Abstract
The recent biotechnological advances and the rapid development of next-generation sequencing technologies accompanied by efficient computational facilities and tools have led to explosive and extensive data generation from finished complete genomes and draft genomes, because of this development, an urgent need arises for fast computing and automated approaches to analyze these bio big-data issued from microbial genomes and metagenomes in effective and a comparative way. Bioinformatics has come to play this major role via microbial bioinformatics and microbiomics which fill in the gap between just data accumulation and theoretical speculations to solution discovery and ready for use applications. In this perspective, our review gives an overview on microbial bioinformatics disciplines and subdisciplines and surveys their items, roles, influencing technologies and challenges, as well as lists the most microbial bioinformatics and metagenomics online resources, assemblers, and software, Furthermore, summarizes all the possible biotechnological applications of microbial bioinformatics and microbiomics in agriculture, food, medicine, industry, energy, and environment.
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1 Introduction
The sequencing technological revolution generated huge bio big data that require the harnessing of bioinformatics to archive, organize, analyze and use it to solve thorny biological problems [1]. Furthermore, the continuous development of high-throughput sequencing technologies during the last two decades, especially whole-genome sequencing (WGS), led to cumulative and extensive data issued from finished microbial genomes, draft genomes and metagenomes have irreversibly changed the way of microbial research and paved the way for microbial bioinformatics.
Since the sequencing of the first bacterial genome of Hemophilus influenzae, several microbial genomes, draft genomes and metagenomes, were finished and need analysis and exploitation, microbial bioinformatics via cloud computing, artificial intelligence and machine learning provides an alternative approach that facilitates the fast treatment of this large genome dataset [2].
In this review, we define microbial bioinformatics and list their disciplines and sub disciplines, roles, influencing technologies and challenges in the post-genomic era, as well as discuss the concepts of microbiomics, enumerate their computational tools, softwares and possible biotechnological applications.
2 Microbial Bioinformatics Multi-interdisciplinarity
While bioinformatics is an interdisciplinary research field that applies methodologies from computer science, mathematics and statistics to the study of biological phenomena, microbial bioinformatics is extremely multi-interdisciplinary, covering fundamental disciplines such as mathematics, statistics, informatics, physics, chemistry biology, microbiology and computational science, as well as applied disciplines such as agriculture, food, medicine, industry, energy and environment (Table 1).
In this review we define microbial bioinformatics and lists their disciplines, roles, influencing technologies and challenges in the post-genomic era, as well as discuss the concepts of microbiomics and their possible biotechnological applications.
3 Microbial Bioinformatics and Microbiomics
Microbial bioinformatics intersecting microbiology and bioinformatics and become to bridges the gap between data and discovery via analyzing the wealthy data gleaned from the fully sequenced microbial genomes and metagenomes to solve the complex biological problems. Microbial bioinformatics items, roles, influencing technologies, and challenges were summarized in Table 2 as well as online resources, assemblers, and software was listed in Table 3. These data banks and computational tools were very useful for promoting various kinds of analyses and meta-analysis which facilitate the discovery of hidden secrets of microbial ecosystem and microbiomic research in various fields.
The microbiome defined as the total genomes of the resident microorganisms of a particular organism [3]. Microbiomics harnessing bioinformatics to the study the microbial genes, genomes, and metagenomes via high throughput technologies accompanied by efficient computing tools which drastically changing the way of microbial DNA analysis, and revolutionized our understanding of microbial diversity, their functional roles in their environment, and association with plant, animal and human hosts. The various microbial bioinformatics applications spanning from environment, energy and agri-foods to bio-pharma- medicine fields were recapitulated in Table 4.
4 Conclusion
Network-based analytical approaches in general and microbial bioinformatics specially become to transform the raw data generated by sequencers to final outputs, furthermore, have proven useful to study systems with complex interactions, such as microbial genomes, metagenomes, and ecomicrobial systems. Development of new techniques in multi-omics approaches a long with sophisticated platforms will open new future directions for the field and facilitate the microbiomic research from diverse perspectives.
Based on the recent advances in sequencing technologies accompanied with latest research findings, we conclude clearly that microbial bioinformatics will become in the 21st century, the main creative and promoting discipline for microbiome research expansion and will provide a deeper understanding for microbiomes structurally and functionally which may fill in the gaps between pure science and practice for solving the medical, agricultural and environmental challenges.
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Thanks, are due to Jouf University and their Deanship of Library Affairs for providing necessary documentations for the completion of this work. The author also, wishes to thank anonymous referees for their helpful comments during the review process.
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Cheba, B.A. (2022). Review on Microbial Bioinformatics: Novel and Promoting Trend for Microbiomics Research and Applications. In: Moldovan, L., Gligor, A. (eds) The 15th International Conference Interdisciplinarity in Engineering. Inter-Eng 2021. Lecture Notes in Networks and Systems, vol 386. Springer, Cham. https://doi.org/10.1007/978-3-030-93817-8_64
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