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Open AccessReview

Detection of Bacterial Pathogens and Antibiotic Residues in Chicken Meat: A Review

1
School of Bioengineering & Food Technology, Shoolini University of Biotechnology and ManagementSciences, Solan 173229, India
2
School of Biological and Environmental Sciences, Shoolini University of Biotechnology and ManagementSciences, Solan 173229, India
3
Department of Agriculture, Sri Guru Teg Bahadur Khalsa College, Sri Anandpur Sahib, Punjab 140117, India
4
Department of Chemistry, Faculty of Science, University of Hradec Kralove,50003 Hradec Kralove, Czech Republic
5
School of Water, Energy and Environment, Cranfield University, Cranfield MK43 0AL, UK
6
Department of Biological Engineering, College of Engineering, Konkuk University, Seoul 05029, Korea
7
School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, Punjab 144411, India
8
Department of Biotechnology, TIFAC-Centre of Relevance and Excellence in Agro and Industrial Biotechnology (CORE), Thapar Institute of Engineering and Technology, Patiala 147001, India
9
Department of Biotechnology, Himachal Pradesh University, Summer Hill, Shimla 171005, India
*
Authors to whom correspondence should be addressed.
Foods 2020, 9(10), 1504; https://doi.org/10.3390/foods9101504
Received: 14 September 2020 / Revised: 15 October 2020 / Accepted: 16 October 2020 / Published: 20 October 2020

Abstract

Detection of pathogenic microbes as well as antibiotic residues in food animals, especially in chicken, has become a matter of food security worldwide. The association of various pathogenic bacteria in different diseases and selective pressure induced by accumulated antibiotic residue to develop antibiotic resistance is also emerging as the threat to human health. These challenges have made the containment of pathogenic bacteria and early detection of antibiotic residue highly crucial for robust and precise detection. However, the traditional culture-based approaches are well-comprehended for identifying microbes. Nevertheless, because they are inadequate, time-consuming and laborious, these conventional methods are not predominantly used. Therefore, it has become essential to explore alternatives for the easy and robust detection of pathogenic microbes and antibiotic residue in the food source. Presently, different monitoring, as well as detection techniques like PCR-based, assay (nucleic acid)-based, enzyme-linked immunosorbent assays (ELISA)-based, aptamer-based, biosensor-based, matrix-assisted laser desorption/ionization-time of flight mass spectrometry-based and electronic nose-based methods, have been developed for detecting the presence of bacterial contaminants and antibiotic residues. The current review intends to summarize the different techniques and underline the potential of every method used for the detection of bacterial pathogens and antibiotic residue in chicken meat.
Keywords: antibiotics; multidrug-resistant bacteria; biosensors; chicken; chromatography-based method; molecular-based methods; immunology-based method antibiotics; multidrug-resistant bacteria; biosensors; chicken; chromatography-based method; molecular-based methods; immunology-based method

1. Introduction

Globally, both developed and developing countries predominantly consume chicken as a meat product. According to the report of Global Livestock Counts, there are around 19 billion chickens in the world [1]. In 2019, consumption of chicken meat in the USA was 16,700 metric tons; in the European Union it was 11,636 metric tons, and in India, it was 4347 metric tons [2]. Chicken meat is stated as white meat, which makes it distinct from other meats like lamb and beef, owing to its low iron content and its lack oftrans-fat. Moreover, no trans-fats make it a healthier option as they are associated with cardiovascular disease, whereas beef and lamb meat contains a high amount of trans-fat [3].
Over the past few decades, different countries have undergone substantial changes in eating habits. With changing lifestyles, people now frequently go out for meals, and middle-class people most often consume chicken meat. Additionally, the relocation of people from rural to urban areas has also contributed to the change in eating patterns [4]. Innovative distribution, preparation and food production techniques have also been found to be responsible for these changes. If necessary preventive measures are not taken into account during marketing, processing and production of chicken, there are chances that chicken eggs and meat can get contaminated via infectious agents which could be pathogenic to humans [4]. Campylobacter and Salmonella are the common pathogenic microbes accounting for >90% cases of food poisonings associated with bacteria and are considered responsible for food safety hazards worldwide [4]. The list of outbreaks associated with chicken/meat consumption has been compiled in Table 1.
Escherichia coli and Salmonella are the predominant bacteria found in the intestines of both animals and humans. These microbes serve as an indicator of fecal contamination in food and water bodies due to the untreated discharge of municipal wastewater in natural water streams [1]. Chicken with E. coli contamination shows the inadequate practice of hygiene in slaughterhouse and trading areas [1]. As per the report of the European Food Safety Authority (EFSA), Campylobacter spp. is a leading food-borne hazard associated with poultry meat, due to cross-contamination during processing in contaminated broiler and the packaging of ready-to-use foods [19]. Moreover, it has been estimated that 50–80% of cases of campylobacteriosis in humans are due to poor handling of the chicken reservoir, whereas, 20–30% can be attributed to consumption of contaminated broiler meat and poor handling during meat preparation [20].
Therefore, to circumvent the problem of contamination, poultry industries have started using antibiotics to enhance the production of meat using enriched feed for disease prevention [21]. The common antibiotics used in chicken farming, along with their biological effects, are shown in Table 2.
Productive application of antibiotics in poultry has substantially improved the growth and health of birds by boosting their immune system [21]. However, the presence of antibiotic residues in meat imposes a problem in humans, as antibiotic residues can elicit an allergic response, imbalance of intestinal microbiota and in few cases, it can lead to the development of resistance against antibiotics [33]. Hence, the purpose of this review is to provide complete knowledge of the conventional and advanced methods available for the detection of bacterial pathogens and antibiotic residue in chicken meat.

2. Source of Bacterial Contamination

According to published literature, there are only two ways of inducing infection in eggshell by bacteria, i.e., horizontal or vertical transmission. In vertical transmission, it occurs through the systemic infection of ovaries or during intercourse with a contaminated cloaca, touching the vagina and lower regions of the oviduct [34]. During the vertical transmission, the yolk, albumen and membrane come into direct contact with the contaminants due to bacterial infection of reproductive organs like oviduct tissue and ovaries. As a result, eggs get contaminated before the formation of the shell [35]. Campylobacter and Salmonella are the bacterial species which predominantly contaminates the eggs via this route of infection. On the other hand, horizontal transmission takes place through broken eggs, blood, hands, insects and water.
Additionally, it also gets transmitted horizontally due to the interaction with dust, feces and soil during transportation and from caging material [34]. The ubiquitous nature of bacteria allows them to contaminate boiler meat [36]. Moreover, the cut meat, as well as the equipment used for cutting, comes into direct contact with air, which easily contaminates the meat. In fresh meat, bacteria are mostly found on the surface instead of inside the meat [37]. On the other hand, in processed meat, as they are marinated, the bacteria get easily penetrated in the muscles [38]. Although water has washing effects, and it decreases the bacterial load during the processing of meat, it also increases the chances of cross-contamination between carcasses [39,40].

3. Conventional Methods of Microbial Detection

3.1. Culture-Based Method

Back in the 19th century, bacterial culture was first introduced. Before that, many biologists were trying to grow bacteria on food or other material on which microbes were first observed [41]. Culture-based methods are the oldest methods used for detecting microbes, even pathogenic strains, as their result confirms the presence of a particular microbe [42]. Culture-based methods are a subtle but time-intensive process [43]. Some bacterial species require an enrichment broth or buffer before their isolation on differential media and serological confirmation [44]. Numerous chicken-borne pathogenic bacteria species confirmed via a culture-based method have been enlisted in Table 3.
Salmonella spp. isolation from chicken, egg and meat products buffered with peptone water, selenite cystine, tetrathionate (TT) or Rappaport-Vassiliadis (RV) are used as the enrichment broth, and brilliant green agar, hektoen enteric agar and xylose lysine deoxycholate (XLD) agar are used as selective media [57,64,68]. Selective media like blood agar, Eosin Methylene Blue (EMB) Agar or MacConkey are used for isolating E. coli [51,60]. Moreover, Campylobacter spp. as well as Enterococcus spp. are isolated with the help of enterococcosel agar and Preston agar [65,69]. Furthermore, Staphylococcus species (both coagulase-positive and negative) are extensively isolated by Baird parker agar and mannitol salt agar [70].

3.2. PCR-Based Method

A polymerase chain reaction (PCR) is also a detection approach as it allows us to robustly replicate the desired DNA segment and serve the dual purpose, i.e., detection and identification of particular species [71]. This process uses a specific set of primers for replicating the desired segment of DNA by following three steps: denaturation, annealing and extension. All these steps work under the desired range of temperature, i.e., denaturation: 90–95 °C (high-temperature), annealing: 55–60 °C (low temperature) and extension: 70–72 °C (intermediate temperature) [72]. PCR approaches are sensitive, precise, detect different pathogenic microbes simultaneously and minimize the risk of contamination, but require highly trained personnel and a robust thermal cycler [43]. The chicken-borne bacterial pathogens identified using different types of PCR have been enlisted in Table 4.
Arunrut et al. [82] developed a real-time loop-mediated isothermal amplification (LAMP) procedure for the identification of Salmonella spp. with the help gene62181533 as a primer sequence. This procedure did not display any cross-reactivity with other pathogenic bacteria. Moreover, spiked chicken sample results obtained for the accuracy, specificity and sensitivity of this procedure were found to be 90.83%, 86.79% and 94.02%, respectively. Alves et al. developed a multiplex-PCR procedure, using specific primers for Campylobacter spp., i.e., OT1559 and 18-1 primers, as well as specific primers for Salmonella spp., i.e., Styinva-JHO-Right and Styinva-JHO-Left primers [83]. The specificity of the assay was found to be 100% and it was able to detect 1 cfu/mL of Salmonella spp. (after nonselective enrichment) and 102 cfu/mL of Campylobacter spp. (after selective enrichment). Another study was conducted for comparative analysis of four PCR kits that are commercially available for the detection of E. coli, E. coli O157-H7, Salmonella spp., and S. aureus, in both artificially and naturally contaminated chicken products. The specificity of the kits for E. coli O157-H7, E. coli, Salmonella spp. and S. aureus in chicken products were found to be 95%, 97%, 96% and 100%, respectively [84].

3.3. Array-Based Method

Array signifies miniature, the two-dimensional high-density matrix of DNA fragments printed over the silicon or glass slide in a distinctive manner. This chip is used for the hybridization of DNA fragments to fluorescent-labelled probes for detection via advanced instrumentation and software [85]. For instance, Microbial Diagnostic Microarrays (MDMs) employs three different kinds of probes like short oligonucleotides, long oligonucleotides and PCR amplicons. Short oligonucleotides show a low binding affinity due to mismatch in 1–2 nucleotide; hence amplification with PCR becomes evident [85]. On the other hand, long oligonucleotides and PCR amplicons show a higher binding affinity and a lower discrimination potential. Therefore, both long oligonucleotides and PCR amplicons can be used in combination with generic amplification approaches like whole genome amplification (WGA). This method is array-based and can robustly identify pathogens. However, this technique is expensive and needs skilled personnel [43]. A list of chicken-borne bacterial pathogens assessed by different types of arrays is shown in Table 5.
Quiñones et al. [89] developed a DNA oligonucleotide array for simultaneous detection of Arcobacter and Campylobacter in retail chicken samples. The probes selected for developing this array were having high affinity for both housekeeping and virulence-associated genes in Arcobacter butzleri, Campylobacter coli and Campylobacter jejuni. Another group of researchers developed a DNA-based bead array for simultaneous determination of 11 pathogens viz. Escherichia coli, E. coli O157: H7, Listeria grayi, L. ivanovii, L. innocua, L. welshimeri, L. monocytogenes, L. seeligeri, Salmonella spp., S. aureus and methicillin-resistant S. aureus [90]. Apart from this, the bead array method has been developed based on fluorescent-labelled paramagnetic beads attached to unique stretches of 24 oligonucleotide (anti-TAG) sequences. These unique 24 oligonucleotide sequences further bind with a biotinylated PCR product containing a complementary TAG sequence. In this method, R-phycoerythrin labelled streptavidin was utilized to detect the presence of biotinylated PCR products. This method exhibited a relative sensitivity, relative accuracy and relative specificity of 95%, 96% and 100%, respectively.

3.4. ELISA-Based Method

One of the most reliable immunoassays used todate is the enzyme-linked immunosorbent assay (ELISA). In this approach, purity of antibody plays a vital role in the specificity, sensitivity and accuracy of this approach [42]. Polyclonal antibodies are not preferred in this approach as multiple epitopes affects specificity as well as the sensitivity of the reaction. The application of different substrates in ELISA has an additional advantage because specific substrates bind with respective conjugate and produce coloration, which could either be read through an ELISA reader in wavelength and color change can be visualized with the naked eye [42]. ELISA can precisely detect the microbial contaminants as well as their toxins and ELISA kits have been developed for identifying pathogenic microbes and toxins according to the requirement [43]. Various ELISA-based methods developed for the detection of chicken-borne pathogenic bacteria have been compiled in Table 6.
Schneid et al. [91] developed an indirect ELISA approach to detect Salmonella enterica serovar Enteritidis in a sample of chicken. For this, to improve the sensitivity, four wells of polystyrene plates were filled with wholly killed cells of bacteria along with monoclonal antibodies and were incubated at 37 °C for 1 h. After incubation, the prepared sample was washed with protein A-peroxide conjugated antibodies, and again the sample was incubated at 37 °C for 1 h, to observe the result by adding chromogenic substrate to the treated sample. Out of 154 tested samples, approximately 26% showed the positive result for the presence of bacteria via ELISA. Lilja and Hänninen [93] conducted another study to assess the quality of a commercially available ELISA kit to identify Campylobacter spp. contamination in retail meat samples of chicken. Out of 97 tested samples, only 13 showed the positive result for Campylobacter by ELISA. Vanderlinde and Grau [95] conducted a similar study, but they used the ELISA kit for the detection of Listeria spp. in the retail meat sample, for which 72 samples showed a positive result for the presence of Listeria spp. out of 74 samples.
Charlermroj et al. [96] conducted the study by using an immune-bead array approach for the simultaneous detection of three food-borne pathogens, i.e., Campylobacter jejuni, Salmonella spp. and Listeria monocytogenes. This array method used the sandwich ELISA principle for the detection of these pathogenic bacteria. In this study, three sets of fluorescently labelled beads were used. Each labelled bead was attached to capturing antibodies specific to pathogenic bacteria, whereas detecting antibodies were labelled with R-phycoerythrin (RPE) having the affinity and specificity for capturing antibodies. This process allows the detector to detect the signals of both labelled beads as well as that of the RPE molecule attached to the detecting antibody. This method was used for assessing the presence of pathogenic bacteria in both ready-to-cook (RTC) as well as ready-to-eat (RTE) chicken products. Moreover, this method was found to be effective in detecting spiked pathogenic bacteria at 1cfu in both types of food sample [96].

4. Advanced Methods of Detection

4.1. Aptamers Based Method

Aptamers are short stretches of single-stranded biomolecules (ssRNA or ssDNA) of 15–80 nucleotide length. These form a three-dimensional structure, which can interact with targeted molecules via base stacking, electrostatic interactions, Van der Waals forces, hydrogen bonding or a combination of these interactions [97]. Synthetic ssRNA or ssDNA libraries are evaluated for identifying aptamers via a process named “Systematic Evolution of Ligands by EXponential enrichment (SELEX)” [98]. Moreover, these aptamers can be developed according to targets ranging from whole cells to ions. Although numerous, aptasensors have been developed for detecting various bacterial pathogens [99,100,101]. Aptamers work in diverse ecological conditions, have a long shelf life and are applicable to a variety of targets. However, RNA-based aptamers have a drawback. RNA-based aptamers degrade very rapidly due to the presence of nucleases in biological media, and in blood in particular, which imposes as a serious issue. Moreover, there are cross-reactivity issues with these aptamers, which restrict the practical application of this approach [102,103]. Aptamers developed for detecting chicken-borne bacterial pathogens have been listed in Table 7.
Renuka et al. [108] developed fluorescent dual aptasensors for onsite sensitive and robust detection of E. coli O157: H7 and assessed its authenticity on different food matrices. In this ssDNA, aptamers labelled with biotin were immobilized on silane-glutaraldehyde functionalized glass slides, which act as capturing ligands and aptamers labelled with quantum dots (QDs) act as revealing probes. The method did not show any cross-reactivity with other pathogenic bacteria. Moreover, a spiked meat sample of chicken showed arecovery rate of 76%. Another group of researchers developed an aptamer linked immunosorbent assay (ALISA) for the detection of enterotoxin B synthesized by Staphylococcus sp. in ready-to-eat (RTE) chicken [109]. This aptamer-based method was found to be cost-effective, thermally stable and sensitive in contrast to PCR assays. Additionally, aptamers can be developed for the molecules which do not have available antibodies.
Feng et al. [110] reported the precise and efficient system based on loop-mediated isothermal amplification (AMC-LAMP) and magnetic capture aptamers for the detection of L. monocytogenes in the raw chicken sample. For this, a set of aptamers (four different types of aptamers having high binding affinity for L. monocytogenes) conjugated to magnetic beads, was used for entrapping L. monocytogenes. After entrapping, the aptamer system is incubated at room temperature for 45 min. Later, the incubated sample was used for direct DNA isolation. After isolation, LAMP assays were carried out at 63 °C for 40 min, and the amplified product was visualized with the help of SYBR Green® I staining. The detection limit of AMC-LAMP was found to be 5 cfu mL−1 with an assay time of 3 h.

4.2. Biosensor-Based Method

The biosensor is a fabricated device encompassing biological entities like an antibody, nucleic acid, receptor or any other bio-recognizing entities, which interacts with an analyte and elicits a response and this response is transformed to an electrical signal via the transducer [111]. The response generated by a biosensor is precise, robust and free from noise and has a precise detection limit. These biosensors can detect a bacterium cell in a rationally small volume and can distinguish one bacterial species from another, and even in the strain of the same species [112,113]. Biosensors are automated systems which demand minimal operator interaction. Nowadays, inexpensive biosensors are available with a simple, portable and easy-to-use design. However, major challenges linked with these biosensors are sample pretreatments like the enrichment of bacteria [114,115]. Numerous biosensors developed for detecting chicken-borne bacterial pathogens have been shown in Table 8.
Kim et al. [123] developed colourimetric-based aptasensors for rapid on-site detection of Campylobacter coli and Campylobacter jejuni in meat samples of chicken. For this, the two-stage aptasensing platform was fabricated using gold nanoparticle (AuNPs), as they aid in a color change from red to purple due to the accumulation of AuNPs. Moreover, this device does not require pH optimization or additional time for aptamers to get absorbed on AuNPs. This colourimetric-based aptasensor has a high specificity towards viable cells of C. coli and C. jejuni. In another study, the electrochemical impedance spectroscopy technique was used to check the presence of E. coli K12 in a meat sample of frozen chicken [124]. For this, antibodies synthesized against E. coli were immobilized on to the gold surface via a physisorption method. The binding of antibodies against E. coli and E. coli K12 on the gold surface was determined with the detection limit of 103 cfu mL−1. Huang et al. [125] developed an enzyme-free biosensor for precise and targeted detection of Salmonella typhimurium with the help of curcumin (CUR) and 1,2,4,5-tetrazine (Tz)–trans-cyclooctene (TCO) acting as a signal reporter and a signal amplifier, respectively. For fabricating this biosensor, nanoparticles containing bovine serum albumin (BSA) and CUR were reacted with TCO and Tz to synthesize Tz-TCO-CUR conjugates. This Tz-TCO-CUR conjugate was further conjugated with anti-S. typhimurium polyclonal antibodies (pAbs) to develop a CUR-TCO-Tz-pAb conjugate.
Furthermore, monoclonal antibodies (mAbs) specifically against S. typhimurium were conjugated with Magnetic nanoparticles (MNPs) via streptavidin-biotin binding for effective and targeted separation of S. typhimurium. Then, CUR-TCO-Tz-pAb conjugates were reacted with MNP-conjugate. The conjugation of both conjugates in the presence of NaOH led to the color change, and color change was used for the determination of S. typhimurium contamination. The detection limit of this biosensor was found to be 50 cfu mL−1 in the meat sample of chicken spiked with S. typhimurium.

4.3. Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry-Based Method

Todate, MALDI-TOF MS is the most predominantly used method to analyze the biomolecules [126]. It works on the principle of ionization of the co-crystallized sample via short laser pulses. As a result, ion gets accelerated, and the time taken by biomolecules to reach the detector is measured. This approach is useful for determining the mass of peptide and protein, along with the mass of unknown protein [127]. Now, it has also been used for differentiating various bacterial species [126]. On the other hand, MALDI-TOF MS can provide an analysis of the peptide fingerprints of microbial proteins that are well-conserved within a species, which enables the characterization of these proteins and their correlation with different species [128]. However, there are a few exceptions, where this method is unable to discriminate between related species because of the inherent similarity of the organisms. For instance, MALDI-TOF MS is incapable of differentiating Shigella from E. coli. This could likely be because these may not be two species, but one, as it has been stated by taxonomists [128]. Another reason for incorrect identification of similar species could be due to a lack of a consolidated knowledgebase.
Rasmussen et al. [129] used MALDI-TOF MS to examine the presence of β-lactamases synthesized by E. coli in both local and imported chicken meat sold in the Ghana market. The result obtained revealed that 153 out of 188 samples contained E. coli, and out of this 29 E. coli showed the presence of β-lactamase. A similar study was conducted in Egypt on chicken meat bought from the retail shop to assess the presence of β-lactamase/carbapenemase-synthesizing Enterobacteriaceae species with the help of MALDI-TOF MS [130]. The result obtained revealed that 69 isolates out of 106 were a β-lactamase producer. In Thailand, MALDI-TOF MS was used to identify the bacterial contaminants present in chicken meat sold in the open meat market. The result obtained showed the presence of 11 different bacterial species viz. Aeromonas caviae, A. veronii, Citrobacter freundii, Enterobacter asburiae, E. coli, Klebsiella pneumoniae, Lactococcus lactis, Staphylococcus warneri, S. epidermidis, S. pasteuri and Serratia fonticola in chicken breast [131]. In Poland, the evaluation of chicken with MALDI-TOF MS revealed the presence of ciprofloxacin as well as tetracycline-resistant C. coli and C. jejuni [132].

4.4. Electronic Nose-Based Method

The term “Electronic Nose” is an array of chemical gas sensors with a broad spectrum of selectivity to measure the volatile mixture contained inside the headspace over the sample to interpret the presence of specific chemical gas via computer-assisted statistic processing tools [133]. In its working mechanism, the prime neurons, i.e., the chemical sensor of the electronic nose has a precise sensitivity towards different odors. The interaction among the gas sensor and odor compounds elicit the change in sensors, which generates an electrical impulse. The generated electrical impulse is further recorded by an analogue instrument with the secondary neurons. In this manner, signals generated by individual sensors form a unique pattern for the gaseous mixture and are deciphered via an artificial neural network (i.e., a multivariate pattern recognition method) [134].
Rajamaki et al. [135] used an electronic nose method to assess the quality of the modified atmosphere (MA)-packaged broiler chicken pieces. The results obtained from this study were also compared with the results of sensory, microbiological and headspace gas chromatography. In this study, the electronic nose method was found to be effective in distinguishing low-quality packed broiler chicken from freshly packed chicken either formerly or on-the-spot as the quality deteriorates. Timsorn et al. [136] modified the e-nose-based method by attaching it with eight metal oxide semiconductor (MOS) sensors to evaluate the freshness of chicken meat and the know population of bacterial contaminants on chicken meat stored at 4 °C as well as 30 °C for up to five days. The result obtained from this study showed a positive correlation (0.94) with the bacterial population on chicken, signifying that the e-nose method is an effective and robust approach to assess the bacterial population in chicken meat with a high accuracy.

5. Conventional Methods of Antibiotics Residue Detection

5.1. Microbial Inhibition Test

The microbial inhibition method is predominantly used for assessing the presence of antibiotic residues in food products of animal origin [137]. This method is also time-consuming and laborious like the culture-based method. The test is performed in both plate and test tubes and, in test tubes, the viable culture of bacteria is mixed with a pH or a redox indicator to detect the residues of antibiotics in food samples [138]. In Europe, a microbial inhibition test was conducted in the plate to check the presence of antibiotic residue in slaughtered animals [139,140]. Moreover, a 3-plate test cultured with three different bacterial species like Bacillus subtilis, Escherichia coli and Staphylococcus aureus was used to reveal the presence of antibiotic residues in the organs of poultry animals [141]. The European Union introduced four plate tests for detecting antibiotic residue in meat, in which one plate has a culture of Micrococcus luteus, and other three plates have a culture of Bacillus subtilis (Table 9) [142].

5.2. ELISA-Based Method

Shahbazi et al. [145] conducted an experiment by using the ELISA method to determine the level of tetracycline in a meat sample and reported the mean value to be 247.32 μg kg−1. Ramatla et al. [150] conducted a similar study, but they assessed the streptomycin residue level. The mean residue value determined for this study was found to be 647.09 μg kg−1, which was higher than the international maximum residue limits (MRL), i.e., 600 μg kg−1. Moreover, the concentration of sulphonamide was determined to be 61.01 μg kg−1 in the different organs of animals, which is below the recommended MRL, i.e., 100 μg kg−1. Additionally, the concentration of tetracycline was also determined and was found to be 168.02 μg kg−1. In another study, the residue level of chloramphenicol, streptomycin, sulfamethazine and tetracycline were determined and were found to be in the range of 74 ppb kg−1, 30–55 ppb kg−1, 1.07–5.60 ppb kg−1 and 35–56 ppb kg−1, respectively. These values were lower than the acceptable limit, i.e., 100 ppb kg−1 established by the EU’s law of drugs [151].
Zhang et al. [152] determined the spiked chloramphenicol recovery rate in chicken muscles in the range of 97–118% via chemiluminescent-ELISA. Various ELISA-based methods used to determine the residues of the antibiotics in chicken meats are shown in Table 10.

5.3. Thin-Layer Chromatography (TLC)-Based Method

TLC is the most predominantly used laboratory method worldwide for food as well as quality control analysis [157]. Different adsorption, ion-exchange and partition layers are used for analyzing the food material, but most of the separations are carried out on a stationary phase with pre-coated silica gel. Alumina and cellulose are used as a stationary phase for some food samples. It is a one-dimensional process in which samples ascend from the gravity flow with the help of the mobile phase in the glass chamber. In the detection of analytes, specific chromogenic or fluorogenic reagents are used, and fluorescence detection is highly recommended due to its high sensitivity and specificity. For instance, a high performance-TLC (HPTLC) method was used to examine the presence of nitroimidazoles [157]. The major advantage of TLC is that it is more time-efficient compared with traditional paper chromatography. Minimal equipment is required for the execution of the TLC procedure. For instance, it requires only a fume cupboard, a TLC plate and a TLC chamber. A chamber is an essential component to run a sample that is to be separated into its components. It is effective even if the sample is scarce. Despite its simplicity and convenience, it has a limitation that it cannot differentiate between the enantiomeric and isomeric forms of a compound. Another challenge with TLC is its requirement for pre-known Rf values [158]. Different TLC-based methods used for detecting antibiotics residue in chicken meats have been compiled in Table 11.

5.4. High-Performance Liquid Chromatography (HPLC)-Based Method

During the 1990s, HPLC gained significant attention as a screening technique due to its automated mode of operation [165]. This approach works on the same principle as chromatography and the detector can be changed according to the nature of the sample under evaluation, as the selection of the detection system is essential for its sensitivity and selectivity. Few samples are not detected via absorbance, and in this case, chromophore, UV-absorbing or fluorescent compounds are used for amending its refractive index or fluorescence, making it suitable for detection [166]. The major advantage of HPLC is its ability to detect multiple residues simultaneously in the sample in a short period. Moreover, developments of high-speed HPLC are highly efficient and require less time for analysis.
Additionally, this system is computer-controlled and fully automated, which makes it an advanced screening technique [165]. HPLC is a costly approach; it requires expensive reagents, columns, a power supply and regular maintenance [167]. Different HPLC-based detection studies conducted to detect the presence of antibiotic residue in chicken meat have been shown in Table 12.
Shalaby et al. [169] used the HPLC approach to assess the presence of tetracycline residue in spiked chicken meat as well as in liver using methanol, acetonitrile and 0.03 M oxalic acid (0:8:92) as the mobile phase. This study revealed that the citrate buffer was more effective in comparison with McIlvaine’s buffer used for matrix extraction. The recovery rate of tetracycline was found to be in the range of 68.7–82.2%. Another study was conducted in which the recovery rate of ten different quinolones (ciprofloxacin, danofloxacin, enrofloxacin, difloxacin, flumequine, lomefloxacin, marbofloxacin, norfloxacin, oxolinic acid, sarafloxacin) were assessed and was found to be 72% in muscle spiked with ten quinolones [169]. In another HPLC-based study, acetonitrile was stated to be an elite extraction solvent for recovering the antibiotic residues of ampicillin, amoxicillin and amoxicillin metabolites from the tissue samples of chicken [172].

6. Advanced Methods of Detection

Biosensor-Based Method

Virolainen et al. [173] and Pikkemaat et al. [174] have published literature about the development of luminescent-based bacterial biosensors for detecting the tetracycline in meat samples. A list of other biosensors developed for the same purpose has been complied in Table 13.
An E. coli-based biosensor, in which plasmid containing the Photorhabdus luminescence-derived bacterial luciferase operon was used, was placed in such a way so that tetracycline-responsive elements of transposon Tn10 could control it [173]. Additionally, this controlled system also contains repressor protein TetR, which has an affinity for the operator sequence in PtetA and helps in reducing the TC binding, which allows transcription from the promoter. Furthermore, usage of bacterial luciferase operon provides a self-luminescent property without any substrate addition to the strain. This characteristic feature makes these cells the sensor element, as they serve as a reagent in the assay.
Gan et al. [176] developed an innovative electrochemical sensor to determine the presence of tetracycline. In this method, the substantial change shown due to the interaction between iron/zinc cations-exchanged montmorillonite layer and tetracycline was measured. Another study stated about amperometric chloramphenicol (CAP) immunosensor for the detection of CAP developed by immobilizing anti-chloramphenicol acetyltransferase (anti-CAT) antibodies on the surface of cadmium sulfide nanoparticles (CdS) modified-dendrimer, which is further bonded with poly 5, 2′: 5′, 2′′-terthiophene-3′-carboxyl acid (poly-TTCA) (conducting polymer). The selection of CdS nanoparticles, dendrimers and gold nanoparticles and their deposition on the polymer layer is made to improve the sensitivity of the probes of this sensor [178].

7. Future Prospect

Lately, molecular-based tests, especially mRNA-based tests, have emerged as powerful tools for the robust detection of pathogenic microbes. A limitation of the mRNA-based tests is the instability of the mRNA, which presents as a pitfall in the assessment of food-borne pathogens. Over the last few decades, the lytic phage-based approaches have been developed for the easy and accurate detection of food-borne pathogens in various matrices. Therefore, the combination of both phage amplification and lysis with enzyme assays, PCR/qPCR or immunoassays could be promising alternatives for the detection of viable pathogenic microbes in food. Even aptamer technology and high-throughput sequencing (HTS) approaches have been developed for detecting pathogenic microbes. HTS is now proclaimed to be a robust sequencing approach to sequence a small stretch of genes. The major advantage of HTS is its large sequence output in terms of its entire genome or the large targeted region over the Sanger sequencing method. Hence, the subsequent advancements in the mRNA-based test, phage amplification and lysis with enzyme assays, PCR/qPCR, immunoassays, aptamer technology and HTS for targeted monitoring of pathogenic microbes from different food samples can uplift the detection procedure to a new level. In the future, new rational biosensing and nanomaterials will also likely be used to achieve the robust detection of pathogenic microbes with great precision ([181,182]).

8. Conclusions

In the last few decades, there have been substantial improvements in the techniques used for identifying bacterial pathogens and antibiotic residue in food samples and especially in meat. Even though there are limitations associated with culture and microscopy, they are still the predominantly used detection techniques. Genetic and PCR are an effective non-culturable technique used for presently determining the bacterial pathogen, and on the other hand, MS techniques have emerged as an effective method for identifying microorganisms and detecting antibiotic residues. However, these approaches are limited to assess the pure cultures and are ineffective indeciphering the complex samples. To overcome this, chromatography-based methods like TLC and HPLC have been simplified and have eased the challenge associated with MS techniques. In the future, the progressive development and combination of these techniques and instruments will advance the ability to detect the pathogenic microbes and antibiotic residues.

Author Contributions

Conceptualization, D.K., S.K.B., V.K. and K.K.; Manuscript writing, H.K.; Manuscript editing, K.B., T.K., E.N., D.S.D., C.C., S.G. and R.V.; Critical revising, D.K., E.N., S.K.B., R.S., T.C.B., V.K. and K.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the University of Hradec Kralove (VT2019–2021).

Acknowledgments

We acknowledge the University of Hradec Kralove (VT2019–2021).

Conflicts of Interest

The authors declare no conflict of interest.

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Table 1. Disease outbreaks due to chicken/meat consumptions.
Table 1. Disease outbreaks due to chicken/meat consumptions.
CountryYearSourcePathogenDiseaseConfirmed CasesReference
Canada2015–2019Frozen raw breaded chicken productsSalmonella enteritidisSalmonellosis584[5]
United Kingdom2017Chicken liver dishesCampylobacter spp.Campylobacteriosis7[6]
India2016Cooked chickenClostridium perfringens
or Bacillus cereus
Food poisoning68[7]
Zimbabwe2014Stewed chickenStaphylococcus aureusFood poisoning53[8]
United States2013–2014Chicken dishesSalmonella HeidelbergSalmonellosis634[9]
Australia2012Chicken liver pâtéCampylobacter spp.Campylobacteriosis15[10]
United States2012Undercooked chicken liverCampylobacter jejuniCampylobacteriosis6[11]
United Kingdom2011Undercooked chicken liver pâtéCampylobacter coli, Campylobacter jejuniCampylobacteriosis22[12]
United Kingdom2011Chicken liver parfaitCampylobacter spp.Campylobacteriosis3[13]
Australia2009Chicken wrapsListeria monocytogenesListeriosis36[14]
United Kingdom2009Chicken liver pâtéSalmonella typhimurium DT8, Campylobacter spp.Campylobacteriosis, Salmonellosis14[15]
United Kingdom2007Lemon-and-coriander chicken wrapsVerotoxin-producing Escherichia coli O157Diarrhoea12[16]
Australia2005Chicken dishesCampylobacter spp.Campylobacteriosis11[17]
United Kingdom1984–1985Live chickenCampylobacter jejuniCampylobacteriosis19[18]
Table 2. Common antibiotics used in chicken farming.
Table 2. Common antibiotics used in chicken farming.
Name of Antibiotic ClassTypes of AntibioticsMode of AdministrationBiological EffectReference
TetracyclinesTetracycline; Oxytetracycline; Doxycycline; ChlortetracyclineOral and intramuscularBacteriostatic activity against a wide array of Gram-positive and-negative bacteria, mycoplasmas, some mycobacteria, as well as several protozoa and filariae[22]
MacrolidesTylosin; TilmicosinOralAntibacterial activity against pathogens such as Gram-positive and-negative bacteria[23]
LipopeptidesPolymyxinsOralAntibacterial activity against Gram-negative bacteria[24]
PenicillinsPenicillinOralGrowth promoter[25,26]
Folate Pathway InhibitorsTrimethoprimOralTreatment of respiratory, gastrointestinal infections[27]
QuinolonesEnrofloxacin; Ciprofloxacin; DanofloxacinOralGrowth promoter and antibacterial activity against pathogens such as Gram-positive and-negative bacteria[28,29,30]
AminoglycosidesNeomycin; StreptomycinOralAntibacterial activity against Gram-negative bacteria[31]
LincosamidesLincomycinOral and intramuscularAntibacterial activity against Gram-positive bacteria[32]
Table 3. Isolation and identification of pathogenic bacteria using different selective and deferential media along with their antibiotic resistance pattern.
Table 3. Isolation and identification of pathogenic bacteria using different selective and deferential media along with their antibiotic resistance pattern.
Source of IsolationSite of IsolationTypes of MediumIncubation Temperature/TimeTypes of BacteriaAntibiogram AssayAntibiotics ResistanceReference
EggShell surface, yolk, albuminMacConkey agar, Eosin methylene blue (EMB) agar, Bismuth sulphite agar, Salmonella Shigella agar, Xylose lysine deoxycholate agar37 °C/24–48 hCitrobacter spp., Enterobacter spp., Escherichia spp., Klebsiella spp., Proteus spp., Shigella spp., Serratia spp.Disk diffusionCefixime, amoxicillin, amoxyclave[45]
Whole egg contentXylose Lysine Deoxycholate agar, MacConkey agar37 °C/24–48 hSalmonella typhi, Salmonella enteritidisDisk diffusionCo-trimoxazole, nalidixic acid, ampicillin, tetracycline, kanamycin[46]
Shell surface, interiorXylose lysine deoxycholate agar, Salmonella Shigella agar37 °C/24 hSalmonella spp.Disk diffusionTetracyclin, ampicillin, amoxicillin[47]
Shell surfaceEosin methylene blue (EMB) agar37 °C/24 hEscherichia coliDisk diffusionPenicillin, ciprofloxacin, rifampicin, kanamycin, streptomycin, cefixime, erythromycin, ampicillin, tetracycline[48]
Shell surfaceSalmonella Shigella agar37 °C/24 hSalmonella typhimurium, Salmonella enteritidisDisk diffusionErythromycin, ampicillin, penicillin, tetracycline[49]
Shell surface, yolk, albuminSalmonella Shigella agar, Xylose lysine deoxycholate agar, Bismuth sulphite agar35–37 °C/24 hSalmonella enterica subsp. salamae, Salmonella enterica subsp. indica, Salmonella paratyphi-A, Salmonella bongori, Salmonella choleraesuisDisk diffusionAmoxicillin, ampicillin[50]
YolkBlood agar, McConkey agar37 °C/24 hEscherichia coliDisk diffusionAmpicillin[51]
Interior contentXylose lysine deoxycholate agar, Bismuth sulphite agar37 °C/24 hSalmonella enteritidisMICAmpicillin, nalidixic acid, tetracycline[52]
Shell surface, interiorMcConkey agar37 °C/24 hEscherichia coli, Salmonella spp., Campylobacter spp. and Listeria spp. Enterobacter spp. Klebsiella spp.Disk diffusionStreptomycin, tetracycline, kanamycin[53]
Shell surfaceEosin methylene blue (EMB) agar37 °C/24 hEscherichia coliDisk diffusionAmpicillin, streptomycin, tetracycline[54]
Shell surface, interiorBrilliant green agar, McConkey agar, Salmonella Shigella agar37 °C/24 hSalmonella enteritidisDisk diffusionBacitracin, erythromycin, novobiocin[55]
Shell surface, yolkBlood agar, Mannitol salt agar37 °C/24–48 hStaphylococcus aureusDisk diffusionErythromycin, tetracycline[56]
Shell surface, yolk, albuminHektoen enteric agar37 °C/24 hSalmonella typhimuriumDisk diffusionBacitracin, polymyxin-B, colistin[57]
Shell surface, yolkHektoen enteric agar37 °C/24 hSalmonella typhimuriumDisk diffusionClindamycin, oxacillin, penicillin, vancomycin[58]
ealthy chickenSkin, feather, nasal, cloacaMannitol salt agar, McConkey agar, Brilliant green agar, Blood agarNDStaphylococcus aureus, Escherichia coli, Pasteurella spp., Salmonella spp.Disk diffusionTetracycline[59]
CloacaEosin methylene blue (EMB) agarNDEscherichia coliDisk diffusionGentamycin, erythromycin, penicillin, cephalexin, amoxicillin, nalidixic acid[60]
CloacaXylose lysine deoxycholate agar, Brilliant green agar37 °C/24 hSalmonella spp.Disk diffusionKanamycin, sulfamethoxazole-trimethoprim, nalidixic acid, ampicillin, cefoxitin, streptomycin, tetracycline, chloramphenicol[61]
CloacaXylose lysine deoxycholate agarNDSalmonella spp.Disk diffusionTetracycline, chloramphenicol, ampicillin, streptomycin[62]
CloacaMcConkey agar, Eosin methylene blue (EMB) agar37 °C/18–24 hEscherichia coliDisk diffusionAmpicillin, tetracycline,
sulfamethoxazole-trimethoprim, nalidixic acid
[63]
MeatDrumsticks, gizzards, liverXylose lysine deoxycholate agar, Brilliant green agar37 °C/24 hSalmonella spp.Disk diffusionErythromycin, penicillin, amoxicillin[64]
Liver, gizzards, heartsEnterococcosel agar37 °C/48 hEnterococcus faecalisDisk diffusionOxytetracycline, dihydrostreptomycin[65]
BrestEnterococcosel agar35 °C/24 hEnterococcus faeciumMICQuinupristin-dalfopristin[66]
Brest, muscleMcConkey agar supplemented with 5% sheep blood37 °C/18–24 hEscherichia coliDisk diffusionTetracycline, chloramphenicol, nitrofurantoin[67]
ND—not defined.
Table 4. PCR approaches used for the detection of chicken-borne pathogens.
Table 4. PCR approaches used for the detection of chicken-borne pathogens.
Type of PCRSample UsedTarget Site of Bacterial PathogenPrimersProbeDetection ChemistryLimit of DetectionReference
SimpleMeat (PND)Spiked Salmonella typhimurium:ogdh geneForward 5′-GCCTTCCTGAAACGTGACCTA-3′ and reverse 5′-ACCATCTCTTTCAGCATGGGT3′NANA102 cfu/mL[73]
MultiplexMeat (Breasts, wings, drumsticks, legs)Clostridium perfringens:cpa, cpb, etx, iA, cpe and cpb2 genesForward 5′-GCTAATGTTACTGCCGTTGA-3′ and reverse 5′-CCTCTGATACATCGTGTAAG-3′; Forward 5′- GCGAATATGCTGAATCATCTA-3′ and reverse 5′-GCAGGAACATTAGTATATCTTC-3′; Forward 5′-GCGGTGATATCCATCTATTC-3′ and reverse 5′-CCACTTACTTGTCCTACTAAC-3′; Forward 5′-ACTACTCTCAGACAAGACAG-3′ and reverse 5′-CTTTCCTTCTATTACTATACG-3′; Forward 5′-GGAGATGGTTGGATATTAGG-3′ and reverse 5′-GGACCAGCAGTTGTAGATA-3′; Forward 5′-AGATTTTAAATATGATCCTAACC-3′ and reverse 5′-CAATACCCTTCACCAAATACTC-3′NANANA[74]
Multiplex Real-TimeMeat (PND)Salmonella spp.: invA; Escherichia coli O157: rfbE; Listeria monocytogenes: hlyA geneForward 5′-GTTGAGGATGTTATTCGCAAAGG-3′ and reverse 5′-GGAGGCTTCCGGGTCAAG-3′; Forward 5′-TGTTCCAACACTGACATATATAGCATCA-3′ and reverse 5′-TGCCAAGTTTCATTATCTGAATCAA-3′; Forward 5′-ACTGAAGCAAAGGATGCATCTG-3′ 3′ and reverse 5′-TTTTCGATTGGCGTCTTAGGA-3′5′-CCGTCAGACCTCTGGCAGTACCTTCCTC-3′; 5′-ATGCTATAAAATACACAGGAGCCACCCCCA-3′; 5′-CACCACCAGCATCTCCGCCTGC-3′TaqMan probes labelled with fluorescent dyes CAL Fluor Orange 560, Quasar 670, Fluorescein amidite (FAM), and 5-Carboxytetramethylrhodamine (TAMRA), respectivelyNA[75]
Real-TimeMeat (PND)Spiked Listeria monocytogenes: ilyA geneForward 5′-GGCTTTCAGCTGGGCATAACCAA-3′ and reverse 5′-GCGGTCAGTGTAAAAAGTGGCACA-3′NABrilliant SYBR Green QPCR Master Mix1 cfu/g[76]
SimpleMeat (Breasts, drumsticks, legs)Arcobacter spp.: 16S rRNAForward 5′-AGAACGGGTTATAGCTTGCTAT-3′ and reverse 5′-GATACAATACAGGCTAATCTCT-3′NANANA[77]
Real-Time QuantitativeMeat (Breasts, wings, legs)Campylobacter jejuni: rpoB geneForward 5′-GAGTAAGCTTGGTAAGATTAAAG-3′ and reverse 5′-AAGAAGTTTTAGAGTTTCTCC-3′NAFluoCycle SYBR GreenMix10 cfu/g[78]
SimpleMeat (PND)Arcobacter, butzleri: 16S rRNA, A. cryaerophilus, A. skirrowii, A. cibarius, gyrA geneForward 5′-AGTTGTTGTGAGGCTCCAC-3′ and reverse 5′-GCAGACACTAATCTATCTCTAAATCA-3′; Forward 5′-TGCTAAAATTGCAGATGTACCA-3′; and reverse 5′- AATTCCTTTTTCAGAAACTGTACG-3′; Forward 5′- GAGACAACTTTTGGAACTATTCTATGA-3′ and reverse 5′-GAAGATAGATTAACTTTTGCTTGTTG-3′; Forward 5′- TGGAAATATTGTTGGTGAAGTTCAG-3′ and reverse 5′- ATCTACATTTACAATACTTACTCCCGAA-3′NANANA[79]
MultiplexMeat (PND)Spiked Salmonella spp. invA, sdf, STM4492 genesForward 5′-AAA CGT TGA AAA ACT GAG GA-3′ and reverse 5′-TCG TCA TTC CAT TAC CTA CC-3′; Forward 5′-AAA TGT GTT TTA TCT GAT GCA AGA GG-3′ and reverse 5′-GTT CGT TCT TCT GGT ACT TAC GAT GAC-3′; Forward 5′-ACA GCT TGG CCT ACG CGA G-3′ and reverse 5′-AGC AAC CGT TCG GCC TGA C-3′NANA105 cfu/mL[80]
Multiplex Real-TimeMeat (Skin)Spiked Salmonella spp.: invA, Campylobacter spp.: 16S rRNAForward 5′-TCGTCATTCCATTACCTACC-3′ and reverse 5′-AAACGTTGAAAAACTGAGGA-3′; Forward 5′-CTGCTTAACACAAGTTGAGTAGG-3′ and reverse 5′-TTCCTTAGGTACCGTCAGAA-3′5′-TCTGGTTGATTTCCTGATCGCA-3′; 5;′- TGTCATCCTCCACGCGGCGTTGCTGC-3′Cyanines, Fluorescein amidite and VIC fluorophores1 and 106 cfu/mL[81]
Real-Time Loop-mediated isothermal amplificationMeat (PND)Spiked Salmonella spp.: gene62181533Forward 5′-TGA TACTGT GTC TGC GTC CC-3′ and reverse 5′-CGG AGC GGA TAAACG GAG TT-3′NANA7 cfu/mL[82]
Multiplex Real-TimeMeat (Skin)Spiked Salmonella spp.: invA, Campylobacter spp.: 16S rRNAForward 5′-TCGTCATTCCATTACCTACC-3′ and reverse 5′-AAACGTTGAAAAACTGAGGA-3′; Forward 5′-CTGCTTAACACAAGTTGAGTAGG-3′ and reverse 5′-TTCCTTAGGTACCGTCAGAA-3′5′-TCTGGTTGATTTCCTGATCGCA-3′; 5′-TGTCATCCTCCACGCGGCGTTGCTGC-3′Labeled with Fluorescein amidite (FAM), Cyanines, and VIC fluorophores1; 102 cfu/mL[83]
PND—parts not defined; NA—not applicable.
Table 5. Array-based approaches used for the detection of chicken-borne pathogens.
Table 5. Array-based approaches used for the detection of chicken-borne pathogens.
Sample UsedTarget Site of Bacterial PathogenProbeArray MatrixLimit of DetectionReference
Meat (Breast, wings, thighs)Spiked Salmonella
spp.: fimY, Shigella spp.: ipaH, Listeria monocytogenes: prfA, Escherichia coli: uspA genes
FY5′-GCCTCAATACAGGAGACAGGTAGCGCC-3′; 5′-ATATCGCTTTGTTGCCAACTGAGCGC-3′; 5′-AAATAAGTAGTGACTCAATGAATAGCCGAG-3′; 5′-AGTTGTAATTATTGCCTGAGAAATGATAC-3′, IH5′-GGGAGTGACAGCAAATGACCTCCGC-3′; 5′-CGGCACTGGTTCTCCCTCTGGGGACCA-3′; 5′-TGTGGATGAGATAGAAGTCTACCTGG-3′; 5′-AGAATGAGTACTCTCAGAGGGTGGCTGAC-3′; 5′-AGAAACTTCAGCTCTCCACTGCCGTGA-3′, PA5′-ACGGGAAGCTTGGCTCTATTTTGCGG-3′; 5′-AGCTTACAAGTATTAGCGAGAACGGGACCA-3′; 5′-ACAAAGGTGCTTTCGTTATAATGTCTGGCT-3′; 5′-AATTTAGAAGTCATTAGCGAACAGGCT-3′; 5′-CATACAGCCTAGCTAAATTTAATGAT-3′; 5′-AAACATCGGTTGGCTATTATAAGTTTAG-3′, UA5′-AAGAGACACATCATGCGCTGACCGAGCT-3; 5′-GGTAGAGAAAGCAGTCTCTATGGCTCGCCC-3′; 5′-ACCGTTCACGTTGATATGCTGATTGTTCCG-3′; 5′-TTGTTTATCTAACGAGTAAGCAAG-3′; 5′-AAGGTAAGGATGGTCTTAACACTGAAT-3′; 5′-GGTGACGTAACGGCACAAGAAACGCTAGCT-3′Nylon membrane103 cfu/mL[86]
Meat (Breast, wings, thighs)Spiked Salmonella serotype enteritidis:
fimY,
Listeria monocytogenes:
prfA, Shigella boydii:
ipaH genes
FY5′-GCCTCAATACAGGAGACAGGTAGCGCC-3′; 5′-ATATCGCTTTGTTGCCAACTGAGCGC-3′; 5′-AAATAAGTAGTGACTCAATGAATAGCCGAG-3′; 5′-AGTTGTAATTATTGCCTGAGAAATGATAC-3′, PA5′-ACGGGAAGCTTGGCTCTATTTTGCGG-3′; 5′-AGCTTACAAGTATTAGCGAGAACGGGACCA-3′; 5′-ACAAAGGTGCTTTCGTTATAATGTCTGGCT-3′; 5′-AATTTAGAAGTCATTAGCGAACAGGCT-3′; 5′-AAACATCGGTTGGCTATTATAAGTTTAG-3′, IH5′-GGGAGTGACAGCAAATGACCTCCGC-3′; 5′-CGGCACTGGTTCTCCCTCTGGGGACCA-3′; 5′-TGTGGATGAGATAGAAGTCTACCTGG-3′; 5′-AGAATGAGTACTCTCAGAGGGTGGCTGAC-3′; 5′-AGAAACTTCAGCTCTCCACTGCCGTGA-3′Nylon membrane104–106 cfu/mL[87]
Meat (PND)Spiked Salmonella enteritidis: sdf, Salmonella typhimurium: STM4497 gene, Campylobacter jejuni: hipO, Campylobacter coli: ceuE geneBtn-TG-T10-AATCAGCCTGTTGTCTGCTCACCATTC-3′; Btn-TG-T10-AGATCATCGTCGACATGCTCAC-3′, Btn-TG-T10-CATTGCGAGATACTATGCTTTG-3′, Btn-TG-T10-CTGTAAGTATTTTGGCAAGTTT-3′DVD chips0.2 pg genomic DNA[88]
PND—parts not defined.
Table 6. ELISA-based approaches used for the detection of chicken-borne pathogens.
Table 6. ELISA-based approaches used for the detection of chicken-borne pathogens.
Type of ELISASample UsedTarget Site of Bacterial PathogenSensitivityLimit of DetectionReference
IndirectMeat (Thighs, legs)Outer membrane protein of Salmonella enterica serovar Enteritidis94%NA[91]
SandwichSpiked wingsSalmonella spp.75%1.6 × 103 cfu/mL[92]
SandwichMeat (PND)Campylobacter spp.NDNA[93]
SandwichSpiked meat (PND) and naturally contaminatedSalmonella spp.ND5 × 103 cfu/mL[94]
PND—parts not defined; ND—not defined; NA—not applicable.
Table 7. Aptamers based approaches used for the detection of chicken-borne pathogens.
Table 7. Aptamers based approaches used for the detection of chicken-borne pathogens.
Sample UsedTarget Site of Bacterial PathogenAptamer Name and SequenceDetection FormatLimit of DetectionReference
Spiked meatListeria monocytogenes: InlA geneA8, 5′-ATC CAT GGG GCG GAGATG AGG GGG AGG AGG GCG GGT ACC CGG TTGAT-3′, A610.2, 5′- GGT TACTGA AGC ATA TGT CCG GGG GAT TGC CAA GCCTTC CC-3′Sandwich ELISA103 cfu/mL[104]
Spiked meatWhole-cell of Salmonella enterica serovar TyphimuriumND, 5′-TATGGCGGCGTCACCCGACGGGGACTTGACATTATGACAG-3′Electrochemical101 cfu/mL[105]
Spiked meat (Breast)Whole cell of Salmonella typhimuriumND, 5′-NH2-ATAGGAGTCACGACGACCAGAAAGTAATGCCCGGTAGTTATTCAAAGATGAGTAGGAAAAGATATGTGCGTCTACCTCTTGACTAAT-3′FRET35 cfu/mL[106]
Spiked cooked meatWhole-cell of Streptococcus pyogenesS2, 5′-GTTCGGGGTCGGGGTGAGTGGGGCCTAGGAGTGGGGGCGC-3′, S8, 5′-ATGGGGGGCGGGGAGGTGGGTACAGGGTCGGGGATGGCAG-3′, S10, 5′-CGGGCGGGGCGTGGGGTGTTGGAGTGGAGGGCGGGGCGGC-3′, S12, 5′-GCGGGCGGGGGGAGGGCGGCCGTGGGCTGCGAGTGGGAGG-3′, S15, 5′-CAGGGTGCGGGAGGGCCAAAGGGGGGAGGGCCCGGGGGGA-3′FRET70 cfu/mL[107]
Spiked chickenE. coli O157: H7F1N, 5′-ATAGGAGTCACGACGACCAGAA, R1N, ATTAGTCAAGAGGTAGACGCACATA, Bio Rev, 5Biosg/ATTAGTCAAGAGGTAGACGCACATAQuantum dots102 cfu/mL[108]
ND—not defined; FRET—fluorescence resonance energy transfer.
Table 8. Biosensor-based approaches used for the detection of chicken-borne pathogens.
Table 8. Biosensor-based approaches used for the detection of chicken-borne pathogens.
Biosensor TypeSensing PlatformChicken MatrixPathogens/ToxinsLimit of DetectionAnalysis TimeReference
Phage magnetoelasticGold electrodeBoneless and skinless breast filletsSpiked Salmonella enterica serovar Typhimurium7.86 × 103 cfu/mm22–10 min[116]
Multiplex fiber opticPolystyrene waveguidesBreastSpiked Listeria monocytogenes, Escherichia coli O157:H7, Salmonella enterica103 cfu/mL<24 h[117]
Fiber opticPolystyrene waveguidesBreastSpiked Salmonella enteritidis102 cfu/mL<8 h[118]
ColorimetricC2 reverse-phase silica gel plates with sensitive dyesBreast filletsSpiked Pseudomonas gessardii, Pseudomonas psychrophila, Pseudomonas fragi, Pseudomonas fluorescensNAND[119]
Dithiobis-succinimidyl propionate-modifiedimmunosensorGold electrodeSkinSpiked Listeria monocytogene103 cfu/25 g45 min[120]
AmperometricScreen-printed electrodeNSSalmonella pullorum100 cfu/mL1.5–2 h[121]
Optical scatteringSELA platesBreastSpiked Listeria monocytogenes, Escherichia coli O157: H7, Salmonella enteritidisND29–40 h[122]
ColorimetricAptamerNSCampylobacter coli, Campylobacter jejuni7.2 × 105 cfu/mL30 min[123]
SELA—Salmonella, Escherichia and Listeria agar; NS—not specified; NA—not applicable; ND—not defined.
Table 9. Microbial inhibition-based approaches used for the detection of antibiotics residue in chicken meat.
Table 9. Microbial inhibition-based approaches used for the detection of antibiotics residue in chicken meat.
Meat SampleMethod TypeTypes of Antibiotics ResidueMicrobial Test StrainsReference
Muscles, kidney, liver, gizzardThree-Plate testTetracycline, β-lactams, sulphonamides, aminoglycosidesBacillus subtilis[143]
Spiked liver, kidney, breast, thigh muscle, skinNDEnrofloxacin, ciprofloxacin, oxytetracyclineGeobacillus stearothermophilus[144]
Breast, liver, thigh tissueFour-Plate testTetracyclineBacillus subtilis[145]
BreastFour-Plate testTetracycline, β-lactams, sulphonamides, aminoglycosidesBacillus subtilis, Micrococcus luteus[146]
FilletNDOxytetracycline, enrofloxacinBacillus subtilis[147]
Breast, thighsFour-Plate testTetracycline, β-lactams, sulphonamides, aminoglycosides, macrolides, quinolonesBacillus subtlis spore, Micrococcus luteus, Escherichia coli[148]
Liver, kidney, muscleFour-Plate testChloramphenicolBacillus subtilis, Staphylococcus aureus[149]
ND—not defined.
Table 10. ELISA-based approaches used for the detection of antibiotic residue in chicken meat.
Table 10. ELISA-based approaches used for the detection of antibiotic residue in chicken meat.
Type of ELISASample UsedTarget AntibioticLimit of DetectionReference
CompetitiveBreast, liver, thigh tissueTetracycline0.05 µg/Kg[145]
CompetitiveLiver, kidneyCiprofloxacin, streptomycin, sulphanilamide, tetracycline10 ppb[150]
NDBreastEnrofl oxacin, ciprofloxacin, streptomycin, chloramphenicolND[153]
CompetitiveBreastTetracycline, streptomycin, chloramphenicol, sulfamethazineND[151]
NDBreastTetracyclineND[154]
Indirect competitiveSpiked musclesChloramphenicol6 ng/L[152]
NDMuscles, liver, kidneyGentamicin0.05 µg/Kg[155]
CompetitiveBreastQuinolone0.05 µg/Kg[28]
CompetitiveBreastQuinolone0.05 µg/Kg[156]
ND—not defined.
Table 11. TLC-based approaches used for the detection of antibiotic residue in chicken/meat.
Table 11. TLC-based approaches used for the detection of antibiotic residue in chicken/meat.
Sample UsedStationary PhaseMobile PhaseTarget AntibioticReference
Breast, thigh muscle, liverSilicaAcetone and Methanol: 1:1Ciprofloxacin, enrofloxacin, oxytetracycline, doxycycline, amoxicillin[159]
LiverSilicaAcetone and Methanol: 1:1ND[160]
Liver, kidneySilicaAcetone and Methanol: 1:1Sulphanilamide, streptomycin, ciprofloxacin, tetracycline[150]
Oral administration of chicken bloodSilicaAcetone and Methanol: 1:1Ciprofloxacin[161]
Spiked musclesSilicaChloroform and n-Butanol: 90:10Sulfadiazine, sulfadoxine, sulfamethazine, sulfathiazole, sulfaquinoxaline[162]
MPNDSilicaAcetone and Methanol: 1:1Doxycycline, oxytetracycline[163]
Breast, thigh muscle, liver, kidneySilicaAcetone and Methanol: 1:1Doxycycline[164]
MPND—meat portion not defined; ND—not defined.
Table 12. HPLC-based approaches used for the detection of antibiotics residue in chicken meat.
Table 12. HPLC-based approaches used for the detection of antibiotics residue in chicken meat.
Sample UsedTypes of AntibioticMethod UsedChromatography Conditions UsedLimit of DetectionReference
ModelColumnSolventFlow Rate
Breast, liver, thigh tissueTetracyclineHPLC-UVKNAUER liquid chromatography system, Berlin, GermanyEurospher RP-C18 column (250 × 4.6 mm i.d.). A guard column (Eurospher 100-5 C18) was used to protect the analytical columnMobile phase was a gradient elution using MeOH; acetonitrile; 0.03 M oxalic acid buffer pH 2.5; water0.9 mL/min25 µg/Kg[145]
Spiked breast, thigh, liver, kidneyOxytetracycline, tetracyclineHPLC-UVHPLC (Shimadzu Corporation, Tokyo, Japan)Inertsil ODS-3 columnMobile phase consisting of methanol:acetonitrile: 0.01 M oxalic acid dihydrate (5:18:77 v/v/v)1 mL/min50 ng/mL[168]
Spiked meat, liverOxytetracycline, tetracycline, chlortetracycline, doxycyclineHPLC-DADThe HPLC system of a HP 1100 chromatograph (Agilent Technologies, Palo Alto, CA, USA)The analytical column was reversed-phase (Nuclosil 100 C18, 25 cm × 4.6 mm I.D., 5 µm, Germany)The mixture of acetonitrile/0.03 M oxalic acid (40:60, v/v); The mixture of methanol/acetonitrile/0.03 M oxalic acid (10:30:60, v/v/v); The mixture of methanol/acetonitrile/0.03 M oxalic acid (20:20:60, v/v/v)1. 1 mL/min; 2. 1 mL/min; 3. 1 mL/min; 4. NS; 5. NS4.4, 5, 13 and 10 ng/g[169]
Spiked muscleMarbofloxacin, ciprofloxacin, norfloxacin, lomefloxacin, danofloxacin, enrofloxacin, sarafloxacin, difloxacin, oxolinic acid, flumequineHPLC-FADHPLC system (Waters, Milford, MA, USA)The reverse phase analytical column was a Symmetry C18 (250 mm × 4.5 mm i.d., 5 µ m) from WatersMobile phase consisted of aqueous formic acid solution (0.02%, pH 2.8) and acetonitrile1.0 mL/min0.3–1.0 ng/g[170]
Spiked muscleOfloxacin, norfloxacin, ciprofloxacin, enrofloxacin, oxytetracycline, tetracycline, chlortetracycline, doxycycline, sulfadiazine, sulfamethazine, sulfadimethoxydiazine,
sulfamonomethoxine, sulfamethoxazole, sulfaquinoxaline
UPLC-MS-MSUPLC system (Waters, Milford, MA, USA)UPLC BEH C18 column(50 mm 9 2.1 mm i.d., 1.7 lm) from WatersMobile phase, consisting of methanol (solvent A) and 0.01% formic acid in water (solvent B)0.3 mL/min0.3 µg/Kg[171]
Spiked muscle, liver, kidneyAmoxicillin, amoxicillin metabolites, ampicillinUPLC-MS-MSUPLC system (Waters, Milford, MA, USA)UPLC HSS T3 column (100 × 2.1 mm, internal diameter (i.d.) 1.8 μm)A (0.15% formic acid) and B (acetonitrile)0.5 mL/min0.01–1.36 µg/Kg[172]
NS—not specified.
Table 13. Biosensor-based approaches used for the detection of antibiotics residue in chicken meat.
Table 13. Biosensor-based approaches used for the detection of antibiotics residue in chicken meat.
Biosensor TypeSensing PlatformChicken MatrixAntibioticLimit of DetectionAnalysis TimeReference
Bioluminescent biosensorBacteria E. coli K12Spiked breast filletTetracycline100 ng/g4 h[173]
ElectrochemicalGold and platinum nanowireSpiked breastPenicillin and tetracycline41.2 μA μM−1 cm−2 and 26.4 μA μM−1 cm−2ND[175]
ElectrochemicalGlassy carbon electrodePNDTetracycline0.10 µMND[176]
ElectrochemicalPencil graphite electrodeSpiked PNDSulfadimethoxine3.7 × 10−16 MND[177]
AmperometricGlassy carbon electrodePNDChloramphenicol45 pg/mLND[178]
Surface plasmon
resonance
NSSpiked muscleChloramphenicol and chloramphenicol glucuronideNDND[179]
Bioluminescent biosensor bacteriaBacteria E. coliSpiked muscleTetracyclineNDND[175]
Surface plasmon
resonance
NSSpiked breastNorfloxacin, sarafloxacin, difloxacin, ciprofloxacin, enrofloxacin, flumequine, danofloxacin, marbofloxacin, pefloxacin, enoxacin, lomefloxacin, ofloxacin, oxolinic acidNDND[180]
NS—not specified; PND—portion not defined; ND—not defined.
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