General bacteria and archaea 16S-rRNA (515Fmod-806Rmod) for Illumina amplicon sequencing v2 (protocols.io.bnf7mbrn)

Abstract Background Recent studies suggested the existence of (poly-)microbial infections in human brains. These have been described either as putative pathogens linked to the neuro-inflammatory changes seen in Parkinson’s disease (PD) and Alzheimer’s disease (AD) or as a “brain microbiome” in the context of healthy patients’ brain samples. Methods Using 16S rRNA gene sequencing, we tested the hypothesis that there is a bacterial brain microbiome. We evaluated brain samples from healthy human subjects and individuals suffering from PD (olfactory bulb and pre-frontal cortex), as well as murine brains. In line with state-of-the-art recommendations, we included several negative and positive controls in our analysis and estimated total bacterial biomass by 16S rRNA gene qPCR. Results Amplicon sequencing did detect bacterial signals in both human and murine samples, but estimated bacterial biomass was extremely low in all samples. Stringent reanalyses implied bacterial signals being explained by a combination of exogenous DNA contamination (54.8%) and false positive amplification of host DNA (34.2%, off-target amplicons). Several seemingly brain-enriched microbes in our dataset turned out to be false-positive signals upon closer examination. We identified off-target amplification as a major confounding factor in low-bacterial/high-host-DNA scenarios. These amplified human or mouse DNA sequences were clustered and falsely assigned to bacterial taxa in the majority of tested amplicon sequencing pipelines. Off-target amplicons seemed to be related to the tissue’s sterility and could also be found in independent brain 16S rRNA gene sequences. Conclusions Taxonomic signals obtained from (extremely) low biomass samples by 16S rRNA gene sequencing must be scrutinized closely to exclude the possibility of off-target amplifications, amplicons that can only appear enriched in biological samples, but are sometimes assigned to bacterial taxa. Sequences must be explicitly matched against any possible background genomes present in large quantities (i.e., the host genome). Using close scrutiny in our approach, we find no evidence supporting the hypothetical presence of either a brain microbiome or a bacterial infection in PD brains.

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Bacterial Diversity of Breast Milk in Healthy Spanish Women: Evolution from Birth to Five Years Postpartum

Nutrients ◽

10.3390/nu13072414 ◽

2021 ◽

Vol 13 (7) ◽

pp. 2414

Author(s):

Laura Sanjulián ◽

Alexandre Lamas ◽

Rocío Barreiro ◽

Alberto Cepeda ◽

Cristina A. Fente ◽

...

Keyword(s):

Breast Milk ◽

16S Rrna ◽

Human Milk ◽

Alpha Diversity ◽

Amplicon Sequencing ◽

Maternal Body Mass Index ◽

16S Rrna Amplicon Sequencing ◽

Spanish Women ◽

Calcium Magnesium ◽

Abundant Genus

The objective of this work was to characterize the microbiota of breast milk in healthy Spanish mothers and to investigate the effects of lactation time on its diversity. A total of ninety-nine human milk samples were collected from healthy Spanish women and were assessed by means of next-generation sequencing of 16S rRNA amplicons and by qPCR. Firmicutes was the most abundant phylum, followed by Bacteroidetes, Actinobacteria, and Proteobacteria. Accordingly, Streptococcus was the most abundant genus. Lactation time showed a strong influence in milk microbiota, positively correlating with Actinobacteria and Bacteroidetes, while Firmicutes was relatively constant over lactation. 16S rRNA amplicon sequencing showed that the highest alpha-diversity was found in samples of prolonged lactation, along with wider differences between individuals. As for milk nutrients, calcium, magnesium, and selenium levels were potentially associated with Streptococcus and Staphylococcus abundance. Additionally, Proteobacteria was positively correlated with docosahexaenoic acid (DHA) levels in breast milk, and Staphylococcus with conjugated linoleic acid. Conversely, Streptococcus and trans-palmitoleic acid showed a negative association. Other factors such as maternal body mass index or diet also showed an influence on the structure of these microbial communities. Overall, human milk in Spanish mothers appeared to be a complex niche shaped by host factors and by its own nutrients, increasing in diversity over time.

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Ultra-accurate microbial amplicon sequencing with synthetic long reads

Microbiome ◽

10.1186/s40168-021-01072-3 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Benjamin J. Callahan ◽

Dmitry Grinevich ◽

Siddhartha Thakur ◽

Michael A. Balamotis ◽

Tuval Ben Yehezkel

Keyword(s):

Microbial Community ◽

16S Rrna ◽

Amplicon Sequencing ◽

Species Level ◽

Full Length ◽

16S Rrna Genes ◽

Rrna Genes ◽

Strain Identification ◽

Long Reads ◽

Long Read

Abstract Background Out of the many pathogenic bacterial species that are known, only a fraction are readily identifiable directly from a complex microbial community using standard next generation DNA sequencing. Long-read sequencing offers the potential to identify a wider range of species and to differentiate between strains within a species, but attaining sufficient accuracy in complex metagenomes remains a challenge. Methods Here, we describe and analytically validate LoopSeq, a commercially available synthetic long-read (SLR) sequencing technology that generates highly accurate long reads from standard short reads. Results LoopSeq reads are sufficiently long and accurate to identify microbial genes and species directly from complex samples. LoopSeq perfectly recovered the full diversity of 16S rRNA genes from known strains in a synthetic microbial community. Full-length LoopSeq reads had a per-base error rate of 0.005%, which exceeds the accuracy reported for other long-read sequencing technologies. 18S-ITS and genomic sequencing of fungal and bacterial isolates confirmed that LoopSeq sequencing maintains that accuracy for reads up to 6 kb in length. LoopSeq full-length 16S rRNA reads could accurately classify organisms down to the species level in rinsate from retail meat samples, and could differentiate strains within species identified by the CDC as potential foodborne pathogens. Conclusions The order-of-magnitude improvement in length and accuracy over standard Illumina amplicon sequencing achieved with LoopSeq enables accurate species-level and strain identification from complex- to low-biomass microbiome samples. The ability to generate accurate and long microbiome sequencing reads using standard short read sequencers will accelerate the building of quality microbial sequence databases and removes a significant hurdle on the path to precision microbial genomics.

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Connecting structure to function with the recovery of over 1000 high-quality metagenome-assembled genomes from activated sludge using long-read sequencing

Nature Communications ◽

10.1038/s41467-021-22203-2 ◽

2021 ◽

Vol 12 (1) ◽

Cited By ~ 2

Author(s):

Caitlin M. Singleton ◽

Francesca Petriglieri ◽

Jannie M. Kristensen ◽

Rasmus H. Kirkegaard ◽

Thomas Y. Michaelsen ◽

...

Keyword(s):

16S Rrna ◽

Wastewater Treatment Plants ◽

In Situ Hybridisation ◽

Amplicon Sequencing ◽

Rrna Genes ◽

Fluorescence In Situ Hybridisation ◽

Sequencing Data ◽

High Quality ◽

16S Rrna Amplicon Sequencing ◽

Long Read

AbstractMicroorganisms play crucial roles in water recycling, pollution removal and resource recovery in the wastewater industry. The structure of these microbial communities is increasingly understood based on 16S rRNA amplicon sequencing data. However, such data cannot be linked to functional potential in the absence of high-quality metagenome-assembled genomes (MAGs) for nearly all species. Here, we use long-read and short-read sequencing to recover 1083 high-quality MAGs, including 57 closed circular genomes, from 23 Danish full-scale wastewater treatment plants. The MAGs account for ~30% of the community based on relative abundance, and meet the stringent MIMAG high-quality draft requirements including full-length rRNA genes. We use the information provided by these MAGs in combination with >13 years of 16S rRNA amplicon sequencing data, as well as Raman microspectroscopy and fluorescence in situ hybridisation, to uncover abundant undescribed lineages belonging to important functional groups.

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Advantage of 16S rRNA amplicon sequencing in Helicobacter pylori diagnosis

Helicobacter ◽

10.1111/hel.12790 ◽

2021 ◽

Author(s):

Boldbaatar Gantuya ◽

Hashem B. El Serag ◽

Batsaikhan Saruuljavkhlan ◽

Dashdorj Azzaya ◽

Takashi Matsumoto ◽

...

Keyword(s):

Helicobacter Pylori ◽

16S Rrna ◽

Amplicon Sequencing ◽

16S Rrna Amplicon Sequencing

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Meta-Apo improves accuracy of 16S-amplicon-based prediction of microbiome function

BMC Genomics ◽

10.1186/s12864-020-07307-1 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Gongchao Jing ◽

Yufeng Zhang ◽

Wenzhi Cui ◽

Lu Liu ◽

Jian Xu ◽

...

Keyword(s):

16S Rrna ◽

Large Scale ◽

Low Cost ◽

Human Microbiome ◽

Amplicon Sequencing ◽

Training Sample ◽

Rrna Gene ◽

16S Amplicon Sequencing ◽

Cross Platform ◽

Functional Profiles

Abstract Background Due to their much lower costs in experiment and computation than metagenomic whole-genome sequencing (WGS), 16S rRNA gene amplicons have been widely used for predicting the functional profiles of microbiome, via software tools such as PICRUSt 2. However, due to the potential PCR bias and gene profile variation among phylogenetically related genomes, functional profiles predicted from 16S amplicons may deviate from WGS-derived ones, resulting in misleading results. Results Here we present Meta-Apo, which greatly reduces or even eliminates such deviation, thus deduces much more consistent diversity patterns between the two approaches. Tests of Meta-Apo on > 5000 16S-rRNA amplicon human microbiome samples from 4 body sites showed the deviation between the two strategies is significantly reduced by using only 15 WGS-amplicon training sample pairs. Moreover, Meta-Apo enables cross-platform functional comparison between WGS and amplicon samples, thus greatly improve 16S-based microbiome diagnosis, e.g. accuracy of gingivitis diagnosis via 16S-derived functional profiles was elevated from 65 to 95% by WGS-based classification. Therefore, with the low cost of 16S-amplicon sequencing, Meta-Apo can produce a reliable, high-resolution view of microbiome function equivalent to that offered by shotgun WGS. Conclusions This suggests that large-scale, function-oriented microbiome sequencing projects can probably benefit from the lower cost of 16S-amplicon strategy, without sacrificing the precision in functional reconstruction that otherwise requires WGS. An optimized C++ implementation of Meta-Apo is available on GitHub (https://github.com/qibebt-bioinfo/meta-apo) under a GNU GPL license. It takes the functional profiles of a few paired WGS:16S-amplicon samples as training, and outputs the calibrated functional profiles for the much larger number of 16S-amplicon samples.

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