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At least 19 records

Cooperative microbial interactions drive spatial segregation in porous environments

The role of microbial interactions and the underlying mechanisms that shape complex biofilm communities are poorly understood. Here we employ a microfluidic chip to represent porous subsurface environments and show that cooperative microbial interactions between free-living and biofilm-forming bacteria trigger active spatial segregation to promote their respective dominance in segregated microhabitats. During initial colonization, free-living and biofilm-forming microbes are segregated from the mixed planktonic inoculum to occupy the ambient fluid and grain surface. Contrary to spatial exclusion through competition, the active spatial segregation is induced by cooperative interactions which improves the fitness of both biofilm and planktonic populations. We further show that free-living Arthrobacter induces the surface colonization by scavenging the biofilm inhibitor, D-amino acids and receives benefits from the public goods secreted by the biofilm-forming strains. Collectively, our results reveal how cooperative microbial interactions may contribute to microbial coexistence in segregated microhabitats and drive subsurface biofilm community succession.

59 BASIC BIOLOGICAL SCIENCES↗

Mass spectrometry imaging of natural carbonyl products directly from agar-based microbial interactions using 4-APEBA derivatization

Aliphatic carboxylic acids, aldehydes, and ketones play diverse roles in microbial adaptation to their microenvironment, from excretion as toxins to adaptive metabolites for membrane fluidity. However, the spatial distribution of these molecules throughout biofilms and how microbes in these environments exchange these molecules remain elusive for many of these bioactive species due to inefficient molecular imaging strategies. Herein, we apply on-tissue chemical derivatization (OTCD) using 4-(2-((4-bromophenethyl)dimethylammonio)ethoxy)benzenaminium dibromide (4-APEBA) on a co-culture of a soil bacterium (Bacillus subtilis NCIB 3610) and fungus (Fusarium sp. DS 682) grown on agar as our model system. Using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), we spatially resolved more than 300 different metabolites containing carbonyl groups within this model system. Various spatial patterns are observable in these species, which indicate possible extracellular or intercellular processes of the metabolites and their up- or downregulation during microbial interaction. The unique chemistry of our approach allowed us to bring additional confidence in accurate carbonyl identification, especially when multiple isomeric candidates were possible, and this provided the ability to generate hypotheses about the potential role of some aliphatic carbonyls in this B. subtilis/Fusarium sp. interaction. The results shown here demonstrate the utility of 4-ABEBA-based OTCD MALDI-MSI in probing interkingdom interactions directly from microbial co-cultures, and these methods will enable future microbial interaction studies with expanded metabolic coverage.

4-APEBA↗

Construction and Modeling of a Coculture Microplate for Real-Time Measurement of Microbial Interactions

The dynamic structures of microbial communities emerge from the complex network of interactions between their constituent microorganisms. Quantitative measurements of these interactions are important for understanding and engineering ecosystem structure. Here, we present the development and application of the BioMe plate, a redesigned microplate device in which pairs of wells are separated by porous membranes. BioMe facilitates the measurement of dynamic microbial interactions and integrates easily with standard laboratory equipment. We first applied BioMe to recapitulate recently characterized, natural symbiotic interactions between bacteria isolated from the Drosophila melanogaster gut microbiome. Specifically, the BioMe plate allowed us to observe the benefit provided by two Lactobacillus strains to an Acetobacter strain. We next explored the use of BioMe to gain quantitative insight into the engineered obligate syntrophic interaction between a pair of Escherichia coli amino acid auxotrophs. We integrated experimental observations with a mechanistic computational model to quantify key parameters associated with this syntrophic interaction, including metabolite secretion and diffusion rates. This model also allowed us to explain the slow growth observed for auxotrophs growing in adjacent wells by demonstrating that, under the relevant range of parameters, local exchange between auxotrophs is essential for efficient growth. The BioMe plate provides a scalable and flexible approach for the study of dynamic microbial interactions.

3D printed device↗

Corrinoids as model nutrients to probe microbial interactions in a soil ecosystem

Earth’s soils are habitats for microbial communities that drive biogeochemical cycling, plant growth, and carbon storage and persistence. The thousands of microbial species living in soil form an intricate web of interactions involving the exchange of molecules produced by different microbes. Understanding in detail how these molecular exchanges occur and how they shape microbial communities may lead to new methods to improve soil health, bioremediation efforts, and better understanding of biogeochemical processes. The overall goal of this research is to gain a deeper knowledge of the microbial interactions that drive soil community structure. However, the high functional and genomic diversity in soil microbiomes has posed a challenge for current microbiology methods to achieve this goal. This research leverages a model group of key metabolites related to cobalamin (vitamin B 12 ), known as corrinoids, to investigate microbial interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Inferring microbial interactions with their environment from genomic and metagenomic data

Microbial communities assemble through a complex set of interactions between microbes and their environment, and the resulting metabolic impact on the host ecosystem can be profound. Microbial activity is known to impact human health, plant growth, water quality, and soil carbon storage which has lead to the development of many approaches and products meant to manipulate the microbiome. In order to understand, predict, and improve microbial community engineering, genome-scale modeling techniques have been developed to translate genomic data into inferred microbial dynamics. However, these techniques rely heavily on simulation to draw conclusions which may vary with unknown parameters or initial conditions, rather than more robust qualitative analysis. To better understand microbial community dynamics using genome-scale modeling, we provide a tool to investigate the network of interactions between microbes and environmental metabolites over time. Using our previously developed algorithm for simulating microbial communities from genome-scale metabolic models (GSMs), we infer the set of microbe-metabolite interactions within a microbial community in a particular environment. Because these interactions depend on the available environmental metabolites, we refer to the networks that we infer as metabolically contextualized , and so name our tool MetConSIN: Met abolically Con textualized S pecies I nteraction N etworks.

59 BASIC BIOLOGICAL SCIENCES↗

Unlocking plant-microbial interactions in deep Mollisols in the Midwestern US: Linking depth gradients in roots, microbial activity, and soil carbon in agroecosystems

Deep-rooted plants may build soil carbon (C) stocks, but most research has focused on shallow soils, leaving gaps in our understanding of how shifts in the balance between decomposition and C inputs drive soil C accumulation with depth. Thus, our objectives were to: (1) link depth gradients in root biomass with microbial activity and soil C stocks down to 1 m, and (2) examine the potential of simple C inputs to prime soil C across depths. To this end, we dug 5 quantitative soil pits in Argiudolls under mature perennial miscanthus plots in the SoyFACE Farm (Champaign-Urbana, IL). We added 13 C labeled glucose to our soils to determine the fate of simple C inputs with depth. We found that fine root biomass, total soil C, mineral-associated organic C (MAOC), particulate organic C (POC), and microbial activity (as measured by potential enzyme activity) declined with depth. POC declined more rapidly than MAOC, resulting in an increase in the ratio of MAOC-to-POC. Root biomass, enzyme activity (either acid phosphatase or n-acetyl-glucosaminadase) activity, and microbial respiration explained 74% and 38% of the variability in soil total C and MAOC, respectively, while POC was dependent on root biomass and microbial respiration (47%). Although the incorporation of simple 13 C inputs into MAOC was similar across depths, these inputs led to greater net MAOC losses in shallow soils than in deeper soils between 50 and 100 cm. The divergent impact of simple C inputs across depths may suggest that MAOC in shallow soils is more susceptible to priming losses, while C inputs into deep soils may instead be more persistent. Collectively, our results suggest that depth gradients in soil C stocks represents a balance between inputs, decomposition, and microbial necromass production and that increases in root C inputs by deep-rooted plants may have the potential to build stable MAOC.

60 APPLIED LIFE SCIENCES↗

Microbial Interactions Related to N 2 O Emissions and Temperature Sensitivity from Rice Paddy Fields

The soil microbiome is a driver of nitrous oxide (N 2 O) emissions in terrestrial ecosystems. Identifying the core microbiome of N 2 O emissions and its temperature sensitivity from trillions of soil microorganisms is a great challenge and is essential to improving the predictability of soil-climate feedback related to increasing temperature. Here, the integrated soil microbiome covering archaeal, bacterial, fungal, algal, and microfaunal communities was studied to disengage the potential linkage with its N 2 O emissions and its temperature sensitivity in paddy fields by hunting for core species pairs. The results showed that between-group interactions of core bacterial and archaeal members and the within-group interactions of core bacterial members jointly contributed to the N 2 O emissions and its temperature sensitivity. The contribution of between-group interactions (32 to 33%) was greater than that of within groups (10 to 18%). These results suggested that N 2 O emissions and their fluctuations related to climate warming are affected by the within- and between-group interactions of the soil microbiome. Our results help advance the knowledge on the importance of microbial keystone species and network associations in controlling N 2 O production and their responses to increasing temperature.

59 BASIC BIOLOGICAL SCIENCES↗

Microbial interactions with phosphorus containing glasses representative of vitrified radioactive waste

The presence of phosphorous in borosilicate glass (at 0.1 – 1.3 mol % P 2 O 5 ) and in iron-phosphate glass (at 53 mol % P 2 O 5 ) stimulated the growth and metabolic activity of anaerobic bacteria in model systems. Dissolution of these phosphorous containing glasses was either inhibited or accelerated by microbial metabolic activity, depending on the solution chemistry and the glass composition. The breakdown of organic carbon to volatile fatty acids increased glass dissolution. The interaction of microbially reduced Fe(II) with phosphorus-containing glass under anoxic conditions decreased dissolution rates, whereas the interaction of Fe(III) with phosphorous-containing glass under oxic conditions increased glass dissolution. Phosphorous addition to borosilicate glasses did not significantly affect the microbial species present, however, the diversity of the microbial community was enhanced on the surface of the iron phosphate glass. Results demonstrate the potential for microbes to influence the geochemistry of radioactive waste disposal environments with implication for wasteform durability.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Accounting for linkages between wildfire-driven shifts in plant-microbial interactions and soil carbon dynamics in Arctic tundra

Increasing wildfire regimes in the rapidly changing Arctic tundra are altering the soil carbon budget through increased permafrost degradation, shrubs expansion, and shifts in microbial activities. Whether future arctic wildfires will result in net C losses or gains in the future will depend on complex biotic and abiotic interactions that regulate belowground C biogeochemical processes, including linkages among biotic communities. One important linkage is plant-microbe interactions. While these interactions are likely shaped or altered by wildfires, they remain little explored in the context of successional trajectories. Yet, incorporating plant-microbe interactions in frameworks for defining and understanding post-fire soil C trajectories is critical to predict belowground C responses to future tundra wildfires. Here, we provide examples of and discuss how fire-mediated changes in plant-soil-microbe (PSM) interactions can impact soil C dynamics in the Arctic tundra. We consider different impacts of wildfires on PSM interactions and their implications to soil C dynamics, as well as the nuances associated with particular wildfire regimes (severity and intensity) and successional timescales. We suggest that accounting for plant-microbial linkages in future wildfire-succession interactions frameworks can inform future experimental designs and reduce uncertainties in our ability to predict the net effect of Arctic wildfires on ecosystem C.

fungi, bacteria↗

Plant myo -inositol transport influences bacterial colonization phenotypes

Plant microbiomes are assembled and modified through a complex milieu of biotic and abiotic factors. Despite dynamic and fluctuating contributing variables, specific host metabolites are consistently identified as important mediators of microbial interactions. We combine information from a large-scale metatranscriptomic dataset from natural poplar trees and experimental genetic manipulation assays in seedlings of the model plant Arabidopsis thaliana to converge on a conserved role for transport of the plant metabolite myo-inositol in mediating host-microbe interactions. While microbial catabolism of this compound has been linked to increased host colonization, we identify bacterial phenotypes that occur in both catabolism-dependent and -independent manners, suggesting that myo-inositol may additionally serve as a eukaryotic-derived signaling molecule to modulate microbial activities. Our data suggest host control of this compound and resulting microbial behavior are important mechanisms at play surrounding the host metabolite myo-inositol.

59 BASIC BIOLOGICAL SCIENCES↗

Microbial Models for Simulating Soil Carbon Dynamics: A Review

Abstract Soils store the largest amount of carbon (C) in the biosphere, and the C pool in soil is critical to the global C balance. Numerous microbial models have been developed over the last few decades to represent microbial processes that regulate the responses of soil organic carbon (SOC) to climate change. However, the representation of microbial processes varies, and how microbial processes are incorporated into SOC models has not been well explored. Here, we reviewed 71 microbial models to characterize the microbial processes incorporated into SOC models and analyzed variations in mechanistic complexity. We revealed that (a) four processes (microbial‐mediated decomposition, mineral interaction, microbial necromass recycling, and active and dormant microbial dynamics) are commonly incorporated in microbial models, (b) ∼48% of models simulate only one microbial process (i.e., microbial‐mediated decomposition) and 35% of models simulate two microbial processes: for example, microbial‐mediated decomposition and mineral interaction, (c) more than 80% microbial models use nonlinear equations, such as forward Michaelis‐Menten kinetics, to represent SOC decomposition, (d) the concept of persistence of SOC due to its intrinsic properties has been replaced by organo‐mineral interaction (∼39% of microbial models) that protects SOC from decomposition, and (e) various temperature and moisture modifiers and pH effects have been used to explain the environmental effect on microbial processes. In the future, to realistically incorporate microbial processes into Earth System Models, it is imperative to identify experimental evidence on rate limitation processes and firmly ground model structure on the field and laboratory data.

Environmental Sciences & Ecology↗

Enhancement on selenium volatilization for phytoremediation: role of plant and soil microbe interaction

This study aimed at quantifying the potential effects of plant and soil microbial interaction on selenium (Se) volatilization, with the specific objectives of identifying soil bacteria associated with rabbitfoot grass (Polypogon monspeliensis) and demonstrating the enhancement of Se volatilization in the soil-Indian mustard (Brassica juncea) system through inoculation of the soil with the identified best Se-volatilizing bacterial strain. Soil bacteria were isolated from topsoil and rhizosphere soils of rabbitfoot grass, and the bacterial colonies were characterized via PCR-DGGE and DGGE band analysis prior to their identification using 16S rDNA sequencing technique.Bacillus cereusproduced over 500-fold more volatile Se in a culture medium treated with 15 µg Se/mL (equal mixture of SeO 4 2- , SeO 3 2- and selenomethionine) than any of the other eight identified bacterial strains. Inoculation of Indian mustard vegetated soil with the best Se volatilizing bacterial strainB. cereusresulted in a significant (p<0.05) increase in Se volatilization during a 7-day time period, compared to the soil-plant system without inoculation ofB. cereus. Thus, inoculation of the soil withB. cereussubstantially enhanced Se removal via biogenic volatilization in the soil-Indian mustard system. This study evaluated the role ofB. cereusin enhancing Se volatilization in soil-plant systems, and demonstrated the importance of plant and soil microbial interaction for Se phytoremediation.

Plant Sciences↗

Interactions with microbial consortia have variable effects in organic carbon and production of exometabolites among genotypes of Populus trichocarpa

Abstract Poplar is a short‐rotation woody crop frequently studied for its significance as a sustainable bioenergy source. The successful establishment of a poplar plantation partially depends on its rhizosphere—a dynamic zone governed by complex interactions between plant roots and a plethora of commensal, mutualistic, symbiotic, or pathogenic microbes that shape plant fitness. In an exploratory endeavor, we investigated the effects of a consortium consisting of ectomycorrhizal fungi and a beneficial Pseudomonas sp. strain GM41 on plant growth (including height, stem girth, leaf, and root growth) and as well as growth rate over time, across four Populus trichocarpa genotypes. Additionally, we compared the level of total organic carbon and plant exometabolite profiles across different poplar genotypes in the presence of the microbial consortium. These data revealed no significant difference in plant growth parameters between the treatments and the control across four different poplar genotypes at 7 weeks post‐inoculation. However, total organic carbon and exometabolite profiles were significantly different between the genotypes and the treatments. These findings suggest that this microbial consortium has the potential to trigger early signaling responses in poplar, influencing its metabolism in ways crucial for later developmental processes and stress tolerance.

59 BASIC BIOLOGICAL SCIENCES↗

Whole‐Cell MALDI‐ToF MS Coupled with Untargeted Metabolomics Facilitates Investigations of Microbial Chemical Interactions

Abstract The emergence of drug‐resistant pathogens necessitates the development of new countermeasures. In this regard, the introduction of probiotics to directly attack or competitively exclude pathogens presents a useful strategy. Application of this approach requires an understanding of how a probiotic and its target pathogen interact. A key means of probiotic‐pathogen interaction involves the production of small molecules called natural products (NPs). Here, we report the use of whole‐cell matrix‐assisted laser desorption/ionization time‐of‐flight (MALDI‐ToF) mass spectrometry to characterize NP production by candidate probiotics (mouse airway microbiome isolates) when co‐cultured with the respiratory pathogen Burkholderia . We found that a Bacillus velezensis strain inhibits growth of and elicits NP production by Burkholderia thailandensis . Dereplication of known NPs detected in the metabolome of this B. velezensis strain suggests that a previously unannotated bioactive compound is involved. Thus, we present the use of whole‐cell MALDI as a broadly applicable method for screening the NP composition of microbial co‐cultures; this can be combined with other ‐omics methods to characterize probiotic‐pathogen and other microbe‐microbe interactions.

Aiosa, Nicole↗

Functional team selection as a framework for local adaptation in plants and their belowground microbiomes

Abstract Multicellular organisms are hosts to diverse communities of smaller organisms known as microbiomes. Plants have distinctive microbiomes that can provide important functions related to nutrition, defense, and stress tolerance. Empirical studies provide convincing evidence that in some—but not all—circumstances, belowground microbiomes help plants adapt to their local environment. The purpose of this review is to develop functional team selection (FTS) as a framework to help predict the conditions necessary for root microbiomes to generate local adaptation for their plant hosts. FTS envisions plants and their microbiomes as complex adaptive systems, and plant adaptations as emergent properties of these systems. If plants have the capacity to recognize and cultivate beneficial microbes and suppress pathogens, then it is possible for plants to evolve the capacity to gain adaptations by curating their microbiome. In resource-limited and stressful environments, the emergent functions of complex microbial systems may contribute to positive feedback linked to plant vigor, and ultimately, local adaptation. The key factors in this process are: (i) selective force, (ii) host constitution, (iii) microbial diversity, and (iv) time. There is increasing interest in harnessing beneficial microbial interactions in agriculture and many microbial growth-promoting products are commercially available, but their use is controversial because a large proportion of these products fail to consistently enhance plant growth. The FTS framework may help direct the development of durable plant-microbiome systems that enhance crop production and diminish pathogens. It may also provide valuable insights for understanding and managing other kinds of host-microbe systems.

Environmental Sciences & Ecology↗

Community response of soil microorganisms to combined contamination of polycyclic aromatic hydrocarbons and potentially toxic elements in a typical coking plant

Both polycyclic aromatic hydrocarbons (PAHs) and potentially toxic elements (PTEs) of coking industries impose negative effects on the stability of soil ecosystem. Soil microbes are regarded as an essential moderator of biochemical processes and soil remediation, while their responses to PAHs-PTEs combined contamination are largely unknown. In the present study, soil microbial diversity and community composition in the typical coking plant under the chronic co-exposure of PAHs and PTEs were investigated and microbial interaction networks were built to reveal microbial co-occurrence patterns. The results indicated that the concentrations of PAHs in the soil inside the coking plant were significantly higher than those outside the plant. The mean concentration of ∑16PAHs was 2894.4 ng·g −1 , which is 5.58 times higher than that outside the plant. The average Hg concentration inside the coking plant was 22 times higher than the background value of Hebei province. The soil fungal community inside the coking plant showed lower richness compared with that of outside community, and there are significant difference in the bacterial and fungal community composition between inside and outside of coking plant ( p < 0.01). Predicted contribution of different environmental factors to each dominant species based on random forest identified 20 and 25 biomarkers in bacteria and fungi, respectively, that were highly sensitive to coking plant soil in operation, such as Betaproteobacteria,Sordariomycetes and Dothideomycetes . Bacterial and fungal communities were shaped by the soil chemical properties (pH), PTEs (Hg), and PAHs together in the coking plant soils. Furthermore, the bacterial and fungal interaction patterns were investigated separately or jointly by intradomain and interdomain networks. Competition is the main strategy based on the co-exclusion pattern in fungal community, and the competitive relationship inside the coking plant is more complex than that outside the plant. In contrast, cooperation is the dominant strategy in bacterial networks based on the co-occurrence pattern. The present study provided insights into microbial response strategies and the interactions between bacteria and fungi under long-term combined contamination.

Shen, Qihui↗

Latent Dirichlet Allocation modeling of environmental microbiomes

Interactions between stressed organisms and their microbiome environments may provide new routes for understanding and controlling biological systems. However, microbiomes are a form of high-dimensional data, with thousands of taxa present in any given sample, which makes untangling the interaction between an organism and its microbial environment a challenge. Here we apply Latent Dirichlet Allocation (LDA), a technique for language modeling, which decomposes the microbial communities into a set of topics (non-mutually-exclusive sub-communities) that compactly represent the distribution of full communities. LDA provides a lens into the microbiome at broad and fine-grained taxonomic levels, which we show on two datasets. In the first dataset, from the literature, we show how LDA topics succinctly recapitulate many results from a previous study on diseased coral species. We then apply LDA to a new dataset of maize soil microbiomes under drought, and find a large number of significant associations between the microbiome topics and plant traits as well as associations between the microbiome and the experimental factors, e.g. watering level. This yields new information on the plant-microbial interactions in maize and shows that LDA technique is useful for studying the coupling between microbiomes and stressed organisms.

59 BASIC BIOLOGICAL SCIENCES↗