Biology subjects

de Lima, L. A.

Publications and source records attributed to de Lima, L. A..

3 recordsLinked to original sources

bioRxiv2023

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 {Delta}hp and {Delta}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.

synthetic biology↗

bioRxiv2023

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 already been commercialised. However, most acetogen strains need complex nutrients, display slow growth, and are not robust for routine 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 a minimal medium with one strain, named "LAbrini" (LT1), 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 sporulation-related mutations in 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 to accelerate phenotyping and genetic engineering and to better understand acetogen metabolism, which we named "LAbrini".

bioengineering↗

bioRxiv2022

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. This 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 ribosomal RNA (rRNA) depletion and first-strand cDNA synthesis are tailored to a specific group of organisms (e.g. eukaryotes vs. 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 by 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. ImportanceRNA-seq is a powerful technique for transcriptome profiling while involving elaborate sample processing before library sequencing. Our work is important as we show that RNA-seq library preparation kits can strongly affect the outcome of the 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 investment infeasible to 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 of sample processing workflows for any given organism.

systems biology↗