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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Towards quantitative microbiome community profiling using internal standards
An inherent issue in high-throughput rRNA gene tag sequencing microbiome surveys is that they provide compositional data in relative abundances. This often leads to spurious correlations, making the interpretation of relationships to biogeochemical rates challenging. To overcome this issue, we quantitatively estimated the abundance of microorganisms by spiking in known amounts of internal DNA standards. Using a 3-year sample set of diverse microbial communities from the Western Antarctica Peninsula, we demonstrated that the internal standard method yielded community profiles and taxon cooccurrence patterns substantially different from those derived using relative abundances. We found that the method provided results consistent with the traditional CHEMTAX analysis of pigments and total bacterial counts by flow cytometry. Using the internal standard method, we also showed that chloroplast 16S rRNA gene data in microbial surveys can be used to estimate abundances of certain eukaryotic phototrophs such as cryptophytes and diatoms. In Phaeocystis, scatter in the 16S/18S rRNA gene ratio may be explained by physiological adaptation to environmental conditions. We conclude that the internal standard method, when applied to rRNA gene microbial community profiling, is quantitative and that its application will substantially improve our understanding of microbial ecosystems.
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- Award ID(s):
- 1643534
- NSF-PAR ID:
- 10091386
- Date Published:
- Journal Name:
- Applied and environmental microbiology
- ISSN:
- 1098-5336
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Chi Fru, Ernest ; Chik, Alex ; Colwell, Fredrick ; Dittrich, Maria ; Engel, Annette ; Keenan, Sarah ; Meckenstock, Rainer ; Omelon, Christopher ; Purkamo, Lotta ; Weisener, Chris (Ed.)more » « less
Roots are common features in basaltic lava tube caves on the island of Hawai‘i. For the past 50 years, new species of cave-adapted invertebrates, including cixiid planthoppers, crickets, thread-legged bugs, and spiders, have been discovered from root patches in lava tubes on different volcanoes and across variable climatic conditions. Assessing vegetation on the surface above lava tube passages, as well as genetic characterization of roots from within lava tubes, suggest that most roots belong to the native pioneer tree, ‘ōhi‘a lehua (
Metrosideros polymorpha ). Planthoppers are the primary consumers of sap at the base of the subsurface food web. However, root physicochemistry and rhizobiome microbial diversity and functional potential have received little attention. This study focuses on characterizing the ‘ōhi‘a rhizobiome, accessed from free-hanging roots inside lava tubes. Using these results, we can begin to evaluate the development and evolution of plant-microbe-invertebrate relationships.We explored lava tubes formed in flows of differing elevations and ages, from about 140 to 3000 years old, on Mauna Loa, Kīlauea, and Hualālai volcanoes on Hawai‘i Island. Invertebrate diversity was evaluated from root galleries and non-root galleries, in situ fluid physicochemistry was measured, and root and bare rock fluids (e.g., water, sap) were collected to determine major ion concentrations, as well as non-purgeable organic carbon (NPOC) and total nitrogen (TN) content. To verify root identity, DNA was extracted, and three sets of primers were used. After screening for only
Metrosideros spp., the V4 region of the 16S rRNA gene was sequenced and taxonomy was assigned.Root fluids were viscous and ranged in color from clear to yellow to reddish orange. Root fluids had 2X to 10X higher major ion concentrations compared to rock water. The average root NPOC and TN concentrations were 192 mg/L and 5.2 mg/L, respectively, compared to rock water that had concentrations of 6.8 mg/L and 1.8 mg/L, respectively. Fluids from almost 300 root samples had pH values that ranged from 2.2 to 5.6 (average pH 4.63) and were lower than rock water (average pH 6.39). Root fluid pH was comparable to soil pH from montane wet forests dominated by ‘ōhi‘a (Selmants et al. 2016), which can grow in infertile soil with pH values as low as 3.6. On Hawai‘i, rain water pH averages 5.2 at sea level and systematically decreases with elevation to pH 4.3 at 2500 m (Miller and Yoshinaga 2012), but root fluid pH did not correlate with elevation, temperature, relative humidity, inorganic and organic constituents, or age of flow. Root fluid acidity is likely due to concentrated organic compounds, sourced as root exudates, and this habitat is acidic for the associated invertebrates.
From 62 root samples, over 66% were identified to the genus
Metrosideros . A few other identifications of roots from lava tube systems where there had been extensive clear-cutting and ranching included monkey pod tree, coconut palm,Ficus spp., and silky oak.The 16S rRNA gene sequence surveys revealed that root bacterial communities were dominated by few groups, including Burkholderiaceae, as well as Acetobacteraceae, Sphingomonadaceae, Acidobacteriaceae, Gemmataceae, Xanthobacteraceae, and Chitinophagaceae. However, most of the reads could not be classified to a specific genus, which suggested that the rhizobiome harbor novel diversity. Diversity was higher from wetter climates. The root communities were distinct from those described previously from ‘ōhi‘a flowers and leaves (Junker and Keller 2015) and lava tube rocky surfaces (Hathaway et al. 2014) where microbial groups were specifically presumed capable of heterotrophy, methanotrophy, diazotrophy, and nitrification. Less can be inferred for the rhizobiome metabolism, although most taxa are likely aerobic heterotrophs. Within the Burkholderiaceae, there were high relative abundances of sequences affiliated with the genus
Paraburkholderia , which includes known plant symbionts, as well as the acidophilic generaAcidocella andAcidisoma from the Acetobacteraceae, which were retrieved predominately from caves in the oldest lava flows that also had the lowest root pH values. It is likely that the bacterial groups are capable of degrading exudates and providing nutritional substrates for invertebrate consumers that are not provided by root fluids (i.e., phloem) alone.As details about the biochemistry of ‘ōhi‘a have been missing, characterizing the rhizobiome from lava tubes will help to better understand potential plant-microbe-invertebrate interactions and ecological and evolutionary relationships through time. In particular, the microbial rhizobiome may produce compounds used by invertebrates nutritionally or that affect their behavior, and changes to the rhizobiome in response to environmental conditions may influence invertebrate interactions with the roots, which could be important to combat climate change effects or invasive species introductions.
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Abstract Objectives Establishment and development of the infant gastrointestinal microbiome (GIM) varies cross‐culturally and is thought to be influenced by factors such as gestational age, birth mode, diet, and antibiotic exposure. However, there is little data as to how the composition of infants' households may play a role, particularly from a cross‐cultural perspective. Here, we examined relationships between infant fecal microbiome (IFM) diversity/composition and infants' household size, number of siblings, and number of other household members.
Materials and methods We analyzed 377 fecal samples from healthy, breastfeeding infants across 11 sites in eight different countries (Ethiopia, The Gambia, Ghana, Kenya, Peru, Spain, Sweden, and the United States). Fecal microbial community structure was determined by amplifying, sequencing, and classifying (to the genus level) the V1–V3 region of the bacterial 16S rRNA gene. Surveys administered to infants' mothers identified household members and composition.
Results Our results indicated that household composition (represented by the number of cohabitating siblings and other household members) did not have a measurable impact on the bacterial diversity, evenness, or richness of the IFM. However, we observed that variation in household composition categories did correspond to differential relative abundances of specific taxa, namely:
Lactobacillus ,Clostridium ,Enterobacter , andKlebsiella .Discussion This study, to our knowledge, is the largest cross‐cultural study to date examining the association between household composition and the IFM. Our results indicate that the social environment of infants (represented here by the proxy of household composition) may influence the bacterial composition of the infant GIM, although the mechanism is unknown. A higher number and diversity of cohabitants and potential caregivers may facilitate social transmission of beneficial bacteria to the infant gastrointestinal tract, by way of shared environment or through direct physical and social contact between the maternal–infant dyad and other household members. These findings contribute to the discussion concerning ways by which infants are influenced by their social environments and add further dimensionality to the ongoing exploration of social transmission of gut microbiota and the “old friends” hypothesis.
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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.more » « less
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Methane seep systems along continental margins host diverse and dynamic microbial assemblages, sustained in large part through the microbially mediated process of sulfate-coupled Anaerobic Oxidation of Methane (AOM). This methanotrophic metabolism has been linked to consortia of anaerobic methane-oxidizing archaea (ANME) and sulfate-reducing bacteria (SRB). These two groups are the focus of numerous studies; however, less is known about the wide diversity of other seep associated microorganisms. We selected a hierarchical set of FISH probes targeting a range of
Deltaproteobacteria diversity. Using the Magneto-FISH enrichment technique, we then magnetically captured CARD-FISH hybridized cells and their physically associated microorganisms from a methane seep sediment incubation. DNA from nested Magneto-FISH experiments was analyzed using Illumina tag 16S rRNA gene sequencing (iTag). Enrichment success and potential bias with iTag was evaluated in the context of full-length 16S rRNA gene clone libraries, CARD-FISH, functional gene clone libraries, and iTag mock communities. We determined commonly used Earth Microbiome Project (EMP) iTAG primers introduced bias in some common methane seep microbial taxa that reduced the ability to directly compare OTU relative abundances within a sample, but comparison of relative abundances between samples (in nearly all cases) and whole community-based analyses were robust. The iTag dataset was subjected to statistical co-occurrence measures of the most abundant OTUs to determine which taxa in this dataset were most correlated across all samples. Many non-canonical microbial partnerships were statistically significant in our co-occurrence network analysis, most of which were not recovered with conventional clone library sequencing, demonstrating the utility of combining Magneto-FISH and iTag sequencing methods for hypothesis generation of associations within complex microbial communities. Network analysis pointed to many co-occurrences containing putatively heterotrophic, candidate phyla such as OD1,Atribacteria , MBG-B, and Hyd24-12 and the potential for complex sulfur cycling involvingEpsilon -,Delta -, andGammaproteobacteria in methane seep ecosystems.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/http://dx.doi.org/10.1128/AEM.02634-18
