Keywords

13.1 Introduction

Aquaculture production has become one of the fastest-growing animal food-producing sectors, contributing significantly to fulfilling the growing need for animal protein by supplying nearly half of all fish and shellfish consumed directly by people. Fish and fishery products provide an average of 35 calories per capita per day in terms of high-quality nutritional sources and readily digested animal proteins, which explains the high consumption (FAO 2020). As a result of its expanding relevance, the aquaculture industry has faced numerous obstacles in producing safe and high-quality fish on a long-term basis. Intensification of aquaculture for meeting the demand, high feed input, water quality deterioration, climate change, poor growth, and disease outbreak could be a major threat in fish culture. The majority of farmed fish is lost each year, resulting in significant economic losses owing to disease outbreaks in diverse culture systems, making farming unprofitable and unsustainable in the long run. Antibiotics and drugs/chemicals used indiscriminately in the culture system frequently cause buildup in the aquatic environment, harm to other creatures, toxicity to the host animal, growth reduction in fish, disruption of the natural reproductive cycle, and financial loss. Residues buildup in fish tissues, posing a health risk to humans who eat the fish. Diverse omics technologies, like genomics, transcriptomics, and proteomics, have been employed to explore the interactional response between different disease-causing agents and fish hosts in recent years. Metabolomics, a new and emerging omics technology, has lately been used to study fish metabolic responses to heavy oil, anoxia, hypoxia, microbial illnesses, pesticides, zero fish meal, and fish oil-based diets. Greater growth rates of farmed species, the higher nutritional content of aquafeeds, improved stock health, and reduced environmental impacts have all been made possible by innovative technology, many of which have been taken from other disciplines. Metabolomics has the potential to be a useful method for identifying and characterizing the metabolomes of any fish or food product. Multiple features of fish can be investigated and biomarkers for their welfare recognized using a metabolomic method, assuring sustainable fish growth and thus the quality and safety of aqua food. Recent metabolomic applications in aquaculture have demonstrated enormous potential for tackling problems across the entire production line, from hatchery production to post-harvest quality control. During the last decade, metabolomics has been implemented in aquaculture with a spectrum of uses in diets and nutrition (Grandiosa et al. 2018, 2020; Huynh et al. 2018), immunology and disease impacts (Nguyen et al. 2019, 2020a, b; Nguyen and Alfaro 2020), environmental stress (Huo et al. 2019; Li et al., 2019; Nguyen and Alfaro 2020), ecotoxicology (Li et al. 2017; Nguyen et al. 2018a), and post-harvest handling (Alfaro et al. 2019; Nguyen et al. 2020a, b).

13.2 Metabolomics

Systems biology is a multidisciplinary method of studying biological processes at the cellular, tissue, and organism levels. The whole genome, transcriptome, proteome, and metabolome are all studied using “omics” technology. Metabolomics is a form of omics that focuses on characterizing, identifying, and quantifying small molecule (<1500 Da) metabolites in the metabolome at high throughput (German et al. 2005). As a result, metabolomics is frequently employed as a sophisticated analytical method to get a deeper understanding of the molecular mechanisms underpinning aquatic creatures’ responses to nutrition, external stresses, infections, and developmental processes. The metabolome is the collection of all tiny molecules, metabolites, or chemicals present in a cell, organ, or organism, according to a formal definition. Tiny molecules include peptides, amino acids, nucleic acids, carbohydrates, organic acids, vitamins, polyphenols, alkaloids, minerals, and just about every other chemical that a cell or organism can use, ingest, or make. Metabolomics identifies biomarkers/chemical signatures indicative of physiological responses of living samples such as whole organisms, tissues, and cells to ambient or culture conditions using unique metabolite profiles. Metabolites provide real-time information on what is going on at the metabolic and physiological levels since they are the most sensitive to environmental changes (Patti et al. 2012). Unexpected issue or risk areas can be recognized using biomarkers, and corrective action can be taken for future management. Though metabolomics in aquaculture is still in its infancy, it has already found widespread application in a variety of fields and applications, including mammalian toxicology, plant chemistry, human nutrition, environmental sciences, food quality, clinical disease diagnostics, and microbial metabolomics, as well as drug discovery. In recent years, metabolomics in aquaculture has become a burgeoning topic, assisting aquaculture in achieving its major goal of increasing production scale while maintaining a high-quality, long-term product. Fish metabolomic study could aid in the investigation of metabolome changes caused by disease, crowding, hypoxia, malnutrition, or other environmental conditions such as pollution, poisons, and temperature fluctuations that might disrupt normal metabolism in the body (Fig. 13.1).

Fig. 13.1
figure 1

‘Omics’ cascade depicts the genotype to phenotype continuum and defines genomics, transcriptomics, proteomics, and metabolomics

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13.2.1 Advantages of Metabolomics over Other Omics Technology

Metabolomics has the following advantages over other omics technologies:

  • Metabolomics is the study of metabolites, which are the end products of biological regulating systems that are extremely vulnerable to outside stimuli. These profiles can be thought of as biological systems’ final response to genetic or environmental change (Fiehn 2002).

  • In comparison with proteome and transcriptome investigations, metabolomics often requires less sample preparation and shorter turnaround times from sample collection to data interpretation, lowering costs.

  • Because metabolites have significantly fewer types/classes than genes or proteins in many species, metabolite data processing is often simpler (Wang et al. 2006; Lu and King 2009).

  • Non-invasive bodily fluids/solids, like plasma and faeces, can be used in metabolomics research, which may be very useful in fish investigations. Furthermore, without destroying a sample, a variety of analytical procedures can be applied (Alfaro and Young 2018). When biological material is restricted and/or several studies are to be performed on a single sample with the goal of data integration, this is particularly valuable.

  • When compared with other “-omic” techniques, metabolomics has several advantages, the most important of which is its biological proximity to the system’s phenotype, allowing for quick detection of system perturbations in the metabolome.

13.3 Basics of Metabolomic Techniques Used in Aquaculture

Metabolomics is a promising method for biomarker discovery since it involves both focused and non-targeted analysis of endogenous and exogenous small-molecule metabolites (<1500 Da). Metabolomics is a global metabolic profiling framework that combines high-resolution analytics (typically NMR and MS) with chemometric statistical tools like principal component analysis (PCA) and partial least squares (PLS) to produce a comprehensive picture of both endogenous and xenobiotic metabolism. Small-molecule biomarkers such as peptides, amino acids, nucleic acids, carbohydrates, organic acids, vitamins, polyphenols, alkaloids, and inorganic substances represent the functional phenotype of a cell, tissue, or organism. The physical and chemical properties of the molecules listed above are extremely diverse, and they exist in a wide concentration range. Technological breakthroughs in metabolomics have enabled the separation and identification of these tiny molecules. These cutting-edge technologies, which include accurate high-resolution MS, NMR, CE, HPLC, and UPLC technology, can detect metabolites in a matter of minutes. A number of analytical systems, including NMR, Fourier transform infrared spectroscopy (FTIR), and MS coupled to separation techniques, such as NMR, GC-MS, LC-MS, FT-MS, and UPLC-MS, have been used for metabolomic applications.

13.4 Sample Collection and Preparation for Metabolomic Study

Because the metabolome can vary extremely quickly in response to slight changes in the environment, extreme caution should be exercised when collecting the sample by limiting biological, technological, and experimental variability. Collected samples must be representative of the biology under study and appropriate for the study’s specific research goals. It’s also crucial to choose the right sample material. Different tissues (e.g., muscle, gills, liver, and pancreas) go through different metabolic processes depending on their role. Even after the metabolome has been taken from the body, it remains in a highly dynamic state in tissues and biological fluids. The ability to accurately measure the metabolome requires the rapid termination of enzyme activity. As a result, metabolic processes within samples must be stopped, or quenched, as quickly as feasible during collection in practically all metabolomic studies. To avoid enzymatic activity recovery, the conventional strategy for quenching metabolism in animal tissues is to freeze samples in liquid nitrogen and store them at or below −80 °C or lyophilize them. The most important aspect of any metabolomic investigation is sample preparation, and sample preparation techniques differ depending on the type of biological material obtained and the analytical platform to be used. Regardless of the method, the metabolite extraction process should be quick and reliable, with as little sample degradation and metabolite alteration as possible (Allwood 2013). For efficient sample extraction, while maintaining the chemical properties of the sample, tissues and cells must be broken down either by grinding in a liquid N2-cooled mortar and pestle (Rosenblum et al. 2005; Viant et al. 2005) or by an electric tissue homogenizer directly in the extraction solvent (Warne et al. 2001; Pears et al. 2005). Methods for metabolite extraction range from simple one-step solvent extraction to more complex approaches requiring multiple phases and/or chemical synthesis steps. Sample preparation and introduction methods for biological samples encompass direct injection, liquid–liquid extraction (LLE), solid-phase extraction (SPE), supercritical fluid extraction, accelerated solvent extraction, microwave-assisted extraction, protein precipitation, and membrane methods such as dialysis or ultracentrifugation. The different types of solvent extraction method include the following:

  1. 1.

    Using a mixture of methanol, water, and chloroform to extract polar and/or nonpolar metabolites.

  2. 2.

    Polar metabolite extraction using methanol alone or in combination with water.

  3. 3.

    Perchloric acid is used to retrieve polar metabolites.

There is no single perfect approach to extract all classes of metabolites with high efficiency due to the enormous range of metabolites found inside tissues, many with widely varying physical and chemical properties. Perchloric acid is commonly used to precipitate proteins and extract hydrophilic metabolites for metabolic fingerprinting research. To extract hydrophilic metabolites, polar organic solvents such as methanol, ethanol, acetonitrile, and acetone are generally combined with water (Coen et al. 2003; Kim et al. 2004; Stentiford et al. 2005a). Hydrophobic metabolites can be extracted using chloroform (Choi et al. 2004; Stentiford et al. 2005b).

13.5 Analytical Tools for Measuring Metabolomes

There is currently no one adaptable platform that can analyze all metabolites inside a sample due to the complexity of metabolites and the high number of metabolites present. Depending on the aims and scope of the investigation, the type of sample material collected, the available sample mass, the accessibility of analytical platforms, and the cost involved, multiple techniques may need to be selected and used to partially overcome the shortcomings of single-analysis techniques. Nuclear magnetic resonance (NMR), mass spectrometry (MS), Fourier transform-infrared spectroscopy (FTIR), and MS coupled to separation techniques, such as NMR, GC-MS, LC-MS, FT-MS, and UPLC-MS, are the most often used high-throughput and high-resolution systems for metabolomics studies. While NMR spectroscopy is best for analyzing bulk metabolites and GC-MS is best for analyzing volatile organic compounds and derivatized primary metabolites, LC-MS can be used to analyze a wide range of semipolar molecules, including many secondary metabolites of interest. LC-MS is a popular instrument because it avoids chemical derivatization. For the identification and quantification of metabolites, MS-based metabolomics offers great selectivity and sensitivity, and when combined with improved and high-throughput separation techniques, the complexity of metabolite separation can be reduced. MS-based approaches, on the other hand, necessitate a sample preparation phase that can result in metabolite loss. To examine the global metabolome, it is ideal to use various techniques at the same time, such as GC-MS, LC-MS, or NMR.

13.6 Nuclear Magnetic Resonance (NMR)

Nuclear magnetic resonance (NMR) is a spectroscopic analytical technique that can uniquely identify and quantify a wide range of organic substances in the micromolar range. It identifies atomic nuclei’s distinctive spin characteristics. When nuclei with specific magnetic properties are submerged in a magnetic field, they align with (low energy state) or against (high energy state) the field. The application of extremely particular radio frequency pulses to the nuclei causes a “spin flip,” which is a change in the energy state (Savorani et al. 2013). Nuclear shielding is a tiny change in the intensity of the applied magnetic field caused by the existence of other nuclei and chemical bonds surrounding a nucleus. A chemical shift occurs when nuclei within a metabolite absorb radiation at slightly different frequencies as a result of this shielding. The sample’s distinct spectrum or “fingerprint” is created by combining all of these various frequencies. Furthermore, more sophisticated spin interactions under varied pulse settings can reveal a wealth of information about a molecule’s chemical bonding and composition. NMR’s main benefit is that it is largely automated and nondestructive, allowing samples to be used for further research while also providing extremely reliable and repeatable readings. Separation of metabolites before detection is not required, and just a minimal amount of sample preparation is required, saving both money and time. Metabolite fingerprinting, profiling, and metabolic flux analysis have all been done with it. The limited sensitivity of NMR makes it unsuitable for the investigation of large numbers of low-abundance metabolites, which is a fundamental restriction for comprehensive metabolite profiling. NMR can be particularly valuable in drug discovery and development since it offers extensive information about a compound’s structural alteration as a result of metabolism.

13.7 Mass Spectrometry

Mass spectrometry (MS) is a technique for determining the molecular weights of compounds. Molecules in a test sample are transformed into gaseous ions, which are then separated and identified in a mass spectrometer based on their mass-to-charge (m/z) ratio. The mass spectrum is a graph showing the ions’ (relative) abundances at different m/z ratios. The ion source, mass analyzer, and detector are the three parts of a mass spectrometer (Glish and Vachet 2003). Different steps involved in all mass spectrometers include:

  1. 1.

    Production of ions in the gas phase.

  2. 2.

    Acceleration of the ions to a specific velocity in an electric field.

  3. 3.

    Separation of the ions in a mass analyzer.

  4. 4.

    Detection of each species of a particular m/z ratio.

Electron ionization and electrospray ionization are the most often utilized ionization procedures in metabolomics research (Lei et al. 2011). MS can be used to analyze biological materials either directly without prior metabolite separation or after chromatographic separation. Direct MS techniques are quick; however, they have low ionization efficiency and ion suppression. MS-based metabolomic techniques often require the separation of metabolites by chromatography or electrophoresis before MS detection to reduce the complexity of the sample matrix and improve the sensitivity and selectivity of the analysis. The most often used procedures for this purpose are gas chromatography (GC), liquid chromatography (LC), and capillary electrophoresis (CE). These instruments are referred to as hyphenated platforms when they are used together (GC-MS, LC-MS, and CE-MS). MS approaches can have exceptionally high sensitivity or at least detection limits.

13.8 Fourier Transform Infrared (FTIR)

The vibrational fingerprints of wide metabolite functional groups can be measured using Fourier transform-infrared (FTIR) spectroscopy, a type of vibrational spectroscopy that uses lower resolution devices (Moore et al. 2014). In metabolic fingerprinting and metabolomics research, FTIR is a typical analytical tool. Because distinct absorption bands may be ascribed to individual molecular bonds, FTIR spectra can be used as a fingerprint to offer extensive information on the chemical structure and composition of substances. Infrared radiation is transmitted through a sample in IR spectroscopy. The sample absorbs some of the IR radiation, and some of it passes through (transmitted). The resulting spectrum depicts the sample’s molecule absorption and transmission, resulting in a molecular fingerprint. The FTIR technique is faster than other procedures, requires a small sample size with minimal or no preparation, does not require the use of solvents, and is more cost-effective.

13.9 Applications of Metabolomics in Nutritional Management

Aquaculture confronts a daunting task in improving feed appropriateness and supporting global fish production growth. Aquaculture, as a burgeoning animal protein-producing business, must evolve dramatically to improve its reliability to meet world demand for fish, while catch fisheries production has nearly stagnated in recent decades (FAO 2020). Because of its well-balanced nutrients and high digestible proteins, high-quality fish meal (FM) is used as a primary nutritional ingredient in the majority of cultured fish. Overreliance on fishmeal (FM) in aquafeed formulations, on the other hand, is seen as one of the primary impediments to the aquaculture sector’s long-term viability, due to supply shortages and price disparities (Van Vo et al. 2015). As a result, aquaculture nutritionists around the world are working hard to identify nutritionally adequate and sustainable alternatives to fishmeal (FM) for fish feed formulation. As a result, feed components derived from terrestrial crops have been thoroughly investigated as FM alternatives (Hardy 2010). As a result, aquaculture must compete for terrestrial feedstuff with cattle, the fuel industry, and direct human consumption, raising concerns about aqua farming’s impact on world food security (Troell et al. 2014). Furthermore, greater levels of plant protein sources in the diet resulted in growth retardation, lowered immunity, altered intestinal architecture, and oxidative stress (Ng et al. 2019; Xu et al. 2016). Some supplements/functional additives are used in the feed mix to address this issue. By interfering with digestion and intestinal function, added nutrients should not harm fish growth and physiology (Krogdahl et al. 2015). As a result, precise characterization of alternative feed ingredients/supplements is required to fully comprehend their impact on fish metabolism and suitability for optimal growth and immunity. The traditional method of evaluating new feed formulations is first determining the analytical composition and digestibility of the feed, followed by examining its impact on fish growth, feed consumption, and other zootechnical characteristics. However, while these traditional approaches are useful for demonstrating the major impact of feedstuffs and feed on fish growth, they may be insufficient for understanding the influence of feeds on fish metabolism and the mechanisms that underpin it. At the level of genes, transcripts, proteins, and metabolites, omics technologies allow a novel holistic view of a biological system. Nutrigenomic techniques, which study the relationship between nutrients and specific gene expression, have grown in importance in recent years, leading to novel discoveries such as the regulation of genes involved in protein, lipid, and carbohydrate metabolism in fish that have given plant-based diets (Panserat et al. 2009a, b; Geay et al. 2011). Nutrigenomics, on the other hand, has the same limitations as transcriptome methods. What happens is partly unknown because post-transcriptional changes and protein functions are not explored. Proteomics has been utilized to better understand the molecular pathways that fish use to respond to external stimuli, such as nutritional supplements, and these discoveries can be utilized to improve feed formulation and optimization. Metabolomics, on the other hand, focuses on a global set of metabolites within the biological system and provides data on metabolic activities. By combining a feeding trial with metabolomic investigations of tissues and biofluids, new insights into feed and nutrient effects could be gained. Metabolomics was utilized as a system biology approach to investigate the effects of dietary nutrients on fish growth by comparing the metabolite profiles of various tissues from different dietary regimens (Schock et al. 2012a, b; Abro et al. 2014a, b; Wagner et al. 2014a, b). Metabolomics can be used to figure out how a particular diet affects fish physiology. It aids in the selection of the appropriate feeds for optimal growth, based on their compatibility with fish metabolism, to maintain a positive link between product quality and feed conversion efficiency. Metabolomics is intended specifically to analyze metabolic reactions to nutritional deficits or excesses, and it may provide in-depth mechanistic insights to help build optimal feeding regimens (Table 13.1).

Table 13.1 Applications of metabolomics in different aspect of fish nutrition
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13.10 Metabolomics in the Management of Fish Health

Fish health is an important part of aquaculture welfare that is influenced by any negative changes in the environment, such as stress and sickness caused by pathogen infection (Segner et al. 2012; FAO 2016). Disease management is also a significant concern for long-term aquaculture operations. Metabolomics has shown great promise in better understanding disease susceptibility and host-pathogen interactions (Solanky et al. 2005; Guo et al. 2014; Ma et al. 2015; Peng et al. 2015), disease characterization (Stentiford et al. 2005a, b; Southam et al. 2008), and treatment efficacy determination (Cheng et al. 2016; Su et al. 2014). The host’s energy metabolism, osmotic control, oxidative stress, cell signalling pathways, and respiratory processes are all affected by pathogen exposure. A changed metabolic profile can be utilized to determine an organism’s health condition and can aid in understanding pathogenesis and immune response. Metabolomics has been applied comprehensively in several aspects of health management, including the metabolic response of shrimp to pathogen invasion (Wu et al. 2017a, b; Ning et al. 2019), toxicity and environmental stress (Li et al. 2017; Chen et al. 2019; Xiao et al. 2019), and super-intensive grow-out conditions (Schock et al. 2013). The hepatopancreas of white leg shrimp L. vannamei infected with the microsporidian Enterocytozoon hepatopenaei (EHP) revealed downregulation of that energy metabolism pathway, according to a study (Ning et al. 2019). In the EHP-infected groups, 49 unique metabolites were discovered, which could be employed as a biomarker to distinguish between EHP-challenged and healthy groups. Nguyen et al. (2021) looked at the metabolic responses of penaeid shrimp to Vibrio parahaemolyticus caused acute hepatopancreatic necrosis disease (AHPND). GC-MS was used to produce the hemolymph metabolome of Penaeus vannamei challenged with V. parahaemolyticus and control shrimp (not exposed to the pathogens). The examination of the pathways revealed Infection with V. parahaemolyticus produces major changes in amino acid metabolism, the TCA cycle, and gluconeogenesis pathways, as well as their intermediates. TCA cycle intermediates such as cis-aconitic acid, citric acid, fumaric acid, isocitric acid, and succinic acid were found to be upregulated, which is generally associated with a high metabolic rate, higher energy demand, and an immunological response (Nguyen et al. 2018b, c, 2018b, c; Song et al. 2019). Increased glucose, which may be used as an energy source to maintain immunological response, was seen in the hepatopancreas of Litopenaeus vannamei infected with WSSV and aberrant amino acid and fatty acid metabolism (Wu et al. 2017a, b). Solanky et al. (2005) compared the metabolite profiles of plasma collected from Atlantic salmon challenged with virulent A. salmonicida to saline-injected and unfed control groups using NMR-based metabolomics. Different NMR spectra (metabolite profiles) were detected for each of these groups, and distinct metabolites were found. For the identification of infected and noninfected persons, a metabolomic-based technique can be developed. In a minimal-exchange, superintensive, and biofloc system, Schock et al. (2013) used NMR-based metabolomic approaches to evaluate the condition of shrimp health throughout the whole production cycle, from the nursery phase through harvest. Tissue-specific metabolic alterations were discovered, primarily in the areas of energy metabolism and nitrogen detoxification. Guo et al. (2014) employed a GC/MS-based metabolomic technique to find biomarkers that differentiated life from death in crucian carps infected with Edwardsiella tarda. The most important metabolites distinguishing survival from death in these E. tarda infected fish were increased unsaturated fatty acid production, particularly palmitic acid, and decreased fructose and mannose metabolism, particularly D-mannose. The metabolic pathways linked to antibiotic resistance have been widely studied using metabolomics (Jiang et al. 2019; Liu et al. 2019; Zhang et al. 2019; Li et al. 2020).

13.11 Conclusion

Metabolomics is a powerful, new science with a lot of potential in aquaculture because it provides a global view of metabolism by identifying many metabolites involved in biological responses of organisms exposed to various circumstances like nutrition, environment, and disease. An improved understanding of metabolic pathway variation aids in the identification of biomarkers and the development of effective nutritional and health management methods that support optimum growth and long-term aquaculture output.