Identification and analysis of genomic islands in Burkholderia cenocepacia genome by using computational approaches

Deepti Jaiswal; Prateek Paul; Upasna Srivastava; Ajay Kumar Singh; Satendra Singh

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Online Published: 25 Jul 2024

IJLSAS. 2023; 5(3): 25-45

Identification and analysis of genomic islands in Burkholderia cenocepacia genome by using computational approaches

Deepti Jaiswal, Prateek Paul, Upasna Srivastava, Ajay Kumar Singh, Satendra Singh.

Abstract
Burkholderia cenocepacia (B. cenocepacia) is a gram-negative bacterium that is commonly found in the environment, may create a biofilm, and is resistant to a variety of antibiotics. It can also cause illness in plants. It can produce "cepacia syndrome" in people with cystic fibrosis, which is marked by a fast-progressing fever, uncontrolled bronchopneumonia, weight loss, and, in some cases, death. The antimicrobial drugs trimethoprim-sulfamethoxazole, ceftazidime, fluoroquinolones and chloramphenicol are used against B. cenocepacia, however their effectiveness and drug resistance is serious concern. The current study is focused on the prediction and analysis of genomic islands in the B. cenocepacia genome by using computational approaches. The Island Viewer 4 was used for the prediction of genomic islands in B. cenocepacia J2315. A total of 74 different regions of genomic islands in B. cenocepacia J2315 were identified. These genomic islands vary in base pair length from 4091 to 72717 bp. Total 93 proteins encoded by identified genomic islands were predicted in B. cenocepacia J2315. Among 93 encoded proteins 02 functionally significant encoded proteins, DNA gyrase subunit beta and Glutamate racemase were selected for further computational analysis. The proteins were classified as stable proteins as their instability index 35.37 and 34.28 respectively. Good quality model of DNA gyrase and glutamate racemase were predeicted as their QMEAN Z-score were -1.62 and -2.36. The highest quality factor of glutamate was found about 94.6%. This computational approach can assist in future for identification and validation of suitable drug targets.

Key words: B. cenocepacia , genomic islands, drug target, motif.

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How to Cite this Article

Pubmed Style

Jaiswal D, Paul P, Srivastava U, Singh AK, Singh S. Identification and analysis of genomic islands in Burkholderia cenocepacia genome by using computational approaches. IJLSAS. 2023; 5(3): 25-45.

Web Style

Jaiswal D, Paul P, Srivastava U, Singh AK, Singh S. Identification and analysis of genomic islands in Burkholderia cenocepacia genome by using computational approaches. https://www.ijlsas.com/?mno=211288 [Access: June 23, 2026].

AMA (American Medical Association) Style

Jaiswal D, Paul P, Srivastava U, Singh AK, Singh S. Identification and analysis of genomic islands in Burkholderia cenocepacia genome by using computational approaches. IJLSAS. 2023; 5(3): 25-45.

Vancouver/ICMJE Style

Jaiswal D, Paul P, Srivastava U, Singh AK, Singh S. Identification and analysis of genomic islands in Burkholderia cenocepacia genome by using computational approaches. IJLSAS. (2023), [cited June 23, 2026]; 5(3): 25-45.

Harvard Style

Jaiswal, D., Paul, . P., Srivastava, . U., Singh, . A. K. & Singh, . S. (2023) Identification and analysis of genomic islands in Burkholderia cenocepacia genome by using computational approaches. IJLSAS, 5 (3), 25-45.

Turabian Style

Jaiswal, Deepti, Prateek Paul, Upasna Srivastava, Ajay Kumar Singh, and Satendra Singh. 2023. Identification and analysis of genomic islands in Burkholderia cenocepacia genome by using computational approaches. International Journal Of Life Sciences and Applied Sciences, 5 (3), 25-45.

Chicago Style

Jaiswal, Deepti, Prateek Paul, Upasna Srivastava, Ajay Kumar Singh, and Satendra Singh. "Identification and analysis of genomic islands in Burkholderia cenocepacia genome by using computational approaches." International Journal Of Life Sciences and Applied Sciences 5 (2023), 25-45.

MLA (The Modern Language Association) Style

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