Taxonomic classification method for metagenomics based on core protein families with Core-Kaiju

Abstract

<jats:title>Abstract</jats:title> <jats:p>Characterizing species diversity and composition of bacteria hosted by biota is revolutionizing our understanding of the role of symbiotic interactions in ecosystems. Determining microbiomes diversity implies the assignment of individual reads to taxa by comparison to reference databases. Although computational methods aimed at identifying the microbe(s) taxa are available, it is well known that inferences using different methods can vary widely depending on various biases. In this study, we first apply and compare different bioinformatics methods based on 16S ribosomal RNA gene and shotgun sequencing to three mock communities of bacteria, of which the compositions are known. We show that none of these methods can infer both the true number of taxa and their abundances. We thus propose a novel approach, named Core-Kaiju, which combines the power of shotgun metagenomics data with a more focused marker gene classification method similar to 16S, but based on emergent statistics of core protein domain families. We thus test the proposed method on various mock communities and we show that Core-Kaiju reliably predicts both number of taxa and abundances. Finally, we apply our method on human gut samples, showing how Core-Kaiju may give more accurate ecological characterization and a fresh view on real microbiomes.</jats:p>

Microbial Community Dynamics during Biodegradation of Crude Oil and Its Response to Biostimulation in Svalbard Seawater at Low Temperature

“…Moreover, the reclassification of species Pseudomonas salina and Pseudomonas sabulinigri, found to be abundant in this experiment, into a new genus, Neopseudomonas, has been recently suggested due to their high variation from the core of the Pseudomonas genus [49]. In this study, the metagenome-based classifiers also yielded substantially higher numbers of genera containing hydrocarbon degraders compared to the amplicon-based approach, which may be related to differences in sequencing depth between sequencing methods but also to the known tendency of Kaiju and Kraken2 to predict a large number of low-proportion false-positive taxa [12,43]. The comparison of different sequencing, classification, and quantitative estimations obtained by different analytical tools highlights that the choice of analytical method has a strong effect on practical decisions, such as the applicability of the oil bioremediation method in seawater, made based on microbial community estimations.…”

“…This discrepancy, characterized by lower proportions of Proteobacteria (especially Gammaproteobacteria) and higher proportions of Bacteroidetes in amplicon-based data compared to metagenome data, seems to be consistent in describing bacterial communities from different water habitats, such as freshwater [45] and Mediterranean seawater [46]. The deviation of amplicon-based taxa proportion estimates compared to metagenome datasets could be attributed to a combination of several factors: the coverage of utilized primers, general PCR bias, variance of copy numbers of the 16S rRNA genes between different taxa, discrepancy of taxon ranks between reference databases, and different sizes and curation levels of reference databases [12,45]. Different metagenome-based classification methods also yielded substantial differences in the estimated proportions of individual taxa at all taxonomic levels, and the overlap of 50 prominent genera between all four metagenome-based classification strategies slightly exceeded 50%.…”

“…In recent years, the rapid development of microbial analysis tools, especially whole DNA metagenomics-based approaches enabling simultaneous retrieval of both taxonomic and functional information, has provided unprecedented amounts of information for use in bioremediation strategy development [12]. Knowledge of the diversity and structure of microbial communities in oil-contaminated Arctic seawater has expanded with several amplicon-or metagenome-based community sequencing studies using different taxonomic classification methods and reference databases [10,11,[13][14][15].…”

“…Knowledge of the diversity and structure of microbial communities in oil-contaminated Arctic seawater has expanded with several amplicon-or metagenome-based community sequencing studies using different taxonomic classification methods and reference databases [10,11,[13][14][15]. The determination of microbiome structure and diversity is based on the assignment of individual reads to taxa by comparing them to reference databases [12], but a "gold standard" method has yet to be established. Hence, for a more realistic assessment of oil biodegradation potential and the realization of bioremediation approaches, information on the possible occurrence and nature of technical biases introduced to the diversity and structure estimates of microbial communities in Arctic seawater by widely used classifiers is needed.…”

Comparative Analysis of 16S rRNA Gene and Metagenome Sequencing in Pediatric Gut Microbiomes

“…Moreover, because shotgun metagenomics does not rely on the characterization of a gene that is uniquely present in microbes to assign taxonomy, it can be used to investigate non-microbial parts of the microbiome (e.g., fungi, viruses, and micro-eukaryotes) that do not have the 16S rRNA gene. These reads can be used to assign taxonomy using different methods: comparison of marker genes ( Segata et al, 2012 ; Tovo et al, 2020 ), species-specific k-mer comparison ( Wood et al, 2019 ), and assembly followed by whole genome alignment ( Couronne et al, 2003 ). Metagenomic reads may also be used to generate assemblies from multiple metagenomic studies, yielding higher resolution assemblies that provide further insight into microbial diversity ( Wilkins et al, 2019 ).…”