ArticleEnvironmental microbiome2024
The impacts of ecological disturbances on the diversity of biosynthetic gene clusters in kauri (Agathis australis) soil.
Article in Environmental microbiome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundThe ancient kauri (Agathis australis) dominated forests of Aotearoa New Zealand are under threat from a multitude of ecological disturbances such as forest fragmentation, biodiversity loss, climate change, and the spread of the virulent soil pathogen Phytophthora agathidicida. Taking a wider ecosystem-level approach, our research aimed to explore the impacts of forest disturbance and disease outbreaks on the biosynthetic potential and taxonomic diversity of the kauri soil microbiome. We explored the diversity of secondary metabolite biosynthetic gene clusters (BGCs) in soils from a range of kauri forests that varied according to historical disturbance and dieback expression. To characterise the diversity of microbial BGCs, we targeted the non-ribosomal peptide synthetase (NRPS) and polyketide synthetase (PKS) gene regions for sequencing using long-read PacBio® HiFi sequencing. Furthermore, the soil bacterial and fungal communities of each forest were characterized using 16 S rRNA and ITS gene region sequencing.
resultsWe identified a diverse array of naturally occurring microbial BGCs in the kauri forest soils, which may offer promising targets for the exploration of secondary metabolites with anti-microbial activity against P. agathidicida. We detected differences in the number and diversity of microbial BGCs according to forest disturbance history. Notably, soils associated with the most undisturbed kauri forest had a higher number and diversity of microbial NRPS-type BGCs, which may serve as a potential indicator of natural levels of microbiome resistance to pathogen invasion.
conclusionsBy linking patterns in microbial biosynthetic diversity to forest disturbance history, this research highlights the need for us to consider the influence of ecological disturbances in potentially predisposing forests to disease by impacting the wider health of forest soil ecosystems. Furthermore, by identifying the range of microbial BGCs present at a naturally high abundance in kauri soils, this research contributes to the future discovery of natural microbial compounds that may potentially enhance the disease resilience of kauri forests. The methodological approaches used in this study highlight the value of moving beyond a taxonomic lens when examining the response of microbial communities to ecosystem disturbance and the need to develop more functional measures of microbial community resilience to invasive plant pathogens.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.