Metagenomic Information Recovery from Human Stool Samples Is Influenced by Sequencing Depth and Profiling Method

Abstract

Sequencing of the 16S rRNA gene (16S) has long been a go-to method for microbiome characterization due to its accessibility and lower cost compared to shotgun metagenomic sequencing (SMS). However, 16S sequencing rarely provides species-level resolution and cannot provide direct assessment of other taxa (e.g., viruses and fungi) or functional gene content. Shallow shotgun metagenomic sequencing (SSMS) has emerged as an approach to bridge the gap between 16S sequencing and deep metagenomic sequencing. SSMS is cost-competitive with 16S sequencing, while also providing species-level resolution and functional gene content insights. In the present study, we evaluated the effects of sequencing depth on marker gene-mapping- and alignment-based annotation of bacteria in healthy human stool samples. The number of identified taxa decreased with lower sequencing depths, particularly with the marker gene-mapping-based approach. Other annotations, including viruses and pathways, also showed a depth-dependent effect on feature recovery. These results refine the understanding of the suitability and shortcomings of SSMS, as well as annotation tools for metagenomic analyses in human stool samples. Results may also translate to other sample types and may open the opportunity to explore the effect of sequencing depth and annotation method.

Longitudinal comparison of the developing gut virome in infants and their mothers

“…As the children aged, Microviridae--primarily Gokoshuviruses and poophages-became the dominant phages in the gut (Liang et al, 2020; Lim et al, 2020; Takahashi et al, 2000). While little is known about the recently identified poophages (Santiago-Rodriguez et al, 2020), the Gokushoviruses have been recently described (Creasy et al, 2018; Székely and Breitbart, 2016; Kirchberger & Ochman, 2020). These phages were initially only identified in Bdellovibrio and Chlamydophila bacteria but have now been identified in Escherichia coli , surviving in the cytoplasm (Kirchberger & Ochman, 2020).…”

Characterizing the limits of shallow shotgun metagenomics for taxonomic profiling of human gut microbiota in clinical studies

“…Previous works suggest that species level taxonomic profiles obtained by mapping reads on reference genomes were highly similar to deep WGS, and that the resulting α-diversity metrics were barely impacted by limiting the sequencing depth to ∼ 500K − 1M reads/sample [12] [15] [16] [17]. Furthermore, mapping on reference genomes was more efficient than on a marker genes catalog in the context of SSM [15]. By contrast, the depth required for functional analysis depends on the level of granularity of the analysis: 500K reads/sample may be sufficient to identify KEGG orthology groups [12], but 3M to 5M reads/sample are necessary to accurately detect genes and pathways [15] [18], and very deep sequencing up to ∼ 60 − 80M reads/sample is needed to study antimicrobial resistance genes [16] [19].…”

Exploring Gut Microbiota in Patients with Colorectal Disease Based on 16S rRNA Gene Amplicon and Shallow Metagenomic Sequencing

“…The shallow metagenomic sequencing (SMS) strategy has been preferred to the 16S rRNA gene amplicon strategy in certain microbiome studies (Zhu et al, 2021). The use of the SMS strategy may decrease the costs associated with metagenomic sequencing strategy (Hillmann et al, 2018;Santiago-Rodriguez et al, 2020). A comparative analysis of infant gut microbiota indicated that 16S rRNA gene amplicon and metagenomic sequencing approaches can provide similar alpha and beta diversity of the gut microbiota (Peterson et al, 2021).…”