• No results found

Microbial biogeography of 1,000 geothermal springs: spatial, temporal, and allopatric dynamics of extremophiles in the Taupō Volcanic Zone, Aotearoa-New Zealand

N/A
N/A
Protected

Academic year: 2023

Share "Microbial biogeography of 1,000 geothermal springs: spatial, temporal, and allopatric dynamics of extremophiles in the Taupō Volcanic Zone, Aotearoa-New Zealand"

Copied!
253
0
0

Loading.... (view fulltext now)

Full text

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.

Figure 2.1 - Map of the Taupō Volcanic Zone (TVZ), Aotearoa-New Zealand. The geothermal fields  from  which  samples  were  collected  are  presented  in  yellow
Figure 2.1 - Map of the Taupō Volcanic Zone (TVZ), Aotearoa-New Zealand. The geothermal fields from which samples were collected are presented in yellow

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.

Figure  2.2  -  Alpha  and  beta  diversity  as  a  function  of  pH  and  temperature
Figure 2.2 - Alpha and beta diversity as a function of pH and temperature

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).

Figure  2.3  -  Constrained  correspondence  analysis  (CCA)  of  beta  diversity  with  significant  physicochemistry
Figure 2.3 - Constrained correspondence analysis (CCA) of beta diversity with significant physicochemistry

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.

Figure 3.1 - Short-term, natural disturbance of Waimangu Stream by Inferno Crater Lake
Figure 3.1 - Short-term, natural disturbance of Waimangu Stream by Inferno Crater Lake

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.

Figure 3.4 - Temporal microbial community composition and relative abundance of Waikite geothermal features
Figure 3.4 - Temporal microbial community composition and relative abundance of Waikite geothermal features

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.

Figure  4.3  -  Read  abundance  of  Venenivibrio  16S  rRNA  genes  as  a  function  of  geothermal  spring  pH  and temperature  in  Aotearoa-New  Zealand
Figure 4.3 - Read abundance of Venenivibrio 16S rRNA genes as a function of geothermal spring pH and temperature in Aotearoa-New Zealand

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.

Figure B.2  - pH,  temperature,  and  alpha  diversity  scales.  A  scatter  plot  of  pH  and  temperature  gradients for all springs sampled  (n=925) is shown
Figure B.2 - pH, temperature, and alpha diversity scales. A scatter plot of pH and temperature gradients for all springs sampled (n=925) is shown

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).

Table B.3 - Multiple linear regression model of significant physicochemical parameters against alpha  diversity (Shannon Index), after collinear variables were removed and an Akaike information criterion  (AIC)  was  applied
Table B.3 - Multiple linear regression model of significant physicochemical parameters against alpha diversity (Shannon Index), after collinear variables were removed and an Akaike information criterion (AIC) was applied

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.

Figure C.2 - Temperature and water level profile of Inferno Crater Lake. The ~30-40 day cycle of Inferno Crater Lake in the Waimangu geothermal field is  indicated by the rise and fall of temperature on the y-axis, with overflow events into Waimangu Stream
Figure C.2 - Temperature and water level profile of Inferno Crater Lake. The ~30-40 day cycle of Inferno Crater Lake in the Waimangu geothermal field is indicated by the rise and fall of temperature on the y-axis, with overflow events into Waimangu Stream

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.

Table C.2 -  Disturbed  features  and  associated  metadata  at  Waimangu  geothermal  field
Table C.2 - Disturbed features and associated metadata at Waimangu geothermal field

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

Figure

Figure 2.1 - Map of the Taupō Volcanic Zone (TVZ), Aotearoa-New Zealand. The geothermal fields  from  which  samples  were  collected  are  presented  in  yellow
Figure  2.2  -  Alpha  and  beta  diversity  as  a  function  of  pH  and  temperature
Figure  2.3  -  Constrained  correspondence  analysis  (CCA)  of  beta  diversity  with  significant  physicochemistry
Figure 3.1 - Short-term, natural disturbance of Waimangu Stream by Inferno Crater Lake
+7

References

Related documents

[Note: this conclusion may alter when the Accommodation Benefit is separated out from the 'before housing costs' income.] However, except for the 50 percent level, for households, there