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At least 73 records · Page 4

Illuminating the pathways to carbon liberation: a systems approach to characterizing the consequential unknowns of carbon transformation and loss from thawing permafrost peatlands (Final Report)

The IsoGenie3 Project delivered new systems-level insights into carbon cycling in thawing permafrost landscapes, with an emphasis on methane and carbon dioxide emissions. From >200 samples from the site collected over a decade, co-analyzed for geochemistry and microbiology, the team recovered ~1,500 assembled microbial genomes and ~1,900 viral population genomes, revealing appreciable genetic novelty - from a new highly abundant bacterial phylum, to novel methane consumers and their activities, to rampant viral novelty. IsoGenie3 linked these organisms to carbon compound transformations (which define the cycling of organic matter in soils, and the loss of the greenhouse gases carbon dioxide and methane), and saw that the microbes at each stage of permafrost thaw had different genetic potential to degrade categories of compounds, expressed that genetic potential differently, and actually transformed carbon compounds into greenhouse gases in different ways. IsoGenie 3 identified that some of the thaw-stage differences were due to plant-microbiome relationships; the plant species across the thaw gradient contributed different carbon compounds into the soil, and hosted distinct microbiota (differing among parts of plants as well as species). Lastly, microbes in the saturated post-thaw conditions appeared likely to contribute to the mobilization and toxification of mercury released during thaw. In parallel with ongoing field sampling and analysis, hypotheses arising from field observations were tested via lab incubation experiments. When communities are taken out of their native habitats, they behave differently, and the team first rigorously quantified the magnitude of this effect on microbiome composition and functional capacity, organic matter composition, and gas production; overall the main system processes were maintained in the lab incubations under the conditions tested. Further, the microbial data could inform geochemical reaction network models of those processes. Then, the team ran experiments with additions of compounds, varying temperature, and “live” vs. “dead” peat (the latter having been gamma irradiated, with a few additional variants to control for methodological artifacts). From these, we (a) determined the importance of plant-derived soluble phenolic compounds in bogs’ extraordinary recalcitrance of organic matter, and carbon gas emissions skewed to carbon dioxide; (b) proposed an abiotic ‘tanning’ mechanism, which could contribute to Sphagnum’s inhibitory effect on anaerobic decomposition through alteration of N availability. IsoGenie3 illuminated longer-term and landscape-scale interactions of permafrost thaw and carbon cycling, advancing knowledge of the drivers of methane dynamics not only across in the permafrost-associated peatland (where hydrology and plant communities dictate microbiomes) but also their interconnected lakes (where sediment carbon quality and resident microbiota are determined by position within lake, and lake features). By leveraging observations of site methane dynamics extending well before this project, the team was able to construct a 44-year portrait of the interplay of permafrost thaw, hydrology, vegetation dynamics, and carbon gas emissions, and the doubling of the fully-thawed fens over this time. From the detailed study of this focal site, IsoGenie3 also aimed to improve model representation of these kinds of sites and processes. To improve predictions of methane transformations, we incorporated acetate and isotope dynamics into the ‘DNDC’ biogeochemistry model. In addition, recovered genomes were grouped into ‘functional groups’, i.e. the genomes that perform a specific function of interest, then used to parameterize maximum growth rate and optimum growth temperature (via signatures in their sequence composition) for the BioCrunch model. The BioCrunch model was then in turn used to test the impact of increasing functional resolution of the microbes, on the carbon gas emissions. Lastly for modeling, the ecosys model was parameterized from the microbial and other data, and used to evaluate drivers of e.g. change in methane emissions. Finally, this project also led to the development of a range of new methods and tools, a new metric of organic matter decomposability, as well as a graph-database solution to multidisciplinary data storage and querying. This project’s ongoing analyses at our focal site also contributed to broader advancements in understanding elements of genetic plasticity and methane metabolism, climate change microbiology and community assembly, global peatland geochemistry and Arctic lakes’ roles in climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Disentangling direct from indirect relationships in association networks

Networks are vital tools for understanding and modeling interactions in complex systems in science and engineering, and direct and indirect interactions are pervasive in all types of networks. However, quantitatively disentangling direct and indirect relationships in networks remains a formidable task. Here, we present a framework, called iDIRECT (Inference of Direct and Indirect Relationships with Effective Copula-based Transitivity), for quantitatively inferring direct dependencies in association networks. Using copula-based transitivity, iDIRECT eliminates/ameliorates several challenging mathematical problems, including ill-conditioning, self-looping, and interaction strength overflow. With simulation data as benchmark examples, iDIRECT showed high prediction accuracies. Application of iDIRECT to reconstruct gene regulatory networks in Escherichia coli also revealed considerably higher prediction power than the best-performing approaches in the DREAM5 (Dialogue on Reverse Engineering Assessment and Methods project, #5) Network Inference Challenge. In addition, applying iDIRECT to highly diverse grassland soil microbial communities in response to climate warming showed that the iDIRECT-processed networks were significantly different from the original networks, with considerably fewer nodes, links, and connectivity, but higher relative modularity. Further analysis revealed that the iDIRECT-processed network was more complex under warming than the control and more robust to both random and target species removal ( P < 0.001). As a general approach, iDIRECT has great advantages for network inference, and it should be widely applicable to infer direct relationships in association networks across diverse disciplines in science and engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Necromass responses to warming: A faster microbial turnover in favor of soil carbon stabilisation

Microbial byproducts and residues (hereafter ‘necromass’) potentially play the most critical role in soil organic carbon (SOC) sequestration. However, little is known about the influence of climate warming on necromass accumulation in the agroecosystem and the underlying mechanisms associated with microbial life strategies. Here, in order to address these knowledge gaps, we used amino sugars as biomarkers of microbial necromass, and investigated their variation through an 8-year trial in an agroecosystem with two warming levels (+1.6 and + 3.2 °C) compared to ambient temperature. The results showed that the lower warming level had no impact on total microbial necromass carbon. Conversely, warming the soil 3.2 °C above ambient increased total microbial necromass by 17 % and its contribution to SOC by 21.3 %, mainly by increasing fungal necromass (+19.8 %), whereas +3.2 °C warming had no impact on bacterial necromass. At the phylum level, compared with the ambient control, +3.2 °C warming induced an increase in the abundance of Proteobacteria and a decrease in both Acidobacteria and Actinobacteria, whereas in the fungal community, Ascomycota increased and Mortierellomycota decreased. This indicates that r-strategists outcompete K-strategists in warmer climates, which led to increased microbial necromass production and accumulation, as supported by the positive correlation between r-strategists and microbial necromass. Stronger microbial competition for resources also resulted in a higher biomass turnover rate, greater cell death, and greater production of microbial necromass. This was supported by the lower bacterial and fungal network complexity and trophic links under warming conditions. In addition, the necromass generated from accelerated microbial turnover further offsets warming-induced deceases in microbial biomass. Consequently, bulk SOC did not change, despite microbial necromass having a much greater response to warming than the soil C pool. Therefore, future climate warming may influence the composition and persistence of SOC during microbial degradation.

54 ENVIRONMENTAL SCIENCES↗

Extracellular Charge Transport in Microbial Redox Chains: Linking the Living and Non-Living Worlds

The fundamental process of electron transfer (ET) within and between molecules dictates all biological energy conversion strategies, including respiration and photosynthesis. This project resulted in a comprehensive physics-based understanding of the mechanisms and limits of redox networks that mediate and regulate electron transport through microbial metabolic pathways, with special emphasis on environmental microbes that can acquire energy by catalyzing anodic or cathodic reactions on solid-state electrodes (extracellular electron transfer, or EET). By performing electron transfer to/from electrodes, such microbes may be used as biocatalysts for converting the energy stored in diverse chemical fuels to electricity, or vice versa (microbial electrosynthesis), in renewable energy technologies.

59 BASIC BIOLOGICAL SCIENCES↗

Soil pore network response to freeze-thaw cycles in permafrost aggregates

This dataset contains data used for the paper "Pore network response to freeze-thaw cycles in permafrost aggregates". The Related References field will be updated with a full citation when available.Climate change in Arctic landscapes may increase freeze-thaw frequency within the active layer as well as newly thawed permafrost. A highly disruptive process, freeze-thaw can deform soil pores and alter the architecture of the soil pore network with varied impacts to water transport and retention, redox conditions, and microbial activity. Our objective was to investigate how freeze-thaw cycles impacted the pore network of newly thawed permafrost aggregates to improve understanding of what type of transformations can be expected from warming Arctic landscapes. We measured the impact of freeze-thaw on pore morphology, pore throat diameter distribution, and pore connectivity with X-ray computed tomography (XCT) using six permafrost aggregates with sizes of 2.5 cm3 from a mineral soil horizon (Bw; 28-50 cm depths) in Toolik, Alaska. Freeze-thaw cycles were performed using a laboratory incubation consisting of five freeze-thaw cycles (-10˚C to 20˚C) over five weeks. Our findings indicated decreasing spatial connectivity of the pore network across all aggregates with higher frequencies of singly connected pores following freeze-thaw. Water-filled pores that were connected to the pore network decreased in volume while the overall connected pore volumetric fraction was not affected. Shifts in the pore throat diameter distribution were mostly observed in pore throats ranges of 100 microns or less with no corresponding changes to the pore shape factor of pore throats. Responses of the pore network to freeze-thaw varied with aggregate, suggesting that initial pore morphology may play a role in driving freeze-thaw response. Our research suggests that freeze-thaw alters the microenvironment of permafrost aggregates during the incipient stage of deformation following permafrost thaw, impacting soil properties and function in Arctic landscapes undergoing transition. This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/Erin-Rooney/XCT-freezethaw (DOI: 10.5281/zenodo.5816355).

54 ENVIRONMENTAL 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↗

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↗

Geological activity shapes the microbiome in deep-subsurface aquifers by advection

Subsurface environments host diverse microorganisms in fluid-filled fractures; however, little is known about how geological and hydrological processes shape the subterranean biosphere. Here, we sampled three flowing boreholes weekly for 10 mo in a 1478-m-deep fractured rock aquifer to study the role of fracture activity (defined as seismically or aseismically induced fracture aperture change) and advection on fluid-associated microbial community composition. We found that despite a largely stable deep-subsurface fluid microbiome, drastic community-level shifts occurred after events signifying physical changes in the permeable fracture network. The community-level shifts include the emergence of microbial families from undetected to over 50% relative abundance, as well as the replacement of the community in one borehole by the earlier community from a different borehole. Null-model analysis indicates that the observed spatial and temporal community turnover was primarily driven by stochastic processes (as opposed to deterministic processes). We, therefore, conclude that the observed community-level shifts resulted from the physical transport of distinct microbial communities from other fracture(s) that outpaced environmental selection. Given that geological activity is a major cause of fracture activity and that geological activity is ubiquitous across space and time on Earth, our findings suggest that advection induced by geological activity is a general mechanism shaping the microbial biogeography and diversity in deep-subsurface habitats across the globe.

59 BASIC BIOLOGICAL SCIENCES↗

Iodate Reduction by Shewanella oneidensis Requires Genes Encoding an Extracellular Dimethylsulfoxide Reductase

Microbial iodate (IO 3 – ) reduction is a major component of the iodine biogeochemical reaction network in anaerobic marine basins and radioactive iodine-contaminated subsurface environments. Alternative iodine remediation technologies include microbial reduction of IO 3 – to iodide (I – ) and microbial methylation of I – to volatile gases. The metal reduction pathway is required for anaerobic IO 3 – respiration by the gammaproteobacterium Shewanella oneidensis . However, the terminal IO 3 – reductase and additional enzymes involved in the S. oneidensis IO 3 – electron transport chain have not yet been identified. In this study, gene deletion mutants deficient in four extracellular electron conduits (EECs; Δ mtrA , Δ mtrA -Δ mtrDEF , Δ mtrA -Δ dmsEF , Δ mtr A-ΔSO4360) and DMSO reductase (Δ dmsB ) of S. oneidensis were constructed and examined for anaerobic IO 3 – reduction activity with either 20 mM lactate or formate as an electron donor. IO 3 – reduction rate experiments were conducted under anaerobic conditions in defined minimal medium amended with 250 μM IO 3 – as anaerobic electron acceptor. Only the Δ mtrA mutant displayed a severe deficiency in IO 3 – reduction activity with lactate as the electron donor, which suggested that the EEC-associated decaheme cytochrome was required for lactate-dependent IO 3 – reduction. The Δ mtrA -Δ dmsEF triple mutant displayed a severe deficiency in IO 3 – reduction activity with formate as the electron donor, whereas Δ mtrA -Δ mtrDEF and Δ mtr A-ΔSO4360 retained moderate IO 3 – reduction activity, which suggested that the EEC-associated dimethylsulfoxide (DMSO) reductase membrane-spanning protein DmsE, but not MtrA, was required for formate-dependent IO 3 – reduction. Furthermore, gene deletion mutant Δ dmsB (deficient in the extracellular terminal DMSO reductase protein DmsB) and wild-type cells grown with tungsten replacing molybdenum (a required co-factor for DmsA catalytic activity) in defined growth medium were unable to reduce IO 3 – with either lactate or formate as the electron donor, which indicated that the DmsAB complex functions as an extracellular IO 3 – terminal reductase for both electron donors. Results of this study provide complementary genetic and phenotypic evidence that the extracellular DMSO reductase complex DmsAB of S. oneidensis displays broad substrate specificity and reduces IO 3 – as an alternate terminal electron acceptor.

, Shewanella oneidensis↗

Microbial inoculum effects on the rumen epithelial transcriptome and rumen epimural metatranscriptome in calves

Manipulation of the rumen microbial ecosystem in early life may affect ruminal fermentation and enhance the productive performance of dairy cows. The objective of this experiment was to evaluate the effects of dosing three different types of microbial inoculum on the rumen epithelium tissue (RE) transcriptome and the rumen epimural metatranscriptome (REM) in dairy calves. For this objective, 15 Holstein bull calves were enrolled in the study at birth and assigned to three different intraruminal inoculum treatments dosed orally once weekly from three to six weeks of age. The inoculum treatments were prepared from rumen contents collected from rumen fistulated lactating cows and were either autoclaved (control; ARF), processed by differential centrifugation to create the bacterial-enriched inoculum (BE), or through gravimetric separation to create the protozoal-enriched inoculum (PE). Calves were fed 2.5 L/d pasteurized waste milk 3x/d from 0 to 7 weeks of age and texturized starter until euthanasia at 9 weeks of age, when the RE tissues were collected for transcriptome and microbial metatranscriptome analyses, from four randomly selected calves from each treatment. The different types of inoculum altered the RE transcriptome and REM. Compared to ARF, 9 genes were upregulated in the RE of BE and 92 in PE, whereas between BE and PE there were 13 genes upregulated in BE and 114 in PE. Gene ontology analysis identified enriched GO terms in biological process category between PE and ARF, with no enrichment between BE and ARF. The RE functional signature showed different KEGG pathways related to BE and ARF, and no specific KEGG pathway for PE. We observed a lower alpha diversity index for RE microbiome in ARF (observed genera and Chao1 (p < 0.05)). Five microbial genera showed a significant correlation with the changes in host gene expression: Roseburia (25 genes), Entamoeba (two genes); Anaerosinus, Lachnospira, and Succiniclasticum were each related to one gene. sPLS-DA analysis showed that RE microbial communities differ among the treatments, although the taxonomic and functional microbial profiles show different distributions. Co-expression Differential Network Analysis indicated that both BE and PE had an impact on the abundance of KEGG modules related to acyl-CoA synthesis, type VI secretion, and methanogenesis, while PE had a significant impact on KEGGs related to ectoine biosynthesis and D-xylose transport. Our study indicated that artificial dosing with different microbial inocula in early life alters not only the RE transcriptome, but also affects the REM and its functions.

59 BASIC BIOLOGICAL SCIENCES↗

Functional Redundancy in Soil Microbial Community Based on Metagenomics Across the Globe

Understanding the contribution of soil microbial communities to ecosystem processes is critical for predicting terrestrial ecosystem feedbacks under changing climate. Our current understanding lacks a consistent strategy to formulate the linkage between microbial systems and ecosystem processes due to the presumption of functional redundancy in soil microbes. Here we present a global soil microbial metagenomic analysis to generalize patterns of microbial taxonomic compositions and functional potentials across climate and geochemical gradient. Our analyses show that soil microbial taxonomic composition varies widely in response to climate and soil physicochemical gradients, while microbial functional attributes based on metagenomic gene abundances are redundant. Among 17 climate zones, microbial taxonomic compositions were more distinct than functional potentials, as climate and edaphic properties showed more significant influence on microbial taxonomic compositions than on functional potentials. Microbial taxonomies formed a larger and more complex co-occurrence network with more module structures than functional potentials. Functional network was strongly inter-connected among different categories, whereas taxonomic network was more positively interactive in the same taxonomic groups. This study provides strong evidence to support the hypothesis of functional redundancy in soil microbes, as microbial taxonomic compositions vary to a larger extent than functional potentials based on metagenomic gene abundances in terrestrial ecosystems across the globe.

59 BASIC BIOLOGICAL SCIENCES↗

High-throughput, single-microbe genomics with strain resolution, applied to a human gut microbiome

We present Microbe-seq, a high-throughput single-microbe method that yields strain-resolved genomes from complex microbial communities. We encapsulate individual microbes into droplets with microfluidics and liberate their DNA, which we amplify, tag with droplet-specific barcodes, and sequence. We use Microbe-seq to explore the human gut microbiome; we collect stool samples from a single individual, sequence over 20,000 microbes, and reconstruct nearly-complete genomes of almost 100 bacterial species, including several with multiple subspecies strains. We use these genomes to probe genomic signatures of microbial interactions: we reconstruct the horizontal gene transfer (HGT) network within the individual and observe far greater exchange within the same bacterial phylum than between different phyla. We probe bacteria-virus interactions; unexpectedly, we identify a significant in vivo association between crAssphage, an abundant bacteriophage, and a single strain of Bacteroides vulgatus. Microbe-seq contributes high-throughput culture-free capabilities to investigate genomic blueprints of complex microbial communities with single-microbe resolution.

59 BASIC BIOLOGICAL SCIENCES↗

Barometric Pumping Through Fractured Rock: A Mechanism for Venting Deep Methane to Mars' Atmosphere

Abstract Both the source of methane on Mars and the mechanism for transmission from the subsurface to the atmosphere are not fully understood. Previous seepage simulations have invoked relatively shallow subsurface sources to explain observed methane signatures on Mars. We propose that barometric‐pressure pumping through fracture networks could be an effective mechanism for methane transport from the deep subsurface on Mars. Using atmospheric pressure data gathered by Curiosity as input, we simulate methane gas transport from depths of 200 m to the surface. Even with such a deep source, our model reproduces the observed seasonality of methane, and the simulated surface methane fluxes fall within the range of previous estimates derived from atmospheric observations. Because 200 m is the likely minimum hospitable depth for living methanogenic microbes, our fracture network model indirectly reinvigorates the possibility of a microbial source of methane on Mars.

58 GEOSCIENCES↗

Viral but not bacterial community successional patterns reflect extreme turnover shortly after rewetting dry soils

As central members of soil trophic networks, viruses have the potential to drive substantial microbial mortality and nutrient turnover. Pinpointing viral contributions to terrestrial ecosystem processes remains a challenge, as temporal dynamics are difficult to unravel in the spatially and physicochemically heterogeneous soil environment. In Mediterranean grasslands, the first rainfall after seasonal drought provides an ecosystem reset, triggering microbial activity during a tractable window for capturing short-term dynamics. In this report we simulated precipitation in microcosms from four distinct dry grassland soils and generated 144 viromes, 84 metagenomes and 84 16S ribosomal RNA gene amplicon datasets to characterize viral, prokaryotic and relic DNA dynamics over 10 days. Vastly different viral communities in each soil followed remarkably similar successional trajectories. Wet-up triggered a significant increase in viral richness, followed by extensive compositional turnover. Temporal succession in prokaryotic communities was much less pronounced, perhaps suggesting differences in the scales of activity captured by viromes (representing recently produced, ephemeral viral particles) and total DNA. Still, differences in the relative abundances of Actinobacteria (enriched in dry soils) and Proteobacteria (enriched in wetted soils) matched those of their predicted phages, indicating viral predation of dominant bacterial taxa. Rewetting also rapidly depleted relic DNA, which subsequently reaccumulated, indicating substantial new microbial mortality in the days after wet-up, particularly of the taxa putatively under phage predation. Production of abundant, diverse viral particles via microbial host cell lysis appears to be a conserved feature of the early response to soil rewetting, and results suggest the potential for ‘Cull-the-Winner’ dynamics, whereby viruses infect and cull but do not decimate dominant host populations.

54 ENVIRONMENTAL SCIENCES↗

Grassland ecosystem type drives AM fungal diversity and functional guild distribution in North American grasslands

Nutrient exchange forms the basis of the ancient symbiotic relationship that occurs between most land plants and arbuscular mycorrhizal (AM) fungi. Plants provide carbon (C) to AM fungi and fungi provide the plant with nutrients such as nitrogen (N) and phosphorous (P). Nutrient addition can alter this symbiotic coupling in key ways, such as reducing AM fungal root colonization and changing the AM fungal community composition. However, environmental parameters that differentiate ecosystems and drive plant distribution patterns (e.g., pH, moisture), are also known to impact AM fungal communities. Identifying the relative contribution of environmental factors impacting AM fungal distribution patterns is important for predicting biogeochemical cycling patterns and plant-microbe relationships across ecosystems. Here, to evaluate the relative impacts of local environmental conditions and long-term nutrient addition on AM fungal abundance and composition across grasslands, we studied experimental plots amended for 10 years with N, P, or N and P fertilizer in different grassland ecosystem types, including tallgrass prairie, montane, shortgrass prairie, and desert grasslands. Contrary to our hypothesis, we found ecosystem type, not nutrient treatment, was the main driver of AM fungal root colonization, diversity, and community composition, even when accounting for site-specific nutrient limitations. We identified several important environmental drivers of grassland ecosystem AM fungal distribution patterns, including aridity, mean annual temperature, root moisture, and soil pH. This work provides empirical evidence for niche partitioning strategies of AM fungal functional guilds and emphasizes the importance of long-term, large scale research projects to provide ecologically relevant context to nutrient addition studies.

59 BASIC BIOLOGICAL SCIENCES↗

Motion Dynamics of Motile Microbes in Pore-Networks and its Implications for Reactive Transport Processes

This report outlines new methods to improve simulations of microbial transport and microbially mediated reactions in porous media. A range of experimental, modeling, and machine learning tools are introduced to make these simulations faster, more reliable, and useful for real-world applications. At the microscopic level, the study investigates how different types of bacteria move through confined spaces. A new artificial intelligence tool called DeepTrackStat, is introduced to track motions dynamics as observed in videos of particles migrating through pore networks. This tool is especially helpful for studying fast-moving microbes and requires less computing power than traditional tracking methods. At larger scales, the research looks at how microbes and chemicals interact in zones where surface water and groundwater meet. To connect the small- and large-scale findings, the study presents a neural network model called STAMNet. This tool helps scale up detailed small-scale microbial motion behaviors to predict large-scale environmental changes more efficiently. By combining lab experiments, computer models, and artificial intelligence, the research presented supports smarter environmental decision-making, especially in bioremediation of contaminated groundwater and protection of water quality.

54 ENVIRONMENTAL SCIENCES↗

Inferring the Contribution of Microbial Taxa and Organic Matter Molecular Formulas to Ecological Assembly

Understanding the mechanisms underlying the assembly of communities has long been the goal of many ecological studies. While several studies have evaluated community wide ecological assembly, fewer have focused on investigating the impacts of individual members within a community or assemblage on ecological assembly. Here, we adapted a previous null model β-nearest taxon index (βNTI) to measure the contribution of individual features within an ecological community to overall assembly. This new metric, called feature-level βNTI (βNTI feat ), enables researchers to determine whether ecological features (e.g., individual microbial taxa) contribute to divergence, convergence, or have insignificant impacts across spatiotemporally resolved metacommunities or meta-assemblages. Using βNTI feat , we revealed that unclassified microbial lineages often contributed to community divergence while diverse groups (e.g., Crenarchaeota, Alphaproteobacteria, and Gammaproteobacteria) contributed to convergence. We also demonstrate that βNTI feat can be extended to other ecological assemblages such as organic molecules comprising organic matter (OM) pools. OM had more inconsistent trends compared to the microbial community though CHO-containing molecular formulas often contributed to convergence, while nitrogen and phosphorus-containing formulas contributed to both convergence and divergence. A network analysis was used to relate βNTI feat values from the putatively active microbial community and the OM assemblage and examine potentially common contributions to ecological assembly across different communities/assemblages. This analysis revealed that P-containing formulas often contributed to convergence/divergence separately from other ecological features and N-containing formulas often contributed to assembly in coordination with microorganisms. Additionally, members of Family Geobacteraceae were often observed to contribute to convergence/divergence in conjunction with both N- and P-containing formulas, suggesting a coordinated ecological role for family members and the nitrogen/phosphorus cycle. Overall, we show that βNTI feat offers opportunities to investigate the community or assemblage members, which shape the phylogenetic or functional landscape, and demonstrate the potential to evaluate potential points of coordination across various community types.

59 BASIC BIOLOGICAL SCIENCES↗

How Does Escherichia coli Allocate Proteome?

Microorganisms are shown to actively partition their intracellular resources, such as pro- teins, for growth optimization. Recent experiments have begun to reveal molecular com- ponents unpinning the partition; however, it remains unclear quantitatively how individual parts orchestrate to yield precise resource allocation that is both robust and dynamic. Here we developed a coarse-grained mathematical framework that centers on guanosine pentaphosphate (ppGpp)-mediated regulation, and used it to systematically uncover the design principles of proteome allocation in Escherichia coli. Our results showed that cellular ability of resource partition lies in an ultrasensitive, negative feedback control- ling topology with the ultrasensitivity arising from zero-order amino acid kinetics and the negative feedback from ppGpp-controlled ribosome synthesis. In addition, together with the time-scale separation between slow ribosome kinetics and fast turnovers of ppGpp and amino acids, the network topology confers the organism an optimization mechanism which mimics sliding mode control, a nonlinear optimization strategy that is widely used in man-made systems. We further showed that such a controlling mechanism is robust against parameter variations and molecular fluctuations, and is also efficient for biomass production over time. Furthermore, this work elucidates the fundamental controlling mechanism of E. coli proteome allocation, thereby providing insights into quantitative microbial physiology as well as the design of synthetic gene networks.

59 BASIC BIOLOGICAL SCIENCES↗