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Vik, J. O.

Publications and source records attributed to Vik, J. O..

12 recordsLinked to original sources

Evaluating sustainable feeds for aquaculture by simulating Atlantic salmon lipid metabolism

Atlantic salmon aquaculture is an important food source globally, but its sustainability is challenged by environmental impacts and the nutritional demands of farmed fish, particularly when it comes to fatty acids. Salmon feeds still rely heavily on fish or soybean meal, which poses sustainability concerns due to overfishing and carbon footprint. Innovations in feed composition seek to address these challenges, e.g., by using more sustainable ingredients, but the impacts of alternative feeds on fish and environment can be hard to quantify. Here, we developed a model with detailed and flexible accounting for lipids - Simulated Salmon Lipid Metabolism (SimSaLipiM) - to predict the nutritional and environmental outcomes of feed formulations. Integrating SimSaLipiM with feed ingredient databases enabled detailed analysis of an in vivo feed trial in silico. The model predicted optimal feed efficiency in agreement with observations as well as a detailed energy budget and fish biomass lipid composition for each feed. We also used the model to formulate novel sustainable feeds and feed supplements by minimising CO2 footprint. Thus, SimSaLipiM makes it easy to identify recipes that optimize key feed properties such as efficiency and environmental impacts. This could be a valuable tool for feed manufacturers, guiding the formulation of feeds that are both sustainable and cost effective. By bridging the gap between feed formulation and the flexible growth and energy requirements of a fish, SimSaLipiM can contribute to advancing sustainable aquaculture.

systems biology↗

Predicting microbial genome-scale metabolic networks directly from 16S rRNA gene sequences

Genome-scale metabolic models are key biotechnology tools that can predict metabolic capabilities and growth for an organism. In particular, these models have become indispensable for metabolic analysis of microbial species and communities such as the gut microbiomes of humans and other animals. Accurate microbial models can be built automatically from genomes, but many microbes have only been observed through sequencing of marker genes such as 16S rRNA and thus remain inaccessible to genome-scale modeling. To extend the scope of genome-scale metabolic models to microbes that lack genomic information, we trained an artificial neural network to build microbial models from numeric representations of 16S rRNA gene sequences. Specifically, we built models and extracted 16S rRNA gene sequences from more than 15,000 reference and representative microbial genomes, computed multiple sequence alignments and large language model embeddings for the 16S rRNA gene sequences, and trained the neural network to predict metabolic reaction probabilities from sequences, alignments, or embeddings. Training was fast on a single graphics processing unit and trained networks predicted reaction probabilities accurately for unseen archaeal and bacterial sequences and species. This makes it possible to reconstruct microbial genome-scale metabolic networks from any 16S rRNA gene sequence and enables simulation of metabolism and growth for all observed microbial life.

systems biology↗

A hierarchy of metabolite exchanges in metabolic models of microbial species and communities

The metabolic network of an organism can be analyzed as a constraint-based model. This analysis can be biased, optimizing an objective such as growth rate, or unbiased, aiming to describe the full feasible space of metabolic fluxes through pathway analysis or random flux sampling. In particular, pathway analysis can decompose the flux space into fundamental and formally defined metabolic pathways. Unbiased methods scale poorly with network size due to combinatorial explosion, but a promising approach to improve scalability is to focus on metabolic subnetworks, e.g., cells metabolite exchanges with each other and the environment, rather than the full metabolic networks. Here, we applied pathway enumeration and flux sampling to metabolite exchanges in microbial species and a microbial community, using models ranging from central carbon metabolism to genome-scale and focusing on pathway definitions that allow direct targeting of subnetworks such as metabolite exchanges (elementary conversion modes, elementary flux patterns, and minimal pathways). Enumerating growth-supporting metabolite exchanges, we found that metabolite exchanges from different pathway definitions were related through a hierarchy, and we show that this hierarchical relationship between pathways holds for metabolic networks and subnetworks more generally. Metabolite exchange frequencies, defined as the fraction of pathways in which each metabolite was exchanged, were similar across pathway definitions, with a few specific exchanges explaining large differences in pathway counts. This indicates that biological interpretation of predicted metabolite exchanges is robust to the choice of pathway definition, and it suggests strategies for more scalable pathway analysis. Our results also signal wider biological implications, facilitating detailed and interpretable analysis of metabolite exchanges and other subnetworks in fields such as metabolic engineering and synthetic biology. Author summaryPathway analysis of constraint-based metabolic models makes it possible to disentangle metabolism into formally defined metabolic pathways. A promising but underexplored application of pathway analysis is to analyze exchanges of metabolites between cells and their environment, which could also help overcome computational challenges and allow scaling to larger systems. Here, we used four different pathway definitions to enumerate combinations of metabolite exchanges that support growth in models of microbial species and a microbial community. We found that metabolite exchanges from different pathway definitions were related to each other through a previously unknown hierarchy, and we show that this hierarchical relationship between pathways holds more generally. Moreover, the fraction of pathways in which each metabolite was exchanged turned out to be remarkably consistent across pathway definitions despite large differences in pathway counts. In summary, our work shows how pathway definitions and their metabolite exchange predictions are related to each other, and it facilitates scalable and interpretable pathway analysis with applications in fields such as metabolic engineering.

systems biology↗

The genome regulatory landscape of Atlantic salmon liver through smoltification

The anadromous Atlantic salmon undergo a preparatory physiological transformation before seawater entry, referred to as smoltification. Key molecular developmental processes involved in this life stage transition, such as remodeling of gill functions, are known to be synchronized and modulated by environmental cues like photoperiod. However, little is known about the photoperiod influence and genome regulatory processes driving other canonical aspects of smoltification such as the large-scale changes in lipid metabolism and energy homeostasis in the developing smolt liver. Here we generate transcriptome, DNA methylation, and chromatin accessibility data from salmon livers across smoltification under different photoperiod regimes. We find a systematic reduction of expression levels of genes with a metabolic function, such as lipid metabolism, and increased expression of energy related genes such as oxidative phosphorylation, during smolt development in freshwater. However, in contrast to similar studies of the gill, smolt liver gene expression prior to seawater transfer was not impacted by photoperiodic history. Integrated analyses of gene expression and transcription factor (TF) binding signatures highlight likely important TF dynamics underlying smolt gene regulatory changes. We infer that ZNF682, KLFs, and NFY TFs are important in driving a liver metabolic shift from synthesis to break down of organic compounds in freshwater. Moreover, the increased expression of ribosomal associated genes after smolts were transferred to seawater was associated with increased occupancy of NFIX and JUN/FOS TFs proximal to transcription start sites, which could be the molecular consequence of rising levels of circulating growth hormones after seawater transition. We also identified differential methylation patterns across the genome, but associated genes were not functionally enriched or correlated to observed gene expression changes across smolt development. This contrasts with changes in TF binding which were highly correlated to gene expression, underscoring the relative importance of chromatin accessibility and transcription factor regulation in smoltification. Author summaryAtlantic salmon migrate between freshwater and seawater as they mature and grow. To survive the transition between these distinct environments, salmon transform their behavior, morphology, and physiology through the process of smoltification. One important adaptation to life at sea is remodeling of metabolism in the liver. It is unknown, however, whether this is a preadaptation that occurs before migration, what degree this is influenced by day length like other aspects of smoltification, and how gene regulatory programs shift to accomplish this transformation. We addressed these questions through a time course experiment where salmon were exposed to short and long day lengths, smoltified, and transferred to seawater. We sampled the livers and measured changes in gene expression, DNA methylation, chromatin accessibility, and transcription factor binding. We found metabolic remodeling occurred in freshwater before exposure to seawater and that day length did not have any long-term effects in liver. Transcription factor binding dynamics were closely linked to gene expression changes, and we describe transcription factors with key roles in smoltification. In stark contrast, we found no links between gene expression changes and DNA methylation patterns. This work deepens our understanding of the regulatory gear shifts associated with metabolic remodeling during smoltification.

genomics↗

Transcriptomics data integration for context-specific modeling of Atlantic salmon metabolism: functional evaluation of methods based on metabolic tasks

MotivationConstraint-based models (CBMs) are used to study the metabolic networks of organisms ranging from microbes to multicellular eukaryotes. Published CBMs are usually generic rather than context-specific, meaning that they do not capture metabolic differences between cell types, tissues, environments, or other conditions. However, only a subset of reactions in a model are likely to be active in any given context, and several methods have therefore been developed to extract context-specific models from generic CBMs through integration of omics data. ResultsWe tested the ability of six model extraction methods (MEMs) to create functionally accurate context-specific models of Atlantic salmon using a generic CBM (SALARECON) and liver transcriptomics data from contexts differing in water salinity (life stage) and dietary lipids. Reaction contents and metabolic task feasibility predictions of context-specific CBMs were mainly determined by the MEM that was used, but life stage explained significant variance in both contents and predictions for some MEMs. Three MEMs clearly outperformed the others in terms of their ability to capture context-specific metabolic activities inferred directly from the data, and one of these (GIMME) was much faster than the others. Context-specific versions of SALARECON consistently outperformed the generic version, showing that context-specific modeling captures more realistic representations of Atlantic salmon metabolism. Contactjon.vik@nmbu.no

systems biology↗

SALARECON connects the Atlantic salmon genome to growth and feed efficiency

Atlantic salmon (Salmo salar) is the most valuable farmed fish globally and there is much interest in optimizing its genetics and rearing conditions for growth and feed efficiency. Marine feed ingredients must be replaced to meet global demand, with challenges for fish health and sustainability. Metabolic models can address this by connecting genomes to metabolism, which converts nutrients in the feed to energy and biomass, but such models are currently not available for major aquaculture species such as salmon. We present SALARECON, a model focusing on energy, amino acid, and nucleotide metabolism that links the Atlantic salmon genome to metabolic fluxes and growth. It performs well in standardized tests and captures expected metabolic (in)capabilities. We show that it can explain observed hypoxic growth in terms of metabolic fluxes and apply it to aquaculture by simulating growth with commercial feed ingredients. Predicted limiting amino acids and feed efficiencies agree with data, and the model suggests that marine feed efficiency can be achieved by supplementing a few amino acids to plant- and insect-based feeds. SALARECON is a high-quality model that makes it possible to simulate Atlantic salmon metabolism and growth. It can be used to explain Atlantic salmon physiology and address key challenges in aquaculture such as development of sustainable feeds. Author summaryAtlantic salmon aquaculture generates billions of euros annually, but faces challenges of sustainability. Salmon are carnivores by nature, and fish oil and fish meal have become scarce resources in fish feed production. Novel, sustainable feedstuffs are being trialed hand in hand with studies of the genetics of growth and feed efficiency. This calls for a mathematical-biological framework to integrate data with understanding of the effects of novel feeds on salmon physiology and its interplay with genetics. We have developed the SALARECON model of the core salmon metabolic reaction network, linking its genome to metabolic fluxes and growth. Computational analyses show good agreement with observed growth, amino acid limitations, and feed efficiencies, illustrating the potential for in silico studies of potential feed mixtures. In particular, in silico screening of possible diets will enable more efficient animal experiments with improved knowledge gain. We have adopted best practices for test-driven development, virtual experiments to assay metabolic capabilities, revision control, and FAIR data and model management. This facilitates fast, collaborative, reliable development of the model for future applications in sustainable production biology.

systems biology↗

Targeted mutagenesis of {triangleup}5 and {triangleup}6 fatty acyl desaturases induce multiplex-mutagenesis and lipogenesis in Atlantic salmon (Salmo salar)

With declining wild fish populations, farmed Atlantic salmon (Salmo salar) has gained popularity as a source for healthy long-chain highly unsaturated fatty acids (LC-HUFA) including 20:5n-3 and 22:6n-3. However, the introduction of plant-based oil in fish diets has reduced the content of these beneficial LC-HUFA. The capability of biosynthesis of LC-HUFAs depends on fatty acids supplied in diets and the genetic potential residing in the fish. Key proteins involved in LC-HUFA synthesis in salmon include fatty acid desaturases 2 (Fads2). In a recent study we used CRISPR/Cas9 to generate two F0 mutant strains of salmon, 1){Delta} 6abc/5Mt with mutations in{Delta} 5fads2, {Delta}6fads2-a, {Delta}6fads2-b and {Delta}6fads2-c genes, and 2){Delta} 6bcMt with mutations in{Delta} 6fads2-b and {Delta}6fads2-c genes. The CRISPR mutated salmon (crispants) had reduced levels of LC-HUFA and expression of targeted fads2 genes. In present study we apply whole transcriptome analysis on these fads2 crispants. Our purpose is to evaluate the genetic mosaicism in fads2 crispants and the effect these mutations had on other lipid metabolism pathways in fish. Both{Delta} 6abc/5Mt and{Delta} 6bcMt crispants demonstrated high percentage of indels within all intended target genes, though different indel types and percentage were observed between individuals. Skipping of a CRISPR-targeted exon was observed in{Delta} 6fads2-a gene of{Delta} 6abc/5Mt salmon. The{Delta} 6abc/5Mt fish also displayed several disruptive indels which resulted in over 100 differentially expressed genes (DEGs) enriched in lipid metabolism pathways in liver. This includes up-regulation of srebp1 genes as well as genes involved in fatty acid de-novo synthesis, fatty acid {beta}-oxidation and lipogenesis. Both elovl5 and elovl2 genes were not changed, suggesting that the genes were not targeted by Srebp1. The mutation of{Delta} 6bcMt surprisingly resulted in over 3000 DEGs which were enriched in factors encoding genes involved in mRNA regulation and stability.

molecular biology↗

Comparative transcriptomics reveals domestication-associated features of Atlantic salmon lipid metabolism

Domestication of Salmo salar has imposed strong selection for production traits since the 1970s. The domestication has also imposed a radical shift in diet. Whereas wild salmon eats invertebrates, crustaceans and fish, the dietary lipids in domestic feed has since 1990 gradually shifted from fish oil (FO) to vegetable oil (VO), causing a decrease intake of long-chain polyunsaturated fatty acids (LC-PUFA). We tested the hypothesis that this shift has induced domestication-specific features of lipid metabolism in a 96-day feeding trial of domesticated and wild salmon fed diets based on FO, VO or phospholipids (PL). We addressed this by sampling tissues central in fat uptake (pyloric caeca) and processing (liver) and quantifying RNA expression and fatty acid composition. Domesticated salmon grew faster than wild salmon, with higher gene expression in glucose and lipid metabolism pathways. The promoters of differentially expressed genes were enriched for transcription factors involved in circadian clock regulation. Domesticated salmon had lower expression of cry2 and nr1d1, genes involved in negative regulation of circadian rhythm, with possible implications for the diurnal cycle of feed ingestion and basal metabolic rate. Only wild salmon showed a significant impact on growth of VO versus PL or FO feed, whereas domesticated but not wild salmon upregulated key LC-PUFA synthesis genes fads2d5 and fads2d6a in response to VO diet. Domesticated salmon had higher LC-PUFA but lower 18:3n-3 and 18:2n-6 in liver when fed VO, suggesting that domesticated salmon can better compensate for dietary shortage of LC-PUFA compared to wild salmon.

molecular biology↗

Transcriptional development of phospholipid and lipoprotein metabolism in different intestinal regions of Atlantic salmon (Salmo salar) fry

BackgroundIt has been suggested that the high phospholipid (PL) requirement in Atlantic salmon (Salmo salar) fry is due to insufficient intestinal de-novo synthesis causing low lipoprotein (LP) production and reduced transport capacity of dietary lipids. However, there has not been performed any in-depth ontological analysis of intestinal PL and LP synthesis with development of salmon. Therefore in this paper we used RNA-seq technology to test the hypothesis that the high PL requirement in salmon fry was associated with undeveloped PL synthesis and LP formation pathways in intestine. There was a special focus on the understanding homologous genes, especially from salmonid-specific fourth vertebrate whole-genome duplication (Ss4R), contribution to salmonid specific features of regulation of PL metabolic pathways. The study was performed in stomach, pyloric caeca and hindgut at 0.16g (1 day before first-feeding), 2.5g and 10g of salmon.\n\nResultsIn general, we found an up-regulation of de-novo phosphatidylcholine (PtdCho) synthesis, phosphatidylethanolamine (PtdEtn) and LP formation pathways in pyloric caeca of salmon between 0.16g and 10g. Thirteen genes in these pathways were highly (q<0.05) up-regulated in 2.5g salmon compared to 0.16g, while only five more significant (q<0.05) genes were found when the fish grew up to 10g. Different homologous genes were found dominating in stomach, pyloric caeca and hindgut. However, the expression of dominating genes in PL and LP synthesis pathways was much higher in pyloric caeca than stomach and hindgut. Salmon-specific homologous (Ss4R) genes had similar expression during development, while other homologs had more diverged expression.\n\nConclusionsAn increasing capacity for PL synthesis and LP formation was confirmed in pyloric caeca. The up-regulation of the de-novo PtdCho pathway confirms that the salmon fry have increasing requirement for dietary PtdCho compared to adult. The similar expressions between Ss4R homologous genes suggest that the functional divergence of these genes was incomplete compared to homologs derived from other whole genome duplication. The results of the present study have provided new information on the molecular mechanisms of phospholipid synthesis and lipoprotein formation in fish.

molecular biology↗

Interoperable genome annotation with GBOL, an extendable infrastructure for functional data mining

BackgroundA standard structured format is used by the public sequence databases to present genome annotations. A prerequisite for a direct functional comparison is consistent annotation of the genetic elements with evidence statements. However, the current format provides limited support for data mining, hampering comparative analyses at large scale.\n\nResultsThe provenance of a genome annotation describes the contextual details and derivation history of the process that resulted in the annotation. To enable interoperability of genome annotations, we have developed the Genome Biology Ontology Language (GBOL) and associated infrastructure (GBOL stack). GBOL is provenance aware and thus provides a consistent representation of functional genome annotations linked to the provenance. GBOL is modular in design, extendible and linked to existing ontologies. The GBOL stack of supporting tools enforces consistency within and between the GBOL definitions in the ontology (OWL) and the Shape Expressions (ShEx) language describing the graph structure. Modules have been developed to serialize the linked data (RDF) and to generate a plain text format files.\n\nConclusionThe main rationale for applying formalized information models is to improve the exchange of information. GBOL uses and extends current ontologies to provide a formal representation of genomic entities, along with their properties and relations. The deliberate integration of data provenance in the ontology enables review of automatically obtained genome annotations at a large scale. The GBOL stack facilitates consistent usage of the ontology.

genomics↗

Diet And Life Stage Associated Remodeling Of Lipid Metabolism Regulation In The Duplicated Atlantic Salmon Genome

Atlantic salmon migrates from rivers to sea to feed, grow and develop gonads before returning to spawn in freshwater. These habitat shifts require great phenotypic plasticity. To address the unresolved question of how the shift in diet between fresh and saltwater affects the regulation of metabolic function, we fed salmon contrasting diets in each of the two life stages. Combining transcriptomics with comparative genomics, we found that lipid metabolism undergoes a concerted shift between fresh- and saltwater stages. Lipogenesis and lipid transport become less active in liver after transition to saltwater, while genes for lipid uptake in gut are more expressed in lipid-rich seawater environments. We assess how the whole-genome duplication that gave rise to the salmonids has impacted the evolution of lipid metabolism, and find signatures of pathway-specific selection pressure on gene duplicates, as well as a limited number of cases of increased gene dosage.

evolutionary biology↗

Functional Analysis of All Salmonid Genomes (FAASG): an international initiative supporting future salmonid research, conservation and aquaculture

We describe an emerging initiative - the Functional Analysis of All Salmonid Genomes (FAASG), which will leverage the extensive trait diversity that has evolved since a whole genome duplication event in the salmonid ancestor, to develop an integrative understanding of the functional genomic basis of phenotypic variation. The outcomes of FAASG will have diverse applications, ranging from improved understanding of genome evolution, through to improving the efficiency and sustainability of aquaculture production, supporting the future of fundamental and applied research in an iconic fish lineage of major societal importance.

genomics↗