Section 3 Diagnosis

**Chapter 5**

## Recent Progress in the Diagnosis of *Staphylococcus* in Clinical Settings

*Xue-Di Zhang, Bin Gu, Muhammad Usman, Jia-Wei Tang, Zheng-Kang Li, Xin-Qiang Zhang, Jia-Wei Yan and Liang Wang*

### **Abstract**

*Staphylococci* are mainly found on the skin or in the nose. These bacteria are typically friendly, causing no harm to healthy individuals or resulting in only minor issues that can go away on their own. However, under certain circumstances, staphylococcal bacteria could invade the bloodstream, affect the entire body, and lead to life-threatening problems like septic shock. In addition, antibiotic-resistant *Staphylococcus* is another issue because of its difficulty in the treatment of infections, such as the notorious methicillinresistant *Staphylococcus aureus* (MRSA) which is resistant to most of the currently known antibiotics. Therefore, rapid and accurate diagnosis of *Staphylococcus* and characterization of the antibiotic resistance profiles are essential in clinical settings for efficient prevention, control, and treatment of the bacteria. This chapter highlights recent advances in the diagnosis of *Staphylococci* in clinical settings with a focus on the advanced technique of surface-enhanced Raman spectroscopy (SERS), which will provide a framework for the real-world applications of novel diagnostic techniques in medical laboratories via bench-top instruments and at the bedside through point-of-care devices.

**Keywords:** *Staphylococcus*, rapid diagnosis, mass spectrometry, Raman spectrometry, machine-learning algorithm

#### **1. Introduction**

Bacteria belonging to the genus *Staphylococcus* is widely distributed in nature and is a common pathogen that causes nosocomial and community-acquired infections. It is a facultatively anaerobic Gram-positive coccus that provides a serious threat to human health due to a combination of toxin-mediated virulence, invasiveness, and antibiotic resistance. *Staphylococcus* is commonly found in the air, water, dust, and human and animal excretions. Every year, Staphylococcus *aureus* (*S. aureus*) causes almost half a million hospitalizations and 50,000 deaths in the United States [1]. This chapter reviewed the recent progress in the diagnosis of staphylococcal bacteria in clinical settings, including the variety of commonly used techniques ranging from traditional culture to emerging molecular methods. Conventionally, the accurate identification of clinical isolates of *Staphylococcus* needs a battery of tests, which is costly in resource-limited settings, though biochemical tests and drug susceptibility methods have the advantages of low cost and easy operation. However, these methods are limited to phenotypic detection only. The nucleic acid amplification methods such as PCR, real-time fluorescence quantification of nucleic acids and ring-mediated isothermal amplification are sensitive and can detect genes for strain typing. In addition, new technologies such as matrix-assisted laser desorption ionization timeof-flight mass spectrometry, gene sequencing, and SERS are ideal for phenotypic abnormalities, slow growth, and culture-negative infections, etc. The principles, characteristics, and applications of which are therefore reviewed, with an emphasis on the use of SERS as an emerging technique for the detection of bacterial pathogens more efficiently.

## **2. Clinical significance of** *Staphylococcus* **infections**

#### **2.1 Staphylococcal species**

The genus *Staphylococcus* belongs to a diverse group of Micrococcaceae bacteria that can cause many diseases. They have the capacity to produce a wide range of extracellular toxins and cell surface virulence factors. There are currently 85 species and 30 subspecies in the genus [2]. Although most people have antibodies with bodies to staphylococcal infection, these are usually ineffective, and the disease can reoccur multiple times [3] . *Staphylococci* can cause a variety of infections: (1) *S. aureus* causes localized abscesses in different places and superficial skin diseases (boils, styes) [4]; (2) *S. aureus* causes deep-seated infections like osteomyelitis, endocarditis, and potentially fatal skin infections [5]; (3) *S. aureus*, along with *Staphylococcus epidermidis*, is a leading cause of hospital-acquired (nosocomial) surgical wound infection and infections caused by indwelling medical device [6]; (4) *S. aureus* releases enterotoxins into food, which causes food poisoning [7]; (5) *S. aureus* releases superantigens into the bloodstream, which results in toxic shock syndrome [8]; and (6) urinary tract infections are caused by *Staphylococcus saprophyticus*, particularly in females [9]. Other *Staphylococci* species, e.g., *Staphylococcus lugdunensis*, *Staphylococcus haemolyticus*, *Staphylococcus warneri*, *Staphylococcus schleiferi,* and *S. intermedius*, are uncommon pathogens. *Staphylococcus* parasites in humans and primates mainly include the following: *S.* aure*us*, *S. epidermidis*, *Staphylococcus capitis*, *Staphylococcus caprae*, *S. saccharolyticus, S. warneri, S. haemolyticus, Staphylococcus hominis, S. saprophyticus, Staphylococcus pasteuri,* and *Staphylococcus xylosus,* etc., among which *S. aureus* colonizes the nasal canals, axillae, and pharynx [10–12], while *S. epidermidis* is a widespread human skin commensal [13]. In addition, *Staphylococcus* species are usually divided into coagulase-positive *Staphylococcus* (CPS) represented by *S. aureus,* and coagulase-negative *Staphylococcus* (CNS) represented by *S. epidermidis*. The most common type *is S. aureus subsp. aureus,* among the clonal populations followed by *S. epidermidis*, *S. haemolyticus*, and *S. saprophyticus subsp. saprophyticus*, etc.

#### **2.2 Staphylococcal biological properties**

*Staphylococcus* is spherical or oval in shape, 0.5–1.5 μm in diameter, forming single, paired, quadruple, short-chain, and irregular grape bunches or clusters. *Staphylococcus* has no flagella and no spores except for a few strains which generally do not form capsules [14]. *S. aureus* produces a wide range of extracellular proteins and polysaccharides, a number of which are associated with virulence [15]. Except for *S. aureus subsp. anaerobius* and *S. saccharolyticus*, most *Staphylococci* are facultative anaerobes. The nutritional requirements for cultivation are not stringent, and the optimum pH is 7.4–7.6.

*Staphylococcus* can grow well on blood agar, brain heart infusion agar, tryptone soy agar, and mannitol salt agar [16]. After 24 h of incubation in the atmospheric environment at 34–37°C, they can form round, smooth, neat-edged, raised, moist, opaque, creamy, porcelain white, pale yellow, or orange-yellow colonies. *S. aureus subsp. anaerobius*, *S. saccharolyticus*, *Staphylococcus auricularis*, *Staphylococcus vitulinus*, *S. lentus*, and *Staphylococcus equorum* grow slowly and gradually, and their colonies are commonly seen after 36 h of incubation. Small colony variants (SCVs) of *Staphylococcus* grow extremely slowly on conventional medium and the colony color is lighter with less pigment [17]. *Staphylococci* are generally salt-tolerant and grow well on agar with 6.5% NaCl. Some Staphylococcal species like *S. aureus* can produce hemolysin, and an apparent β-hemolytic ring can be seen after 24 h of incubation on sheep blood or rabbit blood agar [18]. When routinely cultured, many *Staphylococci* produce fat-soluble carotenoids visible to the naked eye, making the colonies yellow, orange-yellow, or orange and not spread into the agar medium. *Staphylococcus* does not form pigment in liquid medium, grows uniformly and turbidly, slightly precipitates at the bottom of the tube, and is easy to disperse when shaken. *S. aureus* colonies are yellow on Mannitol Salt Medium (MSM). White precipitation rings can be formed around *S. aureus* colonies on Egg-Yolk Salt Agar Medium. Moreover, *S. aureus* colonies are black on Baird-Parker agar, surrounded by turbid bands and transparent rings. The surface antigens of *Staphylococcus* are mainly *Staphylococcus* Protein A (SPA) and polysaccharide antigens. SPA is a surface protein on the cell wall with species and genus specificity while polysaccharide antigens are type-specific. *Staphylococcus* is one of the most resistant non-spore-forming bacteria, which is resistant to dryness and high salinity and can grow in a medium containing 100–150 g/l NaCl.

#### **2.3 Distribution and epidemiology**

*Staphylococcus* is widely distributed in nature, mainly parasitic on mammals and birds' skin, sebaceous glands and mucous membranes. Some *Staphylococcus* and its subspecies are parasitic in selected parts of the host. *S. capitis subsp. capitis* mainly exists in great amounts in the sebaceous glands on the top of the head and forehead of humans, while *S. capitis subsp. ureolyticus* is present in abundance in the armpits of humans. *S. aureus* has the dual characteristics of a colonized and pathogenic bacterium, mainly distributed in the nasal vestibule. About 20% of people have persistent nasal cavity colonization by *S. aureus*, and 30% have intermittent colonization. In addition, *S. aureus* is also colonized in the axilla, pharynx, groin and gastrointestinal tract, etc. [13]. It has been shown in the study that *S. aureus* strains isolated from the blood of 82% of patients with bacteremia are identical to those isolated from the nasal cavity [3, 19]. More than 50 million people are expected to be infected with methicillin-resistant *S. aureus* (MRSA), which is easily transmitted through skin contact. However, MRSA infection is difficult to cure due to its resistance to most antibiotics, while children, elderly people, and sick patients in hospitals and nursing homes are particularly susceptible. While the number of MRSA bloodstream infections in the US has declined in recent years, the infection still resulted in 20,000 fatalities in 2017. In addition, MRSA was responsible for more than 100,000 deaths worldwide in 2019, highlighting the importance of improved surveillance to prevent and manage the spread of this potentially dangerous bacterium [20]. *S. epidermidis*

is the most common *Staphylococcus* on the human body surface, especially in moist areas such as armpits, groin, perineum, anterior nostrils, and toes [21]. *S. haemolyticus* is easily isolated from the apocrine glands in the axilla [16]. In addition, *S. saprophyticus subsp. saprophyticus* is easily isolated from the female rectum and urinary system [22].

#### **2.4 Staphylococcal infections**

*S. aureus* bacteremia, which often leads to metastatic foci of infection, can occur at any site, but it is especially common with infections associated with intravascular catheters. *S. epidermidis* and other coagulase-negative *Staphylococci* are gradually causing hospital-acquired bacteremia because they can form biofilms on intravascular catheters and other foreign objects. *Staphylococcal* bacteremia is a substantial reason for disease and death in debilitated people [23]. Many *Staphylococci* are opportunistic pathogens of the skin and mucous membranes. *S. aureus* is the primary clinic pathogenic bacteria of humans [24]. The diseases caused by the bacterium can be roughly divided into purulent infections and toxin-causing diseases. The former includes superficial infections (boils, carbuncles, folliculitis, paronychia, styes, wound suppuration, abscesses), deep tissue infections (mastitis, cellulitis, necrotizing fasciitis, osteomyelitis, arthritis), and systemic infections like bacteremia. Toxin-related diseases caused by *S. aureus* mainly include staphylococcal scalded skin syndrome (SSSS) caused by an exfoliative toxin, also known as exfoliative dermatitis; toxic shock syndrome (TSS) caused by toxic shock syndrome toxin-1 (TSST-1) and *S. aureus* food poisoning (SFP) caused by staphylococcal enterotoxins (SEs). Lymphangitis is caused by bacterial infection of the lymphatic vessels. The organisms that cause the disease enter the body through a skin wound and are either *Streptococcus* or *Staphylococcus*. The inflamed lymph vessels appear as red streaks under the skin that extend from the infection site to the groin or armpit. The other symptoms may include fever, chills, headache, and appetite loss. The most typical manifestation of staphylococcal disease is skin infections. Superficial infections can be generalized with vesicular pustules and crusting (impetigo) or focal with nodular abscesses (furuncles and carbuncles). Deeper cutaneous abscesses are relatively common. There could be severe necrotizing skin infections. Staphylococcal newborn infections, which can cause skin lesions with or without exfoliation, bacteremia, meningitis, and pneumonia, typically appear within 6 weeks of delivery [25].

Coagulase-negative staphylococci (CNS) represented by *S. epidermidis* have become the leading pathogen of nosocomial infection in recent years. They can cause prosthetic valve endocarditis, urinary system infection, central nervous system infection, and bacteremia. *S. lugdunensis* can cause endocarditis, arthritis, urinary tract infections and bacteremia. In addition, *S. saprophyticus* can often cause urinary tract infection, prostatitis, wound infections, bacteremia, and so on. Chronic infection or intracellular parasitism of *S. aureus* often appears in the form of SCVs during in vitro culture [26]. SCVs are now defined as a subgroup of microorganisms that grow slowly on agar medium, form small colonies, have reduced or absent pigment production, and have altered expression of virulence factors (e.g., reduced production of α-hemolysin). This is quite different from typical *S. aureus* colonies, so it is easy to miss its detection in routine microbial identification. However, SCVs are closely related to chronic and recurrent infections [27, 28]. Typical *S. aureus* colonies and SCVs often coexist on agar medium. Therefore, in-depth study of SCVs is critical to the treatment and control of clinical infections.

## **3. Traditional identification of staphylococcal bacteria**

### **3.1 Microscopic inspection and culture**

Microscopic inspection is based on performing morphological tests on colonies. Clinical specimens were smeared, Gram-stained, and the morphology was observed under a microscope. *S. aureus* is typically identified using tests for clumping factor, coagulase, hemolysins, and thermostable deoxyribonuclease. There are currently available latex agglutination tests. The identity of *S. epidermidis* is established by using commercial bio-typing kits. *Staphylococci* are catalase positive and can withstand quite high sodium chloride concentrations (7.5–10%). This feature is often used in the preparation of *Staphylococci*-specific media. A rapid and efficient method for classifying Gram-positive bacteria species was developed using hyperspectral microscope images. Traditional bacteria detection and identification procedures using specific agar media remain the "gold standard" to differentiate the microorganisms. Furthermore, traditional serotyping approaches based on antibodies or genetic matching, such as plasmid fingerprinting, have been developed [29].

## **3.2 Staphylococcal biochemical identification**

The majority of staphylococcal oxidase tests are negative. *Staphylococcus sciuri*, *S. vitulinus*, *S. lentus*, *Staphylococcus fleurettii,* and *Staphylococcus caseolyticus* are positive for oxidase tests due to the presence of Cytochrome c oxidase. *Staphylococcus* catalase tests are usually positive, while *S. aureus subsp. anaerobius* and *S. saccharolyticus* are negative. Most *Staphylococcus* species can decompose a variety of carbohydrates and deoxidize nitrates, as they are sensitive to lysostaphin and furazolidone, and are resistant to bacitracin and vibriostatic agent O/129 (2,4-diamino-6,7-diisopropylpteridine). The plasma coagulase test and the thermostable nuclease test for *S. aureus* are positive. *S. aureus* is sensitive to novobiocin. The biochemical identification of *Staphylococcus* and other Gram-positive cocci is shown in **Table 1**. It can be known from the table that *Staphylococcus* catalase is positive, which is different from *Enterococcus* and *Streptococcus*. The identification of biochemical reactions within the *Staphylococcus* species is shown in **Table 2**. Mature commercial biochemical identification systems include API Staph (bioMérieux), ID32 Staph (bioMérieux), Vitek (bioMérieux), MicroScan Product Pos ID family (Siemens Health-care Diagnostics), BD BBL Crystal (BD Diagnostics Systems), Sensitire GPID (TREK Diagnostic Systems), etc. Most laboratories use commercial identification systems or automated identification instruments. These methods are simple, convenient, and accurate. However, uncommon strains or strains with phenotypic variants (such as SCVs) require molecular identification due to altered biochemical response patterns.

## **3.3 Antibiotic resistance**

The conventional approaches for antibiotic susceptibility testing of *Staphylococci* include disk diffusion and broth dilution, which can be operated following the American Clinical and Laboratory Standards Institute (CLSI) and the European Committee for Antimicrobial Susceptibility Testing (EUCAST). The disc diffusion method, also known as the Kirby-Bauer (K-B) method, is based on the principle of sticking a disc containing anti-bacteial drugs onto an agar plate inoculated with the test bacteria. The medicine in the disc absorbs the water in the agar and dissolves continuously to spread around


## **Table 1.**

*Main biochemical identifications of Staphylococcus and other gram-positive cocci.*

#### *Recent Progress in the Diagnosis of* Staphylococcus *in Clinical Settings DOI: http://dx.doi.org/10.5772/intechopen.108524*



#### *Staphylococcal Infections - Recent Advances and Perspectives*

#### *Recent Progress in the Diagnosis of* Staphylococcus *in Clinical Settings DOI: http://dx.doi.org/10.5772/intechopen.108524*



#### *Staphylococcal Infections - Recent Advances and Perspectives*


## **Table 2.**

*Identification of biochemical reactions within the species of Staphylococcus.*

## *Recent Progress in the Diagnosis of* Staphylococcus *in Clinical Settings DOI: http://dx.doi.org/10.5772/intechopen.108524*


*Staphylococcal Infections - Recent Advances and Perspectives*


#### *Recent Progress in the Diagnosis of* Staphylococcus *in Clinical Settings DOI: http://dx.doi.org/10.5772/intechopen.108524*


## **Table 3.**

*The main resistant phenotypes and screening methods of Staphylococcus.*

#### *Recent Progress in the Diagnosis of* Staphylococcus *in Clinical Settings DOI: http://dx.doi.org/10.5772/intechopen.108524*

the disc. The growth of bacteria is inhibited within the range of inhibitory concentration around the disc, thus forming a transparent antibacterial ring. Its size reflects the susceptibility of the test bacteria to the drug and is negatively correlated with the test bacteria's minimum inhibitory concentration (MIC). The principle of the broth dilution method is to use Mueller Hinton Broth (MHB) to dilute the antibacterial drugs to different concentrations and then culture the bacteria. The MIC or the minimal bactericidal concentration (MBC) is tested by observing the growth of the bacteria.

Commercial detection systems for the broth dilution method for drug susceptibility mainly include bioMérieux (http://www.biomerieuxusa.com), Siemens Healthcare Diagnostics (http://www.siemens.com), Becton Dickinson Diagnostics (http:// www.bd.com) and Thermo Scientific (http://www.thermoscientific.com). *S. aureus* and *S. epidermidis* have no natural resistance, while *S. saprophyticus*, *Staphylococcus cohnii*, and *S. xylosus* are naturally resistant to novobiocin, and *S. saprophyticus* and *Staphylococcus kloosii* are naturally resistant to fosfomycin. The common resistant phenotypes and screening methods of *Staphylococcus* are shown in **Table 3**. *S. aureus* is a serious danger to worldwide public health security, especially methicillin-resistant *S. aureus* (MRSA), which has become the leading pathogen of nosocomial infections worldwide. Besides that, drug-resistant genes of multidrug-resistant *S. aureus* strains can be spread among humans, animals, and the environment through horizontal transfer [30], making the problem of bacterial drug resistance increasingly serious. Turner et al. [31] reported that *S. aureus* had developed different degrees of resistance to almost all antibiotics in the past 10 years. MRSA refers to *S. aureus* carrying the *mecA* gene and (or) *S. aureus* with a MIC of Oxacillin >4 mg/l, which can be divided into hospital-acquired (HA-MRSA) and community-acquired (CA-MRSA) strains. The drug resistance mechanism of MASA is complex and mainly related to the *mecA* gene encoding penicillin-binding protein PBP2a [32], the *mecC* gene encoding penicillin-binding protein PBP2c [33, 34], exogenous acquisition of staphylococcal chromosome *mec* gene [35], *fem* gene [36, 37] and other factors.

The cefoxitin disk diffusion assay of *mecA*-mediated oxacillin resistance for CoNS in **Table 3** does not apply to *S. lugdunensis* and *S. pseudintermedius*. The detection method of *S. lugdunensis* is the same as that of *S. aureus*. The oxacillin resistance of *S. pseudintermedius* was detected by 1 μg oxacillin disk, while the cefoxitin disc and the MIC methods were both unreliable. When using vancomycin to treat *S. aureus*, *S. aureus* is easy to develop from sensitivity to an intermediate or resistance phenotype. Attention should be paid to the detection of vancomycin sensitivity to *S. aureus*. The detection of vancomycin-intermediate *S. aureus* (VISA) and vancomycin-resistant *S. aureus* (VRSA) by automated drug susceptibility systems or disc diffusion methods is complex and the results are unreliable. Therefore, further confirmation is required. Biochemical identification and routine drug susceptibility testing require the acquisition of pure cultured colonies, which is time-consuming for slow-growing staphylococci.

## **4. Rapid diagnosis of Staphylococcal infections**

#### **4.1 PCR and its derived technologies**

#### *4.1.1 Polymerase chain reaction (PCR)*

Polymerase chain reaction (PCR) is the most extensively used nucleic acid amplification method for bacterial serotyping and confirmation. RT-PCR (Real-time quantitative PCR) has high sensitivity, high specificity, low pollution, and a high degree of automation [38]. Its reaction is monitored in real-time and can quantitatively detect target genes. The detection time of clinical samples can even be shortened to 1 h. Recent literature reports show that RT-PCR technology is currently the most accurate, reproducible and internationally recognized standard method for the quantitative and qualitative detection of nucleic acid molecules. For example, Okolie et al. [39] simultaneously detected marker genes of Coagulase-negative *Staphylococcus* (CoNS), staphylococcal protein A (SPA), Panton-Valentine leukocidin (PVL) and methicillin-resistant *S. aureus* (MRSA) by applying real-time PCR polymorphism analysis. Yang et al. [40] also found that the effect of real-time RT-PCR in detecting methicillin-resistant *S. aureus* (MRSA) was better than drug susceptibility testing. The enterotoxin produced by *S. aureus* in food can cause food poisoning, so *S. aureus* is also a critical detected bacteria in the food industry. Huang et al. [41] found that the TaqMan-MGB probe RT-PCR method established for the *coa* (encoding coagulase) gene of *S. aureus* can enhance the speed and sensitivity of food detection. Multiplex PCR is a PCR reaction that simultaneously amplifies two or more DNA sequences from the same sample [42]. In a study by Schmitz et al. [43] a multiplex PCR on bacteria colonies chosen directly from agar plates without prior DNA preparation is described. In parallel, specific primers were used to detect staphylococcal genes *coa* and *mecA.* Tsai et al. [44] applied multiple PCR technology to detect *Staphylococcus* and *Vibrio vulnificus* in blood and tissue samples of 99 patients with surgically confirmed necrotizing fasciitis (NF) of the extremities. These techniques can be time-consuming and require trained operators who are familiar with the procedure. Therefore, it is interesting to develop a fast, simple, and consistent technology to identify and distinguish between different bacterial species and serotypes.

#### *4.1.2 Isothermal nucleic acid amplification technology*

Classical nucleic acid amplification technology has multiple thermal cycling steps, requires strict laboratory conditions, and relies on the use of high-precision instruments that are difficult to miniaturize. The isothermal amplification technology can perform accurate and rapid analysis on site, and is more suitable for integration into miniaturized systems [45]. Loop-mediated isothermal amplification (LAMP) technology was created by Notomi et al. in 2000 [46]. It is a nucleic acid amplification technology that can perform rapid, specific and sensitive detection of target sequences under isothermal conditions. Yin et al. [47] utilize LAMP technology combined with lateral flow assay (LFA) to simultaneously detect *S. aureus sea* and *seb* genes. Strand displacement amplification (SDA) is an enzymatic reaction-based DNA in vitro amplification technology [48]. After the initial thermal denaturation of the dsDNA target, it only needs to reach 37°C for the reaction. Cai et al. [49] reported an SDA-based biosensor for the detection of *S. aureus*. The aptamer was immobilized on streptavidin-modified magnetic beads as a biorecognition molecule, and then bound to its complementary ssDNA. When *S. aureus* is present, the aptamer binds to it, releasing complementary DNA into the solution and detecting pathogenic microorganisms by SDA amplification. The limit of detection (LOD) of the sensor was 8 CFU/ ml, and the recovery rate was more than 93.9%. The time-consuming amplification step was optimized from 2 h to 45 min. Although the reaction time was longer compared to other amplification reactions, it had high sensitivity and easy-to-reach reaction temperature advantages. In addition, there are room temperature amplification technologies such as recombinase polymerase amplification (RPA), rolling circle amplification (RCA), simultaneous amplification and testing (SAT), etc.

#### **4.2 Immunoassay**

Immunology-based rapid detection technologies for microorganisms include Immune Fluorescence Assay (IFA), Enzyme-linked Immunosorbent Assay (ELISA), Chemiluminescence Immunoassay (CLIA), Radio Immunoassay (RIA), Immunomagnetic Separation (IMS), and Immune Colloidal Gold (ICG) technique, etc. Among them, IMS is a technology that uses the magnetic responsiveness of the magnetic beads to enrich and separate the target substances by coating the recognition substances such as antigens and antibodies on the superparamagnetic nanomagnetic beads with a specific particle size range. The technical operation is simple and fast, with high specificity and sensitivity. Currently, it has been extensively used in protein and nucleic acid purification, cell separation and pathogen detection, such as Multiple Polymerase Chain Reaction (MPCR), Recombinase Polymerase Amplification (RPA), and Loop-Mediated Isothermal Amplification (LAMP). Zhou et al. [50] use avidinlabeled magnetic beads and biotin-labeled SPA monoclonal antibodies to prepare immunomagnetic beads to enrich *S. aureus* from sputum, which is then combined with MPCR to detect the *mecA* gene and *femA* gene of MRSA strains in sputum samples. The detection of MRSA strains has advantages in terms of detection rate, sensitivity and specificity, especially because the detection time can be shortened from 48–72 h to 4–6 h. The most common application of immunoassay techniques is in the detection of *Staphylococcus* toxin. Based on the existing ELISA method, Chang et al. successfully constructed a new staphylococcal enterotoxin A (SEA) detection method for microscale solid phase extraction MSPE-ELISA on magnetic microspheres modified with staphylococcal enterotoxin A (SEA) as an aptamer and introduced solid magnetic phase extraction technology. The sensitivity of magnitude is higher as compared to ELISA kits, enabling the high-sensitivity detection of SEA trace amounts in actual samples. Shan et al. [51] used a carboxyl-modified fluorescent microsphere (PSA-R6G) to immobilize a monoclonal antibody against *S. aureus* as a capture probe. A fluorescein isothiocyanate (FITC)-labeled *S. aureus* secondary fluorescein antibody served as a sensitive reporter antibody. After double labeling with R6G and FITC, multiparameter flow cytometry analysis observed the enriched *S. aureus*. Zhao et al. [52] use vancomycin-immobilized gold nanoparticles (VAN-Au NPs) as the first recognition factor to capture *S. aureus*, and use the second recognition agent of porcine immunoglobulin G (IgG) to ensure its specificity. A novel sandwich-based lateral flow assay (LFA) for highly sensitive and selective detection of *S. aureus*. Tarisse et al. [53] developed an immunoassay that detects the staphylococcal enterotoxins SEA, SEG, SEH, and SEI with high sensitivity and specificity.

### **4.3 Mass spectrometry**

The molecular weight and structure of different biomolecules, such as proteins, nucleic acids, and polysaccharides, can be analyzed using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) technology. The basic principle behind matrix-assisted laser desorption is as follows: after the matrix and the sample form an eutectic, the matrix and the sample absorb laser energy to desorb the sample, and charge transfer between the matrix and the sample occurs to ionize the sample molecules. The mass-to-charge ratio of ions is proportional, and the mass-to-charge ratio can be measured according to the flight time to the detector, and a characteristic fingerprint can be obtained through software processing [54]. MALDI-TOF MS technology has the characteristics of rapidity, accuracy, sensitivity and automation [55], and gradually occupies an important position in the identification of microbiology laboratories [56]. Rychert et al. [57] conducted a multicenter study on Gram-positive aerobic bacteria, and the results showed that in 1146 Gram-positive bacteria samples, the accuracy rate at the species level was 92.8%, and the accuracy at the genus level could reach 95.5%. The time required for MALDI-TOF MS to obtain identification results has been shortened from 5 to 48 h or even longer via traditional biochemical methods to less than 6 min per sample, and the cost of reagents for single-sample detection has been reduced to less than 1/4 of traditional methods. The overall identification accuracy of MALDI-TOF MS is >90%, which is higher than that of conventional methods (80–85%); in addition, MALDI-TOF MS is easy to operate, which significantly shortens the time for professional and technical training of personnel [58, 59]. MALDI-TOF MS can also be used to analyze the antibiotic resistance of bacteria. The advantages of MALDI-TOF MS are good specificity and short experimental time as compared with conventional antibiotic susceptibility testing (AST) [60, 61]. MOLDI-TOF MS can also quickly differentiate between MRSA and MSSA [62, 63]. The most essential characteristic peaks for distinguishing MRSA and methicillin-sensitive *S. aureus* (MSSA) are at the mass spectrum peaks of 3279, 6485, 6555, and 3299 m/z [64].

#### **4.4 Genome sequencing**

In 1977, Sanger et al. [65] invented the dideoxyribonucleotide end termination method, and Maxam and Gilbert [66] developed the chemical degradation method, which marked the birth of the next generation of sequencing technology. Sanger sequencing is the standard technology and its length can be up to 1000 bp and the accuracy is almost 100%, but it has the disadvantages of low throughput, high cost, and long time. Next-generation sequencing (NGS) came into being. Next-generation sequencing platforms mainly include the Roche 454 sequencing platform based on microemulsion PCR and pyrosequencing technology, the Illumina sequencing platform based on bridge PCR and fluorescent reversible terminator sequencing-bysynthesis, the SOLID sequencing platform based on microemulsion PCR and oligonucleotide ligation sequencing, and the Ion Torrent PGM and Proton semiconductor sequencing platforms [67].

In 2014, Wilson et al. [68] reported the world's first case of an infectious disease diagnosed by next-generation sequencing technology. Since then, NGS technology has been gradually recognized and promoted, providing ideas for the diagnosis of unknown pathogens in clinical practice [69] NGS is the most widely used method for high-throughput, massively parallel sequencing of thousands to billions of DNA fragments simultaneously [70]. The third-generation sequencing technology is divided into single-molecule real-time (SMRT) sequencing and nanopore single-molecule sequencing according to different sequencing principles. Gene sequencing can obtain the genomic information of pure colonies and the genomic information of mixed specimens so that highly related lineages can be distinguished with the resolution and precision that other methods lack. Gene sequencing can obtain nearly complete bacterial DNA information, including species, drugresistance genes, virulence factors, mobile elements, etc. The molecular epidemiology and transmission mechanisms of strains are critical to understanding the occurrence and development of various diseases [71]. The widespread availability of genetic sequencing technology has enabled more detailed studies of MRSA transmission patterns, including analysis of past undocumented transmission and

#### *Recent Progress in the Diagnosis of* Staphylococcus *in Clinical Settings DOI: http://dx.doi.org/10.5772/intechopen.108524*

comprehensive, complicated strain evolution [72–74]. In addition, gene sequencing plays a significant role in the study of MRSA colonization and infection [75].

Moore et al. [76] demonstrated that Whole Genome Sequencing (WGS) has a high resolution for strains that other methods cannot distinguish in MRSA colonization and infection studies. WGS is a comprehensive method that analyzes the entire genomic DNA of a cell at once by using sequencing technology. At present, NGS technology still lacks unified laboratory testing operation specifications, and exogenous nucleic acid contamination will likely lead to false positive results, which will seriously affect clinical diagnosis. NGS can detect two or more non-pathogenic bacteria in the same specimen. The analysis may be because NGS has high sensitivity and the nucleic acid residues of non-specimen pathogens with low sequence numbers or dead pathogens are detected together, which is very likely to lead to misjudgment by clinicians, though NGS results lack recognized interpretation. However, the relationship between sequencing results and treatment is unclear, and drug-resistance genes are difficult to detect, so it still needs to be supplemented with drug susceptibility testing. In summary, NGS technology plays an essential role in identifying pathogens and guiding clinical treatment. With the continuous improvement of NGS detection platforms and the proposal of relevant interpretation, NGS technology will be widely used on standards to guide clinical diagnosis and treatment.

### **5. Raman spectroscopy in** *Staphylococcus* **identifications**

#### **5.1 Principles of Raman scattering effects**

Raman scattering is an inelastic scattering phenomenon caused by light striking the surface of a material, revealed by Indian scientist Chandrasekhara Venkata Raman in 1928 [77]. When the molecules of the detected object interact with the incident light photons of the monochromatic beam, elastic and inelastic collisions can occur simultaneously. The scattering mode in which the optical frequency does not change is called Rayleigh scattering. The photon transfers energy to the molecule during an inelastic collision; after it changes direction, some of this energy is transferred to the molecule (Stokes scattering), or the vibration and rotational energy of the molecule is transferred to the photon (Anti-Stokes scattering), changing the frequency of the photon (Raman scattering) [78]. Because Raman scattering can reflect the molecular vibration and vibration-rotation energy level of substances, it is used in molecular structure analysis. However, due to the extremely low scattering efficiency of inelastic scattering, the scattered light intensity is one millionth to one billionth of the incident light intensity, which greatly limits the application of Raman spectroscopy in material analysis and detection, and surface-enhanced Raman spectroscopy was then discovered and developed.

#### **5.2 Surface-enhanced Raman spectroscopy**

In 1974, Fleischmann et al. [79] found that the pyridine molecules adsorbed on the rough silver electrode surface had a significant Raman scattering effect. In 1977, after extensive experimental research and theoretical calculation, Jeanmarie et al. [80] named this enhancement effect related to rough metal surfaces such as silver (Ag), gold (Au), and copper (Cu) as the surface-enhanced Raman scattering effect, and the corresponding technology was called surface-enhanced Raman spectroscopy (SERS).

The Raman scattering signal of pyridine molecules adsorbed on the rough metal silver surface is enhanced by about 6 orders of magnitude compared to the Raman scattering signal of pyridine molecules in solution, which provides the possibility for the detection of biological macromolecules. The principle of SERS is explained mainly through two mechanisms: chemical enhancement and electromagnetic enhancement. The chemical mechanism (CM) describes the electronic interaction between substrates and adsorbed molecules and offers a small enhancement magnitude 102 –103 . The electromagnetic enhancement (EM) mechanism contributes by increasing the electromagnetic field near plasmonic structures caused by incident light excitation of a localized surface plasmon resonance (LSPR). Plasmonic nanomaterials are those in which incident electromagnetic radiation from light can coherently excite conduction electrons to oscillate collectively at metal/dielectric interfaces. The large SERS enhancement factor (EF) generated from EM contribution to plasmonic nanomaterials is in the magnitude of 1010–1014 [81] which is significant for the detection of single molecules [82]. Among them, electromagnetic enhancement receives more attention and acknowledges extensive research work. Label-free SERS detection technology has developed into a research hotspot in the field of microbiology due to its advantages of no need for too much preliminary preparation, non-invasive and short detection time, and excellent application prospects in bacterial detection.

#### **5.3 SERS spectra of staphylococcal bacteria**

The complex biological meaning and structural information contained in Raman spectra result from the vibrational and rotational frequencies of molecules in the sample. The vibration frequencies of biomolecules such as nucleic acids, proteins, lipids, and carbohydrates in bacteria are different, and they appear as unique peaks in Raman spectra. "Full biometric fingerprints" can be used as a basis for distinguishing different bacteria. Efrima et al. [83] used SERS for bacterial detection, distinguishing Gram-positive and Gram-negative bacteria through the difference in SERS profiles on the cell membrane surface. Since then, the application of SERS in bacterial detection, identification, and classification has received rapid attention. Rebrošová et al. [84] detected 54 *S. epidermidis* and 51 *Candida parapsilosis* strains from Mueller-Hinton agar plates using Raman spectroscopy with an accuracy of 96.1% and 98.9%, respectively. Tang et al. [85] applied two deep learning methods, Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM), for SERS detection of 117 *staphylococcal* strains belonging to 9 species of *Staphylococcus,* with an accuracy of 98.21% and 94.33%, and Area Under Curve (AUC) values of 99.93% and 99.83%, respectively [85]. In addition, *Staphylococcus wornerii*, *S. hominis,* and *Staphylococcus korea* have unique peaks at 1003 cm−1. *Staphylococcus xylinum* and *Staphylococcus squirrels* have special peaks at 1089 and 1093 cm−1 [85]. Rebrošová et al. [86] reported that Raman spectroscopy analysis of 277 staphylococcus strains of 16 species, including *S. aureus* and *S. epidermidis*, revealed that the total accuracy of inputting a spectrum was over 99%, and even reached 100% for a few strains, indicating that SERS is a reliable tool for the identification of *Staphylococci*. The most common *S. aureus* Raman peaks are primarily at 731 cm−1 [87], which is produced by glycosidic linkages and originates from the abundant peptidoglycan in the cell wall. The other two main Raman peaks at 958 and 1050 cm−1 are protein C-O groups. The typical peak of saturated lipids at 1458 cm−1 comes from the lipids on the cell wall, while the characteristic peaks of the C-N group are from proteins, peptides, and amino acids on the cell wall [88].

#### *Recent Progress in the Diagnosis of* Staphylococcus *in Clinical Settings DOI: http://dx.doi.org/10.5772/intechopen.108524*

In addition to achieving bacterial classification, SERS technology offers the potential to discriminate various bacterial species that belong to the same family. You et al. [89] used 30 cases of *S. aureus* ATCC25923 and MRSA as the sample training set and 6 cases of ATCC25923 and MRSA as the test set, based on the Principal Component Analysis (PCA) combined linear discriminant analysis (LDA) model for SERS detection. The classification accuracies of ATCC25923 and MRSA on the training and test sets are 76.67% and 75%, respectively according to the PCA-LDA model [89]. In another work, the Ayala team [90] used the SERS technique to differentiate wild-type *S. aureus* and mutant strains lacking carotenoid production. These results confirm the great potential of SERS in identifying *S. aureus*. The feasibility of Raman microscopy has been demonstrated to be able to discriminate various genetically distinct forms of a single bacterial species in situ. The rapid differentiation of resistant and susceptible bacteria can be achieved by collecting the Raman spectral signals of the two and combining them with chemometric methods. In the work of Potluri et al. [91] the PCR and SERS technologies were combined to detect the MRSA-specific genes *mecA* and *femA*, and had good identification of MRSA and MSSA. In identifying MRSA and MSSA, Ciloglu et al. [92] used SERS combined with machine learning techniques for analysis, and the classification accuracy was achieved at 97.8%. In their other work [93], a Sparse Autoencoder (SAE)-based Deep Neural Network (DNN) algorithm was used to analyze and extract features from raw spectral data and classify MRSA and MSSA bacteria with 97.66% accuracy. SERS can be used to analyze the target of drug action and explore the mechanism of antibiotic-resistant, bacteriostatic and bactericidal actions. After the bacteria are treated with drugs, the bacteria are freeze-dried, and the Raman spectrum information of single cells is collected by Raman microscopy. Microscopic imaging can detect the number of drugs entering cells and drug targets, as well as measure the kinetics of drug uptake in cells and point out interactions [94].

#### **5.4 Raman spectroscopy preprocessing**

Raman spectral signals inevitably receive external interference during the acquisition process, such as the mechanical vibration of the instrument itself, cosmic noise, and autofluorescence to a certain extent, which prevents the rapid and accurate analysis of spectral data [95]. Therefore, before formal data analysis, the original Raman signal needs to be preprocessed to eliminate unfavorable factors in the analysis process. Preprocessing can be regarded as a key step in spectral data analysis and is mainly divided into spike removal, smoothing denoising, baseline correction, and vector normalization. For peak removal, when collecting Raman spectra, random, narrow and strong spectral signals appear in the spectral fingerprint due to the random appearance of electronic signals from cosmic particles on CCD or complementary metal-oxidesemiconductor detectors. The existence of spikes will mask other useful information to a great extent; therefore, spike removal is necessary. In general, spikes rarely appear at the same shift in the Raman spectrum of the same sample [96]. In this regard, we can judge whether there is a spike by visually inspecting and comparing the difference in abnormal intensity between different spectral curves [97]. In addition, setting the signal intensity threshold and deriving the spectral data can also achieve the purpose of removing spikes [98]. For the electronic noise composed of cosmic noise, flicker noise, and thermal noise, it will randomly appear in multiple positions of the spectral curve in an unpredictable form, which has a large impact on the quality of Raman spectroscopy data. Savitzky–Golay (S-G) filtering is one of the most commonly used preprocessing methods in the process of smoothing and denoising Raman spectra [99, 100].

This method can keep the shape and width of the signal unchanged while filtering the noise, so as to meet the processing requirements of Raman spectral data in different situations [101]. As one of the recognized best processing steps in Raman spectrum analysis preprocessing [96], baseline correction is used to deal with the continuous distortion caused by uncontrollable factors during Raman spectrum acquisition, such as removing substrate-related Raman signals [99] and fluorescence signals generated by the sample itself [102]. Commonly used methods are asymmetric weighted penalized least squares (arPLS) algorithm [103], adaptive iterative weighted penalized least squares (airPLS) algorithm and polynomial fitting [104]. Normalization is the last step of preprocessing [105]. It is used to deal with the situation of large signal strength caused by uneven sample distribution, laser power difference, experimental environment interference and other factors [104]. Vector normalization is one of the most commonly used normalization methods in Raman spectral analysis [97, 106], It is used to control the difference in Raman signal intensity levels by mapping the data to a range of 0 to 1 for processing [107]. It is worth noting that the order of preprocessing is not fixed and each step does not necessarily need to be performed. When applying to our own experimental data, we need to observe the interaction between each step of preprocessing, and choose the best combination of preprocessing according to the feedback between different preprocessing methods.

#### **5.5 Machine learning analysis of SERS spectra**

Data learning aims to convert Raman spectral signals into computer-recognizable abstract feature information. For previously preprocessed spectral data, we need to use more advanced methods based on machine learning algorithms. Machine Learning (ML) is a method of observing existing data, extracting the rules, and then applying them to unknown samples [98]. Traditional Raman spectrum classification and recognition usually use machine-learning algorithms to model and analyze, but the analysis process of this method is relatively complicated, and it needs to go through operations such as preprocessing and feature extraction. In recent years, deep learning has become a hot research topic. Deep learning is to learn features from large-scale raw datasets and to build predictive models directly. There are many deep learning algorithms, including convolutional neural networks (CNN), fully connected networks, and residual neural networks (ResNet), etc. It has decent performance in mining local features of data and extracting international training highlights [108], and its ability to classify and identify data far exceeds that of traditional multivariate statistical analysis algorithms. Wang et al. [109] prepared positively charged nano-silver-based SERS samples combined with the CNN algorithm for rapid identification of drug resistance in *S. aureus*. Several classifications have achieved good results for the high-intensity SERS fingerprints collected in 107 cells/ml bacterial solution, among which shallow CNN, ResNet25, SVM and Logistic regression all achieved 100% classification accuracy [109]. When the traditional machine learning algorithms SVM, Logistic regression, RF and KNN were used to analyze low-intensity SERS fingerprints collected from low-concentration bacterial solutions of 105 cells/ml and 102 cells/ml, the average recognition accuracy dropped below 80% [109] whereas the shallow layer created by the study CNN achieves 94.5% recognition accuracy, which is more than 25% higher than other ordinary methods [109]. In addition, the SERS combined CNN detection method also achieved good results in identifying MRSA and MSSA. Ho et al. [110] apply deep learning methods to identify 30 common bacterial pathogens. The average separation level was more

*Recent Progress in the Diagnosis of* Staphylococcus *in Clinical Settings DOI: http://dx.doi.org/10.5772/intechopen.108524*

than 82% accurate at low SNR spectra, and an antibiotic treatment identification accuracy of 97.0 ± 0.3% was achieved [110]. The deep learning method distinguishes between MRSA and MSSA isolates with an accuracy of 89 ± 0.1% [110]. Additionally, Tang et al. studied 9 different *Staphylococci*, and constructed 8 different machine learning algorithms and 2 deep learning algorithms for the classification and prediction of all the staphylococcal strains [94]. By calculating and comparing the evaluation indicators of different models, it is found that the deep learning algorithm CNN has the best performance (ACC = 98.21%), and the AUC is also the largest (99.93%) [94]. The results show that the deep learning algorithm has strong classification and prediction capabilities in the detection of bacterial pathogens through surface enhanced Raman spectroscopy.

#### **6. Conclusion and perspectives**

With the continuous development of science and technology, the detection methods of *Staphylococcus* have become more and more diverse, but they all have their advantages and disadvantages. Although the traditional cultivation method is the gold standard, the cultivation time is long, the steps are cumbersome and the technical requirements of the testing personnel are high. Molecular-level identification methods such as PCR, mass spectrometry, and whole-genome sequencing have high sensitivity and specificity with short turn-around time, and can directly detect clinical samples but these techniques have steep learning curves and are expensive. In order to better make up for the shortcomings of various methods, this paper introduces surface-enhanced Raman technology, which has the advantages of low cost, simple operation, label-free, non-invasiveness, high sensitivity, and high specificity in bacterial identification and drug resistance detection, which has great application potential in the near future.



## **Author details**

Xue-Di Zhang1,2 †, Bin Gu3 †, Muhammad Usman3 †, Jia-Wei Tang3 , Zheng-Kang Li4 , Xin-Qiang Zhang4 , Jia-Wei Yan2 \* and Liang Wang4 \*

1 Laboratory Medicine, Medical Technology School of Xuzhou Medical University, Xuzhou, Jiangsu Province, China

2 Laboratory Medicine, Xuzhou Infectious Diseases Hospital, Xuzhou, Jiangsu Province, China

3 Department of Intelligent Medical Engineering, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, Jiangsu Province, China

4 Laboratory Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong Province, China

\*Address all correspondence to: jiawei.yanh@foxmail.com and healthscienc@foxmail.com

† These authors contributed equally to the study.

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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### **Chapter 6**

## Occurrence of Mastitis in Dairy Herds and the Detection of Virulence Factors in Staphylococci

*František Zigo, Zuzana Farkašová, Ibrahim Farag Mohammed Rehan and Ahmed Sayed-Ahmed*

## **Abstract**

Mastitis is still a major challenge that affects milk quality. The study is aimed to examine the health of the mammary gland and identify the udder pathogens and virulence factors that caused mastitis in 960 dairy cows and 940 ewes, respectively. We found that Staphylococci and streptococci are the most common causes of mastitis in those dairy animals. Coagulase-negative staphylococci (CoNS), along with the main udder pathogens such as *S. aureus, S. uberis, and S. agalactiae*, are a major concern for dairy animals. The majority of the virulence factors (production of hemolysis, gelatinase, biofilm, ability to hydrolyze DNA, and antibiotic resistance) were found in *S. chromogens, S. warneri, and S. xylosus* isolates from clinical and chronic cases of mastitis. S. aureus and CoNS strains tested by disk diffusion showed 77.0 and 44.2% resistance to one or more antimicrobial classes in mastitic milk samples from dairy cows and ewes, respectively. The presence of a methicillin-resistant gene *mecA* poses serious complications for treatment and indicates a health risk to milk consumers due to the resistance to β-lactam-antibiotics in two isolates of *S. aureus* and two species of CoNS isolated from cows' mastitic milk samples.

**Keywords:** dairy cows, ewes, mastitis, coagulase-negative staphylococci, biofilm, antibiotics, methicillin resistance gene

## **1. Introduction**

Milk and milk products are important global dietary products, consumed by more than 6 billion people worldwide. In 2019, the recorded milk consumption was 852 million tons, distinguishing the dairy industry as a very profitable market. The milk obtained is a traditional raw material for the production of a range of dairy products, which are unique in their composition, but EU rules emphasize that such products must come from healthy animals, which significantly limits their production and quality [1].

Despite the increasing level of zoohygienic provision of dairy farming, inflammation of the mammary gland-mastitis is still one of the main health problems.

This disease is associated with pain and adversely affects animal health, welfare, milk quality, and the economics of milk production. Direct and indirect losses, caused by mastitis lead to economic losses. For direct losses, we can include treatment costs, discarded milk, labor time, fatalities, and the associated costs with repeated cases of mastitis. Regarding indirect losses, we can include increased culling, decreased milk production, decreased milk quality, loss of premiums, preterm drying-off, animal welfare aspects, and other associated health problems [2, 3]. According to a study by Hogeveen et al. [4], the losses for the global dairy industry are estimated at 16–26 billion euros per year, based on a global population of 271 million dairy cows, with a cost of €61–97 per animal for farmers. In the United States, economically bovine mastitis costs around \$2 billion every year. It has also been identified as one of the most economically relevant diseases in Ireland by Animal Health Ireland [5]. In the Netherlands, van Soest et al. [6] estimated the total cost of mastitis in 108 dairy farms, and found that the average total cost of mastitis is €240/lactating cow per year. In addition, failure costs contributed €120/lactating cow per year and preventive costs also contributed another €120/lactating cow per year.

Due to their polyethological origin, infections of the mammary gland are most often caused by a complex of interactions among the host, environment, and infectious agents that result in bovine mastitis, one of the most frequent diseases of dairy cows and ewes (**Figure 1**). Mastitis has a significant impact on global dairy production, reducing both the quality and quantity of milk produced. In comparison with most other animal diseases, mastitis differs by the fact that several diverse kinds of bacteria can cause the infection. These pathogens are capable of invading the udder, multiplying there, and producing harmful, inflammation-causing compounds [7].

Up to this date, more than 137 different organisms have been recognized as causative agents of ruminant intramammary infection (IMI). They include bacteria,

**Figure 1.**

*Factors promoting mastitis. Source: Zigo et al. [3].*

#### *Occurrence of Mastitis in Dairy Herds and the Detection of Virulence Factors in Staphylococci DOI: http://dx.doi.org/10.5772/intechopen.108256*

viruses, mycoplasma, yeasts, and algae, but bacteria have been identified as the principal causative agent of mastitis (95% of all IMI). In general, each mastitis case is believed to be caused by one primary pathogen, as in milk samples from the affected udder usually only one bacterial species has been identified. However, it is not rare to detect simultaneous infections by two different pathogen species, and even three pathogens have been found in a small proportion of samples [8, 9].

Major and minor pathogens are two main categories used to classify the microorganisms that cause mastitis. *Staphylococcus aureus, Streptococcus agalactiae*, or *Streptococcus dysgalactiale* are the most prevalent major pathogens or contagious udder pathogens, and when they can survive, these areas serve as their primary reservoirs in addition to the mammary gland (MG), the rumen, and the genital regions. As a result, the infection can spread from infected to uninfected quarters or halves [7]. Other pathogens that can cause intramammary infection in ruminants include *coliforms, enterococci*, *Streptococcus* spp., *Pseudomonas aeruginosa*, *Mannheimia hemolytica, Corynebacteria,* CoNS, and fungi, though their prevalence varies depending on the environment [10–12]. The most significant udder pathogens in this group are *Streptococcus uberis* and *E. coli*, which each have a number of pathogenic strains for both people and animals. Both pathogens can be present in the environment and the surroundings of the animals [7].

According to Slovak studies [7, 9, 13], *Staphylococcus chromogenes*, *Staphylococcus epidermidis*, and *Staphylococcus xylosus* are the most common pathogens from CoNS causing mastitis, followed by *Streptococcus agalactiae*, *Staphylococcus aureus*, *Streptococcus dysgalactiae*, *Escherichia coli,* and Enterococci. Of the 42 monitored dairy farms, CoNS and *S. aureus* accounted for 36% and 12% of all positive mastitic cases, respectively.

Namely, *S. aureus* and CoNS have been among the most common microorganisms causing mastitis in dairy cows and health disorders among consumers of milk and dairy products in recent years. According to the World Health Organization, 420,000 lives are lost due to food poisoning; and *Staphylococcus* spp. is characterized as an important agent that can cause foodborne diseases. Poisoning occurs due to the ingestion of preformed enterotoxins in food. Symptoms include vomiting, diarrhea, and cramps; and an outbreak could lead to a public health problem [12–14].

The MG's inflammatory process manifests as symptoms and modifications in the milk and udder tissue. The IMI can be categorized as either persistent (chronic) mastitis or subclinical mastitis. Subclinical forms, which do not exhibit overt indications of inflammation but instead have elevated somatic cell counts (SCC) in the presence of the causative agents, are typically a serious silent issue and are the most common illnesses to result in significant financial loss for owners. Since they cannot be detected without a lab or field test, the subclinical types of IMI frequently become incurable in later stages [9].

Staphylococci can induce different types of intramammary infections depending on the quantity and pathogenicity of the strains, as well as the degree of the udder tissue's response to damage or infection. The interaction between dairy animals' innate resistance and adaptive immunity, as well as the virulence of Staphylococcal strains, determines the course of the clinical inflammation of MG caused by Staphylococci, which is characterized by local visible inflammatory changes in milk and udder tissue, either with or without systemic clinical signs [15]. In general, if there are enough *S. aureus* penetrates into the teat, one of two clinical forms of IMI may develop. Peracute Staphylococcal mastitis occurs infrequently and primarily affects cows and ewes in early lactation with compromised immune systems. The illness is very severe, and is manifested by a high fever, depression, and inappetence. The animals may become comatose and die within

24 hours after the onset of symptoms. The reluctance of infected animals to move is related to grossly swollen infected quarters, which is extremely painful. Blood-stained secretion with serous fluid from the infected part of the udder is usually observed. In surviving animals, blue gangrenous patches may be observed on the infected udder tissue that progress to black, exuding sores [16]. Although early treatment with effective ATB can save an animal suffering from peracute *S. aureus,* the affected quarter is almost always lost [14].

The more common form of *S. aureus* infection is less severe but chronic. The animals with chronic mastitis may not appear affected, and the infected part of the udder does not cause pain. No abnormalities may be observed in the milk. The main complications associated with the treatment of *S. aureus* infection include the fact that many strains can cause this disease and increasing number of them are becoming resistant to an increasing range of antibiotics available for veterinary use. One of the frequent causes of growing resistance is the normal practice on farms of drying dairy cows universally with antibiotics in addition to treating clinical cases of IMI.

According to the study by Ferroni et al. [17] management practices are associated with increased antibiotic consumption, especially in intensive dairy production. The authors analyzed 101 beef and dairy cattle farms in central Italy and compared the overall average antibiotic consumption during one year. The total course of administered ATBs was 3 times higher in the case of dairy cows than in beef farms. Their increased number was mainly related to the treatment of lactating and drying cows with ATBs (**Figure 2**).

The studies Vasiľ et al. [18] and Holko et al. [19] confirm the increased resistance of mainly udder pathogens (*S. aureus, S. uberis*, *and S. agalactiae)* as well as CoNS to those ATBs, that are part of intramammary applicators used for dry treating.

#### **Figure 2.**

*Comparison of average early ATBs consumption between dairy and beef cattle.*

*Note: P = parenteral application, O = oral application, IUT = intrauterine application, IM-LC = intramammary treatment of lactating cows, IM-DC = intramammary application for drying). The overall average antibiotic consumption was expressed in defined course doses (DCDvet)/year and is presented per livestock specialization and by administration route. The total courses administered were higher in farms with intensive dairy production (1034.1 × 10<sup>−</sup><sup>3</sup> DCDvet/year) than in beef farms (330.7 × 10<sup>−</sup><sup>3</sup> DCDvet/year).*

*Occurrence of Mastitis in Dairy Herds and the Detection of Virulence Factors in Staphylococci DOI: http://dx.doi.org/10.5772/intechopen.108256*

Lately, CoNS have become a concern among dairy producers, as their potential as mastitis-pathogens has been observed; and they have already been found in majority of other pathogens. Their predominant isolation can be explained by the fact that CoNS are pathogens adapted to survive in cows or ewes and may be in the mammary gland of sick or healthy animals; while some species are also more resistant to antibiotics than *S. aureus* [13]. Among all the CoNS found in dairy animals, *S. haemolyticus*, *S. chromogenes, S. epidermidis, S. warneri, S. cohnii, S. simulans, S. hominis, S.capitis, and S. xylosus* are the most prevalent species [20, 21].

Following a decline in the incidence of mastitis brought on by the infectious bacteria, the causative CoNS became more prevalent and more resistant to typical ATBs and disinfectants used in dairy farm conditions (**Table 1**). When compared to *S. aureus*, the CoNS often exhibits less virulence and pathogenicity. Their primary pathogenicity factors are biofilm formation and ATB resistance, which enable them to survive the use of medicines and disinfectants during therapy. In a study by Nascimento et al. [20], the most popular antimicrobials used in veterinary practice were tested in vitro against CoNS isolated from mastitic cows. High resistance to the ATBs used to treat cows during lactation was found in tested strains of *S. epidermidis*, *S. saprophyticus*, *S. hominis*, and *S. aerletae*. Also, they could also make some of the Staphylococcal enterotoxins.

Particularly, Staphylococci bacteria that are multiresistant to multiple ATBs pose a severe threat to the public's health [16]. Recent research also suggests that the presence of methicillin-resistant Staphylococci (MRS), which have been found in raw milk and dairyproducts, such as cheese, is indicated by multiresistant Staphylococci, particularly to *β*-lactam ATBs. The public's health is threatened, according to WHO, by


*Percentage of resistant strains for each drug or group.*

#### **Table 1.**

*Resistance of CoNS to two or more antimicrobials.*

the MRS strains' opportunistic capacity to induce mastitis. They might spread zoonotic diseases while acting as a gene repository for dairy cows' antimicrobial resistance. Of the MRS of concern, *Staphylococcus aureus* (MRSA) is the species most widely reported, however, in a number of studies CoNS were also identified as MRS isolates [23, 25, 26].

In addition to the increased antibiotic resistance of Staphylococci, the authors, Vasil et al. [18] and Haveri et al. [27] confirmed biofilm formation and lysines in mastitic milk samples and considered them as important virulence factors involved in the development of CM. Previous research has linked Staphylococci and their virulence factors to the pathogenesis and clinical manifestations of mastitis. They stressed the importance of thorough knowledge of their virulence factors, structures, and products. It is crucial to understand how these microorganisms facilitate adhesion and colonization of the mammary gland epithelium, which allows them to survive, successfully establish themselves, and persist in the host tissue. Therefore, the study was aimed at the occurrence and determination of contagious and environmental udder pathogens in dairy cows' and ewes' herds. Particularly in isolated Staphylococci, the presence of selected virulence factors such as hemolysis, gelatinase, biofilm, hydrolyzed DNA, and resistance to antibiotics with the detection of methicillin resistance gene-*mecA* and their effect on the severity of mastitis were determined.

### **2. Materials and methods**

#### **2.1 Monitored dairy farms**

The practical part of the study was carried out in four different cows' and four sheep herds located in east Slovakia with conventional (nonorganic) farming. The selection of dairy farms for the study was based on criteria such as herd size, breed representation, and milk yield per lactation. Up to 70% of farms located in the east of Slovakia are in the range of 150–300 cattle and 200–400 ewes. Due to the study carried out in Slovakia, dairy farms were selected where there are national breeds of cattle and sheep. The practical part of the study on selected dairy farms with the clinical examination and collection of milk samples were approved by the Ethics Committee at the University of Veterinary Medicine and Pharmacy in Košice no. EKVP 2022/05.

From dairy cows, each herd size ranged from 150 to 300 Slovak spotted cattle bred between 1st and 4th lactation. The dairy cows under investigation on each of the four farms were housed in a system of free housing on straw litter with *ad libitum* access to water. According to international guidelines, a total mixed feed made up of silage, hay, and concentrate was given to them [28]. The rations met the nutritional requirements of cows weighing 650 kg, with an average milk yield of 20–30 kg per day. In the first phase of lactation, the mean average dry matter intake per cow per day was 23.6 kg +/- 3.7 kg. All cows were milked twice daily in parallel (Boumatic, USA) or fishing (DeLaval, Sveden) parlor. From all monitored dairy farms, 270 cows from the first, 215 cows from the second, 250 cows from the third and 225 cows from the fourth herd were investigated.

The four sheep farms were in herd sizes ranging from 200 to 400 animals and consisted of Improved Valachian, Tsigai, and Lacaune breeds. In April, the ewes were on pasture during the day and received concentrates in amounts of 200 g per day during milking. After their lambs were weaned in early April, the ewes were milked twice a day on each farm. In the first two herds, machine milking was performed using a twoline milk parlor 2×14 Miele Melktechnik, (Hochreiter Landtechnik, Germany) and in two other herds, the sheep were milked in two-line milk parlor 2× 16 Alfa Laval Agri

(Alfa Laval, Sweden). From all the monitored sheep farms, during the first month of pasture (April), 220 ewes from the first, 250 ewes from the second, 270 ewes from the third, and 200 ewes from the fourth herd were investigated.

#### **2.2 Dairy animals selection and udder health examination**

The dairy cows from four monitored farms were selected on the basis of the formation of production groups according to the stage of lactation (early lactation 14–100 days of lactation) and the phase of nutrition, which were compiled by the zootechnicians. The selected dairy cows of the same performance class (early lactation) were housed in individual husbandry groups, which included 45–90 animals on each farm.

Ewes from four herds were included in the study two months after lambing between the 1st and 3rd lactation with a stay on pasture and milked twice a day. Complex examination of health status of udder in ewes from four monitored farms was carried out at the start of the milking season (April). On the basis of a clinical assessment, each dairy cow and sheep had a thorough inspection that included sensory evaluation and udder palpation. The California mastitis test (CMT) (Indirect Diagnostic Test, Krause, Denmark) was used to evaluate the milk from the forestripping of each udder quarter or halve – Raw milk samples from cows and ewes with positive test results were collected [19]. CMT scores were 0, +, ++ and +++ for "negative", "weak positive", "positive" or "strong positive", respectively [29].

Following that, of the 960 cows that were investigated, 689 had a negative CMT score, and 271 cows had a CMT score that indicated trace or positive symptoms based on clinical manifestations (score of 1–3), were chosen for aseptic collection of 12 mL mixed quarter milk samples by discarding first squirts with the cleaning of the teat end with 70% alcohol for laboratory analyses of bacterial pathogens, according to Holko et al. [19]. From 940 examined ewes, 756 animals had negative CMT scores and 184 animals with CMT score trace or 1–3 were taken with 12 mL mixed halves milk samples for laboratory analyses. All milk samples from cows and ewes were cooled to 4°C and immediately transported to the laboratory and were analyzed on the following day.

According to the National Mastitis Council [30], each instance of mastitis in positive animals was given a grade that was divided into subclinical, clinical, and chronic forms. A high SCC was found utilizing a CMT evaluation and a positive bacteriological result to identify subclinical mastitis (SM), which was distinguished from clinical mastitis by the absence of obvious symptoms in the udder or alterations in the milk. Clinical mastitis (CM), which can be seen in the milk or in the udder, is divided into three stages: mild mastitis, which is identified by visible changes in secretion; moderate mastitis, which also exhibits localized MG inflammation; and severe mastitis, which also exhibits general symptoms like loss of appetite, difficulty standing, fever, or low body temperature. Based on repeated therapy, a history of clinical evaluation of the MG with a positive CMT score, and the development of udder pathogens, chronic mastitis, or persistent mastitis was identified.

#### **2.3 Bacteriological culture and evaluation of growth on plates**

In the laboratory, 0.2 mL of milk was inoculated from each sample onto a blood agar plate (Oxoid LTD, Hamshire, UK) and incubated aerobically at 37°C for 24 hours. The primocultivated colony from blood agar and identification of *Staphylococcus* spp. were sub-cultured onto different selective bacteriological media (No. 110, Baird-Parker agar, Brilliance UTI Clarity Agar, Oxoid, Hampshire, UK) and incubated

at 37°C for next 24 hours. Cell morphology, Gram staining, the type of hemolysis, and the activities of catalase (3% H2O2, Merck, Darmstadt, Germany) were used to identify colonies, esculin hydrolysis and cytochrome oxidase C (Bactident Oxidase, Merck). The clumping factor test discovered potential *Staphylococcus aureus* (DiaMondiaL Staph Plus Kit, Germany). According to research by Vasiľ et al. [18] and Holko et al. [19], esculin-positive streptococci were grown on modified Rambach agar to identify *Streptococcus uberis* or *Enterococcus* sp.. Lancefield serotyping (DiaMondiaL Strept Kit, Germany) was used to describe esculin-negative streptococci, and the MALDI-TOF MS (Bruker Daltonics, Bremen, Germany) was utilized to identify all gram-negative species. The presence of one or more colony-forming units (CFU) of the major udder pathogens, such as *Staphylococcus aureus, Streptococcus dysgalactiae, or Streptococcus agalactiae*, was considered positive. The sample would be deemed positive if the growth of a significant udder pathogen was discovered in conjunction with other environmental species. Other pathogens were categorized as requiring at least three CFUs to be present. If infectious pathogens did not develop and three or more pathogens were isolated from a single milk sample, the grown samples were deemed contaminated.

#### **2.4 Detection of virulence factors in Staphylococci**

Confirmed Staphylococci based on MALDI-TOF analysis were exposed to deoxyribonuclease (DNase test) and to produce extracellular proteolytic enzymes (Gelatin hydrolysis test) according to Hiko [31]. The formation of biofilm was determined by a phenotypic method by growth on Congo Red agar (CRA) according to Vasiľ et al. [13].

Additionally, it was established that Staphylococci can generate hemolysins, based on Moraveji et al. [32]. After 24 and 48 hours of incubation at 37°C, the lysis zone of each Staphylococcal isolate on plates of blood agar base supplemented with 5% sheep blood was used to phenotypically define the different types of hemolysis.

The susceptibility of Staphylococci isolated from cows' (n = 136) and sheep's (n = 86) infected milk was tested *in vitro* against 14 antimicrobial agents. The susceptibility tests of isolates were carried out on Mueller Hinton agar using a standard disk diffusion procedure [33]. In the current study, antibiotic discs containing penicillin (PEN; 10 μg), ampicillin (AMP; 10 μg), amoxicillin (AMC; 10 μg), amoxicillin+clavulanic acid (AXC; 20/10 μg), ceftiofur (CEF; μg), oxacillin (OXA; 1 μg), cefoxitin (CFX; 30 μg), ciprofloxacin (CPR; 5μg). The diameters determined were classified as susceptible, moderate, or resistant based on CLSI breakpoints, and the zone of inhibition was measured in millimeters [34]. Reference strains of *S. aureus* CCM 4750 and *S. chromogenes* CCM 3386 from the Czech Collection of Microorganisms in Brno, Czech Republic, served as the controls in the assays. The study's chosen antimicrobials represent the range of medications used in veterinary care on Slovak dairy cows.

#### **2.5 Detection of the mecA gene from Isolated Staphylococci**

Phenotypical positive Staphylococci (45 and 26 isolates from cows' and sheeps' mastitic milk samples) based on their antimicrobial resistance to *β*-lactams antimicrobials were subjected to PCR to test for methicillin resistance. Total genomic DNA was isolated according to Hein et al. [35]. Using a BioSpec spectrophotometer, the purity of the DNA recovered from the tested Staphylococci was evaluated (Shimadzu, Japan). According to Poulsen et al. [36], acquired DNA was used in PCR reactions

*Occurrence of Mastitis in Dairy Herds and the Detection of Virulence Factors in Staphylococci DOI: http://dx.doi.org/10.5772/intechopen.108256*

to detect the *mecA* gene using primers MecA1 and MecA2 (Amplia s.r.o., Bratislava, Slovakia). Sanger sequencing was used to confirm the identity of the PCR products (527 bp), in accordance with the guidelines provided by GATC Biotech (AG, Cologne, Germany). The BLAST tool was used to compare the DNA sequences acquired from the isolates to those found in the GenBank-EMBL (the European Molecular Biology Laboratory) database (NCBI software package). As a reference strain for PCR, *S. aureus* CCM 4750 (Czech Collection of Microorganisms, Brno, Czech Republic) was used in this investigation.

#### **2.6 Statistical analysis**

Microsoft Excel 2007® (Microsoft Corp., Redmond, USA) was used to process the study's data, and SPSS version 20 and Excel were used to analyze it (IBM Corp., Armonk, USA). According to specific microbial species and mastitis types, the findings of grown udder pathogens from mastitic cows and ewes were processed and converted to percentages. The percentage of resistant isolates from milk samples that tested positive for *S. aureus* and CoNS for each type of antibiotic was also used to express the antimicrobial resistance results. According to the production of virulence factors, Staphylococcal isolates from clinical, subclinical, or chronic mastitis were compared using the chi-squared test. The significance level was set at 0.05, the critical value χ2 was 2.206 for cows and 1.824 for ewes, and the testing value was G. Within each species, statistical independence between isolates with and without virulence factors was verified when G > χ2, although the independence was not statistically significant when assessing G > χ2.

#### **3. Results**

A thorough analysis of 960 dairy cows from four farms during the early lactation phase (14–100 days of lactation) revealed that 271 animals (28.2%) and 689 cows (71.8%), respectively, had CMT scores of trace or 1–3 for one or more quarters. 756 (80.4%) of the 940 ewes evaluated for udder health during the first month of the grazing season showed negative CMT results. One-hundred eighty-four ewes (19.6%) had positive CMT with a score trace of 1–3. Of the mixed milk samples taken from each examined cow and sheep based on the anamnesis and positive CMT score, bacterial agents causing a mastitis were identified in 230 (84.8%) and 155 (84.2%), respectively (**Figure 3**). For the presence of udder pathogens, 41 (15.1%) and 29 (15.7%) samples from examined cows and ewes with a positive CMT score were identified as negative or contaminated.

Based on the clinical examination of the MG, assessment of CMT, and laboratory diagnosis of milk samples, the occurrence of CM in the monitored cows' and sheep's dairy farms was 9.1% and 4.5%, respectively. The most common form of IMI in monitored cows and ewes was subclinical mastitis, with an incidence of 11.3% and 10.2%, respectively. The occurrence of chronic mastitis was 3.6% and 1.8% in monitored dairy cows and ewes, respectively. Of the cows' and ewes' positive samples, 136 and 86 cases (59.1% and 55.4% of the infected samples) contained the most commonly isolated Staphylococci, respectively (**Table 2**).

The CoNS represented the most commonly detected bacteria (42.6% and 39.9% of positive findings in cows and ewes), causing mainly subclinical mastitis. The *S. aureus* was the second most common pathogen (16.5% and 18.2% of positive findings in cows

**Figure 3.**

and ewes, respectively), primarily causing clinical or chronic mastitis, followed by *E. coli*, streptococci, and enterococci (**Table 2**).

**Tables 3** and **4** summarize, in descending frequency, the isolated strains of *Staphylococcus* spp., and indicate their role in the type of mastitis and the occurrence of selected virulence factors. Isolated *S. aureus* from clinical, chronic, or subclinical cases of mastitis has the highest ability to report virulence factors compared to CoNS and showed hemolysis in blood plates, production of gelatinase, biofilm, and the ability to hydrolyze DNA. The mecA gene was detected in two isolates of *S. aureus* from cows' clinical mastitis. Eight species of CoNS were isolated from mastitic cows, with the following recorded: *S. chromogenes* (22.4%), *S. warneri* (20.4%), *S. xylosus* (18.4%), *S. epidermidis* (9.1%), *S. haemolyticus* (7.1%), *S. hyicus* (10.2%), *S. capitis* (4.4%), and *S. piscifermentans* (4.4%) with testing value χ<sup>2</sup> = 2.206 for statistical significance. From mastitic ewes were isolated six species of CoNS with the following recorded: *S. warneri* (23.7%), *S. chromogenes* (18.6%), *S. xylosus* (18.6%), *S. haemolyticus* (15.2%), *S. caprae* (13.6%) and *S. epidermidis* (10.2%) with testing value χ<sup>2</sup> = 1.808 for statistical significance. From all the cows' and ewes' mastitic samples caused


*Clinical IMI1 - clinical mastitis represented in mild, moderate, or severe forms of intramammary infection; n – number of mastitic animals. Modified from Zigo et al [9].*

#### **Table 2.**

*Pathogens isolated from milk samples of four monitored dairy cows and four sheep herds.*


*Occurrence of Mastitis in Dairy Herds and the Detection of Virulence Factors in Staphylococci DOI: http://dx.doi.org/10.5772/intechopen.108256*

*Legend: IMI1 : the number of isolates and their impact on the type of mastitis; hemolysins2 : the production of hemolysin type α, β or δ; DNAse3 : the capability of Staphylococci to hydrolyze DNA; \*Chi-squared test significance level α= 0.05; critical value χ 2 = 2.206. In isolated Staphylococci, Testing value (G) and statistical independence of virulence factors were validated when G > χ 2 ; the independence was not statistically significant when G < χ 2 . Modified from Zigo et al. [9].*

#### **Table 3.**

*The role of S. aureus and CoNS in the form of mastitis from infected cows and their virulence factors.*

by CoNS, 48 and 26 (48.9% and 44.1%) cases involved the production of hemolysins, 12 and 11 (12.2% and 18.6%) the hydrolysis of DNA, 8 and 12 (8.1% and 20.3%) the production of gelatinase, as well as 27 and 14 (27.5% and 23.7%) involved biofilm production.

In **Table 3**, the significance level of α = 0.05 was confirmed in the isolated Staphylococci *S. aureus, S. chromogenes, S. warner*, and *S. xylosus* from CM and chronic cows' mastitis, which, when compared to less virulent strains, has the highest representation of virulence factors (production of hemolysins, gelatinase, the ability to hydrolyze DNA, and biofilm). In addition, the *mecA* gene was confirmed in one chronic case of mastitis in *S. chromogenes* and one CM case in *S. warneri.* In isolated


*Legend: IMI1 - number of isolates and their influence on type of mastitis; hemolysins2 - production of hemolysin type α, β or δ; DNAse3 - ability of Staphylococci to hydrolyze DNA; \*Chi-squared test significance level α = 0.05; critical value χ 2 = 1.808; Testing value (G) and statistical independence of virulence factors in isolated Staphylococci was confirmed when G > χ 2 ; the independence was not statistically significant when the testing value was G < χ 2 .*

#### **Table 4.**

*The role of S. aureus and NAS in the form of mastitis from infected ewes and their virulence factors.*

Staphylococci from mastitic ewes as demostrated in **Table 4**, the significance level in *S. aureus, S. warneri*, *S. chromogenes,* and *S. xylosus* was confirmed*.* The presence of the *mecA* gene has not been confirmed in tested *S. aureus* and CoNS.

In 136 and 86 isolates of Staphylococci from mastitic cows' and ewes' milk samples, *in vitro* resistance to 14 antimicrobials was tested by the standard disk diffusion method (**Table 5**). Generally, low resistance was shown to tetracycline, amoxicillin reinforced with clavulanic acid, rifaximin, and cephalexin. Of the tested Staphylococci, 95 and 38 isolates (70.0% and 44.2%) from mastitic cows and ewes showed resistance to one or more antimicrobials. To one antimicrobial, 50 and 22 isolates (36.7% and 25.6%) from mastitic cows and ewes were resistant. Mastitic cows and ewes produced 55 and 16 (39.7% and 18.6%) resistant Staphylococci isolates, respectively. Multidrug resistance to three or more antimicrobial classes was recorded in 16 and 4 isolates (11.7% and 4.7%) from cows' and ewes' samples. Tested Staphylococci showed multiresistance to a combination of antimicrobial classes, such as aminoglycosides, *β*-lactams, macrolides, and cephalosporins.


*Occurrence of Mastitis in Dairy Herds and the Detection of Virulence Factors in Staphylococci DOI: http://dx.doi.org/10.5772/intechopen.108256*

*Legend: \*MDR: multidrug resistant isolates to three or more antimicrobial classes; AMX: amoxicillin, AMC: amoxicillin+clavulanat acid; AMP: ampicillin; CEP: cephalexin; CPR: ciprofloxacin; FOX: cefoxitin; LNC: lincomycin; NMC: neomycin; NVB:novobiocin; OXA: oxacillin; PEN:penicillin; RFX - rifaximin; STR:streptomycin; TET:tetracycline. Modified from Zigo et al. [9].*

#### **Table 5.**

*Phenotypic resistance profile in isolates of Staphylococcus spp. from mastitic cows and ewes.*

The 45 and 22 isolates (33.1% and 25.6% of all isolated Staphylococci) from mastitic cows and ewes in which phenotypic resistance was confirmed to *β*-lactam antimicrobials were tested by PCR for methicillin resistance with the detection of the *mecA* gene. From positive cows' milk samples, four isolates of Staphylococci - two of *S. aureus*, one of each of *S. chromogenes* and *S. warneri*, and one of each - were shown to contain the *mecA* gene and to be resistant to both cefoxitin and oxacillin. The outcomes of our research indicated that these isolates were methicillin-resistant Staphylococci (MRS).

#### **4. Discussion**

Milk and milk products are important global dietary products, consumed by more than 6 billion people worldwide. The recorded milk consumption in 2019 was 852 million tons, distinguishing the dairy industry as a very profitable market [1]. However, an infection of the mammary gland caused mainly by bacteria, mastitis, is still a major problem affecting animal welfare, productivity, and the economy; especially in dairy production, which can lead to losses for the dairy industry [37]. The incidence of mastitis is, of course, highly dependent on the lactation stage and health status of dairy animals [29, 38].

During the first 100 days of lactation, we observed the prevalence and etiology of mastitis in four dairy farms with cows and ewes. The majority of cows on the farms and the ones who produce the most milk are those that are in this early lactation stage (14–100 days after calving). The dairy cow produces an amount of milk during the first 100 days of lactation that accounts for 42–45% of the total milk. Aside from hormonal changes, decreased feed intake (which is in contrast to increased milk production), increased lipomobilization with a negative energy balance, and changes in body condition score, cows are also subject to stress factors as a result of this heavy milk production burden [38].

All of the aforementioned risk factors have an impact on both the non-specific and specific immune systems, specifically the MG, via which pathogenic microorganisms from the environment can enter the body more easily. An elevated SCC is one sign of the start of intramammary infection [39]. The qualitative test used in practice to detect mastitis is CMT, which reflects changes in milk consistency and SCC. Based on anamnesis, evaluation of CMT and clinical examination 689 (71.7%) of the 960 examined dairy cows were negative while 271 cows (28.2) showed positive, with scores from 1 to 3, or trace CMT. 230 (84.9%) of 271 cows showing high SCC were positive for the isolation of udder pathogens. This constitutes a significant risk for individual and herd health due to the high risk of spreading the infection to the environment. On monitored sheep's farms during the first month of pasture season, 756 sheep (80.4%) a negative CMT and 184 animals (19.6%) had increased SCC on the basis of CMT score (**Figure 1**). Laboratory examination revealed that 136 samples (14.5%) were positive for the presence of an udder pathogen.

The development of infection often starts when pathogens enter the duct system, travel via the teat canal, interact with the mammary tissue, multiply, and spread throughout the functioning parts of the udder, such as the milk cisterns. The degree to which the udder tissue reacts to injury or infection largely determines how mastitis manifests [7]. The most clinical cases are manifested by increased body temperature, inappetence, redness, swelling, and/or painful udder and/or abnormal milk. In the subclinical forms that were most often confirmed in our study, there were no apparent clinical signs, but an increase in SCC was observed in milk. Of the 230 and 136 infected cows and ewes, 46.9% and 62.0% had subclinical, 37.8% and 27.1% had clinical, and 15.2% and 11.0% had chronic mastitis (**Table 2**).

#### *Occurrence of Mastitis in Dairy Herds and the Detection of Virulence Factors in Staphylococci DOI: http://dx.doi.org/10.5772/intechopen.108256*

The major economic and health issues caused by CM, according to Singha et al. [11], include decreased milk output, poorer milk quality, higher expenses for treatment, involuntary culling, early cow rejection, increased risk of antibiotic resistance, and decreased animal welfare. Therefore, in high-yield dairy cows, CM prevalence should be at its lowest level. Our results indicate that the prevalence of CM in monitored cows' dairy farms was 9.1% which is in contrast with the studies of Silva et al. [40] and Rahman et al. [10], who reported the prevalence of CM from 2.3% to 4.1% in lactating cows.

The incidence of mastitis in sheep farms is extremely variable. Fthenakis [41] found the occurrence of mastitis in sheep is between 4 and 50%. In our study, the incidence of mastitis at the beginning of the pasture season was 16.4% in monitored sheep herds, with the most frequently occurring subclinical form (11.5%). The occurrence of CM was 4.9%, which is considered an acceptable value. On the contrary, studies from British slaughterhouses reported a very high prevalence of CM, ranging from 13–50%. This suggests that CM, or chronic mastitis, is a major cause of the culling of ewes in the UK [42].

According to Wenz et al. [43] and our investigation, gram-positive bacteria (*Staphylococcus* spp. or *Streptococcus* spp.) are frequently the cause of CM in dairy ruminants. However, depending on the farm layout and cleanliness level, a significant number of cows and ewes with coliform mastitis develop bacteremia, and 20% of udder infections are brought on by gram-negative pathogens. This is in line with our findings, which showed that SM and CM brought on by *E. coli* accounted for 11.2% and 12.2%, respectively, of infections from all infected cows and ewes.

Pyörälä and Taponen [12] point to a much-increased risk of CM caused by *S. aureus* and CoNS in a Finnish investigation on the detection and etiology of mastitis, which was also confirmed in all monitored dairy herds. CoNS (42.6% and 39.9% of the 230 and 155 infected cows and sheep samples, respectively) and *S. aureus* (16.5% and 18.2%), which were found in 136 and 86 cases, respectively (59.1% and 55.5%), were the most frequently found. In the milk samples from mastitic cows and ewes, the isolates of *S. aureus* and CoNS of the CM were responsible for 7.8% and 7.4%, and 16.0% and 6.1%, respectively. However, due to ongoing IMI, *S. aureus*, *S. chromogenes*, *S. warneri*, and *S. xylosus* frequently caused chronic mastitis. According to the findings of our investigation, studies by Holko et al. [19] and Idriss et al. [25] found a similar incidence of clinical and chronic mastitis caused by *S. aureus* and certain CoNS in the investigated dairy farms. More than half of all clinical and chronic IMI were caused by Staphylococci occurring more frequently than other udder pathogens (**Table 2**).

Chronic IMI rather than new infections are assumed as suggested by Persson et al. [44]. It has been reported that cows and ewes showing IMI in early lactation stage were also positive during the previous lactation or when dried off. These can originate a persistent subclinical infection into a chronic mastitis in animals that turn immunocompromised after calving or lambing.

Our findings are consistent with Holko et al. investigation's [19], which found a significant incidence of Staphylococci (CoNS and *S. aureus*) identified from tainted milk samples from 42 dairy farms in western Slovakia. The most often found bacteria was the CoNS, which made up 35.9% of positive samples. In contrast to our findings, the authors also confirmed high resistance to aminoglycosides and *β*-lactam antimicrobials without the presence of methicillin resistance genes. The dominant CoNS strains identified from mastitis in dairy ruminants in recent years, according to many reports, are *S. haemolyticus*, *S. chromogenes*, *S. warneri*, and *S. xylosus* [45–47]. CoNS has been mainly isolated from CM in addition to subclinical forms of IMI [45],

which was validated in our investigation. CoNS-induced CM mastitis was associated with increased SCC, biofilm formation ability, and resistance to aminoglycosides and *β*-lactam antimicrobials, particularly penicillin, amoxicillin, and oxacillin.

The increasing prevalence of Staphylococcal infection in dairy ruminants is also influenced by the bacteria's level of pathogenicity and the production of certain virulence factors, which play a critical role in chronic and clinical mastitis cases [48, 49]. These contribute to the infection and include enterotoxins, different enzymes, and cell-associated factors. S*. aureus, S. chromogenes, S. warneri, S. xylosus*, and *S. haemolyticus* all produced hemolysins, hydrolyzed DNAse, and produced gelatinase from the various virulence factors. The isolated Staphylococci *S. aureus, S. chromogenes,* and *S. warneri* from mastitic cows and ewes had the most numerous representations of virulence factors, that may be contributing to the infection ability of isolated strains resulting in the increasing incidence of CM and persistent cases in comparison to strains with no virulence factors (**Tables 3** and **4**).

As biofilms promote Staphylococcal strains to adhere to both biotic and abiotic surfaces, they are regarded as having significant pathogenicity [48]. Bacteria generally produce a biofilm in order to protect themselves from fluctuations in environmental conditions. Substantial hygiene problems and economic losses are associated with biofilm formation in the dairy industry, as it can cause food spoilage and equipment impairment. The quality, quantity, and safety of food products are affected by the persistence of some foodborne pathogens on food contact surfaces and biofilms; and this problem has been reported more frequently [50]. Staphylococci are able to avoid immune defenses by creating biofilms that adhere to the MG epithelium, which leads to recurring or persistent infections [51]. Our findings indicated that seven species of NAS isolated from CM and chronic mastitis, as well as *S. aureus*, were mostly responsible for the biofilm-forming ability. The CoNS that produced chronic mastitis and CM showed the generation of hemolysins, the tendency to hydrolyze DNA, and resistance to antimicrobials as additional significant virulence factors in addition to *S. aureus*.

The relationship between hemolysins and biofilm formation, according to Perez et al. [49], can lessen the body's immunological response and response to antibiotic treatment while increasing Staphylococci interactions with bovine mammary epithelial cells. Our findings supported the idea that bacteria expressing these virulence characteristics had a high level of antibiotic resistance. In their study of Staphylococci isolated from mastitis milk in cows, Melchior et al. [51] indicated that the most frequent virulence factors in isolates recovered from CM were biofilm production and antibiotic resistance. Repeat episodes of mastitis following ineffective treatment showed increased biofilm production in CM strains. It is challenging to treat IMI brought on by *S. aureus* or CoNS even with intramammary antibiotics, therefore adequate care should be given to infections brought on by bacteria that produce biofilms.

The resistance to one or more antimicrobials in our study was detected in 95 and 38 isolates (77.0% and 44.2%) of Staphylococci isolated from infected cows and ewes, respectively. Multiresistant isolates for three or more groups of antimicrobial classes represented 16 and 4 isolates (11.8% and 4.7%). Multirresistance of staphylococci to a wide range of antibiotics such as β-lactams, macrolides, and cephalosporing (**Table 5**) was observed in our analysis. Methicillin resistance staphylococci were confirmed in 45 (33.1%) and 22 (25.6%) isolates from cows and ewes. By PCR the presence of the *mecA* gene was confirmed in two isolates of *S. aureus* and one isolate each of *S. chromogenes* and *S. warneri*, only from mastitic cows. Oxacillin and cefoxitin resistance was present in all *mecA*-positive Staphylococci (n = 4; 2.9%), and these strains were categorized as MRS. When the entire genome was sequenced for a research by Khazandi et al. [22],

*Occurrence of Mastitis in Dairy Herds and the Detection of Virulence Factors in Staphylococci DOI: http://dx.doi.org/10.5772/intechopen.108256*

they discovered the presence of a *mecA* homolog in four oxacillin-resistant *S. sciuri* isolates. The homolog was not found using cefoxitin susceptibility testing or traditional *mecA* PCR. However, in our study, MRS was also phenotypically confirmed, so we do not assume the presence of a false positive *mecA* homolog.

The *S. aureus* and CoNS (n = 634; 36.7%) were the most frequently isolated bacteria from all tested samples in the study by Vyletelová et al. [52], which examined 1729 bulk milk and individual milk samples from ruminants in the Czech Republic. The species were also tested for the presence of the *mecA* gene using the PCR method and for antimicrobial susceptibility using the disc diffusion method. The most prevalent resistant strain was S. aureus (51%), followed by *S. epidermidis* (34.7%), and *S. chromogenes* (12.2%). A tital of 13 isolates of Staphylococci with *β*-lactam antibiotic resistance were found to have the mecA gene, which was primarily found in cow's milk. In a related investigation, Bogdanoviová et al. [53] tracked the prevalence and antibiotic resistance of *S. aureus* at 50 dairy farms in the Czech Republic. The authors found *S. aureus* positive in 58 samples from 261 raw milk and filtered milk samples, with 37 (14.2%) isolated from raw milk and 21 (8.1%) isolated from filtered milk. The majority of isolates from raw milk (17.8%) were found to be resistant to *β*-lactam antibiotics (amoxicillin and oxacillin), followed by isolates that were tetracyclineand macrolide-resistant. Methicillin-resistant *S. aureus* (MRSA) with the *mecA* gene present was found in two isolates from filtered milk and four isolates from raw milk samples using the PCR technique. We can affirm that IMI caused by Staphylococci, primarily *S. aureus*, with enhanced resistance to *β*-lactam antimicrobials is still a significant problem in Czech and Slovak dairy cow farms based on the findings of our study and the previous two investigations [52, 53]. The occurrence of MRS with the presence of the *mecA* gene is also worrying, which is in the range of 3–6% of isolates strains. In the monitored sheep, we did not record the presence of the *mecA* gene, which is probably a consequence of the higher culling of infected ewes with clinical and chronic mastitis and the renewal of herds with young sheep.

Among the resistant Staphylococci*, S. aureus* was identified by the WHO as the primary udder pathogen with the highest pathogenicity and most media attention. However, numerous other Staphylococci species have also been linked to methicillin resistance [54, 55]. In our work, we found the *mecA* gene to be present in two *S. aureus* isolates and one *S. chromogenes* and *S. warneri* strain. The CoNS is believed to be a reservoir for many resistance genes, which lead to greater resistance to antibiotics, according to Vinodkumar et al. [56]. The spread of resistance isolates may be caused, in part, by the presence of antimicrobials and their metabolites in the environment. This unfavorable effect of the heavy use of antimicrobials, along with delayed breakdown in the udder and drying out in cows (without antibiogram prior to application), maybe a contributing factor to rising resistance and MRS in veterinary medicine.

The MRS are usually resistant to *β*-lactam antimicrobials, and infections caused by these pathogens result in failed or frequent therapies, elevated SCC, and substandard milk quality. Studies from Norway revealed that MRSA has only ever been correlated to one case of cow mastitis when it comes to MRSA becoming the cause of the disease [23].

This contrasts with our findings and the current modeling in Belgium, where Bardiau et al. [56] revealed a comparable prevalence of MRSA in 4.4% of milk samples from clinical cases of mastitis and Vanderhaeghen et al. [57] identified MRSA in 9.3% of milk samples from farms relating with *S. aureus* mastitis, in contrast to our findings. Although our findings showed that the tested Staphylococci were more resistant to *β*-lactam antimicrobials than in previous studies, we can conclude that the occurrence of MRS in the monitored farms was roughly the same.

## **5. Conclusion**

In dairy cows and ewes, Staphylococci and Streptococci were shown to be the most common causes of mastitis. Because of their virulence features, their prevalence poses a major risk to subsequent milk consumption. More than half of the mastitic cases from the cows and ewes under investigation were brought on by Staphylococci, particularly CoNS. Additionally, compared to other, less virulent CoNS strains, some strains of CoNS (*S. warneri, S. chromogenes*, and *S. xylosus*) with *S. aureus* isolated from clinical and chronic mastitis showed a high degree of pathogenicity in the synthesis of additional virulence factors. Resistance to aminoglycoside and *β*-lactam antimicrobials was frequently found in the tested Staphylococci, possibly because these are the antimicrobials most commonly used in dairy ruminant drying and mastitis treatment. Detection MRS by the presence of the *mecA* gene was confirmed in two isolates (2.9%) (one *S. aureus* and one isolate each of *S. chromogenes* and *S. warneri*) from mastitic cows. We can state that *S. aureus* still comes on top in the number of chronic or severe mastitis cases, as well as the number of virulence factors, but some CoNS species could have the same aggressive potential based on their production of gelatinase, hemolysis, biofilm, hydrolyzed DNA, and multidrug resistance.

According to the "*Farm to Fork*" strategy, the European Union intends to minimize the use of ATBs in cattle production by 50% by 2030 due to the frequent resistance of udder infections that cause mastitis and the occurrence of MRS in veterinary practice. Future use of antimicrobials during treatment in veterinary medicine and the dairy industry is still feasible, but only if it can be justified primarily in light of the findings of targeted diagnostics, which reveal each dairy animal's individual udder's physiological state through anamnestic data, clinical examination, SCC, and sample culture with an antibiogram. Designing effective prophylaxis and treatment guidelines to minimize the detrimental effects on milk yield and culling hazards in dairy animals requires knowledge of the virulence of both *S. aureus* and CoNS species associated with mastitis; particularly when combined with resistance patterns and the presence of MRS isolates.

### **Acknowledgements**

The study was supported by Slovak grant **KEGA 009UVLF-4/2021**: *Innovation and implementation of new knowledge of scientific research and breeding practice to improve the teaching of foreign students in the subject of animal husbandry* and international **Visegrad Fund no. 22010056**: *Factors determining the occurrence of bovine mastitis in dairy herds situated in marginal regions.* The project is co-financed by the governments of Hungary, Poland, Czechia, and Slovakia through Visegrad Grants from the International Visegrad Fund.

## **Potential conflict of interest**

The authors declare no conflict of interest.

*Occurrence of Mastitis in Dairy Herds and the Detection of Virulence Factors in Staphylococci DOI: http://dx.doi.org/10.5772/intechopen.108256*

## **Author details**

František Zigo1 \*, Zuzana Farkašová1 , Ibrahim Farag Mohammed Rehan2,3 and Ahmed Sayed-Ahmed4

1 Department of Nutrition and Animal Husbandry, University of Veterinary Medicine and Pharmacy, Košice, Slovakia

2 Faculty of Veterinary Medicine, Department of Husbandry and Development of Animal Health, Menoufia University, Menoufia, Egypt

3 Faculty of Pharmacy, Department of Pathobiochemistry, Meijo University, Aichi, Japan

4 Faculty of Veterinary Medicine, Department of Anatomy and Embryology, Menoufia University, Menoufia, Egypt

\*Address all correspondence to: frantisek.zigo@uvlf.sk

© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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