Genetic Diversity in <i>Staphylococcus aureus</i> and Its Relation to Biofilm Production

Awan, Furqan; Ali, Muhammad Muddassir; Mushtaq, Muhammad; Ijaz, Muhammad

doi:10.5772/intechopen.99967

Cited by 6 publications

(3 citation statements)

References 82 publications

(107 reference statements)

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“…Another interesting finding from this study was that strains belonging to S. aureus segregated to two separate clusters, indicating the within-species diversity. In the course of evolution, it undergoes both horizontal and vertical gene transfer events that have resulted in the genetically diversified bacterial population (Furqan Awan et al, 2021). Their diversity makes them resistant towards almost all the antimicrobial drugs used (Mlynarczyk-Bonikowska et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

A machine learning-based strategy to elucidate the identification of antibiotic resistance in bacteria

Parthasarathi,

Gaikwad,

Rajesh

et al. 2024

Front. Antibiot.

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Microorganisms, crucial for environmental equilibrium, could be destructive, resulting in detrimental pathophysiology to the human host. Moreover, with the emergence of antibiotic resistance (ABR), the microbial communities pose the century’s largest public health challenges in terms of effective treatment strategies. Furthermore, given the large diversity and number of known bacterial strains, describing treatment choices for infected patients using experimental methodologies is time-consuming. An alternative technique, gaining popularity as sequencing prices fall and technology advances, is to use bacterial genotype rather than phenotype to determine ABR. Complementing machine learning into clinical practice provides a data-driven platform for categorization and interpretation of bacterial datasets. In the present study, k-mers were generated from nucleotide sequences of pathogenic bacteria resistant to antibiotics. Subsequently, they were clustered into groups of bacteria sharing similar genomic features using the Affinity propagation algorithm with a Silhouette coefficient of 0.82. Thereafter, a prediction model based on Random Forest algorithm was developed to explore the prediction capability of the k-mers. It yielded an overall specificity of 0.99 and a sensitivity of 0.98. Additionally, the genes and ABR drivers related to the k-mers were identified to explore their biological relevance. Furthermore, a multilayer perceptron model with a hamming loss of 0.05 was built to classify the bacterial strains into resistant and non-resistant strains against various antibiotics. Segregating pathogenic bacteria based on genomic similarities could be a valuable approach for assessing the severity of diseases caused by new bacterial strains. Utilization of this strategy could aid in enhancing our understanding of ABR patterns, paving the way for more informed and effective treatment options.

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Section: Discussionmentioning

confidence: 99%

A machine learning-based strategy to elucidate the identification of antibiotic resistance in bacteria

Parthasarathi,

Gaikwad,

Rajesh

et al. 2024

Front. Antibiot.

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“…Staphylococcus aureus juga ditemukan mengkontaminasi sejumlah permukaan sarana kesehatan, termasuk kursi, AC, meja, keran, pusaran air, dan bangku kayu, serta barang-barang dalam ruangan, seperti telepon, remote TV, dan kartu ATM. Paparan Staphylococcus aureus menjadi faktor risiko kolonisasi bakteri ini pada sarana kesehatan dan memiliki kemungkinan meningkatnya resiko paparan ke petugas kesehatan atau penularan ke lingkungan (Awan et al, 2021;Cheung et al, 2021;Elisa et al, 2022).…”

Section: Pendahuluanunclassified

Pengembangan Protokol Deteksi Staphylococcus aureus Berbasis Molekuler

Koentjoro,

Alviani,

Jatmiko

et al. 2024

Bioscientist j. ilm. bosbiol.

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Staphylococcus aureus becomes a normal flora in humans, especially on the skin and in the nose. However, if it becomes excessive or if there are pathogenic variants, it can cause various health problems. The purpose of the study is to develop a molecular-based detection method for Staphylococcus aureus using the norA primer gene. The norA gene in Staphylococcus aureus is known to play a role in pathogenesis with its antibiotic resistance ability. This type of research is analytical observational with a cross-sectional method. The methods in the study include the isolation and identification of Staphylococcus aureus from healthcare facility equipment. Isolation and identification include bacterial isolation using Blood Agar Plate (BAP) media; isolate purification, Gram staining; biochemical tests using Mannitol Salt Agar (MSA) media, glucose tests, Voges Proskauer (VP) tests, catalase tests, and coagulase tests. Furthermore, S. aureus isolates were tested using a molecular-based method, namely Polymerase Chain Reaction (PCR). This method includes DNA isolation stages, qualitative testing with agarose gel electrophoresis, semi-quantitative testing with image J software, amplification with Real-Time Polymerase Chain Reaction (RT-PCR) using norA gene primers. The Mann-Whitney test results gave a value of p = 0.334 (p> 0.05) indicating the suitability between the culture method and the PCR method with the developed protocol in detecting Staphylococcus aureus. The developed method includes the use of base sequences in the norA gene primer, optimization of annealing and extension temperatures, and the concentration of DNA templates used.

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“…The former, which encodes genes present in all isolates, comprises approximately 75% of the 2.8 Mbp genome. The latter, which represents 25% of the total genome, is dominated by mobile genetic elements (MGEs), the main agents of horizontal gene transfer [ 79 ]. Many types of MGEs are found in bovine S. aureus .…”

Section: Advances In the Use Of Pfge In Epidemiologic Studies Of Bovi...mentioning

confidence: 99%

Pulsed-Field Gel Electrophoresis Analysis of Bovine Associated Staphylococcus aureus: A Review

Chadi¹,

Arcangioli

2023

Pathogens

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For decades now, DNA fingerprinting by means of pulsed-field gel electrophoresis (PFGE) continues to be the most widely used to separate large DNA molecules and distinguish between different strains in alternating pulses. This is done by isolating intact chromosomal DNA and using restriction enzymes with specific restriction sites to generate less than 30 restriction fragments from 50 Kb to 10 Mbp. These results make clone-specific band profiles easy to compare. Specialized equipment is required for the optimization of DNA separation and resolution, among which a contour-clamped homogeneous electric field (CHEF) apparatus is the most commonly used. As a result, the PFGE analysis of a bacterial genome provides useful information in terms of epidemiological investigations of different bacterial pathogens. For Staphylococcus aureus subtyping, despite its limitations and the emergence of alternative methods, PFGE analysis has proven to be an adequate choice and the gold standard for determining genetic relatedness, especially in outbreak detection and short-term surveillance in the veterinary field.

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Genetic Diversity in Staphylococcus aureus and Its Relation to Biofilm Production

Cited by 6 publications

References 82 publications

A machine learning-based strategy to elucidate the identification of antibiotic resistance in bacteria

A machine learning-based strategy to elucidate the identification of antibiotic resistance in bacteria

Pengembangan Protokol Deteksi Staphylococcus aureus Berbasis Molekuler

Pulsed-Field Gel Electrophoresis Analysis of Bovine Associated Staphylococcus aureus: A Review

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