Reagent contamination can critically impact sequence-based microbiome analyses

Salter, Susannah J.; Cox, Michael J.; Turek, Elena; Calus, Szymon T.; Cookson, William; Moffatt, Miriam F.; Turner, Paul; Parkhill, Julian; Loman, Nicholas J.; Walker, Alan W.

doi:10.1101/007187

Cited by 44 publications

(51 citation statements)

References 71 publications

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“…These data were confirmed by quantitative PCR with primers specific for SFB genes (Fig 3C). The presence of the Methylobacterium genus has been associated with contamination in samples with low biomass (Barton et al, 2006;Salter et al, 2014 Figure 3. Development of antinuclear antibodies in lymphotoxin-deficient mice is influenced by gut microbiota.…”

Section: Resultsmentioning

confidence: 99%

Commensal microbiota influence systemic autoimmune responses

et al. 2015

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Antinuclear antibodies are a hallmark feature of generalized autoimmune diseases, including systemic lupus erythematosus and systemic sclerosis. However, the processes underlying the loss of tolerance against nuclear self-constituents remain largely unresolved. Using mice deficient in lymphotoxin and Hox11, we report that approximately 25% of mice lacking secondary lymphoid organs spontaneously develop specific antinuclear antibodies. Interestingly, we find this phenotype is not caused by a defect in central tolerance. Rather, cell-specific deletion and in vivo lymphotoxin blockade link these systemic autoimmune responses to the formation of gut-associated lymphoid tissue in the neonatal period of life. We further demonstrate antinuclear antibody production is influenced by the presence of commensal gut flora, in particular increased colonization with segmented filamentous bacteria, and IL-17 receptor signaling. Together, these data indicate that neonatal colonization of gut microbiota influences generalized autoimmunity in adult life.

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Section: Resultsmentioning

confidence: 99%

Commensal microbiota influence systemic autoimmune responses

et al. 2015

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“…There is a growing recognition of the challenges in using metagenomic sequencing for detecting low abundance pathogens (Naccache et al 2013;Salter et al 2014). The abundance of microbial content found in the HGP data further demonstrates the ongoing challenge to differentiate clinically relevant low abundance microbial content from other sources of biological contamination.…”

Section: Discussionmentioning

confidence: 99%

Using populations of human and microbial genomes for organism detection in metagenomes

et al. 2015

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Identifying causative disease agents in human patients from shotgun metagenomic sequencing (SMS) presents a powerful tool to apply when other targeted diagnostics fail. Numerous technical challenges remain, however, before SMS can move beyond the role of research tool. Accurately separating the known and unknown organism content remains difficult, particularly when SMS is applied as a last resort. The true amount of human DNA that remains in a sample after screening against the human reference genome and filtering nonbiological components left from library preparation has previously been underreported. In this study, we create the most comprehensive collection of microbial and reference-free human genetic variation available in a database optimized for efficient metagenomic search by extracting sequences from GenBank and the 1000 Genomes Project. The results reveal new human sequences found in individual Human Microbiome Project (HMP) samples. Individual samples contain up to 95% human sequence, and 4% of the individual HMP samples contain 10% or more human reads. Left unidentified, human reads can complicate and slow down further analysis and lead to inaccurately labeled microbial taxa and ultimately lead to privacy concerns as more human genome data is collected.

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“…By consulting databases that catalog classical contaminant sequences, such as those present in DNA extraction kits (cf. Salter et al, 2014), indigenous minor or rare biosphere microorganisms can be identified with higher confidence. In some cases, oligotyping may differentiate closely related but distinct taxa (McLellan et al, 2013) as well as the respective origin of these taxa (i.e., from the subsurface vs. introduced at some point during the analysis) (cf.…”

Section: The Deep Biospherementioning

confidence: 99%