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At least 577 records · Page 32

nf-core/proteinfamilies: a scalable pipeline for the generation of protein families

The growth of metagenomics-derived amino acid sequence data has transformed our understanding of protein function, microbial diversity, and evolutionary relationships. However, the vast majority of these proteins remain functionally uncharacterized. Grouping the millions of such uncharacterized sequences with the few experimentally characterized ones allows the transfer of annotations, while the inspection of conserved residues with multiple sequence alignments can provide clues to function, even in the absence of existing functional information. To address the challenges associated with this data surge and the need to group sequences, we present a scalable, open-source, parametrizable Nextflow pipeline (nf-core/proteinfamilies) that generates nascent protein families or assigns new proteins to existing families. The computational benchmarks demonstrated that resource usage scales approximately linearly with input size, and the biological benchmarks showed that the generated protein families closely resemble manually curated families in widely used databases.

Nextflow↗

Advancing river corridor science beyond disciplinary boundaries with an inductive approach to catalyse hypothesis generation

Abstract A unified conceptual framework for river corridors requires synthesis of diverse site‐, method‐ and discipline‐specific findings. The river research community has developed a substantial body of observations and process‐specific interpretations, but we are still lacking a comprehensive model to distill this knowledge into fundamental transferable concepts. We confront the challenge of how a discipline classically organized around the deductive model of systematically collecting of site‐, scale‐, and mechanism‐specific observations begins the process of synthesis. Machine learning is particularly well‐suited to inductive generation of hypotheses. In this study, we prototype an inductive approach to holistic synthesis of river corridor observations, using support vector machine regression to identify potential couplings or feedbacks that would not necessarily arise from classical approaches. This approach generated 672 relationships linking a suite of 157 variables each measured at 62 locations in a fifth order river network. Eighty four percent of these relationships have not been previously investigated, and representing potential (hypothetical) process connections. We document relationships consistent with current understanding including hydrologic exchange processes, microbial ecology, and the River Continuum Concept, supporting that the approach can identify meaningful relationships in the data. Moreover, we highlight examples of two novel research questions that stem from interpretation of inductively‐generated relationships. This study demonstrates the implementation of machine learning to sieve complex data sets and identify a small set of candidate relationships that warrant further study, including data types not commonly measured together. This structured approach complements traditional modes of inquiry, which are often limited by disciplinary perspectives and favour the careful pursuit of parsimony. Finally, we emphasize that this approach should be viewed as a complement to, rather than in place of, more traditional, deductive approaches to scientific discovery.

54 ENVIRONMENTAL SCIENCES↗

Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA). Final report

The goal of the Stahl lab is to use a combination of isotopic, genomic, and activity-based analyses in the field, of selected field isolates, and defined synthetic communities to identify sources and sinks of different nitrogen species in the field, focusing on the FRC at the ORNL. The most general research objective is to characterize variants in the pathway for denitrification among field isolates and synthetic microbial assemblies as a foundation for predicting the biotic and abiotic controls of nitrogen and carbon transformations in the field. Specifically, we have focused on characterizing environmental controls of nitrous oxide emissions, an important greenhouse gas and ozone depleting molecule. Studies have mapped the flux of nitrous oxide and controlling genetic elements within the FRC subsurface, indicating the importance of different enzyme variants in nitrous oxide production and consumption in controlling surface emissions. We have developed methods to quantify and catalog the isotopic signatures imparted on nitrous oxide by different nitrous oxide reductase variants in isolated organisms and model synthetic communities. We have developed methods to quantify and catalog the nitrous oxide affinity of field relevant isolates and their biomass yield when respiring nitrous oxide on different carbon substrates. We continue to expand the collection of field-relevant microbial isolates within ENIGMA by focused enrichment and isolation from field material. These objectives have been facilitated by the development of new technologies, including: 1) the development of a multiplexed automated optical density measurement system for quantifying growth kinetics of microorganisms dependent on gaseous substrates in monoculture or gas exchange in synthetic communities and 2) the development of a microcalorimetric analysis format to quantify the impact of environmental stress on microbial maintenance energy. Since field relevant processes are mediated by assemblies of organisms interacting with each other and their local environment, we have also collaborated with other ENIGMA investigators on the assembly and characterization of synthetic communities. These studies have evaluated the role of organisms lacking a complete pathway for denitrification in the control of field processes, measuring process rates of assemblies of organisms that individually lack the full denitrification pathway but mediate the complete denitrification when growing together. These efforts have so far resulted in the publication of 18 peer reviewed papers ranging from ecological and physiological drivers of pathway optimization to field-scale process characterization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Biomanufacturing from gaseous C1 feedstocks: A perspective on opportunities and challenges

Single-carbon (C1) substrates including carbon dioxide, carbon monoxide, and methane are abundantly available from natural and anthropogenic sources and present potential feedstocks for biomanufacturing. Utilizing these C1 gas feedstocks in bioprocesses for sustainable production of chemicals and fuels could prove pivotal in removing excess carbon from the atmosphere. This perspective describes the spectrum and sources of CO2, CO, and CH4 and examines emerging opportunities in microbial bioconversion and bioelectrochemical processes for these feedstocks. We discuss existing challenges in bioprocess development that currently restrict the commercialization of C1 biomanufacturing technologies. We detail different aerobic and anaerobic bioconversion approaches for C1 feedstocks employing pure and mixed cultures and examine the suitability of each scenario for producing specific molecules. Beyond strain engineering and bioprocess constraints, we address often overlooked factors that limit the development of efficient and reliable bioprocesses, including technology availability for research and safety considerations. We then discuss and recommend the necessary safety features and technological research tools for developing fast, safe, and efficient bioprocesses using gaseous feedstocks to support the scale-up and commercialization of C1 biomanufacturing technologies. This perspective provides an overview of the current scientific and industrial state of the art and offers insights into future technological needs that must be addressed to realize the potential of biomanufacturing from gaseous feedstocks. Synopsis: C1 gases offer a sustainable feedstock for biomanufacturing of fuels and chemicals. This work analyzes bioconversion methods, challenges, and safety considerations, and emphasizes the need for improved technology to enable commercialization.

Biomanufacturing↗

Bacterial population-level trade-offs between drought tolerance and resource acquisition traits impact decomposition

Microbes drive fundamental ecosystem processes, such as decomposition. Environmental stressors are known to affect microbes, their fitness, and the ecosystem functions that they perform; yet, understanding the causal mechanisms behind this influence has been difficult. We used leaf litter on soil surface as a model in situ system to assess changes in bacterial genomic traits and decomposition rates for 18 months with drought as a stressor. We hypothesized that genome-scale trade-offs due to investment in stress tolerance traits under drought reduce the capacity for bacterial populations to carry out decomposition, and that these population-level trade-offs scale up to impact emergent community traits, thereby reducing decomposition rates. We observed drought tolerance mechanisms that were heightened in bacterial populations under drought, identified as higher gene copy numbers in metagenome-assembled genomes. A subset of populations under drought had reduced carbohydrate-active enzyme genes that suggested—as a trade-off—a decline in decomposition capabilities. These trade-offs were driven by community succession and taxonomic shifts as distinct patterns appeared in populations. We show that trait–trade-offs in bacterial populations under drought could scale up to reduce overall decomposition capabilities and litter decay rates. Using a trait-based approach to assess the population ecology of soil bacteria, we demonstrate genome-level trade-offs in response to drought with consequences for decomposition rates.

59 BASIC BIOLOGICAL SCIENCES↗

Ultra-sensitive isotope probing to quantify activity and substrate assimilation in microbiomes

Abstract Background Stable isotope probing (SIP) approaches are a critical tool in microbiome research to determine associations between species and substrates, as well as the activity of species. The application of these approaches ranges from studying microbial communities important for global biogeochemical cycling to host-microbiota interactions in the intestinal tract. Current SIP approaches, such as DNA-SIP or nanoSIMS allow to analyze incorporation of stable isotopes with high coverage of taxa in a community and at the single cell level, respectively, however they are limited in terms of sensitivity, resolution or throughput. Results Here, we present an ultra-sensitive, high-throughput protein-based stable isotope probing approach (Protein-SIP), which cuts cost for labeled substrates by 50–99% as compared to other SIP and Protein-SIP approaches and thus enables isotope labeling experiments on much larger scales and with higher replication. The approach allows for the determination of isotope incorporation into microbiome members with species level resolution using standard metaproteomics liquid chromatography-tandem mass spectrometry (LC–MS/MS) measurements. At the core of the approach are new algorithms to analyze the data, which have been implemented in an open-source software ( https://sourceforge.net/projects/calis-p/ ). We demonstrate sensitivity, precision and accuracy using bacterial cultures and mock communities with different labeling schemes. Furthermore, we benchmark our approach against two existing Protein-SIP approaches and show that in the low labeling range used our approach is the most sensitive and accurate. Finally, we measure translational activity using 18 O heavy water labeling in a 63-species community derived from human fecal samples grown on media simulating two different diets. Activity could be quantified on average for 27 species per sample, with 9 species showing significantly higher activity on a high protein diet, as compared to a high fiber diet. Surprisingly, among the species with increased activity on high protein were several Bacteroides species known as fiber consumers. Apparently, protein supply is a critical consideration when assessing growth of intestinal microbes on fiber, including fiber-based prebiotics. Conclusions We demonstrate that our Protein-SIP approach allows for the ultra-sensitive (0.01 to 10% label) detection of stable isotopes of elements found in proteins, using standard metaproteomics data.

59 BASIC BIOLOGICAL SCIENCES↗

Microbial life in 25-m-deep boreholes in ancient permafrost illuminated by metagenomics

This study describes the composition and potential metabolic adaptation of microbial communities in northeastern Siberia, a repository of the oldest permafrost in the Northern Hemisphere. Samples of contrasting depth (1.75 to 25.1 m below surface), age (from ~ 10 kyr to 1.1 Myr) and salinity (from low 0.1–0.2 ppt and brackish 0.3–1.3 ppt to saline 6.1 ppt) were collected from freshwater permafrost (FP) of borehole AL1_15 on the Alazeya River, and coastal brackish permafrost (BP) overlying marine permafrost (MP) of borehole CH1_17 on the East Siberian Sea coast. To avoid the limited view provided with culturing work, we used 16S rRNA gene sequencing to show that the biodiversity decreased dramatically with permafrost age. Nonmetric multidimensional scaling (NMDS) analysis placed the samples into three groups: FP and BP together (10–100 kyr old), MP (105–120 kyr old), and FP (> 900 kyr old). Younger FP/BP deposits were distinguished by the presence of Acidobacteriota, Bacteroidota, Chloroflexota_A, and Gemmatimonadota, older FP deposits had a higher proportion of Gammaproteobacteria, and older MP deposits had much more uncultured groups within Asgardarchaeota, Crenarchaeota, Chloroflexota, Patescibacteria, and unassigned archaea. The 60 recovered metagenome-assembled genomes and un-binned metagenomic assemblies suggested that despite the large taxonomic differences between samples, they all had a wide range of taxa capable of fermentation coupled to nitrate utilization, with the exception of sulfur reduction present only in old MP deposits.

54 ENVIRONMENTAL SCIENCES↗

Trace Metal Uptake and Mercury Methylation by Sediments from a Stream in Tennessee

The formation and transport of methylmercury (MeHg), a neurotoxin, in aquatic environments is a global concern for human health as MeHg can bioaccumulate and biomagnify to high concentrations in aquatic food webs. MeHg is formed by conversion from inorganic mercury through microbial mediated methylation. Sulfate-reducing bacteria have been identified as the primary organisms responsible for MeHg production. Pure-culture studies suggest that low availability of cobalt and copper may inhibit mercury methylation, but whether such limitations occur in the environment is unclear. To explore the possible interaction between trace metal availability and mercury methylation, sediments from the East Fork Poplar Creek in Oak Ridge, Tennessee were sampled and then incubated in the presence and absence of added dissolved cobalt and copper. Three types of data are provided in this package. The first reports the uptake of dissolved cobalt and copper by these stream sediments on short time scales (24 hours) in the form of final dissolved and adsorbed concentrations. The second data component consists of a time series of dissolved concentrations and pH values for stream sediments incubated with artificial stream water containing different addition levels of dissolved cobalt or copper. The dissolved concentrations reported include total iron, manganese, sulfur, phosphorus, nickel, zinc and cobalt, dissolved concentrations of sulfate and orthophosphate, and the amount of cobalt or copper adsorbed by the sediment. The third data component reports data at 0 and 72 hours of incubation time for stream sediments to which cobalt was added. These data include concentrations of methylmercury with isotope labeling to enable determination of methylation and demethylation rates as well as dissolved concentrations of sulfate, phosphate, chloride, iron, cobalt, and organic carbon. All data are provided in text-based CSV format with header sections indicating the data contained in each file and the corresponding units. Note that "u" is used in place of Greek lower-case mu to indicate the micro prefix on units. A Table of Contents file (Data_package_TableofContents.txt) provides an index for the data contained in the individual files.

54 ENVIRONMENTAL SCIENCES↗

Grating-Based Imaging-Scattering with Portable Neutron Generator

Company: Adelphi Technology, Inc. Title: Grating-Based Imaging-Scattering with Portable Neutron Generator PI: Dr. Jay Theodore Cremer, Jr. Topic: 26a Statement of the problem or situation that is being addressed. Successful plant growth depends upon an efficient and robust root system. The plant root is part of a larger system of water and microbial flows in the soil system. While much effort has been exerted to develop an imaging system for water, microbes, and roots, the problem is challenging, and no widely accepted imaging method currently exists. The optical solutions use a highly modified soil system. X-ray imaging methods are insensitive to the soft tissues in the presence of sand. Thermal neutron imaging has been often tested, but found inadequate, due to limited access and low image resolution. This project will develop a new strategy for neutron imaging of plant/soil systems. The project will allow long duration experiments in greenhouse environments and increase the image information content to the micron scale. General statement of how this problem is being addressed. Portable, rugged thermal and fast neutron sources are being developed where portable means a two-soldier team can carry the source and power unit to survey rough terrain for explosives. In the past decade, microfabrication of X-ray and thermal/cold neutron optics has opened a new imaging strategy. The standard transmission image is now supplemented with simultaneous acquisition of a phase contrast image and an image revealing scattering features. In materials science, the interferometric neutron scattering image has been used to detect early crack formation in stressed additive manufacturing test samples. The detection requires sensitivity to scattering features at the 1-micron scale. By addition of our proposed grating-optic to Adelphi Technology’s radiographic/tomographic imaging system, which is based on portable thermal neutron source, the resulting thermal neutron scatter image of the plant/soil system, will reveal details at 1-micron. Commercial Applications and Other Benefits Neutron interferometry imaging has greater penetration through large metal components compared to industrial X-ray imaging. The low-cost, large area optics developed for greenhouse applications, combined with the robust, portable neutron generator, can then be marketed as a system for inspection of additive manufactured components. In the aerospace industry, all freshly printed components are validated with X-ray CT. Scheduled maintenance again requires X-ray CT as the ability to predict aerospace component lifetime does not yet exist. Large aerospace components are only partially observed with X-ray imaging. Key Words Neutron radiography/tomography, grating interferometry, thermal neutron generator imaging, plant root and soil imaging, rhizosphere imaging, deployable neutron imaging systems Summary for Members of Congress A rugged, portable source of thermal neutrons is adapted for neutron interferometry imaging with the addition of low-cost, 3D printed optics. The first application of our proposed deployable, compact thermal neutron generator imaging system, using a grating optic, is plant root/soil science in greenhouse settings and agricultural laboratories.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Comparison of automated chemical-guided segmentation and human annotation of soil organic matter in X-ray microcomputed tomography imaging in contrasted soil types

Soil organic matter (OM) formation and persistence is strongly influenced by the spatial distribution of organic substrates and microscale soil heterogeneity by dictating OM accessibility to microorganisms. However, traditional size and/or density fractionation techniques disrupt aggregate architecture, eliminating spatial information needed to fully understand intra-aggregate OM distribution. To quantify three-dimensional OM spatial distribution and automate segmentation in X-ray microcomputed tomography (µCT) imaging without human annotation bias, we developed an iodine gas vapor (I2) based staining workflow that eliminates labor-intensive manual annotation while maintaining segmentation accuracy, using aggregates from four taxonomically diverse soils (Xerofluvent, Haploxeroll Sphagnofibrist, Palehumult) with an 8-fold range of soil organic carbon. Human annotation of 10 µCT slices by the experienced and inexperienced annotators resulted in variations up to 3% in the Dice similarity coefficient (DSC), reflecting a degree of inherent subjectivity of manual labeling. Such inconsistencies are expected to compound as the number of manually annotated slices increases. Dual-energy µCT imaging at 33.1 keV (below the iodine (I) K-edge) and 33.2 keV (above the I K-edge) was used to resolve aggregate microstructure following I2 staining. The automated image subtraction pipeline identified OM regions by the I Kedge induced brightness increases, achieving DSC values of 0.58–0.83 relative to an experienced annotator. Sensitivity analyses revealed that the reconstruction alpha value—optimized via the open-source tool TomocuPy—and the 3D registration slice count were the primary determinants of accuracy, providing a novel benchmark for dual-energy soil imaging. The pipeline without GPU acceleration achieved 9.6 to 43.2 times faster than manual annotation. Using GPU-accelerated image post-processing and affine transformation matrices, the pipeline successfully segmented OM elements for large-scale datasets (3232×3232 pixel, 2048 slices) within ~5200 s from raw file acquisition to segmented output. The high-throughput approach enables the quantification of OM spatial distribution across diverse and heterogeneous soil.

Soil microbial biomass↗

High-throughput functional trait testing for bacterial pathogens

Functional traits are characteristics that affect the fitness and metabolic function of a microorganism. There is growing interest in using high-throughput methods to characterize bacterial pathogens based on functional virulence traits. Traditional methods that phenotype a single organism for a single virulence trait can be time consuming and labor intensive. Alternatively, machine learning of whole-genome sequences (WGS) has shown some success in predicting virulence. However, relying solely on WGS can miss functional traits, particularly for organisms lacking classical virulence factors. We propose that high-throughput assays for functional virulence trait identification should become a prominent method of characterizing bacterial pathogens on a population scale. This work is critical as we move from compiling lists of bacterial species associated with disease to pathogen-agnostic approaches capable of detecting novel microbes. We discuss six key areas of functional trait testing and how advancing high-throughput methods could provide a greater understanding of pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

Verazine biosynthesis from simple sugars in engineered Saccharomyces cerevisiae

Steroidal alkaloids are FDA-approved drugs (e.g., Zytiga) and promising drug candidates/leads (e.g., cyclopamine); yet many of the ≥697 known steroidal alkaloid natural products remain underutilized as drugs because it can be challenging to scale their biosynthesis in their producing organisms. Cyclopamine is a steroidal alkaloid produced by corn lily (Veratrum spp.) plants, and it is an inhibitor of the Hedgehog (Hh) signaling pathway. Therefore, cyclopamine is an important drug candidate/lead to treat human diseases that are associated with dysregulated Hh signaling, such as basal cell carcinoma and acute myeloid leukemia. Cyclopamine and its semi-synthetic derivatives have been studied in (pre)clinical trials as Hh inhibitor-based drugs. However, challenges in scaling the production of cyclopamine have slowed efforts to improve its efficacy and safety profile through (bio)synthetic derivatization, often limiting drug development to synthetic analogs of cyclopamine such as the FDA-approved drugs Odomzo, Daurismo, and Erivedge. If a platform for the scalable and sustainable production of cyclopamine were established, then its (bio)synthetic derivatization, clinical development, and, ultimately, widespread distribution could be accelerated. Ongoing efforts to achieve this goal include the biosynthesis of cyclopamine in Veratrum plant cell culture and the semi-/total chemical synthesis of cyclopamine. Herein, this work advances efforts towards a promising future approach: the biosynthesis of cyclopamine in engineered microorganisms. We completed the heterologous microbial production of verazine (biosynthetic precursor to cyclopamine) from simple sugars (i.e., glucose and galactose) in engineered Saccharomyces cerevisiae (S. cerevisiae) through the inducible upregulation of the native yeast mevalonate and lanosterol biosynthetic pathways, diversion of biosynthetic flux from ergosterol (i.e., native sterol in S. cerevisiae) to cholesterol (i.e., biosynthetic precursor to verazine), and expression of a refactored five-step verazine biosynthetic pathway. The engineered S. cerevisiae strain that produced verazine contains eight heterologous enzymes sourced from seven different species. Importantly, S. cerevisiae-produced verazine was indistinguishable via liquid chromatography-mass spectrometry from both a commercial standard (Veratrum spp. plant-produced) and Nicotiana benthamiana-produced verazine. To the best of our knowledge, this is the first report describing the heterologous production of a steroidal alkaloid in an engineered yeast. Verazine production was ultimately increased through design-build-test-learn cycles to a final titer of 83 ± 3 μg/L (4.1 ± 0.1 μg/g DCW). Finally, this research lays the groundwork for future microbial biosynthesis of cyclopamine, (bio)synthetic derivatives of cyclopamine, and other steroidal alkaloid natural products.

59 BASIC BIOLOGICAL SCIENCES↗

Syntrophic Co-Cultures of Clostridium Organisms to Produce Higher Alcohols & Other C6-C8 Metabolites (Final Report)

The goal of this project was to advance the systems biology understanding and predictive modeling of synthetic & syntrophic Clostridium microbial consortia, focusing on elucidation of metabolic networks and environmental signals in the consortia. The project has direct applicability to lignocellulosic-biomass based production of higher alcohols as advanced biofuels and C6-C8 metabolites, that can be used as chemicals or serve as biofuel precursors. This project studied and optimized three synthetic syntrophic systems. It examined the population dynamics using flow-cytometry, time-lapse microscopy and PCR analysis. 13C-based tracer analyses was used to examine the metabolite exchange between the syntrophic cell populations and the impact of those interactions on the transcriptome of the individual populations. To enhance our analytical and predictive capabilities, genome-scale models (GSMs) for these syntrophies was developed. RNAseq data for these syntrophic coculture systems were acquired to enable a molecular level understanding of the syntrophies aiming to identify the genetic networks of each organism in the co-culture and compare those against the networks of pure cultures.

09 BIOMASS FUELS↗

Using Mineralogy to Interpret Martian Geologic History

The surface mineralogy of Mars is key to interpreting the planet’s geologic history and constraining when and where Mars may have been habitable to microbial life. Orbital mineralogical data from infrared spectrometers collected over the last two decades have demonstrated that Mars is more than a basaltic planet. Thermal infrared (TIR) emission spectrometers have identified regional variations in igneous minerals, iron oxides, and chloride salts, showing evidence for magmatic evolution and aqueous alteration. Orbital visible/shortwave infrared reflectance spectra provide detailed information about the aqueous history of Mars through the identification of clay minerals, sulfates, carbonates, zeolites, and amorphous materials in ancient ~3-4-billion-year-old terrains. Mineralogical data from rovers allow us to better characterize mineral formation mechanisms by identifying mineral assemblages and placing them in geologic context using outcrop- to grain-scale images. TIR and Mössbauer data from the Mars Exploration Rovers helped identify an ancient dune-interdune playa environment with multiple episodes of groundwater at Meridiani Planum and volcanism-induced hydrothermalism at Gusev crater. The CheMin X-ray diffractometer on the Mars Science Laboratory Curiosity rover in Gale crater is the first fully quantitative mineralogical instrument sent to another planetary surface. CheMin data allow the quantification of minerals and X-ray amorphous materials with a mineral detection limit of <1 wt.% and provide crystal chemistry of major phases from refined unit-cell parameters. CheMin has revealed local mineralogical changes in ancient sedimentary rocks not seen from orbit and helped identify habitable environments. Throughout the 600+ m of vertical stratigraphy studied so far, changes in clay mineralogy, Fe-oxides/oxyhydroxides, sulfates, and carbonates demonstrate a long history of surface and groundwater at Gale crater with variable salinity, pH, Eh, and temperature. Recent CheMin data document a decrease in clay minerals and an increase in sulfate minerals in younger strata that corresponds with a change from fluvio-lacustrine to eolian depositional environments, potentially documenting a change to a drier climate across the planet.

E. B. Rampe↗

Radiocarbon Analyses Quantify Peat Carbon Losses With Increasing Temperature in a Whole Ecosystem Warming Experiment

Abstract Climate warming is expected to accelerate peatland degradation and release rates of carbon dioxide (CO 2 ) and methane (CH 4 ). Spruce and Peatlands Responses Under Changing Environments is an ecosystem‐scale climate manipulation experiment, designed to examine peatland ecosystem response to climate forcings. We examined whether heating up to +9 °C to 3 m‐deep in a peat bog over a 7‐year period led to higher C turnover and CO 2 and CH 4 emissions, by measuring 14 C of solid peat, dissolved organic carbon (DOC), CH 4 , and dissolved CO 2 (DIC). DOC, a major substrate for heterotrophic respiration, increased significantly with warming. There was no 7‐year trend in the DI 14 C of the ambient plots which remained similar to their DO 14 C. At +6.75 °C and +9 °C, the 14 C of DIC, a product of microbial respiration, initially resembled ambient plots but became more depleted over 7 years of warming. We attributed the shifts in DI 14 C to the increasing importance of solid phase peat as a substrate for microbial respiration and quantified this shift via the radiocarbon mass balance. The mass‐balance model revealed increases in peat‐supported respiration of the catotelm depths in heated plots over time and relative to ambient enclosures, from a baseline of 20%–25% in ambient enclosures, to 35%–40% in the heated plots. We find that warming stimulates microorganisms to respire ancient peat C, deposited under prior climate (cooler) conditions. This apparent destabilization of the large peat C reservoir has implications for peatland‐climate feedbacks especially if the balance of the peatland is tipped from net C sink to C source.

54 ENVIRONMENTAL SCIENCES↗

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↗

Leveraging the signature of heterotrophic respiration on atmospheric CO 2 for model benchmarking

Spatial and temporal variations in atmospheric carbon dioxide (CO 2 ) reflect large-scale net carbon exchange between the atmosphere and terrestrial ecosystems. Soil heterotrophic respiration (HR) is one of the component fluxes that drive this net exchange, but, given observational limitations, it is difficult to quantify this flux or to evaluate global-scale model simulations thereof. Here, we show that atmospheric CO 2 can provide a useful constraint on large-scale patterns of soil heterotrophic respiration. We analyze three soil model configurations (CASA-CNP, MIMICS, and CORPSE) that simulate HR fluxes within a biogeochemical test bed that provides each model with identical net primary productivity (NPP) and climate forcings. We subsequently quantify the effects of variation in simulated terrestrial carbon fluxes (NPP and HR from the three soil test-bed models) on atmospheric CO 2 distributions using a three-dimensional atmospheric tracer transport model. Our results show that atmospheric CO 2 observations can be used to identify deficiencies in model simulations of the seasonal cycle and interannual variability in HR relative to NPP. In particular, the two models that explicitly simulated microbial processes (MIMICS and CORPSE) were more variable than observations at interannual timescales and showed a stronger-than-observed temperature sensitivity. Our results prompt future research directions to use atmospheric CO 2 , in combination with additional constraints on terrestrial productivity or soil carbon stocks, for evaluating HR fluxes.

54 ENVIRONMENTAL SCIENCES↗

Mapping microhabitats of lignocellulose decomposition by a microbial consortium

The leaf-cutter ant fungal garden ecosystem is a naturally evolved model system for efficient plant biomass degradation. Degradation processes mediated by the symbiotic fungus Leucoagaricus gongylophorus are difficult to characterize due to dynamic metabolisms and spatial complexity of the system. Herein, we performed microscale imaging across 12-µm-thick adjacent sections of Atta cephalotes fungal gardens and applied a metabolome-informed proteome imaging approach to map lignin degradation. This approach combines two spatial multiomics mass spectrometry modalities that enabled us to visualize colocalized metabolites and proteins across and through the fungal garden. Spatially profiled metabolites revealed an accumulation of lignin-related products, outlining morphologically unique lignin microhabitats. Metaproteomic analyses of these microhabitats revealed carbohydrate-degrading enzymes, indicating a prominent fungal role in lignocellulose decomposition. Integration of metabolome-informed proteome imaging data provides a comprehensive view of underlying biological pathways to inform our understanding of metabolic fungal pathways in plant matter degradation within the micrometer-scale environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗