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At least 19 records

Modest functional diversity decline and pronounced composition shifts of microbial communities in a mixed waste-contaminated aquifer

Background: Microbial taxonomic diversity declines with increased environmental stress. Yet, few studies have explored whether phylogenetic and functional diversities track taxonomic diversity along the stress gradient. Here, we investigated microbial communities within an aquifer in Oak Ridge, Tennessee, USA, which is characterized by a broad spectrum of stressors, including extremely high levels of nitrate, heavy metals like cadmium and chromium, radionuclides such as uranium, and extremely low pH (< 3). Results: Both taxonomic and phylogenetic α-diversities were reduced in the most impacted wells, while the decline in functional α-diversity was modest and statistically insignificant, indicating a more robust buffering capacity to environmental stress. Differences in functional gene composition (i.e., functional β-diversity) were pronounced in highly contaminated wells, while convergent functional gene composition was observed in uncontaminated wells. The relative abundances of most carbon degradation genes were decreased in contaminated wells, but genes associated with denitrification, adenylylsulfate reduction, and sulfite reduction were increased. Compared to taxonomic and phylogenetic compositions, environmental variables played a more significant role in shaping functional gene composition, suggesting that niche selection could be more closely related to microbial functionality than taxonomy. Conclusions: Overall, we demonstrated that despite a reduced taxonomic α-diversity, microbial communities under stress maintained functionality underpinned by environmental selection.

59 BASIC BIOLOGICAL SCIENCES↗

Development and Validation of a Process Model and Open-Source Process Simulator for Microalgae-Based Tertiary Phosphorus Recovery

Microalgae-based tertiary wastewater treatment has the potential to meet stringent effluent phosphorus limits, with the added benefit of producing a marketable feedstock. However, the lack of validated mechanistic models and their implementation in process simulators have limited the adoption of this technology. In this study, an updated lumped pathway metabolic model (Phototrophic-Mixotrophic Process Model, PM 2 ), including both photoautotrophic and heterotrophic metabolisms of microalgae, was developed to predict effluent phosphorus concentration and biomass yield in response to dynamic influent and varying environmental conditions. The model was implemented in QSDsan – an open-source, Python-based design and simulation platform – for robust simulation under uncertainty. A global sensitivity analysis was performed to prioritize model parameters for calibration. The model was then calibrated and validated using batch experimental data and 45 days of continuous online monitoring data from a full-scale (568 m 3 ·d -1 ) microalgae-based tertiary wastewater treatment plant (EcoRecover process). In particular, along with dynamic influent composition, temperature and light intensity data with diel variation were provided as model inputs to reflect the microalgal behavior under day-night cycling. Overall, the QSDsan-based microalgae process simulator was able to predict effluent phosphorus within 0.02–0.04 mg-P·L -1 , while also capturing the general trends of state variables according to nutrient availability.

Lumped pathway metabolic model↗

Mixed and membrane-separated culturing of synthetic cyanobacteria-yeast consortia reveals metabolic cross-talk mimicking natural cyanolichens

Metabolite exchange mediates crucial interactions in microbial communities, significantly impacting global carbon and nitrogen cycling. Understanding these chemically-mediated interactions is essential for elucidating natural community functions and developing engineered synthetic communities. This study investigated membrane-separated bioreactors (mBRs) as a novel tool to identify transient metabolites and their producers/consumers in mixed microbial communities. We compared three co-culture methods (direct mixed, 2-chamber mBR, and 3-chamber mBR) to grow a synthetic binary community of the cyanobacterium Synechococcus elongatus PCC 7942 and the fungus Rhodotorula toruloides NBRC 0880, as well as axenic S. elongatus. Despite not being natural lichen constituents, these organisms exhibited interactions resembling those in cyanolichens. S. elongatus fixed CO 2 into sugars as the primary shared metabolite, while R. toruloides secreted various biochemicals, predominantly sugar alcohols, mirroring the metabolite exchange observed in natural lichens. The mBR systems successfully captured metabolite gradients and revealed rapidly consumed compounds, including TCA cycle intermediates and amino acids. Our approach demonstrated that the 2-chamber mBR optimally balanced metabolite exchange and growth dynamics. This study provides insights into cross-species metabolic interactions and presents a valuable tool for investigating and engineering synthetic microbial communities with potential applications in biotechnology and environmental science.

59 BASIC BIOLOGICAL SCIENCES↗

Patchy burn severity explains heterogeneous soil viral and prokaryotic responses to fire in a mixed conifer forest

ABSTRACT Effects of fire on soil viruses and virus–host dynamics are largely unexplored, despite known microbial contributions to biogeochemical processes and ecosystem recovery. Here, we assessed how viral and prokaryotic communities responded to a prescribed burn in a mixed conifer forest. We sequenced 91 viral-size fraction metagenomes (viromes) and 115 16S rRNA gene amplicon libraries from 120 samples: four samples at five timepoints (two before fire and three after fire) at six sites (four treatment, two control). We hypothesized that compositional differences would be most significant between burned and unburned soils, but instead, plot location best distinguished viral communities, more than treatment (burned or not), depth (0–3 or 3–6 cm), or timepoint. For both viruses and prokaryotes, some burned communities resembled unburned controls, while others were significantly different, revealing heterogeneous responses to fire. These patterns were explained by burn severity, here defined by soil chemistry. Viral but not prokaryotic richness decreased significantly with burn severity, and low viromic DNA yields indicated substantial loss of viral biomass at higher severity. The relative abundances of Firmicutes, Actinobacteriota, and the viruses predicted to infect them increased significantly with burn severity, suggesting survival and viral infection of these fire-responsive and potentially spore-forming taxa. The degree of burn severity experienced by each patch of soil, rather than burn status alone, differed over mere meters in the same fire. Therefore, our analyses highlight the importance of high-resolution, paired biogeochemical data to explain soil community responses to fire. IMPORTANCE The impact of fire on the soil microbiome, particularly on understudied soil viral communities, warrants investigation, given known microbial contributions to biogeochemical processes and ecosystem recovery. Here, we collected 120 soil samples before and after a prescribed burn in a mixed conifer forest to assess the impacts of this disturbance on soil viral and prokaryotic communities. We show that simple categorical comparisons of burned and unburned areas were insufficient to reveal the underlying community response patterns. The patchy nature of the fire (indicated by soil chemistry data) led to significant changes in viral and prokaryotic community composition in areas of high burn severity, while communities that experienced lower burn severity were indistinguishable from those in unburned controls. Our results highlight the importance of considering highly resolved burn severity and biogeochemical measurements, even in nearby soils after the same fire, in order to understand soil microbial responses to prescribed burns.

Microbiology↗

Response of soil nutrient pools and microbiomes to recurrent wildfire disturbance and varying burn severities in a mixed conifer forest

Wildfire is a pervasive disturbance in mixed-conifer forests, yet the relative influence of fire recurrence versus burn severity on soil biogeochemistry and microbial communities remains poorly quantified. We examined a natural gradient of fire history (0–3 prior fires) and burn severity (low–high) spanning 50 yr in a mixed-conifer ecosystem to assess how repeated fire shapes soil carbon (C) and nitrogen (N) pools, their isotopic signatures, mineral and particulate fractions, microbial community composition, carbon-use, CO₂ fluxes, and vegetation cover. Successive fires produced progressively higher bare-ground percentages and lower tree cover, which were tightly linked to declines in microbial diversity and reductions bulk %C, and %N. δ 13 C increased with fire frequency, indicating preferential loss of labile C through combustion or enhanced microbial oxidation, thereby explaining the observed net soil-C decline. Conversely, δ 15 N decreased and pH increased as tree density declined, reflecting altered N cycling and reduced acidification in post-fire soils. Fire recurrence, more than severity, corresponded with a marked shift in the bacterial community: for example, Xanthobacteraceae—key N-fixers and C-cyclers—diminished, while N-fixing Bacillaceae increased, underscoring the tightly coupled nature of soil nutrient dynamics and microbiome composition after repeated burns. Our results demonstrate that fire recurrence appears to be a stronger driver of post-fire soil ecosystem responses in this mixed-conifer forest, influencing both abiotic nutrient pools and the functional potential of the soil microbiome. These findings provide a more enhanced assessment and understanding to date of the biogeochemical consequences of repeated wildfire disturbance that can be used to inform management strategies aimed at preserving soil health in fire-prone landscapes.

54 ENVIRONMENTAL SCIENCES↗

Metagenome-assembled genomes provide insight into the metabolic potential during early production of Hydraulic Fracturing Test Site 2 in the Delaware Basin

Demand for natural gas continues to climb in the United States, having reached a record monthly high of 104.9 billion cubic feet per day (Bcf/d) in November 2023. Hydraulic fracturing, a technique used to extract natural gas and oil from deep underground reservoirs, involves injecting large volumes of fluid, proppant, and chemical additives into shale units. This is followed by a “shut-in” period, during which the fracture fluid remains pressurized in the well for several weeks. The microbial processes that occur within the reservoir during this shut-in period are not well understood; yet, these reactions may significantly impact the structural integrity and overall recovery of oil and gas from the well. To shed light on this critical phase, we conducted an analysis of both pre-shut-in material alongside production fluid collected throughout the initial production phase at the Hydraulic Fracturing Test Site 2 (HFTS 2) located in the prolific Wolfcamp formation within the Permian Delaware Basin of west Texas, USA. Specifically, we aimed to assess the microbial ecology and functional potential of the microbial community during this crucial time frame. Prior analysis of 16S rRNA sequencing data through the first 35 days of production revealed a strong selection for a Clostridia species corresponding to a significant decrease in microbial diversity. Here, we performed a metagenomic analysis of produced water sampled on Day 33 of production. This analysis yielded three high-quality metagenome-assembled genomes (MAGs), one of which was a Clostridia draft genome closely related to the recently classified Petromonas tenebris. This draft genome likely represents the dominant Clostridia species observed in our 16S rRNA profile. Annotation of the MAGs revealed the presence of genes involved in critical metabolic processes, including thiosulfate reduction, mixed acid fermentation, and biofilm formation. These findings suggest that this microbial community has the potential to contribute to well souring, biocorrosion, and biofouling within the reservoir. Our research provides unique insights into the early stages of production in one of the most prolific unconventional plays in the United States, with important implications for well management and energy recovery.

natural gas↗

The anaerobic fungus Neocallimastix californiae shifts metabolism and produces melanin in response to lignin-derived aromatic compounds

Biological deconstruction of lignocellulose for sustainable chemical production offers an opportunity to harness evolutionarily specialized enzymes and organisms for industrial bioprocessing. While hydrolysis of cellulose and hemicellulose by CAZymes yields fermentable sugars, ligninolysis releases a heterogeneous mix of aromatic compounds that likely play a crucial role in shaping microbial communities and microbial metabolism. Here, we interrogated the metabolomic and transcriptomic response of a lignocellulolytic anaerobic fungus, Neocallimastix californiae, to a heterogeneous mixture of aromatic compounds derived from lignin. Through exposing the fungus to both a concentration it might experience in its native environment and an elevated concentration of alkaline lignin, we observe that N. californiae transforms vanillin and that supplying alkaline lignin at 0.125 g/L, alongside cellulose, enhances the growth and polysaccharide-degrading activity of N. californiae. Altogether, our results further suggest that vanillin consumption, increased polymer-degrading activity, increased metabolic activity, and transcriptomic remodeling of amino acid synthesis genes all coincide with increased melanin production by fungal cells. These observations challenge previous notions that aromatics from lignocellulose only inhibit the growth and polymer deconstruction capabilities of the biomass-degrading anaerobic fungi (Neocallimastigomycetes). This study demonstrates that anaerobic fungi have a complex relationship with aromatic chemicals derived from lignin and hemicellulose and shift their metabolism in response to the addition of lignocellulose-derived aromatics to their growth medium. Further, as no known pathways for the biochemical transformation of aromatics were detected in these organisms despite observed transcriptome remodeling in the presence of aromatics, we suggest they might encode novel biochemical routes for scavenging amino acid building blocks from aromatic monomers derived from hemicellulose side chains and lignin.

Anaerobic fungi↗

Community structure and function during periods of high performance and system upset in a full-scale mixed microalgal wastewater resource recovery facility

Microalgae have the potential to exceed current nutrient recovery limits from wastewater, enabling water resource recovery facilities (WRRFs) to achieve increasingly stringent effluent permits. The use of photobioreactors (PBRs) and the separation of hydraulic retention and solids residence time (HRT/SRT) further enables increased biomass in a reduced physical footprint while allowing operational parameters (e.g., SRT) to select for desired functional communities. However, as algal technology transitions to full-scale, there is a need to understand the effect of operational and environmental parameters on complex microbial dynamics among mixotrophic microalgae, bacterial groups, and pests (i.e., grazers and pathogens) and to implement robust process controls for stable long-term performance. Here, we examine a full-scale, intensive WRRF utilizing mixed microalgae for tertiary treatment in the US (EcoRecover, Clearas Water Recovery Inc.) during a nine-month monitoring campaign. We investigated the temporal variations in microbial community structure (18S and 16S rRNA genes), which revealed that stable system performance of the EcoRecover system was marked by a low-diversity microalgal community (D INVSIMPSON = 2.01) dominated by Scenedesmus sp. (MRA = 55 %-80 %) that achieved strict nutrient removal (effluent TP < 0.04 mg·L -1 ) and steady biomass concentration (TSS monthly avg . = 400–700 mg·L −1 ). Operational variables including pH, alkalinity, and influent ammonium (NH 4 + ), correlated positively (p < 0.05, method = Spearman) with algal community during stable performance. Further, the use of these parameters as operational controls along with N/P loading and SRT allowed for system recovery following upset events. Importantly, the presence or absence of bacterial nitrification did not directly impact algal system performance and overall nutrient recovery, but partial nitrification (potentially resulting from NO 2 − accumulation) inhibited algal growth and should be considered during long-term operation. The microalgal communities were also adversely affected by zooplankton grazers (ciliates, rotifers) and fungal parasites (Aphelidium), particularly during periods of upset when algal cultures were experiencing culture turnover or stress conditions (e.g., nitrogen limitation, elevated temperature). Altogether, the active management of system operation in order to maintain healthy algal cultures and high biomass productivity can result in significant periods (>4 months) of stable system performance that achieve robust nutrient recovery, even in winter months in northern latitudes (WI, USA).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Bioaerosols as indicators of central Arctic ice nucleating particle sources

The Arctic is warming at a rapid rate, with implications for microbial communities as the ecosystems change. Some microbes and biogenic materials can affect the persistence of long-lived mixed-phase clouds by serving as ice nucleating particles (INPs). The presence of INPs modulates the cloud phase, and long-term measurements are important to elucidate their seasonal sources and to predict future change. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2019–2020 provided the first year-long measurements of bioaerosols and INPs in the central Arctic, with 3 d filters for amplicon sequencing and cumulative INP concentrations from −5 to −30 °C. Here, we investigated the INP seasonal cycle and its relation to the seasonal cycle of bacteria and eukaryotes. INPs were greatly elevated and compositionally similar in summer, aligning with a greater prevalence of local bioaerosol sources, but, despite this, a diverse mixture of sources (marine and terrestrial) was present all times. A common broader Arctic INP population is hypothesized for much of the year by comparable coincident data collected in Svalbard and a sensitivity of both the INPs and bioaerosols to large-scale events.

Barry, Kevin R. [Colorado State Univ., Fort Collin↗

A Computational Workflow of Elucidating Viral Impact on Mediating Microbial Response to In-situ Experimental Warming: Bridging microbial modeling to carbon and mineral modeling

Viruses are abundant in soils and shape microbial communities in ways that can potentially influence ecosystem processes, yet their contributions to carbon cycling and mineral transformations remain poorly understood. Here we present a multi-phase framework that links virus-host interactions to soil biogeochemistry by combining ecological simulations, genome- and community-scale metabolic modeling, and statistical and machine-learning analyses. We first calibrated microbial abundance profiles under explicit infection scenarios to capture how viral pressure alters community structure, then explored alternative interaction strategies, including kill-the-winner, piggyback-the-winner, and mixed lytic-lysogenic modes, through forward simulations. These ecological shifts were translated into metabolic consequences using exchange fluxes summarized into biologically meaningful categories, while integrated statistical and machine-learning screens elevated subtle but consistent signals. Application of this framework revealed that viral infections shift the balance between organic and inorganic fluxes, redirecting metabolism from diffuse organic transformations toward inorganic pools such as protons and CO 2 , directly linking viral regulation to respiration and soil carbon balance. The roll-up analysis also isolated perturbations in critical mineral ions, including magnesium, manganese, zinc, and copper, which serve as essential enzymatic cofactors. In piggyback-the-winner scenarios, uptake of these ions was strongly suppressed. Contrasting viral strategies produced distinct community structures and metabolic outcomes, from broad suppression under kill-the-winner dynamics to dramatic redistributions under high-lytic and high-gain lysogenic regimes that collapsed vulnerable microbial populations while promoting opportunists. Together, these results provide a tractable path to trace viral perturbations from host abundance shifts to metabolic flux adjustments and ecosystem-scale processes, offering a practical way to include viruses in earth system models.

54 ENVIRONMENTAL SCIENCES↗

Data and scripts associated with a manuscript modeling microbial regulation of priming effects

This data package is associated with the publication “Modeling Microbial Regulatory Feedback in Organic Matter Decomposition Identifies Copiotrophic Traits as Key Drivers of Positive Priming” published as a preprint on BioRXiv by Ahamed et al. (2026); https://doi.org/10.1101/2024.08.11.607483. The package contains MATLAB scripts and saved simulation outputs used to implement a cybernetic model of microbial regulation during complex organic matter (OM) decomposition governing priming effects. It includes models of (i) single microbial functional groups (copiotrophic or oligotrophic degraders) and (ii) binary consortia composed of degraders and non-degraders with contrasting or common growth traits. Simulation results were generated using Monte Carlo analyses, with randomized key model parameters across a range of environmental mixing fractions of complex and labile OM. The dataset was created to provide a transparent and reusable computational framework for systematically exploring how microbial growth traits, metabolic regulation, and community composition influence OM decomposition dynamics and priming effects. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes the variable definitions. This package includes: (1) annotated MATLAB code implementing the system of ordinary differential equations and cybernetic control laws; (2) saved output files containing data (e.g., biomass, substrates, enzyme levels, priming metrics); and (3) scripts for processing saved outputs and regenerating figures. Specifically, the data package contains three main MATLAB scripts: runPrimingModel.m, runPlotData.m, and runPlotSuppFigS1.m, along with this readme and supporting documentation. Users should begin with runPrimingModel.m, which contains the annotated code implementing the system of ordinary differential equations and cybernetic control laws. This script runs the Monte Carlo simulations of microbial OM decomposition and allows users to modify microbial trait definitions, adjust parameter distributions, or define new community configurations. Simulation outputs are automatically saved as .mat files in the folder named SavedData, which stores all pre-generated results included in this package. The second script, runPlotData.m, reads files from the SavedData folder and processes them to regenerate the figures presented in the manuscript. The third script, runPlotSuppFigS1.m, specifically generates Figure S1 in the Supplementary Material of the manuscript. The package also includes the aforementioned files in non-proprietary .txt format. If users intend to use them, they should first save the files in their respective .m or .mat formats prior to execution in MATLAB.

Biomass concentration↗

Predictive links between microbial communities and biological oxygen utilization in the Arctic Ocean

Microbial metabolism influences rates of net community production (NCP), exerting a direct biological control on marine oxygen and carbon fluxes. In the Arctic, it is increasingly important to understand and quantify this process, as ecological and oceanographic conditions shift due to changing climate. Here, we describe potential ecological links between pelagic microbial diversity and an NCP precursor, biological oxygen utilization, using machine learning and paired observations of community structure and metabolic activity from a seasonally and spatially variable transect of the Arctic Ocean (2019–2020 MOSAiC Expedition). Community structure was determined using 16S (prokaryotic) and 18S (eukaryotic) rRNA gene amplicon sequencing, and metabolic activity was derived from ΔO 2 /Ar. Using self-organizing maps, we identified clear successional patterns in observed microbial community structure that were seasonally driven in the upper ocean and vertically stratified with depth. Metabolic activity was also stratified, with a primarily net heterotrophic water column (median −1.5% biological oxygen saturation), excepting periodic oxygen supersaturation (maximum: 13.6%) within the mixed layer. Using DNA sequences as predictor variables, we then constructed a random forest regression model that reliably reconstructed biological oxygen concentrations (root mean squared error = 4.14 μmol kg −1 ). Top predictors from this model were from heterotrophic (bacteria) or potentially mixotrophic (dinoflagellate) taxa. These analyses highlight biologically driven diagnostic tools that can be used to expand biogeochemical datasets and improve the microbial perspectives and metabolisms represented in ecological models of net productivity and carbon flux in a changing Arctic Ocean.

Chamberlain, Emelia J. [Univ. of San Diego, San Di↗

MISIP: a data standard for the reuse and reproducibility of any stable isotope probing-derived nucleic acid sequence and experiment

DNA/RNA-stable isotope probing (SIP) is a powerful tool to link in situ microbial activity to sequencing data. Every SIP dataset captures distinct information about microbial community metabolism, process rates, and population dynamics, offering valuable insights for a wide range of research questions. Data reuse maximizes the information derived from the labor and resource-intensive SIP approaches. Yet, a review of publicly available SIP sequencing metadata showed that critical information necessary for reproducibility and reuse was often missing. Here, we outline the Minimum Information for any Stable Isotope Probing Sequence (MISIP) according to the Minimum Information for any (x) Sequence (MIxS) framework and include examples of MISIP reporting for common SIP experiments. Our objectives are to expand the capacity of MIxS to accommodate SIP-specific metadata and guide SIP users in metadata collection when planning and reporting an experiment. The MISIP standard requires 5 metadata fields—isotope, isotopolog, isotopolog label, labeling approach, and gradient position—and recommends several fields that represent best practices in acquiring and reporting SIP sequencing data (e.g., gradient density and nucleic acid amount). The standard is intended to be used in concert with other MIxS checklists to comprehensively describe the origin of sequence data, such as for marker genes (MISIP-MIMARKS) or metagenomes (MISIP-MIMS), in combination with metadata required by an environmental extension (e.g., soil). The adoption of the proposed data standard will improve the reuse of any sequence derived from a SIP experiment and, by extension, deepen understanding of in situ biogeochemical processes and microbial ecology.

Simpson, Abigayle↗

Structured interactions drive abrupt transitions in the spatial organization of microbial communities

Bacteria possess diverse mechanisms to regulate their motility in response to environmental and physiological signals, enabling them to navigate complex habitats and adapt their behavior. Some of these mechanisms are species specific and enable cells to modulate their movement based on the ecological identity of neighboring species. Here, we introduce a model in which bacteria interact via local signals that either enhance or suppress the motility of neighboring cells depending on species type. Through large-scale simulations and a coarse-grained stochastic model, we demonstrate the emergence of a sharp transition driven by nucleation processes: increasing the density of motility-suppressing interactions drives the system from a fully mixed, motile phase to a state characterized by large, stationary bacterial clusters. Remarkably, in systems with a large number of interacting species, this transition can be triggered solely by altering the structure of the motility-regulation interaction matrix while maintaining species and interaction densities constant. In particular, we find that heterogeneous and modular interactions promote the transition more readily than homogeneous random ones. These findings add a dimension to the theory of motility-induced phase separation and contribute to the ongoing effort to understand microbial interactions, suggesting that structured, nonrandom ones may be key to reproducing commonly observed spatial patterns in microbial communities.

bacterial communities↗

Microbial Ecology and Site Characteristics Underlie Differences in Salinity-Methane Relationships in Coastal Wetlands

Methane (CH 4 ) is a potent greenhouse gas emitted by archaea in anaerobic environments such as wetland soils. Tidal freshwater wetlands are predicted to become increasingly saline as sea levels rise due to climate change. Previous work has shown that increases in salinity generally decrease CH 4 emissions, but with considerable variation, including instances where salinization increased CH 4 flux. We measured microbial community composition, biogeochemistry, and CH 4 flux from field samples and lab experiments from four different sites across a wide geographic range. We sought to assess how site differences and microbial ecology affect how CH 4 emissions are influenced by salinization. CH 4 flux was generally, but not always, positively correlated with CO 2 flux, soil carbon, ammonium, phosphate, and pH. Methanogen guilds were positively correlated with CH 4 flux across all sites, while methanotroph guilds were both positively and negatively correlated with CH 4 depending on site. There was mixed support for negative relationships between CH 4 fluxes and concentrations of alternative electron acceptors and abundances of taxa that reduce them. CH 4 /salinity relationships ranged from negative, to neutral, to positive and appeared to be influenced by site characteristics such as pH and plant composition, which also likely contributed to site differences in microbial communities. The activity of site-specific microbes that may respond differently to low-level salinity increases is likely an important driver of CH 4 /salinity relationships. Our results suggest several factors that make it difficult to generalize CH 4 /salinity relationships and highlight the need for paired microbial and flux measurements across a broader range of sites.

54 ENVIRONMENTAL SCIENCES↗

Pine‐fungal co‐invasion alters whole‐ecosystem properties of a native eucalypt forest

Summary Pine‐fungal co‐invasions into native ecosystems are increasingly prevalent across the southern hemisphere. In Australia, invasive pines slowly spread into native eucalypt forests, creating novel mixed forests. We sought to understand how pine‐fungal co‐invasions impact interconnected above‐ and belowground ecosystem characteristics. We sampled beneath maturePinus radiataandEucalyptus racemosain a pine‐invaded eucalypt forest in New South Wales, Australia. We measured microbial community composition via amplicon sequencing of 16S, ITS2, and 18S rDNA regions, microbial metabolic activity via Biolog plate substrate utilization, and soil, leaf litter, and understory plant characteristics. Pines were associated with decreased topsoil moisture, increased pine litter, and decreased eucalypt litter total phosphorus content. Soils and roots beneath pines had distinct microbial community composition and activity relative to eucalypts, including decreased bacterial diversity, decreased microbial utilization of several C‐ and N‐rich substrates, and enrichment of pine‐associated ectomycorrhizae. Introduced suilloid fungi were abundant across both pine and eucalypt soils and roots. Many ecosystem impacts increased with pine size. Invasive pines and their ectomycorrhizae have significant impacts on eucalypt forest properties as they grow. Interconnected impacts at the scale of individual trees should be considered when managing invaded forests and predicting effects of pine invasions.

Plant Sciences↗

Unraveling Bacterial Adaptation Strategies in the Microbiome Shaped by the Chemical Environment of the Plant Rhizosphere

The rhizosphere is a dynamic environment where rhizodeposits that include primary and secondary metabolites and mucilage serve as nutrient sources for soil microorganisms, attracting them toward plant roots. However, understanding how these microbes specifically respond to plant root chemical signals has been hindered by the challenges of disentangling physical and chemical interactions between the microbes and plant roots. To address this, we implemented an innovative filter-based experimental setup on plant roots that creates a physical barrier while facilitating the exchange of chemical signals. The proteomic analysis of 10 Populus root-associated bacterial strains grown in the presence or absence of a plant in either individual or mixed community conditions provided detailed insights into the functional responses of these strains to the root chemical environment. Additionally, this approach allowed us to discern the impact of root exudates on overall community dynamics. In particular, metaproteomic analyses revealed that each of these 10 microbial members responds uniquely to the presence of the plant, with Bacillus and Pantoea exhibiting the most dramatic favorable impact. Proteomic examination revealed the details of metabolism fine-tuning, including processes such as chemotaxis and ATP-binding cassette transporter proteins. This study demonstrates the application of a filter-based experimental setup to study microbial responses to plant chemicals and sheds light on adaptation strategies employed by various bacterial strains for survival in the rhizosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phage-based delivery of CRISPR-associated transposases for targeted bacterial editing

Phage λ, a well-characterized temperate phage, has been recently leveraged for bacterial genome editing by selectively delivering base editors into targeted bacterial species. We extend this concept by engineering phage λ to deliver CRISPR-guided transposases, accomplishing large insertions and targeted gene disruptions. To achieve this, we engineered phage λ using homologous recombination paired with Cas13a-based counterselection for precise phage modifications. Initially, we established the utility of Cas13a in phage λ by conducting minimal recoding edits, deletions, and insertions. Subsequently, we scaled up the engineering to embed the comprehensive DNA-editing CRISPR-Cas transposase (DART) system within the phage genome, creating λ-DART phages. These modified λ-DART phages were then employed to infectEscherichia coli, generating CRISPR RNA-guided transposition events in the host genome. Applying our engineered λ-DART phages to monocultures and a mixed bacterial community comprising three genera led to efficient, precise, and specific gene knockouts and insertions in the targetedE. colicells, achieving editing efficiencies surpassing 50% of the population. This research enhances phage-mediated genome editing by enabling efficient in situ gene integrations in bacteria, offering an avenue for further application in microbial community contexts. This scalable method enables flexible microbial genome editing in situ to manipulate the function and composition of diverse ecosystems.

Science & Technology - Other Topics↗