing taxa, poor cultivability or high influence of other community members on their abundance. This study employed computational approach to identify autochtonous probiotic candidates with strong community regulating potential in the intestine of the hybrid African catfish ( Clarias gariepinus × Heterobranchus longifilis) . At the same time, given the well-documented variations in the distribution of microbial residents between mucus and luminal niche, the study model-validated mucus and digesta metataxonomic markers, which is pivotal to accurate identification of disease-causing or mitigating taxa and the impact of metataxonome-targeting interventions. Mid and hind-intestinal digesta and mucus samples of intensively reared hybrid catfish (35 animals) were collected, DNA was extracted, and Illumina paired-end sequencing was used for metataxonomic analysis. Taxonomic and metabolic features, as inferred from PicrusT analysis, were employed as predictors in Random Forest model for compartment categorization. LiNGAM was utilized to determine the key taxonomic and metabolic variables, adjusted for compartmental variances, while the impact of community on associations of taxonomic and metabolic features with the compartment were assessed through Ridge Regression model. Cause-effect exploration identified Cetobacterium , Akkermansia , and Rhodococcus as cultivable community assemblage drivers, with opportunistic pathogen reducing potential and without significant impact from other taxa on their abundance, making them perspective probiotic candidates in the hybrid catfish. Though less impactful, viewpoint probiotic choices include Mangrovibacter and Anaerofilum , with benefits linked to stimulation of the growth of the uncultivable Butirycicocaccae UCG-008. The results furthermore supported Butirycicocaccae UCG-008 , Turicibacter , Anaeroplasma , Clostridium sensu stricto 13 and Mangrovibacter as robust metataxonomic markers in the compartment-predictive model. The research has a heuristic potential to advance fish probiotic research and development of cost-effective tools for reliable intestinal compartment identification.

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Journal
Scientific Reports
Published
2026-08-17
DOI
https://doi.org/10.1038/s41598-026-64457-0
Primary Topic
Aquaculture disease management and microbiota
Type
article
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article

Biocomputational exploration of intestinal keystone taxa and digesta versus mucus-associated markers in intensively reared hybrid African catfish (Clarias gariepinus × Heterobranchus longifilis)

Gyöngyvér Fazekas, Erzsébet Baka, Zsuzsanna J. Sándor, Jovanka Lukić et al.
Scientific Reports
Aquaculture disease management and microbiota
article

Biocomputational exploration of intestinal keystone taxa and digesta versus mucus-associated markers in intensively reared hybrid African catfish (Clarias gariepinus × Heterobranchus longifilis)

Gyöngyvér Fazekas, Erzsébet Baka, Zsuzsanna J. Sándor, Jovanka Lukić, Zsolt Nagy, Shivendra Kumar, Anita Szűcs, Robert Egessa
article en

Abstract

Abstract Microbiome-governed probiotic selection is widely accepted approach to host disease mitigation. It is contingent upon both proper identification of putative disease-associated taxa and the ability to induce sustainable correction in their abundance. This might be challenging in case of disease-causing taxa, poor cultivability or high influence of other community members on their abundance. This study employed computational approach to identify autochtonous probiotic candidates with strong community regulating potential in the intestine of the hybrid African catfish ( Clarias gariepinus × Heterobranchus longifilis) . At the same time, given the well-documented variations in the distribution of microbial residents between mucus and luminal niche, the study model-validated mucus and digesta metataxonomic markers, which is pivotal to accurate identification of disease-causing or mitigating taxa and the impact of metataxonome-targeting interventions. Mid and hind-intestinal digesta and mucus samples of intensively reared hybrid catfish (35 animals) were collected, DNA was extracted, and Illumina paired-end sequencing was used for metataxonomic analysis. Taxonomic and metabolic features, as inferred from PicrusT analysis, were employed as predictors in Random Forest model for compartment categorization. LiNGAM was utilized to determine the key taxonomic and metabolic variables, adjusted for compartmental variances, while the impact of community on associations of taxonomic and metabolic features with the compartment were assessed through Ridge Regression model. Cause-effect exploration identified Cetobacterium , Akkermansia , and Rhodococcus as cultivable community assemblage drivers, with opportunistic pathogen reducing potential and without significant impact from other taxa on their abundance, making them perspective probiotic candidates in the hybrid catfish. Though less impactful, viewpoint probiotic choices include Mangrovibacter and Anaerofilum , with benefits linked to stimulation of the growth of the uncultivable Butirycicocaccae UCG-008. The results furthermore supported Butirycicocaccae UCG-008 , Turicibacter , Anaeroplasma , Clostridium sensu stricto 13 and Mangrovibacter as robust metataxonomic markers in the compartment-predictive model. The research has a heuristic potential to advance fish probiotic research and development of cost-effective tools for reliable intestinal compartment identification.

Scientific Reports
Magyar Agrár- és Élettudományi Egyetem (HU), Research Institute for Fisheries and Aquaculture (HU), National Agricultural Research Organisation (UG), Central Agricultural University (IN)
Magyar Agrár- és Élettudományi Egyetem
Life in Land
Openalex Percentile: Top 16%
Aquaculture disease management and microbiota
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