Soil microbial functional gene dataset associated with Agathis australis
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ABSTRACT:
SUBMITTER: Lawrence P
PROVIDER: S-EPMC10694058 | biostudies-literature | 2023 Nov
REPOSITORIES: biostudies-literature
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Project description: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.
| S-EPMC11391841 | biostudies-literature
Project description:Globally, the conversion of primary forests to plantations and agricultural landscapes is a common land use change. Kauri (Agathis australis) is one of the most heavily impacted indigenous tree species of New Zealand with <1% of primary forest remaining as fragments adjacent to pastoral farming and exotic forest plantations. By contrasting two forest systems, we investigated if the fragmentation of kauri forests and introduction of pine plantations (Pinus radiata) are significantly impacting the diversity and composition of soil microbial communities across Waipoua kauri forest, New Zealand. Using next generation based 16S rRNA and ITS gene region sequencing, we identified that fungal and bacterial community composition significantly differed between kauri and pine forest soils. However, fungal communities displayed the largest differences in diversity and composition. This research revealed significant shifts in the soil microbial communities surrounding remnant kauri fragments, including the loss of microbial taxa with functions in disease suppression and plant health. Kauri dieback disease, caused by Phytophthora agathidicida, currently threatens the kauri forest ecosystem. Results from this research highlight the need for further investigations into how changes to soil microbial diversity surrounding remnant kauri fragments impact tree health and disease expression.
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Project description:Leaf surface microbial communities play an important role in forest ecosystems and are known to be affected by environmental and host conditions, including diseases impacting the host. Phytophthora agathidicida is a soil-borne pathogen that causes severe disease (kauri dieback) in one of New Zealand's endemic trees, Agathis australis (kauri). This research characterised the microbial communities of the A. australis phyllosphere (i.e. leaf surface) using modern molecular techniques and explored the effects of P. agathidicida on those communities. Fresh leaves were collected from trees where P. agathidicida was and was not detected in the soil and characterisation of the leaf surface microbial community was carried out via high-throughput amplicon sequencing of the internal transcribed spacer (ITS) and 16S ribosomal RNA regions. Nutrients in leaf leachates were also measured to identify other possible drivers of microbial diversity. The dominant phyllosphere microbial phylum was Proteobacteria followed by Acidobacteria. The phyllosphere microbial richness of A. agathis associated with P. agathidicida-infected soils was found to be generally lower than where the pathogen was not detected for both prokaryote (bacterial) and fungal phyla. Leaf leachate pH as well as boron and silicon had significant associations with bacterial and fungal community structure. These findings contribute to the development of a comprehensive understanding of A. australis leaf surface microbial communities and the effects of the soil pathogen P. agathidicida on those communities.
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Project description:Functional attributes of microbial communities are difficult to study, and most current techniques rely on DNA- and rRNA-based profiling of taxa and genes, including microarrays containing sequences of known microorganisms. To quantify gene expression in environmental samples in a culture-independent manner, we constructed an environmental functional gene microarray (E-FGA) consisting of 13,056 mRNA-enriched anonymous microbial clones from diverse microbial communities to profile microbial gene transcripts. A new normalization method using internal spot standards was devised to overcome spotting and hybridization bias, enabling direct comparisons of microarrays. To evaluate potential applications of this metatranscriptomic approach for studying microbes in environmental samples, we tested the E-FGA by profiling the microbial activity of agricultural soils with a low or high flux of N₂O. A total of 109 genes displayed expression that differed significantly between soils with low and high N₂O emissions. We conclude that mRNA-based approaches such as the one presented here may complement existing techniques for assessing functional attributes of microbial communities.
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Project description:Soil microbial biomass carbon (SMBC) is important in regulating soil organic carbon (SOC) dynamics along soil profiles by mediating the decomposition and formation of SOC. The dataset (VDMBC) is about the vertical distributions of SOC, SMBC, and soil microbial quotient (SMQ = SMBC/SOC) and their relations to environmental factors across five continents. Data were collected from literature, with a total of 289 soil profiles and 1040 observations in different soil layers compiled. The associated environment data collectd include climate, ecosystem types, and edaphic factors. We developed this dataset by searching the Web of Sciene and the China National Knowledge Infrastructure from the year of 1970 to 2019. All the data in this dataset met two creteria: 1) there were at least three mineral soil layers along a soil profile, and 2) SMBC was measured using the fumigation extraction method. The data in tables and texts were obtained from literature directly, and the data in figures were extracted by using the GetData Graph digitizer software version 2.25. When climate and soil properties were not available from publications, we obtainted the data from the World Weather Information Service (https://worldweather.wmo.int/en/home.html) and SoilGrids at a spatial resolution of 250 meters (version 0.5.3, https://soilgrids.org). The units of all the variables were converted to the standard international units or commonly used ones and the values were transformed correspondingly. For example, the value of soil organic matter (SOM) was converted to SOC by using the equation (SOC = SOM × 0.58). This dataset can be used in predicting global SOC changes along soil profiles by using the multi-layer soil carbon models. It can also be used to analyse how soil microbial biomass changes with plant roots as well as the composition, structure, and functions of soil microbial communities along soil profiles at large spatial scales. This dataset offers opportunities to improve our prediction of SOC dynamics under global changes and to advance our understanding of the environmental controls.
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Project description:The recent application of macroecological tools and concepts has made it possible to identify consistent patterns in the distribution of microbial biodiversity, which greatly improved our understanding of the microbial world at large scales. However, the distribution of microbial functions remains largely uncharted from the macroecological point of view. Here, we used macroecological models to examine how the genes encoding the functional capabilities of microorganisms are distributed within and across soil systems. Models built using functional gene array data from 818 soil microbial communities showed that the occupancy-frequency distributions of genes were bimodal in every studied site, and that their rank-abundance distributions were best described by a lognormal model. In addition, the relationships between gene occupancy and abundance were positive in all sites. This allowed us to identify genes with high abundance and ubiquitous distribution (core) and genes with low abundance and limited spatial distribution (satellites), and to show that they encode different sets of microbial traits. Common genes encode microbial traits related to the main biogeochemical cycles (C, N, P and S) while rare genes encode traits related to adaptation to environmental stresses, such as nutrient limitation, resistance to heavy metals and degradation of xenobiotics. Overall, this study characterized for the first time the distribution of microbial functional genes within soil systems, and highlight the interest of macroecological models for understanding the functional organization of microbial systems across spatial scales.
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Project description:Various agriculture management practices may have distinct influences on soil microbial communities and their ecological functions. In this study, we utilized GeoChip, a high-throughput microarray-based technique containing approximately 28,000 probes for genes involved in nitrogen (N)/carbon (C)/sulfur (S)/phosphorus (P) cycles and other processes, to evaluate the potential functions of soil microbial communities under conventional (CT), low-input (LI), and organic (ORG) management systems at an agricultural research site in Michigan. Compared to CT, a high diversity of functional genes was observed in LI. The functional gene diversity in ORG did not differ significantly from that of either CT or LI. Abundances of genes encoding enzymes involved in C/N/P/S cycles were generally lower in CT than in LI or ORG, with the exceptions of genes in pathways for lignin degradation, methane generation/oxidation, and assimilatory N reduction, which all remained unchanged. Canonical correlation analysis showed that selected soil (bulk density, pH, cation exchange capacity, total C, C/N ratio, NO(3)(-), NH(4)(+), available phosphorus content, and available potassium content) and crop (seed and whole biomass) variables could explain 69.5% of the variation of soil microbial community composition. Also, significant correlations were observed between NO(3)(-) concentration and denitrification genes, NH(4)(+) concentration and ammonification genes, and N(2)O flux and denitrification genes, indicating a close linkage between soil N availability or process and associated functional genes.
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Project description:To compare microbial functional diversity in different oil-contaminated fields and to know the effects of oil contaminant and environmental factors, soil samples were taken from typical oil-contaminated fields located in five geographic regions of China. GeoChip, a high-throughput functional gene array, was used to evaluate the microbial functional genes involved in contaminant degradation and in other major biogeochemical/metabolic processes. Our results indicated that the overall microbial community structures were distinct in each oil-contaminated field, and samples were clustered by geographic locations. The organic contaminant degradation genes were most abundant in all samples and presented a similar pattern under oil contaminant stress among the five fields. In addition, alkane and aromatic hydrocarbon degradation genes such as monooxygenase and dioxygenase were detected in high abundance in the oil-contaminated fields. Canonical correspondence analysis indicated that the microbial functional patterns were highly correlated to the local environmental variables, such as oil contaminant concentration, nitrogen and phosphorus contents, salt and pH. Finally, a total of 59% of microbial community variation from GeoChip data can be explained by oil contamination, geographic location and soil geochemical parameters. This study provided insights into the in situ microbial functional structures in oil-contaminated fields and discerned the linkages between microbial communities and environmental variables, which is important to the application of bioremediation in oil-contaminated sites.
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