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Research article
Metagenome gene prediction of naturally fermented milk products of India using PICRUSt2 and Piphillin
Jyoti Prakash Tamang
Sikkim University
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Naturally fermented milk (NFM) products are popular food delicacies in Indian states of Sikkim and Arunachal Pradesh. Bacterial communities in these NFM products of India were previously analysed by high-throughput sequence method. However, predictive gene functionality of NFM products of India has not been studied. In this study, raw sequences of NFM products of Sikkim and Arunachal Pradesh were accessed from NCBI database server. PICRUSt2 and Piphillin tools were applied to study microbial functional gene prediction in combination with the commonly used error-corrected denoising programs like DADA2 and Deblur.
Results: Significant functional hits were observed from the Piphillin analysis which included some interesting pathways including GABAergic synapse, glutamatergic synapse and serotonergic synapse, which are known to be probiotic-related, among others that are absent in PICRUSt2 analysis. This study also showed the negative correlation of lactic acid bacteria (LAB) members (Lactococcus, Lactobacillus, Leuconostoc) with most of the disease-related functions, which were on the other hand, positively correlated with unwanted contaminants like Staphylococcus, Bacillus and Pseudomonas.
Conclusion: The study explored the potential of microbial functional gene prediction using PICRUSt2 and Piphillin software, and indicated the significance of the presence of LAB in these NFM products of India. Since most LAB members are known to be potential health-promoting bacteria, their negative correlation to many of the disease-related functions also indicates their role in combatting unwanted potential contaminants.
Keywords
Metagenome gene prediction, PICRUSt2, Piphillin, naturally fermented milk products, DADA2, Deblur.
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This is a list of supplementary files associated with this preprint. Click to download.
- SupplementaryTable1.docx
Supplementary Table 1: Unique predictive pathways as per Piphillin and PICRUSt2 analysis based on the NFM data of Arunachal Pradesh and Sikkim, India.
- SupplementaryTable2.docx
Supplementary Table 2: Significant PICRUSt2-predictive pathways compared among the different sample types (dahi, chhurpi, churkam and lipid-rich NFM products are mar/gheu) [19] using two-sided Welch's t-test in STAMP.
- SupplementaryTable3.docx
Supplementary Table 3: Significant PICRUSt2-predictive pathways compared among the two regions using two-sided Welch's t-test in STAMP. 35 samples are collected from Arunachal Pradesh and 19 samples are from Sikkim [19].
- SupplementaryTable4.docx
Supplementary Table 4: Significant PICRUSt2-predictive pathways compared among the different sample types using two-sided Welch's t-test in STAMP. Four different types of NFM products were analyzed: chhurpi, churkam, dahi and mar/gheu [19]
- SupplementaryTable5.docx
Supplementary Table 5: Significant PICRUSt2-predictive pathways compared among the two source of milk using two-sided Welch's t-test in STAMP. NFM products used in this study are based on cow and yak milk for their preparation [19].
- SupplementaryTable6.docx
Supplementary Table 6: Significant Piphillin-predictive pathways compared among the two regions using two-sided Welch's t-test in STAMP. 35 samples of NFM products are collected from Arunachal Pradesh and 19 samples are from Sikkim [19].
- SupplementaryTable7.docx
Supplementary Table 7: Significant Piphillin-predictive pathways compared among the different sample types using two-sided Welch's t-test in STAMP. Four different types of NFM products were analyzed: chhurpi, churkam, dahi and mar/gheu [19].
- SupplementaryTable8.docx
Supplementary Table 8: Correlation of dominant bacterial genera with the PICRUSt2-significant pathways observed.
- SupplementaryTable9.docx
Supplementary Table 9: Correlation of dominant bacterial genera with the Piphillin-significant pathways observed.
- SupplementaryFigure.1.tif
Supplementary Figure 1: Bar graph representation (relative abundance) of major 45 predictive pathways as per PICRUSt2 analysis with sequences denoised against DADA2 algorithm clustered with SILVA database.
- SupplementaryFigure.2.tif
Supplementary Figure 2: Bar graph representation (relative abundance) of major 45 predictive pathways as per Piphillin analysis with sequences denoised against DADA2 algorithm clustered with SILVA database.
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Research article
Metagenome gene prediction of naturally fermented milk products of India using PICRUSt2 and Piphillin
Jyoti Prakash Tamang
Sikkim University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 29 Sep, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Epigenetics & Genomics
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Naturally fermented milk (NFM) products are popular food delicacies in Indian states of Sikkim and Arunachal Pradesh. Bacterial communities in these NFM products of India were previously analysed by high-throughput sequence method. However, predictive gene functionality of NFM products of India has not been studied. In this study, raw sequences of NFM products of Sikkim and Arunachal Pradesh were accessed from NCBI database server. PICRUSt2 and Piphillin tools were applied to study microbial functional gene prediction in combination with the commonly used error-corrected denoising programs like DADA2 and Deblur.
Results: Significant functional hits were observed from the Piphillin analysis which included some interesting pathways including GABAergic synapse, glutamatergic synapse and serotonergic synapse, which are known to be probiotic-related, among others that are absent in PICRUSt2 analysis. This study also showed the negative correlation of lactic acid bacteria (LAB) members (Lactococcus, Lactobacillus, Leuconostoc) with most of the disease-related functions, which were on the other hand, positively correlated with unwanted contaminants like Staphylococcus, Bacillus and Pseudomonas.
Conclusion: The study explored the potential of microbial functional gene prediction using PICRUSt2 and Piphillin software, and indicated the significance of the presence of LAB in these NFM products of India. Since most LAB members are known to be potential health-promoting bacteria, their negative correlation to many of the disease-related functions also indicates their role in combatting unwanted potential contaminants.
Figure 1
Figure 2
Figure 3
Figure 4