Contaminations in (meta)genome data: An open issue for the scientific community

In silico analysis of Ffp1, an ancestral Porphyromonas spp. fimbrillin, shows differences with Fim and Mfa

Background. Scant information is available regarding fimbrillins within the genus Porphyromonas, with the notable exception of those belonging to Porphyromonas gingivalis, which have been extensively researched for several years. Besides fim and mfa, a third P. gingivalis adhesin called filament-forming protein 1 (Ffp1) has recently been described and seems to be pivotal for outer membrane vesicle (OMV) production. Objective. We aimed to investigate the distribution and diversity of type V fimbrillin, particularly Ffp1, in the genus Porphyromonas. Methods. A bioinformatics phylogenomic analysis was conducted using all accessible Porphyromonas genomes to generate a domain search for fimbriae, using hidden Markov model profiles. Results. Ffp1 was identified as the sole fimbrillin present in all analysed genomes. After manual verification (i.e. biocuration) of both structural and functional annotations and 3D modelling, this protein was determined to be a type V fimbrillin, with a closer structural resemblance to a Bacteroides ovatus fimbrillin than to FimA or Mfa1 from P. gingivalis. Conclusion. It appears that Ffp1 is an ancestral fimbria, transmitted through vertical inheritance and present across all Porphyromonas species. Additional investigations are necessary to elucidate the biogenesis of Ffp1 fimbriae and their potential role in OMV production and niche adaptation.

Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host

BACKGROUND

Producing animal protein while reducing the animal's impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible.

RESULTS

Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets.

CONCLUSIONS

Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual's future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.

Metagenomic profiling pipelines improve taxonomic classification for 16S amplicon sequencing data

Most experiments studying bacterial microbiomes rely on the PCR amplification of all or part of the gene for the 16S rRNA subunit, which serves as a biomarker for identifying and quantifying the various taxa present in a microbiome sample. Several computational methods exist for analyzing 16S amplicon sequencing. However, the most-used bioinformatics tools cannot produce high quality genus-level or species-level taxonomic calls and may underestimate the potential accuracy of these calls. We used 16S sequencing data from mock bacterial communities to evaluate the sensitivity and specificity of several bioinformatics pipelines and genomic reference libraries used for microbiome analyses, concentrating on measuring the accuracy of species-level taxonomic assignments of 16S amplicon reads. We evaluated the tools DADA2, QIIME 2, Mothur, PathoScope 2, and Kraken 2 in conjunction with reference libraries from Greengenes, SILVA, Kraken 2, and RefSeq. Profiling tools were compared using publicly available mock community data from several sources, comprising 136 samples with varied species richness and evenness, several different amplified regions within the 16S rRNA gene, and both DNA spike-ins and cDNA from collections of plated cells. PathoScope 2 and Kraken 2, both tools designed for whole-genome metagenomics, outperformed DADA2, QIIME 2 using the DADA2 plugin, and Mothur, which are theoretically specialized for 16S analyses. Evaluations of reference libraries identified the SILVA and RefSeq/Kraken 2 Standard libraries as superior in accuracy compared to Greengenes. These findings support PathoScope and Kraken 2 as fully capable, competitive options for genus- and species-level 16S amplicon sequencing data analysis, whole genome sequencing, and metagenomics data tools.

Wochenende - modular and flexible alignment-based shotgun metagenome analysis

BACKGROUND

Shotgun metagenome analysis provides a robust and verifiable method for comprehensive microbiome analysis of fungal, viral, archaeal and bacterial taxonomy, particularly with regard to visualization of read mapping location, normalization options, growth dynamics and functional gene repertoires. Current read classification tools use non-standard output formats, or do not fully show information on mapping location. As reference datasets are not perfect, portrayal of mapping information is critical for judging results effectively.

RESULTS

Our alignment-based pipeline, Wochenende, incorporates flexible quality control, trimming, mapping, various filters and normalization. Results are completely transparent and filters can be adjusted by the user. We observe stringent filtering of mismatches and use of mapping quality sharply reduces the number of false positives. Further modules allow genomic visualization and the calculation of growth rates, as well as integration and subsequent plotting of pipeline results as heatmaps or heat trees. Our novel normalization approach additionally allows calculation of absolute abundance profiles by comparison with reads assigned to the human host genome.

CONCLUSION

Wochenende has the ability to find and filter alignments to all kingdoms of life using both short and long reads, and requires only good quality reference genomes. Wochenende automatically combines multiple available modules ranging from quality control and normalization to taxonomic visualization. Wochenende is available at https://github.com/MHH-RCUG/nf_wochenende .

A perspective on the role of lanthanides in biology: Discovery, open questions and possible applications

Because of their use in high technologies like computers, smartphones and renewable energy applications, lanthanides (belonging to the group of rare earth elements) are essential for our daily lives. A range of applications in medicine and biochemical research made use of their photo-physical properties. The discovery of a biological role for lanthanides has boosted research in this new field. Several methanotrophs and methylotrophs are strictly dependent on the presence of lanthanides in the growth medium while others show a regulatory response. After the first demonstration of a lanthanide in the active site of the XoxF-type pyrroloquinoline quinone methanol dehydrogenases, follow-up studies showed the same for other pyrroloquinoline quinone-containing enzymes. In addition, research focused on the effect of lanthanides on regulation of gene expression and uptake mechanism into bacterial cells. This review briefly describes the discovery of the role of lanthanides in biology and focuses on open questions in biological lanthanide research and possible application of lanthanide-containing bacteria and enzymes in recovery of these special elements.

Metascan: METabolic Analysis, SCreening and ANnotation of Metagenomes

Large scale next generation metagenomic sequencing of complex environmental samples paves the way for detailed analysis of nutrient cycles in ecosystems. For such an analysis, large scale unequivocal annotation is a prerequisite, which however is increasingly hampered by growing databases and analysis time. Hereto, we created a hidden Markov model (HMM) database by clustering proteins according to their KEGG indexing. HMM profiles for key genes of specific metabolic pathways and nutrient cycles were organized in subsets to be able to analyze each important elemental cycle separately. An important motivation behind the clustered database was to enable a high degree of resolution for annotation, while decreasing database size and analysis time. Here, we present Metascan, a new tool that can fully annotate and analyze deeply sequenced samples with an average analysis time of 11 min per genome for a publicly available dataset containing 2,537 genomes, and 1.1 min per genome for nutrient cycle analysis of the same sample. Metascan easily detected general proteins like cytochromes and ferredoxins, and additional pmoCAB operons were identified that were overlooked in previous analyses. For a mock community, the BEACON (F1) score was 0.72–0.93 compared to the information in NCBI GenBank. In combination with the accompanying database, Metascan provides a fast and useful annotation and analysis tool, as demonstrated by our proof-of-principle analysis of a complex mock community metagenome.

Geographically diverse canid sampling provides novel insights into pre-industrial microbiomes

Canine microbiome studies are often limited in the geographic and temporal scope of samples studied. This results in a paucity of data on the canine microbiome around the world, especially in contexts where dogs may not be pets or human associated. Here, we present the shotgun sequences of fecal microbiomes of pet dogs from South Africa, shelter and stray dogs from India, and stray village dogs in Laos. We additionally performed a dietary experiment with dogs housed in a veterinary medical school, attempting to replicate the diet of the sampled dogs from Laos. We analyse the taxonomic diversity in these populations and identify the underlying functional redundancy of these microbiomes. Our results show that diet alone is not sufficient to recapitulate the higher diversity seen in the microbiome of dogs from Laos. Comparisons to previous studies and ancient dog fecal microbiomes highlight the need for greater population diversity in studies of canine microbiomes, as modern analogues can provide better comparisons to ancient microbiomes. We identify trends in microbial diversity and industrialization in dogs that mirror results of human studies, suggesting future research can make use of these companion animals as substitutes for humans in studying the effects of industrialization on the microbiome.

The Dark mAtteR iNvestigator (DARN) tool: getting to know the known unknowns in COI amplicon data

The mitochondrial cytochrome C oxidase subunit I gene (COI) is commonly used in environmental DNA (eDNA) metabarcoding studies, especially for assessing metazoan diversity. Yet, a great number of COI operational taxonomic units (OTUs) or/and amplicon sequence variants (ASVs) retrieved from such studies do not get a taxonomic assignment with a reference sequence. To assess and investigate such sequences, we have developed the Dark mAtteR iNvestigator (DARN) software tool. For this purpose, a reference COI-oriented phylogenetic tree was built from 1,593 consensus sequences covering all the three domains of life. With respect to eukaryotes, consensus sequences at the family level were constructed from 183,330 sequences retrieved from the Midori reference 2 database, which represented 70% of the initial number of reference sequences. Similarly, sequences from 431 bacterial and 15 archaeal taxa at the family level (29% and 1% of the initial number of reference sequences respectively) were retrieved from the BOLD and the PFam databases. DARN makes use of this phylogenetic tree to investigate COI pre-processed sequences of amplicon samples to provide both a tabular and a graphical overview of their phylogenetic assignments. To evaluate DARN, both environmental and bulk metabarcoding samples from different aquatic environments using various primer sets were analysed. We demonstrate that a large proportion of non-target prokaryotic organisms, such as bacteria and archaea, are also amplified in eDNA samples and we suggest prokaryotic COI sequences to be included in the reference databases used for the taxonomy assignment to allow for further analyses of dark matter. DARN source code is available on GitHub at https://github.com/hariszaf/darn and as a Docker image at https://hub.docker.com/r/hariszaf/darn.

Inline index helped in cleaning up data contamination generated during library preparation and the subsequent steps

BACKGROUND

High-throughput sequencing involves library preparation and amplification steps, which may induce contamination across samples or between samples and the environment.

METHODS

We tested the effect of applying an inline-index strategy, in which DNA indices of 6 bp were added to both ends of the inserts at the ligation step of library prep for resolving the data contamination problem.

RESULTS

Our results showed that the contamination ranged from 0.29 to 1.25% in one experiment and from 0.83 to 27.01% in the other. We also found that contamination could be environmental or from reagents besides cross-contamination between samples.

CONCLUSIONS

Inline-index method is a useful experimental design to clean up the data and address the contamination problem which has been plaguing high-throughput sequencing data in many applications.

Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank

Genomic analyses are sensitive to contamination in public databases caused by incorrectly labeled reference sequences. Here, we describe Conterminator, an efficient method to detect and remove incorrectly labeled sequences by an exhaustive all-against-all sequence comparison. Our analysis reports contamination of 2,161,746, 114,035, and 14,148 sequences in the RefSeq, GenBank, and NR databases, respectively, spanning the whole range from draft to “complete” model organism genomes. Our method scales linearly with input size and can process 3.3 TB in 12 days on a 32-core computer. Conterminator can help ensure the quality of reference databases. Source code (GPLv3): https://github.com/martin-steinegger/conterminator