Allopatric speciation in the bacterium Aquificota enables genus-level endemism in Aotearoa-New Zealand. All landowners and Māori collaborators in the Taupō Volcanic Zone, Aotearoa-New Zealand are recognized as having mana whenua (customary rights) to data generated from ecosystems within the rohe of iwi (tribal areas).
Diversity and ecology of microorganisms
Population- and community-level studies are complementary and necessary to disentangle complex ecosystem behaviors in any microbial habitat. Others propose alternative characterizations, such as functionally based ecotypes 24 , 25 , microbial diversity units 26 or the more recent sequence of multiples (ASV) 27 .
Biogeography
Patterns of biogeography
Processes of biogeography
Diversification refers to mutation, speciation, horizontal gene transfer, evolutionary drift or any significant change in the genotypes of microbial communities45,62. A combined approach, investigating all determinative processes of microbial diversity within an ecosystem, is desirable to understand the dynamics of the whole community and the ecological role in the local environment5.
Microbial ecology of geothermal features
A number of studies have found temperature to be the main driver of microbial community structure in geothermal deposits, mats and/or streams92,93,143, particularly where there was a temperature gradient, and some studies have also shown other physicochemical conditions such as pH and/or sulfur. promote microbial community assembly in geothermal features. Other metrics besides the 16S rRNA gene (eg, whole-genome sequencing, functionality) can also improve our understanding of how microbial diversity is shaped in geothermal features.
Research aims
Whakaari-White Island near the Bay of Plenty coast to Mount Ruapehu in the Central Plateau. To embrace this possibility and develop a greater understanding of the driving influences behind microbial biogeography, I therefore propose to sample and examine the spatial and temporal biogeography of 1,000 geothermal spring water columns in the TVZ, at both community and population levels, from the 1,000 Springs Project ( MBIE title: Microbial Bioinventory of Geothermal Ecosystems).
Hypotheses & objectives
Based on the four biogeographical processes discussed in this literature review, selection and dispersal will be examined in detail. Taxonomic, alpha and beta diversity measures will be used to assess the level of ecosystem stability in these extreme habitats.
Thesis overview
This chapter was the basis for the manuscript by Power et al, which was published in Nature Communications. The final chapter of this thesis summarizes the main findings from spatial, temporal and population analyzes of 925 geothermal spring ecosystems in Aotearoa, New Zealand.
Preface
As the lead author of this research chapter, I was tasked with field sampling for the 1000 Springs Project. While Charles Lee processed the sequences that appear on the 1000 Springs Project website, I developed my own custom bioinformatics pipeline for processing the raw sequences into operational taxonomic units (OTUs) and associated read abundances that were used in this chapter.
Abstract
Introduction
We then performed community analysis of the bacterial and archaeal population (16S rRNA gene amplicon sequencing) and quantified 46 physicochemical parameters for each sample. The panel inset highlights the location of the TVZ in the central North Island of Aotearoa New Zealand.
Methods
For ordination visualizations, a square root transformation was applied to relative OTU abundances prior to non-metric multidimensional scaling (k=2) using the metaMDS function in the vegan package. A second set of filter criteria was applied to geochemical parameters to identify metadata that correlated significantly with beta diversity.
Results & discussion
This trend was consistent in pH- and temperature-bound samples (Figure B.6; ANOSIM: |R|=0.46 and 0.18, respectively, P<0.001); further confirming pH, more than temperature, accounted for observed variations in beta diversity. Of the 14 currently described genera within Aquificae, six genera were relatively abundant in our dataset (mean relative abundance >0.1%; Figure 2.5): Aquifex, Hydrogenobacter, Hydrogenobaculum and Thermocrinis (family Aquificaceae); and Sulfurihydrogenibium and Venenivibrio (family Hydrogenothermaceae).
Summary
Supplementary Information
Data availability
Preface
Matthew Stott, Craig Cary, Ian McDonald, and Carlo Carere contributed to the experimental design of this chapter and edited the text. All scripts developed for statistics and figures are available through GitLab (https://gitlab.com/morganlab/collaboration-1000Springs/1000Springs), with the raw sequences used in this chapter deposited at the European Nucleotide Archive (ENA ) under study approaches PRJEB24353 and PRJEB55115.
Abstract
Introduction
To build consensus on the drivers of geothermal microbial variation over time, further studies are needed, preferably with consistent methods across multiple hot springs, to develop a more holistic view of ecosystem dynamics. In addition, we sampled 12 geothermal features exhibiting moderate temperatures (60–70 °C) across a range of pH values (pH 3, 5, 7, or 9) bimonthly over a one-year period to assess the causes of the community structure across the pH scale (ie pH sites).
Methods
Briefly, the 16S rRNA gene was analyzed using the original Earth Microbiome Project primers and the Ion PGM next-generation sequencing system. Operational taxonomic units (OTUs) generated by processing the 16S rRNA gene sequences and associated sample metadata were imported into R using the import_biom function.
Results
Aquificota was also the most abundant phylum in five of six features from the pH 5 and 7 groups (such as the genus Venenivibrio; Figure C.6), with notable variation for this phylum occurring only in Kuirau Park Feature 60. Similarity analysis confirmed this variation in beta diversity was greater between pH groups than within pH groups (p=0.001, ANOSIM; Figure C.7), indicating the significant influence of pH on driving diversity in these ecosystems at a spatial scale.
Discussion
The pH 7 group had the greatest change in alpha diversity, especially for the Shannon diversity index (Figure 3.6), which could be a result of the increased number of taxa that prefer circumneutral conditions153. In contrast, the largest changes in beta diversity were detected in pH 3, 5 and 9 groups (Figure 3.6), corresponding to the variation observed in relative abundances of taxa in these features.
Summary
Regardless, geothermal features of a range of source fluids across the pH scale showed both stochastic and deterministic fluctuations in the relative abundances of microbial communities, suggesting that not all geothermal features adhere to the same processes of community assembly over time.
Supplementary Information
Data availability
Preface
I led the experimental design of the metagenome section, with input from Xochitl Morgan, Matthew Stott and Carlo Carere. A separate manuscript has been generated for the sequencing, assembly and annotation of the Venenivibrio stagnispumantis CP.B2T genome and is published in Microbiology Resource Announcements197.
Abstract
Introduction
Interestingly, while the sister genera of Venenivibrio (Hydrogenothermus, Persephonella and Sulfurihydrogenibium) are globally distributed, we were unable to find any verifiable records of Venenivibrio taxa (cultured species or via molecular signatures) outside of Aotearoa-New Zealand. The ubiquity of Venenivibrio within Aotearoa-New Zealand, but the apparent absence of this taxon globally, led us to explore the hypothesis that the genus Venenivibrio is endemic to the Aotearoa-New Zealand archipelago.
Methods
To interrogate the observed widespread distribution of Venenivibrio in Aotearoa New Zealand, specific growth characteristics of the type strain CP.B2T were reanalysed, including temperature, pH, salinity and O2 tolerances. In addition, the GTDB relative evolutionary divergence (RED) score of CP.B2T was calculated317 and average nucleotide identity (ANI) scores were generated from the Hydrogenothermaceae in IMG using the Compare Genomes function.
Results
A local polynomial regression of Venenivibrio 16S rRNA gene read abundance (contours) was applied to examine the relationship with both spring pH and temperature (n=466), with abundance also described by color and size of the dots. A map of the Taupō Volcanic Zone (TVZ), showing geothermal fields where Venenivibrio 16S rRNA genes were detected, highlighted in yellow.
Discussion
The four Aotearoa-New Zealand and two global MAGs generated from this study are shown in bold. Aotearoa-New Zealand exists as an isolated archipelago in the South Pacific Ocean; near the convergent boundary between the Pacific-Australian tectonic plate.
Summary
Supplementary Information
Data availability
Thesis summary & conclusions
Amplicon sequencing of the 16S rRNA gene from 925 individual geothermal spring water columns generated 28,381 OTUs from quality-controlled reads (with an average of 43,905 reads per sample). Conversely, beta diversity analyzes for stream sites (Waikite Features 3, 4, and 8) suggested that microbial community structure continued to change at the end of the experiment.
Future work
While allopatry has clearly played a role in the evolution of the genus within the Hydrogenothermaceae family, it is unlikely to be the sole cause of contemporary endemism. The variability of the 16S rRNA gene in bacterial genomes and its implications for bacterial community analyses.
Supplementary methods
Chloroform:isoamyl alcohol (24:1), in equal volumes (1:1) to the filtrate, was added to each duplicate and vortexed. The remaining 15 variables have been added to the CCA model, with geothermal fields and spring communities (Figure 2.3).
Supplementary figures
The variation between pH (a) and temperature (b) groups is shown in red, with the variation within individual groups in black. Two geothermal fields (Whangairorohea and Misc) only sampled one spring and are therefore not shown in this analysis.
Supplementary tables
Variables were added to the model in order of highest to lowest best fit from simple linear regression. Geothermal fields Whangairorohea, Ohaaki and Misc were removed from this analysis due to low spring numbers present (n<3).
Supplementary figures
Measures of diversity were calculated from sequencing multiples of the 16S rRNA gene found in the microbial communities of these traits over time. Diversity was calculated from sequencing the 16S rRNA gene multiples found in the microbial communities of these traits over time.
Supplementary tables
Geothermal Feature Waimangu Waimangu Inferno Waimangu Waimangu Waimangu Waimangu Feature 2 Feature 3 Crater Lake Feature 4 Feature 5 Feature 6 Feature 7 Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD. Geothermal Feature Whangapoa Kuirau Park Kuirau Park Melting Melting Feature 1 Feature 87 Feature 101 Feature 45 Feature 1 Feature 2.
Supplementary methods
Phase contrast microscopy was used to assess growth due to the tendency for CP.B2T to flocculate. The growth temperature range for CP.B2T was tested between C using a custom temperature gradient oscillator (10 oscillations/min).
Supplementary results
There was no evidence of sulfite dehydrogenase (sorAB or soeA) in the genome, although genes were present for biosynthesis of the cofactor molybdopterin391. While the arsRBC operon of arsenic resistance was annotated in the CP.B2T genome, there was no indication of the arsenic ATPase ABC transporter gene (arsA; as part of the more complex arsRDABC operon)324.
Supplementary figures
Supplementary tables
Abstract
Announcement
Data availability
