Assessment of ethanol tolerance of Kluyveromyces marxianus CCT 7735 selected by adaptive laboratory evolution.

Kluyveromyces marxianus CCT 7735 shows potential for producing ethanol from lactose; however, its low ethanol tolerance is a drawback for its industrial application. The first aim of this study was to obtain four ethanol-tolerant K. marxianus CCT 7735 strains (ETS1, ETS2, ETS3, and ETS4) by adaptive laboratory evolution. The second aim was to select among them the strain that stood out and to evaluate metabolic changes associated with the improved ethanol tolerance in this strain. The ETS4 was selected for displaying a specific growth rate higher than the parental strain under ethanol stress (122%) and specific ethanol production rate (0.26 g/g/h) higher than those presented by the ETS1 (0.22 g/g/h), ETS2 (0.17 g/g/h), and ETS3 (0.17 g/g/h) under non-stress condition. Further analyses were performed with the ETS4 in comparison with its parental strain in order to characterize metabolic changes. Accumulation of valine and metabolites of the citric acid cycle (isocitric acid, citric acid, and cis-aconitic acid) was observed only in the ETS4 subjected to ethanol stress. Their accumulation in this strain may have been important to increase ethanol tolerance. Furthermore, the contents of fatty acid methyl esters and ergosterol were higher in the ETS4 than in the parental strain. These differences likely contributed to enhance ethanol tolerance in the ETS4. KEY POINTS: • K. marxianus ethanol-tolerant strains were selected by adaptive laboratory evolution. • Valine and metabolites of the TCA cycle were accumulated in the ETS4. • High contents of fatty acids and ergosterol contributed to enhance ethanol tolerance.

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

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.

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

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.

Faster Growth Enhances Low Carbon Fuel and Chemical Production Through Gas Fermentation.

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.

RNA-seq Sample Preparation Kits Strongly Affect Transcriptome Profiles of a Gas-Fermenting Bacterium.

Transcriptome analysis via RNA sequencing (RNA-seq) has become a standard technique employed across various biological fields of study. The rapid adoption of the RNA-seq approach has been mediated, in part, by the development of different commercial RNA-seq library preparation kits compatible with standard next-generation sequencing (NGS) platforms. Generally, the essential steps of library preparation, such as rRNA depletion and first-strand cDNA synthesis, are tailored to a specific group of organisms (e.g., eukaryotes versus prokaryotes) or genomic GC content. Therefore, the selection of appropriate commercial products is of crucial importance to capture the transcriptome of interest as closely to the native state as possible without introduction of technical bias. However, researchers rarely have the resources and time to test various commercial RNA-seq kits for their samples. This work reports a side-by-side comparison of RNA-seq data from Clostridium autoethanogenum obtained using three commercial rRNA removal and strand-specific library construction products of NuGEN Technologies, Qiagen, and Zymo Research and assesses their performance relative to published data. While all three vendors advertise their products as suitable for prokaryotes, we found significant differences in their performance regarding rRNA removal, strand specificity, and most importantly, transcript abundance distribution profiles. Notably, RNA-seq data obtained with Qiagen products were most similar to published data and delivered the best results in terms of library strandedness and transcript abundance distribution range. Our results highlight the importance of finding appropriate organism-specific workflows and library preparation products for RNA-seq studies. IMPORTANCE RNA-seq is a powerful technique for transcriptome profiling while involving elaborate sample processing before library sequencing. We show that RNA-seq library preparation kits can strongly affect the outcome of an RNA-seq experiment. Although library preparation benefits from the availability of various commercial kits, choosing appropriate products for the specific samples can be challenging for new users or for users working with unconventional organisms. Evaluating the performance of different commercial products requires significant financial and time investments infeasible for most researchers. Therefore, users are often guided in their choice of kits by published data involving similar input samples. We conclude that important consideration should be given to selecting sample processing workflows for any given organism.