Combinatorial metabolomic and transcriptomic analysis of muscle growth in hybrid striped bass (female white bass Morone chrysops x male striped bass M. saxatilis)

Authors: RAJAB, SARAH - North Carolina State University; Andersen, Linnea; KENTER, LINAS - University Of New Hampshire; BERLINSKY, DAVID - University Of New Hampshire; BORSKI, RUSSELL - North Carolina State University; MCGINTY, ANDREW - North Carolina State University; ASHWELL, CHRISTOPHER - North Carolina State University; FERKET, PETER - North Carolina State University; DANIELS, HARRY - North Carolina State University; READING, BENJAMIN - North Carolina State University

Submitted to: BMC Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/19/2024
Publication Date: 6/10/2024
Citation: Rajab, S., Andersen, L.K., Kenter, L.W., Berlinsky, D.L., Borski, R.J., Mcginty, A.S., Ashwell, C.M., Ferket, P.R., Daniels, H.V., Reading, B.J. 2024. Combinatorial metabolomic and transcriptomic analysis of muscle growth in hybrid striped bass (female white bass Morone chrysops x male striped bass M. saxatilis). BMC Genomics. 25:580. https://doi.org/10.1186/s12864-024-10325-y.
DOI: https://doi.org/10.1186/s12864-024-10325-y

Interpretive Summary: Hybrid striped bass (cross between female white bass, Morone chrysops, and male striped bass, M. saxatilis) are an important aquaculture product in the United States (4th largest by farm gate value) and other countries around the world. Understanding the cellular functions that regulate their growth is important for successful breeding of an animal with agriculturally-important traits, such as reaching market size in less time. Examining the genes that regulate growth and other cellular processes (gene transcripts, transcriptomics) and the molecules present in cell as a result of the genes (metabolites, metabolomics) are two approaches to gaining this insight, as was done here. Specifically, white muscle tissue gene expression and liver metabolites of hybrid striped bass that grow well (top 10% of population) and grow poorly (bottom 10% of population) were measured and analyzed, as these tissues are the primary market product (the fillet) and site of metabolism coordination, respectively. The combination of the two allowed for the identification of cellular processes that contribute to the observation of different growth rates within a population of hybrid striped bass, including a higher number of muscle fibers smaller in diameter in the fish that grow well and indicators of muscle inflammation and stress in the fish that grow poorly. This work identified important biomarkers that can be examined in these fish, their parental species, and other organisms for breeding efforts, as well as in the context of animal physiology generally.

Technical Abstract: Background: Understanding growth regulatory pathways is important in aquaculture, fisheries, and vertebrate physiology generally. Machine learning pattern recognition and sensitivity analysis were employed to examine metabolomic small molecule profiles and transcriptomic gene expression data generated from liver and white skeletal muscle of hybrid striped bass (white bass Morone chrysops x striped bass M. saxatilis) representative of the top and bottom 10 % by body size of a production cohort. Results: Larger fish (good-growth) had significantly greater weight, total length, hepatosomatic index, and specific growth rate compared to smaller fish (poor-growth) and also had significantly more muscle fibers of smaller diameter (= 20 µm diameter), indicating active hyperplasia. Metabolomic differences included enhanced energetics (glycolysis, citric acid cycle) and amino acid metabolism in good-growth fish, and enhanced stress, muscle inflammation (cortisol, eicosanoids) and dysfunctional liver cholesterol metabolism in poor-growth fish. Gene transcripts that were down-regulated in good-growth fish were generally those identified as being differentially expressed between groups. Several molecules with important growth regulatory functions were up-regulated in muscle of fish that grew poorly: growth factors including agt and agtr2 (angiotensins), nicotinic acid (which stimulates growth hormone production), gadd45b, rgl1, zfp36, cebpb, and hmgb1; insulin-like growth factor signaling (igfbp1 and igf1); cytokine signaling (socs3, cxcr4); cell signaling (rgs13, rundc3a), and differentiation (rhou, mmp17, cd22, msi1); mitochondrial uncoupling proteins (ucp3, ucp2); and regulators of lipid metabolism (apoa1, ldlr). Growth factors pttg1, egfr, myc, notch1, and sirt1 were notably up-regulated in muscle of good-growing fish. Conclusion: A combinatorial pathway analysis using metabolomic and transcriptomic data collectively suggested promotion of cell signaling, proliferation, and differentiation in muscle of good-growth fish, whereas muscle inflammation and apoptosis was observed in poor-growth fish, along with elevated cortisol (an anti-inflammatory hormone), perhaps related to muscle wasting, hypertrophy, and inferior growth. These findings provide important biomarkers and mechanisms by which growth is regulated in fishes and other vertebrates as well.