Background

Host genetics can shape microbiome composition, but to what extent it does, remains unclear. Like any other complex trait, this important question can be addressed by estimating the heritability (h²) of the microbiome-the proportion of variance in the abundance in each taxon that is attributable to host genetic variation. However, unlike most complex traits, microbiome heritability is typically based on relative abundance data, where taxon-specific abundances are expressed as the proportion of the total microbial abundance in a sample.

Results

We derived an analytical approximation for the heritability that one obtains when using such relative, and not absolute, abundances, based on an underlying quantitative genetic model for absolute abundances. Based on this, we uncovered three problems that can arise when using relative abundances to estimate microbiome heritability: (1) the interdependency between taxa can lead to imprecise heritability estimates. This problem is most apparent for dominant taxa. (2) Large sample size leads to high false discovery rates. With enough statistical power, the result is a strong overestimation of the number of heritable taxa in a community. (3) Microbial co-abundances lead to biased heritability estimates.

Conclusions

We discuss several potential solutions for advancing the field, focusing on technical and statistical developments, and conclude that caution must be taken when interpreting heritability estimates and comparing values across studies. Video Abstract.

Members of the phylum Acidobacteria are among the most abundant soil bacteria on Earth, but little is known about their response to environmental changes. We asked how the relative abundance and biogeographic patterning of this phylum and its subgroups responded to forest-to-pasture conversion in soils of the western Brazilian Amazon. Pyrosequencing of 16S rRNA genes was employed to assess the abundance and composition of the Acidobacteria community across 54 soil samples taken using a spatially nested sampling scheme at the landscape level. Numerically, Acidobacteria represented 20% of the total bacterial community in forest soils and 11% in pasture soils. Overall, 15 different Acidobacteria subgroups of the current 26 subgroups were detected, with Acidobacteria subgroups 1, 3, 5, and 6 accounting together for 87% of the total Acidobacteria community in forest soils and 75% in pasture soils. Concomitant with changes in soil chemistry after forest-to-pasture conversion-particularly an increase in properties linked to soil acidity and nutrient availability-we observed an increase in the relative abundances of Acidobacteria subgroups 4, 10, 17, and 18, and a decrease in the relative abundances of other Acidobacteria subgroups in pasture relative to forest soils. The composition of the total Acidobacteria community as well as the most abundant Acidobacteria subgroups (1, 3, 5, and 6) was significantly more similar in composition across space in pasture soils than in forest soils. These results suggest that preponderant responses of Acidobacteria subgroups, especially subgroups 1, 3, 4, 5, and 6, to forest-to-pasture conversion effects in soils could be used to define management-indicators of agricultural practices in the Amazon Basin. These acidobacterial responses are at least in part through alterations on acidity- and nutrient-related properties of the Amazon soils.

Microbial communities associated with plant leaf surfaces (i.e., the phyllosphere) are increasingly recognized for their role in plant health. While accumulating evidence suggests a role for host filtering of its microbiota, far less is known about how community composition is shaped by dispersal, including from neighboring plants. We experimentally manipulated the local plant neighborhood within which tomato, pepper, or bean plants were grown in a 3-month field trial. Focal plants were grown in the presence of con- or hetero-specific neighbors (or no neighbors) in a fully factorial combination. At 30-day intervals, focal plants were harvested and replaced with a new age- and species-matched cohort while allowing neighborhood plants to continue growing. Bacterial community profiling revealed that the strength of host filtering effects (i.e., interspecific differences in composition) decreased over time. In contrast, the strength of neighborhood effects increased over time, suggesting dispersal from neighboring plants becomes more important as neighboring plant biomass increases. We next implemented a cross-inoculation study in the greenhouse using inoculum generated from the field plants to directly test host filtering of microbiomes while controlling for directionality and source of dispersal. This experiment further demonstrated that focal host species, the host from which the microbiome came, and in one case the donor hosts' neighbors, contribute to variation in phyllosphere bacterial composition. Overall, our results suggest that local dispersal is a key factor in phyllosphere assembly, and that demographic factors such as nearby neighbor identity and biomass or age are important determinants of phyllosphere microbiome diversity.

Land use change is one of the greatest environmental impacts worldwide, especially to tropical forests. The Amazon rainforest has been subject to particularly high rates of land use change, primarily to cattle pasture. A commonly observed response to cattle pasture establishment in the Amazon is the conversion of soil from a methane sink in rainforest, to a methane source in pasture. However, it is not known how the microorganisms that mediate methane flux are altered by land use change. Here, we use the deepest metagenomic sequencing of Amazonian soil to date to investigate differences in methane-cycling microorganisms and their traits across rainforest and cattle pasture soils. We found that methane-cycling microorganisms responded to land use change, with the strongest responses exhibited by methane-consuming, rather than methane-producing, microorganisms. These responses included a reduction in the relative abundance of methanotrophs and a significant decrease in the abundance of genes encoding particulate methane monooxygenase. We also observed compositional changes to methanotroph and methanogen communities as well as changes to methanotroph life history strategies. Our observations suggest that methane-cycling microorganisms are vulnerable to land use change, and this vulnerability may underlie the response of methane flux to land use change in Amazon soils.

Deforestation in the Brazilian Amazon occurs at an alarming rate, which has broad effects on global greenhouse gas emissions, carbon storage, and biogeochemical cycles. In this study, soil metagenomes and metagenome-assembled genomes (MAGs) were analyzed for alterations to microbial community composition, functional groups, and putative physiology as it related to land-use change and tropical soil. A total of 28 MAGs were assembled encompassing 10 phyla, including both dominant and rare biosphere lineages. Amazon Acidobacteria subdivision 3, Melainabacteria, Microgenomates, and Parcubacteria were found exclusively in pasture soil samples, while Candidatus Rokubacteria was predominant in the adjacent rainforest soil. These shifts in relative abundance between land-use types were supported by the different putative physiologies and life strategies employed by the taxa. This research provides unique biological insights into candidate phyla in tropical soil and how deforestation may impact the carbon cycle and affect climate change.

Deforestation threatens the integrity of the Amazon biome and the ecosystem services it provides, including greenhouse gas mitigation. Forest-to-pasture conversion has been shown to alter the flux of methane gas (CH₄ ) in Amazonian soils, driving a switch from acting as a sink to a source of atmospheric CH₄ . This study aimed to better understand this phenomenon by investigating soil microbial metagenomes, focusing on the taxonomic and functional structure of methane-cycling communities. Metagenomic data from forest and pasture soils were combined with measurements of in situ CH₄ fluxes and soil edaphic factors and analysed using multivariate statistical approaches. We found a significantly higher abundance and diversity of methanogens in pasture soils. As inferred by co-occurrence networks, these microorganisms seem to be less interconnected within the soil microbiota in pasture soils. Metabolic traits were also different between land uses, with increased hydrogenotrophic and methylotrophic pathways of methanogenesis in pasture soils. Land-use change also induced shifts in taxonomic and functional traits of methanotrophs, with bacteria harbouring genes encoding the soluble form of methane monooxygenase enzyme (sMMO) depleted in pasture soils. Redundancy analysis and multimodel inference revealed that the shift in methane-cycling communities was associated with high pH, organic matter, soil porosity and micronutrients in pasture soils. These results comprehensively characterize the effect of forest-to-pasture conversion on the microbial communities driving the methane-cycling microorganisms in the Amazon rainforest, which will contribute to the efforts to preserve this important biome.

The Amazon rainforest is a biodiversity hotspot and large terrestrial carbon sink threatened by agricultural conversion. Rainforest-to-pasture conversion stimulates the release of methane, a potent greenhouse gas. The biotic methane cycle is driven by microorganisms; therefore, this study focused on active methane-cycling microorganisms and their functions across land-use types. We collected intact soil cores from three land use types (primary rainforest, pasture, and secondary rainforest) of two geographically distinct areas of the Brazilian Amazon (Santarém, Pará and Ariquemes, Rondônia) and performed DNA stable-isotope probing coupled with metagenomics to identify the active methanotrophs and methanogens. At both locations, we observed a significant change in the composition of the isotope-labeled methane-cycling microbial community across land use types, specifically an increase in the abundance and diversity of active methanogens in pastures. We conclude that a significant increase in the abundance and activity of methanogens in pasture soils could drive increased soil methane emissions. Furthermore, we found that secondary rainforests had decreased methanogenic activity similar to primary rainforests, and thus a potential to recover as methane sinks, making it conceivable for forest restoration to offset greenhouse gas emissions in the tropics. These findings are critical for informing land management practices and global tropical rainforest conservation.

There has been a recent major upsurge in the concerns about reproducibility in many areas of science. Within the neuroimaging domain, one approach is to promote reproducibility is to target the re-executability of the publication. The information supporting such re-executability can enable the detailed examination of how an initial finding generalizes across changes in the processing approach, and sampled population, in a controlled scientific fashion. ReproNim: A Center for Reproducible Neuroimaging Computation is a recently funded initiative that seeks to facilitate the "last mile" implementations of core re-executability tools in order to reduce the accessibility barrier and increase adoption of standards and best practices at the neuroimaging research laboratory level. In this report, we summarize the overall approach and tools we have developed in this domain.

Amazonian rainforest is undergoing increasing rates of deforestation, driven primarily by cattle pasture expansion. Forest-to-pasture conversion has been associated with increases in soil methane (CH₄) emission. To better understand the drivers of this change, we measured soil CH₄ flux, environmental conditions, and belowground microbial community structure across primary forests, cattle pastures, and secondary forests in two Amazonian regions. We show that pasture soils emit high levels of CH₄ (mean: 3454.6 ± 9482.3 μg CH₄ m^-2 d^-1), consistent with previous reports, while forest soils on average emit CH₄ at modest rates (mean: 9.8 ± 120.5 μg CH₄ m^-2 d^-1), but often act as CH₄ sinks. We report that secondary forest soils tend to consume CH₄ (mean: -10.2 ± 35.7 μg CH₄ m^-2 d^-1), demonstrating that pasture CH₄ emissions can be reversed. We apply a novel computational approach to identify microbial community attributes associated with flux independent of soil chemistry. While this revealed taxa known to produce or consume CH₄ directly (i.e. methanogens and methanotrophs, respectively), the vast majority of identified taxa are not known to cycle CH₄. Each land use type had a unique subset of taxa associated with CH₄ flux, suggesting that land use change alters CH₄ cycling through shifts in microbial community composition. Taken together, we show that microbial composition is crucial for understanding the observed CH₄ dynamics and that microorganisms provide explanatory power that cannot be captured by environmental variables.