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Metabolite sensing is a fundamental biological process, and the perception of dynamic changes in the extracellular environment is of paramount importance for the survival of organisms. Bacteria usually adjust their metabolisms to changing environments via transcriptional regulation.
We report here the genome sequences of three Aquimarina megaterium strains isolated from the octocoral Eunicella labiata . We reveal a coding potential for versatile carbon metabolism and biosynthesis of natural products belonging to the polyketide, nonribosomal peptide, and terpene compound classes.
Recent genomic analyses have revealed that anaerobic gut fungi possess both the largest number and highest diversity of lignocellulolytic enzymes of all sequenced fungi, explaining their ability to decompose lignocellulosic substrates, e.g., agricultural waste, into fermentable sugars. Despite their potential, the development of engineering methods for these organisms has been slow due to their complex life cycle, understudied metabolism, and challenging anaerobic culture requirements.
Increasing anthropogenic inputs of fixed nitrogen are leading to greater eutrophication of aquatic environments, but it is unclear how this impacts the flux and fate of carbon in lacustrine and riverine systems. Here, we present evidence that the form of nitrogen governs the partitioning of carbon among members in a genome-sequenced, model phototrophic biofilm of 20 members. Consumption of NO 3 – as the sole nitrogen source unexpectedly resulted in more rapid transfer of carbon to heterotrophs than when NH 4 + was also provided, suggesting alterations in the form of carbon exchanged. The form of nitrogen dramatically impacted net community nitrogen, but not carbon, uptake rates. Furthermore, this alteration in nitrogen form caused very large but focused alterations to community structure, strongly impacting the abundance of only two species within the biofilm and modestly impacting a third member species. Our data suggest that nitrogen metabolism may coordinate coupled carbon-nitrogen biogeochemical cycling in benthic biofilms and, potentially, in phototroph-heterotroph consortia more broadly. It further indicates that the form of nitrogen inputs may significantly impact the contribution of these communities to carbon partitioning across the terrestrial-aquatic interface.
The photosynthetic and diazotrophic cyanobacterium Trichodesmium is a key contributor to marine biogeochemical cycles in the subtropical-oligotrophic oceans. Trichodesmium form colonies that harbor a distinct microbial community in comparison to the surrounding seawater. The presence of their associated bacteria can expand Trichodesmium’s functional potential and is predicted to influence the cycling of carbon, nitrogen, phosphorus, and iron (C, N, P, and Fe). To link the bacteria associated with Trichodesmium to key functional traits and elucidate how community structure can influence nutrient cycling, we characterized Red Sea Trichodesmium colonies using metagenomics and metaproteomics. Colonies harbored bacteria that typically associate with algae and particles, such as the ubiquitous Alteromonas macleodii, but also lineages specific to Trichodesmium, such as members from the order Balneolales. The majority of associated bacteria were auxotrophic for different vitamins, indicating their dependency on vitamin production by Trichodesmium. The associated bacteria carry functional traits including siderophore biosynthesis, reduced phosphorus metabolism, and denitrification pathways. The analysis supports Trichodesmium as an active hotspot for C, N, P, Fe, and vitamin exchange. In turn, Trichodesmium may rely on associated bacteria to meet its high Fe demand as several lineages synthesize photolabile siderophores (e.g., vibrioferrin, rhizoferrin, petrobactin) which can enhance the bioavailability of particulate Fe to the entire consortium. Collectively, the results indicate that Trichodesmium colonies provide a structure where these interactions can take place. While further studies are required to clarify the exact nature of these interactions, Trichodesmium’s reliance on particle and algae-associated bacteria and the observed redundancy of key functional traits likely underpins the resilience of Trichodesmium within an ever-changing global environment.
Miscanthus × giganteus is a promising high-yielding perennial plant to meet growing bioenergy demands; however, the degree to which the soil microbiome affects its nitrogen cycling and subsequently, biomass yield remains unclear. In this study, we hypothesize that contributions of metabolically active soil microbial membership may be underestimated with DNA-based approaches. We assessed the response of the soil microbiome to nitrogen availability in terms of both DNA and RNA soil microbial communities from the Long-term Assessment of Miscanthus Productivity and Sustainability (LAMPS) field trial. DNA and RNA were extracted from 271 samples, and 16S small subunit (SSU) rRNA amplicon sequencing was performed to characterize microbial community structure. Significant differences were observed in the resulting soil microbiomes and were best explained by the sequencing library of origin, either DNA or RNA. Similar numbers of membership were detected in DNA and RNA microbial communities, with more than 90% of membership shared. However, the profile of dominant membership within DNA and RNA differed, with varying proportions of Actinobacteria and Proteobacteria and Firmicutes and Proteobacteria. Only RNA microbial communities showed seasonal responses to nitrogen fertilization, and these differences were associated with nitrogen-cycling bacteria. The relative abundance of bacteria associated with nitrogen cycling was 7-fold higher in RNA than in DNA, and genes associated with denitrifying bacteria were significantly enriched in RNA, suggesting that these bacteria may be underestimated with DNA-only approaches. Our findings indicate that RNA-based SSU characterization can be a significant and complementing resource for understanding the role of soil microbiomes in bioenergy crop production.
Data supporting manuscript submitted to PNAS: Video-Rate Raman-based Metabolic Imaging by Airy Light-Sheet Illumination and Photon-Sparse Detection. The data set includes: [1] raw data and [2] related images used in the analyses described within the manuscript.
Abstract Background Biochemical reaction prediction tools leverage enzymatic promiscuity rules to generate reaction networks containing novel compounds and reactions. The resulting reaction networks can be used for multiple applications such as designing novel biosynthetic pathways and annotating untargeted metabolomics data. It is vital for these tools to provide a robust, user-friendly method to generate networks for a given application. However, existing tools lack the flexibility to easily generate networks that are tailor-fit for a user’s application due to lack of exhaustive reaction rules, restriction to pre-computed networks, and difficulty in using the software due to lack of documentation. Results Here we present Pickaxe, an open-source, flexible software that provides a user-friendly method to generate novel reaction networks. This software iteratively applies reaction rules to a set of metabolites to generate novel reactions. Users can select rules from the prepackaged JN1224min ruleset, derived from MetaCyc, or define their own custom rules. Additionally, filters are provided which allow for the pruning of a network on-the-fly based on compound and reaction properties. The filters include chemical similarity to target molecules, metabolomics, thermodynamics, and reaction feasibility filters. Example applications are given to highlight the capabilities of Pickaxe: the expansion of common biological databases with novel reactions, the generation of industrially useful chemicals from a yeast metabolome database, and the annotation of untargeted metabolomics peaks from an E. coli dataset. Conclusion Pickaxe predicts novel metabolic reactions and compounds, which can be used for a variety of applications. This software is open-source and available as part of the MINE Database python package ( https://pypi.org/project/minedatabase/ ) or on GitHub ( https://github.com/tyo-nu/MINE-Database ). Documentation and examples can be found on Read the Docs ( https://mine-database.readthedocs.io/en/latest/ ). Through its documentation, pre-packaged features, and customizable nature, Pickaxe allows users to generate novel reaction networks tailored to their application.
In every omics experiment, genes or their products are identified for which even state of the art tools are unable to assign a function. In the biotechnology chassis organism Pseudomonas putida, these proteins of unknown function make up 14% of the proteome. This missing information can bias analyses since these proteins can carry out functions which impact the engineering of organisms. As a consequence of predicting protein function across all organisms, function prediction tools generally fail to use all of the types of data available for any specific organism, including protein and transcript expression information. Additionally, the release of Alphafold predictions for all Uniprot proteins provides a novel opportunity for leveraging structural information. We constructed a bespoke machine learning model to predict the function of recalcitrant proteins of unknown function in Pseudomonas putida based on these sources of data, which annotated 1079 terms to 213 proteins. Among the predicted functions supplied by the model, we found evidence for a significant overrepresentation of nitrogen metabolism and macromolecule processing proteins. These findings were corroborated by manual analyses of selected proteins which identified, among others, a functionally unannotated operon that likely encodes a branch of the shikimate pathway.
Abstract Bacterial communities are ubiquitous, found in natural ecosystems, such as soil, and within living organisms, like the human microbiome. The dynamics of these communities in diverse environments depend on factors such as spatial features of the microbial niche, biochemical kinetics, and interactions among bacteria. Moreover, in many systems, bacterial communities are influenced by multiple physical mechanisms, such as mass transport and detachment forces. One example is gut mucosal communities, where dense, closely packed communities develop under the concurrent influence of nutrient transport from the lumen and fluid-mediated detachment of bacteria. In this study, we model a mucosal niche through a coupled agent-based and finite-volume modeling approach. This methodology enables us to model bacterial interactions affected by nutrient release from various sources while adjusting individual bacterial kinetics. We explored how the dispersion and abundance of bacteria are influenced by biochemical kinetics in different types of metabolic interactions, with a particular focus on the trade-off between growth rate and yield. Our findings demonstrate that in competitive scenarios, higher growth rates result in a larger share of the niche space. In contrast, growth yield plays a critical role in neutralism, commensalism, and mutualism interactions. When bacteria are introduced sequentially, they cause distinct spatiotemporal effects, such as deeper niche colonization in commensalism and mutualism scenarios driven by species intermixing effects, which are enhanced by high growth yields. Moreover, sub-ecosystem interactions dictate the dynamics of three-species communities, sometimes yielding unexpected outcomes. Competitive, fast-growing bacteria demonstrate robust colonization abilities, yet they face challenges in displacing established mutualistic systems. Bacteria that develop a cooperative relationship with existing species typically obtain niche residence, regardless of their growth rates, although higher growth yields significantly enhance their abundance. Our results underscore the importance of bacterial niche dynamics in shaping community properties and succession, highlighting a new approach to manipulating microbial systems.
The reconstruction and analysis of genome-scale metabolic models constitutes a powerful systems biology approach, with applications ranging from basic understanding of genotype-phenotype mapping to solving biomedical and environmental problems. However, the biological insight obtained from these models is limited by multiple heterogeneous sources of uncertainty, which are often difficult to quantify. Here we review the major sources of uncertainty and survey existing approaches developed for representing and addressing them. A unified formal characterization of these uncertainties through probabilistic approaches and ensemble modeling will facilitate convergence towards consistent reconstruction pipelines, improved data integration algorithms, and more accurate assessment of predictive capacity.
Engineering efforts targeted at increasing ethanol by modifying the central fermentative metabolism of Clostridium thermocellum have been variably successful. Here, we aim to understand this variation by a multifaceted approach including genomic and transcriptomic analysis combined with chemostat cultivation and high solids cellulose fermentation. Three strain lineages comprising 16 strains total were examined. Two strain lineages in which genes involved in pathways leading to organic acids and/or sporulation had been knocked out resulted in four end-strains after adaptive laboratory evolution (ALE). A third strain lineage recapitulated mutations involving adhE that occurred spontaneously in some of the engineered strains.
Fuels and chemicals derived from non-fossil sources are needed to lessen human impacts on the environment while providing a healthy and growing economy. 3-hydroxypropionic acid (3-HP) is an important chemical building block that can be used for many products. Biosynthesis of 3-HP is possible; however, low production is typically observed in those natural systems. Biosynthetic pathways have been designed to produce 3-HP from a variety of feedstocks in different microorganisms. In this study, the 3-HP β-alanine pathway consisting of aspartate decarboxylase, β-alanine-pyruvate aminotransferase, and 3-hydroxypropionate dehydrogenase from selected microorganisms were codon optimized for Aspergillus species and placed under the control of constitutive promoters. The pathway was introduced into Aspergillus pseudoterreus and subsequently into Aspergillus niger, and 3-HP production was assessed in both hosts. A. niger produced higher initial 3-HP yields and fewer co-product contaminants and was selected as a suitable host for further engineering. Proteomic and metabolomic analysis of both Aspergillus species during 3-HP production identified genetic targets for improvement of flux toward 3-HP including pyruvate carboxylase, aspartate aminotransferase, malonate semialdehyde dehydrogenase, succinate semialdehyde dehydrogenase, oxaloacetate hydrolase, and a 3-HP transporter. Overexpression of pyruvate carboxylase improved yield in shake-flasks from 0.09 to 0.12 C-mol 3-HP C-mol -1 glucose in the base strain expressing 12 copies of the β-alanine pathway. Deletion or overexpression of individual target genes in the pyruvate carboxylase overexpression strain improved yield to 0.22 C-mol 3-HP C-mol -1 glucose after deletion of the major malonate semialdehyde dehydrogenase. Further incorporation of additional β-alanine pathway genes and optimization of culture conditions (sugars, temperature, nitrogen, phosphate, trace elements) for 3-HP production from deacetylated and mechanically refined corn stover hydrolysate improved yield to 0.48 C-mol 3-HP C-mol -1 sugars and resulted in a final titer of 36.0 g/L 3-HP. The results of this study establish A. niger as a host for 3-HP production from a lignocellulosic feedstock in acidic conditions and demonstrates that 3-HP titer and yield can be improved by a broad metabolic engineering strategy involving identification and modification of genes participated in the synthesis of 3-HP and its precursors, degradation of intermediates, and transport of 3-HP across the plasma membrane.
Abstract Background Recent engineering efforts have targeted the ethanologenic bacterium Zymomonas mobilis for isobutanol production. However, significant hurdles remain due this organism’s vulnerability to isobutanol toxicity, adversely affecting its growth and productivity. The limited understanding of the physiological impacts of isobutanol on Z. mobilis constrains our ability to overcome these production barriers. Results We utilized a systems-level approach comprising LC–MS/MS-based lipidomics, metabolomics, and shotgun proteomics, to investigate how exposure to ethanol and isobutanol impact the lipid membrane composition and overall physiology of Z. mobilis . Our analysis revealed significant and distinct alterations in membrane phospholipid and fatty acid composition resulting from ethanol and isobutanol exposure. Notably, ethanol exposure increased membrane cyclopropane fatty acid content and expression of cyclopropane fatty acid (CFA) synthase. Surprisingly, isobutanol decreased cyclopropane fatty acid content despite robust upregulation of CFA synthase. Overexpression of the native Z. mobilis’ CFA synthase increased cyclopropane fatty acid content in all phospholipid classes and was associated with a significant improvement in growth rates in the presence of added ethanol and isobutanol. Heterologous expression of CFA synthase from Clostridium acetobutylicum resulted in a near complete replacement of unsaturated fatty acids with cyclopropane fatty acids, affecting all lipid classes. However, this did not translate to improved growth rates under isobutanol exposure. Correlating with its greater susceptibility to isobutanol, Z. mobilis exhibited more pronounced alterations in its proteome, metabolome, and overall cell morphology—including cell swelling and formation of intracellular protein aggregates —when exposed to isobutanol compared to ethanol. Isobutanol triggered a broad stress response marked by the upregulation of heat shock proteins, efflux transporters, DNA repair systems, and the downregulation of cell motility proteins. Isobutanol also elicited widespread dysregulation of Z. mobilis ’ primary metabolism evidenced by increased levels of nucleotide degradation intermediates and the depletion of biosynthetic and glycolytic intermediates. Conclusions This study provides a comprehensive, systems-level evaluation of the impact of ethanol and isobutanol exposure on the lipid membrane composition and overall physiology of Z. mobilis . These findings will guide engineering of Z. mobilis towards the creation of isobutanol-tolerant strains that can serve as robust platforms for the industrial production of isobutanol from lignocellulosic sugars.
Background: Microbial colonization of subsurface shales following hydraulic fracturing offers the opportunity to study coupled biotic and abiotic factors that impact microbial persistence in engineered deep subsurface ecosystems. Shale formations underly much of the continental USA and display geographically distinct gradients in temperature and salinity. Complementing studies performed in eastern USA shales that contain brine-like fluids, here we coupled metagenomic and metabolomic approaches to develop the first genome-level insights into ecosystem colonization and microbial community interactions in a lower-salinity, but high-temperature western USA shale formation. Results: We collected materials used during the hydraulic fracturing process (i.e., chemicals, drill muds) paired with temporal sampling of water produced from three different hydraulically fractured wells in the STACK (Sooner Trend Anadarko Basin, Canadian and Kingfisher) shale play in OK, USA. Relative to other shale formations, our metagenomic and metabolomic analyses revealed an expanded taxonomic and metabolic diversity of microorganisms that colonize and persist in fractured shales. Importantly, temporal sampling across all three hydraulic fracturing wells traced the degradation of complex polymers from the hydraulic fracturing process to the production and consumption of organic acids that support sulfate- and thiosulfate-reducing bacteria. Furthermore, we identified 5587 viral genomes and linked many of these to the dominant, colonizing microorganisms, demonstrating the key role that viral predation plays in community dynamics within this closed, engineered system. Lastly, top-side audit sampling of different source materials enabled genome-resolved source tracking, revealing the likely sources of many key colonizing and persisting taxa in these ecosystems. Conclusions: These findings highlight the importance of resource utilization and resistance to viral predation as key traits that enable specific microbial taxa to persist across fractured shale ecosystems. We also demonstrate the importance of materials used in the hydraulic fracturing process as both a source of persisting shale microorganisms and organic substrates that likely aid in sustaining the microbial community. Moreover, we showed that different physicochemical conditions (i.e., salinity, temperature) can influence the composition and functional potential of persisting microbial communities in shale ecosystems. Together, these results expand our knowledge of microbial life in deep subsurface shales and have important ramifications for management and treatment of microbial biomass in hydraulically fractured wells.
Abstract Background Biofilms in sulfide-rich springs present intricate microbial communities that play pivotal roles in biogeochemical cycling. We studied chemoautotrophically based biofilms that host diverse CPR bacteria and grow in sulfide-rich springs to investigate microbial controls on biogeochemical cycling. Results Sulfide springs biofilms were investigated using bulk geochemical analysis, genome-resolved metagenomics, and scanning transmission X-ray microscopy (STXM) at room temperature and 87 K. Chemolithotrophic sulfur-oxidizing bacteria, including Thiothrix and Beggiatoa , dominate the biofilms, which also contain CPR Gracilibacteria, Absconditabacteria, Saccharibacteria, Peregrinibacteria, Berkelbacteria, Microgenomates, and Parcubacteria. STXM imaging revealed ultra-small cells near the surfaces of filamentous bacteria that may be CPR bacterial episymbionts. STXM and NEXAFS spectroscopy at carbon K and sulfur L 2,3 edges show that filamentous bacteria contain protein-encapsulated spherical elemental sulfur granules, indicating that they are sulfur oxidizers, likely Thiothrix . Berkelbacteria and Moranbacteria in the same biofilm sample are predicted to have a novel electron bifurcating group 3b [NiFe]-hydrogenase, putatively a sulfhydrogenase, potentially linked to sulfur metabolism via redox cofactors. This complex could potentially contribute to symbioses, for example, with sulfur-oxidizing bacteria such as Thiothrix that is based on cryptic sulfur cycling. One Doudnabacteria genome encodes adjacent sulfur dioxygenase and rhodanese genes that may convert thiosulfate to sulfite. We find similar conserved genomic architecture associated with CPR bacteria from other sulfur-rich subsurface ecosystems. Conclusions Our combined metagenomic, geochemical, spectromicroscopic, and structural bioinformatics analyses of biofilms growing in sulfide-rich springs revealed consortia that contain CPR bacteria and sulfur-oxidizing Proteobacteria, including Thiothrix , and bacteria from a new family within Beggiatoales. We infer roles for CPR bacteria in sulfur and hydrogen cycling.
The nonconventional yeast Issatchenkia orientalis can grow under highly acidic conditions and has been explored for production of various organic acids. However, its broader application is hampered by the lack of efficient genetic tools to enable sophisticated metabolic manipulations. We recently constructed an episomal plasmid based on the autonomously replicating sequence (ARS) from Saccharomyces cerevisiae (ScARS) in I. orientalis and developed a CRISPR/Cas9 system for multiplexed gene deletions. Here we report three additional genetic tools including: (1) identification of a 0.8 kb centromere-like (CEN-L) sequence from the I. orientalis genome by using bioinformatics and functional screening; (2) discovery and characterization of a set of constitutive promoters and terminators under different culture conditions by using RNA-Seq analysis and a fluorescent reporter; and (3) development of a rapid and efficient in vivo DNA assembly method in I. orientalis , which exhibited ~100% fidelity when assembling a 7 kb-plasmid from seven DNA fragments ranging from 0.7 kb to 1.7 kb. As proof of concept, we used these genetic tools to rapidly construct a functional xylose utilization pathway in I. orientalis .
Producing scalable, economically viable, low-carbon biofuels or biochemicals hinges on more efficient bioconversion processes. While microbial conversion can offer robust solutions, the native microbial growth process often redirects a large fraction of carbon to CO 2 and cell mass. By integrating genome-scale metabolic models with techno-economic and life cycle assessment models, this study analyzes the effects of converting cell mass lipids to hydrocarbon fuels, and CO 2 to methanol on the facility’s costs and life-cycle carbon footprint. Results show that upgrading microbial lipids or both microbial lipids and CO 2 using renewable hydrogen produces carbon-negative bisabolene. Additionally, on-site electrolytic hydrogen production offers a supply of pure oxygen to use in place of air for bioconversion and fuel combustion in the boiler. To reach cost parity with conventional jet fuel, renewable hydrogen needs to be produced at less than $\$2.2$ to $\$3.1$/kg, with a bisabolene yield of 80% of the theoretical yield, along with cell mass and CO 2 yields of 22 wt% and 54 wt%, respectively. The economic combination of cell mass, CO 2 , and bisabolene yields demonstrated in this study provides practical insights for prioritizing research, selecting suitable hosts, and determining necessary engineered production levels.