A breath of fresh air in microbiome science: shallow shotgun metagenomics for a reliable disentangling of microbial ecosystems

Gabriele Andrea Lugli , Marco Ventura

Microbiome Research Reports ›› 2022, Vol. 1 ›› Issue (2) : 8

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Microbiome Research Reports ›› 2022, Vol. 1 ›› Issue (2) :8 DOI: 10.20517/mrr.2021.07
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A breath of fresh air in microbiome science: shallow shotgun metagenomics for a reliable disentangling of microbial ecosystems

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Abstract

Next-generation sequencing technologies allow accomplishing massive DNA sequencing, uncovering the microbial composition of many different ecological niches. However, the various strategies developed to profile microbiomes make it challenging to retrieve a reliable classification that is able to compare metagenomic data of different studies. Many limitations have been overcome thanks to shotgun sequencing, allowing a reliable taxonomic classification of microbial communities at the species level. Since numerous bioinformatic tools and databases have been implemented, the sequencing methodology is only the first of many choices to make for classifying metagenomic data. Here, we discuss the importance of choosing a reliable methodology to achieve consistent information in uncovering microbiomes.

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Metagenomics / microbiota / bioinformatics / microbial DNA sequencing

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Gabriele Andrea Lugli, Marco Ventura. A breath of fresh air in microbiome science: shallow shotgun metagenomics for a reliable disentangling of microbial ecosystems. Microbiome Research Reports, 2022, 1(2): 8 DOI:10.20517/mrr.2021.07

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References

[1]

Yarza P,Pruesse E.Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences.Nat Rev Microbiol2014;12:635-45

[2]

Nilsson RH,Bahram M,Baldrian P.Mycobiome diversity: high-throughput sequencing and identification of fungi.Nat Rev Microbiol2019;17:95-109

[3]

Ragupathi NK, Muthuirulandi Sethuvel DP, Inbanathan FY, Veeraraghavan B. Accurate differentiation of Escherichia coli and Shigella serogroups: challenges and strategies.New Microbes New Infect2018;21:58-62 PMCID:PMC5711669

[4]

Milani C,Turroni F.Evaluation of bifidobacterial community composition in the human gut by means of a targeted amplicon sequencing (ITS) protocol.FEMS Microbiol Ecol2014;90:493-503

[5]

Wagner J,Browne HP,Francis SC.Evaluation of PacBio sequencing for full-length bacterial 16S rRNA gene classification.BMC Microbiol2016;16:274 PMCID:PMC5109829

[6]

Caruso V,Asquith M.Performance of microbiome sequence inference methods in environments with varying biomass.mSystems2019;4:e00163-18 PMCID:PMC6381225

[7]

Conrads G.Challenges of next-generation sequencing targeting anaerobes.Anaerobe2019;58:47-52

[8]

Park C,Choi SH.Comparison of 16S rRNA gene based microbial profiling using five next-generation sequencers and various primers.Front Microbiol2021;12:715500 PMCID:PMC8552068

[9]

Pérez-Cobas AE,Buchrieser C.Metagenomic approaches in microbial ecology: an update on whole-genome and marker gene sequencing analyses.Microb Genom2020;6:mgen000409 PMCID:PMC7641418

[10]

Lugli GA,Milani C.Genetic insights into the dark matter of the mammalian gut microbiota through targeted genome reconstruction.Environ Microbiol2021;23:3294-305 PMCID:PMC8359967

[11]

Beaudry MS,Kieran TJ.Improved microbial community characterization of 16S rRNA via metagenome hybridization capture enrichment.Front Microbiol2021;12:644662 PMCID:PMC8110821

[12]

Hillmann B,Shields-Cutler RR.Evaluating the information content of shallow shotgun metagenomics.mSystems2018;3:e00069-18 PMCID:PMC6234283

[13]

Milani C,Fontana F.METAnnotatorX2: a Comprehensive tool for deep and shallow metagenomic data set analyses.mSystems2021;6:e0058321 PMCID:PMC8269244

[14]

Lugli GA,Mancabelli L,van Sinderen D.A microbiome reality check: limitations of in silico-based metagenomic approaches to study complex bacterial communities.Environ Microbiol Rep2019;11:840-7

[15]

Ye SH,Park DJ.Benchmarking metagenomics tools for taxonomic classification.Cell2019;178:779-94 PMCID:PMC6716367

[16]

Bernard G,Lannes R,Bapteste E.Microbial darkmatter investigations: Howmicrobial studies transform biological knowledge and empirically sketch a logic of scientific discovery.Genome Biol Evol2018;10:707-15 PMCID:PMC5830969

[17]

Rahi P,Shouche YS.Matrix-assisted laser desorption/ionization time-of-flight mass-spectrometry (MALDI-TOF MS) based microbial identifications: challenges and scopes for microbial ecologists.Front Microbiol2016;7:1359 PMCID:PMC5003876

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