Dataset Information

On the Role of Bioinformatics and Data Science in Industrial Microbiome Applications.

ABSTRACT: Advances in sequencing and computational biology have drastically increased our capability to explore the taxonomic and functional compositions of microbial communities that play crucial roles in industrial processes. Correspondingly, commercial interest has risen for applications where microbial communities make important contributions. These include food production, probiotics, cosmetics, and enzyme discovery. Other commercial applications include software that takes the user's gut microbiome data as one of its inputs and outputs evidence-based, automated, and personalized diet recommendations for balanced blood sugar levels. These applications pose several bioinformatic and data science challenges that range from requiring strain-level resolution in community profiles to the integration of large datasets for predictive machine learning purposes. In this perspective, we provide our insights on such challenges by touching upon several industrial areas, and briefly discuss advances and future directions of bioinformatics and data science in microbiome research.

SUBMITTER: van den Bogert B

PROVIDER: S-EPMC6696986 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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On the Role of Bioinformatics and Data Science in Industrial Microbiome Applications.

van den Bogert Bartholomeus B Boekhorst Jos J Pirovano Walter W May Ali A

Frontiers in genetics 20190809

Advances in sequencing and computational biology have drastically increased our capability to explore the taxonomic and functional compositions of microbial communities that play crucial roles in industrial processes. Correspondingly, commercial interest has risen for applications where microbial communities make important contributions. These include food production, probiotics, cosmetics, and enzyme discovery. Other commercial applications include software that takes the user's gut microbiome ...[more]

PMID: 31447883

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Project description:BACKGROUND:One of the major challenges facing investigators in the microbiome field is turning large numbers of reads generated by next-generation sequencing (NGS) platforms into biological knowledge. Effective analytical workflows that guarantee reproducibility, repeatability, and result provenance are essential requirements of modern microbiome research. For nearly a decade, several state-of-the-art bioinformatics tools have been developed for understanding microbial communities living in a given sample. However, most of these tools are built with many functions that require an in-depth understanding of their implementation and the choice of additional tools for visualizing the final output. Furthermore, microbiome analysis can be time-consuming and may even require more advanced programming skills which some investigators may be lacking. RESULTS:We have developed a wrapper named iMAP (Integrated Microbiome Analysis Pipeline) to provide the microbiome research community with a user-friendly and portable tool that integrates bioinformatics analysis and data visualization. The iMAP tool wraps functionalities for metadata profiling, quality control of reads, sequence processing and classification, and diversity analysis of operational taxonomic units. This pipeline is also capable of generating web-based progress reports for enhancing an approach referred to as review-as-you-go (RAYG). For the most part, the profiling of microbial community is done using functionalities implemented in Mothur or QIIME2 platform. Also, it uses different R packages for graphics and R-markdown for generating progress reports. We have used a case study to demonstrate the application of the iMAP pipeline. CONCLUSIONS:The iMAP pipeline integrates several functionalities for better identification of microbial communities present in a given sample. The pipeline performs in-depth quality control that guarantees high-quality results and accurate conclusions. The vibrant visuals produced by the pipeline facilitate a better understanding of the complex and multidimensional microbiome data. The integrated RAYG approach enables the generation of web-based reports, which provides the investigators with the intermediate output that can be reviewed progressively. The intensively analyzed case study set a model for microbiome data analysis.

Dataset Information

On the Role of Bioinformatics and Data Science in Industrial Microbiome Applications.

Publications

On the Role of Bioinformatics and Data Science in Industrial Microbiome Applications.

Similar Datasets

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