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At least 37 records · Page 2

Active predation, phylogenetic diversity, and global prevalence of myxobacteria in wastewater treatment plants

The operation of modern wastewater treatment plants (WWTPs) is driven by activated sludge microbiota, a complex assemblage of trophically interacting microorganisms. Microbial predation is crucial to fundamental understanding of how biological interactions drive microbiome structuring and functioning of WWTPs. However, predatory bacteria have received little attention regarding their diversity, activity, and ecological function in activated sludge, limiting the exploitation of food web interactions for wastewater microbiome engineering. Here, by using rRNA-stable isotope probing of activated sludge microbiota with 13 C-labeled prey bacteria, we uncovered diverse as-yet-uncultivated putative predatory bacteria that actively incorporated 13 C-biomass. Myxobacteria, especially Haliangium and the mle1-27 clade, were found as the dominant active predators, refreshing conventional views based on a few predatory isolates of Bdellovibrionota from WWTPs. The identified predatory bacteria showed more selective predation on prey compared with the protists dominated by ciliates, providing in situ evidence for inter-domain predation behavior divergence in activated sludge. Putative predatory bacteria were tracked over a two-year microbiome monitoring effort at a local WWTP, revealing the predominance of Myxococcota (6.5 ± 1.3%) over Bdellovibrionota (1.0 ± 0.2%) lineages. Phylogenetic analysis unveiled highly diverse myxobacteria inhabiting activated sludge and suggested a habitat filtering effect in global WWTPs. Further mining of a global activated sludge microbiome dataset revealed the prevalence of Myxococcota (5.4 ± 0.1%) species and potential impacts of myxobacterial predation on process performance. Collectively, our findings provided unique insights into the predating activity, diversity, and prevalence of Myxococcota species in activated sludge, highlighting their links with wastewater treatment processes via trophic regulation of enteric and functional bacteria.

59 BASIC BIOLOGICAL SCIENCES↗

Microbial spies and bloggers: programming cells to convert environmental information into discernible signals

Microbes regulate their dynamic behaviors using the chemical and physical characteristics of their environment. The ability of microbes to continuously convert this physicochemical information into biochemical information and to use organic matter in the environment as a power source makes these organisms attractive as chassis for building sensors. However, most biosensors have severe limitations when considering applications in hard-to-image settings like soils, sediments, and wastewater. Emerging technologies at the interface of biomolecular design, microbiome engineering, and synthetic biology offer new tools to program cells and communities as biosensors for these settings. Here, in this review, we describe innovations in biosensor outputs that are enabling new applications in complex environments, including reporters that are read out using electrochemical, gas chromatography, hyperspectral imaging, and next-generation sequencing methods. We also discuss computational advances that are accelerating the diversification of sensing components by mining metagenomics data for new transcriptional regulators and by designing allosteric protein switches that directly regulate reporter outputs using analytes. We highlight emerging opportunities for programming undomesticated microbes in communities to function as distributed sensors in the environment. Finally, we discuss the need for responsible biosensor development and to modernize regulatory frameworks to support evidence-based assessment of environmental biosensors.

analyte↗

High-throughput mapping of the phage resistance landscape in E. coli

Bacteriophages (phages) are critical players in the dynamics and function of microbial communities and drive processes as diverse as global biogeochemical cycles and human health. Phages tend to be predators finely tuned to attack specific hosts, even down to the strain level, which in turn defend themselves using an array of mechanisms. However, to date, efforts to rapidly and comprehensively identify bacterial host factors important in phage infection and resistance have yet to be fully realized. Here, we globally map the host genetic determinants involved in resistance to 14 phylogenetically diverse double-stranded DNA phages using two model Escherichia coli strains (K-12 and BL21) with known sequence divergence to demonstrate strain-specific differences. Using genome-wide loss-of-function and gain-of-function genetic technologies, we are able to confirm previously described phage receptors as well as uncover a number of previously unknown host factors that confer resistance to one or more of these phages. We uncover differences in resistance factors that strongly align with the susceptibility of K-12 and BL21 to specific phage. We also identify both phage specific mechanisms, such as the unexpected role of cyclic-di-GMP in host sensitivity to phage N4, and more generic defenses, such as the overproduction of colanic acid capsular polysaccharide that defends against a wide array of phages. Our results indicate that host responses to phages can occur via diverse cellular mechanisms. Our systematic and high-throughput genetic workflow to characterize phage-host interaction determinants can be extended to diverse bacteria to generate datasets that allow predictive models of how phage-mediated selection will shape bacterial phenotype and evolution. The results of this study and future efforts to map the phage resistance landscape will lead to new insights into the coevolution of hosts and their phage, which can ultimately be used to design better phage therapeutic treatments and tools for precision microbiome engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Microbial community composition controls carbon flux across litter types in early phase of litter decomposition

Leaf litter decomposition is a major carbon input to soil, making it a target for increasing soil carbon storage through microbiome engineering. We expand upon previous findings to show with multiple leaf litter types that microbial composition can drive variation in carbon flow from litter decomposition and specific microbial community features are associated with synonymous patterns of carbon flow among litter types. Although plant litter type selects for different decomposer communities, within a litter type, microbial composition drives variation in the quantity of dissolved organic carbon (DOC) measured at the end of the decomposition period. Bacterial richness was negatively correlated with DOC quantity, supporting our hypothesis that across multiple litter types there are common microbial traits linked to carbon flow patterns. Variation in DOC abundance (i.e. high versus low DOC) driven by microbial composition is tentatively due to differences in bacterial metabolism of labile compounds, rather than catabolism of non-labile substrates such as lignin. The temporal asynchrony of metabolic processes across litter types may be a substantial impediment to discovering more microbial features common to synonymous patterns of carbon flow among litters. Overall, our findings support the concept that carbon flow may be programmed by manipulating microbial community composition.

59 BASIC BIOLOGICAL SCIENCES↗

Tetranucleotide frequencies differentiate genomic boundaries and metabolic strategies across environmental microbiomes

Microbiomes are constrained by physicochemical conditions, nutrient regimes, and community interactions across diverse environments, yet genomic signatures of this adaptation remain unclear. Metagenome sequencing is a powerful technique to analyze genomic content in the context of natural environments, establishing concepts of microbial ecological trends. Here, we developed a data discovery tool-a tetranucleotide-informed metagenome stability diagram-that is publicly available in the integrated microbial genomes and microbiomes (IMG/M) platform for metagenome ecosystem analyses. We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments and that specific functional and metabolic trends can be observed in this structuring. Our tool places metagenomes sampled from diverse environments into clusters and along gradients of tetranucleotide frequency similarity, suggesting microbiome community compositions specific to gradient conditions. Within the resulting metagenome clusters, we identify protein-coding gene identifiers that are most differentiated between ecosystem classifications. We plan for annual updates to the metagenome stability diagram in IMG/M with new data, allowing for refinement of the ecosystem classifications delineated here. This framework has the potential to inform future studies on microbiome engineering, bioremediation, and the prediction of microbial community responses to environmental change. IMPORTANCE: Microbes adapt to diverse environments influenced by factors like temperature, acidity, and nutrient availability. We developed a new tool to analyze and visualize the genetic makeup of over 12,000 microbial communities, revealing patterns linked to specific functions and metabolic processes. This tool groups similar microbial communities and identifies characteristic genes within environments. By continually updating this tool, we aim to advance our understanding of microbial ecology, enabling applications like microbial engineering, bioremediation, and predicting responses to environmental change.

Kellom, Matthew↗

A Genomic Catalogue of Earth’s Microbiomes - Introductory KBase Narrative

The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled unprecedented insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this powerful approach to over 10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, human- and animal-host associated microbiomes, engineered environments, and natural and agricultural soils to capture extant microbial metabolic and functional potential. We present a comprehensive catalogue of 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units (OTUs), spanning 135 phyla, which expand the known phylogenetic diversity of Bacteria and Archaea by 44%. We also demonstrate the utility of this collection for secondary metabolite biosynthetic potential and predicting host-virus linkage, which can provide a view into the global distribution of lysogenic viruses. This resource underscores the value of leveraging genome-centric approaches to reveal genomic properties of uncultivated microbes that impact on ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

Persistence Control of Engineered Functions in Complex Soil Microbiomes (PerCon SFA), Secure Biosystems Design Project Data Catalog at PNNL DataHub

The Persistence Control of Engineered Functions in Complex Soil Microbiomes Project (PerCon SFA) at Pacific Northwest National Laboratory (PNNL) is a Genomic Sciences Program Biosystems Design, Science Focus Area research project consortium. Collaborating across highly integrated institutions, PerCon SFA scientists are exploring how environmental niches can be sculpted using the mechanisms of genome reduction and metabolic addiction to drive secure rhizosphere community design for robust biomass cropping in challenging environments. The PerCon SFA DataHub project repository contains publication-relevant digital dataset and metadata DOI packages, enabling exploration and download of integrated experimental dataset catalogs publicly available to a global scientific community. and metadata repository allow for exploring and downloading integrated experimental biodesign omics dataset catalogs, including experimental protocols and/or workflows, raw and/or processed data, as required by the repository, and other relevant supporting materials and/or metadata required for research reproducibility and reporting.

59 BASIC BIOLOGICAL SCIENCES↗

Polysaccharide utilization loci in Bacteroides determine population fitness and community-level interactions

Polysaccharide utilization loci (PULs) are co-regulated bacterial genes that sense nutrients and enable glycan digestion. Human gut microbiome members, notably Bacteroides, contain numerous PULs that enable glycan utilization and shape ecological dynamics. To investigate the role of PULs on fitness and inter-species interactions, we develop a CRISPR-based genome editing tool to study 23 PULs in Bacteroides uniformis (BU). BU PULs show distinct glycan-degrading functions and transcriptional coordination that enables the population to adapt upon loss of other PULs. Exploiting a BU mutant barcoding strategy, we demonstrate that in vitro fitness and BU colonization in the murine gut are enhanced by deletion of specific PULs and modulated by glycan availability. PULs mediate glycan-dependent interactions with butyrate producers that depend on the degradation mechanism and glycan utilization ability of the butyrate producer. Thus, PULs determine community dynamics and butyrate production and provide a selective advantage or disadvantage depending on the nutritional landscape.

59 BASIC BIOLOGICAL SCIENCES↗

Microbiome differences in sugarcane and metabolically engineered oilcane accessions and their implications for bioenergy production

Abstract Oilcane is a metabolically engineered sugarcane ( Saccharum spp. hybrid) that hyper-accumulates lipids in its vegetable biomass to provide an advanced feedstock for biodiesel production. The potential impact of hyper-accumulation of lipids in vegetable biomass on microbiomes and the consequences of altered microbiomes on plant growth and lipid accumulation have not been explored so far. Here, we explore differences in the microbiome structure of different oilcane accessions and non-modified sugarcane. 16S SSU rRNA and ITS rRNA amplicon sequencing were performed to compare the characteristics of the microbiome structure from different plant compartments (leaf, stem, root, rhizosphere, and bulk soil) of four greenhouse-grown oilcane accessions and non-modified sugarcane. Significant differences were only observed in the bacterial microbiomes. In leaf and stem microbiomes, more than 90% of the entire microbiome of non-modified sugarcane and oilcane was dominated by similar core taxa. Taxa associated with Proteobacteria led to differences in the non-modified sugarcane and oilcane microbiome structure. While differences were observed between multiple accessions, accession 1566 was notable in that it was consistently observed to differ in its microbial membership than other accessions and had the lowest abundance of taxa associated with plant-growth-promoting bacteria. Accession 1566 is also unique among oilcane accessions in that it has the highest constitutive expression of the WRI 1 transgene. The WRI 1 transcription factor is known to contribute to significant changes in the global gene expression profile, impacting plant fatty acid biosynthesis and photomorphogenesis. This study reveals for the first time that genetically modified oilcanes associate with distinct microbiomes. Our findings suggest potential relationships between core taxa, biomass yield, and TAG in oilcane accessions and support further research on the relationship between plant genotypes and their microbiomes.

09 BIOMASS FUELS↗

Biotic Interactions Are More Important than Propagule Pressure in Microbial Community Invasions

ABSTRACT Microbial probiotics are intended to improve functions in diverse ecosystems, yet probiotics often fail to establish in a preexisting microbiome. This is a species invasion problem. The relative importance of the two major factors controlling establishment in this context—propagule pressure (inoculation dose and frequency) and biotic interactions (composition of introduced and resident communities)—is unknown. We tested the effect of these factors in driving microbial composition and functioning following 12 microbial community invasions (e.g., introductions of many microbial invaders) in microcosms. Ecosystem functioning over a 30-day postinvasion period was assessed by measuring activity (respiration) and environment modification (dissolved organic carbon abundance). To test the dependence on environmental context, experiments were performed in two resource environments. In both environments, biotic interactions were more important than propagule pressure in driving microbial composition and community function, but the magnitude of effect varied by environment. Successful invaders comprised approximately 8% of the total number of operational taxonomic units (OTUs). Bacteria were better invaders than fungi, with average relative abundances of 7.4% ± 6.8% and 1.5% ± 1.4% of OTUs, respectively. Common bacterial invaders were associated with stress response traits. The most resilient bacterial and fungal families, in other words, those least impacted by invasions, were linked to antimicrobial resistance or production traits. Illuminating the principles that determine community composition and functioning following microbial invasions is key to efficient community engineering. IMPORTANCE With increasing frequency, humans are introducing new microbes into preexisting microbiomes to alter functioning. Example applications include modification of microflora in human guts for better health and those of soil for food security and/or climate management. Probiotic applications are often approached as trial-and-error endeavors and have mixed outcomes. We propose that increased success in microbiome engineering may be achieved with a better understanding of microbial invasions. We conducted a microbial community invasion experiment to test the relative importance of propagule pressure and biotic interactions in driving microbial community composition and ecosystem functioning in microcosms. We found that biotic interactions were more important than propagule pressure in determining the impact of microbial invasions. Furthermore, the principles for community engineering vary among organismal groups (bacteria versus fungi).

59 BASIC BIOLOGICAL SCIENCES↗

Higher-order interaction effects among operating conditions and feedstocks shape reactor microbiomes and fatty acid production profiles

Arrested anaerobic digestion (AAD) offers a promising route for producing fatty acids (FAs) from organic residues, yet optimal conditions for selectively generating medium-chain fatty acids (MCFAs) remain poorly defined. Here, we systematically evaluated the main and interaction effects of pH (5, 7, 9), feedstock (food waste, manure), temperature (35 and 45 °C), and inoculum source on microbiome composition and FA production. Anaerobic digester sludge and a novel bison rumen inoculum were compared. Significant higher-order interactions among operating parameters governed FA profiles and microbiome structure. Butyric acid production was driven by a three-way interaction among pH, feedstock, and temperature (p < 0.001), with maximum concentrations achieved in food waste reactors at pH 5.0 and 35 °C (1.2 ± 0.1 g L −1 with sludge and 1.1 ± 0.3 g L −1 with rumen). MCFA production exhibited significant four-way interactions (p < 0.1 to p < 0.001). At 45 °C and pH 5.0, inoculum source tuned MCFA selectivity: sludge favored pentanoic acid (0.4 ± 0.1 g L −1 ), whereas rumen favored hexanoic and heptanoic acids (up to 0.4 ± 0.2 g L −1 ). Manure reactors produced < 0.2 g L −1 MCFAs under all conditions. Genera, including Megasphaera, Prevotella, and Lactobacillus, were associated with production of specific MCFAs. PICRUSt2-based pathway predictions were consistent with MCFA production patterns and suggested a potential role for lactic acid–driven chain elongation pathways. This study provides insights into how interacting operating conditions shape AAD microbiomes, their FA profiles, and advances the trajectory of research aimed at engineering robust and controllable microbiomes for waste valorization.

09 BIOMASS FUELS↗

Stochasticity in microbiology: managing unpredictability to reach the Sustainable Development Goals

Pure (single) cultures of microorganisms and mixed microbial communities (microbiomes) have been important for centuries in providing renewable energy, clean water and food products to human society and will continue to play a crucial role to pursue the Sustainable Development Goals. To use microorganisms effectively, microbial engineered processes require adequate control. Microbial communities are shaped by manageable deterministic processes, but also by stochastic processes, which can promote unforeseeable variations and adaptations. Here, we highlight the impact of stochasticity in single culture and microbiome engineering. First, we discuss the concepts and mechanisms of stochasticity in relation to microbial ecology of single cultures and microbiomes. Second, we discuss the consequences of stochasticity in relation to process performance and human health, which are reflected in key disadvantages and important opportunities. Third, we propose a suitable decision tool to deal with stochasticity in which monitoring of stochasticity and setting the boundaries of stochasticity by regulators are central aspects. Stochasticity may give rise to some risks, such as the presence of pathogens in microbiomes. We argue here that by taking the necessary precautions and through clever monitoring and interpretation, these risks can be mitigated.

59 BASIC BIOLOGICAL SCIENCES↗

CRISPR-based engineering of phages for in situ bacterial base editing

Investigation of microbial gene function is essential to the elucidation of ecological roles and complex genetic interactions that take place in microbial communities. While microbiome studies have increased in prevalence, the lack of viable in situ editing strategies impedes experimental progress, rendering genetic knowledge and manipulation of microbial communities largely inaccessible. Here, we demonstrate the utility of phage-delivered CRISPR-Cas payloads to perform targeted genetic manipulation within a community context, deploying a fabricated ecosystem (EcoFAB) as an analog for the soil microbiome. First, we detail the engineering of two classical phages for community editing using recombination to replace nonessential genes through Cas9-based selection. We show efficient engineering of T7, then demonstrate the expression of antibiotic resistance and fluorescent genes from an engineered λ prophage within an Escherichia coli host. Next, we modify λ to express an APOBEC-1-based cytosine base editor (CBE), which we leverage to perform C-to-T point mutations guided by a modified Cas9 containing only a single active nucleolytic domain (nCas9). We strategically introduce these base substitutions to create premature stop codons in-frame, inactivating both chromosomal ( lacZ ) and plasmid-encoded genes (mCherry and ampicillin resistance) without perturbation of the surrounding genomic regions. Furthermore, using a multigenera synthetic soil community, we employ phage-assisted base editing to induce host-specific phenotypic alterations in a community context both in vitro and within the EcoFAB, observing editing efficiencies from 10 to 28% across the bacterial population. The concurrent use of a synthetic microbial community, soil matrix, and EcoFAB device provides a controlled and reproducible model to more closely approximate in situ editing of the soil microbiome.

59 BASIC BIOLOGICAL SCIENCES↗

Defined synthetic microbial communities colonize and benefit field-grown sorghum

The rhizosphere constitutes a dynamic interface between plant hosts and their associated microbial communities. Despite the acknowledged potential for enhancing plant fitness by manipulating the rhizosphere, the engineering of the rhizosphere microbiome through inoculation has posed significant challenges. These challenges are thought to arise from the competitive microbial ecosystem where introduced microbes must survive, and the absence of adaptation to the specific metabolic and environmental demands of the rhizosphere. Here, in this study, we engineered a synthetic rhizosphere community (SRC1) with the anticipation that it would exhibit a selective advantage in colonizing the host Sorghum bicolor, thereby potentially fostering its growth. SRC1 was assembled from bacterial isolates identified either for their potential role in community cohesion through network analysis or for their ability to benefit from host-specific exudate compounds. The growth performance of SRC1 was assessed in vitro on solid media, in planta under gnotobiotic laboratory conditions, and in the field. Our findings reveal that SRC1 cohesion is most robust when cultivated in the presence of the plant host under laboratory conditions, with lineages being lost from the community when grown either in vitro or in a native field setting. We establish that SRC1 effectively promotes the growth of both above- and below-ground plant phenotypes in both laboratory and native field contexts. Furthermore, in laboratory conditions, these growth enhancements correlate with the transcriptional dampening of lignin biosynthesis in the host. Collectively, these results underscore the potential utility of synthetic microbial communities for modulating crop performance in controlled and native environments alike.

60 APPLIED LIFE SCIENCES↗

LinkML: an open data modeling framework

Background Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, nonstandardized spreadsheets, or data repositories. This lack of structure challenges interoperability, making data integration, validation, and reuse difficult. Findings LinkML (Linked Data Modeling Language) is an open framework that simplifies the process of authoring, validating, and sharing data. LinkML can describe a range of data structures, from flat, list-based models to complex, interrelated, and normalized models that utilize polymorphism and compound inheritance. It offers an approachable syntax that is not tied to any one technical architecture and can be integrated seamlessly with many existing frameworks. The LinkML syntax provides a standard way to describe schemas, classes, and relationships, allowing modelers to build well-defined, stable, and optionally ontology-aligned data structures. Once defined, LinkML schemas may be imported into other LinkML schemas. These key features make LinkML an accessible platform for interdisciplinary collaboration and a reliable way to define and share data semantics. Conclusions LinkML helps reduce heterogeneity, complexity, and the proliferation of single-use data models while simultaneously enabling compliance with FAIR (Findable, Accessible, Interoperable, and Reusable) data standards. LinkML has seen increasing adoption in various fields, including biology, chemistry, biomedicine, microbiome research, finance, electrical engineering, transportation, and commercial software development. In short, LinkML makes implicit models explicitly computable and allows data to be standardized at their origin. LinkML documentation and code are available at https://linkml.io/.

AI-ready data↗