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DOI :10.26650/experimed.1262138   IUP :10.26650/experimed.1262138    Tam Metin (PDF)

An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes

Muzaffer Arıkan

Objective: Cancer is a leading cause of death worldwide, requires development of new effective, specific, and safe strategies that do not carry the disadvantages of traditional cancer treatment approaches. Hence, this study aimed to identify anticancer peptide candidates in fermented food microbiomes through an in silico investigation. Materials and Methods: One hundred eight shotgun metagenomic sequencing samples from six studies on fermented food microbiomes were downloaded from the NCBI and ENA databases and included in the study. Bioinformatic analyses including quality control of raw data, de novo assembly, prediction of protein sequences, anticancer peptide predictions by an integrated use of four different prediction tools, toxicity predictions and database comparisons were performed. Results: One hundred forty-two novel anticancer peptide candidates were identified. Liquor, coffee, kefir fermentation samples contained the greatest numbers of anticancer peptide candidates while sugar, dairy, coconut kefir and brine-type fermentations were dominant sources according to the substrate type. Conclusion: This study indicates the potential of fermented food microbiomes as a useful source for candidate anticancer peptide detection. In vitro and in vivo validations of detected peptides may lead to development of new candidate molecules for cancer therapy in the future.


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Referanslar

  • 1. Avilés-Gaxiola S, Gutiérrez-Grijalva EP, León-Felix J, Angulo-Escalante MA, Heredia JB. Peptides in colorectal cancer: Current state of knowledge. Plant Foods Hum Nutr 2020; 75(4): 467-76. [CrossRef] google scholar
  • 2. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018; 68(6): 394-424. [CrossRef] google scholar
  • 3. Ellis MA, Graboyes EM, Wahlquist AE, Neskey DM, Kaczmar JM, Schopper HK, et al. Primary surgery vs radiotherapy for early stage oral cavity cancer. Otolaryngol - Head Neck Surg (United States) 2018; 158(4): 649-59. [CrossRef] google scholar
  • 4. Lobb RJ, Jacobson GM, Cursons RT, Jameson MB. The interaction of selenium with chemotherapy and radiation on normal and malignant human mononuclear blood cells. Int J Mol Sci 2018; 19(10): 3167. [CrossRef] google scholar
  • 5. Sharma P, Kaur H, Kehinde BA, Chhikara N, Sharma D, Panghal A. Food-derived anticancer peptides: a review. Int J Pept Res Ther 2021; 27(1): 55-70. [CrossRef] google scholar
  • 6. Hoskin DW, Ramamoorthy A. Studies on anticancer activities of antimicrobial peptides. Biochim Biophys Acta2008; 1778(2): 35775. [CrossRef] google scholar
  • 7. Chiangjong W, Chutipongtanate S, Hongeng S. Anticancer peptide: Physicochemical property, functional aspect and trend in clinical application. Int J Oncol 2020; 57(3): 678-96. [CrossRef] google scholar
  • 8. Pan X, Xu J, Jia X. Research progress evaluating the function and mechanism of anti-tumor peptides. Cancer Manag Res 2020; 12: 397-409. [CrossRef] google scholar
  • 9. Shoombuatong W, Schaduangrat N, Nantasenamat C. Unraveling the bioactivity of anticancer peptides as deduced from machine learning. EXCLI J 2018; 17: 734-52. google scholar
  • 10. Baruah R, Ray M, Halami PM. Preventive and therapeutic aspects of fermented foods. J Appl Microbiol 2022; 132(5): 3476-89. [CrossRef] google scholar
  • 11. Martinez-Villaluenga C, Peñas E, Frias J. Bioactive peptides in fermented foods. In: Fermented foods in health and disease prevention . Elsevier; 2017. p. 23-47. [CrossRef] google scholar
  • 12. Tasdemir SS, Sanlier N. An insight into the anticancer effects of fermented foods: A review. J Funct Foods 2020; 75: 104281. [CrossRef] google scholar
  • 13. Liang X, Li F, Chen J, Li J, Wu H, Li S, et al. Large-scale comparative review and assessment of computational methods for anti-cancer peptide identification. Brief Bioinform. 2021; 22(4): bbaa312. [CrossRef] google scholar
  • 14. Nurk S, Meleshko D, Korobeynikov A, Pevzner PA. MetaSPAdes: A new versatile metagenomic assembler. Genome Res. 2017; 27(5): 824-34. [CrossRef] google scholar
  • 15. Seemann T. Prokka: Rapid prokaryotic genome annotation. Bioinformatics 2014; 30(14): 2068-9. [CrossRef] google scholar
  • 16. Shen W, Le S, Li Y, Hu F. SeqKit: A cross-platform and ultrafast toolkit for FASTA/Q file manipulation. PLoS One 2016; 11(10): e0163962. [CrossRef] google scholar
  • 17. Agrawal P, Bhagat D, Mahalwal M, Sharma N, Raghava GPS. AntiCP 2.0: An updated model for predicting anticancer peptides. Brief Bioinform 2021; 22(3): bbaa153. [CrossRef] google scholar
  • 18. Boopathi V, Subramaniyam S, Malik A, Lee G, Manavalan B, Yang D-C. mACPpred: A support vector machine-based meta-predictor for identification of anticancer peptides. Int J Mol Sci 2019; 20(8): 1964. [CrossRef] google scholar
  • 19. Ahmed S, Muhammod R, Khan ZH, Adilina S, Sharma A, Shatabda S, et al. ACP-MHCNN: An accurate multi-headed deep-convolutional neural network to predict anticancer peptides. Sci Rep 2021; 11(1): 23676. [CrossRef] google scholar
  • 20. Schaduangrat N, Nantasenamat C, Prachayasittikul V, Shoombuatong W. ACPred: A computational tool for the prediction and analysis of anticancer peptides. Molecules 2019; 24(10): 1973. [CrossRef] google scholar
  • 21. Gupta S, Kapoor P, Chaudhary K, Gautam A, Kumar R, Raghava GPS. In silico approach for predicting toxicity of peptides and proteins. Patterson RL, editor. PLoS One 2013; 8(9): e73957. [CrossRef] google scholar
  • 22. Tyagi A, Tuknait A, Anand P, Gupta S, Sharma M, Mathur D, et al. CancerPPD: a database of anticancer peptides and proteins. Nucleic Acids Res 2015 ; 43(Database Issue): D837-43. [CrossRef] google scholar
  • 23. Leech J, Cabrera-Rubio R, Walsh AM, Macori G, Walsh CJ, Barton W, et al. Fermented-food metagenomics reveals substrate-associated differences in taxonomy and health-associated and antibiotic resistance determinants. mSystems 2020; 5(6): e00522-20.. [CrossRef] google scholar
  • 24. Durrant MG, Bhatt AS. Automated prediction and annotation of small open reading frames in microbial genomes. Cell Host Microbe 2021; 29(1): 121-31. [CrossRef] google scholar
  • 25. dos Reis SA, da Conceiçao LL, e Dias MM, Siqueira NP, Rosa DD, de Oliveira LL, et al. Kefir reduces the incidence of pre-neoplastic lesions in an animal model for colorectal cancer. J Funct Foods 2019; 53: 1-6. [CrossRef] google scholar
  • 26. Jalali F, Sharifi M, Salehi R. Kefir induces apoptosis and inhibits cell proliferation in human acute erythroleukemia. Med Oncol 2016; 33(1): 1-9. [CrossRef] google scholar
  • 27. Esener OBB, Balkan BM, Armutak EI, Uvez A, Yildiz G, Hafizoglu M, et al. Donkey milk kefir induces apoptosis and suppresses proliferation of Ehrlich ascites carcinoma by decreasing iNOS in mice. Biotech Histochem 2018; 93(6): 424-31. [CrossRef] google scholar
  • 28. Sharifi M, Moridnia A, Mortazavi D, Salehi M, Bagheri M, Sheikhi A. Kefir: A powerful probiotics with anticancer properties. Med Oncol 2017; 34(11):183. [CrossRef] google scholar
  • 29. Arikan M, Mitchell AL, Finn RD. GF. Microbial composition of Kombucha determined using amplicon sequencing and shotgun metagenomics. J Food Sci 2020; 85(2): 455-64. 30. [CrossRef] google scholar
  • 30. Pothakos V, De Vuyst L, Zhang SJ, De Bruyn F, Verce M, Torres J, et al. Temporal shotgun metagenomics of an Ecuadorian coffee fermentation process highlights the predominance of lactic acid bacteria. Curr Res Biotechnol. 2020; 2:1-15. [CrossRef] google scholar

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APA

Arıkan, M. (2023). An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes. Experimed, 13(1), 64-72. https://doi.org/10.26650/experimed.1262138


AMA

Arıkan M. An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes. Experimed. 2023;13(1):64-72. https://doi.org/10.26650/experimed.1262138


ABNT

Arıkan, M. An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes. Experimed, [Publisher Location], v. 13, n. 1, p. 64-72, 2023.


Chicago: Author-Date Style

Arıkan, Muzaffer,. 2023. “An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes.” Experimed 13, no. 1: 64-72. https://doi.org/10.26650/experimed.1262138


Chicago: Humanities Style

Arıkan, Muzaffer,. An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes.” Experimed 13, no. 1 (Jul. 2024): 64-72. https://doi.org/10.26650/experimed.1262138


Harvard: Australian Style

Arıkan, M 2023, 'An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes', Experimed, vol. 13, no. 1, pp. 64-72, viewed 25 Jul. 2024, https://doi.org/10.26650/experimed.1262138


Harvard: Author-Date Style

Arıkan, M. (2023) ‘An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes’, Experimed, 13(1), pp. 64-72. https://doi.org/10.26650/experimed.1262138 (25 Jul. 2024).


MLA

Arıkan, Muzaffer,. An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes.” Experimed, vol. 13, no. 1, 2023, pp. 64-72. [Database Container], https://doi.org/10.26650/experimed.1262138


Vancouver

Arıkan M. An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes. Experimed [Internet]. 25 Jul. 2024 [cited 25 Jul. 2024];13(1):64-72. Available from: https://doi.org/10.26650/experimed.1262138 doi: 10.26650/experimed.1262138


ISNAD

Arıkan, Muzaffer. An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes”. Experimed 13/1 (Jul. 2024): 64-72. https://doi.org/10.26650/experimed.1262138



ZAMAN ÇİZELGESİ


Gönderim09.03.2023
Kabul04.04.2023
Çevrimiçi Yayınlanma07.04.2023

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