Introduction
Animal-derived foods, such as meat, milk, and their processed products, generally have high water activity and nutritional value. Therefore, they are highly susceptible to spoilage by microorganisms, especially pathogenic bacteria (Odeyemi et al., 2020; Saha et al., 2024; Tapia et al., 2020; Yuan et al., 2019). A cold chain system is the simplest way to control the freshness and microbiological safety of animal-derived foods. By applying this system, food quality is maintained by controlling the temperature at a low level during the entire process of harvesting fresh foods from the production site and then storing and transporting them to the final consumption site (Montanari, 2008; Ndraha et al., 2018). However, this approach is not perfect, as some microorganisms survive and multiply even at low temperatures. Low-temperature storage improves food storability; however, contamination with psychrotrophic bacteria may make this impossible (Chen et al., 2020).
Psychrotrophic bacteria, defined as cold-tolerant bacteria, have the ability to grow at temperatures below 7°C, such as those found in refrigerated conditions. These bacteria are known for causing spoilage in food products, especially animal-derived foods (Moyer et al., 2017; Tatini and Kauppi, 2002). Psychrotrophic bacteria can grow at low temperatures, although their growth is limited to a maximum temperature of approximately 20°C. Typically, these bacteria do not thrive over 35°C (Kanekar and Kanekar, 2022). Thus, they appear to be a subgroup of mesophiles, whose optimum growth range is between 30°C to 40°C. However, they are not a subgroup of psychrophiles, which prefer much colder environments, typically below 15°C (Cavicchioli, 2016). During storage at low temperatures, psychrotrophic bacteria that adapt to the low temperatures thrive better than mesophilic bacteria, leading to an increase in their cell population (Samaržija et al., 2012; Wickramasinghe et al., 2019). Moreover, compared to the mesophilic bacteria in raw milk, the quantity of psychrotrophic bacteria increased by over 10%. Psychrotrophic bacteria can produce enzymes related to heat resistance (e.g., proteolytic enzymes, lipolytic enzymes, and phospholipases), some of which have antibiotic resistance or the ability to produce toxins. Thus, psychrotrophic bacteria proliferate at low temperatures and not only spoil food but can also be difficult to inactivate through heat treatment (sterilization process) and can have adverse effects on human health.
Therefore, in this review, we aimed to determine the growth characteristics and species composition of psychrotrophic bacteria that are commonly observed in animal-derived foods and to check their contamination (distribution) status. In addition, we proposed a technique for reducing the number of psychrotrophic bacteria that can be applied to animal-derived food.
Characteristics of Psychrotrophic Bacteria
Psychrotrophic bacteria enter food from their mesophilic habitats and continue to grow at a slow pace in refrigerated environments. There are several reasons why psychrotrophic bacteria can continue to survive and grow even at low temperatures. First, they can maintain the activity of various enzymes involved in metabolism even under cold conditions. These bacteria possess enzymes that can be activated at low temperatures, and they provide thermolability and increase complementarity between the substrate and the active site, thereby providing high specific activity at low temperatures (Cavicchioli et al., 2002; Chattopadhyay, 2006; D’Amico et al., 2002). As a result, the activation energy is lowered, helping to maintain the substrate-enzyme reaction even at low temperatures (De Maayer et al., 2014). Second, they can maintain the membrane fluidity even at low temperatures due to their ability to regulate the composition of the cell membranes. The cell membrane transmits various signals and exchanges substances, especially nutrients. Therefore, cellular survival is highly dependent on the fluidity of the cell membrane (Moyer et al., 2017; Najjar et al., 2007; Wang et al., 2016). The membrane fluidity is determined by composition of the phospholipid bilayer comprising the cell membrane, which is odd-numbered, unsaturated, and anteiso fatty acids (Hagve, 1988; Yoon et al., 2015). Especially, polyunsaturated fatty acids (PUFAs) had a low melting point, thus controlling the amount of PUFAs at low temperatures can be a good way to maintain membrane fluidity (Casanueva et al., 2010; Hassan et al., 2020). Moreover, a-C15:0, an anteiso fatty acid, plays a key role in bacterial survival at low temperatures; for example, a-C15:0 is a major component of bacteria living in the Antarctic region (Chattopadhyay and Jagannadham, 2003). In addition to changes in the composition of fatty acids in the cell membrane, changes in various transport proteins, which play a role in transporting substances into and out of the cytoplasm, also occur in the cell membrane. Psychrotrophic bacteria upregulate the expression of some of these proteins to ensure smooth transport of substances even at low temperatures (De Maayer et al., 2014). Third, they have or can uptake some substances that help them survive at low temperatures, such as antifreeze proteins (AFPs) and compatible solutes. AFPs, possess by psychrotrophic bacteria, which control the expression of proteins related to cold and heat shock, or by switching to a viable but nonculturable state (Chattopadhyay, 2006). They can prevent freezing or thawing damage to bacteria by inhibiting the growth of ice crystals at low temperatures (Celik et al., 2013). Psychrotrophic bacteria can respond to low temperatures by accumulating compatible solutes in the cytoplasm to increase the concentration of solutes and thereby increasing osmotic pressure (Casanueva et al., 2010). For example, glycine betaine, a type of compatible solute, is a substance that Listeria monocytogenes can synthesize, and its synthesis becomes active at low temperatures, which can stimulate the growth of L. monocytogenes at low temperatures (Beumer et al., 1994; Chan and Wiedmann, 2008; Zeisel et al., 2003). It should be remembered that all of the previously mentioned events are regulated by gene expression.
Psychrotrophic bacteria are the main cause of the spoilage of chilled and frozen foods derived from animals, including raw or cooked meat, dairy products, butter, fresh or cooked seafood, and vegetables (Wei et al., 2019). The most common psychrotrophic bacteria found in animal-derived food are Pseudomonas, Listeria, Yersinia, Serratia, Aerococcus, Acinetobacter, and Flavobacterium (Chen et al., 2020; Júnior et al., 2018; Yuan et al., 2017). Pseudomonas is the main bacterium that causes meat spoilage because it produces protein and fat hydrolases, biosurfactants, and colors (Rouger et al., 2018). Dhama et al. (2013) reported that meat and meat products, and dairy products are common sources of L. monocytogenes, an intracellular gram-positive bacterium that may survive and grow under refrigeration.
Contamination of Animal-Derived Foods due to Psychrotrophic Bacteria
Animal-derived foods often contaminated by psychrotrophic bacteria, including Listeria, Pseudomonas, and Yersinia. Numerous studies have reported cases of contamination in a variety of animal resources, including dairy products (milk and cheese), meat (poultry, pork, and beef), and animal-derived products (Table 1). Despite not being classified as a psychrotrophic bacterium, Clostridium has been commonly detected in animal-derived foods stored at low temperature.
Microorganisms | Type of foods | No. of positive samples (%) | Reference | |
---|---|---|---|---|
Listeria spp. | Dairy products | Raw sheep milk | 14/62 (22.6) | Rahimi et al. (2010) |
Raw cow milk | 10/90 (11.1) | |||
Raw goat milk | 4/60 (6.7) | |||
Cheese | 17/90 (18.9) | |||
Ice cream | 7/68 (10.3) | |||
Butter | 2/40 (5.0) | |||
Raw milk | 41/140 (29.2) | Akrami-Mohajeri et al. (2018) | ||
Cheese | 17/120 (14.2) | |||
Butter | 4/100 (4.0) | |||
Raw milk | 2/30 (6.7) | Ismaiel et al. (2014) | ||
Raw milk | 84/766 (11.0) | Al-Mariri et al. (2013) | ||
Listeria monocytogenes | Meat | Pig carcass | 12/430 (2.8) | Oswaldi et al. (2021) |
Raw pork | 104/356 (29.2) | Li et al. (2018) | ||
Raw meat | 98/525 (18.7) | Kramarenko et al. (2013) | ||
Frozen lean beef | 1/30 (3.3) | Ismaiel et al. (2014) | ||
Raw meats (minced pork and beef meat) | 103/295 (34.9) | Vitas and Garcia-Jalon (2004) | ||
Poultry | 57/158 (36.1) | |||
Raw processed meat | 149/765 (19.5) | Matle et al. (2019) | ||
Raw intact meat | 56/557 (10.1) | |||
Dairy products | White cheese | 5/105 (4.8) | Kahraman et al. (2010) | |
Processed cheese | 1/70 (1.4) | |||
Queso fresco cheese | 7/75 (9.3) | Beltran et al. (2015) | ||
Adobera cheese | 12/100 (12.0) | Torres-Vitela et al. (2012) | ||
Panela cheese | 6/100 (6.0) | |||
Ready-to-eat (RTE) meat products | Ham and turkey | 6/507 (1.2) | Lambertz et al. (2012) | |
RTE milk products | 13/4,901 (0.3) | Kramarenko et al. (2013) | ||
RTE meat products | 135/6,746 (2.0) | |||
RTE meat products | 59/436 (13.5) | Matle et al. (2019) | ||
Pseudomonas spp. | Dairy products | Raw milk | 93/103 (90.3) | Marchand et al. (2012) |
Raw milk | 35/50 (70.0) | Aziz et al. (2022) | ||
Milk (raw, n=4; pasteurized, n=8) | 6/12 (50.0) | Carminati et al. (2019) | ||
Cheese | 3/20 (15.0) | |||
White cheese | 32/140 (22.9) | Arslan et al. (2011) | ||
Meat | Chicken meat | 7/15 (46.7) | Mahato et al. (2020) | |
Chicken meat | 91/168 (54.2) | Wu et al. (2023) | ||
Pork meat | 18/91 (19.8) | |||
Frozen chicken meat | 69/320 (21.6) | Elbehiry et al. (2022) | ||
Fresh beef | 3/60 (5.0) | Rezaloo et al. (2022) | ||
Frozen beef | 8/60 (13.3) | |||
Beef | 122/230 (53.0) | Benie et al. (2017) | ||
Smoked fish | 33/140 (23.6) | |||
Fresh fish | 49/140 (35.0) | |||
RTE meat product | Sausage | 5/60 (8.3) | Sofy et al. (2017) | |
Luncheon meat | 11/60 (18.3) | |||
Beef burger | 1/60 (1.7) | |||
Frozen burger | 1/25 (4.0) | Hassan et al. (2020) | ||
Animal | Fecal samples | 46/704 (6.5) | Ruiz-Roldán et al. (2020) | |
Yersinia enterocolitica | Dairy products | Dairy products (cheese, butter, and yogurt) | 6/49 (12.2) | Mancini et al. (2022) |
Raw cow milk | 12/44 (27.3) | |||
Raw goat milk | 1/4 (25.0) | |||
Raw milk | 19/446 (4.3) | Jamali et al. (2015) | ||
Raw milk | 11/50 (22.0) | Ahmed et al. (2019) | ||
Fermented milk | 6/50 (12.0) | |||
Pasteurized milk | 2/50 (4.0) | |||
Ripened salted cheese | 1/50 (2.0) | |||
Meat | Chicken | 132/720 (18.3) | Momtaz et al. (2013) | |
Chicken | 37/50 (74.0) | Palau et al. (2024) | ||
Pork | 8/10 (80.0) | |||
Pork | 11/237 (4.6) | Esnault et al. (2013) | ||
Beef | 11/210 (5.2) | |||
Poultry | 12/202 (5.9) | |||
Chicken | 41/190 (21.6) | Soltan Dallal et al. (2010) | ||
Beef | 19/189 (10.1) | |||
Clostridium botulinum | Honey | Polish honey | 5/240 (2.1) | Grenda et al. (2018) |
Kazakh honey | 1/197 (0.5) | Maikanov et al. (2019) | ||
Clostridium perfringens | Honey | Kazakh honey | 18/197 (9.1) | Maikanov et al. (2019) |
Dairy products | Raw milk | 78/79 (98.7) | Feligini et al. (2014) | |
Curd | 79/79 (100.0) | |||
Meat and meat products | Beef | 20/40 (50.0) | Issimov et al. (2022) | |
Lamb | 9/40 (22.5) | |||
Ground beef | 11/40 (27.5) | |||
Minced lamb | 16/40 (40.0) | |||
Raw chicken | 6/25 (24.0) | Shaltout et al. (2017) | ||
Raw beef | 4/25 (16.0) |
Listeria spp. have been identified in various animal-derived food sources across different regions, highlighting their prevalence in the food chain and their potential risks to public health. Particularly concerning for animal-derived food safety is the fact that L. monocytogenes can grow at refrigerated conditions. Raw milk and cheese (Akrami-Mohajeri et al., 2018; Costanzo et al., 2020; Rahimi et al., 2010), meats (Li et al., 2018; Oswaldi et al., 2021), and ready-to-eat (RTE) meat products (Calvo-Arrieta et al., 2021; Meza-Bone et al., 2023) are the most common animal-derived foods contaminated with L. monocytogenes. In Syria, research has shown that 11.0% of raw milk samples tested positive for Listeria spp. (Al-Mariri et al., 2013). In Egypt, Listeria spp. were found in cheese and raw milk at rates ranging from 3.3% to 6.7% (Ismaiel et al., 2014). In Turkey, Kahraman et al. (2010) found that 4.8% of L. monocytogenes were detected in white cheese samples, whereas processed cheese samples had a detection rate of 1.4%. In Mexico, L. monocytogenes was detected in 9.3% of queso fresco, 12.0% of adobera, and 6.0% of panela cheese, all of which are type of fresh cheese (Beltran et al., 2015; Torres-Vitela et al., 2012). In South Africa, L. monocytogenes was detected in a range of meat and meat products obtained from cattle, pork, sheep, game meat, and poultry (Matle et al., 2019). In this study, L. monocytogenes were found in 10.1% of uncooked whole meat, 13.5% of RTE meat products, and 19.5% of uncooked processed meat. In Spain, Vitas and Garcia-Jalon (2004) analyzed 396 meat product samples obtained from 55 small meat-processing plants, and L. monocytogenes were detected in 36.1% of poultry meat, 34.9% of minced pork and beef. In Quevedo, a city in Ecuador, 16.3% of L. monocytogenes was present in RTE meat products, including grilled hamburger meat, mortadella, and salami. The concentration of L. monocytogenes ranged from 4 to 6 Log CFU/g, or possibly much higher (Meza-Bone et al., 2023).
Pseudomonas is a prevalent member of the microbiota in various animal-derived foods, including pork (Bruckner et al., 2012), chicken (Elbehiry et al., 2022; Wu et al., 2023), beef (Ercolini et al., 2009), and milk (Aziz et al., 2022). Wu et al. (2023) identified 109 Pseudomonas aeruginosa isolates, which constituted 42.1% of 259 samples collected across six districts in Beijing, China. Especially, 91 isolates from chicken samples (54.2%) and 18 from pork samples (19.8%). Similarly, Mahato et al. (2020) described that P. aeruginosa was detected in 46.7% of chicken meat samples. Among the 370 meat and meat product samples analyzed by Rezaloo et al. (2022), 29 samples were contaminated with P. aeruginosa. Notably, imported frozen beef harbored the highest prevalence (20.0%), followed by frozen beef (13.3%) and fresh beef samples (5.0%). Benie et al. (2017) reported that the prevalence of P. aeruginosa among smoked fish, fresh fish, and beef samples was 23.6%, 35.0%, and 53.0%, respectively. Furthermore, P. aeruginosa prevalence among sausage, luncheon meat, beef burger, and frozen burger samples was 8.3%, 18.3%, 1.7%, and 4.0%, respectively (Sheir et al., 2020; Sofy et al., 2017). In the dairy foods, P. aeruginosa was detected in 70.0% of milk samples and 24.0% of samples collected from a milk tank at a dairy cattle farm in Egypt (Aziz et al., 2022). Carminati et al. (2019) found that Pseudomonas spp. was isolated from 50.0% of milk and 15.0% of cheese samples, with concentrations between 3.45 and 4.05 Log CFU/mL or g. Similarly, Arslan et al. (2011) reported that 22.9% of Pseudomonas spp. was isolated from 140 homemade white cheese samples, with the dominant isolate being Pseudomonas pseudoalcaligenes (15.0%), followed by Pseudomonas alcaligenes (5.0%), P. aeruginosa (1.4%), and P. fluorescens biovar V (0.7%). Furthermore, certain Pseudomonas species, including potentially pathogenic ones like Pseudomonas fulva, P. aeruginosa, and Pseudomonas putida have been found in the fecal samples of healthy animals. A study analyzing 704 animal fecal samples identified 133 isolates of Pseudomonas spp. belonging to 23 different species, recovered from 46 samples (6.5%; Ruiz-Roldán et al., 2020).
Yersinia, particularly Y. enterocolitica, has been isolated and found to contaminate various types of animal-derived foods, such as raw and undercooked pork meats, milk, and dairy products (Ali et al., 2021). Yersinia presence in animal-derived foods poses significant public health risks as it can cause yersiniosis, which can range from mild self-limiting gastroenteritis to more severe illnesses, including septicemia and yersiniosis (Hordofa, 2021). Swine serves as the main reservoir for Y. enterocolitica, with pathogenic strains found in swine and pork products are most commonly reported in human illnesses (MacDonald et al., 2012). Further food-producing animals that have been linked to Y. enterocolitica include sheep, poultry, and cattle. Palau et al. (2024) isolated Y. enterocolitica from 53 of 70 samples (75.7%), including 37 from 50 chicken (74.0%), 8 from 10 pork (80.0%), and 8 from 10 salmon (80.0%). In France, Y. enterocolitica was found in 5.9% of chicken and 4.6% of pork samples (Esnault et al., 2013). Furthermore, Soltan Dallal et al. (2010) recovered Yersinia spp. from 16% of 379 samples, with 21.6% from chicken and 10.1% from beef. In the dairy foods, Y. enterocolitica was detected in 12.2% of dairy products made from raw milk, 27.3% of raw cow milk, and 25.0% of raw goat milk collected from Apulia and Basilicata regions in Southern Italy (Mancini et al., 2022). Ahmed et al. (2019) reported that Y. enterocolitica was isolated from raw milk and dairy products in 40% of examined samples. Notably, the highest isolation rate was 22.0% from raw milk, followed by 12.0%, 4.0%, and 2.0% from fermented milk, pasteurized milk, and ripened salted cheese, respectively. Additionally, in Iran, Y. enterocolitica was isolated from 4.3% of bulk raw milk samples including cow, sheep, and goat milk (Jamali et al., 2015).
Clostridium spp. is generally not considered psychrotrophic bacteria, however, it is notable for their ability to produce endospores that can endure diverse environmental conditions, including cold temperatures. Clostridium botulinum and Clostridium perfringens are recognized for their potential to induce foodborne illnesses through toxins or spores (Grenda et al., 2017). Additionally, C. botulinum can be found in honey as dormant spores. The low water activity and pH (acidic) of honey, which generally inhibit the growth of many bacteria, did not affect C. botulinum spores. Grenda et al. (2018) reported a 2.1% prevalence of C. botulinum in honey samples in Poland. Additionally, Maikanov et al. (2019) found that C. botulinum was isolated in only 0.5% of the samples, and C. perfringens was isolated from 18 of the 197 honey samples (9.1%). One incidence of newborn botulism was reported in the United Kingdom in 2001, and it seemed that the cause was powdered infant formula contaminated with C. botulinum spores (Brett et al., 2005). According to Barash et al. (2010), 78.0% of the powdered infant formula samples contained clostridial spores, specifically Clostridium sporogenes. The isolation of clostridial spores indicates that neurotoxic clostridial spores may be found in these products. In Italy, clostridial spores were detected in 99.0% of the 527 analyzed sheep milk samples. Among these samples, 86% had spore concentrations higher than the 1,000 spores/L (Turchi et al., 2016). Furthermore, C. perfringens was found in 98.7% of raw milk in tanks and 100.0% of curd samples used for Grana Padano cheese production in Northern Italy (Feligini et al., 2014). In meat and meat products, C. perfringens was detected in 50.0% of beef, 22.5% of lamb, 27.5% of ground beef, and 40.0% of minced lamb by Issimov et al. (2022). Shaltout et al. (2017) reported that C. perfringens was detected in 15.0% of beef and chicken before and after cooking, represented by 24.0% of raw chicken, 12.0% of cooked chicken, 16.0% of raw beef, and 8.0% of cooked beef samples.
Reduction of Psychrotrophic Bacteria in Animal-Derived Foods
Thermal technologies have been used to deactivate microorganisms present in animal-derived food products. However, these techniques have a negative effect on the nutritional and sensory values of the treated food products (Jauhar et al., 2020). Conventional decontamination technologies for meat and meat products include heat processing, chilled storage, vacuum packing, and chemical preservation. However, the use of heat during processing might reduce the nutritional value and sensory characteristics, while chemically treated products might show significant residue deposition (Jadhav et al., 2021). To eliminate pathogenic bacteria from animal-derived foods without heating and affecting the quality of the food, nonthermal techniques have been presented as alternatives to conventional pasteurization (Lee and Yoon, 2024). The various specific nonthermal techniques are described below.
Each microorganism has its own unique oxygen requirement, and therefore, the growth of microorganisms can be controlled by changing the air composition. One method of adjusting the composition of air is the modified atmosphere packaging (MAP). This method particularly focuses on aerobic microorganisms because it replaces oxygen in the air with carbon dioxide or nitrogen (Farber et al., 2003; Kader, 1986). It not only inhibits the growth of aerobic microorganisms, but also prevents rancidity of fat caused by oxygen, thus it can be effectively applied to meat products containing fat. As an example, Y. enterocolitica and L. monocytogenes might survive in MAP foods between 0°C to 1°C (Barakat and Harris, 1999; Hudson et al., 1994). When pure nitrogen gas was injected into raw milk, the Pseudomonas growth was significantly limited, and when carbon dioxide was added to raw milk, the microbiological quality was maintained for a long period of time, making it possible to produce milk with a long shelf life (Munsch-Alatossava et al., 2010; Vianna et al., 2012; Yuan et al., 2019). In contrast, Huang et al. (2020) reported higher concentrations of Pseudomonas in roasted chicken stored under MAP (40% CO2/60% N2) conditions. Also, it has limitations in that spoilage caused by lactic acid bacteria (LAB) is occasionally observed. LAB lowers pH and causes muscle tissue destruction and moisture lose in meat stored under high CO2 level (Wang et al., 2017; Wickramasinghe et al., 2019).
Additionally, supercritical carbon dioxide (SC-CO2) can be used to control pathogenic bacteria in animal-derived foods. SC-CO2 diffuses CO2 to lower cytoplasmic pH and extracts important components to change microbial cell membranes (Guerrero et al., 2017). It is currently not known how SC-CO2 exhibits bactericidal activity, potentially, might depend on variables including pressure, temperature, and exposure time. According to the previous studies, SC-CO2 might enhance membrane fluidity and permeability, as well as its ability to extract membrane components such as phospholipids (Budisa and Schulze-Makuch, 2014; Jauhar et al., 2020). Wei et al. (1991) initially investigated the inactivation of L. monocytogenes and Salmonella in spiked chicken meat using SC-CO2 treatment, and 1–2 Log CFU/g of L. monocytogenes and Salmonella were reduced at 13.7 MPa and 35°C for 2 h. Furthermore, Ferrentino et al. (2013) reported that the growth of L. monocytogenes in dry-cured ham was reduced by 3 Log CFU/g at 45°C and 12 MPa for 5 min, and by 7 Log CFU/g at 50°C and 12 MPa for 15 min.
The application of cold plasma treatment has generated significant attention as a low-energy, non-thermal, and eco-friendly technique (Koddy et al., 2021). Previous studies have shown that the application of cold plasma can extend the storage duration of food products by inactivating bacteria and enzymes, while maintaining the overall quality of the food (Koddy et al., 2021; Zhang et al., 2021). The cell membrane and enzymes are predominantly damaged by reactive nitrogen species (RNS) and reactive oxygen species (ROS) during cold plasma treatment (Kang et al., 2021; Liao et al., 2017). Kim et al. (2011) reported a decrease of about 1–2 Log CFU/g for L. monocytogenes, Esherichia coli, and Salmonella on sliced bacon when treated with He and He/O2 plasmas. Ulbin-Figlewicz and Jarmoluk (2014) found a notable reduction of 2 Log CFU/g for Y. enterocolitica within 2 min and 2 Log CFU/g for P. fluorescens after 5 and 10 min of exposure to cold plasma for beef.
Bacteriophage (Phage) refers to a virus that uses bacteria as a host, and when infected with a specific bacterium, it has a life cycle of self-proliferating within the bacterium and lysis the bacterium (Cooper, 2016). Phages are increasingly being applied as a biological control method to improve the microbiological safety in the food industry. Currently, phages targeting bacteria such as L. monocytogenes are being sold with approval from the Food and Drug Administration (Moye et al., 2018). LISTEX P100 phage is one of the phages that fight against L. monocytogenes, and effectively reduced L. monocytogenes (2.5 Log units reduction) that had been artificially contaminated in Brazilian fresh sausages (Rossi et al., 2011). Commercial phages based on LISTEX P100 are safe enough to be registered as GRAS (Sillankorva et al., 2012). Mohammadi et al. (2022) examined phages effect of C. perfringens lysis, and phages induced survival of C. perfringens in pasteurized milk and chicken meat. The effect of phages to lyse bacteria becomes stronger when bacteria are metabolically active, so the effect is better at room temperature or 37°C rather than at low temperatures (Cooper, 2016; Tomat et al., 2018). Since decreased metabolism of bacteria means decreased metabolism of phages, the latency period of phages may be somewhat longer at low temperatures. Nevertheless, since the bacterial lytic ability of phages is clearly observed even at low temperatures (Cooper, 2016), it may be effective in controlling the growth of psychrotrophic bacteria.
High-pressure processing (HPP) is a non-thermal technique that changes protein structure, causes protein denaturation, and lowers enzyme activity in microorganisms in order to prevent the growth of pathogenic psychrotrophic bacteria (Hurtado et al., 2019; Wiśniewski et al., 2024). HPP increases the duration that various foods, including seafood, dairy products, meat products (RTE sliced deli meat, dry-cured meat, and hotdog products), and liquid products (fruit juices and purees), may be stored without spoiling. The storage duration of products preserved with this technology is a few days to a few weeks, and they should be kept at a temperature below 7°C (Silva and Evelyn, 2023). Park et al. (2022) reported a significant reduction in L. monocytogenes in raw beef when treated with HPP for 2 to 7 min at 500 MPa and 4°C, decreasing from 3.9 to 6.5 Log CFU/g. In contrast, Stratakos et al. (2019) reported that extending the duration of HPP treatment from 3 to 5 min at pressure of 400, 500, and 600 MPa at 18°C in raw milk only slightly increased L. monocytogenes decline from 5.7 to 5.9 Log CFU/g. However, HPP has several limitations, including difficulties in commercialization due to high installation and maintenance costs (Aganovic et al., 2017). Furthermore, HPP is ineffective against spores and certain enzymes that are resistant to pressure, and it may induce color changes in some animal foods (Bolumar et al., 2020; Myers et al., 2013).
Ohmic heating is an innovative technique for heating food substances promptly, uniformly, and efficiently and is effective at inactivating microorganisms (Richa et al., 2017). The importance of the relationship between metallic prosthetic groups (polyphenol oxidase, lipoxygenases, and alkaline phosphatase) and electric current was emphasized by Makroo et al. (2020). Ohmic heating, depending on variables such as electrical conductivity, time, and electric field strength, effectively eliminates pathogens (L. monocytogenes, E. coli, and Salmonella) and spoilers (Leuconostoc mesenteroides and P. aeruginosa) in animal-derived foods (Lee et al., 2012; Saxena et al., 2016). Salmonella in baby formula and Streptococcus thermophilus in milk were reduced by about 5 Log CFU/mL at 60°C in 2.91 min and 15 min, respectively, using ohmic heating, which demonstrated a more intense inactivation rate than conventional heating (Pires et al., 2021; Sun et al., 2008). Furthermore, ohmic heating reduced P. aeruginosa in meatball samples by 3 Log CFU/g at 125°C for 5 min (Mitelut et al., 2011).
Ultraviolet (UV) light, with wavelengths ranging from 100 to 400 nm (Barba et al., 2017), has been used to increase the storage duration of various animal-derived foods by bactericidal inactivation and enzyme inhibition (Manzocco et al., 2009; Monteiro et al., 2020; Visuthiwan and Assatarakul, 2021). UV light can deactivate microbial enzymes through: (1) UV radiation is absorbed by chromophore groups or proteins, which produces excited states or radicals, and (2) proteins can be indirectly oxidized by singlet oxygen, which is formed from other chemicals that absorb light energy. These actions can cause oxidative stress, leading to alterations in the three-dimensional conformation of proteins and a decrease in their catalytic activity (Lante et al., 2013). UV-C light decreased the counts of L. monocytogenes, Pseudomonas spp., and β-lactamase producing bacteria from 1.1 to 2.8 Log CFU/cm2 at 0.05 to 3 J/cm2 (10 mW/cm2, from 5 to 300 s; McLeod et al., 2018). Additionally, Brochothrix thermosphacta and Y. enterocolitica counts were decreased by up to 1.1 Log CFU/g and 0.8 Log CFU/g, respectively, by UV-C light during refrigerated storage at concentrations of 408 and 4,080 mJ/cm2 (Reichel et al., 2020).
Conclusion
Psychrotrophic bacteria present a significant challenge in maintaining the safety and quality of animal-derived foods during storage and transportation, particularly under refrigerated conditions. Understanding the characteristics and prevalence of these bacteria as well as their contamination patterns in various animal resources is crucial for implementing effective control measures. Nonthermal techniques offer promising alternatives to traditional thermal techniques for reducing psychrotrophic bacterial contamination in animal-derived foods while preserving their sensory and nutritional properties. Further research and implementation of these technologies are essential to ensure the microbiological safety and storage duration of animal-derived products in the food industry.