Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Autotrophic adaptive laboratory evolution of the acetogen Clostridium autoethanogenum delivers the gas-fermenting strain LAbrini with superior growth, products, and robustness

ABSTRACT: Microbes able to convert gaseous one-carbon (C1) waste feedstocks are increasingly important to transition to the sustainable production of renewable chemicals and fuels. Acetogens are interesting biocatalysts since gas fermentation using Clostridium autoethanogenum has been commercialised. However, most acetogen strains need complex nutrients, display slow growth, and are not robust for bioreactor fermentations. In this work, we used three different and independent adaptive laboratory evolution (ALE) strategies to evolve the wild-type C. autoethanogenum to grow faster, without yeast extract and to be robust in operating continuous bioreactor cultures. Multiple evolved strains with improved phenotypes were isolated on minimal media with one strain, named “LAbrini”, exhibiting superior performance regarding the maximum specific growth rate, product profile, and robustness in continuous cultures. Whole-genome sequencing of the evolved strains identified 25 mutations. Of particular interest are two genes that acquired seven different mutations across the three ALE strategies, potentially as a result of convergent evolution. Reverse genetic engineering of mutations in potentially sporulation-related genes CLAU_3129 (spo0A) and CLAU_1957 recovered all three superior features of our ALE strains through triggering significant proteomic rearrangements. This work provides a robust C. autoethanogenum strain “LAbrini” to accelerate phenotyping and genetic engineering and to better understand acetogen metabolism.

ORGANISM(S): Clostridium autoethanogenum

PROVIDER: GSE225123 | GEO | 2024/06/12

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Autotrophic adaptive laboratory evolution of the acetogen Clostridium autoethanogenum delivers the gas-fermenting strain LAbrini with superior growth, products, and robustness

Project description:Microbes able to convert gaseous one-carbon (C1) waste feedstocks are increasingly important to transition to the sustainable production of renewable chemicals and fuels. Acetogens are interesting biocatalysts since gas fermentation using Clostridium autoethanogenum has been commercialised. However, most acetogen strains need complex nutrients, display slow growth, and are not robust for bioreactor fermentations. In this work, we used three different and independent adaptive laboratory evolution (ALE) strategies to evolve the wild-type C. autoethanogenum to grow faster, without yeast extract and to be robust in operating continuous bioreactor cultures. Multiple evolved strains with improved phenotypes were isolated on minimal media with one strain, named “LAbrini”, exhibiting superior performance regarding the maximum specific growth rate, product profile, and robustness in continuous cultures. Whole-genome sequencing of the evolved strains identified 25 mutations. Of particular interest are two genes that acquired seven different mutations across the three ALE strategies, potentially as a result of convergent evolution. Reverse genetic engineering of mutations in potentially sporulation-related genes CLAU_3129 (spo0A) and CLAU_1957 recovered all three superior features of our ALE strains through triggering significant proteomic rearrangements. This work provides a robust C. autoethanogenum strain “LAbrini” to accelerate phenotyping and genetic engineering and to better understand acetogen metabolism.

2024-06-12 | PXD047330 | Pride

Adaptive laboratory evolution of Clostridium autoethanogenum to metabolize CO2 and H2 enhances growth rates in chemostat and unravels proteome and metabolome alterations

Project description:Gas fermentation of CO₂ and H₂ is an attractive means to sustainably produce fuels and chemicals. Clostridium autoethanogenum is a model organism for industrial CO-to-ethanol and presents an opportunity for CO₂-to-ethanol processes. As we have previously characterized its CO₂/H₂ chemostat growth, here we use adaptive laboratory evolution (ALE) with the aim of improving growth with CO₂/H₂. Seven ALE lineages were generated, all with improved specific growth rates. Developed with 2% CO supplementation of CO₂/H₂, Evolved lineage D has the highest ethanol/acetate of ALE lineages when fermenting CO₂/H₂. Chemostat comparison against the parental strain shows no change in acetate or ethanol production, while Evolved D could achieve a higher maximum dilution rate. Complete multi-omics analyses at steady-state revealed that although Evolved D has widespread proteome changes, intracellular metabolites prevent phenotype shifts. Yet, we observe numerous insights to CO₂/H₂ metabolism via these multi-omics results and link these to mutations, suggesting novel targets for metabolic engineering.

2024-05-09 | PXD048075 | Pride

Adaptive laboratory evolution of Clostridium autoethanogenum to metabolize CO2 and H2 enhances growth rates in chemostat and unravels proteome and metabolome alterations

2024-05-09 | PXD048143 | Pride

Gas-fermenting acetogens regulate their metabolism to maintain ATP homeostasis

Project description:Acetogens are promising cell factories for producing fuels and chemicals from waste feedstocks via gas fermentation, but quantitative characterization of carbon, energy, and redox metabolism is required to guide their rational metabolic engineering. Here, we explore acetogen gas fermentation using physiological, metabolomics, and transcriptomics data for Clostridium autoethanogenum steady-state chemostat cultures grown on syngas at various gas-liquid mass transfer rates. We observe that C. autoethanogenum shifts from acetate to ethanol production to maintain ATP homeostasis at higher biomass concentrations but reaches a limit at a molar acetate/ethanol ratio of ∼1. This regulatory mechanism eventually leads to depletion of the intracellular acetyl-CoA pool and collapse of metabolism. We accurately predict growth phenotypes using a genome-scale metabolic model. Modeling revealed that the methylene-THF reductase reaction was ferredoxin reducing. This work provides a reference dataset to advance the understanding and engineering of arguably the first carbon fixation pathway on Earth.

2017-05-22 | GSE90792 | GEO

Deletion of genes linked to the C1-fixing gene cluster affects growth, by-products, and proteome of Clostridium autoethanogenum

Project description:Gas fermentation has emerged as a sustainable route to produce fuels and chemicals by recycling inexpensive one-carbon (C1) feedstocks from gaseous and solid waste using gas-fermenting microbes. Currently, acetogens that utilise the Wood-Ljungdahl pathway to convert carbon oxides (CO and CO2) into valuable products are the most advanced biocatalysts for gas fermentation. However, our understanding of the functionalities of the genes involved in the C1-fixing gene cluster and its closely-linked genes is incomplete. Here, we investigate the role of two genes with unclear functions – hypothetical protein (hp; LABRINI_07945) and CooT nickel binding protein (nbp; LABRINI_07950) – directly adjacent and expressed at similar levels to the C1-fixing gene cluster in the gas-fermenting model-acetogen Clostridium autoethanogenum. Targeted deletion of either the hp or nbp gene using CRISPR/nCas9, and phenotypic characterisation in heterotrophic and autotrophic batch and autotrophic bioreactor continuous cultures revealed significant growth defects and altered by-product profiles for both ∆hp and ∆nbp strains. Variable effects of gene deletion on autotrophic batch growth on rich or minimal media suggest that both genes affect the utilisation of complex nutrients. Autotrophic chemostat cultures showed lower acetate and ethanol production rates and higher carbon flux to CO2 and biomass for both deletion strains. Additionally, proteome analysis revealed that disruption of either gene affects the expression of proteins of the C1-fixing gene cluster and ethanol synthesis pathways. Our work contributes to a better understanding of genotype-phenotype relationships in acetogens and offers engineering targets to improve carbon fixation efficiency in gas fermentation.

2023-05-10 | PXD040151 | Pride

Faster growth enhances low carbon fuels and commodity chemcial production through gas fermentation

Project description:Gas fermentation offers both fossil carbon-free sustainable production of fuels and chemicals and recycling of gaseous and solid waste using gas-fermenting microbes. Bioprocess development, systems-level analysis of biocatalyst metabolism, and engineering of cell factories are advancing the widespread deployment of the commercialised technology. Acetogens are particularly attractive biocatalysts but effects of the key physiological parameter – specific growth rate (μ) – on acetogen metabolism and the gas fermentation bioprocess have not been established yet. Here, we investigate the μ-dependent bioprocess performance of the model-acetogen Clostridium autoethanogenum in CO and syngas (CO+CO2+H2) grown chemostat cultures and assess systems-level metabolic responses using gas analysis, metabolomics, transcriptomics, and metabolic modelling. We were able to obtain steady-states up to μ ~2.8 day-1 (~0.12 h-1) and show that faster growth supports both higher yields and productivities for reduced by-products ethanol and 2,3-butanediol. Transcriptomics data revealed differential expression of 1,337 genes with increasing μ and suggest that C. autoethanogenum uses transcriptional regulation to a large extent for facilitating faster growth. Metabolic modelling showed significantly increased fluxes for faster growing cells that were, however, not accompanied by gene expression changes in key catabolic pathways for CO and H2 metabolism. Cells thus seem to maintain sufficient “baseline” gene expression to rapidly respond to CO and H2 availability without delays to kick-start metabolism. Our work advances understanding of transcriptional regulation in acetogens and shows that faster growth of the biocatalyst improves the gas fermentation bioprocess.

2022-04-12 | GSE196640 | GEO

Escherichia coli strain:BW25113

Project description:Genome sequencing data of evolved strains from ALE experiments

| PRJDB6152 | ENA

Absolute proteome quantification in the gas-fermenting acetogen Clostridium autoethanogenum

Project description:Microbes that can recycle one-carbon (C1) greenhouse gases into fuels and chemicals are vital for the biosustainability of future industries. Acetogens are the most efficient known microbes for fixing carbon oxides CO2 and CO. Understanding proteome allocation is important for metabolic engineering as it dictates metabolic fitness. Here, we use absolute proteomics to quantify intracellular concentrations for >1,000 proteins in the model-acetogen Clostridium autoethanogenum grown on three gas mixtures. We detect prioritisation of proteome allocation for C1 fixation and significant expression of proteins involved in the production of acetate and ethanol as well as proteins with unclear functions. The data also revealed which isoenzymes are important. Integration of proteomic and metabolic flux data demonstrated that enzymes catalyse high fluxes with high concentrations and high in vivo catalytic rates. We show that flux throughput was dominantly controlled through enzyme catalytic rates rather than concentrations. Our work serves as a reference dataset and advances systems-level understanding and engineering of acetogens.

2022-05-22 | PXD025732 | Pride

A TetR-Family Protein (CAETHG_0459) Activates Transcription From a New Promoter Motif Associated With Essential Genes for Autotrophic Growth in Acetogens

Project description:Acetogens can fix carbon (CO or CO2) into acetyl-CoA via the Wood–Ljungdahl pathway (WLP) that also makes them attractive cell factories for the production of fuels and chemicals from waste feedstocks. Although most biochemical details of the WLP are well understood and systems-level characterization of acetogen metabolism has recently improved, key transcriptional features such as promoter motifs and transcriptional regulators are still unknown in acetogens. Here, we use differential RNA-sequencing to identify a previously undescribed promoter motif associated with essential genes for autotrophic growth of the model-acetogen Clostridium autoethanogenum. RNA polymerase was shown to bind to the new promoter motif using a DNA-binding protein assay and proteomics enabled the discovery of four candidates to potentially function directly in control of transcription of the WLP and other key genes of C1 fixation metabolism. Next, in vivo experiments showed that a TetR-family transcriptional regulator (CAETHG_0459) and the housekeeping sigma factor (sA) activate expression of a reporter protein (GFP) in-frame with the new promoter motif from a fusion vector in Escherichia coli. Lastly, a protein–protein interaction assay with the RNA polymerase (RNAP) shows that CAETHG_0459 directly binds to the RNAP. Together, the data presented here advance the fundamental understanding of transcriptional regulation of C1 fixation in acetogens and provide a strategy for improving the performance of gas-fermenting bacteria by genetic engineering.

2019-10-28 | GSE108700 | GEO

Metabolomic study of Escherichia coli K-12 MG1655 and mutants

Project description:Metabolomic analysis of Wildtype, crp mutant and its five adaptively evolved populations evolved in glucose minimal media with 40 mM MOPS during its exponential phase of growth. Three biological and two technical replicate samples (n=6) were harvested for each of the strains while growing in a bioreactor aerobically at 37 degree Celsius and 700 rpm. This study aims to characterize and compare the metabolic profile of all these strains.

2020-06-06 | ST001394 | MetabolomicsWorkbench

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data