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Biology subjects

Stott, M. B.

Publications and source records attributed to Stott, M. B..

2 recordsLinked to original sources

Microbial biogeography of 1,000 geothermal springs in New Zealand

Geothermal springs are model ecosystems to systematically investigate microbial biogeography as they i) represent discrete, homogenous habitats; ii) are abundantly distributed across multiple geographical scales; iii) span broad geochemical gradients; and iv) have simple community structures with reduced metazoan interactions. Taking advantage of these traits, we undertook the largest known consolidated study of geothermal ecosystems (http://1000springs.org.nz) to determine factors that influence biogeographical patterns. Rigorously standardised methodologies were used to measure microbial communities, 46 physicochemical parameters, and metadata from 1,019 hotspring samples across New Zealand. pH was found to be the primary influence on diversity in springs < 70 {degrees}C with community similarity decreasing with geographic distance. Surprisingly, community composition was dominated by two genera (Venenivibrio and Acidithiobacillus) in both average relative abundance (11.2 and 11.1 %) and prevalence (74.2 and 62.9 % respectively) across physicochemical spectrums of 13.9 - 100.6 {degrees}C and pH < 1 - 9.7. This study provides an unprecedented insight into the ecological conditions that drive community assembly in geothermal springs, and can be used as a foundation to improve the characterisation of global microbial biogeographical processes.

microbiology

Identifying accurate metagenome and amplicon software via a meta-analysis of benchmarking studies

Environmental DNA sequencing has rapidly become a widely-used technique for investigating a range of questions, particularly related to health and environmental monitoring. There has also been a proliferation of bioinformatic tools for analysing metagenomic and amplicon datasets, which makes selecting adequate tools a significant challenge. A number of benchmark studies have been undertaken; however, these can present conflicting results. We have applied a robust Z-score ranking procedure and a network meta-analysis method to identify software tools that are generally accurate for mapping DNA sequences to taxonomic hierarchies. Based upon these results we have identified some tools and computational strategies that produce robust predictions.

bioinformatics