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Download references. Green regions V4, V5, and V6 are associated with the shortest geodesic distance, which implies that they may be the optimal choice for phylogeny-related analyses, including phylogenetic analysis of novel bacteria phyla. Figure 2. Illustration of different variable regions Yang et al.
Since 16S rRNA gene is conserved in bacteria, and contain hypervariable regions that can provide species-specific signature sequences, 16S rRNA sequencing is widely used in identification of bacteria and phylogenetic studies. It has been widely applied in basic research, as well as medical, forensic, agricultural, and industrial microbiology. Figure 3.
At the same time, computational methods have made it possible to distinguish between legitimate vs. These technological and methodological advances mean researchers now have the potential to perform high-throughput sequencing that can accurately detect single-nucleotide variants across the entire 16S gene.
Although it is tempting to assume that single-nucleotide variants may represent distinct, closely related taxa, we caution against this overly simplistic interpretation due to the fact that many bacterial genomes contain multiple polymorphic copies of the 16S gene 12 , 13 , We aligned PacBio full-length 16S sequences to a reference database containing a single representative 16S sequence for each member of our mock community and used the alignment statistics to evaluate the accuracy of this sequencing approach.
However, we did observe a coincidence of deletion errors with the location homopolymer runs in our reference sequences Supplementary Fig. We subsequently validated deletions within the Escherichia coli 16S gene using Illumina whole genome shotgun WGS sequencing, which demonstrated that only one of the deletions occurring in PacBio sequences was genuine Supplementary Fig. For example, reads aligned to the E. MG showed a substitution profile, which mirrored exactly that predicted by aligning all seven of the 16S sequences known to be present in this genome 15 Fig.
We were further able to validate the stoichiometry of these nucleotide substitutions by quantifying variation in comparably aligned Illumina WGS reads Fig. Alignments to other reference sequences in our mock community showed a similar trend of abundant substitutions localized to specific base positions along the 16S gene, although we note that the signal-to-noise ratio increased significantly when the 16S gene in question had fewer than aligned reads Supplementary Fig.
Polymorphisms in E. Magnified regions show respective positions in the alignment of all seven 16S genes present in the E. Dashed lines indicate the expected proportion of nucleotide substitutions, given there are seven 16S gene copies within each genome.
The observation that long-read sequencing can identify 16S polymorphisms within the same genome has important implications. First, it demonstrates that it is not valid to assume that high-throughput sequence reads differing by one or few nucleotides represent a distinct taxa 6 , Within a single genome, two or more 16S sequences may be identical, whereas others may be unique. Correspondingly, some homologous 16S loci may retain identical sequence between two closely related strains, whereas others may have diverged at one or few nucleotide positions.
In this context, any community-level or taxonomic interpretation of 16S data should ideally account for the fact that the relative abundance of 16S sequences arising from very closely related taxa will reflect a linear combination of i the frequency with which each unique sequence is represented across genomes and ii the relative abundance of the genomes for each taxon.
Second, although intragenomic 16S sequence variation complicates community-level analysis, it also has the potential to increase the power of the 16S gene to discriminate between closely related taxa, because it enables sequence-based comparison to extend across multiple divergent loci. For example, sufficient nucleotide variation exists to distinguish E.
Thus, we argue that, when appropriately accounted for, multiple polymorphic 16S copies are not an inconvenience to be overlooked, rather they will enable the 16S gene to be used in strain-level microbiome analysis.
We also note that the power of intragenomic 16S sequence variation to discriminate closely related taxa is likely to diminish when partial 16S sequences are used. For example, SNPs distinguishing the E. Microbiome communities are often complex, existing in diverse biochemical environments e.
This complexity is not well represented in either in-silico or mock community experiments. We therefore performed an additional experiment to demonstrate that sequencing of the full 16S gene while accounting for intragenomic 16S SNPs can resolve closely related bacterial taxa in vivo. To evaluate the extent to which each of these sequencing approaches can resolve closely related taxa, we focused on the genus Bacteroides.
In addition to being abundant in the human gut, this genus is highly diverse, containing multiple species that can exert both good and bad effects on human health It has also been used previously as a model taxon for demonstrating the utility of the 16S gene for high-resolution taxonomic analysis When we calculated Bacteroides abundance at the genus level, V1—V9 sequencing and V1—V3 sequencing produced comparable results.
However, species-level quantification via mWGS sequencing revealed far greater diversity, with a different Bacteroides species dominant in the gut of each individual Fig. Based on these results we conclude that, when used in conjunction with an appropriate identity threshold e. We further note that, although full-length 16S sequencing may be optimal for species-level analysis, highly informative variable regions e. Detecting Bacteroides in human stool samples.
Abundance is shown for the most abundant species as quantified by mWGS for abundance estimates of all Bacteroides species detected by each platform, see Supplementary Table 5. Profiles are shown for the two stool samples with high B. In both c and d , nucleotide substitutions were identified relative to a single reference 16S gene for B.
Taking advantage of the fact that Bacteroides vulgatus was present at high relative abundance in two of our human gut microbiome samples, we next asked whether intragenomic variation between 16S gene copies could be detected in vivo. We aligned every full-length sequence classified as belonging to our B. We then compared the resulting nucleotide substitution profiles Fig. The majority of nucleotide variation present in our in vivo generated B. Although we did not know the true number of B. Variation also existed at specific loci that could potentially indicate meaningful differences between the in vivo and ATCC reference genomes.
These numbers correspond closely to the numbers expected if a polymorphism were present six and five out of seven 16S genes, respectively. In conclusion, we show that full-length 16S sequencing of the human gut microbiome can accurately resolve single-nucleotide substitutions that reflect intragenomic variation between 16S gene copies. The presence of such variation indicates that 16S sequences must be clustered to reflect meaningful taxonomic units.
Analysis of microbial communities at these taxonomic levels promises to provide a very different perspective to the one afforded by genus-level abundance estimates. Having demonstrated that it is possible to resolve intragenomic copy variants in vivo, we next sought to establish the extent to which such copy variants appear in taxa commonly found within the human gut microbiome.
We further sought to establish whether such profiles can routinely be used to distinguish between strains of the same species. We cultured taxa from the gut microbiome of the healthy individuals depicted in Fig. We subsequently performed full-length 16S gene sequencing on isolates and aligned sequenced reads to identify nucleotide substitutions characteristic of intragenomic 16S gene copy variants.
In total, of sequenced isolates 54 of 61 OTUs had one or more SNP, indicating the presence of 16S gene polymorphisms, and unique SNP profiles were identified when accounting for potential sequencing error Fig. Intragenomic 16S gene polymorphisms in human gut microbiome isolates.
SNP locations were identified through phasing full-length 16S gene sequences generated for each individual isolate. X -axis denotes position along the 16S gene. Y -axis denotes individual isolates clustered based on their inferred phylogeny. Dark blue region indicates the location of a polymorphism. For clarity, a maximum of five isolates belonging to the same species are shown.
For details of nucleotide substitution profiles for all sequenced isolates, see Supplementary Data 2. For each species, two isolate nucleotide substitution profiles are shown; however, additional examples can be found in Supplementary Data 2. Dashed lines indicate the expected proportion of nucleotide substitutions, given the number of 16S gene copies predicted for each genome. Notably, comparing SNP profiles for isolates assigned to the same OTU frequently revealed differences in the frequency of SNPs that were suggestive of differences in intragenomic 16S gene copies between closely related taxa.
Examples of different substitution profiles are shown for three taxa Fig. In conclusion, we show that many of the culturable members of the human gut microbiome frequently possess 16S gene polymorphisms, which, when properly accounted for, have the potential to resolve strains of the same species. Here, we have presented the results of four experiments that collectively demonstrate the taxonomic resolution achievable in the current 16S gene-based microbiome studies.
In particular, we have focused on whether sequencing the full 16S gene while accounting for 16S gene copy variants makes the detection of bacterial species and strains a realistic prospect. High-throughput sequencing of the full 16S gene with sufficient accuracy to discriminate between copy variants has until recently been constrained by a lack of available sequencing technologies.
The advent of long-read approaches on Nanopore 4 and PacBio 3 platforms has changed this. Several previous studies have provided detailed evaluation of PacBio CCS for targeted amplicon sequencing 21 , 22 , 23 , 24 , and some have demonstrated this approach is capable of improving discrimination between bacterial species present in microbial communities 24 , Although our study necessarily addresses important technical details, its goal is to explore the full potential of the 16S gene for discriminating bacterial taxa rather than re-evaluate a particular sequencing technology.
In addressing this goal, however, we highlighted the prevalence of sequencing errors in PacBio CCS reads as a factor that limits the ability to resolve highly similar sequences. A particular problem was deletion errors coincident with homopolymer runs in the target sequence.
Although random sequencing errors may be overcome by increased sequencing depths, such systematic errors may occur at a given frequency and hence may not be improved by greater sequencing effort. Future work would benefit from explicitly determining how recent advances in sequencing platforms, chemistries, and computational approaches can improve these errors.
Given the emphasis of our study, we chose to overcome such platform-specific errors by focusing on substitutions and ignoring the contribution of insertions and deletions to intragenomic 16S gene copy polymorphisms. The presence of a single deletion in one of the seven E. MG 16S genes demonstrates that this is an imperfect approach.
Therefore, current limitations that may be specific to the sequencing approach used do not invalidate our investigation of full-length 16S gene sequencing as a viable method for discriminating between species and strains.
In the ensuing discussion, we address several important conclusions from this investigation. First, we conclude that sequencing the entire 16S gene provides real and significant advantages over sequencing commonly targeted variable regions.
Assuming our in-silico experimental dataset provided a reasonable approximation of bacterial species, we conclude that most variable regions are sufficient to identify genera, but they are unlikely to ever adequately discriminate between species.
In consequence, irrespective of the resolution at which they are clustered, variable regions will likely underrepresent the true species richness of a microbiome sample. Second, we argue that intragenomic variation in the 16S gene should not be ignored. In particular, we caution against the conclusion that quantifying exact sequence variants ESVs is preferential to more traditional OTU-based approaches Given that the majority of bacterial isolates we sequenced contained multiple, variant copies of the 16S gene within their genome, this assumption may not always be correct.
The potential for 16S copy variants to bias estimates of bacterial diversity is well established 27 , and we and others 25 have shown the number of unique sequences detected in a mock community is far greater than the number of species known to be present. We note that, similar to OTUs, ESVs do not need to accurately represent individual taxa, to be useful and informative However, our results show that quantifying ESVs will likely overestimate species richness, just as OTUs based on variable regions may underestimate it.
As a means of quantifying individual taxa, ESVs may also be limited, due to the fact that multiple unique sequences originating from the same genome are not necessarily present at the same relative abundance e.
Although these caveats do not preclude the use of ESVs as useful indicators of either taxonomy or diversity, they must necessarily be accounted for when interpreting results.
Third, we argue that appropriate clustering of intragenomic 16S gene sequence variation can in fact be a valuable method by which to provide accurate representation of bacterial species. Previous studies have reported intragenomic 16S gene polymorphisms as a problem that potentially confounds bacterial species richness estimates 25 , By contrast, we demonstrate that, when handled correctly, the presence of such polymorphisms in full-length 16S reads has the potential to aid in taxonomic classification.
Finally, by extensive culturing of bacteria present in the human gut microbiome, we provide support for the observation that intragenomic 16S gene copy variants are present in a significant proportion of bacterial taxa 12 , In situ hybridization can not only determine the morphological characteristics and abundance of microbes, but also analyze their spatial distribution.
The ribose type of microorganism gene was determined by observing the enzyme cut electrophoresis atlas and numerical analysis, and then compared with the data in the ribosome library, and the relationship between the microbial composition of the samples and the species of different microorganisms was analyzed.
Some of the gene sequences remain stable in the long course of evolution. Nucleotide probes have been applied to the identification of clinical bacteria, sequence analysis, molecular classification of bacteria, and phylogenetic analysis. Ribosomal rRNA is essential for the survival of all living things. At the same time, its conservatism is relative.
There are different degrees of difference in the families, genera and species of different bacteria, so 16S rRNA can be used as both It is a marker for bacterial classification and can be used as a target molecule for detection and identification of clinical pathogens.
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