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Article

Investigating the Toxicity of Compounds Yielded by Staphylococci on Vero Cells

by
Margaret Selina Modimola
1,*,
Ezekiel Green
2,
Patrick Njobeh
2,
Jeremiah Senabe
3,
Gerda Fouche
4,
Lyndy McGaw
4,
Sanah Malomile Nkadimeng
4,
Kgama Mathiba
3 and
Julian Mthombeni
1
1
Department of Biomedical Sciences, The University of Johannesburg, Doornfontein Campus, Johannesburg 2028, South Africa
2
Department of Biotechnology and Food Technology, The University of Johannesburg, Doornfontein Campus, Johannesburg 2028, South Africa
3
Council for Scientific and Industrial Research (CSIR), Meiring Naude Rd, Brummeria, Pretoria 0184, South Africa
4
Paraclinical Sciences Department, University of Pretoria, Onderstepoort, Pretoria 0110, South Africa
*
Author to whom correspondence should be addressed.
Toxins 2022, 14(10), 712; https://doi.org/10.3390/toxins14100712
Submission received: 25 August 2022 / Revised: 22 September 2022 / Accepted: 10 October 2022 / Published: 18 October 2022
(This article belongs to the Collection Staphylococcus aureus Toxins)
Browse Figure
Review Reports Versions Notes

Abstract

:
Bacterial secondary metabolites play a major role in the alleviation of diseases; however, the cytotoxicity of other metabolites cannot be ignored as such metabolites could be detrimental to human cells. Three Staphylococci strains Staphylococcus aureus, staphylococcus epidermidis and staphylococcus saprophyticus were used in the experiments. These strains are well known to cause hospital and community-acquired infections. Secondary metabolites from S. aureus isolated from milk of cows with clinical features of mastitis (swollen udders and the production of watery clotted milk), S. saprophyticus (ATCC 35552), and S. epidermidis (ATCC 51625) were exposed to a minimal medium then screened using Gas Chromatography High-Resolution Time-of-flight Mass Spectrometry (GC-HRTOF-MS) and identified with Nuclear Magnetic Resonance (NMR). From S. epidermidis, two compounds were isolated: oleamide and methyl palmitate; three from S. aureus, including fluoranthene, 3-methyl-2-phenyl-1H-pyrrole, and cyclo(L-Leu-L-Propyl); while S. saprophyticus yielded succinic acid, 1,2,6-hexantriol, veratramine, and 4-methyl-pentyl-amine. The secondary metabolites were tested for cytotoxicity using the Vero cell line. Fluoranthene exhibited toxicity with an LC50 of 0.0167 mg/mL to Vero cells, while the other metabolites did not. Methyl palmitate was the least toxic of all of the metabolites. The results imply that none of the compounds, except fluoranthene, pose any danger to human cells.
Keywords:
Vero cells; cytotoxic; fluoranthene; methyl palmitate; secondary metabolites
Key Contribution: This research investigates toxicity of the Staphylococci-derived compounds to evaluate if the identified compounds could be used as possible pharmacotherapy agents without causing detrimental effects to the host cells.

1. Introduction

Cytotoxic investigations evaluate the effect and, consequently, the fate of a compound. These investigations play a role in eliminating possible pharmacotherapy compounds that could be detrimental to host cells [1].
The investigation of the toxicity of compounds from Staphylococcus species [(S. saprophyticus (ATCC 35552), S. epidermidis (ATCC 51625), and S. aureus (isolated from milk)] could influence the decision on whether or not such compounds could be employed to alleviate challenging medical conditions. The selection of Staphylococci strains was due to the role these bacteria have as the cause of nosocomial infections. The ability to cause infection is attributed to the toxin or enzyme produced by these strains during host infection [2,3].
Secondary metabolism in bacteria occurs during the stationary phase, wherein bacterial species divert from biomass production to the production of small, low molecular weight bio-active molecules known as secondary metabolites [4]. Metabolite yield can be influenced by whether a bacterial culture is axenic or mixed (co-cultivation). There is a better secondary metabolite yield in mixed than axenic culture [5,6]. The co-cultivation approach could also produce higher levels of desired products [7,8]. Metabolite production also depends on temperature, pH levels, and the composition of the growth medium as well as the incubation period, [9,10].
Some bacterial metabolites are fundamental in the production of health-protecting products. For example, tetanus toxoid (TT), a vaccine that prevents tetanus (a condition characterized by lockjaw) was derived from Clostridium tetani toxins [11]. Streptomycin, a broad-spectrum antibiotic, is a product of the Streptococcus griseus toxin [12,13]. Over and above this, secondary metabolites can be used medically as adjuvants to enhance the activity of treatment therapies as well as weapons to target other microbes [14,15,16].
However, not all secondary metabolites contribute positively to health, as some are associated with health-threatening conditions. Some bacterial metabolites may be carcinogenic [17], cytotoxic [18], nephron-toxic and cardio-toxic [19]. In this study, we evaluated the possible toxic effect of bacterial secondary metabolites from Staphylococcus species (S. aureus, S. epidermidis, and S. saprophyticus) on Vero cells. Cytotoxicity investigations play a role in the decision as to whether a compound can be used as an antimicrobial or not [20]. These investigations contribute toward the elimination of compounds that could have a negative effect as pharmacotherapy agents [21,22].
Cytotoxicity studies can be carried out by employing Vero cells and the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay. Vero cells originate from African green monkey kidneys and are well recognized in research due to their accessibility and versatile nature and have been employed in various research studies, for example in plant extract and bacterial cytotoxicity investigations [23]. Vero cell lineage is continuous and has an abnormal number of chromosomes, i.e., less or more than 23 pairs of chromosomes. This characteristic allows them to be replicated through numerous cycles of division without any deterioration of function. Unlike normal mammalian cells, Vero cells are interferon-deficient, thus they do not secrete interferon when infected with viruses. However, they have the interferon-alpha/beta receptor, therefore respond normally when recombinant interferon is added to culture media.
In [24], the cellular response and mechanism of the toxic action of three different continuous cell lines used routinely in toxicological studies (HeLa, 3T3, and Vero cell lines) against rotenone (ROT, CAS 83-79-4) and Pentachlorophenol (PCP, CAS 87-86-5), known environmental pollutants was investigated. It was discovered that Vero cells superseded 3T3 and HeLa cell lines in sensitivity after PCP and ROT treatments. The detection limits in Vero cells after PCP exposure showed a significant difference from a minimum concentration of 1 micromolar (µM) when using the MTT reduction test
The MTT assay is a colorimetric test that evaluates the activity of the mitochondria, sausage-shaped membrane-bound organelles found within bacterial cells. These organelles maintain cellular homeostasis by regulating calcium signaling, apoptosis, energy production, and cell metabolism [25]. The mitochondria house the respiratory complex known as Succinate dehydrogenase (SDH). SDH catalyzes the production of nicotinamide adenine dinucleotide (NADH), a coenzyme found in living cells. Interaction between NADH and MTT results in the reduction of MTT to purple formazan. Only live cells produce NADH; therefore, the presence of purple color indicates active metabolism within bacterial cells or live cells [1]. The reduction of MTT is measured as absorbance on a microplate reader at a wavelength of 570 nm.
The study aimed to generate secondary metabolites from the aforementioned bacterial strains, identify the compounds and investigate the toxicity of the compounds on Vero cells. This exercise is necessary to evaluate if the identified compounds could be safely used as therapeutic products.

2. Results

2.1. Laboratory Identification/Confirmation of Staphylococci Strains

The results of the three staphylococci strains are represented in Table 1. After incubation, the S. aureus strain exhibited growth on MSA agar with yellow colonies while the other two strains produced pink colonies. All the strains grew on DNA agar plates, but the clearing zones were absent around the growth of S. epidermidis and S. saprophyticus after the plate was flooded with hydrochloric acid post incubation. Coagulase production was absent in S. epidermidis and S. saprophyticus, while S. aureus produced coagulase.

2.2. Antibiotics Susceptibility Results

The antibiotic susceptibility results are depicted in Table 2. The table shows three staphylococci strains and the antibiotic concentrations that these strains were tested against as well as the resistant, intermediate and susceptibility zones in millimeters. The S. aureus and S. saprophyticus strains were susceptible to all of the antibiotics allotted in Table 3, while S. epidermidis was resistant to Vancomycin and Oxacillin. The results imply that the strains were not multidrug-resistant strains.

2.3. The GC-HRTOF-MS Screening Results

The extracts from the three Staphylococci strains (S. aureus (isolated from milk), S. epidermidis (ATCC 51625) and S. saprophyticus (ATCC 35552)) were screened with GC-HRTOF-MS and are represented in Table 3, Table 4 and Table 5. Each table describes the compounds from each bacterial strain, various times for compound elution, the mass-to-charge ratio (m/z), the molecular mass of the compounds and the peak area (the amount of compound present). Secondary metabolites yielded by Staphylococci strains (Table 3, Table 4 and Table 5) were acids, alcohols, alkenes, amines, heterocyclic compounds, esters, and fatty acids. Similar compounds eluted by S. aureus and S. saprophyticus was succinic acid that was eluted at 25:44 min; fragments (66.5316; 69.1228) and (44.0497; 74.0237) with average peaks of 1,152,910 and 748,584 for S. aureus and S. saprophyticus, respectively.
An organosilicon compound such as dimethoxy-diphenyl silane was present in S. epidermidis and S. aureus. This compound appeared at 13:53 and 30:17 min with fragments (137,0420;167,0525) and (91.0544;167.0525) at peak averages of 957,364 and 55,316 in S. aureus and S. epidermidis, respectively.
Anticholigenic agents and halogenated pyrroles were reported only in S. epidermidis. The sulphides were not eluted by S. epidermidis and S. aureus, but by S. saprophyticus only.

2.3.1. Prominent Metabolites

The prominent secondary metabolites (above 1%) yielded by Staphylococci are summarized in Figure 1. Data indicates that S. saprophyticus (ATCC 35552) yielded 9% and 12% more other compounds than S. epidermidis and S. aureus, respectively. Organosilicon compounds were more prevalent in S. epidermidis but ≤1% in S. aureus and S. saprophyticus while aromatic heterocyclic compounds contributed 4.87%; however, amino acids were ≤1% compared to S. aureus and S. epidermidis. Other prevalent compounds in S. saprophyticus were alcohols acids, alkaloids, and alkenes.

2.3.2. Statistical Analysis for Metabolites Yield

Prominent secondary metabolites were distributed as per peak areas. There were seven values for S. aureus, five for S. epidermidis and eleven for S. saprophyticus resulting in a total number of 23. Due to the distribution (normal or not normal) of the secondary metabolites, the Kruskal Wallis test (a non-parametric test) was carried out to establish if the percentage peak area average differed significantly across the prominent metabolites yielded by the three Staphylococci strains, as the total sum of the values was 23. The Kruskal-Wallis results are depicted in Table 6.
In Table 6, the percentage peak area average does not differ significantly (p = 0.396) across the three metabolites classes as indicated by the significance level.

2.4. Identification of Compounds

The compounds from S. aureus (isolated from milk), S. saprophyticus (ATCC 35552) and S. epidermidis (ATCC 51625) were reported as chemical shifts (1H NMR). The compounds identified in S. aureus were characterized by 1H NMR showing the signals of arrangements of aromatic hydrocarbons (Fluoranthene), heterocyclic compounds (3-Methyl-2-phenyl-1H-pyrrole) and amino acids (Cyclo(L-Leu-L-Propyl). For S. epidermidis, the compounds were identified as Oleamide (amide) and Methylpalmitate (ester), while S. saprophyticus (ATCC 35552) yielded an amine, alkaloid, alcohol, and acid. The identified compounds were Veratramine (alkaloid); 1,2,6-Hexantriol (alcohol); Succinic acid (acid) and 4-Methyl-pentyl-amine (amine). The chemical shifts of the above-mentioned compound are indicated below.

2.4.1. S. saprophyticus-Derived Compounds

  • 4-Methyl-pentylamine (C7H1).
Classification: Amine
Chemical shift: 1H NMR (600 Varian MHz, CDCL3): δ 2.58–2.53 (m, 2 H, CH2-NH2), 2.42 (s, 3 H, NH-CH3), 1.50–1.26 (m, 8 H, 4 CH2), 0.91–0.86 (m, 3 H, CH3) ppm.
  • Veratramine (C27H39NO2)
Classification: Alkaloid
Chemical shift: 1H NMR (600 Varian MHz, CDCL3) 0.83 (3 H, d, J ¼ 7.0 Hz, 27-H), 1.15 (3 H, s, 19-H), 1.40 (3 H, d, J ¼ 7.5 Hz, 21-H), 2.11 (1 H, brs, 20-H), 2.32 (3 H, s, 18-H), 2.50 (1 H, dd, J ¼ 9.0, 4.0 Hz, 22-H), 3.27 (1 H, m, 23-H), 3.52 (1 H, m, 3-H), 5.49 (1 H, brd, J ¼ 4.0 Hz, 6-H), 6.97 (1 H, d, J ¼ 7.5 Hz, 15-H), 7.22 (1 H,d J ¼ 7.5 Hz, 16-H).
  • 1,2,6-hexanetriol (C6H14O3)
Classification: Alcohol
Chemical shift: 1H NMR (600 Varian MHz, CDCL3) δ = 5.37-4.56 (brs, 3H), 3.78-3.69 (m, 1H), 3.62-3.54 (m, 1H), 3.51-3.40 (m, 2H), 1.69-1.53 (m, 2H), 1.53-1.31 (m, 2H), 1.18 (d, J = 6.3 Hz, 3H) ppm.
  • Succinic acid (C4H6O4)
Classification: Acid
Chemical shift: 1H NMR (600 Varian MHz, CDCL3) δ 2.42 (α, β-CH).

2.4.2. S. aureus-Derived Compounds

  • Flouranthene (C16H10)
Classification: Polycyclic aromatic hydrocarbon
Chemical shift: 1H NMR (600 Varian MHz, CDCL3): J =0.0HzH3); 8.02ppm (d, 1H, J = 8.1 Hz, H4); 8.23 ppm (d, 1H, J-7.9 Hz, H6).
  • Cyclo (leucyl-prolyl (C11H18).
Classification: Amino acid
Chemical shift: 1H NMR (600 Varian MHz, CDCL3) δ 0.96 (3H, d, J = 6.4 Hz, 11-CH3), 1.00 (3H, d, J = 6.4 Hz, H-12), 1.52 (1H, ddd, J = 5.0, 9.6, 14.8 Hz, H-10), 1.74 (1H, m, H-11), 1.90 (1H, m, H-4), 1.98-2.09 (2H, m, H-4, H-10), 2.13 (1H, m, H-5), 2.35 (1H, dddd, J = 3.2, 8.0, 8.0, 12.8 Hz, H-5), 3.56 (2H, m, H-3), 4.01 (1H, dd, J = 3.4, 9.6 Hz, H-9), 4.11 (1H, t, J = 8.0 Hz, H-6), and 5.86 (1H, br.s, NH).
  • 3-Methyl-2-phenyl-1H-pyrrole (C11H11N)
Classification: Heterocyclic compounds
The NMR shift was represented as: 1H NMR (600 Varian MHz, CDCL3) ppm 7.39-7.24 (m, 4H), 7.16-7.10 (m, 1H), 6.92 (t, J = 2.5 Hz, 1H), 6.81-6.79 (m, 1H), 6.11 (t, J = 2.5 Hz, 1H), 2.10 (s, 3H).

2.4.3. S. epidermidis-Derived Compounds

  • Oleamide (C18H35NO)
Classification: Amides
Chemical shift: 1H NMR (600 Varian MHz, CDCL3): 6.00 (br s, 1H, NH), 5.27 (m, 2H, H-9, H-10), 3.26 (dt, 2H, H-1′, 5.5, 6.0), 2.34 (t, 2H, H-2′, 6.0), 5.7), 2.17 (s, 6H, NCH3), 2.10 (t, 2H, H-2, 7.4), 2.00-1.90 (m, 4H, 2H-8, 2H-11), 1.62-1.53 (m, 2H, H-3), 1.23-1.20 (m, 20H), 0.81 (t, 3H, H-18, 6.6).
  • Methyl palmitate (C17H34O2)
Classification: Esters
Chemical shift: 1H NMR (600 Varian MHz, CDCL3): 5.74 (br, 1H, NH, 3.26 (t, 2H), 2.87–2.31 (m, 3H), 1.78–1.59 (m, 2H), 1.60–1.40 (br, 4H), 1.35–1.15 (br, 48H, CH2), 0.87 (t, 6H, CH3).

2.5. Cytotoxic Studies

Table 7 displays the LC50 of compounds derived from S. aureus, S. epidermidis, and S. saprophyticus. The LC50 values ranged from 0.0167–0.0441 mg/mL. Fluoranthene was the most toxic because its LC50 value (0.016 mg/mL) was the lowest of all the compounds, and relatively close to that of the positive control (doxorubicin) with an LC50 of 0.0097 mg/mL. Other compounds had relatively low cytotoxicity to Vero cell lines.

Statistical Analysis for Cell Viability

The ANOVA test was carried out to check the relationship between concentration and percent cell viability (Table 8 and Table 9). Table 8 shows that there is a statistically significant (p < 0.05) linear relationship between concentration and percent cell viability. In Table 7 the R square value (coefficient of determination) is 0.724 suggesting that 72.4% of the variance in percent viability is explained by the concentration of the sample.

3. Discussions

S. aureus strains exhibited susceptibility to Augmentin and Oxacillin. The efficacy of Augmentin against S. aureus is also documented by [26]. Since the S. aureus strain was susceptible to Augmentin and Oxacillin, it is classified as methicillin-sensitive S. aureus [MSSA] [27]. Such was likely to be susceptible to Ceftriaxone as shown in the current study. Ceftriaxone, a β-lactam cephalosporin, binds to the bacterial-penicillin binding proteins, disrupting the synthesis of the bacterial cell wall [28]. This antibiotic is used as an alternative to Cephazolin in the treatment of methicillin-sensitive S. aureus-related infections. It is a preferred antibiotic due to its shorter administration period and frequency [29]. S. aureus also showed susceptibility to Cotrimoxazole, contrary to what was reported in [30], where resistance to Cotrimoxazole was evident in MSSA. However, the susceptibility of S. aureus to Vancomycin correlates with the findings of [30]. Staphylococcus saprophyticus was sensitive to all the antibiotics, while S. epidermidis was resistance to Vancomycin and Oxacillin but susceptible to other antibiotics. The acceptance of S. epidermidis as a pathogen in various areas of the human body is progressively increasing [31] The susceptibility of stains to almost all of the allotted antibiotics imply that the strains were not multidrug resistant, therefore exposure of such strains to a nutrient depleted environment, such as minimal medium, could enhance the results regarding the production of secondary metabolites.
The GC-HRTOF-MS analyses of secondary metabolites from three Staphylococci strains yielded acids, alcohols, alkenes, amines, heterocyclic compounds, esters, and fatty acids. The presence of alkenes, alcohols and acids in S. aureus was also reported by [32,33].
Common compounds for S. aureus and S. saprophyticus include succinic acid, which was eluted at 25:44 min with fragments (66.5316; 69.1228) and (44.0497; 74.0237) with average peaks of 1,152,910 and 748,584 for S. aureus and S. saprophyticus, respectively. Another compound eluted was an organosilicon, dimethoxy-diphenylsilane, that appeared at 13:53 and 30:17 min with fragments (137,0420;167,0525) and (91.0544;167.0525) with a peak average of 957,364 and 55,316 in S. aureus and S. epidermidis, respectively.
The S. saprophyticus metabolite yield exceeded that of S. epidermidis and S. aureus by 9 and 12%, respectively. Organosilicon compounds were more prevalent in S. epidermidis but ≤1% in S. aureus and S. saprophyticus. In S. saprophyticus, aromatic heterocyclic compounds were 4.87%; however, amino acids were ≤1% compared to S. aureus and S. epidermidis. Other prevalent compounds in S. saprophyticus were alcohols acids, alkaloids, and alkenes.
The GC-HRTOF-MS screening revealed the presence of different compounds of which some are known to possess antimicrobial properties. The screening also revealed that there was more production of secondary metabolites in S. saprophyticus, which exceeded that of S. aureus and S. epidermidis. However, the abundance, time of elution and distribution of each metabolite differed from one strain to another. This was noted at the elution of Succinic acid, for S. aureus and S. saprophyticus; this acid was eluted at the same time (25:44 min); with fragments (66.5316; 69.1228) and (44.0497; 74.0237) and average peaks of 1,152,910 and 748,584 for S. aureus and S. saprophyticus, respectively. Another compound eluted was an organosilicon, Dimethoxydiphenylsilane in S. aureus with elution time being 13:53 min, fragments (137,0420;167,0525) and peak average 957364, while in S. epidermidis, it was eluted at 30:17min, fragments (91.0544;167.0525) and peak average 55316.
In prominent secondary metabolites, the percentage peak area average was not normally distributed. The Kruskal Wallis Test was carried out to check if the percentage peak area average differed significantly across the prominent metabolites yielded by the three Staphylococci strains. The Kruskal-Wallis test revealed the percentage peak area average was statistically significant (p = 0.396).
Extracts from Staphylococci were purified and, thereafter, identified by Nuclear Magnetic Resonance (NMR) using Varian 600 MHz. The identification of compounds was achieved through the analyses of the protons. Identification is necessary to know the type of compound involved, thus allowing pharmaceutical scientists to produce new health-protecting products. Proton analyses were reported as chemical shifts (1H NMR) with 1H NMR showing signals of arrangements of the chemical shifts present in S. saprophyticus (ATCC 35552) representing amine, alkaloid hydrocarbon, alcohol, and acid. The identified compounds were Veratramine (alkaloid); 1,2,6-Hexantriol (alcohol); Succinic acid (acid) and 4-Methyl-pentyl-amine (amine).
The cytotoxicity results revealed that none of the compounds from S. saprophyticus and S. epidermidis, and only some of the compounds from S. aureus, showed cytotoxicity in the Vero cells. The LC50 of bacterial compounds was higher than that of Doxorubicin (positive control) in toxicity on Vero cells. The LC50 of these compounds ranged from 0.023–0.044 mg/mL.
The compounds were viewed as being toxic if the LC50 was equal to or lower than doxorubicin [0.0101]. The recorded LC50 ranges were 0.0167–0.0441 mg/mL against Vero cells); 4-Methyl-pentyl amine [0.0231]; Fluoranthene [0.0167]; Cyclo (leucyl-prolyl [0.0310]; Oleamide [0.0333]; Veratramine [0.0274]; Methyl palmitate [0.0441]; 3-methyl-2-phenyl-1H-pyrrole [0.0341]; 1,2,6-Hexanetriol [0.0333]; and Succinic acid [0.0334]. According to the American National Cancer Institution guidelines, and stated by other researchers, compounds with a LC50 ≤ 20 µg/mL are harmful [34,35]. The secondary metabolites that yielded these compounds were extracted with dichloromethane and the concentration of compounds was 2000 µg/mL. According to [36] the dichloromethane-extracted compounds exhibited action on cells at the lower concentration of 573.6 µg/mL [20]. Therefore, since we used dichloromethane in the extraction process, the compounds could have an impact on Vero cells at concentrations lower than 2000 µg/mL.
The Spearman’s correlation analysis showed that the test values were statistically significant; (p-value < 0.05) and correlation; (r = −0.912), suggesting that there was a correlation between the concentration and percent viability. These results suggested that cell viability was dependent on the higher LC50 value.
Compounds to be used as therapeutic agents must be efficient at lower concentrations while non-toxic to the host cell. This selective toxicity compares the therapeutic effect of the therapeutic agent to the amount that causes toxicity. The concentration of agents should destroy pathogens but also be tolerated by the host [12].
Fluoranthene was identified as being cytotoxic with an LC50 of 0.0167. Fluoranthenes are classified as polycyclic aromatic hydrocarbons (PAHs). PAHs are light yellow, white, or colorless solid compounds [37]. PAHs are classified according to their molecular weight; the high-molecular-weight PAHs consist of more aromatic rings while lower molecular weight PAHs have two or three aromatic rings. PAHs are unmanageable, toxic pollutants existing in the highest concentrations [38]. They are also found in popular beverages, such as coffee and tea, due to the heating steps during preparations and atmospheric deposition on raw plants, [39]. Other sources of PAHs are man-made, such as fuels from car exhausts, diesel, and coal [40]. When PAHs are released into the environment, they are ingested or inhaled and, thereafter, stored in fatty tissues, or metabolized and then excreted in urine [41]. The PAHs reduce ATP production in the mitochondrion, causing alterations in mitochondrial morphology and hindering mitochondria-dependent apoptotic pathways [42].
Fluoranthenes are the most toxic among the PAHs. The toxicity of fluoranthene was described by [43] wherein exposure to fluoranthene for 24 h negatively affected the photosynthetic ability of seven species of marine algae. The same species decreased in cell density after 72 h of exposure.
The LC50 of the other bacterial metabolites was higher than that of the positive control so they were less toxic to Vero cells. Furthermore, methyl palmitate was considered the least toxic of the nine compounds because its LC50 value (0.04 mg/mL) was furthest from the control. Other identified compounds are discussed below.
Succinic acid is produced aerobically and anaerobically by most bacteria as by-products of metabolism. This acid controls the growth of various bacterial species and possesses different levels of efficiency as an antimicrobial [44]. Succinate, a salt from succinic acid, plays a role in the production of fumaric acid necessary for initiating Krebs’s cycle, an energy generation mechanism important for normal body functioning. Succinate supplements degrade toxic aldehydes (by-products of alcohol metabolism) to water and carbon dioxide. Succinic acid enhances the recovery of immune as well as neural systems and it is a well-recognized antibiotic due to its acidic nature; however, it is corrosive at higher concentrations [45,46].
Methyl palmitate, a fatty acid methyl ester (FAME) plays a role as an antioxidant and antimicrobial. It was reported by [47] that the antimicrobial properties of microalgae were due to the higher concentration (23.08%) of palmitic acid. FAMEs have strong antimicrobial activities at the lowest MIC. This result indicated that FAME possesses antioxidant as well as antimicrobial properties against health-threatening conditions. Other identified non-toxic compounds include the following.
The antibacterial and antifungal properties of Cyclo (leucyl-prolyl) against bacteria and pathogenic fungi were reported by [48] and [49] respectively. MMS-50 also exhibited a bacteriostatic effect on Streptococcus mutants at the minimum and maximum inhibitory concentrations of 100 and 250 μg/mL, respectively [50].
Methyl-2-phenyl-1H-pyrrole originates from pyrroles; pyrroles interact with biomolecules of living systems to form compounds of medicinal importance. Pyrrole-containing antibiotics are widely used medically and agriculturally and are efficient against gram-negative (E. coli) and Gram-positive bacteria (S. aureus) at 30 and 31 µg/mL, respectively. Pyrrole antibiotics include tetrapyrrole prodigiosin, chlorinated pyrroles, and aminocoumarin [51].
Oleamides, also present in endophytes, are active against disease-causing agents. They target bacterial protein synthesis and cause leakage of intracellular components. The therapeutic properties cover a range of conditions, such as diabetes, cancer, and parasitic and bacterial infections [52].
Veratramine lowers blood pressure and plays a role in basal cell carcinoma therapeutics [53]. It was also reported that the antitumor activity of veratramine that prevented the downstream signaling pathway of transcription factor activator protein-1 (AP-1), which regulates apoptosis and other cell functions [54].
Methyl-pentyl amine is also recognized for its antimicrobial activity. Co-polymers derived from 4-methyl-pentyl amine, imidized and 3-(dimethylamino) (DMAPA), and 1-propylamine showed antimicrobial properties against Gram-negative bacteria [55].
1,2,6-Hexanetriol is recognized for its non-toxic nature and is, therefore, used as a solvent base for many steroids in cream applications and skin conditioners. Hexanetriol is also used in pharmaceutical drug manufacturing and testing. It can substitute glycerol due to hygroscopicity and stability. It enhances the efficacy of ingredients used in a formulation used in crop protection. Hexanetriol derivatives are used as corrosion inhibitors. It is recognized for its stability and high boiling point [56].

4. Conclusions

The aim of screening secondary metabolites from Staphylococci and the subsequent identification of compounds resulted in nine compounds. Eighty-nine percent of the identified compounds were considered safe to Vero cells and, therefore, to human cells based on high LC50, except for fluoranthene.

5. Methods

The investigation of the cytotoxic effect of staphylococci compounds on Vero cells was performed in vitro to determine the effect of compounds on Vero cells and, thus, on human cells.

5.1. Staphylococci Strains

The staphylococci strains used for the experiment are depicted in Table 10. These include Staphylococcus aureus (S. aureus), Staphylococcus epidermidis (S. epidermidis) [ATCC 51625] and Staphylococcus saprophyticus (S. saprophyticus) [ATCC 35552]. These bacterial strains were in porous beads, which served as carriers to support the micro-organisms and were stored at 2 °C. They were purchased from Thermofisher Scientific, Johannesburg, South Africa) except for the Methicillin-sensitive Staphylococcus aureus, which was isolated from milk. The S. aureus sample was obtained from cows with clinical features of mastitis such as swollen udders and the production of watery clotted milk [57]. Using an automatic somatic cell counter (SCC), the number of somatic cells (white cells)/mL of milk was enumerated. Counts of 200,000 cells/mL of milk or more were indicative of mastitis [58,59]. Five hundred (500) μL of milk from mastitic cows was centrifuged at 200× g for 5 min at room temperature and the sediment was cultured on blood and nutrient agar.

5.1.1. Identification and Confirmation of Staphylococci Strains and the Preservation of S. aureus Strain

The culture characteristics of three staphylococci strains (S. epidermidis, S. saprophyticus and S. aureus) was identified by using laboratory tests such as growth on the Mannitol salt agar (MSA) and DNAse plates as well as antimicrobial susceptibility testing. The MSA plate differentiate between mannitol-fermenters (S. aureus) and non-fermenters (other staphylococci). The Mannitol-fermenting bacteria appear as yellow conies while non-fermenters are pink. The ability to grow in a high concentration of salt (7.5%), such as in MSA plate, is a characteristic of the staphylococcus genus [60]. DNase agar, a differential medium that determines if bacteria produce an enzyme deoxyribonuclease (DNase). This enzyme catalyzes the hydrolytic cleavage of phosphodiester linkages in the DNA backbone, thereby degrading DNA. Bacteria that produce the enzyme DNAse hydrolyze DNA and this is indicated by a clearing zone around the colonies on the DNA agar upon flooding the plate with hydrochloric acid [61]. Coagulase is an enzyme that facilitates the conversion of fibrinogen to fibrin and it distinguishes S. aureus from other staphylococci [62]. For the coagulase test, colonies from each bacterial strain were put on a slide, emulsified, then 2 drops of plasma were added, thereafter the slides were examined for clumps.
After identification, the S. aureus strain was preserved by inoculating a colony from MSA, into 500 μL nutrient broth (NB) and incubated overnight, thereafter 500 μL of the overnight culture was added to 500 μL of 50% glycerol in a 2 mL screw top tube, gently agitated, and frozen at −80 °C. The preservation of S. aureus strain was necessary because unlike other staphylococci used in this research, it was not an ATCC strain, therefore it was not priorly preserved.

5.1.2. Resuscitation of Staphylococci Strains

Resuscitation of strains refers to the process of reviving bacterial strains after cryopreservation. For S. aureus, previously glycerol preserved strains were resuscitated by adding 500 uL of preserved culture and 500 µL of NB into 1000 µL; thereafter, incubated overnight at 37 °C. After incubation, the contents of the vial were transferred into a 500 mL Schotts bottle. For other bacterial strains, each bacteria-containing bead was reconstituted by immersing the bead into a vial of 1 mL nutrient broth and incubated for 18–24 h at 37 °C. For other staphylococci strains; each bacteria-containing bead was reconstituted by immersing the bead into a vial of 1 mL nutrient and incubated for 18–24 h at 37 °C. The content from each vial was thereafter transferred into the corresponding bottle of 500 mL nutrient broth and further incubated for 18–24 h at 37 °C.

5.1.3. Susceptibility of Staphylococci Strains to Antibiotics

The susceptibility of the Staphylococci to antibiotics was tested to check if they possess the antibiotic-resistant characteristic. Susceptibility to antibiotics refers to the ability of antibiotics to kill or inhibit bacteria [63]. The selection of the antibiotics was according to the South African treatment regimen guidelines for Staphylococci infections.
A colony from 24-h-old subcultures of each strain was inoculated into a vial containing 2 mL saline and vortexed for 2 min to obtain a uniform suspension with turbidity equivalent to 0.5 McFarland standard (1.5 × 108 colony forming units (CFU/mL). The suspension of each strain was streaked onto the corresponding Muller-Hinton plates purchased from Thermofisher, Johannesburg, South Africa) and, thereafter, the discs of Augmentin (30 µg), Ceftriaxone (30 µg), Oxacillin (5 µg), (30 µg) and Cotrimoxazole (25 µg) were placed onto the aforementioned streaked plates, then incubated for 24 h [64,65]. After incubation, the susceptibility zone of each antibiotic was measured using a caliper. Susceptibility was recorded as millimeters (mm).

5.2. Minimum Broth Preparation and Secondary Metabolites Production

A simulated environment was developed to enhance the bacterial strains to undergo secondary metabolism. This was achieved through the preparation of a nutrient-limited growth medium, minimal broth. The minimal broth was prepared according to [66]. The protocols involved weighing and dissolving 0.5 g NaCl, 1.0 g NH4Cl, 3.0 g KH2PO4, and 12.8 g Na2HPO4 in 478 mL deionized water, which was autoclaved at 121 °C and thereafter cooled to 50 °C. When the salts were cooled, 0.1 mL (Thiamine 0.5% v/w solution), 0.1 mL of 1M CaCl2, 2 mL (1M of (MgSO4) and 20 mL (Glucose 20% solution) were then filter sterilised into an M9 salts solution. Fifty (50) mL of previously incubated broths of S. aureus, S. epidermidis, and S. saprophyticus were transferred into separate 500 mL of minimal broth and, thereafter, placed in a shaking incubator (150× g) for 7 days at 30 °C. After 7 days, the bacterial culture broths were centrifuged for 15 min at 10 000× g to remove the biomass [66].

5.3. Metabolites Extraction and Analyses

5.3.1. Extraction

Extraction of secondary metabolites was performed according to the protocol stated by [67], however, with few modifications. Accordingly, equal volumes of dichloromethane and ethyl acetate (1:1, v/v) were used for the extraction. One hundred (100) mL each of dichloromethane and ethyl acetate (1:1, v/v) were added to 200 mL of sample, and the mixture vortexed and transferred to a separation funnel and shaken thoroughly, each time with the lid opened to release excess pressure. The separation funnel was then mounted onto a ring stand to allow the separation of the phases.
The separation of phases occurred due to gravity and was based on the principle that immiscible liquids separate into layers depending on their densities, creating different layers of solution-solute. The Teflon stopper and the tap were then opened to release the lower phase into a clean beaker. After the removal of the lower phase, the Teflon stopper was closed, and the upper layer was poured out through the top into another container. The upper layer was concentrated using a vacuum rotary evaporator. The temperature at which the sample was to be concentrated was selected, taking into consideration the average boiling point of dichloromethane (39.6 °C) and ethyl acetate (77.1 °C). The samples (upper layers) from S. aureus; S. epidermidis and S. saprophyticus were therefore concentrated at 58 °C, (average of 39.6 °C and 77.1 °C); thereafter, the secondary metabolites were freeze-dried, and each was transferred to previously weighed sterile flasks and stored in a dark cupboard.

5.3.2. Screening and Analyses

The preparation for sample screening and analyses was performed according to [68]. Previously dried extracts from each S. aureus, S. saprophytic, and S. epidermis was individually reconstituted by adding 1 mL of chromatographic grade methanol and then filtered into amber vials.
The GC-HRTOF-MS system (LECO Corporation, St Joseph, MI, USA) operating at a high resolution was calibrated using Perfluorotributylamine (PFTBA) and 11 masses as the pre-analysis calibration, C5F10N (m/z 263.9871), C8F16N (m/z 413.9775), C9F18N (m/z 463.9743), C9F20N (m/z 501.9711), C3F6 (m/z 149.9904), C2F4 (m/z 99.9936), C2F4N (113.9967), CF3 (m/z 68.9952), C2F5 (m/z 130.9920), and C4F9 (m/z 218.9856). The intensity and resolution were 41.392 and 40.200, respectively. A microliter (1 µL) of each previously methanol-treated sample was injected into the system using helium gas as the carrier gas. The transfer and inlet temperatures were 225 and 250 °C, respectively. The temperature of the oven was set at 70 °C, and kept for 0.5 min, thereafter, adjusted from 10 °C /min to 150 °C and retained for 2 min. The oven temperature was then adjusted from 10 °C/min to 330 °C and kept for 3 min to bake out the column. The triplicate of each sample, respectively, was introduced into the GC-HR-TOF-MS equipment with solvent blanks to check for contamination and impurities.
From the data obtained, peak selection, retention time alignment, and matching detection were carried out on the ChromaTOF-HRT® software (LECO Corporation, St Joseph, MI, USA). The data were also processed by making use of other parameters, such as a signal-to-noise of 100 and a minimum match similarity of >70% before the compound name was assigned by comparing the molecular formula, retention time, and mass spectra data. Percentage peak areas were then calculated, and the respective observed m/z fragments obtained from the ChromaTOF-HRT® data station were recorded. The metabolite class was then elucidated with the corresponding m/z fragments and molecular formula. The concurrent versions system (CVS) GC-MS data were converted into Excel, then all the noise peaks were deleted. Only compounds after 183 s and appearing in 2 or all were considered. The compounds were characterized based on their chemical and physical modes of action.

5.3.3. Purification of Crude Secondary Metabolites and Identification of Compounds from Staphylococci

The crude secondary metabolites from S. aureus, S. epidermis and S. saprophytic were purified using the column chromatography method to the method stated in [69], with modifications. This process aimed to achieve pure compounds. Purification of the extracts was carried out using adsorbent and mobile phases, the former comprising of silica gel and methanol while the latter consisted of aluminum, thin layer chromatography (TLC) plates, and solvents of various concentrations. For the adsorbent phase; 1.2 g was dissolved in 25 mL of methanol and then absorbed with 6 g silica gel. The sample was dried and transferred to a column packed with silica gel. The sample was then eluted with a 2, 5, 8, 10, 15 and 20% methanol and dichloromethane solution. For the mobile phase we used 5% methanol and dichloromethane (comprised of 5 and 95 mL of methanol and dichloromethane); 10% methanol and dichloromethane (10 and 90 mL of methanol and dichloromethane), and 10% acetone and dichloromethane (10 and 90 mL acetone and dichloromethane), respectively. The TLC plates were developed with the above-mentioned solvents to accommodate the polar and less polar secondary metabolites.
Ten mL fractions (parts collected from a batch of a compound during the separation process) from the column were collected in a test tube each time. This collection procedure was carried out during elution for all concentrations. After collection, each fraction was spotted on a TLC plate using a capillary tube to check for the presence of compounds. Spotting was repeated 2× or 3× to concentrate the compound onto the spot for improved compound detection. The TLC plate had a row of spots corresponding to various fractions and then eluted in tanks with 10% methanol and dichloromethane to identify and check the retention factor (RF). The RF of a compound referred to the distance of the compound divided by the distance of the solvent front. The TLC was then viewed under UV light at 254 nm wavelengths. Fractions containing pure compounds were collected and those with similar RF were combined. Such compounds were placed in a fume hood to evaporate solvents; thereafter, they were dried and stored in vials.
For the impure extracts, the solid phase extraction (SPE) method was used. This method involves a solid adsorbent found within a cartridge. A one-gram silica gel cartridge was used to elute the sample. The cartridge was conditioned by adding 10 mL each of distilled water, then dichloromethane, and distilled water again; thereafter, the impure sample was loaded 10 mL at a time. The cartridge was loaded on a vacuum pump to allow for the separation process. After collecting the sample, the cartridge was rinsed with distilled water and subsequently with 5, 10, 20, and 100% methanol concentrations to decrease polarity.
The extracts were further purified employing a 10 mL acetonitrile and then a methanol pre-conditioned Varian Bond Elute C18 cartridge. Extracts were thereafter eluted with acetonitrile and methanol at the following ratios: 20, 40, 60, 80 and 100% except for S. saprophytic, which was less polar, therefore the sample was eluted with acetone and dichloromethane, and thereafter with 100% acetonitrile. The collected compounds were identified using a Varian 600 MHz NMR spectrometer (Agilient Technologies, CA, USA). This spectrophotometer is a three-channel instrument that operates at a 1H frequency of 600 MHz (14.1 T). It has a double resonance broad-band-probe head (600 DB Auto X) for general solutions analyses while well a triple-resonance-probe [5 mm Auto HCN PFG] is for biological solutions. [7,70].
Before the analyses, each pure sample was dissolved in 0.7 mL deuterated chloroform [CDCl3] (Sigma Aldrich, Taufkirchen, Germany) and then transferred into clean NMR tubes. The height of the sample in the tube was ensured to be around 5 cm, then the tubes were loaded onto the sampler. The sampler containing the MNR tubes was then wiped off with a clean paper towel to allow for proper grip during spinning and to avoid contaminating the spinner.
The tubes were then positioned in such a way that the solution was situated in the detected region of the NMR probe of the Varian 600 MHz spectrometer. An equidistant between the center of the detected region and the meniscus of the solution at the top as well as the bottom of the NMR tube was ensured to allow for the sample to shim properly. The Varian 600 MHz spectrometer was also equipped with a shim, a device that adjusts the homogeneity of the magnetic field, thus the samples were shimmed before analyses. The data obtained were processed using Varian VNMRJ Software.

5.4. Preparation, Proliferation, and Harvesting of Vero Cells

A cryopreserved (−80 °C) vial containing Vero cells [E6 cell lines] (Thermo Fisher Scientific, Johannesburg, South Africa) was thawed by gently agitating in a 37 °C water bath, ensuring that the cap of the vial was not submerged to prevent possible contamination from the water-bath. After thawing, the vial was sprayed with 70% ethanol to maintain sterility. Vero cells suspension from the cryovial were then transferred into a 15 mL conical tube containing 10mL minimal essential medium [MEM] (Thermo Fisher Scientific, South Africa) and thereafter centrifuged 400× g for 5 min at room temperature. The supernatant was discarded, and the cells were re-suspended in 10 mL MEM containing 5% fetal calf serum (Biological Scientific Solutions, New Delhi, India) and 0.1% gentamicin (Virbac Pharmaceuticals, Johannesburg, South Africa), thereafter transferred into a 50 cm2 vented-cap tissue culture flask and incubated at 37 °C with 5% CO2 until proliferation was achieved.
The proliferation of Vero cells is dependent on their attachment to the solid surface. Cells were monitored every second day and the media was changed every fourth day till the cells reached a >90% confluent monolayer. Confluence refers to the state where the culture flask contains twice the number of cells compared to the initial amount. Cell confluence was also identified by the presence of a turbid appearance in the culture medium, as the cells clumped together, and a decrease in medium pH due to the production of lactic acid as the metabolism by-product.
When the culture in the flask was turbid and contained almost double the number of cells compared to the initial start-up culture, the growth medium was discarded; then 2 mL Dulbecco’s Phosphate Buffered Saline [DPBS] pH 7.2–7.4 (Thermo Fisher Scientific, Johannesburg, South Africa) was added to the cells. The cells were then centrifuged for 5 min at 400 rpm and the pellet was re-suspended in 10 mL DPBS. A 5 mL volume of Trypsin ethylenediaminetetraacetic acid (EDTA) was added to the flask containing the cells and incubated for 2–3 min at 37 °C until the cells detached from the flask. A total of 5 mL MEM was added to the culture to inactivate the trypsin EDTA; the culture was then transferred to a clean flask and the concentration of cells was adjusted to 5 × 104 cells/mL using MEM [71].

5.5. Cytotoxicity Assay

A cytotoxicity assay was carried out as described initially by) [72] and later used by) [73]. The serial dilutions of compounds were prepared in MEM by pipetting two hundred (200) µL of the cell suspension into each well of columns 2 to 11 of a sterile 96-well microtiter plate. Two hundred µL of MEM was added to columns 1 and 12 to maintain humidity, minimize evaporation, and consequent well-to-well variability. The plates were then incubated in a 5% CO2 incubator at 37 °C for 24 h until the cells reached the exponential growth phase. The MEM was aspirated from the cells, which were then washed with 150 mL phosphate-buffered saline [PBS], (Whitehead Scientific, Johannesburg, South Africa) and replaced with 200 µL of MEM with compounds of each of S. aureus, S. epidermidis, and S. saprophyticus at differing concentrations in quadruplicate.
The cells were least disturbed during aspiration and the addition of the medium and test compounds, respectively. A positive control [doxorubicin chloride] (Pfizer Laboratories, Johannesburg, South Africa) and untreated cells (negative control) were included in each assay. The microtiter plates were incubated in a 5% CO2 incubator at 37 °C for 48 h.
After incubation, the MEM was aspirated and the cells were washed, thereafter 30 µL of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide [MTT] (Sigma Aldrich, Taufkirchen, Germany) from a stock solution of 5 mg/mL in PBS was added to each well and the plates were re-incubated at 37 °C in a 5% CO2 incubator for 4 h. The medium from each well was then carefully removed; however, not disturbing the MTT crystals in the wells. Fifty µL was added to each well to dissolve the MTT formazan crystals with the plates gently agitated to ensure thorough mixing.
The wells in column 1, containing MTT and medium but without cells, were used to validate the performance of the plate reader (BioTek Synergy, Winooski, VT, USA) equipped with KC4 software [1.20.0.42] (BioTek Instruments Winooski, VT, USA) data reduction software. The cell viability percentage was calculated using the following formula:
Percentage (%) Viability = Sample absorbance/control absorbance) × 100.
The lethal concentrations (LC50) values were calculated as the concentration of compounds resulting in a 50% reduction of absorbance relative to that of untreated cells. The linear regression analysis of the concentrations-response curve plotted between the sample concentration of two inherent assays was used to obtain the 50% lethal concentration of the positive control and that of the tested compounds.

Author Contributions

Conceptualization, M.S.M.; Data curation, J.S. and G.F.; Formal analysis, M.S.M. and K.M.; Investigation, M.S.M.; Resources, L.M.; Software, S.M.N.; Supervision, E.G. and P.N.; Validation, J.M.; Writing—original draft, M.S.M.; Writing—review and editing, Gerda Fouche, L.M. and K.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Research Foundation-LEAP-Agri Research Cooperation Programme (Reference: Leap Agri-483). The funders had no role in the design of the study; analyses, interpretation of data; manuscript writing; and the decision to publish the results.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Part of the data is available on https://uoj-researchportal.esploro.exlibrisgroup.com/esploro/outputs/doctoral/Secondary-metabolites-produced-by-Staphylococcus-species/9910534007691?institution=27UOJ_INST (accessed on 24 August 2022).

Acknowledgments

We convey our gratitude to the technical staff of the Council for Scientific and Industrial Research (CSIR) for the advanced methodologies protocols and compound identification. We also acknowledge Anesu Kuhudzai from the University of Johannesburg for statistical analyses.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Aslantürk, O.S. In Vitro Cytotoxicity and Cell Viability Assays: Principles, Advantages, and Disadvantages. 2017, pp. 1–18. Available online: https://cdn.intechopen.com/pdfs/57717.pdf (accessed on 7 November 2021).
  2. Silva, K.; Silva, L.; Silva, G.; Borges, C.L.; Novaes, E.; Paccez, J.D.; Fontes, W.; Giambiagi-deMarval, M.; Soares, C.; Parente-Rocha, J.A. Staphylococcus saprophyticus proteomic analyses elucidate differences in the protein repertories among clinical strains related to virulence and persistence. Pathogens 2020, 6, 69. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Yang, N.J.; Chiu, I.M. Bacterial signaling to the nervous system through toxins and metabolites. J. Mol. Biol. 2017, 429, 587–605. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Monistero, V.; Graber, H.U.; Pollera, C.; Cremonesi, P.; Castiglioni, B.; Bottini, E.; Ceballos-Marquez, A.; Lasso-Rojas, L.; Kroemker, V.; Wente, N.; et al. Staphylococcus aureus isolates from bovine mastitis in eight countries: Genotypes, detection of genes encoding different toxins, and other virulence genes. Toxins 2018, 10, 247. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Liu, C.; Kakeya, H. Cryptic chemical communication: Secondary metabolic responses revealed by microbial co-culture. Chemistry 2020, 15, 327–337. [Google Scholar] [CrossRef] [PubMed]
  6. Zhuang, L.; Zhang, H. Utilizing cross-species co-cultures for discovery of novel natural products. Curr. Opin. Biotechnol. 2021, 69, 252–262. [Google Scholar] [CrossRef]
  7. Knight, M.J.; Webber, A.L.; Pell, A.J.; Guerry, P.; Barbet-Massin, E.; Bertini, I.; Felli, I.C.; Gonnelli, L.; Pierattelli, R.; Emsley, L.; et al. Fast resonance assignment and fold determination of human superoxide dismutase by high-resolution proton-detected solid-state MAS NMR spectroscopy. Angew. Chem. Int. Ed. 2011, 50, 11697–11701. [Google Scholar] [CrossRef]
  8. Ruiz, B.; Chávez, A.; Forero, A.; García-Huante, Y.; Romero, A.; Sánchez, M.; Rocha, D.; Sánchez, B.; Rodríguez-Sanoja, R.; Sánchez, S.; et al. Production of microbial secondary metabolites: Regulation by the carbon source. Crit. Rev. Microbiol. 2010, 36, 146–167. [Google Scholar] [CrossRef]
  9. Brakhage, A.A. Regulation of fungal secondary metabolism. Nat. Rev. Microbiol. 2013, 11, 21–32. [Google Scholar] [CrossRef] [PubMed]
  10. Frisvad, J.C. Media and growth conditions for induction of secondary metabolite production. Methods Mol. Biol. 2012, 944, 47–58. [Google Scholar]
  11. Yaya, S.; Kota, K.; Buh, A.; Bishwajit, G. Prevalence and predictors of taking tetanus toxoid vaccine in pregnancy: A cross-sectional study of 8,722 women in Sierra Leone. BMC Public Health 2020, 20, 1–9. [Google Scholar] [CrossRef]
  12. Dalhoff, A. Is the selective toxicity of antibacterial agents still a valid concept or do we miss chances and ignore risks? Infection 2021, 49, 29–56. [Google Scholar] [CrossRef]
  13. de Lima Procopio, R.E.; da Silvaa, I.R.; Martins, M.K.; de Azevedo, J.L.; de Araújo, J.M. Antibiotics produced by Streptomyces. Braz. J. Infect. Dis. 2012, 16, 466–471. [Google Scholar] [CrossRef] [Green Version]
  14. Demain, A.L.; Fang, A. The natural functions of secondary metabolites. Adv. Biochem. Eng./Biotechnol. 2000, 69, 1–39. [Google Scholar] [CrossRef]
  15. Fey, P.D.; Olson, M.E. Current concepts in biofilm formation of Staphylococcus epidermidis. Future Microbiol. 2010, 5, 917–933. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Tiwari, V.; Meena, K.; Tiwari, M. Differential anti-microbial secondary metabolites in different ESKAPE pathogens explain their adaptation in the hospital setup. Infect. Genet. Evol. 2018, 66, 57–65. [Google Scholar] [CrossRef] [PubMed]
  17. Cary, J.W.; Gilbert, M.K.; Lebar, M.D.; Majumdar, R.; Calvo, A.M. Aspergillus flavus secondary metabolites: More than just aflatoxins. Food Safety 2018, 6, 7–32. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Hrouzek, P.; Tomek, P.; Lukešová, A.; Urban, J.; Voloshko, L.; Pushparaj, B.; Ventura, S.; Lukavský, J.; Stys, D.; Kopecký, J. Cytotoxicity and secondary metabolites production in terrestrial Nostoc strains, originating from different climatic/geographic regions and habitats: Is their cytotoxicity environmentally dependent? Environ. Toxicol. 2011, 26, 345–358. [Google Scholar] [CrossRef] [PubMed]
  19. Zeng, X.; Cai, H.; Yang, J.; Qiu, H.; Cheng, Y.; Liu, M. Pharmacokinetics and cardiotoxicity of doxorubicin and its secondary alcohol metabolite in rats. Biomed. Pharmacother. 2019, 116, 108964. Available online: https://www.sciencedirect.com/science/article/pii/S0753332219300204 (accessed on 1 December 2021). [CrossRef]
  20. Lemke, T.L.; Williams, D.A. (Eds.) Foye’s Principles of Medicinal Chemistry; Lippincott Williams & Wilkins: Philadelphia, PA, USA, 2013; Available online: https://creighton.pure.elsevier.com/en/publications/foyes-principles-of-medicinal-chemistry-seventh-edition (accessed on 15 July 2020).
  21. Bacskay, I.; Nemes, D.; Fenyvesi, F.; Varadi, J.; Vasvári, G.; Feher, P.; Vecsernyes, M.; Ujhelyi, Z. Role of cytotoxicity experiments in pharmaceutical development. In Cytotoxicity; IntechOpen: Rijeka, Croatia, 2017; Available online: https://https://www.intechopen.com/chapters/58235 (accessed on 12 November 2021). [CrossRef] [Green Version]
  22. Kocherova, I.; Kempisty, B.; Hutchings, G.; Moncrieff, L.; Dompe, C.; Janowicz, K.; Petitte, J.; Shibli, J.A.; Mozdziak, P. Cell-based approaches in drug development—A concise review. Med. J. Cell Biol. 2020, 8, 44–49. [Google Scholar] [CrossRef]
  23. Jethva, K.; Bhatt Dhara Zaveri, M. In-vitro cytotoxicity activity of some selected ethnomedicinal plants against Vero cell line. Int. J. Pharm. Sci. Rev. Res. 2016, 37, 130–133. [Google Scholar]
  24. Freire, P.F.; Peropadre, A.; Pérez, J.M.; Herrero, M.O.; Hazen, M.J. An integrated cellular model to evaluate cytotoxic effects in mammalian cell lines. Toxicol. Vitr. 2009, 23, 1553–1558. [Google Scholar] [CrossRef] [PubMed]
  25. Torralba, D.; Baixauli, F.; Sánchez-Madrid, F. Mitochondria know no boundaries: Mechanisms and functions of intercellular mitochondrial transfer. Front. Cell Dev. Biol. 2016, 4, 1–11. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Evans, J.; Hannoodee, M.; Wittler, M. Amoxicillin Clavulanate. Available online: https://www.ncbi.nlm.nih.gov/books/NBK538164/ (accessed on 12 July 2020).
  27. Al-Zoubi, M.S.; Al-Tayyar, I.A.; Hussein, E.; Jabali, A.A.; Khudairat, S. Antimicrobial susceptibility pattern of Staphylococcus aureus isolated from clinical specimens in northern area of Jordan. Iran. J. Microbiol. 2015, 7, 265–272. [Google Scholar]
  28. Katzung, B.; Masters, S.; Trevor, A. Basic and Clinical Pharmacology; McGraw-Hill: New York, NY, USA, 2012; pp. 797–801. Available online: https://www.academia.edu/35509985/Basic_and_Clinical_Pharmacology_Katzung_Masters_and_Trevor_.pdf (accessed on 15 July 2020).
  29. Lowe, R.A.; Barber, K.E.; Wagner, J.L.; Bell-Harlan, A.M.; Stover, K.R. Ceftriaxone for the treatment of methicillin-susceptible Staphylococcus aureus bacteremia: A case series. J. Pharmacol. Pharmacother. 2017, 8, 140–144. [Google Scholar]
  30. Dilnessa, T. Antimicrobial Susceptibility Pattern of Staphylococcus aureus. 2019. Available online: https://www.intechopen.com/books/-i-staphylococcus-aureus-i-/antimicrobial-susceptibility-pattern-of-staphylococcus-aureus (accessed on 21 July 2020).
  31. Meers, P.D.; Whyt, W.; Sandys, G. Coagulase-negative staphylococci and micrococci in urinary tract infections. J. Clin. Pathol. 1975, 28, 270–273. [Google Scholar] [CrossRef] [Green Version]
  32. Filipiak, W.; Sponring, A.; Baur MMFilipiak, A.; Ager, C.; Wiesenhofer, H.; Nagl, M.; Troppmair, J.; Amann, A. Molecular analysis of volatile metabolites released specifically by Staphylococcus aureus and Pseudomonas aeruginosa. BMC Microbiol. 2012, 12, 113. [Google Scholar] [CrossRef] [Green Version]
  33. Fitzgerald, S.; Dufy, E.; Holland, L.; Morrin, A. Multi-strain volatile profiling of pathogenic and commensal cutaneous bacteria. Sci. Rep. 2020, 10, 17971. [Google Scholar] [CrossRef]
  34. Nkadimeng, S.M.; Nabatanzi, A.; Steinmann, C.M.L.; Eloff, J.N. Phytochemical, cytotoxicity, antioxidant and anti-inflammatory effects of Psilocybe Natalensis magic mushroom. Plants 2020, 9, 1127. [Google Scholar] [CrossRef]
  35. Ntungwe, E.; Domínguez-Martín, E.M.; Teodósio, C.; Teixidó-Trujillo, S.; Armas Capote, N.; Saraiva, L.; Díaz-Lanza, A.M.; Duarte, N.; Rijo, P. Preliminary biological activity screening of Plectranthus spp. extracts for the search of anticancer lead molecules. Pharmaceuticals 2021, 14, 402. [Google Scholar] [CrossRef]
  36. Nemudzivhadi, V.; Masoko, P. In vitro assessment of cytotoxicity, antioxidant, and anti-inflammatory activities of Ricinus communis (Euphorbiaceae) leaf extracts. Evid.-Based Complementary Altern. Med. eCAM 2014, 2014, 625961. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Abdel-Shafy, H.I.; Mansour, M.S.M. A review on polycyclic aromatic hydrocarbons: Source, environmental impact, effect on human health and remediation. Egypt. J. Pet. 2016, 25, 107–123. [Google Scholar] [CrossRef] [Green Version]
  38. Mojiri, A.; Zhou, J.L.; Ohashi, A.; Ozaki, N.; Kindaichi, T. A comprehensive review of polycyclic aromatic hydrocarbons in water sources, their effects, and treatments. Sci. Total Environ. 2019, 696. [Google Scholar] [CrossRef] [PubMed]
  39. Duedahl-Olesen, L.; Navaratnam, M.A.; Jewula, J.; Jensen, A. PAH in some brands of tea and coffee. Polycycl. Aromat. Compd. 2015, 35, 74–90. [Google Scholar] [CrossRef]
  40. Patel, A.B.; Shaikh, S.; Jain, K.R.; Desai, C.; Madamwar, D. Polycyclic aromatic hydrocarbons: Sources, toxicity, and remediation approaches. Front. Microbiol. 2020, 11, 562813. [Google Scholar] [CrossRef]
  41. Harris, K.L.; Banks, L.D.; Mantey, J.A.; Huderson, A.C.; Ramesh, A. Bioaccessibility of polycyclic aromatic hydrocarbons: Relevance to toxicity and carcinogenesis. Expert Opin. Drug Metab. Toxicol. 2013, 9, 1465–1480. [Google Scholar] [CrossRef] [Green Version]
  42. van Meteren, N. Extracellular Vesicles Released by Polycyclic Aromatic Hydrocarbons-Treated Hepatocytes Trigger Oxidative Stress in Recipient Hepatocytes by Delivering Iron. 2020. Available online: https://www.sciencedirect.com/science/article/am/pii/S0891584920311862 (accessed on 10 March 2022).
  43. Rodger, K.; Mc-Lellan, I.; Peshkur, T. Can the legacy of industrial pollution influence antimicrobial resistance in Estuarine sediments? Environ. Chem. Lett. 2019, 17, 595–607. [Google Scholar] [CrossRef] [Green Version]
  44. Nghiem, N.P.; Kleff, S.; Schwegmann, S. Succinic acid technology development and commercialization. Fermentation 2017, 3, 26. [Google Scholar] [CrossRef]
  45. Murphy, M.P.; O’Neill, L.A.J. Krebs cycle reimagined: The emerging roles of succinate and itaconate as signal transducers. Cell 2018, 174, 780–784. [Google Scholar] [CrossRef] [Green Version]
  46. Tretter, L.; Patocs, A.; Chinopoulos, C. Succinate is an intermediate in metabolism, signal transduction, ROS, hypoxia, and tumorigenesis. Biochim. Biophys. Acta (BBA) Bioenerg. 2016, 1857, 1086–1101. [Google Scholar] [CrossRef]
  47. Davoodbasha, M.; Edachery, B.; Nooruddin, T.; Lee, S.Y.; Kim, J.W. Evidence of C16 fatty acid methyl esters extracted from microalga for the effective antimicrobial and antioxidant properties. Microbial. Pathog. 2018, 115, 233–238. [Google Scholar] [CrossRef] [PubMed]
  48. Kumar, N.S.; Pradeep, T.; Jani, G.; Silpa, D.; Kumar, B.V. Design, synthesis, and antimicrobial screening of novel pyridyl-2-amidrazone incorporated isatin mannich bases. J. Adv. Pharm. Technol. Res. 2012, 3, 57–61. [Google Scholar] [PubMed]
  49. Kumar, R.; Chandar, B.; Parani, M. Use of succinic & oxalic acid in reducing the dosage of colistin against New Delhi metallo-β-lactamase-1 bacteria. Indian J. Med. Res. 2018, 147, 97–101. [Google Scholar]
  50. Gowrishankar, S.; Poornima, B.; Pandian, S.K. Inhibitory efficacy of cyclo(L-leucyl-L-prolyl) from mangrove rhizosphere bacterium-Bacillus amyloliquefaciens (MMS-50) toward cariogenic properties of Streptococcus mutants. Res. Microbiol. 2014, 165, 278–289. [Google Scholar] [CrossRef] [PubMed]
  51. Abd El-Hameed, R.H.; Sayed, A.I.; Mahmoud Ali, S.; Mosa, M.A.; Khoder, Z.M.; Fatahala, S.S. Synthesis of novel pyrroles and fused pyrroles as antifungal and antibacterial agents. J. Enzym. Inhib. Med. Chem. 2021, 36, 2183–2198. [Google Scholar] [CrossRef]
  52. Tanvir, R.; Javeed, R.; Rehman, Y. Fatty acids and their amide derivatives from endophytes: New therapeutic possibilities from a hidden source. FEMS Microbiol. Lett. 2018, 365, fny114. [Google Scholar] [CrossRef] [PubMed]
  53. Yin, L.; Xia, Y.; Xu, P.; Zheng, W.; Gao, Y.; Xie, F.; Ji, Z. Veratramine suppresses human hepG2 liver cancer cell growth in-vitro and in-vivo by inducing autophagic cell death. Oncol. Rep. 2020, 44, 477–486. [Google Scholar] [CrossRef]
  54. Bai, F.; Liu, K.; Li, H.; Wang, J.; Zhu, J.; Hao, P.; Zhu, L.; Zhang, S.; Shan, L.; Ma, W. Veratramine modulates AP-1-dependent gene transcription by directly binding to programmable DNA. Nucleic. Acids Res. 2018, 46, 546–557. [Google Scholar] [CrossRef] [Green Version]
  55. Szkudlarek, M.; Heine, E.; Keul, H.; Beginn, U.; Möller, M. Synthesis, characterization, and antimicrobial properties of peptides mimicking copolymers of maleic anhydride and 4-methyl-1-pentene. Int. J. Mol. Sci. 2018, 19, 2617. [Google Scholar] [CrossRef] [Green Version]
  56. Krishna, S.H.; Cao, J.; Tamura, T.; Nakagawa, Y.; De Bruyn, M.; Jacobson, G.S.; Weckhuysen, B.M.; Dumesic, J.A.; Tomishige, K.; Huber, G.W. Synthesis of hexane-tetrols and -triols with fixed hydroxyl group positions and stereochemistry from methyl glycosides over supported metal catalysts. Am. Chem. Soc. 2020, 8, 800–805. [Google Scholar] [CrossRef]
  57. Magro, G.; Biffani, S.; Minozzi, G.; Ehricht, R.; Monecke, S.; Luini, M.; Piccinini, R. Virulence genes of S. aureus from dairy cow mastitis and contagiousness risk. Toxins 2017, 9, 195. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Petzer, I.M.; Karzis, J.; Donkin, E.F.; Webb, E.C.; Etter, E.M.C. Somatic cell count thresholds in composite and quarter milk samples as indicator of bovine intramammary infection status. Onderstepoort J. Vet. Res. 2017, 84, 1–10. [Google Scholar] [CrossRef] [Green Version]
  59. Zigo, F.; Vasil, M.; Ondrasovicova, S.; Vyrostkova, J.; Bujok, J.; Pecka-Kielb, E. Maintaining optimal mammary gland health and prevention of mastitis. Front. Vet. Sci. 2021, 8, 1–17. [Google Scholar] [CrossRef]
  60. Davis, J.; Farrah, S.; Wilkie, A. Selective growth of Staphylococcus aureus from flushed dairy manure wastewater using acriflavine-supplemented mannitol salt agar. Lett. Appl. Microbiol. 2006, 42, 606–611. [Google Scholar] [CrossRef] [PubMed]
  61. Rao, J.G.; Qamruddin, A.O.; Hassan, I.A.; Burnie, J.P.; Ganner, M. Cluster of clinical isolates of epidemic methicillin-resistant Staphylococcus aureus (EMRSA) with a negative deoxyribonuclease (DNase) test-implications for laboratory diagnosis and infection control. J. Hosp. Infect. 2002, 51, 238–239. [Google Scholar] [CrossRef] [PubMed]
  62. McAdow, M.; Missiakas, D.M.; Schneewind, O. Staphylococcus aureus secretes coagulase and von Willebrand factor binding protein to modify the coagulation cascade and establish host infections. J. Innate Immun. 2012, 4, 141–148. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Bayot, M.L.; Bragg, B.N. Antimicrobial Susceptibility Testing. 2020. Available online: https://pubmed.ncbi.nlm.nih.gov/30969536/ (accessed on 12 September 2021).
  64. Eduardo, L.G.; Ramirez, B.S.; Maribel, C.F.; Pescador, M.G.N.; Cruz, F.J.M. Low accuracy of the McFarland method for estimation of bacterial populations. Afr. J. Microbiol. Res. 2018, 12, 736–740. [Google Scholar]
  65. Szeto, W.; Yam, W.C.; Huang, H.; Leung, D.Y.C. The efficacy of vacuum-ultraviolet light disinfection of some common environmental pathogens. BMC Infect. Dis. 2020, 20, 127. [Google Scholar] [CrossRef] [Green Version]
  66. Gigliobianco, T.; Lakaye, B.; Wins, P.; El Moualij, B.; Zorzi, W.; Bettendorff, L. Adenosine thiamine triphosphate accumulates in Escherichia coli cells in response to specific conditions of metabolic stress. BMC Microbiol. 2010, 10, 148. [Google Scholar] [CrossRef] [Green Version]
  67. Balachandran, C.; Duraipandiyan, V.; Ignacimuthu, S. Cytotoxic (A549) and antimicrobial effects of Methylobacterium sp. isolate (ERI-135) from Nilgiris forest soil, India. Asian Pac. J. Trop. Biomed. 2012, 2, 712–716. [Google Scholar] [CrossRef] [Green Version]
  68. Adebo, O.A.; Kayitesi, E.; Tugizimana, F.; Njobeh, P.B. Differential metabolic signatures in naturally and lactic acid bacteria (LAB) fermented ting (a Southern African food) with different tannin content, as revealed by gas chromatography-mass spectrometry (GC–MS)-based metabolomics. Food Res. Int. 2019, 121, 326–335. [Google Scholar] [CrossRef] [PubMed]
  69. Coskun, O. Separation techniques: Chromatography. Northern Clin. Istanbul. 2016, 3, 156–160. [Google Scholar] [CrossRef] [Green Version]
  70. Zia, K.; Siddiqui, T.; Ali, S.; Farooq, I.; Zafar, M.S.; Khurshid, Z. Nuclear Magnetic Resonance Spectroscopy for Medical and Dental Applications: A comprehensive review. Eur. J. Dent. 2019, 13, 124–128. [Google Scholar] [CrossRef] [Green Version]
  71. Mwinga, J.L.; Asong, J.A.; Van Staden, J.; Nkadimeng, S.M.; McGaw, L.J.; Aremu, A.O.; Mbeng, W.O. In vitro antimicrobial effects of Hypoxis hemerocallidea against six pathogens with dermatological relevance and its phytochemical characterization and cytotoxicity evaluation. J. Ethnopharmacol. 2019, 242, 112048. [Google Scholar] [CrossRef]
  72. Mossman, T. Rapid colorimetric assay for cellular growth and survival: Application to proliferation and cytotoxicity assays. J. Immunol. Methods 1983, 65, 55–63. [Google Scholar] [CrossRef]
  73. Benov, L. Effect of growth media on the MTT colorimetric assay in bacteria. PLoS ONE 2019, 14, e0219713. [Google Scholar] [CrossRef]
Toxins 14 00712 g001 550
Figure 1. Prominent metabolites yielded by Staphylococci.
Figure 1. Prominent metabolites yielded by Staphylococci.
Toxins 14 00712 g001
Table
Table 1. Laboratory tests.
Table 1. Laboratory tests.
Bacterial StrainGrowth on MSA PlateGrowth on DNAse PlateDNAse Production (Clearing Zone of Clearing)Coagulase
Production
S. aureusyellow colonies+++
S. epidermidispink colonies+−−
S. saprophyticuspink colonies+−−
+ = positive, − = negative.
Table
Table 2. Antibiotic sensitivity results.
Table 2. Antibiotic sensitivity results.
Bacterial StrainAntibiotic ConcentrationRes.Int.Sus.Zone-Size (mm)/Results
S. aureus
(Isolated from milk)		Augmentin (30 µg)≤1314–17≥1825 = S
Ceftriaxone (30 µg)≤1314–20≥2120 = S
Oxacillin (5 µg)≤1213–20≥2122 = S
Vancomycin (30 µg)≤1010–11≥1220 = S
Cotrimoxazole (25 µg)≤1011–15≥1620 = S
S. epidermidisAugmentin (30 µg)≤1314–17≥1825 = S
Ceftriaxone (30 µg)≤1314–20≥2120 = S
Oxacillin (5 µg)≤1213–20≥2111 = R
Vancomycin (30 µg)≤1010–11≥128 = R
Cotrimoxazole (25 µg≤1011–15≥1620 = S
S. saprophyticusAugmentin (30 µg)≤1314–17≥1825 = S
Ceftriaxone (30 µg)≤1314–20≥2120 = S
Oxacillin (5 µg)≤1213–20≥2122 = S
Vancomycin (30 µg)≤1010–11≥1220 = S
Cotrimoxazole (25 µg)≤1011–15≥1620 = S
Sus. = susceptible, Res. = resistant, Int. = intermediate.
Table
Table 3. Secondary metabolites yielded by S. aureus (isolated from milk).
Table 3. Secondary metabolites yielded by S. aureus (isolated from milk).
Metabolites ClassRT (min)Observed Iron m/zm/zMetabolite NameMolecular
Formula		Peak Ave
Acids05:45269.0349111.0680;
131.1293		5-(2,6-dichlorophenyl)thiophene-2-carboxylic acidC11H6Cl2O2S532,778
08:03219.1047109.0762;
70.0409		(2-bromo-4-nitrophenyl)acetic acidC10H7F3O2584,679
25:44324.166266.5316;
69.1228		Succinic acidC4H6O41,152,910
Alkaloids12:52219.137757.0700;
70.0778		9-Eicosene, (E)-C20H40243,785
17:03210,1256124,0631;
180,0893		221U 5,6,8-IndolizidineC15H27N2,313,600
Alkenes23:09265.170755.0545;
57.0701		1-NonacoseneC29H58779,656
Amides17:50157.142059.0367;
72.0444		PelargonamideC9H19NO2,852,295
19:38264.194759.0367;
72.0444		OleamideC18H35NO5,474,773
03:57101.120144.0497;
43.0179		Methyl isopentyl amineC6H15N1,176,352
Amines04:40260.272584.0808;
31.0181		Cholestan-3-amine, N,N,4,4-tetramethyl-, (3ß,5a)-C31H57N4,216,599
18:08182.0842182.0838;
310181		1-amino-4-azafluoreneC12H10N2424,629
18:28227,221059.0367;
72.0445		2-FluoroisoproterenolC11H16FNO3440,174
05:2885.041285.0522;
43.0180		(Difluorophosphino)amine; AminodifluorophosphineF2H2NP8,467,743
11:47163.0993104.0621;
191.1430		Acetamide, N-phenethyl-C10H13NO7,464,331
21:23268.193367.1005;
77.0230		Flexzone 7LC18H24N2175,865
Amino Acids15:45154,073783,0729;
111,0678		Cyclo-prolylglycineC7H10N2O224,522,536
16:24210,136070.0652;
72.0808		Cyclo(leucyloprolyl)C11H18N2O275,187,945
Azoles/Thiazoles23:02315.113639.0832;
76.0183		Tinuvin 326C17H18ClN3O235,435
Azoles/Heterocyclic Compounds12:55157.0888128,0622;
156,0811		3-Me-4-Ph-pyrroleC11H11N620,446
Biphenyl Compounds12:57169.088972.0808;
169.0887		4-BiphenylamineC12H11N282,773
Dicarboxylic Acids07:14100.022256.0259;
82.0651		SuccinyloxideC4H4O33,109,952
Ergot Amines/Ergot Alkaloids21:47273.9903125.0708;
70.0652		DihydroergotamineC33H37N5O531,862,103
Esters20:13256.1935165,1026;
235,1317		Methyl 2,2’,4-tri-O-methylanziateC28H38O7765,489
22:18329.034666.5315;
79.0293		 C24H28BrNO41,654,714
09:38344.014870.1217;
72.9902		3-Methylbutyl N-heptafluorobutyryltryptophanateC20H21F7N2O3506,683
11:53194.0939121,0286;
149,0601		Ethyl 4-ethoxybenzoateC11H14O3260,016
Fatty Acid Esters17:11228.204674,0363;
87,0442		Methyl tridecanoateC14H28O2586,047
Fatty acids21:38255.250959.0367;
72.0444		Palmitic amideC16H33NO2,419,744
Fatty Acids/Palmitic Acids18:13258,250343.0545;
102.0676		Hexadecanoic acid, isopropyl esterC19H38O2357,808
Fatty Amides18:33171.162159.0367;
72.0445		CapramideC10H21NO435,229
19:49199.189559.0366;
72.0444		LauramideC12H25NO15,918,923
Fluorenes/Aromatic Hydrocarbons19:24202.0777100.0306;
202.0777		FluoranthreneC16H10106,095
Furans15:40128.058044.0496;
128,0580		Methyl 5-methylfuryl sulfideC6H8OS3,347,846
Heterocyclic compounds08:18117.057490.0465;
117.0574		KetoleC8H7N3,834,426
08:25267.999584.0808;
105.0700		PyridrolC18H21NO25,271,632
10:54155,0730155.0730;
127.0543		3-PhenyIpyridineC11H9N1,187,944
12:40219.038570.0652;
97.0888		AprobarbitalC10H14N2O314,490,692
19:40254.201189.0391;
171.0919		FenoharmanC18H18N2588,461
Pyridones23:51227.144967.0102;
75.5266		1-(2-Acetyl-3-methylphenyl)-2(1H)-pyridinonC14H13NO2503,418
Hydroxytryptophan/Hydroxy Amino Acid11:50219.1475146.0967;
130.9917		4-Hydroxy-DL-tryptophanC11H12N2O3143,938
Nitriles19:00139.0868139.0868;
198.1152		3,5-difluoro-benzonitrileC7H3F2N191,900
Organosilicon compounds13:58418.034973.0468;
73.0468		HexadecamethylcyclooctasiloxaneC16H48O8Si8658,716
13:53244.0919137.0420;
167.0525		DiphenyldimethoxysilaneC14H16O2Si957,364
11:15505.106373.0468;
147.0657		CTK6B0391C18H52O7Si71,255,677
Phenols23:41209,1376190.0977;
135.0554		CinnamolaurineC18H19NO3581,769
18:51225.089993.0574;
225.0896		2-(benzotriazol-2-yl)-5-methylphenolC13H11N3O299,376
Phenols/Organic Hydroxy Compound12:36206.1665191.1430;
163.1119		Phenol, 2,5-di-tert-butyl-C14H22O148,266
Thiazole06:50140.1421125.0836;
91.0254		4-(Trimethylsilyl)pyrazoleC6H12N2Si3,059,569
13:15181.001468.6765;
108.0031		Benzothiazole, 2-(methylthio)C8H7NS270,845
07:20135.013869.1227;
72.0686		benzisothiazoleC7H5NS164,406
Unsaturated Aliphatic hydrocarbons17:53282.052357.0700;
69.0699		(5E)-5-IcoseneC20H401,126,073
Table
Table 4. Secondary metabolites yielded by S. epidermidis (ATCC 51625).
Table 4. Secondary metabolites yielded by S. epidermidis (ATCC 51625).
Metabolites ClassRT (min)Observed Ion m/zm/zMetabolite NameMolecular
Formula		Peak Areas Average
Acids07:05215.086070.0414;
99.0680		Beta-ureidopropionic acidC4H8N2O328,087
07:11359.0380204.1133;
289.1786		propanoic acidC₃H₆O₂36,531
08:03226.1468211.1231;
226.1468		DTXSID40154910C16H18O1,352,933
25:44344.069985.0397;
114.0423		CTK9A2446C31H44N4O51,360,725
28:47268.0383104.0622;
68.5348		Cannabinolic acidC22H26O43539
Alcohol04:05309.348257.0700;
125.1325		HenicosanolC21H44O615,961
Aldehyde05:53178.110169.0574;
178.1101		Benzothiazole, 2-amino-5,6-dimethyl-C9H10N2S132,889
06:28167.135345.0576;
87.0680		3-Cyclopentylpropionamide, N,N-dimethyl-C10H19NO411,894
08:01140.0580111.0554;
140.0580		Benzaldehyde, 4-benzyloxy-3-methoxy-2-nitro-C15H13NO5689,665
04:19109.0615109,0887;
43.0887		propan-2-one,C6H14O6,431,210
Alkaloids30:34324.1647204.1126;
323.161		QuinineC20H24N2O210,651
Alkene07:15270.047655.0544;
83.0855		(E)-5-OctadeceneC18H36381,486
11:00405.081857,0699;
97.1013		NonacoseneC29H58164,163
Alkyl-phenylketones09:24150.0676107.0493;
135.0442		1-acetyl-2-hydroxy-5-methylbenzeneC9H10O2447,852
Amide07:53147.118059.0367;
126.0312		N-(6-Chloro-2-pyrazinyl)-2-(1-piperidinyl)acetamideC11H15ClN4O264,451
Amines03:15224.829868.0258;
1120714		CyclopentanoneoximeC5H9NO292,727
03:23169.0877141.0699;
169.0886		4-phenylanilineC6H5-C6H4NH216,716
03:45420.0086204,1133;
275,1631		Ethyl (1S)-1-phenyl-3,4-dihydro-1H-isoquinoline-2-carboxylateC18H19NO2453,344
04:50181.0014148,0217;
181,0014		dimethyl ketoneCH3COCH31,018,170
06:44208.085470.0652;
97.0889		2-Ethyl(dimethyl)silyloxybutaneC8H20OSi48,784
06:50157.0885128.0620;
156.0808		3-methyl-4-phenylpyrroleC11H11N45,870
07:01287.9991130.0652;
166.0739		3-Methylbutyl N-heptafluorobutyryltryptophanateC12H24O2712,718
08:40284.048584,0807;
31,0184		N,N,4,4-Tetramethylcholestan-3-amineC31H57N79,967
29:13136.0994108.0684;
135.0917		2,6-DiethylpyrazineC8H12N27879
11:02277.213985.0523;
177.0658		Stearamide mea,C20H41NO2295,552
Amino acids10:03223.664099.0512;
125.0710		Phenylalanine, methyl esterC10H13NO22,534,272
09:34257.1639154.0652;
171.0918		5-Hydroxy-L-tryptophanC11H12N2O317,277,429
Anticholinergic agent07:56176.997186.0386;
99.0679		BenactizinaC20H25NO328,780
Aromatic hydrocarbons10:19268.9954121.0648;
149.0961		4,4’-(1,2-Diethylethylene)bis(anisole)C20H26O2113,270
Azole05:48241.133983.0730;
193.0844		4-Methoxy-6-methyl-1,3,5-triazin-2-amineC5H8N4O98,612
Benzene10:24117.057490.0465;
117.0574		1H-indoleC8H7N15,162,269
Benzene/amines29:23155.0729127.0542; 155.07729N-(4-methylphenyl)pyridin-3-amineC25H21N9681
Beta carbolines07:27168.0685140.0498;
184.1125		CarbazolineC11H8N242,951
Carboxamides07:46287.985959.0368;
83.0855		OleamideC18H35NO33,866
03:13219.2235152.1435;
31.0185		3-Ethyl-5-methyl-2,4-heptadieneC10H18673,311
03:29347.0880135.0804;
156.0808		Propanone,C3H6O18,547
Cytochrome30:56281.164185.1013;
149.0231		Tetrahydropyran Z-10-dodecenoateC17H30O318,827
Esters09:14389,0513125.0709;
153.0658		Epoxypropanol methacrylateC7H10O322,299
27:59347.3253135.0903;
1490958		Phthalic acid, di(8-chlorooctyl) esterC24H36Cl2O410,848
Ether09:22136.012845.0336;
59.0492		Carbitol,C6H14O3234,708
Fatty acids06:14181.034671,0855,;
98.0966		Undec-2-en-4-olC11H22O129,187
10:16270.254874.0362;
143.1068		Palmitic acid methyl esterC17H34O212,371,227
Halogenated pyrroles.08:32268.017444.133;
59.0367		PhantomC15H11BrClF3N2O1,251,965
Heterocyclic compound07:15221.1369124.0633;
180.0894		2,3-DihydrothiopheneC4H6S392,746
29:51211.144470.0652;
154,0740		L-Phe-D-Pro lactamC11H18N2O215,224
08:25315.113091.0544;
300.0896		2,6-Dimethyl-3-isopentylpyrazineC17H18ClN3O96,316
Ketone05:25246.135891,0543;
127,0864		Propanone,(CH3)2CO403,574
Organic acid06:31269.9949179,0688;
263,9868		Cypionic acidC20H22O2153,948
Organosilicon compounds30:17244.091691.0544;
167.0525		DimethoxydiphenylsilaneC14H16O2Si55,316
30:19211.1355168.0809;
211.1335		MethyloctyldimethoxysilaneC10H16OSi2,187,251
Phenols05:24206.166557.0700;
191.1430		2,4-Di-tert-butylphenolC14H22O451,861
Polycyclic aromatic hydrocarbon09:37202.0774101.0393;
202.0774		Benzo(jk)FluorenC20H1244,281
29:19202.0777178.0976;
202.0777		Beta-PyreneC16H103558
Protein05:27219.160691.0543;
99,0555		Cyclo(Ala-Phe)C12H14N2O29,331,496
Pyridines05:45231.103875.0234;
231.1038		2,6-DPhPyC17H13N304,326
07:33182.0840154.0654;
182.0840		brevicollineC12H10N243,227
Pyrrolidine06:00180.943941.0387;
84.0444		PyrrolidonC4H7NO35,732
Pyrrolidinone06:01190.075441.0387;
84.0444		5-(Cyclohexylmethyl)-2-pyrrolidinoneC11H19NO50,942
Quinolines10:32227.9064154.0737Acetone anilC12H15N280,959
Unsaturated aliphatic hydrocarbons06:35252.280455.0545;
83.0855		3-eicoseneC20H40474,139
Table
Table 5. Secondary metabolites yielded by S. saprophyticus (ATCC 35552).
Table 5. Secondary metabolites yielded by S. saprophyticus (ATCC 35552).
Metabolites ClassRT (min)Observed Ion m/zm/zMetabolite NameMolecular FormulaPeak Areas Average
Acids25:44324.165144.0497;
74.0237		Succinic acidC4H6O4748,584
Acids/Esters09:33156.505941.0388;
84.0444		2-Pyrrolidinecarboxylic acid-5-oxo-, ethyl esterC11H14O330,578,538
Acids/Propionates19:00210.0846139.0865;
225.0758		Linalyl propionateC7H11NO3125,699
Adipates/Acids21:38299.273759.0367;
129.0547		Diethylhexyl adipateC13H22O21,358,675
Alkanes12:58225.467957.0700;
71.0855		CetaneC22H42O4234,536
Alcohols04:52174.047174.0237;
86.0964		Undec-2-en-4-olC16H341,854,763
14:06264.0909138.0789;
151.0867		2-(4-Fluoro-phenyl)-cyclohexanolC11H22O649,839
04:19136.014445.0337;
59.0493		ethyl carbitolC12H15FO1,2961,908
Alkaloids/Ergotamines21:47567.0431125.0711;
153.0660		ErgotamineC6H14O341,429,291
Alkaloids16:15401.980657.0212;
114.0424		VeratramineC33H37N5O54,429,604
Alkane21:34336.375357.0699;
97.1013		CyclotetracosaneC27H39NO24,929,019
Alkene19:50266.296657.0700;
83.0855		Nonadec-1-eneC24H487,761,975
09:24224.070355.0544;
83.0855		CeteneC19H38328,938
12:52264.164644.0497;
86.0964		Octadec-9-eneC16H321,546,382
Amides22:59364.408230.0343;
44.0497		Histidine amideC18H3616,30,440
21:27286.263159.0367;
72.0444		oleic acid amideC6H10N4O14,326,846
19:48255.25659.0367;
72.0444		Cetyl amideC18H35NO2,500,587
Amines13:13192.1621177.1388;
192.1612		2-Propanamine, N-[(3-nitrophenyl)methylene]-C16H33NO61,970
25:54393.3375250.1583;
322.2517		bis(4-t-octylphenyl)amineC11H14N2O2103,487
10:19227.068544.0497;
57.0211		N,N,4,4-Tetramethyl-5alpha-cholestan-3beta-amineC28H43N4,308,153
23:20264.279144.0806;
171.0916		PhenoharmaneC31H57N134,169
19:22238.216985.0523;
98.0602		N-lauroylethanolamineC18H18N2202,235
Aromatic Hydrocarbons18:52202.0776101.0395;
202.0775		Benzo(jk)fluoreneC14H29NO2160,110
Aromatic
Heterocyclic
organic
compound		08:17117.057490.0465;
117.0574		IndoleC16H105,054,596
09:37131.0729130.0652;
145.0762		SkatoleC8H7N412,362
Azoles/Pyrroles12:54157.0886128.0622;
156.0809		3-Me-4-Ph-pyrroleC9H9N1,455,835
17:08221.1279124.0632;
180.0895		2-undecyl-1H-pyrroleC11H11N2,640,782
Azoles/Triazoles23:01315.1132119.0856;
300.0898		Tinuvin 326C15H27N742,229
18:50225.089744.0496;
86.0964		Tinuvin PC17H18ClN3O817,086
Biphenyl Compounds12:10169.0888115.0544;
169.0888		4-BiphenylamineC13H11N3O130,219
Benzoate11:53194.0938211.0285;
149.0599		4-Ethoxy ethylbenzoateC12H11N315,670
Butyl Esters15:21219.0888104.0622;
135.0805		Butyl fumarateC12H20O4253,338
Esters12:00270.046174.0237;
86.0964		isohexyl esterC16H30O4118,061
Ethyl Ethers03:13125.071344.0496;
86.0964		Chloromethyl isobutyl etherC3H7ClO1,473,624
Fatty Acids17:11270.255230.0343;
74.0237		Methyl palmitateC17H34O2358,875
Heterocyclic Compounds/Pyridines10:54155.073127.0543;
155.0730		3-PhenyIpyridineC11H9N1,702,430
Hydrocarbons17:53280.312883.0856;
97.1014		3-eicoseneC20H404,116,824
Indole18:13168.0684140.0497;
168.0684		CarbazolineC11H8N21,824,128
Indole/Benzene18:06182.083930.0343;
74.0237		AzobenzeneC12H10N22,035,127
Ketones17:07225.1517140.0581;
196.1208		2-Methyl-4-amino-6-methoxy-s-triazineC5H8N4O586,977
Nitriles10:36154.0527127.0418;
154.0527		IsoquinaldonitrileC10H6N2236,359
03:18108.068481.0574;
108.0684		1,6-Dihydroimidazole[4,5-d]imadazole/DiaminomaleonitrileC8H7N1,245,557
Olefin/Alkenes23:09343.06657.0701;
97.1012		NonacoseneC29H582,784,072
Organosilicon Compunds11:15506.106473.0468;
147.0657		CTK6B0391C18H52O7Si71,529,176
13:58490.058673.0468;
355.0699		Hexadecamethyl-cyclooctasioxaneC16H48O8Si8661,927
Phenols11:45206.166657.0700;
191.1431		2,4-Di-tert-butylphenolC14H22O1,293,238
Pyrenes19:24202.077788.0308;
202.0777		ß-PyreneC16H10143,873
Pyridines20:27231.103774.0236;
86.0964		Pyridine, 2,6-diphenyl-C17H13N436,201
Pyrroles04:58109.088794.0653;
109.0887		2,3,4-TrimethylpyrroleC7H11N3,128,380
04:25269.049159.0367;
151.0898		PylonC15H11BrClF3N2O1,066,266
13:42157.088777.5362;
156.0810		2-Methyl-5-phenylpyrroleC11H11N230,614
Quinazolines/heterocyclic compounds08:56144.068398.0602;
144.0683		4-MethylquinazolineC9H8N2215,987
Sulphides/sulphur compounds03:59125.9626110.9393;
125.9626		DimethyltrisulfaneC2H6S31,926,298
Thiophenes13:09169.053109.0762,
137.0710		benzothiophene sulfoneC12H8O2S330,702
Table
Table 6. The Kruskal Wallis test results.
Table 6. The Kruskal Wallis test results.
Test Statistics a,b
%Peaks Area Average
Kruskal-Wallis H1.854
df2
Asymp. Sig.0.396
a Kruskal Wallis Test; b Grouping Variable: Metabolites Class.
Table
Table 7. Lethal concentration (LC50) of secondary metabolites extracted from S. aureus, S. epidermidis, and S. saprophyticus.
Table 7. Lethal concentration (LC50) of secondary metabolites extracted from S. aureus, S. epidermidis, and S. saprophyticus.
CompoundOriginLethal Concentration (LC50) in mg/mL)
(1) 4-Methyl-pentyl amineS. saprophyticus (ATCC 35552)0.0231 ± 0.0027
(2) FluorantheneS. aureus (isolated from milk0.0167 ± 0.0003
(3) Cyclo (leucyl-prolylS. aureus (isolated from milk)0.0310 ± 0.0012
(4) OleamideS.epiderdis (ATCC 51625)0.0333 ± 0.0012
(5) VeratramineS. saprophyticus (ATCC 35552)0.0274 ± 0.0007
(6) Methyl palmitateS. epidermidis (ATCC 51625)0.0441 ± 0.0040
(7) 3-methyl-2-phenyl-1H-pyrroleS. aureus (isolated from milk0.0341 ± 0.0093
(8)1,2,6-HexanetriolS. saprophyticus (ATCC 35552)0.0333 ± 0.0031
(9) Succinic acidS. saprophyticus (ATCC 35552)0.0334 ± 0.0017
Doxorubicin 0.0101 ± 0.0004
Table
Table 8. ANOVA table indicating the relation between the % viability of Vero cell and the concentration of the sample.
Table 8. ANOVA table indicating the relation between the % viability of Vero cell and the concentration of the sample.
ANOVA a
ModelSum of SquaresdfMean SquareFSig.
1Regression2173.09812173.098136.7070.000 b
Residual826.5945215.896
Total2999.69353
a Dependent Variable: Percent Viability; b Predictors: (Constant), Concentration.
Table
Table 9. A summary for evaluating the method used in data analysis.
Table 9. A summary for evaluating the method used in data analysis.
Model Summary b
ModelRR SquareAdjusted R SquareStd. Error of the Estimate
10.851 a0.7240.7193.98698469
a Predictors: (Constant), Concentration; b Dependent Variable: Percent Viability.
Table
Table 10. Bacterial strains used for the experimental work.
Table 10. Bacterial strains used for the experimental work.
Bacterial StrainSource/or Supplier of Bacterial StrainStrain ATCC
Staphylococcus aureusCow milk, MSA agar confirmedIsolated from milk
Staphylococcus epidermidisThermofisher Scientific, South AfricaATCC 51625
Staphylococcus saprophyticusThermofisher Scientific, South AfricaATCC 35552
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Modimola, M.S.; Green, E.; Njobeh, P.; Senabe, J.; Fouche, G.; McGaw, L.; Nkadimeng, S.M.; Mathiba, K.; Mthombeni, J. Investigating the Toxicity of Compounds Yielded by Staphylococci on Vero Cells. Toxins 2022, 14, 712. https://doi.org/10.3390/toxins14100712

AMA Style

Modimola MS, Green E, Njobeh P, Senabe J, Fouche G, McGaw L, Nkadimeng SM, Mathiba K, Mthombeni J. Investigating the Toxicity of Compounds Yielded by Staphylococci on Vero Cells. Toxins. 2022; 14(10):712. https://doi.org/10.3390/toxins14100712

Chicago/Turabian Style

Modimola, Margaret Selina, Ezekiel Green, Patrick Njobeh, Jeremiah Senabe, Gerda Fouche, Lyndy McGaw, Sanah Malomile Nkadimeng, Kgama Mathiba, and Julian Mthombeni. 2022. "Investigating the Toxicity of Compounds Yielded by Staphylococci on Vero Cells" Toxins 14, no. 10: 712. https://doi.org/10.3390/toxins14100712

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