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1. Characterization of captive and wild 13-lined ground squirrel cecal microbiotas using Illumina-based sequencing

   https://doi.org/10.1186/s42523-021-00154-9  

   Chiang, Edna ; Deblois, Courtney L. ; Carey, Hannah V. ; Suen, Garret ( January 2022 , Animal Microbiome)

   Hibernating animals experience extreme changes in diet that make them useful systems for understanding host-microbial symbioses. However, most of our current knowledge about the hibernator gut microbiota is derived from studies using captive animals. Given that there are substantial differences between captive and wild environments, conclusions drawn from studies with captive hibernators may not reflect the gut microbiota’s role in the physiology of wild animals. To address this, we used Illumina-based sequencing of the 16S rRNA gene to compare the bacterial cecal microbiotas of captive and wild 13-lined ground squirrels (TLGS) in the summer. As the first study to use Illumina-based technology to compare the microbiotas of an obligate rodent hibernator across the year, we also reported changes in captive TLGS microbiotas in summer, winter, and spring.

   Wild TLGS microbiotas had greater richness and phylogenetic diversity with less variation in beta diversity when compared to captive microbiotas. Taxa identified as core operational taxonomic units (OTUs) and found to significantly contribute to differences in beta diversity were primarily in the familiesLachnospiraceaeandRuminococcaceae. Captive TLGS microbiotas shared phyla and core OTUs across the year, but active season (summer and spring) microbiotas had different alpha and beta diversities than winter season microbiotas.

   This is the first study to compare the microbiotas of captive and wild rodent hibernators. Our findings suggest that data from captive and wild ground squirrels should be interpreted separately due to their distinct microbiotas. Additionally, as the first study to compare seasonal microbiotas of obligate rodent hibernators using Illumina-based 16S rRNA sequencing, we reported changes in captive TLGS microbiotas that are consistent with previous work. Taken together, this study provides foundational information for improving the reproducibility and experimental design of future hibernation microbiota studies.

    

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2. OGUs enable effective, phylogeny-aware analysis of even shallow metagenome community structures

   https://doi.org/2021.04.04.438427  

   Qiyun Zhu ; Shi Huang ; Antonio Gonzalez ; Imran McGrath ; Daniel McDonald ; Niina Haiminen ; George Armstrong ; Yoshiki Vázquez-Baeza ; Julian Yu ; Justin Kuczynski ; et al ( April 2021 , bioRxiv)

   We introduce Operational Genomic Unit (OGU), a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent from taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldomly applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in one synthetic and two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome datasets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project dataset, and more accurate prediction of human age by the gut microbiomes in the Finnish population. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate OGU adoption in future metagenomics studies. Importance Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. However, current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution compared to 16S rRNA amplicon sequence variant analysis. To solve these challenges, we introduce Operational Genomic Units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition while (ii) permitting use of phylogeny-aware tools. Our analysis of real-world datasets shows several advantages over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGU as standard practice in metagenomic studies. 

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3. Evolutionary signal in the gut microbiomes of 74 bird species from Equatorial Guinea

   https://doi.org/10.1111/mec.15354  

   Capunitan, Darien C. ; Johnson, Oscar ; Terrill, Ryan S. ; Hird, Sarah M. ( February 2020 , Molecular Ecology)

   How the microbiome interacts with hosts across evolutionary time is poorly understood. Data sets including many host species are required to conduct comparative analyses. Here, we analyzed 142 intestinal microbiome samples from 92 birds belonging to 74 species from Equatorial Guinea, using the 16S rRNA gene. Using four definitions for microbial taxonomic units (97%OTU, 99%OTU, 99%OTU with singletons removed, ASV), we conducted alpha and beta diversity analyses. We found that raw abundances and diversity varied between the data sets but relative patterns were largely consistent across data sets. Host taxonomy, diet and locality were significantly associated with microbiomes, at generally similar levels using three distance metrics. Phylogenetic comparative methods assessed the evolutionary relationship between the microbiome as a trait of a host species and the underlying bird phylogeny. Using multiple ways of defining “microbiome traits”, we found that a neutral Brownian motion model did not explain variation in microbiomes. Instead, we found a White Noise model (indicating little phylogenetic signal), was most likely. There was some support for the Ornstein‐Uhlenbeck model (that invokes selection), but the level of support was similar to that of a White Noise simulation, further supporting the White Noise model as the best explanation for the evolution of the microbiome as a trait of avian hosts. Our study demonstrated that both environment and evolution play a role in the gut microbiome and the relationship does not follow a neutral model; these biological results are qualitatively robust to analytical choices.

    

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4. Ranking the biases: The choice of OTUs vs. ASVs in 16S rRNA amplicon data analysis has stronger effects on diversity measures than rarefaction and OTU identity threshold

   https://doi.org/10.1371/journal.pone.0264443  

   Chiarello, Marlène ; McCauley, Mark ; Villéger, Sébastien ; Jackson, Colin R. ( February 2022 , PLOS ONE)

   Moreno-Hagelsieb, Gabriel (Ed.)

   Advances in the analysis of amplicon sequence datasets have introduced a methodological shift in how research teams investigate microbial biodiversity, away from sequence identity-based clustering (producing Operational Taxonomic Units, OTUs) to denoising methods (producing amplicon sequence variants, ASVs). While denoising methods have several inherent properties that make them desirable compared to clustering-based methods, questions remain as to the influence that these pipelines have on the ecological patterns being assessed, especially when compared to other methodological choices made when processing data (e.g. rarefaction) and computing diversity indices. We compared the respective influences of two widely used methods, namely DADA2 (a denoising method) vs. Mothur (a clustering method) on 16S rRNA gene amplicon datasets (hypervariable region v4), and compared such effects to the rarefaction of the community table and OTU identity threshold (97% vs. 99%) on the ecological signals detected. We used a dataset comprising freshwater invertebrate (three Unionidae species) gut and environmental (sediment, seston) communities sampled in six rivers in the southeastern USA. We ranked the respective effects of each methodological choice on alpha and beta diversity, and taxonomic composition. The choice of the pipeline significantly influenced alpha and beta diversities and changed the ecological signal detected, especially on presence/absence indices such as the richness index and unweighted Unifrac. Interestingly, the discrepancy between OTU and ASV-based diversity metrics could be attenuated by the use of rarefaction. The identification of major classes and genera also revealed significant discrepancies across pipelines. Compared to the pipeline’s effect, OTU threshold and rarefaction had a minimal impact on all measurements. 

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5. Eukaryotic algal community composition in tropical environments from solar salterns to the open sea

   https://doi.org/10.3389/fmars.2023.1131351  

   Eckmann, Charlotte A. ; Eberle, Jessica S. ; Wittmers, Fabian ; Wilken, Susanne ; Bergauer, Kristin ; Poirier, Camille ; Blum, Marguerite ; Makareviciute-Fichtner, Kriste ; Jimenez, Valeria ; Bachy, Charles ; et al ( June 2023 , Frontiers in Marine Science)

   Tropical environments with unique abiotic and biotic factors—such as salt ponds, mangroves, and coral reefs—are often in close proximity. The heterogeneity of these environments is reflected in community shifts over short distances, resulting in high biodiversity. While phytoplankton assemblages physically associated with corals, particularly their symbionts, are well studied, less is known about phytoplankton diversity across tropical aquatic environments. We assess shifts in phytoplankton community composition along inshore to offshore gradients by sequencing and analyzing 16S rRNA gene amplicons using primers targeting the V1-V2 region that capture plastids from eukaryotic phytoplankton and cyanobacteria, as well as heterotrophic bacteria. Microbial alpha diversity computed from 16S V1-V2 amplicon sequence variant (ASV) data from 282 samples collected in and around Curaçao, in the Southern Caribbean Sea, varied more within the dynamic salt ponds, salterns, and mangroves, compared to the seemingly stable above-reef, off-reef, and open sea environments. Among eukaryotic phytoplankton, stramenopiles often exhibited the highest relative abundances in mangrove, above-reef, off-reef, and open sea environments, where cyanobacteria also showed high relative abundances. Within stramenopiles, diatom amplicons dominated in salt ponds and mangroves, while dictyochophytes and pelagophytes prevailed above reefs and offshore. Green algae and cryptophytes were also present, and the former exhibited transitions following the gradient from inland to offshore. Chlorophytes and prasinophyte Class IV dominated in salt ponds, while prasinophyte Class II, including Micromonas commoda and Ostreococcus Clade OII, had the highest relative abundances of green algae in mangroves, above-reef, off-reef, and the open sea. To improve Class II prasinophyte classification, we sequenced 18S rRNA gene amplicons from the V4 region in 41 samples which were used to interrelate plastid-based results with information on uncultured prasinophyte species from prior 18S rRNA gene-based studies. This highlighted the presence of newly described Ostreococcus bengalensis and two Micromonas candidate species. Network analyses identified co-occurrence patterns between individual phytoplankton groups, including cyanobacteria, and heterotrophic bacteria. Our study reveals multiple uncultured and novel lineages within green algae and dictyochophytes in tropical marine habitats. Collectively, the algal diversity patterns and potential co-occurrence relationships observed in connection to physicochemical and spatial influences help provide a baseline against which future change can be assessed. 

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