Biology subjects

Meyer, K. M.

Publications and source records attributed to Meyer, K. M..

11 recordsLinked to original sources

bioRxiv2025

Microbial dispersal from surrounding vegetation influences phyllosphere microbiome assembly of corn and soybean

Non-crop plants surrounding large plantings of agricultural crops can provide numerous ecological services to adjacent agricultural plants but have rarely been considered as a source of microorganisms during the early stages of their growth. In this study we test whether agricultural plants in close proximity to surrounding woodland habitat fragments develop a denser microbiome than plants farther away, and whether the composition of the crop microbiomes more closely resembles the composition of the surrounding vegetation when in close proximity. During the early stages of development, we sampled epiphytic bacteria from corn and soybean leaves over 4 and 3 weekly sampling timepoints, respectively, using a spatially explicit design, and on the final timepoint for both host species we additionally sampled a younger cohort of leaves. To contextualize the source strength of the surrounding vegetation we also sampled the soil at each sampling location. Both crop species exhibited a microbiome density gradient and a decay of microbiome similarity to surrounding vegetation over a distance of 100 m from the field edges at many timepoints. Phyllosphere microbiome similarity to the soil also tended to increase into the field interior. The strength of host plant microbiome filtering also depended on the proximity to the surrounding vegetation, with intermediate to most distant locations exhibiting the highest values of host filtering, reflecting an apparent decrease in immigrant inoculum. The bacterial communities of younger leaves tended to more closely resemble those of the older surrounding conspecific leaves than either the soil or surrounding woodland vegetation, reflecting the growing dominance of inoculum from within developing crop canopies as plants grew. Overall, our study sheds light on the important role that dispersal of bacteria from nearby leaves can play in phyllosphere microbiome assembly and highlights the diminishing role that soil plays in assembly of phyllosphere microbiomes as plant sources are closer or more abundant.

ecology↗

bioRxiv2023

Transmission mode shapes host specialization of the phyllosphere microbiome

The collection of microorganisms inhabiting aboveground plant tissue, termed the phyllosphere microbiome, is shaped by both microbial dispersal and host filtering effects. Because plants often occur in multispecies assemblages, microbiome diversity is likely shaped by plant community composition through microbial transmission between conspecific (same species) and heterospecific (different species) host plants. Although rarely examined, the relative incidence of con-versus heterospecific transmission should impact microbiome-level specialization. Using four species of plants we experimentally tested this idea by passaging an initially diverse microbial community either between conspecific or heterospecific plants in the greenhouse. While conspecific transmission lines exhibited persistent host effects, these effects decreased in the heterospecific transmission lines, suggesting a shift towards more generalist microbiomes. Similarly, when microbiomes were transplanted onto a set of novel host plant species, host effects were weaker for these heterospecific lines than the conspecific lines. Finally, microbiomes conspecifically passaged on tomato plants were found to outcompete those passaged on either bean or pepper when co-inoculated onto tomato hosts, suggesting microbiome-level host specialization under conspecific transmission. Overall, we find that both transmission mode and host association history shape microbiome diversity, that repeated conspecific transmission results in microbiome specialization, and that repeated heterospecific transmission can drive microbiomes to develop generalist characteristics.

ecology↗

bioRxiv2022

Relative abundance data can misrepresent heritability of the microbiome

Host genetics can shape microbiome composition, but to what extent it does, remains unclear. Like any other complex trait, this question can be addressed by estimating the heritability (h2) of the microbiome - the proportion of variance in the abundance of 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. We derived an analytical approximation for the heritability that one obtains when using such relative abundances and we uncovered three problems: 1) The interdependency between taxa leads to imprecise heritability estimates. 2) Large sample size leads to high false discovery rates, overestimating the number of heritable taxa. 3) Microbial co-abundances lead to biased heritability estimates. We conclude that caution must be taken when interpreting heritability estimates and comparing values across studies.

evolutionary biology↗

bioRxiv2021

Plant neighborhood shapes diversity and reduces interspecific variation of the phyllosphere microbiome

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 three-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. 16S 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.

ecology↗

bioRxiv2020

Amazonian soil metagenomes indicate different physiological strategies of microbial communities in response to land use change

Despite the global importance in ecological processes, the Amazon rainforest has been subjected to high rates of deforestation, mostly for pasturelands, over the last few decades. In this study, we used a combination of deep shotgun metagenomics and a machine learning approach to compare physiological strategies of microbial communities between contrasting forest and pasture soils. We showed that microbial communities (bacteria, archaea and viruses), and the composition of protein-coding genes are distinct in each ecosystem. The diversities of these metagenomic datasets are strongly correlated, indicating that the protein-coding genes found in any given sample of these soil types are predictable from their taxonomic lineages. Shifts in metagenome profiles reflected potential physiological differences caused by forest-to-pasture conversion with alterations in gene abundances related to carbohydrate and energy metabolisms. These variations in these gene contents are associated with several soil factors including C/N, temperature and H++Al3+ (exchangeable acidity). These data underscore that microbial community taxa and protein-coding genes co-vary. Differences in gene abundances for carbohydrate utilization, energy, amino acid, and xenobiotic metabolisms indicate alterations of physiological strategy with forest-to-pasture conversion, with potential consequences to C and N cycles. Our analysis also indicated that soil virome was altered and shifts in the viral community provide insights into increased health risks to human and animal populations.

microbiology↗

bioRxiv2020

Belowground changes to community structure alter methane-cycling dynamics in Amazonia

Amazonian rainforest is undergoing increasing rates of deforestation, driven primarily by cattle pasture expansion. Forest-to-pasture conversion has been associated with changes to ecosystem processes, including substantial increases in soil methane (CH4) emission. The drivers of this change in CH4 flux are not well understood. To address this knowledge gap, we measured soil CH4 flux, environmental conditions, and belowground microbial community attributes across a land use change gradient (old growth primary forest, cattle pasture, and secondary forest regrowth) in two Amazon Basin regions. Primary forest soils exhibited CH4 uptake at modest rates, while pasture soils exhibited CH4 emission at high but variable rates. Secondary forest soils exhibited low rates of CH4 uptake, suggesting that forest regrowth following pasture abandonment could reverse the CH4 sink-to-source trend. While few environmental variables were significantly associated with CH4 flux, we identified numerous microbial community attributes in the surface soil that explained substantial variation in CH4 flux with land use change. Among the strongest predictors were the relative abundance and diversity of methanogens, which both increased in pasture relative to forests. We further identified individual taxa that were associated with CH4 fluxes and which collectively explained ~50% of flux variance. These taxa included methanogens and methanotrophs, as well as taxa that may indirectly influence CH4 flux through acetate production, iron reduction, and nitrogen transformations. Each land type had a unique subset of taxa associated with CH4 fluxes, suggesting that land use change alters CH4 cycling through shifts in microbial community composition. Taken together, our results suggest that changes in CH4 flux from agricultural conversion could be driven by microbial responses to land use change in the surface soil, with both direct and indirect effects on CH4 cycling. This demonstrates the central role of microorganisms in mediating ecosystem responses to land use change in the Amazon Basin.

ecology↗

bioRxiv2020

Rainforest-to-pasture conversion stimulates soil methanogenesis across the Brazilian Amazon

The Amazon rainforest is a biodiversity hotspot and large terrestrial carbon sink that is threatened by agricultural conversion. Rainforest-to-pasture conversion leads to the release of a potent greenhouse gas by converting soil from a methane sink into a source. 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 (Santarem, Para and Ariquemes, Rondonia) 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 explain the greater methane flux. Furthermore, we found that secondary rainforests recovered as methane sinks, indicating the potential for reforestation to offset greenhouse gas emissions in the tropics. These findings are critical for informing land management practices and global tropical rainforest conservation.

microbiology↗

bioRxiv2019

Linking microbial communities to ecosystem functions: what we can learn from genotype-phenotype mapping in organisms

Microorganisms mediate many important ecosystem functions, yet it remains unclear to what extent microbial diversity or community composition is important for determining the rates of ecosystem-scale functions. This uncertainty limits our ability to predict and manage crucial microbially-mediated processes, such as nutrient loss and greenhouse gas emissions. Our lack of understanding stems from the relatively large diversity of microorganisms, the difficulty in directly identifying functional groups, and our limited ability to manipulate microbial community attributes. For this reason, we propose that integrating traditional biodiversity-ecosystem function research with ideas from genotype-phenotype mapping could provide the new perspective our discipline needs. We identify three insights from genotype-phenotype mapping that could be useful for microbial biodiversity-ecosystem function studies: the concept of \"agnostic\" mapping, the use of more powerful ways to account for multiple comparisons, and the incorporation of covariates into models of ecosystem function. We illustrate the potential for these approaches to elucidate microbial biodiversity-ecosystem function relationships by analyzing a subset of published data measuring methane oxidation rates from incubations of tropical soil. We assert that combining the approaches of traditional biodiversity-ecosystem function research with ideas from genotype-phenotype mapping will not only generate novel hypotheses about how complex microbial communities drive ecosystem function, but also help scientists predict and manage changes to ecosystem functions resulting from human activities.

ecology↗

bioRxiv2019

Community structure ecosystem function relationships in the Congo Basin methane cycle depend on the physiological scale of function

Belowground ecosystem processes can be highly variable and difficult to predict using microbial community data. Here we argue that this stems from at least three issues: 1) complex covariance structure of samples (with environmental conditions or spatial proximity) can make distinguishing biotic drivers a challenge, 2) communities can control ecosystem processes through multiple mechanisms, making the identification of these controls a challenge and 3) ecosystem function assessments can be broad in physiological scale, encapsulating multiple processes with unique microbially mediated controls. We test these assertions using methane (CH4)-cycling processes in soil samples collected along a wetland-to-upland habitat gradient in the Congo Basin. We perform our measurements of function under controlled laboratory conditions and include environmental covariates in statistical analyses to aid in identifying biotic drivers. We divide measurements of microbial communities into four attributes (abundance, activity, composition, and diversity) that represent different forms of community control. Lastly, our process measurements differ in physiological scale, including broader processes (gross methanogenesis and methanotrophy) that involve more mediating groups, to finer processes (hydrogenotrophic methanogenesis and high-affinity CH4 oxidation) with fewer mediating groups. We observed that finer scale processes can be more readily predicted from microbial community structure than broader scale processes. In addition, the nature of those relationships differed, with broad processes limited by abundance while fine-scale processes were associated with diversity and composition. These findings demonstrate the importance of carefully defining the physiological scale of ecosystem function and performing community measurements that represent the range of possible controls on ecosystem processes.

ecology↗

bioRxiv2019

Consistent bacterial responses to land use change across the tropics

Bacterial communities are a major component of global diversity and are intimately involved in most terrestrial biogeochemical processes. Despite their importance, we know far less about the response of bacteria to human-induced environmental change than we do about other organisms. Understanding the response of organisms to land use change is especially pressing for tropical rainforests, which are being altered at a higher rate than any other ecosystem. Here, we conduct a meta-analysis of studies performed in each of the major tropical rainforest regions to ask whether there are consistent responses of belowground bacterial communities to the conversion of tropical rainforest to agriculture. Remarkably, we find common responses despite wide variation across studies in the types of agriculture practiced and the research methodology used to study land use change. These responses include changes in the relative abundance of phyla, most notably decreases in Acidobacteria and Proteobacteria and increases in Actinobacteria, Chloroflexi and Firmicutes. We also find that alpha diversity (at the scale of single soil cores), consistently increases with ecosystem conversion. These consistent responses suggest that, while there is great diversity in agricultural practices across the tropics, common features such as the use of slash-and-burn tactics have the potential to alter bacterial community composition and diversity belowground.

ecology↗

bioRxiv2018

Use of RNA and DNA to Identify Mechanisms of Microbial Community Homogenization

Biotic homogenization is a commonly observed response following conversion of native ecosystems to agriculture, but our mechanistic understanding of this process is limited for microbial communities. In the case of rapid environmental changes, inference of homogenization mechanisms may be confounded by the fact that only a minority of taxa is active at any given point. RNA- and DNA-based community inference may help to distinguish the active fraction of a community from inactive taxa. Using these two community inference methods, we asked how soil prokaryotic communities respond to land use change following transition from rainforest to agriculture in the Congo Basin. Our results indicate that the magnitude of community homogenization is larger in the RNA-inferred community than the DNA-inferred perspective. We show that as the soil environment changes, the RNA-inferred community structure tracks environmental variation and loses spatial structure. The DNA-inferred community loses its association with environmental variability. Homogenization of the DNA-inferred community appears to instead be driven by the range expansion of a minority of taxa shared between the forest and conversion sites, which is also seen in the RNA-inferred community. Our results suggest that complementing DNA-based surveys with RNA can provide unique perspectives on community responses to environmental change.\n\nIMPORTANCETwo primary mechanisms by which community homogenization occurs are: 1) the loss of environmental heterogeneity driving community convergence, and 2) increased rates of biotic mixing, driven by exotic invasions or range expansions. Better identifying these mechanisms could help inform future mitigation strategies. Only a minority of soil taxa tends to be active at any time, which makes identifying these mechanisms difficult. To circumvent this problem, we measured prokaryotic community structure in two ways: RNA-based inference (which should enrich for active taxa), and DNA-based inference (which includes active and inactive taxa) along a gradient of land use change. Our results suggest that changes to soil heterogeneity impact the RNA-inferred community, while range expansions contribute to the homogenization of both DNA- and RNA-inferred communities. Thus, RNA-based community inference may be a more sensitive indicator of environmentally driven homogenization, and researchers interested in microbial responses to rapid environmental change should consider this method.

ecology↗