Exploring potential biomarkers in foods of animal origin

Abstract

Biomarkers are important tools in almost every biological field, serving as means of understanding biological conditions, responses or processes. Although, applicability and importance of biomarkers in medicine and food are extensively studied and reported in literature, this review will emphasize on biomarkers associated with food and foods of animal origin like meat, fish, milk and egg. Evaluation of quality, safety and adulteration of food commodities is of the utmost importance with the ever-increasing global demand. As meat is the most nutrient rich and demanded commodity, emphasis on meat quality and safety biomarkers is elaborately discussed, highlighting well known biomarkers for sensory attributes of meat like tenderness affected by certain structural proteins and proteolytic enzymes, colour stability determined by myoglobin chemistry and antioxidant activity, volatile chemicals, amino acids, and fatty acids determining flavour, texture and juiciness controlled by intramuscular fat and water-holding capacity etc. Moreover, consumer satisfaction goes hand in hand with attributes like safety, traceability and adulteration of meat, which are also assessed using biomarkers that comprehensively contribute in determining the overall quality of the meat. The meat industry is able to improve product consistency, safety and consumer appeal through these precision-based techniques and biomarkers. This review categorises these biomarkers as chemical and biological in nature, with certain biomarkers overlapping between the categories with respect to its composition, origin and detectability. Additionally, the review highlights the techniques for detecting the biomarkers in conventional and advanced settings starting from basic biochemical methods to advanced techniques.

Introduction

Biomarkers are quantifiable biological substances that offer important insights into environmental, pathogenic or physiological processes. They are used in food science, toxicology and medicine as diagnostic, prognostic and predictive methods. These compounds can reveal information about disease states, exposure to toxins, food quality, species authenticity and even adulteration detection. There are numerous biomarkers used extensively in food sector for ensuring nutritional quality, safety and authenticity. Moreover, in response to increasing concerns about food fraud, mislabelling, and contamination, the use of biomarkers in food analysis has become more prevalent (Bekhit et al. 2019). Foods of animal origin, particularly meat, fish, eggs and dairy are more vulnerable to fraudulent activities among other food categories because of their high economic importance and intricate supply systems. Significant progress has been achieved in finding such biomarkers for foods of animal origin, especially in meat, fish, eggs, and milk during the last decade, promoting safety, quality control and authentication. Apart from chemical biomarkers for detecting and quantifying residues of pesticides, food colours and food additives, there are biological biomarkers as well that are derived from proteins, metabolites, DNA or RNA, that can be used for precise identification of species, evaluate freshness, find allergens and detect food spoilage. The classification of biomarkers according their nature of origin and their respective functions are depicted in Fig. 1. It shows a significant overlapping between biological and chemical biomarkers as certain biomarkers can result from either chemical exposure as well as biological responses. Nucleic acids for instance can provide various information and act as indicators of species identity, stress responses and spoilage. As degradation patterns are predictable, RNA biomarkers, which are generated from genes in the DNA and include mitochondrial 12S rRNA, 16S rRNA and cytochrome c oxidase subunit I (COI) mRNA, act as indicators of species identity, stress responses and spoilage. On the other hand, DNA-based biomarkers such as 12S rRNA gene or cytochrome b are stable genomic sequences that are utilized for species identification using PCR (Bello et al. 2021). COI and cytb gene-based DNA barcoding in fish and seafood has been enhanced for better species discrimination, particularly in combating mislabelling. Such DNA-based markers are although still essential for identifying species in meat, but because of their dynamic degradation patterns, RNA biomarkers are being utilized more and more to evaluate freshness and processing conditions. MiR-1, miR-133a and miR-206 are examples of novel microRNAs (miRNAs) that have become more stable, muscle-specific markers which can differentiate across species, even in processed meats (Rodríguez et al. 2004). Evidently, there exists biomarkers which can determine different aspects of a food commodity, from its species of origin, to its adulteration safety as well as quality and spoilage. Protein biomarkers are another class of such biomarkers that are used extensively in food quality assessments. Some examples include lactoferrin, used for detection of milk authenticity, parvalbumin, used for detection of fish allergens etc. Similarly, peptide biomarkers from myosin and actin, discovered using LC–MS provide species authentication even in cooked food. Such proteomic techniques have identified myoglobin isoforms and troponin breakdown products as indications of meat softness and oxidation as well (Dal Bello et al. 2021). Peptide markers like collagen and myosin assist in authenticating processed seafood. The glycosylation patterns of egg white proteins aid in the differentiation of different bird species. Milk adulteration with plant proteins can be recognized by proteomic biomarkers, such as β-lactoglobulin and α-lactalbumin variations, and heat-treated dairy products are identified by peptide profiling. Moving on to metabolite biomarkers such as hypoxanthine, that is used for meat freshness assessments, biogenic amines used for spoilage etc. These metabolites indicate biochemical changes and are extensively used in determining quality of meat and other food products. Similarly, real-time spoilage assessment is provided by metabolite indicators such hypoxanthine, inosine, trimethylamine oxide (TMAO) etc. and some volatile organic compounds (VOCs), that are metabolites involved in important pathways, help us determine the quality by comparison to its standard or control levels. There exist certain advanced biosensors nowadays that allow for quick on-site detection of such metabolites as well, which does not require detailed metabolite profiling. There are also some biogenic amines, such as cadaverine and histamine, that indicate microbial spoilage. Fatty acid profiles and lactose degradation products are also examples of metabolite markers that evaluate freshness and processing impacts.

Fig. 1.

Classification of chemical and biological biomarkers according their nature of origin and functions

Future prospects for animal-origin food biomarkers includes multi-omics integration, which integrates proteomics, metabolomics, transcriptomics and genomics to provide comprehensive and holistic approach to food profiling. Rapid on-site authentication will be made possible by portable biosensors and CRISPR-based detection systems, and AI-driven biomarker discovery will speed up the process of finding new markers in big datasets. Biomarkers originating from extracellular vesicles (EVs), such as proteins and miRNAs, have potential for non-destructive testing, and sensors based on nanomaterials may transform real-time spoilage monitoring (Nimse et al. 2016). Additionally, by connecting biomarker data to supply chain records, blockchain technology may improve traceability. As food fraud becomes increasingly intricate, these developments will be essential to maintaining food safety, authenticity and consumer confidence in products with animal origins worldwide. This review will highlight such biomarkers that are extensively used in food industry to determine quality, safety and consumer protection from fraudulent adulterations, while also trying to map out the different intersecting categories of biomarkers for better clarity on its usage and applications.

Biomarkers of food safety and quality control

Biomarkers act as powerful tool in food industry by serving as indicators for detecting various aspects of food like quality, safety, nutritional value and authenticity. Biomarkers have enabled the detection of pathogens such as viruses, bacteria etc. by offering prevention from foodborne illness and contaminants (Lolli et al. 2020), while also establishing the transparency and trust in the food supply chain by ensuring the authenticity by verification of nutritional content and by the detection of adulterants. Food manufacturers can take maximum benefits by optimizing their production process, making products with cost effectiveness and specific health benefits. The regulatory bodies can safeguard public health and promote a more sustainable food system by effectively enforcing food regulations and standards by using food biomarkers. The overall impact of biomarkers in food industry is profound and can bring improvements in food safety, innovation and quality. The food biomarkers can be classified into chemical biomarkers and biological biomarkers.

Chemical biomarkers

Chemical biomarkers are the molecules that indicates the presence of specific chemicals in the food. These biomarkers can be used to detect food contaminants such as pesticides, heavy metals, mycotoxins, food additives such as preservatives, artificial colours, flavour enhancers and nutrients including vitamins, minerals, and fatty acids. Chemical biomarkers can be of targeted and non-targeted types. Targeted chemical biomarkers are specific molecules, the presence of which indicates the presence of particular contaminant or nutrient whereas non-targeted ones are the molecules that indicate a class of compounds or specific metabolic Bello pathways (et al. 2021). Chemical biomarkers can be detected by chromatography as well as spectroscopy, and are rapid and highly sensitive to detection even in trace amount of compound (Lolli et al. 2020). But it has some limitations such as cost intensive detection, interference of other compounds and complexity of food matrices etc.

Biological biomarkers

Biological markers of food are biological molecules that indicate the presence of specific molecules or classes of compounds in the food. These biomarkers are used to detect pathogens and spoilage microorganisms such as bacteria, parasites, viruses etc., food allergens such as gluten, lactose etc. and are also used to authenticate the food products such as species identification etc. Biological biomarkers can be classified as protein biomarkers, metabolic biomarkers, DNA biomarkers and RNA biomarkers (Lolli et al. 2020). Protein biomarkers are the specific proteins present in food indicating the presence of food allergens such as casein (milk protein), gelatin (meat and bone collagen protein), ovalbumin (egg white protein), Ara h 1 (peanut protein), soy protein (soya bean protein) or pathogens such as bacterial proteins (toxins, adhesins, virulence factors etc.), viral proteins like structural proteins (envelope proteins of Ebola, HIV), non-structural proteins (Polymerase protein in influenza), immunoevasins (Herpis simplex virus ICP47), parasitic proteins like surface antigens (Plasmodium falciparum circumsporozoite protein of malaria) etc. (Bello et al. 2021). Food spoilage microbes like bacteria, yeast and mold releases various metabolites affecting food safety, quality and shelf-life (Lolli et al. 2020). These metabolites include VOCs like ethanol, acetic acid, aldehydes which induces off flavors, odors and leads to spoilage. Non-volatile metabolites like lactic acid, succinic acid induces texture changes, sliminess and sourness in food. Toxins like aflatoxin, botulinum toxin produced by bacteria and molds can even be fatal for consumers. Enzymes like proteases, amylases, lypases produced by bacteria or molds can lead to food quality and texture changes due to breaking down of food components and exopolysaccharides (Pessione et al. 2016).

DNA biomarkers are the specific genetic sequences that can help in authentication of food products, detect foodborne pathogens and monitor quality of food. DNA biomarkers can be derived from various sources such as mitochondrial DNA, nuclear DNA of animal derived foods, chloroplast DNA and nuclear DNA of plant-derived foods and DNA of microorganisms (Lolli et al. 2020). DNA biomarkers are of different types such as species specific DNA biomarkers which are used to identify the species of origin in case of adulterated meat and meat products, genotype specific DNA biomarkers which are used to distinguish between the breeds of a particular species, pathogen specific DNA biomarkers which are used for detection of particular pathogens in food and quantitative DNA biomarkers which can measure the amount of specific DNA sequences in food to identify food authenticity. The DNA biomarkers have their application in food authentication which can prevent adulteration and mislabeling, provides food safety and evaluate quality by identifying the pathogenic microorganism in food, identifying contamination and spoilage and in maintaining the traceability of the food products in the supply chain by ensuring transparency and accountability (Pessione et al. 2016). DNA biomarkers can be identified by using techniques such as PCR, real-time PCR, microarray, DNA sequencing etc.

RNA biomarkers on the other hand have evolved into powerful tools for validating and assessing the quality of animal derived foods (Münger et al. 2018). Due to their high copy number and stability, mitochondrial RNA markers like 12S rRNA and 16S rRNA are frequently used to identify species in meat, while myostatin mRNA aids in assessing muscle growth and meat tenderness (Girish et al. 2004). In cooked meat, microRNAs such as miR-1 and miR-206 function as tissue-specific, persistent biomarkers that allow for species separation and evaluation of heat treatment (Fabre et al. 2014). Ovalbumin and ovomucoid mRNA confirm the use of egg-derived ingredients in processed foods, whereas vitellogenin mRNA indicates the nutritional value of eggs and the health of hens (Mukae et al. 2021). Casein (CSN1S1, CSN2, and CSN3) and lactoferrin mRNAs in milk authenticate sources and identify adulteration (Rani et al. 2020). miR-21 and miR-148a in milk exosomes show the stage of lactation and the health of the udder (Rani et al. 2020). The uses of RNA biomarkers in quality control, fraud prevention and food safety demonstrate its increasing significance in the food sector, as new RNA markers are being investigated for increased accuracy and dependability (Münger et al. 2018). Muscle-specific mRNAs like myogenin and myosin heavy chain degrade significantly within 72 h post-mortem at 4 °C (Kuang et al. 2014).

Nutritional biomarkers are the indicators of the nutritional status, nutrient absorption and dietary exposure of an individual. Nutritional biomarker provides valuable insights into the health and wellbeing of individuals and provides nutritional recommendations. They are divided into different types such as exposure biomarkers which measures the dietary intake such the intake of carbohydrate, fats, protein, vitamins etc. (Picó et al. 2019). Nutrient biomarkers are of different types such as vitamin biomarkers which can measure the vitamin levels in the body such as the vitamin D levels indicates the bone health, vitamin K level indicates the blood coagulation process, vitamin B12 levels indicates the health of RBC formed. Mineral biomarkers measure the mineral levels of the body such as level of iron in blood indicates the hemoglobin level in the blood and calcium level in the body indicates the bone health of an individual (Gorokhova et al. 2005). Glycemic biomarker which measures the insulin sensitivity and blood sugar control. Fatty acid biomarker indicates the fatty acid profile of the body and fat intake by the individual. The advantage of nutritional biomarkers includes personalized nutrition, as personalized nutrition can be provided to the patients with dietary diseases. It can help in preventing diseases by identifying individuals at risk for dietary diseases (Pessione et al. 2016). Limitations of nutritional biomarker are their variability as the level of biomarkers can vary due to factors like age, sex etc. and some biomarker detection methods are costly.

Biomarkers of animal origin foods

Animal origin food biomarkers are biological molecules which are used to identify the source of food, feed or other products derived from animals. These biomarkers may consist of proteins, DNA or substances that are particular to one or more species (Ye et al. 2023). Scientists can ensure compliance with standards, including halal or kosher certification and prevent adulteration or contamination by evaluating these biomarkers to identify the presence of components produced from animals. Furthermore, animal origin biomarkers aid in the tracking of food products, facilitating the surveillance of supply chains and the verification of product labelling, all of which contribute to increased transparency and customer confidence.

Biomarkers in milk

Milk has a wide range of bioactive substances and the biomarkers it contains change based on the species, processing method, stage of fermentation and storage. Fresh milk key biomarkers such as lactose, β-lactoglobulin, α-lactalbumin (whey protein), where casein fractions are core proteins and are used for detection of milk quality (Heirbaut et al. 2023). Similarly, calcium, phosphorus, magnesium levels in milk reflects bioavailability and daily mineral intake by the animal and immunoglobulins such as IgG, IgA specially found in colostrum and raw milk are identified as immune health biomarkers (Hurley et al. 2011). Fermented milk products such as yoghurt, kefir, buttermilk, fermented cheese etc. contains biomarkers, for example, short-chain fatty acids such as acetate, butyrate, propionate etc. have been identified as gut health markers which are produced when gut bacteria ferment dietary fibres that are not absorbed in the small intestine, such as polysaccharides and resistant starch (Shawky et al. 2024). Other Biomarkers found in the fermented milk products are lactate, pyruvate, ile-pro-pro (IPP), val-pro-pro (VPP) derived from casein and are associated with antihypertensive effects and the exopolysaccharides produced by lactic acid bacteria in milk which provides insights into the milk quality and bacterial health (Antanaitis et al. 2021). Milk products such as powdered milk, condensed milk, ice-cream, paneer, khoya etc. contains lactulose which helps in the identification of ultra-high temperature processing, oxidized lipids in milk, i. e. aldehydes, conjugated dienes which is an indicators of fat degradation during storage and the ripening and microbial activity in cheese can be identified by tyrosine breakdown products like tyramine, phenylethylamine etc. (Schuster-Wolff-Bühring et al. 2011). Species specific milk biomarkers includes species-specific caseins (αs1-casein, β-casein variants). Fatty acid profiles in milk can also help in identifying the species, for instance, goat milk is rich in medium-chain triglycerides (MCTs) and camel milk has unique antimicrobial peptides.

Biomarkers in egg

The biomarker profiles of the proteins, lipids, vitamins, and antioxidant chemicals in eggs are influenced by processing and heat treatment, which also affects the nutritional contents of the egg. Fresh egg biomarkers contain Ovalbumin, ovotransferrin, ovomucin, lysozyme which are the key proteins that serves as intake markers and freshness indicators, whereas choline and phosphatidylcholine serves as the biomarkers for neuroprotection and lipid metabolism, lutein and zeaxanthin are the xanthophylls that are identified as biomarkers linked to yolk quality and biotin, riboflavin are the B-complex vitamins found in high-quality fresh eggs (Zhao et al. 2016). Boiled and thermally processed eggs contains a different range of biomarkers that includes, lysinoalanine a heat-induced marker formed from lysine-asparagine reactions, especially in overcooked eggs, advanced glycation end products are the egg biomarkers that increases with high heat and are also the biomarkers of oxidation and chronic disease risk whereas protein carbonyls are the oxidative stress markers of egg which increases with cooking intensity. Egg powders that have been lyophilized (freeze-dried) provide a variety of biomarkers for evaluating their nutritional content and quality (Yogeswari et al. 2024). Lipid oxidation in eggs can be assessed by malondialdehyde and hydroxy alkenal and oleic, palmitic, linoleic acids can help in the identification of retention of fatty acid profile of the lyophilized eggs (Rivas-Hernández et al. 2024).

Biomarkers in fish

The biomarker profiles of fish differ greatly depending on their species, habitat and processing. Biomarkers for freshwater fish serve as indicators of the health by reflecting their exposure to environmental changes and contaminants. These biomarkers can act as early warning systems for pollution and offer information about the quality of the water. Freshwater fish biomarker includes arachidonic acid (AA) which is higher in freshwater fish species like tilapia and carp, linoleic acid (LA) which gets elevated due to grain-based aquafeeds, alanine, glycine that are the amino acids reflecting freshwater metabolic profiles of fishes (De la Torre et al. 2007). Saltwater fish biomarkers are quantifiable measures of its wellbeing and health, including the way it reacts to pollutants and stresses in its environment, for instance, eicosapentaenoic acid, docosahexaenoic acid (DHA) and trimethylamine N-oxide which are key markers for the detection of marine fish like salmon, tuna, and mackerel, squalene and selenoneine that are the antioxidant compounds especially found in deep-sea fish species, taurine is abundant in marine fish and can be identified as a biomarker and has cardiovascular and metabolic implications (Copat et al. 2020). Shellfish biomarkers are quantifiable markers of biological states and processes in shellfish that reveal information about their health, exposure to pollutants in the environment, and the impact of different stressors (Abdallah et al. 2024). Chitin and glucosamine are structural polysaccharides which are shell-derived biomarkers that gives shells its rigidity. Glycine-betaine, taurine, arginine found in shellfish and serves as osmolytes and amino acids specific to shellfish.

Biomarkers of meat

Meat biomarkers are the specific molecules present in meat and meat products such as proteins, nucleic acid sequences etc. These biomarkers can be used to authenticate meat and meat products. Verify the authenticity to ensure that the meat or the product belongs to the declared meat species and also the quality assurance to detect the freshness or spoilage of the meat and meat products. These biomarkers can be proteins, DNA, RNA or metabolic in nature (Fig. 2).

Fig. 2.

Graphical representation of different categories of biomarkers in meat

Biomarkers for animal species detection

Haemoglobin (Hb)

Haemoglobin is the protein present in RBC that helps in transportation of oxygen from lungs to tissues. Haemoglobin is used as biomarker for the detection of meat species as it has distinct peptide profiles for different animal species. For example, bovine haemoglobin is used to detect beef in meat products (Buehler et al. 2013). Similarly, identification of porcine, chicken and salmon haemoglobin are used to detect pork, chicken and salmon in meat products respectively. (Fossi et al. 1994). The haemoglobin biomarker can be detected by ELISA or western blotting techniques.

Myoglobin

Myoglobin is a muscle protein found in tissue and can be treated as biomarker for meat species detection as it has distinct peptide profiles for different animal species. Myoglobin from lamb and venison (deer meat) can be differentiated from other species due to its unique peptide sequences (Buehler et al. 2013). Myoglobin is also used for adulteration detection in meat products as studies says that it can detect horse meat in beef (Fossi et al. 1994). The Mb can be extracted and detected using ELISA (Enzyme-Linked Immunosorbent Assay) or Western blotting. This biomarker is highly specific and sensitive, allowing for the detection of trace amounts of adulteration in meat products.

Actin: Actin is a highly conserved cytoskeletal protein and a promising meat specificity biomarker because for its tissue-specific expression patterns and isoforms. Different meats, including beef, pork, chicken, and fish, express different isoforms of actin (such as α-skeletal, α-cardiac, and γ-smooth muscle actin), which can be recognized by using sophisticated proteomic or molecular methods like PCR or mass spectrometry (Jia and Shi 2023, Buehler et al. 2013). By acting as molecular fingerprints, these isoforms make it possible to identify distinct types of meat in food items. As actin is abundant and stable in muscle tissues, it can be used to identify adulteration or mislabelling in meat products, guaranteeing food authenticity and adherence to legal requirements.

Mitochondrial DNA (mtDNA)

The distinctive features of mitochondrial DNA (mtDNA), high copy number, maternal inheritance and species-specific sequence differences make it an extremely useful biomarker for meat specificity identification. Even in processed or deteriorated meat samples mtDNA is easier to detect since it is found in numerous copies per cell, unlike nuclear DNA. Since the 16S rRNA and cytochrome b genes in mtDNA are conserved within species but show considerable interspecies diversity, they are frequently targeted for species identification (Montiel-Sosa et al. 2000). To distinguish between different types of meat including beef, pork, chicken and fish, these areas are amplified and analysed using PCR, DNA sequencing, and real-time PCR methods.

Fatty acid profiles

The unique makeup of fatty acid profiles in various animal species makes them useful biomarkers for meat specificity identification. This uniqueness is altered by genetics, metabolism, and food. For instance, ruminant foods like beef and lamb usually have higher amounts of branched-chain fatty acids and conjugated linoleic acid, but pig and chicken have higher amounts of unsaturated fatty acids like linoleic and oleic acid (Leiva and Granados 2020). Even in processed meat products, these profiles hold up well, making them trustworthy for identifying species and spotting adulteration.

Biomarkers for sensory qualities of meat

The characteristics of meat that are detected by the human senses-taste, smell, texture, colour, juiciness, and tenderness are referred to as its sensory qualities. These characteristics work together to determine the meat's overall palatability and consumer approval. The chemical makeup of the meat, including its peptides, amino acids, and volatile substances produced while cooking, affects its flavour and aroma. One of the most important elements is texture, especially softness, which is influenced by the kind of muscle fibre, the amount of connective tissue, and post-mortem aging processes that break down proteins (Buehler et al. 2013). Another important visual cue for meat freshness is colour and it conveys freshness and quality. The ability of meat to retain water and fat content of it are related to its juiciness, which influences mouthfeel (Leiva and Granados 2020). These sensory qualities are crucial for assessing meat quality and ensuring customer satisfaction because they are impacted by a number of variables, such as animal breed, food, slaughter conditions, and cooking techniques. Different types of biomarkers detectable at various stages of post mortem spoilage of meat are depicted in Fig. 3.

Fig. 3.

Types of biomarkers detectable at different stages of post mortem spoilage of meat

Tendernes

Tenderness is one of the most desired qualities of meat for consumers. The first step of muscle to meat conversion begins with muscle apoptosis which is the process of cell death. Meat tenderization is related to apoptosis and is mostly enzymatic in nature and various intracellular proteolytic systems are involved in it. To increase the post mortem tenderness of meat, techniques such as electrical stimulation, pelvis hung, tender stretch, tender cut, pulse electric field etc. have been proposed. Number of protein markers related to meat tenderness have been identified till date based on specifically three processes i.e. glycolytic pathways, oxidative energy supply pathways and both the pathways with heat shock proteins (Ouali et al. 2006). From the glycolysis pathway, enzymes phosphoglucomutase and triosephosphate isomerase have been identified as the potential markers of tenderness. Di-hydroxy acetone phosphate is an important cross-road for various other metabolic pathways (Ouali et al. 2006). It can also enter the glycerol-phosphate shuttle which is a shuttle between cytosolic and mitochondrial glycerol-3-phosphate dehydrogenase and plays an important role in skeletal muscle. From the energy producing phase, 5 out of 6 enzymes have been identified as the markers of meat tenderness. These enzymes include glyceraldehyde-3-phosphatedehydrogenase, phosphoglycerate kinase, enolase or phosphor pyruvate hydratase, pyruvate kinase, lactate dehydrogenase.

The markers related to meat tenderness from the oxidative energy metabolism includes, 3-hydroxy isobutyrate dehydrogenase, β-Hydroxyacyl CoA-dehydrogenase, cytochrome c, Succinate dehydrogenase, succinyl Co-A synthase and Isocitrate dehydrogenase (Ouali et al. 2006). Heat shock proteins (HSPs) play the role of molecular chaperones during protein assembly, folding and unfolding of proteins and refolding of proteins. Few HSPs as tenderisation biomarkers of meat are HSP 70 helps in slowing down the process of cellular death, protects tissue against oxidative stress and fat deposition (Buehler et al. 2013). HSP 21 helps in responding to heat-stress regulation, stabilization of myofibrillar proteins, and protection of actin filaments. Desmin, α-Crystallin helps in the protection of structural proteins. HSP 60 helps in prevention of structure degradation of proteins from apoptotic processes in muscle cell. Other meat tenderness markers are caspase, cytochrome c, galactine 1, proteolytic enzymes such as cathepsins, calpains, the 20S proteasome are members of the caspases family (Kalapos 1999, Jia et al. 2006).

Colour

Colour is one of the crucial characteristics of meat that affects consumer acceptability and quality perception. Color changes post mortem due to a number of physical and biological factors. Meat color biomarkers are quantifiable signals that offer important insights into the safety and quality of meat. The primary colour biomarkers responsible for the red colour of meat are myoglobin and hemoglobin. As almost all haemoglobin drains out during slaughter and only myoglobin becomes responsible for the meat colour. Myoglobin exists in three forms which are oxymyoglobin (MbO₂) responsible for fresh red colour of meat, deoxy myoglobin (Mb) responsible for purplish red colour of meat and metmyoglobin (MMb) responsible for the brownish red colour of oxidised meat (Ouali et al. 2006). Like myoglobin, haemoglobin also exists in two different forms which are, oxyhaemoglobin (HbO₂) responsible for the bright red colour of fresh meat and deoxyhaemoglobin (Hb) responsible for the purplish red colour of meat (Bekhit et al. 2019). Cytochrome c, influences meat colour by regulating oxygen availability in cells (Lebret et al. 2015). Glutathione, helps in maintaining the meat colour by reducing oxidative stress (Bekhit et al. 2019). Superoxide dismutase maintains meat colour and is involved in antioxidant activity also catalase enzyme protects the meat colour. Troponin T protein involved in muscle contraction and meat colour. Desmin is involved in muscle structure and effect meat colour. Actin and myosin which are two leading proteins associated with muscle contraction can also effect the meat colour (Buehler et al. 2013). Metabolic biomarkers such as p^H decline which leads to intense red colour due to increased myoglobin oxidation, lactic acid accumulation leads to intense red colour in meat, depletion of glycogen leads to colour intensity (Kuang et al. 2014). Carotenoids such as zeaxanthine, lycopene, beta-carotene, nitric oxide contributes to the meat colour (Jia et al. 2006).

Texture

Meat texture biomarkers are the biological molecules that gives idea about the meat quality post mortem and to improve the quality and consistency of the meat and meat products. Proteins that can be identified as the meat texture biomarkers are titin, troponin-T, desmin, dystrophin, tropomyosin, actin, myosin etc. Actin and myosin proteins are related to the contraction and relaxation of the muscle tissue (Jia et al. 2006). The structure and function of actin can affect the texture of meat whereas different isoforms of myosin heavy chain are associated with the different meat texture. Meat texture is also influenced by tropomyosin, a protein that is essential for controlling muscle tension and relaxation. Tropomyosin suppresses muscular contraction by attaching itself to actin filaments in muscle cells. Meat with higher tropomyosin levels is often softer and can identify as a texture biomarker (Jia and Shi 2023). Titin protein is essential for preserving the suppleness and structure of muscle cells. By providing muscle cells flexibility and enabling them to revert to their initial shape following contraction, titin functions like a molecular spring. Meat with higher titin levels tends to be softer and have a better texture (Liu et al. 2025). Desmin is essential for preserving the organization and structure of muscle cells, which in turn influences the texture of meat. By creating a scaffold around the Z-disks, desmin gives muscle cells structural support and preserves the integrity of the cells. Meat with higher desmin content tends to be softer and have a better texture (Jia and Shi 2023).

A proteolytic enzyme called mu-calpain aids in the tenderization of meat by breaking down proteins during post-mortem storage. Activation of mu-calpain is linked to better texture and tenderness in meat. Meat with higher mu-calpain activity is typically softer (Liu et al. 2025). Calpastatin enzyme controls the tenderization of meat by blocking mu-calpain activity essential for preserving the structure and functionality of muscle proteins. Cathepsin B aids in the tenderization of meat by breaking down proteins. Meat with higher cathepsin B activity is typically more tender. As it aids in the breakdown of proteins, cathepsin B is a crucial biomarker for the texture of meat (Liu et al. 2025). Cathepsin L, a proteolytic enzyme aids in the tenderization of meat by breaking down proteins. During post-mortem storage, it is essential for the breakdown of muscle proteins and increasing texture and tenderness. Gene expression biomarkers can be used to predict meat texture and can improve the consistency and quality of meat products. These includes CAST gene, CAPN1 gene, CAPN3 gene, myostatin gene etc. The calpastatin enzyme, which controls the tenderization of meat, is encoded by the CAST gene. Meat tenderization is impacted by mu-calpain activity, which is regulated by CAST gene expression (Liu et al. 2025). The control of meat tenderization is associated with the expression of this gene. Meat with higher CAPN1 gene expression is typically more tender. The calpain-3 enzyme, which aids in the tenderization of meat, is encoded by the CAPN3 gene (Gagaoua et al. 2016). Similarly, muscle growth and development control is encoded by the myostatin gene. Meat texture is influenced by the regulation of muscle fibre size and type, which is connected to myostatin gene expression (Gagaoua et al. 2016). Metabolic biomarkers of meat texture include glycolytic potential and lactate dehydrogenase. Lipid biomarkers of the meat texture include marbling score and fatty acid composition (Liu et al. 2025). Marbling score measures the amount of intramuscular fat present in the meat, the higher value of which is related to the more tender and flavourful meat.

Juiciness and flavour

Meat juiciness, a crucial sensory characteristic that affects consumer desire, is controlled by a complicated web of biomarkers that differ between species. Protein denaturation, moisture content, and intramuscular fat (IMF) are the main indicators in beef. IMF, especially marbling, improves juiciness by lubricating the chewing process, and moisture content, which is determined by water-holding capacity (WHC), guarantees succulence. During cooking, myofibrillar proteins like actin and myosin become denatured, which changes their water retention and impacts juiciness. Pork has larger quantities of glycogen, which changes into lactic acid after death and affects p^H and WHC. WHC and collagen are the main factors that contribute to poultry's juiciness; collagen hydrolyzes during cooking and helps retain moisture. Furthermore, because white muscle fibres hold moisture better than red, the proportion of white to red muscle fibres in poultry affects juiciness. The composition of connective tissue, especially collagen and elastin, and IMF are important indicators in lamb. Juiciness is improved by collagen, which is transformed into gelatin during cooking, although elastin has less of an impact. Proteolytic enzymes like cathepsins and calpains contribute to post-mortem tenderization in all species, which change protein structures and water retention to indirectly impact juiciness. Additionally, by altering lipid oxidation and flavour perception, species-specific variations in fatty acid composition. To maximize meat quality and satisfy consumer demands for juiciness, it is crucial to comprehend these biomarkers and their species-specific roles (Liu et al. 2025).

The complex sensory quality of meat flavour is regulated by numerous biomarkers that differ greatly between species and each adds in a different way to the overall flavor profile. The main biomarkers of beef are volatile substances that are produced during cooking by lipid oxidation and Maillard reactions, such as aldehydes, ketones, and chemicals containing sulfur. While sulfur components like hydrogen sulfide and methanethiol give off “meaty” and “roasted” scents, aldehydes like hexanal and pentanal add to the distinctive “grassy” and “fatty” overtones. Furthermore, glutamic acid and inosine monophosphate (IMP) promote umami, intensifying savory sensations. Branching-chain fatty acids (BCFAs) such as 4-methyloctanoic and 4-methylnonanoic acids, which give pork its species-specific “porky” flavor, have a significant impact on the flavor profile of the meat. Additionally, pork has higher concentrations of thiamine, which when heated, releases volatiles that contain sulfur and intensify meaty scents. Carbonyl molecules, such as 2,4-decadienal and 2-undecenal, which are byproducts of the oxidation of polyunsaturated fatty acids, are what give poultry flavor its “chicken-like” and “fatty” characteristics. Poultry has a milder flavor than red meats because of its lower intramuscular fat content, but it has depth thanks to amino acids like cysteine and methionine, which break down into volatiles that contain sulfur when cooked. Branched-chain fatty acids, specifically 4-methyloctanoic and 4-ethyloctanoic acids, are responsible for the unique flavor of lamb. These acids are produced in the rumen and stored in adipose tissue, giving the meat a “gamey” and “muttony” flavor. Flavor intensity can also be affected by the presence of phenolic chemicals like skatole and indole that are obtained from the animal's food (Gagaoua et al. 2016). The Maillard process, which creates heterocyclic chemicals like pyrazines and thiazoles that provide food roasted and nutty overtones, is essential to flavor development in all species. The distinct flavor profiles of beef, hog, poultry, and lamb are also shaped by species-specific variations in the makeup of amino acids, peptides, and reducing sugars, which affect the outcome of the Maillard process. To maximize meat flavor and satisfy customer preferences, it is crucial to comprehend these indicators and their species-specific roles. A detailed compilation of such sensory biomarkers is listed in Table 1.

Table 1.

Selected biomarkers of sensory properties of meat

Properties	Biomarkers	Function	References
Tenderness	Phosphoglucomutase-1 (PGM1)	Higher PGM1 levels associated with faster glycolysis and quicker pH drop resulting in more meat tenderness	Buehler et al. (2013)
	Pyruvate kinase-M2 (PKM2)	High level of PKM2 leads to tougher meat texture
	Myosin-binding protein-C	Cardiac myosin binding protein-C in meat be used to detect the potential adulteration with non-heart muscle tissue
	Myosin regulatory light chain-2 (MLC-2)	The phosphorylation level of MLC-2 gets affected by pre-slaughter stress level effecting meat tenderness and texture
	Troponin I	Troponin I can identify adulterant in mammalian meat and is relatively resistant to heat, making it detectable even in cooked meat products	Dal Bello et al. (2021)
	Dihydroxyacetone phosphate	DHAP influences muscle pH, tenderness, and water-holding capacity
	Phosphoglycerate kinase	PGK level can affect the meat quality, colour, pH and glycolytic activity
	Enolase	Enolase activity improves the meat tenderness as glycolysis leads to the breaking down of the connective tissue also to the decline of muscle pH Impacts the meat colour post slaughter by impacting the oxidation state of myoglobin	Dal Bello et al. (2021)
	Aldehyde dehydrogenase	Higher activity of aldehyde dehydrogenase is associated with tenderness, juiciness and flavour of meat and decreases lipid oxidation	Jia et al. (2006)
	3-Hydroxyisobutyrate dehydrogenase (3-HIBDH)	3-HIBDH increases the tenderness and texture of meat
	β-Hydroxyacyl CoA-dehydrogenase	β-Hydroxyacyl CoA-dehydrogenase can act as an indicator for the pre-slaughter stress and diet
	β-enolase	Higher β-enolase activity in muscles result in a faster depletion of ATP and also make tender meat	Ye et al. (2023)
	Cytochrome c	Higher activity of cytochrome c leads to increase in meat tenderness
	Succinate dehydrogenase (SDH)	Higher levels of SDH activity typically indicate more meat tenderness	Kalapos (1999)
	Succinyl Co-A synthase	Succinyl Co-A synthase, also known as succinyl-CoA synthetase, affects the general metabolic state of muscle fibers results in more tenderness
	Isocitrate dehydrogenase (IDH)	Higher levels of IDH indicates more tender meat
	HSP70, HSP 60, HSP 90	Elevated levels of HSP70, HSP60, HSP90 proteins may significantly decline the meat quality	Ouali et al. (2006) Dal Bello et al. (2021)
	HSP40	HSP40 influences proteolytic enzymes, degrade muscle proteins and improve tenderness HSP40 may influence postmortem pH decline, which affects meat quality
	HSP21	Higher level of HSP 21 protein in meat leads to tougher meat The rate of degradation of HSP 21 post-mortem is an indicator of the meat tenderization potential
	Desmin	Desmin degradation is influenced by temperature, pH decline, aging time and this leads to the production of more tenderized meat
	α-Crystallin	α-Crystallin is associated with stabilizing the cytoskeletal proteins such as desmin and actin Higher degradation indicates more tender meat	Lebret (2015)
	Caspase	Higher activity of caspases is related to increased meat tenderness	Liu et al. (2025)
	Galactine 1	Breakdown pattern of Galectin-1's of make it a promising biomarker for meat tenderness
	20S proteasome	20S proteasome shows proteolytic activity to muscle proteins and leads to the degradation of structural proteins and increasing the tenderness of meat
Colour	Myoglobin	Myoglobin is a potent indicator for assessing the quality, freshness, and spoilage of meat because of its ability to change color	Bekhit et al. (2019)
	Deoxymyoglobin	Presence of deoxymyoglobin indicates meat is less exposed to oxygen in case of fresh meat and indicates effective oxygen exclusion in vacuum packaged meat
	Oxymyoglobin	Oxymyoglobin is a meat color indicator that is responsible for the bright red colour of meat
	Metmyoglobin	Metmyoglobin forms brownish discolouration in meat and its presence indicates the oxidation and microbial spoilage
	Haemoglobin	Higher levels of deoxyhaemoglobin indicates reduced oxygen exposure, improper storage and meat quality degradation
	Cytochrome c	Higher levels of cytochrome can reflect oxidative stress in meat, which is a key factor in colour deterioration	Jia et al. (2023)
	Suproxide dismutase (SOD)	Higher SOD activity is associated with reduced oxidative damage and better colour retention and tends to have improved redness (a* value)
	Catalase	Higher catalase activity is associated with reduced oxidative damage and better colour retention as higher catalase activity tends to have improved redness (a* value)
	Toponin T	The rate and extent of degradation of troponin T can influence the structural integrity of muscle fibres, which in turn affects meat colour by inducing oxidative stress	Lebret et al. (2015)
	Glycogen	Low glycogen reserves can lead to high pH and DFD meat, while rapid glycolysis can result in low pH and PSE meat
	Adenosine triphosphate (ATP)	ATP hydrolysis contributes to the production of lactic acid, which lowers muscle pH, which affect myoglobin stability and meat colour
	Nicotinamide adenine dinucleotide (NADH)	Higher NADH levels tends to have improved redness (a* value)
	Flavin adenine dinucleotide (FAD)	The redox state of FAD with other antioxidants can influence meat colour. Higher FADH₂ is associated with improved redness (a* value)
	Zeaxanthine	Zeaxanthine presence in animal diets can influence the colour and oxidative stability of meat	Gagaoua et al. (2016)
	Nitric oxide	Higher levels of nitric oxide is associated with improved redness (a* value) and reduced metmyoglobin formation
Texture	Collagen	Collagen contributes to meat toughness when present in high amounts	Fossiet al. (1994) Lebret (2015) Bekhit et al. (2019)
	Myosin	It is a major protein in muscle fibres, influencing meat firmness and plays a role in water-holding capacity, affecting juiciness
	Actin	Actin works with myosin to determine muscle contraction and texture and it affects meat toughness when not properly degraded during aging
	Troponin-T	Degradation of troponin-T indicates proteolysis and development of tenderness. It can be used as a marker for meat aging and texture quality
	Calpastatin	Higher levels of calpastatin can lead to tougher meat	Jia et al. (2006) Montiel-Sosa et al. (2000)
	Calpains	Calpains are enzymes that break down muscle proteins resulting in enhancing texture
	Desmin	Desmin is a structural protein that maintains muscle integrity and its degradation is linked to improved meat texture
	Titin	Titin is a giant protein that contributes to muscle elasticity. Its degradation during aging of meat affects meat texture and tenderness
	Nebulin	Nebulin stabilizes the actin filaments Breakdown of nebulin influences meat texture
	Lipids (intramuscular fat)	Lipids enhances juiciness and flavour in meat and contributes to tenderness texture
	Proteoglycans	Proteoglycans affects the structural integrity of muscle tissue and influence texture in meat	Liu et al. (2025)
	Galactin	Post-mortem conversion of galactin influences meat texture
	Cathepsin	Cathepsins are lysosomal enzymes that breaks down muscle proteins which helps in enhancing texture
	Metalloproteinases (MMPs)	Metalloproteases playes a role in post-mortem proteolysis and texture development
	Sarcomere length	Sarcomere length influences the overall muscle structure and texture
Juiciness	Intramuscular Fat (Marbling)	Marbling enhances juiciness in meat by releasing fat during cooking	Lolli et al. (2020)
	Water-Holding Capacity (WHC)	WHC retains water within muscle fibers that directly influencing juiciness and also affects drip loss during storage and cooking, impacting texture
	Myoglobin	Myoglobin influences water retention in muscle tissues and linked to juiciness perception
	Collagen	Collagen converts to gelatin during cooking, trapping water and enhancing juiciness	Jia et al. (2006)
	pH (Post-Mortem)	Higher pH (closer to neutral) improves WHC affecting juiciness
	Glycogen	Breakdown of glycogen increases the water retention that influences juiciness
	Proteoglycans	Proteoglycans contributes to the structural integrity and juiciness of meat	Lebret, (2015) Bekhit et al. (2019) Liu et al. (2025) Gagaoua et al. (2016)
	Tropomyosin	Tropomyosin stabilizes muscle fibers and plays a role in maintaining juiciness during cooking
	Lipids (Phospholipids)	Phospholipids contributes to the release of flavoured juices during cooking and enhances juiciness by interacting with water and fat in muscle tissues
	Calpains	Calpains indirectly enhances juiciness by optimizing muscle structure
	Cathepsins	Cathepsins contribute to juiciness by enhancing tenderness and moisture retention
	Lactate Dehydrogenase (LDH)	LDH influences juiciness by regulating muscle hydration and drip loss
	Creatine Kinase	Creatine kinase affects water retention that influences juiciness by maintaining muscle hydration during processing

Biomarkers of microbial meat spoilage

Meat microbial biomarkers play a crucial role in ensuring meat safety and quality and are biological molecules that indicates the presence, growth or metabolic activity of microorganisms in meat. Microbial biomarkers are of different types such as bacterial DNA biomarker which indicates the presence of contamination and key target genes are 16SrRNA, gyrB or specific virulence factors. 16SrRNA is a genetic marker which is used to identify microorganisms in complex communities and because of its availability in bacteria and archea, evolutionary properties of 16SrRNA can be used as a common tool in microbial ecology (Zhang et al. 2023). PCR, qPCR, next generation sequencing techniques can be used to detect the specific 16SrRNA. Bacterial proteins can also be identified as microbial markers. Flagellin protein which is main component of bacterial flagella such as salmonella, E.coli etc. helps bacteria to move. Flagellin can be detected by techniques like ELISA, western blot or mass spectrometry. Lipopolysaccharides which is a component of the outer membrane of the gram-negative bacteria plays a key role in the structural integrity of bacteria and it can be used as a microbial biomarker for the detection of gram-negative bacteria such as E. Coli, Pseudomonas aeruginosa etc. (Muthusamy et al. 2024). Lipopolysaccharides can be detected by techniques like ELISA, western blot, mass spectroscopy etc. Toxins produced by bacteria are also identified as the biomarkers for identification of particular pathogens. Botulinum, a neurotoxin and causes muscle paralysis by blocking neurotransmitter release can be used to identify Clostridium botulinum. Tetanus, a neurotoxin and causes muscle spasms by blocking neurotransmitter release can be used to identify Clostridium tetani. Staphylococcal enterotoxin B a superantigen and causes food poisoning by stimulating the T-cell activation can be used to identify Staphylococcus aureus. Shiga toxin a cytotoxin that inhibits protein synthesis causing cell death can be used to identify Shigella dysenteriae and some of the E.coli strains. Cholera toxin is an enterotoxin and stimulates adenylate cyclase causing diarrhea can be used to identify Vibrio cholera. Epsilon toxin and Alpha toxin that forms pores in cell membranes leading to cell death can be used to identify Clostridium perfringes. Bacterial adhesin proteins allows the bacteria to attach to the bacterial surfaces. Bacterial adhesins for example FimH that binds to mannose containing receptors on host cells can be used to identify E.coli responsible for causing urinary tract infection (UTI), Pili that binds to the CD46 receptors on host cells can be used to identify Neisseria gonorrhoeae that causes gonorrhoea, invasin that binds to β1-intigrin receptors on host cells can be used to identify Yersinia pseudotuberculosis that causes enteric infections, Intimin binds to TIR receptors (Toll and interculin-1 receptor) on host cells causing diarrheal diseases and is the indication of the presence of enteropathogenic E.coli. Presence of fibronectin-binding protein, an adhesin that binds to fibronectin on host cells and collagen binding protein can be used to identify Staphylococcus aureus, (Fadda et al. 2010). Few bacterial metabolites can also serve as the microbial biomarkers for identification of certain species of bacteria, for example, volatile organic compounds, short chain fatty acids, indole, phenylacetate, hydrogen sulfide, putrescine, cadaverine, adenosine triphosphate etc. Bacterial enzymes such as alkaline phosphatase, β-galactosidase, β-glucuronidase, catalase, lipase, protease, urease, DNase etc. can be used to identify specific types of bacteria. Colorimetric assays, fluroscence assays, ELISA etc. techniques can be used for identification of microbial enzyme biomarkers (Fadda et al. 2010).

Fungal biomarkers show if fungus are present, growing, or engaged in metabolic processes. These biomarkers are essential for identifying fungal contamination in diverse settings, tracking the effectiveness of treatment, and diagnosing fungal illnesses. Meat fungal biomarkers include mycotoxins, fungal DNA, fungal metabolites, etc. Mycotoxins such as aflatoxin M1, ochratoxin A can be used to identify aspergillus and penicillium species in meat and meat products. Fungal proteins such glycoprotein and different enzymes such as protease, lipase, amylase etc. can be used as the identifying factors of fungal biomarkers in meat and meat products. Fungal metabolites such as volatile organic compounds, polyketides can be used to identify fugal contamination in meat and meat products (Muthusamy et al. 2024). Similarly, viral biomarkers show if viruses are present, replicating, or metabolizing. Viral meat biomarkers will include viral nucleic acids, viral proteins, viral antigens. Viral nucleic acids such as HIV RNA, hepatitis C virus RNA, influenza virus RNA can be used to identify viral contamination in meat and meat products and these viral nucleic acids can get detected by nested PCR, qPCR, NGS, sanger sequencing, deep sequencing, microarrays etc. Proteins produced by viruses both structural and non-structural can be used as the identifier for viral contamination in meat and meat products. The examples of viral proteins may include HIV p24 antigen, hepatitis B surface antigen, influenza virus hemagglutinin etc. and can get detected by ELISA, western blot and mass spectrometry (Fadda et al. 2010). A detailed representation of such biomarkers can be found in Table 2.

Table 2.

Selected biomarkers of meat spoilage

Properties	Biomarkers	Function	References
Microbial biomarkers	16SrRNA	The diversity and abundance of bacteria detected through 16S rRNA sequencing can serve as a marker for microbial load, which is directly related to meat spoilage and shelf life	Muthusamy et al. (2024)
	Flagellin	Flagellin has been explored as a potential microbial biomarker for detecting bacterial contamination, particularly for motile pathogens such as Salmonella, Escherichia coli, and Pseudomonas
	Lipopolysaccharides (LPS)	The presence of LPS in meat samples indicates contamination with Gram-negative bacteria, and LPS-producing bacteria, such as Pseudomonas and Enterobacteriaceae, are often associated with meat spoilage	Fadda et al. (2010)
	Staphylococcal enterotoxin B (SEB)	SEB is a potent exotoxin produced by Staphylococcus aureus and its presence in meat samples indicates contamination with S. aureus and the potential for staphylococcal food poisoning	Zhang et al. (2023)
	Shiga toxin	Shiga toxin is produced by specific pathogenic strains of E. coli (STEC) and Shigella. STEC, particularly E. coli O157:H7, is a significant concern in meat, especially ground beef
	Cholera toxin	Cholera toxin is uniquely produced by toxigenic strains of V. cholerae, making it a highly specific marker for this bacterium	Pessione et al. (2016)
	Fibronectin binding protein (FnBP)	FnBPs can act as indicators for the presence of pathogens like Staphylococcus aureus and Listeria monocytogenes in meat FnBPs facilitate bacterial adhesion and biofilm formation on meat surfaces, accelerating spoilage
	Indole	Indole presence in meat signals microbial activity by releasing to unpleasant odors that helps in assessing spoilage and hygiene levels during storage and processing
	Phenylacetate	Pseudomonas species produce phenylacetate, which gives meat its bad smells and odors	Fadda et al. (2010)
	Hydrogen sulphide	Sulfur-reducing bacteria like Salmonella and E. coli produce hydrogen sulfide (H₂S), which is a sign of microbial activity in meat and contributes to the characteristic “rotten egg” smell in meat	Zhang et al. (2023)
	Putresceine	Bacterias like Pseudomonas and Enterobacteriaceae make putrescine by decarboxylating amino acids and contributes to unpleasant odour in meat	Muthusamy et al. (2024)
	Cadaverine	By decarboxylating lysine, bacteria like Enterobacteriaceae and Pseudomonas generate cadaverine, which aids foul odour in meat	Zhang et al. 2023
	Alkaline phosphatase	Alkaline phosphatase (ALP) is an enzyme naturally present in raw milk and meat and elevated ALP levels in meat can also signal contamination by certain bacteria that produce similar enzymes	Fadda et al. (2010)
	β-galactosidase	Activity of β-galactosidase can be used to monitor microbial growth and spoilage in meat specially spoilage caused by E.coli
	β-glucuronidase	β-glucuronidase is an enzyme produced specifically by E. coli and some other enteric bacteria and its activity of can be used to track E.coli growth and spoilage in meat	Zhang et al. (2023)
	Catalase	Catalase is an enzyme produced by bacteria like Staphylococcus and Pseudomonas and its activity can signal oxidative spoilage in meat
	Lipase	Lipase produced by spoilage bacteria such as Pseudomonas and Staphylococcus which presence in meat indicates lipid breakdown and rancidity development
	Amylase	Amylase is an enzyme produced by bacteria such as Bacillus and Pseudomonas and its activity can signal the breakdown of carbohydrates in meat, leading to texture changes and off-flavours,	Muthusamy et al. (2024)

Methods and techniques for detection of biomarkers

Foods of animal origin can be reliably determined for species, freshness and potential health hazards by identifying certain proteins, DNA sequences, metabolites, or chemical residues. A number of analytical methods have been developed for this purpose, ranging from advanced technologies like mass spectrometry, nuclear magnetic resonance and next-generation sequencing to more conventional procedures like ELISA, PCR, and chromatography. In order to ensure food safety, authenticity and regulatory compliance, reliable biomarker detection techniques are crucial as consumer demands for transparency and food traceability increases (Nimse et al. 2016).

Conventional methods for detection of biomarkers

Conventional methods for identifying biomarkers in foods derived from animals have long served as the basis of safety assurance, species identification, food quality management and spoilage detection. The most basic of all of these methods is sensory evaluation, which includes evaluations of colour, flavour, texture and odour. These factors have long been used to determine whether products like milk, meat and fish have been spoiled. Despite being subjective and sensitive to human variability, sensory analysis is still a primary screening method used in food inspection. Conventional methods like thiobarbituric acid reactive substances (TBARS) assay are often used in conjunction with chemical assays to track oxidative spoilage or protein degradation. Colorimetric and gravimetric techniques were commonly employed as food control systems progressed. It is common practice in dairy to assess quality and identify dilution or substitute by analyzing the fat and protein composition using the Gerber or Kjeldahl methods, etc. (Vallverdú-Queralt et al. 2016). Immunological techniques, like ELISA have become a commonly used conventional tools for the detection of biomarkers through molecular and biochemical methods. ELISA allows it possible to detect species-specific proteins and allergens in animal derived foods. To identify pig gelatin in meatballs, detecting egg proteins in baked goods or measuring the allergen β-lactoglobulin in milk, ELISA technique can be used. It is particularly advantageous when processing compromises the integrity of DNA. Several protein-based immunoassays, such as dot blotting and western blotting, provide semi-quantitative analysis of particular dietary proteins. Despite being more time-consuming, these techniques have a high specificity and are frequently employed to validate ELISA results (Picó et al. 2019). Food biomarker detection has significantly improved through advances in chromatographic techniques, even if they are considered as a component of traditional lab procedures. One of the earliest methods, thin layer chromatography, has been used to examine the lipids or simple amino acids found in milk and meat. More sophisticated methods like gas chromatography and high-performance liquid chromatography are widely employed to find tiny compounds like hormones, antibiotics, and spoilage markers like biogenic amines in meat and fish. Polymerase chain reaction is a common molecular technique for species identification and is widely employed in the certification of meat and dairy products (Russ et al. 2016). The presence of specific species DNA in mixed or processed food samples can be identified using conventional PCR, RT-PCR, multiplex PCR, digital PCR etc. Spectrophotometric methods, such as UV–visible spectrophotometry are frequently used to examine chemical or enzymatic interactions involving food ingredients. Even with all of their benefits, conventional methods have drawbacks. Many of them requires laboratory facilities, competent staff and rigorous sample preparation. Additionally, they are not as fast, sensitive or capable of multiplexing as more recent alternatives. However, they still play a crucial part in routine food inspection, especially in underdeveloped nations or for regulatory objectives that call for approved techniques (Picó et al. 2019). Thus, they continue to be an essential component in the detection of biomarkers.

Advanced methods for detection of biomarkers

The limitations of conventional methods have been overcome by technological advances, which has significantly enhanced the detection of biomarkers in foods of animal origin. These innovative techniques focus on speed, sample non-destructiveness, high sensitivity and specificity by enabling in situ, real-time assessments for food safety and traceability. Fourier Transform Infrared Spectroscopy (FTIR) is one of the most powerful techniques which develops molecular fingerprints by analyzing patterns of infrared light absorption (Kumar et al. 2022). It is frequently used to find variations in the lipid and protein profiles of meat in order to identify adulteration. Mid-Infrared (MIR) and near-infrared (NIR) spectroscopy provide quick, non-destructive testing with minimal sample preparation, which is helpful for evaluating the quality of meat and milk (Nimse et al. 2016). Another vibrational spectroscopy method with advantages is Raman spectroscopy, which has negligible water interference and is non-invasive (Guo et al. 2021). Detecting adulteration in egg powders and differentiating milk from various species have both been accomplished with effectiveness with the method. Nuclear Magnetic Resonance spectroscopy although offers highly accurate metabolite and lipid profiling, yet it does require extra infrastructure. The gold standard for species authentication is presently mass spectrometry-based proteomics, such as LC–MS/MS, MALDI-TOF MS and Orbitrap M etc. These techniques make it possible to identify particular peptides or protein biomarkers in meat or dairy products. For example, MALDI-TOF MS may identify the animal origin of milk by profiling casein variants, whereas LC–MS/MS allows for accurate quantification of allergenic proteins and veterinary medication residues etc. Next-Generation Sequencing and DNA microarrays have transformed food forensics by enabling the simultaneous identification of DNA of several species in complex food matrices. Similarly, digital PCR provides extremely accurate and sensitive target DNA quantification without the use of standard curves. For on-site, real-time analysis, biosensors, especially electrochemical and optical biosensors are becoming popular (Kumar et al. 2022). The purpose of these biosensors is to identify particular proteins, DNA or trace metabolites on spot. Immuno-magnatic separation also provides rapid and efficient separation of target molecules from complex mixtures. Surface-Enhanced Raman Scattering also helps in biosensing by detection of biomarkers or other biological molecules by creating intense local electromagnetic fields around the surface, typically by using plasmon resonance in nanostructured metals like gold or silver. Chemometric modeling and machine learning are powerful methods for discovering biomarkers as they use statistical methods and big datasets to find molecules that might indicate presence of specific molecules. For the analysis of complex data generated by high-throughput technologies like proteomics, metabolomics and genomics, these methods are particularly effective (Guo et al. 2021). These advanced methods of biomarker discovery, over the conventional methods proves as reliable tools by offering faster, more accurate and scalable solutions for ensuring the safety, quality, and integrity of animal-origin foods.

Conclusion

In conclusion, the identification of biomarkers in foods of animal origin is of utmost importance to ensure consumer acceptance and safety. The most convenient biomarkers are that a normal person can identify in real time. Point of care detection techniques are therefore widely researched nowadays, developing novel techniques and apparatus to identify such biomarkers. Detection of quality and safety biomarkers in meat along with the introduction of traceability has enabled the consumers and producers to attain an equilibrium in determining the quality of the product. This represents a revolutionary step in ensuring the overall quality, safety and authenticity of foods of animal origin. Biomarkers that act as microbial indicators are essential for identifying foodborne pathogens and spoilage organisms ensuring food safety and increasing shelf life. As food fraud becomes increasingly intricate, these developments will be essential to maintaining food safety, authenticity and consumer confidence in products with animal origins worldwide.

Author’s contribution

All the listed authors have equally contributed.

Funding

The required fund has been received from ICAR-National Research Centre on Pig.

Data availability

Available with the institute.

Code availability

Not applicable.

Declarations

Conflicts of interest

No conflicts of interest exist.

Ethical approval

All the research works carried out at Food Quality Control Lab is approved by Institute Animal Ethics Committee and Institute Biosecurity Council.

Consent to participate

Not applicable

Consent for publication

Approved by the Performance Monitoring and Evaluation (PME) cell of the institute for sending for publication to JFST.