Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2019 Feb;60(1):103-111.
doi: 10.1007/s13353-019-00482-2. Epub 2019 Jan 25.

A Crash Course in Sequencing for a Microbiologist

Affiliations
Free PMC article
Review

A Crash Course in Sequencing for a Microbiologist

Aleksandra Kozińska et al. J Appl Genet. .
Free PMC article

Abstract

For the last 40 years, "Sanger sequencing" allowed to unveil crucial secrets of life. However, this method of sequencing has been time-consuming, laborious and remains expensive even today. Human Genome Project was a huge impulse to improve sequencing technologies, and unprecedented financial and human effort prompted the development of cheaper high-throughput technologies and strategies called next-generation sequencing (NGS) or whole genome sequencing (WGS). This review will discuss applications of high-throughput methods to study bacteria in a much broader context than simply their genomes. The major goal of next-generation sequencing for a microbiologist is not really resolving another circular genomic sequence. NGS started its infancy from basic structural and functional genomics, to mature into the molecular taxonomy, phylogenetic and advanced comparative genomics. Today, the use of NGS expended capabilities of diagnostic microbiology and epidemiology. The use of RNA sequencing techniques allows studying in detail the complex regulatory processes in the bacterial cells. Finally, NGS is a key technique to study the organization of the bacterial life-from complex communities to single cells. The major challenge in understanding genomic and transcriptomic data lies today in combining it with other sources of global data such as proteome and metabolome, which hopefully will lead to the reconstruction of regulatory networks within bacterial cells that allow communicating with the environment (signalome and interactome) and virtual cell reconstruction.

Keywords: Microbiome; Next-generation sequencing; Phylogenetic analysis; Sanger sequencing; Structural genomics; Transcriptomics.

Conflict of interest statement

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Figures

Fig. 1
Fig. 1
Differences of experimental approach between classical (a) and experiments involving high-throughput analyses such as NGS (b)
Fig. 2
Fig. 2
A schematic structure of a pan-genome that includes genes shared by all strains/isolates, genes shared by all genomes (core genome), and strain-specific genes that are present only in individual
Fig. 3
Fig. 3
A virtual cell reconstruction that will be possible in the future based on a combination of multiple levels of the “-omics” data
Fig. 4
Fig. 4
Overview of the different steps involved in the use of NGS technologies for data gathering and utilization. After Angers-Loustau et al. (2018), modified

Similar articles

See all similar articles

Cited by 2 articles

References

    1. Alm RA, Ling LS, Moir DT, King BL, Brown ED, Doig PC, Smith DR, et al. Genomic-sequence comparison of two unrelated isolates of the human gastric pathogen helicobacter pylori. Nature. 1999;397(6715):176–180. doi: 10.1038/16495. - DOI - PubMed
    1. Anderson S, Bankier AT, Barrell BG, de Bruijn MH, Coulson AR, Drouin J, Eperon IC, et al. Sequence and organization of the human mitochondrial genome. Nature. 1981;290(5806):457–465. doi: 10.1038/290457a0. - DOI - PubMed
    1. Angers-Loustau A, Petrillo M, Bengtsson-Palme J, Berendonk T, Blais B, Chan K-G, Coque TM, et al. The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies. F1000Res. 2018;7:459. doi: 10.12688/f1000research.14509.2. - DOI - PMC - PubMed
    1. Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, Formsma K, et al. The RAST server: rapid annotations using subsystems technology. BMC Genomics. 2008;9:75. doi: 10.1186/1471-2164-9-75. - DOI - PMC - PubMed
    1. Bashiardes S, Zilberman-Schapira G, Elinav E. Use of metatranscriptomics in microbiome research. Bioinf Biol Insights. 2016;10:BBI.S34610. doi: 10.4137/BBI.S34610. - DOI - PMC - PubMed

MeSH terms

LinkOut - more resources

Feedback