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

Lugli, Gabriele Andrea; Ventura, Marco

doi:10.20517/mrr.2021.07

Cited by 8 publications

(10 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous metagenome studies have reported 97–99 % accuracy for pathogen identification at genus level for microbes using shallow sequencing (<500 000 sequences) [41–44]. Results from our study broadly agreed with those of previous studies.…”

Section: Discussionsupporting

confidence: 91%

Development and evaluation of Microbe Finder (MiFi)®: a novel in silico diagnostic platform for pathogen detection from metagenomic data

Narayanan

Espindola

Malayer

et al. 2023

Journal of Medical Microbiology

View full text Add to dashboard Cite

Introduction. With expanding demand for diagnostics, newer methodologies are needed for faster, user-friendly and multiplexed pathogen detection. Metagenome-based diagnostics offer potential solutions to address these needs as sequencing technologies have become affordable. However, the diagnostic utility of sequencing technologies is currently limited since analysis of the large amounts of data generated, are either computationally expensive or carry lower sensitivity and specificity for pathogen detection. Hypothesis/Gap Statement. There is a need for novel, user friendly, and computationally inexpensive platforms for metagenome sequence analysis for diagnostic applications. Methods. In this study, we report the use of MiFi® (Microbe Finder), a computationally inexpensive algorithm with a user-friendly online interface, for accurate, rapid and multiplexed pathogen detection from metagenome sequence data. Detection is accomplished based on identification of signature genomic sequence segments of the target pathogen in metagenome sequence data. In this study we used bovine respiratory disease (BRD) complex as a model. Results and Conclusions. Using MiFi®, multiple target bacteria and a DNA virus were successfully detected in a multiplex format from metagenome sequences acquired from bovine lung tissue. Overall, 51 clinical samples were assessed and MiFi® showed 100 % analytical specificity and varying levels of analytical sensitivity (62.5 %–100 %) when compared with other traditional pathogen detection techniques, such as PCR. Consistent detection of bacteria was possible from lung samples artificially spiked with 109–104 c.f.u. of Mannheimia haemolytica .

show abstract

Section: Discussionsupporting

confidence: 91%

Development and evaluation of Microbe Finder (MiFi)®: a novel in silico diagnostic platform for pathogen detection from metagenomic data

Narayanan

Espindola

Malayer

et al. 2023

Journal of Medical Microbiology

View full text Add to dashboard Cite

show abstract

“…We using more advanced techniques, i.e. third-generation sequencing technologies (shallow) metagenomics [96,97] for more accurate analysis.…”

Section: Discussionmentioning

confidence: 99%

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Matchado,

Rühlemann,

Reitmeier

et al. 2024

Microbial Genomics

View full text Add to dashboard Cite

Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type two diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.

show abstract

“…The resulting genome sequence has been polished through Polypolish (Wick and Holt, 2022 ) using Illumina paired-end reads. The whole process was managed by the MEGAnnotator2 pipeline (Lugli and Ventura, 2022 ).…”

Section: Methodsmentioning

confidence: 99%

Genomic and ecological approaches to identify the Bifidobacterium breve prototype of the healthy human gut microbiota

Argentini,

Lugli,

Tarracchini

et al. 2024

Front. Microbiol.

Self Cite

View full text Add to dashboard Cite

Members of the genus Bifidobacterium are among the first microorganisms colonizing the human gut. Among these species, strains of Bifidobacterium breve are known to be commonly transmitted from mother to her newborn, while this species has also been linked with activities supporting human wellbeing. In the current study, an in silico approach, guided by ecology- and phylogenome-based analyses, was employed to identify a representative strain of B. breve to be exploited as a novel health-promoting candidate. The selected strain, i.e., B. breve PRL2012, was found to well represent the genetic content and functional genomic features of the B. breve taxon. We evaluated the ability of PRL2012 to survive in the gastrointestinal tract and to interact with other human gut commensal microbes. When co-cultivated with various human gut commensals, B. breve PRL2012 revealed an enhancement of its metabolic activity coupled with the activation of cellular defense mechanisms to apparently improve its survivability in a simulated ecosystem resembling the human microbiome.

show abstract

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

Cited by 8 publications

References 10 publications

Development and evaluation of Microbe Finder (MiFi)®: a novel in silico diagnostic platform for pathogen detection from metagenomic data

Development and evaluation of Microbe Finder (MiFi)®: a novel in silico diagnostic platform for pathogen detection from metagenomic data

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Genomic and ecological approaches to identify the Bifidobacterium breve prototype of the healthy human gut microbiota

Contact Info

Product

Resources

About