Size-variable zone in V3 region of 16S rRNA

Rapid and accurate taxonomic classification of cpn60 amplicon sequence variants

The "universal target" region of the gene encoding the 60 kDa chaperonin protein (cpn60, also known as groEL or hsp60) is a proven sequence barcode for bacteria and a useful target for marker gene amplicon-based studies of complex microbial communities. To date, identification of cpn60 sequence variants from microbiome studies has been accomplished by alignment of queries to a reference database. Naïve Bayesian classifiers offer an alternative identification method that provides variable rank classification and shorter analysis times. We curated a set of cpn60 barcode sequences to train the RDP classifier and tested its performance on data from previous human microbiome studies. Results showed that sequences accounting for 79%, 86% and 92% of the observations (read counts) in saliva, vagina and infant stool microbiome data sets were classified to the species rank. We also trained the QIIME 2 q2-feature-classifier on cpn60 sequence data and demonstrated that it gives results consistent with the standalone RDP classifier. Successful implementation of a naïve Bayesian classifier for cpn60 sequences will facilitate future microbiome studies and open opportunities to integrate cpn60 amplicon sequence identification into existing analysis pipelines.

Variable Region Sequences Influence 16S rRNA Performance

16S rRNA gene sequences are commonly analyzed for taxonomic and phylogenetic studies because they contain variable regions that can help distinguish different genera. However, intra-genus distinction using variable region homology is often impossible due to the high overall sequence identities among closely related species, even though some residues may be conserved within respective species. Using a computational method that included the allelic diversity within individual genomes, we discovered that certain Escherichia and Shigella species can be distinguished by a multi-allelic 16S rRNA variable region single nucleotide polymorphism (SNP). To evaluate the performance of 16S rRNAs with altered variable regions, we developed an in vivo system that measures the acceptance and distribution of variant 16S rRNAs into a large pool of natural versions supporting normal translation and growth. We found that 16S rRNAs containing evolutionarily disparate variable regions were underpopulated both in ribosomes and in active translation pools, even for an SNP. Overall, this study revealed that variable region sequences can substantially influence the performance of 16S rRNAs and that this biological constraint can be leveraged to justify refining taxonomic assignments of variable region sequence data. IMPORTANCE This study reevaluates the notion that 16S rRNA gene variable region sequences are uninformative for intra-genus classification and that single nucleotide variations within them have no consequence to strains that bear them. We demonstrated that the performance of 16S rRNAs in Escherichia coli can be negatively impacted by sequence changes in variable regions, even for single nucleotide changes that are native to closely related Escherichia and Shigella species; thus, biological performance is likely constraining the evolution of variable regions in bacteria. Further, the native nucleotide variations we tested occur in all strains of their respective species and across their multiple 16S rRNA gene copies, suggesting that these species evolved beyond what would be discerned from a consensus sequence comparison. Therefore, this work also reveals that the multiple 16S rRNA gene alleles found in most bacteria can provide more informative phylogenetic and taxonomic detail than a single reference allele.

Sarecycline inhibits protein translation in Cutibacterium acnes 70S ribosome using a two-site mechanism

Acne vulgaris is a chronic disfiguring skin disease affecting ∼1 billion people worldwide, often having persistent negative effects on physical and mental health. The Gram-positive anaerobe, Cutibacterium acnes is implicated in acne pathogenesis and is, therefore, a main target for antibiotic-based acne therapy. We determined a 2.8-Å resolution structure of the 70S ribosome of Cutibacterium acnes by cryogenic electron microscopy and discovered that sarecycline, a narrow-spectrum antibiotic against Cutibacterium acnes, may inhibit two active sites of this bacterium's ribosome in contrast to the one site detected previously on the model ribosome of Thermus thermophilus. Apart from the canonical binding site at the mRNA decoding center, the second binding site for sarecycline exists at the nascent peptide exit tunnel, reminiscent of the macrolides class of antibiotics. The structure also revealed Cutibacterium acnes-specific features of the ribosomal RNA and proteins. Unlike the ribosome of the Gram-negative bacterium Escherichia coli, Cutibacterium acnes ribosome has two additional proteins, bS22 and bL37, which are also present in the ribosomes of Mycobacterium smegmatis and Mycobacterium tuberculosis. We show that bS22 and bL37 have antimicrobial properties and may be involved in maintaining the healthy homeostasis of the human skin microbiome.

Selecting 16S rRNA Primers for Microbiome Analysis in a Host-Microbe System: The Case of the Jellyfish Rhopilema nomadica

Amplicon sequencing of the 16S rRNA gene is extensively used to characterize bacterial communities, including those living in association with eukaryotic hosts. Deciding which region of the 16S rRNA gene to analyze and selecting the appropriate PCR primers remains a major decision when initiating any new microbiome study. Based on a detailed literature survey of studies focusing on cnidarian microbiomes, we compared three commonly used primers targeting different hypervariable regions of the 16S rRNA gene, V1V2, V3V4, and V4V5, using the jellyfish Rhopilema nomadica as a model. Although all primers exhibit a similar pattern in bacterial community composition, the performance of the V3V4 primer set was superior to V1V2 and V4V5. The V1V2 primers misclassified bacteria from the Bacilli class and exhibited low classification resolution for Rickettsiales, which represent the second most abundant 16S rRNA gene sequence in all the primers. The V4V5 primer set detected almost the same community composition as the V3V4, but the ability of these primers to also amplify the eukaryotic 18S rRNA gene may hinder bacterial community observations. However, after overcoming the challenges possessed by each one of those primers, we found that all three of them show very similar bacterial community dynamics and compositions. Nevertheless, based on our results, we propose that the V3V4 primer set is potentially the most suitable for studying jellyfish-associated bacterial communities. Our results suggest that, at least for jellyfish samples, it may be feasible to directly compare microbial community estimates from different studies, each using different primers but otherwise similar experimental protocols. More generally, we recommend specifically testing different primers for each new organism or system as a prelude to large-scale 16S rRNA gene amplicon analyses, especially of previously unstudied host-microbe associations.

Multi-locus evaluation of gastrointestinal bacterial communities from Zalophus californianus pups in the Gulf of California, México

Background

The gastrointestinal (GI) bacterial communities of sea lions described to date have occasionally revealed large intraspecific variability, which may originate from several factors including different methodological approaches. Indeed, GI bacterial community surveys commonly rely on the use of a single hypervariable region (HR) of 16S rRNA, which may result in misleading structural interpretations and limit comparisons among studies. Here, we considered a multi-locus analysis by targeting six HRs of 16S rRNA with the aims of (i) comprehensively assessing the GI bacterial consortium in rectal samples from Zalophus californianus pups and (ii) elucidating structural variations among the tested HRs. In addition, we evaluated which HRs may be most suitable for identifying intrinsic, structurally related microbiome characteristics, such as geographic variations or functional capabilities.

Methods

We employed a Short MUltiple Regions Framework (SMURF) approach using the Ion 16S™ Metagenomic Kit. This kit provides different proprietary primers designed to target six HRs of the 16S rRNA gene. To date, the only analytical pipeline available for this kit is the Ion Reporter™ Software of Thermo Fisher Scientific. Therefore, we propose an in-house pipeline to use with open-access tools, such as QIIME2 and PICRUSt 2, in downstream bioinformatic analyses.

Results

As hypothesized, distinctive bacterial community profiles were observed for each analyzed HR. A higher number of bacterial taxa were detected with the V3 and V6-V7 regions. Conversely, the V8 and V9 regions were less informative, as we detected a lower number of taxa. The synergistic information of these HRs suggests that the GI microbiota of Zalophus californianus pups is predominated by five bacterial phyla: Proteobacteria (~50%), Bacteroidetes (~20%), Firmicutes (~18%), Fusobacteria (~7%), and Epsilonbacteraeota (~4%). Notably, our results differ at times from previously reported abundance profiles, which may promote re-evaluations of the GI bacterial compositions in sea lions and other pinniped species that have been reported to date. Moreover, consistent geographic differences were observed only with the V3, V4, and V6-V7 regions. In addition, these HRs also presented higher numbers of predicted molecular pathways, although no significant functional changes were apparent. Together, our results suggests that multi-locus analysis should be encouraged in GI microbial surveys, as single-locus approaches may result in misleading structural results that hamper the identification of structurally related microbiome features.

Microbial profiles of Greek PDO cheeses assessed with amplicon metabarcoding

Greece is a country possessing many cheese products granted with a PDO (Protected Designation of Origin) certificate, with high exporting activities. In this study, we analyzed six popular cheese PDO products purchased from different industries to assess their microbial communities using amplicon metabarcoding analysis. To this end, using Next Generation Sequencing technology, we sequenced the 16S rRNA gene and the ITS spacer for prokaryotes and fungi, respectively. Alpha diversity indices revealed higher bacterial species richness for some cheeses (Kopanisti, Batzos) and poor for others (Feta, Galotiri). Kopanisti, together with Kalathaki and Anevato, also presented increased species diversity concerning fungal populations. Results showed that lactic acid bacteria (LAB) prevailed the bacterial populations in all samples (Lactococcus, Lactobacillus, Streptococcus, Leuconostoc), whereas for fungi, members of the Saccharomycetaceae, Dipodascaceae and Debaryomycetaceae families prevailed the fungal populations. Several other genera were identified that make up each product's microbiome leading to the creation of the unique organoleptic attributes of Greek PDO cheeses. However, the identified species could not be directly linked to certain cheese types, assuming that starter and adjunct cultures, combined with the raw material used during production greatly impact the microbial communities in cheeses. Our data, produced for the first time for six Greek PDO cheeses, can be exploited in the process of creating a core microbial signature within each cheese type, supporting the Greek brand name and valorizing cheese products.

BEExact: a Metataxonomic Database Tool for High-Resolution Inference of Bee-Associated Microbial Communities

High-throughput 16S rRNA gene sequencing technologies have robust potential to improve our understanding of bee (Hymenoptera: Apoidea)-associated microbial communities and their impact on hive health and disease. Despite recent computation algorithms now permitting exact inferencing of high-resolution exact amplicon sequence variants (ASVs), the taxonomic classification of these ASVs remains a challenge due to inadequate reference databases. To address this, we assemble a comprehensive data set of all publicly available bee-associated 16S rRNA gene sequences, systematically annotate poorly resolved identities via inclusion of 618 placeholder labels for uncultivated microbial dark matter, and correct for phylogenetic inconsistencies using a complementary set of distance-based and maximum likelihood correction strategies. To benchmark the resultant database (BEExact), we compare performance against all existing reference databases in silico using a variety of classifier algorithms to produce probabilistic confidence scores. We also validate realistic classification rates on an independent set of ∼234 million short-read sequences derived from 32 studies encompassing 50 different bee types (36 eusocial and 14 solitary). Species-level classification rates on short-read ASVs range from 80 to 90% using BEExact (with ∼20% due to "bxid" placeholder names), whereas only ∼30% at best can be resolved with current universal databases. A series of data-driven recommendations are developed for future studies. We conclude that BEExact (https://github.com/bdaisley/BEExact) enables accurate and standardized microbiota profiling across a broad range of bee species-two factors of key importance to reproducibility and meaningful knowledge exchange within the scientific community that together, can enhance the overall utility and ecological relevance of routine 16S rRNA gene-based sequencing endeavors.IMPORTANCE The failure of current universal taxonomic databases to support the rapidly expanding field of bee microbiota research has led to many investigators relying on "in-house" reference sets or manual classification of sequence reads (usually based on BLAST searches), often with vague identity thresholds and subjective taxonomy choices. This time-consuming, error- and bias-prone process lacks standardization, cripples the potential for comparative cross-study analysis, and in many cases is likely to incorrectly sway study conclusions. BEExact is structured on and leverages several complementary bioinformatic techniques to enable refined inference of bee host-associated microbial communities without any other methodological modifications necessary. It also bridges the gap between current practical outcomes (i.e., phylotype-to-genus level constraints with 97% operational taxonomic units [OTUs]) and the theoretical resolution (i.e., species-to-strain level classification with 100% ASVs) attainable in future microbiota investigations. Other niche habitats could also likely benefit from customized database curation via implementation of the novel approaches introduced in this study.

Hot in Cold: Microbial Life in the Hottest Springs in Permafrost

Chukotka is an arctic region located in the continuous permafrost zone, but thermal springs are abundant there. In this study, for the first time, the microbial communities of the Chukotka hot springs (CHS) biofilms and sediments with temperatures 54–94 °C were investigated and analyzed by NGS sequencing of 16S rRNA gene amplicons. In microbial mats (54–75 °C), phototrophic bacteria of genus Chloroflexus dominated (up to 89% of all prokaryotes), while Aquificae were the most numerous at higher temperatures in Fe-rich sediments and filamentous “streamers” (up to 92%). The electron donors typical for Aquificae, such as H₂S and H₂, are absent or present only in trace amounts, and the prevalence of Aquificae might be connected with their ability to oxidize the ferrous iron present in CHS sediments. Armatimonadetes, Proteobacteria, Deinococcus-Thermus, Dictyoglomi, and Thermotogae, as well as uncultured bacteria (candidate divisions Oct-Spa1-106, GAL15, and OPB56), were numerous, and Cyanobacteria were present in low numbers. Archaea (less than 8% of the total community of each tested spring) belonged to Bathyarchaeota, Aigarchaeota, and Thaumarchaeota. The geographical location and the predominantly autotrophic microbial community, built on mechanisms other than the sulfur cycle-based ones, make CHS a special and unique terrestrial geothermal ecosystem.