Comparative analyses of 18S rDNA regions for assessing the eukaryotic community in ancient lake sediment samples

Comparative analysis of size-fractional eukaryotic microbes in subtropical riverine systems inferred from 18S rRNA gene V4 and V9 regions

Nucleotide positions in the hypervariable V4 and V9 regions of the small subunit (SSU)-rDNA locus are normally difficult to align and are usually removed before standard phylogenetic analyses. Yet, with next-generation sequencing data, amplicons of these regions are all that are available to answer ecological and evolutionary questions that rely on phylogenetic inferences. With ciliates, we asked how inclusion of the V4 or V9 regions, regardless of alignment quality, affects tree topologies using distinct phylogenetic methods (including PairDist that is introduced here). Results show that the best approach is to place V4 amplicons into an alignment of full-length Sanger SSU-rDNA sequences and to infer the phylogenetic tree with RAxML. A sliding window algorithm as implemented in RAxML shows, though, that not all nucleotide positions in the V4 region are better than V9 at inferring the ciliate tree. With this approach and an ancestral-state reconstruction, we use V4 amplicons from European nearshore sampling sites to infer that rather than being primarily terrestrial and freshwater, colpodean ciliates may have repeatedly transitioned from terrestrial/freshwater to marine environments.

MALDI-TOF MS analysis of Y-SNPs in ancient samples

The human gut microbiota has become the subject of an increasing amount of attention, due to an emerging understanding of its role in maintaining health throughout our lives. Since only a small proportion of the gut bacteria can be quantified using traditional plate culturing methods, culture-independent approaches are required for determining the structure of complex microbial communities. To avoid cloning bias and low phylotype coverage that affects amplicon cloning and sequencing strategies, high-throughput methods such as phylogenetic arrays and massively parallel sequencing are now being used to find more than just the most abundant taxa, at significantly lower costs and higher speeds. The target for these methods is the 16S ribosomal RNA gene that is present in all prokaryotes. Since the gene is too long to be sequenced using high-throughput methods, regions of high variability (from V1 - V9) are selected for amplification and either direct sequencing, or hybridization against phylogenetic microarrays. In our recent study1 we compared sequencing of amplified V4 and V6 regions using 454 FLX Pyrosequencing2 with the HITChip, an oligonucleotide microarray for taxonomic profiling of human intestinal tract communities based on concatenations of known V1 and V6 regions.3 We found good correlations between the phylogenetic classifications stemming from the two technologies, especially at lower-order ranks (phylum, class, order, and to a lesser extent, family), which indicates high robustness of both approaches. However, the V6 regions proved to be much less suitable for taxonomic classification than the V4 region, probably due to this region simply being too variable. Although this study was, to our knowledge, the deepest sequencing of single gastrointestinal samples reported to date, the microbial richness levels had still not leveled out, with up to 1,800 unique phylotypes detected in one community. Encouragingly for studies with lower sequencing coverage per sample, we also noticed that a fifth of the sequencing depth (40,000 as opposed to 200,000 reads) was sufficient for capturing a majority of microbial diversity within a sample.

Over the last fifteen years, there has been a large increase in the literature on microbial community composition in marine sediment (Inagaki et al., 2006, 2015; Biddle et al., 2012; Briggs et al., 2012; Breucker et al., 2013; Lloyd, 2014; Teske et al., 2014; Nunoura et al., 2016; Walsh et al., 2016; Petro et al., 2017; Harrison et al., 2018; Hoshino et al., 2020), and seawater (Quaiser et al., 2011; Hamdan et al., 2013; Walsh et al., 2016; Medina-Silva et al., 2018; Mestre et al., 2018; Quero et al., 2019). As molecular study of these biomes progresses, and the tools available for detailed analyses expand, it has become important to evaluate those tools for their effectiveness and limitations. By combining environmental microbial investigations with evaluation of some of the most common genetic protocols, I have characterized microbial diversity and community composition in (i) Pacific, Atlantic, and Arctic seawater and (ii) Pacific and Atlantic sediment, and I have identified the common results obtainable using (i) two different 16S ribosomal RNA gene (rRNA) hypervariable regions of interest, and (ii) the two amplicon analysis pipelines most commonly used to determine microbial diversity and community composition. My first manuscript, “Influence of 16S rRNA Hypervariable Region on Estimates of Bacterial Diversity and Community Composition in Seawater and Marine Sediment”, looks at the bacterial diversity and community composition of deep-ocean sediment and overlying seawater from one site in the Central North Atlantic and one site in the Equatorial Pacific. In each case, we amplified both the V4 and V6 hypervariable regions of the 16S rRNA gene of each sample and clustered the sequences into operational taxonomic units (OTUs) of 97% similarity. In doing so, we determined that while OTU-level diversity metrics and community composition are quite different between the two tags, (i) vertical patterns of relative diversity are broadly the same, (ii) community composition is very similar for both tags at the class level, and (iii) while the open ocean communities are very similar between the Pacific and Atlantic oceans, the sediment communities of each ocean differ greatly. My second manuscript, “Patterns of Relative Bacterial Richness and Community Composition in Seawater and Marine Sediment are Robust for both Operational Taxonomic Units and Amplicon Sequence Variants”, examines how the choice of bioinformatic analysis pipeline affects characterization of taxonomic richness and community composition in seawater (from 12 sites in the North Atlantic Ocean and Canadian Arctic) and sediment

Secondary structure construction and molecular identification of rRNA 18S V4 region E23-5–E23-6 of parasitic lice of Hominidae

环境样本中微型和微微型浮游植物高通量测序的引物优化

Sequences of the 18S rDNAs from two Collembolan insects: shorter sequences in the V4 and V7 regions

The microflora of a kefir grain was identified using a polymerase chain reaction-based strategy combined with 16S rRNA gene sequencing. DNA was extracted from the kefir grain and amplified in its 16S rDNA V1 and V2 regions. To guarantee a good representation of the overall lactic acid bacteria populations, DNA amplification was performed separately with primers specific either to the dominant or to the less abundant bacterial groups. The amplified fragments were cloned in Escherichia coli and then sequenced. Sequences of the V1 region were gathered into 5 groups of similarity and identified by aligning with the sequences of a public library. The V1 region allowed the identification of Lactobacillus kefiranofaciens, L. kefir, L. parakefir, and Lactococcus lactis but was inappropriate for the identification of leuconostocs at species level. Among 16S rDNA variable regions, the V2 region showed the highest variability between Leuconostoc species. Nevertheless, even in the V2 region, differences were too tenuous for effective identification of L. mesenteroides. The methodology described here allowed detection of the dominant species within each targeted microbial group.

The taxonomic characterization of ancient microbiomes is a key step in the rapidly growing field of paleomicrobiology. While PCR amplification of the 16S ribosomal RNA (rRNA) gene is a widely used technique in modern microbiota studies, this method has systematic biases when applied to ancient microbial DNA. Shotgun metagenomic sequencing has proven to be the most effective method in reconstructing taxonomic profiles of ancient dental calculus samples. Nevertheless, shotgun sequencing approaches come with inherent limitations that could be addressed through hybridization enrichment capture. When employed together, shotgun sequencing and hybridization capture have the potential to enhance the characterization of ancient microbial communities. Here, we develop, test, and apply a hybridization enrichment capture technique to selectively target 16S rRNA gene fragments from the libraries of ancient dental calculus samples generated with shotgun techniques. We simulated data sets generated from hybridization enrichment capture, indicating that taxonomic identification of fragmented and damaged 16S rRNA gene sequences was feasible. Applying this enrichment approach to 15 previously published ancient calculus samples, we observed a 334-fold increase of ancient 16S rRNA gene fragments in the enriched samples when compared to unenriched libraries. Our results suggest that 16S hybridization capture is less prone to the effects of background contamination than 16S rRNA amplification, yielding a higher percentage of on-target recovery. While our enrichment technique detected low abundant and rare taxa within a given sample, these assignments may not achieve the same level of specificity as those achieved by unenriched methods.

Two gene regions commonly used to characterise the diversity of eukaryotic communities using metabarcoding are the 18S ribosomal DNA V4 and V9 gene regions. We assessed the effectiveness of these two regions for characterising diverisity of coastal eukaryotic microalgae communities (EMCs) from tropical and temperate sites. We binned amplicon sequence variants (ASVs) into the high level taxonomic groups: dinoflagellates, pennate diatoms, radial centric diatoms, polar centric diatoms, chlorophytes, haptophytes and ‘other microalgae’. When V4 and V9 generated ASV abundances were compared, the V9 region generated a higher number of raw reads, captured more diversity from all high level taxonomic groups and was more closely aligned with the community composition determined using light microscopy. The V4 region did resolve more ASVs to a deeper taxonomic resolution within the dinoflagellates, but did not effectively resolve other major taxonomic divisions. When characterising these communities via metabarcoding, the use of multiple gene regions is recommended, but the V9 gene region can be used in isolation to provide high-level community biodiversity to reflect relative abundances within groups. This approach reduces the cost of sequencing multiple gene regions whilst still providing important baseline ecosystem function information.

To investigate whether arbitrarily primed (AP)-PCR and/or 16S rDNA sequencing could be used as rapid methods for epidemiological typing and species identification of clinical Burkholderia isolates from patients with cystic fibrosis (CF), a total of 39 clinical B. cepacia isolates, including 33 isolates from 14 CF patients, were fingerprinted. ERIC-2 primer was used for AP-PCR. The AP-PCR clustering analysis resulted in 14 different clusters at a 70% similarity level. The AP-PRC patterns were individual despite considerable similarities. To sequence rDNA, a broad-range PCR was applied. The PCR product included four variable loops (V8, V3, V4 and V9) of the 16S ribosomal small subunit RNA gene. The multiple sequence alignment produced 12 different patterns, 5 of them including more than one isolate. Heterogeneity of the bases in the V3 region, indicating the simultaneous presence of at least two different types of 16S rRNA genes in the same cell, was revealed in 10 isolates. Most of the CF patients were adults who had advanced disease at follow-up. Both the sequencing and the AP-PCR patterns revealed genetic heterogeneity of isolates between patients. According to the results obtained, AP-PCR could advantageously be used for epidemiological typing of Burkholderia, whereas partial species identification could effectively be obtained by sequencing of the V3 region of the 16S RNA gene.

The 5S ribosomal RNA (rRNA) genes of Eruca sativa were cloned and characterized. They are organized into clusters of tandemly repeated units. Each repeat unit consists of a 119-bp coding region followed by a noncoding spacer region that separates it from the coding region of the next repeat unit. Our study reports novel gene variants of the 5S rRNA genes in plants. Two families of the 5S rDNA, the 0.5-kb size family and the 1-kb size family, coexist in the E. sativa genome. The 0.5-kb size family consists of the 5S rRNA genes (S4) that have coding regions similar to those of other reported plant 5S rDNA sequences, whereas the 1-kb size family consists of the 5S rRNA gene variants (S1) that exist as 1-kb BamHI tandem repeats. S1 is made up of two variant units (V1 and V2) of 5S rDNA where the BamHI site between the two units is mutated. Sequence heterogeneity among S4, V1, and V2 units exists throughout the sequence and is not limited to the noncoding spacer region only. The coding regions of V1 and V2 show approximately 20% dissimilarity to the coding regions of S4 and other reported plant 5S rDNA sequences. Such a large variation in the coding regions of the 5S rDNA units within the same plant species has been observed for the first time. Restriction site variation is observed between the two size classes of 5S rDNA in E. sativa.(ABSTRACT TRUNCATED AT 250 WORDS)

Characterization and physical mapping of 18S and 5S ribosomal genes in Indian major carps (Pisces, Cyprinidae)

DNA sequencing methods have been used for the molecular taxonomic discrimination of dinoflagellate protists, particularly using partial 18S rRNA sequences. This study evaluated the taxonomic discrimination power of rRNA gene hypervariable regions (V1 to V9) in dinoflagellates from a large dataset. These included 77 dinoflagellate species (9 orders, 17 families, 40 genera). The complete 18S rRNA sequences of the dinoflagellates ranged from 1,787 to 1,813 bp in length, and consisted of eight V regions with a total combined length of 678 to 699 bp. Regions longer than 100 bp were recoded for V2, V4, and V8 regions; high nucleotide divergences were detected in V1, V2, and V4 regions. Statistic tests showed that the divergences of individual V regions were significantly different (t-test, P < 0.05) compared with the complete 18S rRNA. The V2 region showed the highest score (83.5%) for PI sites. Moreover, intra-genus DNA similarities of the V2 were considerably low (<93%). Neighbor-joining analyses showed that phylogenetic resolution in the V2–V4 region was 1.32-fold higher than that of the complete 18S rRNA. These results demonstrate that V2 has the highest taxonomic resolving power within the 18S rRNA gene of dinoflagellates, suggesting the V2 and adjacent regions (e.g., V1 to V4) may be the best for marker considerations.