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Yamin, D.; Uskoković, V.; Wakil, A.M.; Goni, M.D.; Shamsuddin, S.H.; Mustafa, F.H.; Alfouzan, W.A.; Alissa, M.; Alshengeti, A.; Almaghrabi, R.H.; et al. Detection of Antibiotic-Resistant Bacteria. Encyclopedia. Available online: https://encyclopedia.pub/entry/50938 (accessed on 01 August 2024).
Yamin D, Uskoković V, Wakil AM, Goni MD, Shamsuddin SH, Mustafa FH, et al. Detection of Antibiotic-Resistant Bacteria. Encyclopedia. Available at: https://encyclopedia.pub/entry/50938. Accessed August 01, 2024.
Yamin, Dina, Vuk Uskoković, Abubakar Muhammad Wakil, Mohammed Dauda Goni, Shazana Hilda Shamsuddin, Fatin Hamimi Mustafa, Wadha A. Alfouzan, Mohammed Alissa, Amer Alshengeti, Rana H. Almaghrabi, et al. "Detection of Antibiotic-Resistant Bacteria" Encyclopedia, https://encyclopedia.pub/entry/50938 (accessed August 01, 2024).
Yamin, D., Uskoković, V., Wakil, A.M., Goni, M.D., Shamsuddin, S.H., Mustafa, F.H., Alfouzan, W.A., Alissa, M., Alshengeti, A., Almaghrabi, R.H., Fares, M.A.A., Garout, M., Al Kaabi, N.A., Alshehri, A.A., Ali, H.M., Rabaan, A.A., Aldubisi, F.A., Yean, C.Y., & Yusof, N.Y. (2023, October 30). Detection of Antibiotic-Resistant Bacteria. In Encyclopedia. https://encyclopedia.pub/entry/50938
Yamin, Dina, et al. "Detection of Antibiotic-Resistant Bacteria." Encyclopedia. Web. 30 October, 2023.
Detection of Antibiotic-Resistant Bacteria
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This entry is adapted from the peer-reviewed paper 10.3390/diagnostics13203246

Antibiotic resistance is a global public health concern, posing a significant threat to the effectiveness of antibiotics in treating bacterial infections. The accurate and timely detection of antibiotic-resistant bacteria is crucial for implementing appropriate treatment strategies and preventing the spread of resistant strains.

antimicrobial resistance (AMR) antibiotic-resistant bacteria PCR

1. Introduction

1.1. Antibiotic Resistance: A Growing Global Health Challenge

The evolution and manufacture of antibiotics in the last century have been among the most outstanding achievements in the field of medicine [1]. Antimicrobials are being recognized as one of the most efficacious forms of chemotherapy in the annals of medical progress. It is unnecessary to mention the number of lives antibiotics have rescued and how greatly they helped to control infectious diseases, which were the primary reasons for human death and morbidity before the advent of antibiotics [2]. Today, antibiotics are either therapeutic or prophylactic drugs and are commonly utilized in medicine and agriculture. The first identified antibacterial chemical was penicillin [3], a β-lactam antibiotic. Soon after this remarkable discovery, antibiotics were employed to treat human illnesses, starting with sulfonamide and followed by the aminoglycosides streptomycin and streptothricin [1][4][5].
Antimicrobial resistance (AMR) refers to the capacity of pathogens and other microbes to withstand the influence of an antibiotic that was formerly vulnerable, thus allowing the organisms to prevail and thrive [6]. AMR is unavoidable because microorganisms adopt genetic changes to reduce the fatal effects of antibiotic therapy [7][8]. The natural history of genes responsible for antibiotic resistance traces the phylogenetic reconstruction. It has unveiled the enduring existence of genetic elements that provide resistance to various classes of antibiotics in natural environments, predating the advent of antibiotics [9][10]. Phylogenetic analysis based on the structure of serine and Metallo-β-lactamases, for instance, revealed that these primitive enzymes developed more than two billion years ago, with specific serine beta-lactamases found on plasmids for millions of years [11][12]. Prior to the general application of penicillin in medicine, data revealed that bacteria can degrade this compound through an enzymatic breakdown [2][13]. AMR was originally discovered in gonococci, streptococci, and staphylococci. In fact, following the commercially produced antibiotic, penicillin became available in 1941. It took only a year before penicillin-resistant Staphylococcus aureus developed [14]. Subsequently, a derivative of penicillin was launched into the marketplace in 1960 to address penicillin-resistant S. aureus, which also developed resistance to methicillin that same year [8][15].
AMR is raising a huge concern up to date due to its widespread use and the short duration of antibiotics to acquire resistance. Almost 70% of bacteria causing infections are resistant to at least one medication [16]. AMR is now considered one of the most critical risks to public health in health care facilities, as well as in food protection. According to the 2019 Antibiotic Resistance Threats Report by the Centers for Disease Control and Prevention (CDC), over 2.8 million cases of antibiotic-resistant infections occur annually in the United States, with over 35,000 fatalities [17]. Similarly, a survey carried out in India showed that an alarming rate of child mortality due to antibiotic-resistant bacterial infection occurs almost every 9 min and over 50,000 fatalities among infants as a result of sepsis due to germs becoming resistant to standard antibiotics [7]. The World Health Organization (WHO) reported in 2019 that AMR causes the deaths of 700,000 people worldwide each year, and by 2050, it will result in the deaths of 20 million, costing over $2.9 trillion in healthcare [8]. In addition, from 2015 to 2019, the European Antimicrobial Resistance Surveillance Network (EARS-Net) [18] revealed that the prevalence of AMR in the European Union is changing in relation to bacterial species, antibiotic class, and geographical location. According to the survey conducted, methicillin-resistant Staphylococcus aureus (MRSA) is continuously posing threats with as high as 74% of all S. aureus infections globally. S. aureus impacts approximately 120,000 persons in the US, resulting in nearly 20,000 deaths [19], and the number of deaths attributable solely to MRSA exceeded 100,000 in 2019 [15]. In its most recent Global Antimicrobial Surveillance System (GLASS) [20], the WHO demonstrated widespread AMR across 500,000 people with documented bacterial infections in 22 different countries. The most frequently encountered antibiotic-resistant bacteria included Escherichia coli, S. aureus, Streptococcus pneumoniae, and Klebsiella pneumoniae [15]. Ciprofloxacin, a commonly used antibiotic for urinary tract infections (UTIs), has shown varying levels of resistance across different bacterial strains. Resistance to E. coli ranged from 8.4% to 92.9%, while for K. pneumoniae, it ranged from 4.1% to 79.4%. Penicillin resistance reached 51% in multiple countries, as reported by the GLASS. In 2019, the GLASS collected data on MRSA bloodstream infections (BSIs) from 25 countries, zones, and regions, as well as E. coli bloodstream infection data from 49 countries. According to a study [21], MRSA had a median prevalence of 12.11%. Additionally, the study revealed a 36% resistance rate among E. coli to third-generation cephalosporins.
According to the findings presented by Migliori et al. [22], the data pertaining to the monitoring of drug resistance in patients with tuberculosis (TB) indicated that 3.5% of the current patients with TB and 18% with previous case of TB treatment globally are projected to develop specifically rifampicin-resistant (RR) TB or even a multidrug-resistant (MDR) [22]. In 2017, there was a notable global rise in the incidence of new cases of MDR/RR-TB recorded, which resulted in the deaths of 230,000 people that year [8][23].

1.2. Importance of Accurate Detection of Antibiotic-Resistant Bacteria

Healthcare-associated infections (HAIs) are the most frequent leading cause of clinical complications, affecting 5% to 10% of patients and increasing healthcare costs substantially, with expenses encompassing medical treatment, extended hospital stays, and legal fees associated with HAI-related litigations, totaling around USD 4 billion [24]. Moreover, the emergence of AMR bacteria in HAIs further complicates the financial burden. These multidrug-resistant organisms can necessitate specialized treatments and longer hospitalization, significantly escalating costs. Effective risk management in HAI prevention is crucial to curb both the incidence of HAIs and the spread of AMR. It involves strict adherence to infection control practices, prudent antibiotic use, and surveillance to detect and manage resistant pathogens, all of which are vital to mitigate the economic impact and enhance patient safety [24]. Action plans are being developed by the WHO and other organizations in this sector to enhance the understanding of AMR, reduce the prevalence of infectious diseases through the implementation of infection prevention measures, optimize antimicrobial treatments, create new drugs and treatment strategies, and improve the effectiveness of antimicrobial medicines. It should be noted that there has been significant progress in preventing AMR with these strategies. Although enormous efforts have been undertaken to address AMR, it remains an inescapable issue that diminishes the efficacy of antibiotics in the treatment of infections.
For infectious illnesses to be treated as effectively as possible, early infection diagnosis is essential. Despite significant advancements in medical technology, the detection and diagnosis of microbiological diseases often require several days to complete, leading to a prolonged turnaround time (TAT) [25][26][27]. For this reason, physicians are driven to initiate practically achievable antibiotic therapies, often broad-spectrum, prior to carrying a diagnosis. This technique may lead to adverse repercussions not only for the health of the patient but also in terms of exacerbating the developing AMR crisis. Thus, the demand for speedy, sensitive, and affordable kits for AMR diagnostics has become critical. The adoption of such avenues will greatly lower the TAT for antibiotic susceptibility determination, thereby allowing the selection of improved, target-specific medicines [25]. In short, diagnostic testing is considered a vital tool in any approach against AMR [28].
Generally, a clinical microbiology analysis focuses on phenotypic approaches to evaluate the antimicrobial susceptibility patterns of pathogens [29]. These methods are still relevant because of their benefits, such as being affordable and easy to carry out and having a clear criterion for interpretation. However, they are too cumbersome to provide rapid susceptibility data, thereby delaying the initiation of the therapy [30]. These restrictions have been discovered to have ramifications in patient management; for example, a delay in the commencement of the antibiotic therapy has been linked to increases in both mortality [31] and hospitalization time [32]. This has made it difficult to apply the back-end method of the antimicrobial stewardship program, which has proven gratifying outcomes in patient management and the battle against AMR [33]. To overcome the limitations of the phenotypic approach and enhance both patient care and the management of antibiotic resistance, continuous endeavors are underway to advance the development of rapid antimicrobial susceptibility testing (AST) technologies. These techniques are designed to expedite the identification of pathogenic organisms and assess their susceptibility to antimicrobial agents.
In clinical diagnostics, there are approximately five different methods to speed up AST: (I) bypassing traditional culture methods by directly detecting the pathogen or resistance mechanism in the initial sample; (II) eliminating the need for secondary culture-based susceptibility testing; (III) reducing the time required for analysis and improving the sensitivity for detecting the infectious agent; (IV) enhancing early identification of the pathogen in the initial stages of the disease and at lower microbial concentrations; and (V) early detection of emerging drug resistance during treatment, especially in the context of spreading less susceptible quasi-species [34][35].

2. Traditional Culture-Based Methods

2.1. Conventional Antibiotic Susceptibility Testing (AST)

The European Committee on Antimicrobial Susceptibility Testing (EUCAST) and the Clinical and Laboratory Standards Institute (CLSI) have recommended the use of phenotypic testing for accurate antibiotic resistance diagnosis. This research-based approach involves determining whether a bacterium multiplies when an antibiotic is added, regardless of the resistance mechanism. These tests help determine which antibiotics are effective and what doses should be administered during therapy. Traditional AST procedures, such as disk diffusion, broth microdilution, gradient tests, breakpoint tests, and agar dilution, rely on exposing bacterial isolates to a series of antimicrobials and visually detecting growth.
The minimum inhibitory concentration (MIC) is the principal approach frequently utilized for determining antimicrobial sensitivity. This approach aims to measure the lowest antimicrobial concentration that restricts visible bacterial growth when conducted in either agar or broth. In this method, solutions containing a specified number of bacteria (typically 0.5 according to the MacFarland standard) are introduced onto agar or broth containing diluted antimicrobial concentrations [36].
Following the designated incubation period, the presence or absence of microbial growth is observed. This straightforward and cost-effective method does not necessitate specially designed equipment. The therapeutic antimicrobial concentration can be modulated for optimal therapy once the MIC has been ascertained. Nonetheless, the effectiveness of this approach is constrained when it comes to assessing resistance in non-cultivable live bacteria, and its success depends on factors such as the duration of incubation, the concentration of diluted antimicrobial agents, and initial bacterial inoculum. It is, overall, a semi-quantitative technique that may not yield a precise MIC value [36].
The disc diffusion method is a laboratory technique that involves placing a paper disc coated with an antimicrobial substance onto a solid agar medium. This leads to the formation of a circular area without microbial growth, referred to as the zone of inhibition, surrounding the disc. This zone indicates the degree of inhibition of microbial growth. This qualitative approach categorizes samples as resistant, intermediate, or susceptible. It is a practical and easily executable technique, particularly suited for rapidly growing bacteria. However, limitations include the use of antimicrobial agents that exhibit poor diffusion in agar and difficulties encountered in interpreting results for fastidious and anaerobic microbes [37].
The E-test® combines elements of the previously mentioned methods, resembling disk diffusion but yielding MIC data. The experimental procedure involves the placement of a rectangular device onto an agar plate. One side of the device is designed to create a concentration gradient of antimicrobial agents, while the other side is equipped with a scale for interpretation purposes. Despite sharing the time-related limitations of the prior tests, the E-test® employs an immobilized antimicrobial gradient indicated on a ruler, offering a simpler means to directly quantify microorganism susceptibility. This is particularly advantageous for challenging-to-culture organisms like Mycobacterium bovis and Haemophilus influenzae, as well as anaerobes.
Research involving the propagation of bacteria sourced from animal-based food (ABF), especially within the meat distribution system, has been widespread globally. These studies reveal the consistent presence of various microorganisms that are resistant, often to multiple antimicrobials. Notable bacteria in ABF encompass Vibrio parahaemolyticus, Enterococcus faecium, Enterococcus faecalis, E. coli, Bacillus cereus, Listeria monocytogenes, S. aureus, Yersinia enterocolitica, Campylobacter spp., and Salmonella spp. Previous investigations have highlighted resistance to numerous antimicrobial classes, such as ciprofloxacin, tetracycline, benzalkonium chloride, gentamicin, chloramphenicol, enteromycin, cadmium chloride, methicillin, streptomycin, ampicillin, sulfafurazole, nalidixic acid, vancomycin, sulfonamides, clindamycin, and amoxicillin [38].
Irrespective of the merits and demerits of conventional techniques for detecting AMR in bacteria, they play a crucial role in selecting the most optimal therapy against resistant bacteria in clinical diseases. Presently, the medical and scientific communities unanimously acknowledge that prophylactic antimicrobial use, even as growth promoters, is the primary driver of increased resistance across multiple antimicrobial classes. Prudent utilization of these medicinal products is vital, both in production and prophylaxis for animals, adhering to correct dosages and frequencies. Such caution helps prevent interference with human infection treatment and curtails the prevalence of species resistant to multiple antimicrobial drug classes. Despite reported shortcomings, traditional methods remain prevalent for identifying AMR due to their simplicity. Even studies utilizing molecular techniques initially resort to these conventional methods for their ease of use and ability to provide an overall insight into the presence of target AMR and microorganisms.

2.2. Advancements in Culture-Based Techniques

The use of modern optoelectronic systems, fiber optics, microfluidics, and indicator dyes that are sensitive to the redox state or pH can improve the sensitivity and overall performance of optical systems used for testing purposes [39]. Automated AST systems that have received approval from the Food and Drug Administration (FDA), including the MicroScan WalkAway 205 (Siemens Healthcare Diagnostics, West Sacramento, CA, USA), BD Phoenix Automated Microbiology System (BD Diagnostics, Becton Dickinson, San Diego, CA, USA), Vitek 2 System (bioMérieux, Craponne, France), and Sensititre ARIS 2X (Trek Diagnostic Systems, Brooklyn Heights, OH, USA), are of significant importance in clinical laboratories. These systems are equipped with diverse antimicrobial panels tailored for Gram-positive and Gram-negative pathogens. For example, these systems assess turbidity in liquid cultures automatically from multi-wells and use a redox indicator to detect microorganisms. Some systems, such as the Alfed 60 ASTTM system from Alifax in Italy, utilize highly sensitive laser-light scattering technology to identify bacterial proliferation in liquid culture broth. This device enables the rapid retrieval of antibiotic susceptibility information directly from positive blood culture bottles within a time frame of 4–6 h. These broth dilution-based devices employ pre-manufactured AST cassettes or cards that consist of positive controls and wells with escalating doses of antibiotics. They continually observe the growth’s development and examine minimal inhibitory concentration (MIC) trends for large groups of organisms using their extensive databases [40].
The Microscan WalkAway functions as a reader system coupled with an incubator, allowing for the continuous monitoring of results through photometry or fluorometry. The system has the capability to evaluate a range of 40–96 microdilution trays that consist of fixed doses of antimicrobial agents. These trays are manually inserted with bacterial cultures. The MIC results may be achieved within a very brief time frame of 7–18 h, with the duration depending on the classification of the pathogens as either Gram-negative or Gram-positive [41].
The BD Phoenix Automated Microbiology System is equipped to analyze a total of 99 test panels, each containing 84 wells with dilutions of antimicrobial agents. Growth monitoring is performed using both a turbidimeter and a calorimeter. This system can determine MIC values for various pathogens, including Gram-negative, Gram-positive, Streptococcus pneumoniae, β-hemolytic, and viridans, within a time frame of 6–16 h [41].
The Vitek 2 System is an advanced automated platform that utilizes miniaturized reagent cards containing both antimicrobials and testing media, which are distributed across 64 wells. It has the capacity to simultaneously conduct 30–240 tests within a span of 4–10 h, covering Gram-negative, Gram-positive, and S. pneumoniae pathogens [41].
The Sensititre ARIS 2X operates as an automated system based on fluorescence. It necessitates an 18–24 h incubation period to assess growth for MIC determination. Notably, the Sensititre ARIS 2X includes an autoinoculator, which serves to minimize human error. This system is suitable for assessing Gram-negative, Gram-positive, S. pneumoniae, Haemophilus species, and non-fermentative Gram-negative bacilli [41].

3. Molecular Techniques

Molecular-based techniques have advantages over phenotypic assays in detecting antibiotic resistance genes (ARGs), such as multiplex targeting, giving more accurate identification and detection. These techniques offer a viable alternative in certain taxonomic units where susceptibility breakpoints have not been defined. Non-purified polymicrobial samples can also be used in molecular-based approaches, which can lead to faster response times to newly added resistance factors [40]. However, molecular-based techniques have limitations, such as the inability to determine MICs and the possibility of missing some ARGs due to their limited sensitivity and coverage. Moreover, developing molecular-based assays for detecting the broad diversity of AMR genes can be costly [42]. Nonetheless, molecular-based approaches are continually being improved, using amplification and nucleic acid hybridization techniques to enhance the detection of ARGs and their expression. Overall, molecular-based techniques provide a quick and sensitive detection of ARG [43].

3.1. Nucleic Acid Amplification Technology (NAAT) in AST

Nucleic acid amplification testing (NAAT) is a highly robust method for detecting pathogens, particularly when used in combination with a syndromic strategy. Many diagnostic panels offered by companies like Bosch, BioMérieux, Eplex, Elitech, Becton Dickinson, and Qiagen include the detection of specific ARGs. They provide therapeutically useful data, particularly when a comprehensive antibiogram is not required. However, the detection of specific ARGs does not necessarily confirm antibiotic resistance. The identified ARGs may not exhibit a direct correlation with the pathogen responsible for the illness, or the resistance gene detected may not possess functional capabilities. NAAT does not determine MICs or provide explicit recommendations for antibiotic use. One notable benefit of NAAT is its capacity prompt updates in response to the emergence of novel pathogens and resistance factors [39]. Examples of NAATs used for antibiotic resistance detection include Polymerase Chain Reaction (PCR), multiplex PCR, Reverse Transcriptase Polymerase Chain Reaction (RT-PCR), Real-Time PCR (qPCR), and Isothermal Amplification Methods.

3.1.1. Polymerase Chain Reaction (PCR) and Multiplex PCR

PCR is an in vitro technology that permits the exponential amplification of specified sequences of DNA and RNA. However, false-positive results can occur due to contamination or cross-reactivity with other related organisms or genes. To address this, various quality control measures have been developed, including the use of negative controls and the validation of assay specificity and sensitivity. They have also been used for the environmental monitoring of AMR genes in soil, water, and food samples. However, PCR-based methods have limitations in terms of their ability to detect unknown or novel resistance genes and their dependence on the availability of specific primers for target genes [44]. Unlike conventional culture methods, this approach can amplify genes from non-cultivable or dead microorganisms that might otherwise go unrecognized by standard techniques [38][45]. Despite these limitations, PCR remains a valuable tool in AMR research and surveillance. These are just a few examples, as there are many different AMR genes that can be detected using PCR: mecA gene, which confers resistance to methicillin in Staphylococcus aureus [46]; blaSHV gene, which confers resistance to beta-lactam antibiotics in Enterobacteriaceae [47]; tetM gene, which confers resistance to tetracycline antibiotics in many bacterial species [48]; and vanA gene, which confers resistance to vancomycin in Enterococcus species [49].
Multiplex reaction in PCR may be optimized by an upgraded technique with respect to the traditional PCR, as well as qPCR. This experimental procedure involves the use of several primers within the solution mixture, enabling the detection and differentiation of multiple microbial species during a single run. The main advantage is the decreased cost and time required with the simultaneous amplification of various genes [50]. PCR has been shown to be a good way to find point mutations in broad-spectrum AMR genes, as long as either of the primers is designed to bind at sites where the sequence changes [38][51]. Multiplex PCR techniques have also been devised to swiftly and simultaneously detect multiple pathogens in clinical specimens, along with the identification of AMR genes within the pathogens. Examples of multiplex PCR techniques for detecting AMR genes encompass the RespiFinder SMART 22 assay [52], the SuperBug ID assay [53], the Allplex™ Gastrointestinal Panel Assay [54], and the BD MAX™ MDR-TB assay [55].

3.1.2. Reverse Transcriptase Polymerase Chain Reaction (RT-PCR)

The process of RT-PCR involves transcribing an RNA molecule into a complementary DNA molecule (cDNA) and amplifying it using PCR. This technique is known for its excellent specificity, sensitivity, and reliability [45][56]. Compared to DNA molecules, cDNA molecules generated from the original RNA have a higher degree of purity, as they lack contaminants such as proteins that may affect the accuracy of the test. As a result, cDNA is more specific and can be more easily detected by primers. In addition, RT-PCR can identify reproducing cells with great sensitivity, making it useful for detecting live bacteria in samples that may be contaminated with antibiotic-resistant bacteria (ABF). This is particularly important in identifying the risk of consuming ABF that can cause difficult-to-treat illnesses due to high levels of ARGs. RT-PCR is also used to qualitatively examine gene expression and is necessary for other molecular methods, such as qPCR for measuring RNA levels and microarray for identifying multiple target gene expressions [57][58]. In eukaryotic cells, RT-PCR can distinguish between exons and introns and is useful for identifying genetic disorders and evaluating antimicrobial drug therapy [58][59]. However, a significant drawback of this technique is the instability of RNA molecules, which makes sample processing challenging and requires experienced and well-trained personnel. Consequently, RT-PCR analyses can be time-consuming and expensive [60]. The specific genes targeted for detection may vary depending on the type of antimicrobial resistance being investigated and the bacterial species under study.
To assess the effectiveness of antibiotics against Chlamydia spp., Khan et al. [61] developed a RT-PCR assay, comparing it with standard immunofluorescence (IF) staining tests. The RT-PCR method revealed higher minimal inhibitory concentrations (MICs) of antimicrobial drugs for a Chlamydia pneumoniae test strain compared to IF staining, signifying its enhanced precision. Specifically, doxycycline and tetracycline exhibited the lowest MICs at 1 mg/L, while erythromycin and ciprofloxacin had higher values at 1.6 and 16 mg/L, respectively. On the other hand, Cangelosi et al. [62] pursued a new approach for assessing resistance in M. tuberculosis. They introduced a RT-PCR probe assay tailored to the precursor rRNA of M. tuberculosis. Precursor rRNA includes terminal stems that are excised during the formation of mature rRNA subunits. Disrupting RNA synthesis profoundly impacts the number of these stems in bacterial cells. The hybridization outcomes confirmed the assay’s specificity for M. tuberculosis, and it accurately predicted resistance to rifampin and ciprofloxacin, as anticipated.

3.1.3. PCR Combined with Restriction Fragment Length Polymorphism (PCR–RFLP)

PCR-RFLP is a technique that involves using restriction enzymes to digest amplified DNA fragments that contain unique nucleotide sequences. This process can be used to verify the target sequence of genes that encode AMR through RFLP analysis [63]. However, PCR-RFLP is a complex and multi-step procedure that is often considered unfavorable due to the extended duration necessary for obtaining outcomes and the increased expenses associated with diverse restriction enzymes [38]. For example, the blaCTX-M gene, renowned for its capacity to bestow resistance against extended-spectrum beta-lactam antibiotics, was detected using PCR-RFLP. PCR–RFLP has been utilized for the identification of genetic variations in the gyrA gene that are related to AMR in Campylobacter [64]. PCR-RFLP analysis unveiled the presence of a point mutation at the Thr-86 position of the gyrA gene in isolates that had previously been identified as ciprofloxacin-resistant using the MIC method. Another example in Salmonella highlighted the effectiveness of the PCR–RFLP technique in identifying mutations within the quinolone resistance-determining region of the gyrA gene in nalidixic acid-resistant strains found in poultry samples, thus underscoring the potential contribution of such point mutations to AMR [65].
The mismatched PCR-RFLP assay was developed to identify mutations in A. baumannii associated with fluoroquinolone (FQ) resistance. Two sets of primers were designed for the detection of gyrA and parC mutations, which was achieved by including artificial restriction enzyme cleavage sites in PCR products. The assay was evaluated using a total of 58 strains of A. baumannii and 37 strains of other Acinetobacter species. FQ-susceptible strains had their PCR products digested, while FQ-resistant strains with mutations in gyrA and parC did not. Importantly, the assay could distinguish A. baumannii from other Acinetobacter species, making it a valuable tool for quick FQ resistance assessment in A. baumannii without precise species identification. However, it cannot detect mutations at other locations or in other genes, and further research is needed to confirm its differentiation capabilities. Nonetheless, it offers a rapid, specific, and cost-effective method for detecting significant FQ resistance mutations in A. baumannii, aiding clinical assessments and epidemiological studies [66].

3.1.4. Real-Time Polymerase Chain Reaction (qPCR)

Quantitative PCR (qPCR) is a technique that can provide an estimate of the number of microorganisms present in a sample. Quantitative reverse transcription PCR (qRT-PCR) can also be employed to assess the expression level of resistance genes following exposure to varying antibiotic doses, providing an estimate of MIC values. However, the expense of qRT-PCR equipment and reagents generally exceeds what is reasonable for routine AST testing. In qPCR, the amplified fraction of DNA can be identified and measured throughout the amplification process by using fluorescent probes that release detectable signals [45][63][67]. The utilization of fluorescent probes, such as molecular beacons, in PCR amplifications facilitates real-time monitoring of the amplification process, resulting in quicker reaction times and the ability to quantify both the relative and absolute quantities of microorganisms in the sample [63]. However, qPCR equipment and reagents are more expensive than those used in traditional PCR. In addition, environmental or food matrix microorganisms that are not the focus of the research may inhibit the reaction [63]. To assess the clinical consequence of AMR, the use of RT-qPCR to measure the expression level of resistance genes is critical [38]. blaCTX-M gene is responsible for resistance to extended-spectrum beta-lactam antibiotics. It is frequently found in Gram-negative bacteria, such as E. coli, and qPCR was proven to successfully detect the existence of this gene [68]. The primers and probes used in qPCR are designed to target specific regions of the gene, allowing for its detection and quantification. Also, mecA gene MRSA can be detected using qPCR [69]. In addition, tet genes which encode resistance to tetracycline antibiotics are commonly found in various bacterial species. qPCR can be used to detect different tet genes, such as tetA, tetB, tetM, etc. [70]. Moreover, van genes are present in vancomycin-resistant Enterococcus (VRE) strains. qPCR can be used to detect vanA, vanB, and other van gene variants [71].

3.1.5. Isothermal Amplification Methods

Recent advances in molecular biology include the use of isothermal DNA amplification removing the requirement for thermocycling, which is required for standard PCR procedures. Numerous techniques for isothermal nucleic acid amplification have been devised, including nucleic acid sequence-based amplification (NASBA), strand displacement amplification (SDA), rolling circle amplification (RCA), transcription mediated amplification (TMA), recombinase polymerase amplification (RPA), helicase-dependent amplification (HDA), and loop-mediated isothermal amplification (LAMP) [72]. These methods paved the way for the development of cutting-edge, next-generation molecular diagnostics [73]. Yamamoto et al. [74] proposed a technique utilizing LAMP for the detection of carbapenem-resistant A. baumannii (CRAb) strains carrying the blaOXA-23 gene.
Furthermore, Poirier et al. [75] introduced the creation of LAMP rapid diagnostic assays. These assays were devised for the swift detection of both Klebsiella pneumoniae and carbapenemase genes within clinical samples [75]. A significant advantage of isothermal methods, as opposed to conventional PCR-based techniques, is the elimination of the need for thermocycling. Consequently, this leads to decreased power consumption and shorter analysis times. The reliance on thermocyclers has become outdated, given the availability of alternative temperature control methods like water baths or hotplates [76]. Furthermore, it is important to highlight that isothermal amplification, as opposed to PCR, offers improved speed and sensitivity [77]. This is because isothermal amplification does not rely on distinct heat cycles, thus enabling continuous amplification. As a result, this method can produce detectable amplicons in less than 10 min. Several isothermal approaches, such as RCA, LAMP, and HDA, provide the advantage of not requiring template denaturation and being capable of withstanding biological components, particularly in the case of LAMP and HDA [78]. While it is true that isothermal technologies such as LAMP demand more sophisticated primer design techniques, they offer improved specificity in comparison to PCR. A study on multiple isothermal approaches in terms of simplicity, affordability, sensitivity, and repeatability indicated that both LAMP and RPA methods show significant promise for point-of-need (PON) diagnostics, particularly in low-resource settings. Both methods employ a single-step process, involving incubation at a specific temperature, and they require minimal amounts of DNA template [76]. Furthermore, isothermal methods offer advantages for microfluidic-based techniques for the same reasons mentioned above [79]. It is worth noting that LAMP amplicons have the ability to be visually detected without the use of any specialized equipment, as evidenced by the observation of turbidity or color change [60]. However, isothermal techniques also possess significant limitations. The efficiency of multiplexing approaches in isothermal procedures is diminished because of the heightened complexity of the experimental design [80]. Furthermore, it is important to acknowledge that numerous isothermal amplification techniques involve intricate reaction processes, often demanding a significant number of primers. For example, the LAMP approach requires the use of 4–6 primers, whereas other techniques, like NASBA, entail multiple enzymatic phases [28][78]. Nevertheless, in addition to the speedy and simultaneous provision of trustworthy data, isothermal PCR has been observed to exhibit numerous advantageous characteristics, including cost-effectiveness, high sensitivity, specificity, ease of use, minimal spatial requirements, and widespread accessibility [35][81][82][83][84].

3.2. Next-Generation Sequencing (NGS)

NGS enables the rapid analysis of bacterial genomes within hours. A diverse range of technology solutions have been launched, including benchtop equipment with dimensions similar to a laser printer, such as 454 GS Junior (Roche, Basel, Switzerland), MiSeq (Illumina, San Diego, CA, USA), and Ion Torrent PGM (Life Technologies, Grand Island, NY, USA). In prior research, the MiSeq (Illumina) has exhibited a superior performance, boasting higher productivity per run and lower error rates. The results interpretation of whole bacterial genomes is typically carried out through either allelic comparisons [85] or the examination of single nucleotide polymorphisms (SNPs) [86]. Commercial software programs such as SeqSphere+ version 6.0.2 or BioNumerics version 8.1.1 have the potential to enhance the process of data assessment and interpretation.
The NGS permits resistance detection based on the existence of the underlying mechanism, as opposed to pharmacodynamic criteria alone [87], and, as such, may eventually transform microbial resistance testing. NGS has gained substantial recognition in the realm of resistance testing, particularly for infectious agents with slow growth and unconventional resistance patterns, such as Mycobacterium tuberculosis strains resistant to multiple drugs or extensively resistant (XDR). The capability to swiftly detect or exclude resistance determinants through NGS has profoundly influenced the therapeutic approaches adopted for these strains. The comprehensive genetic analysis within five days enabled accurate resistance discovery in the complete genome of M. tuberculosis isolates from Burmese, Hmong, and Indian immigrants living in the USA [88]. Similar genome sequencing results were presented for drug-resistant strains from Russia, which contained nearly all known mutations related to drug resistance [89]. However, resistance testing based on NGS is not limited to mycobacteria. NGS was utilized to detect transmissible plasmids in multidrug-resistant E. coli isolates with an ESBL phenotype. These isolates were consistently observed to transfer their cefotaxime resistance marker during laboratory conjugation studies [90]. In the course of epidemics, high-throughput sequencing proves to be a helpful tool for tracking resistant plasmids [91]. Nonetheless, while the commercial NGS assay known as the Hospital Acquired Infection BioDetection System, developed by Pathogenica in Boston, MA, USA, has proven effective in detecting outbreaks caused by Enterobacteriaceae strains carrying Extended-Spectrum Beta-Lactamase (ESBL), it has been observed to lack the capability to distinguish between ESBL and non-ESBL TEM and SHV β-lactamases or to identify specific CTX-M gene groups [92]. The costs and paucity of user-friendly bioinformatics platforms are now impediments to the widespread application of the NGS technology in microbiological diagnostic and resistance screening [93]. NGS methods deliver high-resolution genotyping in a short time frame of about two to five days [93]. Hence, NGS is poised to be the logical evolution for routine microbiological laboratory diagnostics of bacterial diseases and the forecasting of antibiotic susceptibility [94], probably replacing traditional cultural practices in the medium-to-long term [35]. In addition, NGS is able to characterize new resistance mechanisms when they are found. This may be accomplished by sequencing isolates that have already been shown to be phenotypically resistant, offering a significant advantage over other nucleic acid-based approaches [28].

3.2.1. Whole-Genome Sequencing (WGS)

In light of the current advancements in the cost-effectiveness of sequencing technology, WGS has become a readily available and useful tool for combating antibiotic resistance, a significant challenge to modern healthcare. WGS has made substantial progress in this field, ranging from the creation of innovative antimicrobial drugs and diagnostic tests to real-time surveillance. It has also contributed to the understanding of the factors that enable the emergence and persistence of resistance [38].
WGS-AST has evolved as a rapid and precise approach for detecting AMR. In certain instances, there is a clear correlation between genotype and phenotype, allowing the detection of specific AMR genes using clinically applicable molecular testing. However, a majority of antimicrobial resistance mechanisms entail multiple genes and intricate cellular signaling pathways, and many of them are not fully comprehended. Hence, the field of WGS offers an alternative approach for grasping these mechanisms. By capturing the entire genome of pathogens isolated in clinical settings, WGS enables a thorough identification of AMR. Furthermore, it has been reported by Yusof et al. [28] that WGS is one of the predominant approaches employed across the studies included in the systematic review and meta-analysis for identifying mutations in colistin resistance genes among K. pneumoniae isolates was WGS.
The WGS of DNA taken from the tested samples is assembled using programs such as SPAdes, Velvet, ABySS, and SOAPdenovo, which are based on a De Bruijn graph. Small sequencing reads may be assembled into contigs, which can be annotated to seek resistance genes. WGS does have one major drawback, however: it generates vast quantities of data, making it impossible to forecast the presence of undiscovered AMR genes or gene variations associated with antibiotic resistance. Fortunately, the datasets derived from the application of WGS to clinical isolates can be effectively analyzed using various freely available bioinformatic tools. These tools include ResFinder, AMRfinder, Comprehensive Antibiotic Resistance Database (CARD), ARG-ANNOT, ARGs-OAP, RGI, ARGs-OAP (v2), ARIBA, PointFinder, NCBI-AMRFinder, SRST2, SEAR, ShortBRED, PATRIC, SSTAR, KmerResistance, GROOT, and DeepArgs, among others. These tools are actively curated and offer the capability to identify genetic elements associated with antimicrobial resistance (such as SNP mutations, horizontal gene transfer, inversions, etc.) without necessitating extensive expertise in bioinformatics. For example, a draft genome of E. coli INF191/17/A was predicted as an extended-spectrum beta-lactamase (ESBL) strain carrying fourteen antibiotic resistance genes, using the ResFinder database [95]. The choice of database is dependent on the goal of each study (i.e., resistance genes, virulence genes, and proteins), as well as the sequence confidence contained in each database [96].
WGS used prediction tools that were dependent on large, high-quality AMR gene databases to determine and forecast the existence of AMR genes and other AMR mechanisms in a particular clinical isolate. The disparities among these tools are predicated upon the algorithms employed by their respective databases and the composition of their data. While numerous studies have highlighted the effectiveness of bioinformatic resources in detecting AMR, a recent inter-laboratory study conducted by Doyle and O’Sullivan [97] unveiled notable disparities among the results among various laboratories. These discrepancies were attributed to the varied software and analytical pipelines utilized for the identification and prediction of AMR gene presence or absence in identical clinical isolates. Consequently, a lack of alignment with phenotypic AST results was observed, signifying suboptimal concordance. The inconsistent findings seen in this study can be attributed to several factors, including the choice of bioinformatics tool, the quality of the WGS sequences, and the interpretation of the data obtained from the bioinformatic analysis.
The primary advantage of WGS-based techniques for studying AMR is that they may concurrently examine all the components involved in the establishment of the phenotypic and determine the link between each ARG and mobile or nonmobile elements harboring it. WGS also paves the way for genome-wide studies to be developed from the examination of several genes and mutations [85][86][98][99][100][101][102][103]. Katiyar et al. [104] employed WGS to conduct a thorough investigation of AMR genes, aiming to identify potential associations with phenotypes that could enhance the selection of more precise treatments. Notably, their research revealed that all fluoroquinolone-resistant strains exhibited mutations in the gyrA, gyrB, parC, and parE genes. This study advances the understanding of WGS’s capacity to predict resistance genotypes and their links to phenotypic traits, enabling the rapid detection of AMRdeterminants and facilitating targeted antibiotic usage directly guided by genetic sequences [105]. Moreover, WGS is crucial for conducting phylogenomic investigations encompassing the accessory genome that goes beyond the standard multi-locus sequence typing (MLST) analysis, which takes into consideration simply the core genome. The acquisition of virulence determinants and AMR is a crucial factor in the evolution of bacterial development [106][107]. Therefore, the utilization of WGS techniques is of utmost importance in comprehending the fundamental elements involved in the progression of virulence and AMR. In addition to their use in epidemiology, WGS methods play a crucial role in elucidating emerging mechanisms of resistance and predicting the potential evolution of resistance, including resistance to therapies that are not yet accessible on the market. Here, it needs to be highlighted that epidemiological investigations must inevitably rely on what is known. The discovery of new resistance mechanisms is typically laborious, and WGS techniques help tackle this challenge. Indeed, the use of these technologies is progressively expanding in the identification of genes associated with AMR, facilitating the creation of genome repositories and the annotation of genes derived from strains that are clinically significant [108].
In the United States, the national laboratory capabilities for monitoring AMR and conducting WGS are on the rise and expanding, consisting of networks run by universities and state public health laboratories under federal management. The Centers for Disease Control and Prevention (CDC) oversees the Antibiotic Resistance Laboratory Network (ARLN) to quickly identify the developing resistance risks in relation to healthcare settings, food, and the general public. This vast network executes WGS for a wide range of pathogens, encompassing all isolates of M. tuberculosis; Neisseria gonorrhoeae; and other important pathogens, such as those linked to outbreaks. One further limitation of WGS methods is their typical reliance on the isolation of the organism. In order to overcome this challenge, metagenomic analyses such as Nanopore, which is portable, rapid, and produces long reads, can be utilized, particularly in microbiomes with low complexity.

3.2.2. Metagenomics for Antimicrobial Surveillance

The main focus of metagenomic approaches is short-read NGS data, which make it possible to measure hundreds of transmissible resistance genes in a single sample without having to use any predefined genes. Consequently, these data will provide more insight into the types of bacteria, diseases, and virulence genes that are present, and the collected data may be reanalyzed in the future if new genes of interest are discovered [109]. It has been shown that metagenomics is superior to conventional methods of AMR surveillance in pig herds [110], and it has proven to be an efficient tool for comparing AMR in animals [111], as well as for investigating epidemiological data [112]. Due to its various benefits, metagenomics is widely regarded as a promising method for AMR surveillance. Eventually, it is plausible that a centralized surveillance system for AMR may emerge that facilitates the detection of all resistance genes [8][109].
In Neisseria gonorrhoeae, an analysis of transcriptomes revealed that the transcriptional response to azithromycin is influenced by genetic distance and the population structure. When exposed to drugs, transcripts for rpsO, rplN, omp3, and NGO1079 exhibited the most significant changes between phenotypes [113].
The expression of almost half of the genes involved in multidrug resistance in Salmonella enterica serovar Typhimurium was altered after exposure to subinhibitory doses of chlortetracycline and florfenicol. Notably, there was an increase in genes associated with adhesion function and those located inside Salmonella pathogenicity islands subsequent to drug exposure [114].
Metagenomics has emerged as a valuable tool for the identification and analysis of pathogens and their genotypic resistance [56], and it has the potential to delineate microbial communities without the need for traditional culture-based methods [115][116]. This approach involves the sequencing of the entire genetic material of the community. Boolchandani et al. [96] conducted a comprehensive analysis to elucidate the inherent benefits and drawbacks associated with AMR gene databases. Metagenomic sequencing has been found to be highly effective in the analysis of microorganism ecology [67][117]. Along with NGS, a comprehensive database of sequences from diverse contexts is acquired [118]. Although it has the disadvantage of being a pricey technology, it is a solid choice for providing the capability for an extensive analysis in research involving bacterial resistomes [119]. Furthermore, metagenomics, being an open-approach molecular technique, is subject to some constraints. One such drawback is the potential inadequacy in providing comprehensive sequencing of a species’ genome, particularly when the samples originate from intricate communities like those seen in soil ecosystems [38].

3.3. DNA Microarray

Microarray technology is a noteworthy avenue to be acknowledged in the context of analyzing genetic AMR in bacteria. The utilization of this methodology enables the examination of gene expression through the process of hybridizing oligonucleotide sequences that serves to purify and amplify specific RNA molecules from the targeted sample. This permits its usage for numerous applications, especially for determining the function of specific genes [120][121]. This method has been widely recognized as the most effective method for studying transcriptomes. The application of microarray technology for the identification of AMR genes can be maximized by various hybridization techniques, allowing for the simultaneous analysis on a single substrate (such as glass, membrane, or gel pad) containing several probes [121][122][123]. Another important benefit is that preceding cultivation of bacteria is not essential, as the DNA sample may be immediately isolated to generate the microarrays [124]. Microarray usage has been superseded in recent years by NGS approaches. One disadvantage of microarrays, for example, is the necessity for the previous information on the genetic areas to be investigated. In addition, by analyzing the selected target locations alone, one may end up missing vital and critical information in the samples. Another key challenge is the hybridization of identical sequences, hindering the reading and analysis of target genes. An example of a DNA microarray is the one developed by Frye et. al. [125] to detect ARGs identified in the National Center for Biotechnology Information Database.

3.4. Fluorescence In Situ Hybridization (FISH)

The conventional method of FISH relies on the targeted binding of fluorescently labeled, single-stranded oligonucleotide probes, typically ranging from 18 to 25 bases in length, to the ribosomal RNA (rRNA) of the desired organism. This technique is then followed by an analysis using a fluorescence microscope, which enables the identification of microorganisms at either the genus or species level. In theory, it is possible to hybridize FISH probes with many types of intracellular RNAs. However, rRNA is particularly advantageous as a target for FISH due to the abundance of ribosomes in a cell involved in protein synthesis, which enables the amplification of fluorescence intensity [126]. This classic FISH approach is both speedy and easy to standardize and may be employed as such for molecular rapid testing. Minor alterations to the procedure entail the use of commercially patented peptide nucleic acid (PNA) probes or probes that integrate locked nucleic acids (LNAs) as opposed to conventional single-stranded DNA probes. The PNA-FISH approach is advantageous in reducing nonspecific probe attachment mainly because of the electrically neutral backbone of the oligonucleotides. This technology is particularly suitable for routine diagnostic purposes due to its improved level of consistency. However, PNA probes that are covered by patents tend to have a high cost [127]. FISH is highly suited for the discovery of resistance determinants if two conditions are met. Ribosomally mediated resistance, including its influence on antibiotic drugs such as macrolide or linezolid, is particularly advantageous due to the abundance of rRNA copies in viable cells, thus facilitating the generation of distinct fluorescence signals. Moreover, FISH may be utilized efficiently in cases when just a limited number of variable bases exhibit resistance. This implies that a probe panel with a high number of probes is not necessary. The initial study of resistance testing based on FISH for mechanisms of resistance unrelated to those relying on rRNA has been reported [128]. FISH technology has advanced to include signal-amplified, catalyzed reported deposition (CARD) FISH; doubly labeled oligonucleotide probe-based (DOPE-based) FISH; combinatorial labeling and spectral imaging (CLASI) FISH; and the combination of FISH with other diagnostic approaches, as well as FISH procedures for gene identification which require in situ amplification of the respective gene, as in case of the RCA FISH [129]. Some examples of AMR genes that can be detected by FISH include blaCTX-M [130], mecA [131], and vanA [132].
The rapidity, simplicity, and low cost of the FISH-based identification of resistance determinants make it a potentially useful diagnostic method. The concomitant quick diagnosis of antimicrobial resistance can provide a prompt adjustment of antimicrobial therapy, resulting in potential benefits for the patient’s well-being. The key benefit of FISH is its potential application for resistance testing directly from primary materials, including tissues, with minimum effort. Hence, FISH may also be utilized in resource-limited environments where pricey technologies are not accessible. In contrast to PCR, FISH may also ascribe a particular resistance mechanism to bacteria. However, thus far, FISH is confined to only a few indications for which methods have been published [35]. As an additional issue, standardization of FISH-based resistance testing is often absent. If used from primary sample materials like tissue, tissue autofluorescence has to be addressed, requiring some knowledge to understand such diagnostic results. To minimize the potential for misinterpretations, it is essential to conduct counterstaining with a pan-eubacterial FISH probe and nonspecific DNA staining when conducting a FISH analysis on tissue samples. These steps are crucial for confirming the presence of nucleic acids associated with the identified infections [133]. Considering the aforementioned constraints, it is likely that FISH for resistance testing will serve as an interim method until amplification-based solutions are readily available as user-friendly and economically viable benchtop systems in the commercial sector [35].

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Dina Yamin
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Abubakar Muhammad Wakil
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Mohammed Dauda Goni
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Shazana Hilda Shamsuddin
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Fatin Hamimi Mustafa
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Wadha A. Alfouzan
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Mohammed Alissa
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Amer Alshengeti
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Rana H. Almaghrabi
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Mona A. Al Fares
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Mohammed Garout
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Nawal A. Al Kaabi
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Ahmad A. Alshehri
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Hamza M. Ali
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Ali A. Rabaan
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Fatimah Abdullah Aldubisi
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Chan Yean Yean
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Nik Yusnoraini Yusof
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