Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data

Davis, Nicole M.; Proctor, Diana M.; Holmes, Susan; Relman, David A.; Callahan, Benjamin J.

doi:10.1101/221499

Cited by 122 publications

(99 citation statements)

References 62 publications

(105 reference statements)

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“…To determine the level of false positives related to laboratory processing, we used negative controls for the DNA isolation and PCR processes and sequenced these negative controls. Contaminating sequences are expected to be present at greater proportions in negative controls than in samples (Davis, Proctor, Holmes, Relman, & Callahan, ). To remove potentially contaminating sequence reads from samples, we defined a sequence removal threshold, the maximum number of reads attributed to a taxon in a negative control.…”

Section: Discussionmentioning

confidence: 99%

“…We suggest that negative controls be used for each step in the metabarcoding process (DNA isolation, PCR) and these negative controls should be included in the pool for Illumina sequencing. The data from negative controls can be used to remove contaminating sequences from samples in silico (Davis et al., ). Third, in order to reduce false‐positive determinations, we suggest that researchers take precautions to reduce environmentally common windborne pollen by approaches such as bleaching surfaces, filtering incoming air, the use of a laminar flow hood and/or not conducting procedures during the time period when wind‐pollinated trees (such as Pinus ) are producing pollen.…”

Section: Discussionmentioning

confidence: 99%

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Quantitative and qualitative assessment of pollen DNA metabarcoding using constructed species mixtures

et al. 2018

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Pollen DNA metabarcoding-marker-based genetic identification of potentially mixed-species pollen samples-has applications across a variety of fields. While basic species-level pollen identification using standard DNA barcode markers is established, the extent to which metabarcoding (a) correctly assigns species identities to mixes (qualitative matching) and (b) generates sequence reads proportionally to their relative abundance in a sample (quantitative matching) is unclear, as these have not been assessed relative to known standards. We tested the quantitative and qualitative robustness of metabarcoding in constructed pollen mixtures varying in species richness (1-9 species), taxonomic relatedness (within genera to across class) and rarity (5%-100% of grains), using Illumina MiSeq with the markers rbcL and ITS2. Qualitatively, species composition determinations were largely correct, but false positives and negatives occurred. False negatives were typically driven by lack of a barcode gap or rarity in a sample. Species richness and taxonomic relatedness, however, did not strongly impact correct determinations. False positives were likely driven by contamination, chimeric sequences and/or misidentification by the bioinformatics pipeline. Quantitatively, the proportion of reads for each species was only weakly correlated with its relative abundance, in contrast to suggestions from some other studies. Quantitative mismatches are not correctable by consistent scaling factors, but instead are context-dependent on the other species present in a sample. Together, our results show that metabarcoding is largely robust for determining pollen presence/absence but that sequence reads should not be used to infer relative abundance of pollen grains.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Quantitative and qualitative assessment of pollen DNA metabarcoding using constructed species mixtures

et al. 2018

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“…The impact of contamination increases in samples with small amounts of true exogenous DNA and can swamp the signal from the host's microbiome (Lusk, ; Salter et al., ). Contamination can be assessed using negative controls (e.g., Davis, Proctor, Holmes, Relman, & Callahan, ). However, the data used in this study were initially produced with the sole focus on the host organism.…”

Section: Methodsmentioning

confidence: 99%

Host‐derived population genomics data provides insights into bacterial and diatom composition of the killer whale skin

et al. 2018

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Recent exploration into the interactions and relationship between hosts and their microbiota has revealed a connection between many aspects of the host's biology, health and associated micro-organisms. Whereas amplicon sequencing has traditionally been used to characterize the microbiome, the increasing number of published population genomics data sets offers an underexploited opportunity to study microbial profiles from the host shotgun sequencing data. Here, we use sequence data originally generated from killer whale Orcinus orca skin biopsies for population genomics, to characterize the skin microbiome and investigate how host social and geographical factors influence the microbial community composition. Having identified 845 microbial taxa from 2.4 million reads that did not map to the killer whale reference genome, we found that both ecotypic and geographical factors influence community composition of killer whale skin microbiomes. Furthermore, we uncovered key taxa that drive the microbiome community composition and showed that they are embedded in unique networks, one of which is tentatively linked to diatom presence and poor skin condition. Community composition differed between Antarctic killer whales with and without diatom coverage, suggesting that the previously reported episodic migrations of Antarctic killer whales to warmer waters associated with skin turnover may control the effects of potentially pathogenic bacteria such as Tenacibaculum dicentrarchi. Our work demonstrates the feasibility of microbiome studies from host shotgun sequencing data and highlights the importance of metagenomics in understanding the relationship between host and microbial ecology.

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“…Because we did not sequence a negative extraction control, we used decontam's frequency-filtering technique, which assumes a negative linear relationship between initial DNA concentration and frequency of the potential contaminant (Davis et al, 2018). Because we did not sequence a negative extraction control, we used decontam's frequency-filtering technique, which assumes a negative linear relationship between initial DNA concentration and frequency of the potential contaminant (Davis et al, 2018).…”

Section: Co Nta M I N Ati O N Eli M I N Ati O N M E Th O Ds a N D R Ementioning

confidence: 99%

Habitat fragmentation is associated with dietary shifts and microbiota variability in common vampire bats

Ingala

Becker

Holm

et al. 2019

Ecology and Evolution

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Host ecological factors and external environmental factors are known to influence the structure of gut microbial communities, but few studies have examined the impacts of environmental changes on microbiotas in free‐ranging animals. Rapid land‐use change has the potential to shift gut microbial communities in wildlife through exposure to novel bacteria and/or by changing the availability or quality of local food resources. The consequences of such changes to host health and fitness remain unknown and may have important implications for pathogen spillover between humans and wildlife. To better understand the consequences of land‐use change on wildlife microbiotas, we analyzed long‐term dietary trends, gut microbiota composition, and innate immune function in common vampire bats (Desmodus rotundus) in two nearby sites in Belize that vary in landscape structure. We found that vampire bats living in a small forest fragment had more homogenous diets indicative of feeding on livestock and shifts in microbiota heterogeneity, but not overall composition, compared to those living in an intact forest reserve. We also found that irrespective of sampling site, vampire bats which consumed relatively more livestock showed shifts in some core bacteria compared with vampire bats which consumed relatively less livestock. The relative abundance of some core microbiota members was associated with innate immune function, suggesting that future research should consider the role of the host microbiota in immune defense and its relationship to zoonotic infection dynamics. We suggest that subsequent homogenization of diet and habitat loss through livestock rearing in the Neotropics may lead to disruption to the microbiota that could have downstream impacts on host immunity and cross‐species pathogen transmission.

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Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data

Cited by 122 publications

References 62 publications

Quantitative and qualitative assessment of pollen DNA metabarcoding using constructed species mixtures

Quantitative and qualitative assessment of pollen DNA metabarcoding using constructed species mixtures

Host‐derived population genomics data provides insights into bacterial and diatom composition of the killer whale skin

Habitat fragmentation is associated with dietary shifts and microbiota variability in common vampire bats

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