A multi-view model for relative and absolute microbial abundances

Williamson, Brian D.; Willis, Amy

doi:10.1101/761486

Cited by 12 publications

(9 citation statements)

References 24 publications

(24 reference statements)

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“…Recent reports have argued that HTS datasets are limited to this type of information because library sizes are arbitrary (Gloor et al, 2017;Quinn et al, 2018) at least under traditional (equimolar) protocols. To explicitly diverge from this scenario, we refer to the total CFU of a given taxon within a given sample as the taxon's corresponding absolute abundance in that sample-a sample-wise notion of absolute abundance that has appeared previously in the literature (Williamson et al, 2019).…”

Section: A Note On Terminologymentioning

confidence: 99%

“…One way to recover absolute bacterial abundance for each sample is through association of relative information from HTS technology with absolute information from other methods. This has been previously done using qPCR or flow cytometry as absolute abundance methodologies and HTS as provider of bacterial proportions (Vandeputte et al, 2017;Williamson et al, 2019;Zemb et al, 2020). Here, however, by fixing volumes rather than concentrations during library preparation, our strategy allows the detection of major variations in input DNA within a specified quantification range.…”

Section: Proportionality Between Hts Reads and Absolute Abundancementioning

confidence: 99%

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Equivolumetric Protocol Generates Library Sizes Proportional to Total Microbial Load in 16S Amplicon Sequencing

Cruz¹,

Christoff²,

Oliveira³

2021

Front. Microbiol.

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High-throughput sequencing of 16S rRNA amplicon has been extensively employed to perform microbiome characterization worldwide. As a culture-independent methodology, it has allowed high-level profiling of sample bacterial composition directly from samples. However, most studies are limited to information regarding relative bacterial abundances (sample proportions), ignoring scenarios in which sample microbe biomass can vary widely. Here, we use an equivolumetric protocol for 16S rRNA amplicon library preparation capable of generating Illumina sequencing data responsive to input DNA, recovering proportionality between observed read counts and absolute bacterial abundances within each sample. Under specified conditions, we show that the estimation of colony-forming units (CFU), the most common unit of bacterial abundance in classical microbiology, is challenged mostly by resolution and taxon-to-taxon variation. We propose Bayesian cumulative probability models to address such issues. Our results indicate that predictive errors vary consistently below one order of magnitude for total microbial load and abundance of observed bacteria. We also demonstrate our approach has the potential to generalize to previously unseen bacteria, but predictive performance is hampered by specific taxa of uncommon profile. Finally, it remains clear that high-throughput sequencing data are not inherently restricted to sample proportions only, and such technologies bear the potential to meet the working scales of traditional microbiology.

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Section: A Note On Terminologymentioning

confidence: 99%

Section: Proportionality Between Hts Reads and Absolute Abundancementioning

confidence: 99%

Equivolumetric Protocol Generates Library Sizes Proportional to Total Microbial Load in 16S Amplicon Sequencing

Cruz¹,

Christoff²,

Oliveira³

2021

Front. Microbiol.

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“…One way to recover absolute bacterial abundance is to associate relative information from high-throughput technology with absolute information from other methods. This has been previously done using qPCR or flow cytometry data as absolute abundance methodologies, and NGS as provider of bacterial proportions 7,9,27 . Here, however, total microbial load gains importance as a measure of total contamination for surveillance of indoor environments, as opposed to merely a means to project proportions onto absolute terms.…”

Section: Modeling Absolute Abundance Using Ngs Datamentioning

confidence: 99%

Equivolumetric protocol generates library sizes proportional to total microbial load in next-generation sequencing

Gnf¹,

Ap²,

Lfv³

2020

Preprint

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Next-generation sequencing (NGS) has been extensively employed to perform microbiome characterization worldwide. As a culture-independent methodology, it has allowed high-level profiling of sample microbial composition. However, most studies are limited to information regarding relative bacterial abundances, ignoring scenarios in which sample microbe biomass can vary widely. Here, we develop an equivolumetric protocol for amplicon library preparation capable of generating NGS data responsive to input DNA, recovering proportionality between observed read counts and absolute bacterial abundances. Under specified conditions, we argue that the estimation of colony-forming units (CFU), the most common unit of bacterial abundance in classical microbiology, is challenged mostly by resolution and taxon-to-taxon variation. We propose Bayesian cumulative probability models to address such issues. Our results indicate that predictive errors vary consistently below one order of magnitude for observed bacteria. We also demonstrate our approach has the potential to generalize to previously unseen bacteria, but predictive performance is hampered by specific taxa of uncommon profile. Finally, it remains clear that NGS data are not inherently restricted to relative information only, and microbiome science can indeed meet the working scales of traditional microbiology.

show abstract

“…One way to recover absolute bacterial abundance for each sample is to associate relative information from high-throughput technology with absolute information from other methods. This has been previously done using qPCR or flow cytometry data as absolute abundance methodologies, and NGS as provider of bacterial proportions [7,9,31]. Here, however, total microbial load gains importance for surveillance of built environments as a measure of total contamination at sampling site, as opposed to merely a means to project proportions onto absolute terms.…”

Section: Modelling Absolute Abundance Using Ngs Datamentioning

confidence: 99%

“…Recent reports have argued that NGS datasets are limited to this type of information because library sizes are arbitrary [10,58] at least under traditional (equimolar) protocols. To explicitly diverge from this scenario, we refer to the total CFU of a given taxon within a given sample as the taxon's corresponding absolute abundance in that sample -a sample-wise notion of absolute abundance that has appeared previously in the literature [31].…”

Section: A Note On Terminologymentioning

confidence: 99%

Microbiome meets classical microbiology: quantifying sample CFU using 16S rRNA gene sequencing data

Cruz¹,

Christoff²,

Oliveira³

2020

Preprint

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Background Next-generation sequencing (NGS) has been extensively employed to perform microbiome characterization worldwide. As a culture-independent methodology, it has allowed high-level profiling of sample microbial composition. However, most studies are limited to sample information regarding relative bacterial abundances (sample proportions), ignoring scenarios in which sample microbe biomass can vary widely. Here, we develop an equivolumetric protocol for amplicon library preparation capable of generating NGS data responsive to input DNA, recovering proportionality between observed read counts and absolute bacterial abundances within each sample. Within a determined range, we show that the estimation of sample colony-forming units (CFU), the most common unit of bacterial abundance in classical microbiology, is challenged mostly by resolution and taxon-to-taxon variation. We propose Bayesian cumulative probability models to address such issues.Results Observed read counts were consistently proportional to input DNA, total microbial load, and bacterium-specific sample abundances, although a saturation tendency was observed as abundances increased. Using Bayesian cumulative probability models, predictive errors in sample CFU estimation varied constantly below one order of magnitude - as measured by the mean absolute log10-ratio (MALR). For total microbial load, observed MALR was no greater than 0.2 during both cross-validation and validation on a test dataset. For observed bacteria, estimation of taxon-specific CFU showed MALR values of at most 0.5. We also performed leave-one-group-out cross-validation to assess predictive performance for previously unseen bacteria. While most bacteria showed MALR no greater than 1, such a threshold was exceeded only by Bacillus cereus.Conclusions Being able to estimate sample CFU in a high-throughput fashion has a wide range of applications, from the study of built environments to public health surveillance. This study shows that equivolumetric protocols along with cumulative probability models allow sample CFU estimation from microbiome datasets. Further, our approach has the potential to generalize to previously unmodeled bacteria, an important feature in high-throughput settings. Lastly, it remains clear that NGS data are not inherently restricted to sample proportions only, and microbiome science can finally meet the working scales of classical microbiology.

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A multi-view model for relative and absolute microbial abundances

Cited by 12 publications

References 24 publications

Equivolumetric Protocol Generates Library Sizes Proportional to Total Microbial Load in 16S Amplicon Sequencing

Equivolumetric Protocol Generates Library Sizes Proportional to Total Microbial Load in 16S Amplicon Sequencing

Equivolumetric protocol generates library sizes proportional to total microbial load in next-generation sequencing

Microbiome meets classical microbiology: quantifying sample CFU using 16S rRNA gene sequencing data

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