scholarly journals Metabolic Reconstruction and Modeling Microbial Electrosynthesis

2016 ◽  
Author(s):  
Christopher W. Marshall ◽  
Daniel E. Ross ◽  
Kim M. Handley ◽  
Pamela B. Weisenhorn ◽  
Janaka N. Edirisinghe ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Electron Flow ◽  
Metabolic Model ◽  
Anaerobic Growth ◽  
Metabolic Reconstruction ◽  
Chemical Production ◽  
Community Members ◽  
Microbial Electrosynthesis ◽  
High Performing ◽  
Production Platform

AbstractMicrobial electrosynthesis is a renewable energy and chemical production platform that relies on microbial taxa to capture electrons from a cathode and fix carbon. Yet the metabolic capacity of multispecies microbial communities on electrosynthetic biocathodes remains unknown. We assembled 13 genomes from a high-performing electroacetogenic culture, and mapped their transcriptional activity from a range of conditions. This allowed us to create a metabolic model of the primary community members (Acetobacterium, Sulfurospirillum, and Desulfovibrio). Acetobacterium was the primary carbon fixer, and a keystone member of the community. Based on transcripts upregulated near the electrode surface, soluble hydrogenases and ferredoxins from Acetobacterium and hydrogenases, formate dehydrogenase, and cytochromes of Desulfovibrio were essential conduits for electron flow from the electrode into the electrosynthetic community. A nitrogenase gene cluster with an adjacent ferredoxin and one of two Rnf complexes within the genome of the Acetobacterium were also upregulated on the electrode. Nitrogenase is known to serve as a hydrogenase, thereby it would contribute to hydrogen production by the biocathode. Oxygenases of microaerobic members of the community throughout the cathode chamber, including Sulfurospirillum and Rhodobacteraceae, were expressed. While the reactors were maintained anaerobically, this gene expression would support anaerobic growth and thus electrosynthesis by scrubbing small amounts of O2 out of the reactor. These molecular discoveries and metabolic modeling now serve as a foundation for future examination and development of electrosynthetic microbial communities.

scholarly journals Metagenome-assembled genomes infer potential microbial metabolism in alkaline sulphidic tailings

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Wenjun Li ◽  
Xiaofang Li
Keyword(s):  
Community Structure ◽  
Mine Tailings ◽  
Fluorescent In Situ Hybridization ◽  
High Throughput Sequencing ◽  
Microbial Consortia ◽  
Metabolic Reconstruction ◽  
Metal Release ◽  
Community Members ◽  
Oxidative Stresses

Abstract Background Mine tailings are hostile environment. It has been well documented that several microbes can inhabit such environment, and metagenomic reconstruction has successfully pinpointed their activities and community structure in acidic tailings environments. We still know little about the microbial metabolic capacities of alkaline sulphidic environment where microbial processes are critically important for the revegetation. Microbial communities therein may not only provide soil functions, but also ameliorate the environment stresses for plants’ survival. Results In this study, we detected a considerable amount of viable bacterial and archaeal cells using fluorescent in situ hybridization in alkaline sulphidic tailings from Mt Isa, Queensland. By taking advantage of high-throughput sequencing and up-to-date metagenomic binning technology, we reconstructed the microbial community structure and potential coupled iron and nitrogen metabolism pathways in the tailings. Assembly of 10 metagenome-assembled genomes (MAGs), with 5 nearly complete, was achieved. From this, detailed insights into the community metabolic capabilities was derived. Dominant microbial species were seen to possess powerful resistance systems for osmotic, metal and oxidative stresses. Additionally, these community members had metabolic capabilities for sulphide oxidation, for causing increased salinity and metal release, and for leading to N depletion. Conclusions Here our results show that a considerable amount of microbial cells inhabit the mine tailings, who possess a variety of genes for stress response. Metabolic reconstruction infers that the microbial consortia may actively accelerate the sulphide weathering and N depletion therein.

scholarly journals Lactose-Inducible System for Metabolic Engineering of Clostridium ljungdahlii

2014 ◽  
Vol 80 (8) ◽  
pp. 2410-2416 ◽  
Author(s):  
Areen Banerjee ◽  
Ching Leang ◽  
Toshiyuki Ueki ◽  
Kelly P. Nevin ◽  
Derek R. Lovley
Keyword(s):  
Ethanol Production ◽  
Genetic Manipulation ◽  
Electron Flow ◽  
Model Organism ◽  
Inducible Expression ◽  
Carbon Flow ◽  
Wild Type ◽  
Content Type ◽  
Microbial Electrosynthesis ◽  
Clostridium Ljungdahlii

ABSTRACTThe development of tools for genetic manipulation ofClostridium ljungdahliihas increased its attractiveness as a chassis for autotrophic production of organic commodities and biofuels from syngas and microbial electrosynthesis and established it as a model organism for the study of the basic physiology of acetogenesis. In an attempt to expand the genetic toolbox forC. ljungdahlii, the possibility of adapting a lactose-inducible system for gene expression, previously reported forClostridium perfringens, was investigated. The plasmid pAH2, originally developed forC. perfringenswith agusAreporter gene, functioned as an effective lactose-inducible system inC. ljungdahlii. Lactose induction ofC. ljungdahliicontaining pB1, in which the gene for the aldehyde/alcohol dehydrogenase AdhE1 was downstream of the lactose-inducible promoter, increased expression ofadhE130-fold over the wild-type level, increasing ethanol production 1.5-fold, with a corresponding decrease in acetate production. Lactose-inducible expression ofadhE1in a strain in whichadhE1and theadhE1homologadhE2had been deleted from the chromosome restored ethanol production to levels comparable to those in the wild-type strain. Inducing expression ofadhE2similarly failed to restore ethanol production, suggesting thatadhE1is the homolog responsible for ethanol production. Lactose-inducible expression of the four heterologous genes necessary to convert acetyl coenzyme A (acetyl-CoA) to acetone diverted ca. 60% of carbon flow to acetone production during growth on fructose, and 25% of carbon flow went to acetone when carbon monoxide was the electron donor. These studies demonstrate that the lactose-inducible system described here will be useful for redirecting carbon and electron flow for the biosynthesis of products more valuable than acetate. Furthermore, this tool should aid in optimizing microbial electrosynthesis and for basic studies on the physiology of acetogenesis.

Variations of electron flux and microbial community in air-cathode microbial fuel cells fed with different substrates

2012 ◽  
Vol 66 (4) ◽  
pp. 748-753 ◽  
Author(s):  
Jaecheul Yu ◽  
Younghyun Park ◽  
Haein Cho ◽  
Jieun Chun ◽  
Jiyun Seon ◽  
...  
Keyword(s):  
Fuel Cells ◽  
Microbial Communities ◽  
Microbial Fuel Cells ◽  
Electricity Generation ◽  
Electron Flow ◽  
Batch Mode ◽  
Electrochemically Active ◽  
Oxidation Of Organic Compounds ◽  
Current Production ◽  
Electron Sink

Microbial fuel cells (MFCs) can convert chemical energy to electricity using microbes as catalysts and a variety of organic wastewaters as substrates. However, electron loss occurs when fermentable substrates are used because fermentation bacteria and methanogens are involved in electron flow from the substrates to electricity. In this study, MFCs using glucose (G-MFC), propionate (P-MFC), butyrate (B-MFC), acetate (A-MFC), and a mix (M-MFC, glucose:propionate:butyrate:acetate = 1:1:1:1) were operated in batch mode. The metabolites and microbial communities were analyzed. The current was the largest electron sink in M-, G-, B-, and A-MFCs; the initial chemical oxygen demands (CODini) involved in current production were 60.1% for M-MFC, 52.7% for G-MFC, 56.1% for B-MFC, and 68.3% for A-MFC. Most of the glucose was converted to propionate (40.6% of CODini) and acetate (21.4% of CODini) through lactate (80.3% of CODini) and butyrate (6.1% of CODini). However, an unknown source (62.0% of CODini) and the current (34.5% of CODini) were the largest and second-largest electron sinks in P-MFC. Methane gas was only detected at levels of more than 10% in G- and M-MFCs, meaning that electrochemically active bacteria (EAB) could out-compete acetoclastic methanogens. The microbial communities were different for fermentable and non-fermentable substrate-fed MFCs. Probably, bacteria related to Lactococcus spp. found in G-MFCs with fermentable substrates would be involved in both fermentation and electricity generation. Acinetobacter-like species, and Rhodobacter-like species detected in all the MFCs would be involved in oxidation of organic compounds and electricity generation.

scholarly journals Spatially-resolved correlative microscopy and microbial identification reveals dynamic depth- and mineral-dependent anabolic activity in salt marsh sediment

2020 ◽  
Author(s):  
Jeffrey Marlow ◽  
Rachel Spietz ◽  
Keun-Young Kim ◽  
Mark Ellisman ◽  
Peter Girguis ◽  
...  
Keyword(s):  
Salt Marsh ◽  
Microbial Communities ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Community Members ◽  
Marsh Sediment ◽  
Anabolic Activity ◽  
Salt Marsh Sediment ◽  
Rrna Gene Sequencing ◽  
And Function

AbstractCoastal salt marshes are key sites of biogeochemical cycling and ideal systems in which to investigate the community structure of complex microbial communities. Here, we clarify structural-functional relationships among microorganisms and their mineralogical environment, revealing previously undescribed metabolic activity patterns and precise spatial arrangements within salt marsh sediment. Following 3.7-day in situ incubations with a non-canonical amino acid that was incorporated into new biomass, samples were embedded and analyzed by correlative fluorescence and electron microscopy to map the microscale arrangements of anabolically active and inactive organisms alongside mineral grains. Parallel sediment samples were examined by fluorescence-activated cell sorting and 16S rRNA gene sequencing to link anabolic activity to taxonomic identity. Both approaches demonstrated a rapid decline in the proportion of anabolically active cells with depth into salt marsh sediment, from ∼60% in the top cm to 10-25% between 2-7 cm. From the top to the bottom, the most prominent active community members shifted from sulfur cycling phototrophic consortia, to sulfate-reducing bacteria likely oxidizing organic compounds, to fermentative lineages. Correlative microscopy revealed more abundant (and more anabolically active) organisms around non-quartz minerals including rutile, orthoclase, and plagioclase. Microbe-mineral relationships appear to be dynamic and context-dependent arbiters of biogeochemical cycling.Statement of SignificanceMicroscale spatial relationships dictate critical aspects of a microbiome’s inner workings and emergent properties, such as evolutionary pathways, niche development, and community structure and function. However, many commonly used methods in microbial ecology neglect this parameter – obscuring important microbe-microbe and microbe-mineral interactions – and instead employ bulk-scale methodologies that are incapable of resolving these intricate relationships.This benchmark study presents a compelling new approach for exploring the anabolic activity of a complex microbial community by mapping the precise spatial configuration of anabolically active organisms within mineralogically heterogeneous sediment through in situ incubation, resin embedding, and correlative fluorescence and electron microscopy. In parallel, active organisms were identified through fluorescence-activated cell sorting and 16S rRNA gene sequencing, enabling a powerful interpretive framework connecting location, identity, activity, and putative biogeochemical roles of microbial community members.We deploy this novel approach in salt marsh sediment, revealing quantitative insights into the fundamental principles that govern the structure and function of sediment-hosted microbial communities. In particular, at different sediment horizons, we observed striking changes in the proportion of anabolically active cells, the identities of the most prominent active community members, and the nature of microbe-mineral affiliations. Improved approaches for understanding microscale ecosystems in a new light, such as those presented here, reveal environmental parameters that promote or constrain metabolic activity and clarify the impact that microbial communities have on our world.

In Situ Gene Expression in Mixed-Culture Biofilms: Evidence of Metabolic Interactions between Community Members

1998 ◽  
Vol 64 (2) ◽  
pp. 721-732 ◽  
Author(s):  
Søren Møller ◽  
Claus Sternberg ◽  
Jens Bo Andersen ◽  
Bjarke Bak Christensen ◽  
Juan Luis Ramos ◽  
...  
Keyword(s):  
Gene Expression ◽  
Microbial Communities ◽  
Pure Culture ◽  
Fluorescent Protein ◽  
Confocal Laser ◽  
Specific Gene ◽  
Community Members ◽  
Metabolic Interactions ◽  
Green Fluorescent

ABSTRACT Microbial communities growing in laboratory-based flow chambers were investigated in order to study compartmentalization of specific gene expression. Among the community members studied, the focus was in particular on Pseudomonas putida and a strain of anAcinetobacter sp., and the genes studied are involved in the biodegradation of toluene and related aromatic compounds. The upper-pathway promoter (Pu) and themeta-pathway promoter (Pm) from the TOL plasmid were fused independently to the gene coding for the green fluorescent protein (GFP), and expression from these promoters was studied inP. putida, which was a dominant community member. Biofilms were cultured in flow chambers, which in combination with scanning confocal laser microscopy allowed direct monitoring of promoter activity with single-cell spatial resolution. Expression from thePu promoter was homogeneously induced by benzyl alcohol in both community and pure-culture biofilms, while the Pmpromoter was induced in the mixed community but not in a pure-culture biofilm. By sequentially adding community members, induction ofPm was shown to be a consequence of direct metabolic interactions between an Acinetobacter species and P. putida. Furthermore, in fixed biofilm samples organism identity was determined and gene expression was visualized at the same time by combining GFP expression with in situ hybridization with fluorescence-labeled 16S rRNA targeting probes. This combination of techniques is a powerful approach for investigating structure-function relationships in microbial communities.

scholarly journals A metabolic reconstruction of Lactobacillus reuteri JCM 1112 and analysis of its potential as a cell factory

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Thordis Kristjansdottir ◽  
Elleke F. Bosma ◽  
Filipe Branco dos Santos ◽  
Emre Özdemir ◽  
Markus J. Herrgård ◽  
...  
Keyword(s):  
Experimental Data ◽  
Metabolic Engineering ◽  
Growth Rates ◽  
Lactobacillus Reuteri ◽  
Metabolic Model ◽  
Metabolic Reconstruction ◽  
Cell Factory ◽  
A Genome ◽  
A Cell ◽  
Genome Scale

Abstract Background Lactobacillus reuteri is a heterofermentative Lactic Acid Bacterium (LAB) that is commonly used for food fermentations and probiotic purposes. Due to its robust properties, it is also increasingly considered for use as a cell factory. It produces several industrially important compounds such as 1,3-propanediol and reuterin natively, but for cell factory purposes, developing improved strategies for engineering and fermentation optimization is crucial. Genome-scale metabolic models can be highly beneficial in guiding rational metabolic engineering. Reconstructing a reliable and a quantitatively accurate metabolic model requires extensive manual curation and incorporation of experimental data. Results A genome-scale metabolic model of L. reuteri JCM 1112T was reconstructed and the resulting model, Lreuteri_530, was validated and tested with experimental data. Several knowledge gaps in the metabolism were identified and resolved during this process, including presence/absence of glycolytic genes. Flux distribution between the two glycolytic pathways, the phosphoketolase and Embden–Meyerhof–Parnas pathways, varies considerably between LAB species and strains. As these pathways result in different energy yields, it is important to include strain-specific utilization of these pathways in the model. We determined experimentally that the Embden–Meyerhof–Parnas pathway carried at most 7% of the total glycolytic flux. Predicted growth rates from Lreuteri_530 were in good agreement with experimentally determined values. To further validate the prediction accuracy of Lreuteri_530, the predicted effects of glycerol addition and adhE gene knock-out, which results in impaired ethanol production, were compared to in vivo data. Examination of both growth rates and uptake- and secretion rates of the main metabolites in central metabolism demonstrated that the model was able to accurately predict the experimentally observed effects. Lastly, the potential of L. reuteri as a cell factory was investigated, resulting in a number of general metabolic engineering strategies. Conclusion We have constructed a manually curated genome-scale metabolic model of L. reuteri JCM 1112T that has been experimentally parameterized and validated and can accurately predict metabolic behavior of this important platform cell factory.

scholarly journals Impacts of Maize Domestication and Breeding on Rhizosphere Microbial Community Recruitment from a Nutrient Depleted Agricultural Soil

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Vanessa L. Brisson ◽  
Jennifer E. Schmidt ◽  
Trent R. Northen ◽  
John P. Vogel ◽  
Amélie C. M. Gaudin
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Composition ◽  
Microbial Community Composition ◽  
Microbial Community Analysis ◽  
Agricultural System ◽  
Community Members ◽  
Genetic Groups ◽  
Maize Domestication ◽  
Rhizosphere Microbial Community

Abstract Maize domestication and breeding have resulted in drastic and well documented changes in aboveground traits, but belowground effects on root system functioning and rhizosphere microbial communities remain poorly understood, despite their critical importance for nutrient and water acquisition. We investigated the rhizosphere microbial community composition and structure of ten Zea mays accessions along an evolutionary transect (two teosinte, three inbred maize lines, and five modern maize hybrids) grown in nutrient depleted soil from a low input agricultural system. Microbial community analysis revealed significant differences in community composition between soil compartments (proximal vs. distal rhizosphere) and between plant genetic groups (teosinte, inbred, and modern hybrid). Only a small portion of the microbial community was differentially selected across plant genetic groups: 3.7% of prokaryotic community members and 4.9% of fungal community members were significantly associated with a specific plant genetic group. Indicator species analysis showed the greatest differentiation between modern hybrids and the other two plant genetic groups. Co-occurrence network analysis revealed that microbial co-occurrence patterns of the inbred maize lines’ rhizosphere were significantly more similar to those of the teosintes than to the modern hybrids. Our results suggest that advances in hybrid development significantly impacted rhizosphere microbial communities and network assembly.

scholarly journals A Genome-Scale Metabolic Model of Thalassiosira pseudonana CCMP 1335 for a Systems-Level Understanding of Its Metabolism and Biotechnological Potential

2020 ◽  
Vol 8 (9) ◽  
pp. 1396
Author(s):  
Ahmad Ahmad ◽  
Archana Tiwari ◽  
Shireesh Srivastava
Keyword(s):  
Carbon Fixation ◽  
Electron Flow ◽  
Single Gene ◽  
Metabolic Model ◽  
Thalassiosira Pseudonana ◽  
Marine Diatom ◽  
Omega 3 ◽  
Biotechnological Potential ◽  
A Genome ◽  
Genome Scale

Thalassiosira pseudonana is a transformable and biotechnologically promising model diatom with an ability to synthesise nutraceuticals such as fucoxanthin and store a significant amount of polyglucans and lipids including omega-3 fatty acids. While it was the first diatom to be sequenced, a systems-level analysis of its metabolism has not been done yet. This work presents first comprehensive, compartmentalized, and functional genome-scale metabolic model of the marine diatom Thalassiosira pseudonana CCMP 1335, which we have termed iThaps987. The model includes 987 genes, 2477 reactions, and 2456 metabolites. Comparison with the model of another diatom Phaeodactylum tricornutum revealed presence of 183 unique enzymes (belonging primarily to amino acid, carbohydrate, and lipid metabolism) in iThaps987. Model simulations showed a typical C3-type photosynthetic carbon fixation and suggested a preference of violaxanthin–diadinoxanthin pathway over violaxanthin–neoxanthin pathway for the production of fucoxanthin. Linear electron flow was found be active and cyclic electron flow was inactive under normal phototrophic conditions (unlike green algae and plants), validating the model predictions with previous reports. Investigation of the model for the potential of Thalassiosira pseudonana CCMP 1335 to produce other industrially useful compounds suggest iso-butanol as a foreign compound that can be synthesized by a single-gene addition. This work provides novel insights about the metabolism and potential of the organism and will be helpful to further investigate its metabolism and devise metabolic engineering strategies for the production of various compounds.

scholarly journals Genome Scale Constraint-Based Metabolic Reconstruction of Propionibacterium Freudenreichii DSM 20271

2021 ◽  
Author(s):  
Mahsa Sadat Razavi Borghei ◽  
Meysam Mobasheri ◽  
Tabassom Sobati
Keyword(s):  
Metabolic Networks ◽  
Metabolic Model ◽  
Physiological Data ◽  
Metabolic Reconstruction ◽  
Modeling And Analysis ◽  
Microbial Cell Factories ◽  
Culture Optimization ◽  
Cell Factories ◽  
Functional Features ◽  
Genome Scale

Abstract Propionibacterium is an anaerobic bacterium with a history of use in the production of Swiss cheese and, more recently, several industrial bioproducts. While the use of this strain for the production of organic acids and secondary metabolites has gained growing interest, the industrial application of the strain requires further improvement in the yield and productivity of the target products. Systems modeling and analysis of metabolic networks are widely leveraged to gain holistic insights into the metabolic features of biotechnologically important strains and to devise metabolic engineering and culture optimization strategies for economically viable bioprocess development. In the present study, a high-quality genome-scale metabolic model of P. freudenreichii ssp. freudenreichii strain DSM 20271 was developed based on the strain’s genome annotation and biochemical and physiological data. The model covers the functions of 23% of the strain’s ORFs and accounts for 711 metabolic reactions and 647 unique metabolites. Literature-based reconstruction of the central metabolism and rigorous refinement of annotation data for establishing gene-protein-reaction associations renders the model a curated omic-scale knowledge base of the organism. Validation of the model against experimental data indicates that the reconstruction can capture the key structural and functional features of P. freudenreichii metabolism, including the growth rate, the pattern of flux distribution, the strain’s aerotolerance behavior, and the change in the mode of metabolic activity during the transition from an anaerobic to an aerobic growth regime. The model also includes an accurately curated pathway of cobalamin biosynthesis, which was used to examine the capacity of the strain to produce vitamin B12 precursors. Constraint-based reconstruction and analysis of the P. freudenreichii metabolic network also provided novel insights into the complexity and robustness of P. freudenreichii energy metabolism. The developed reconstruction, hence, may be used as a platform for the development of P. freudenreichii-based microbial cell factories and bioprocesses.

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