Transcriptomic studies of solventogenic clostridia, Clostridium acetobutylicum and Clostridium beijerinckii

Patáková, Petra; Branská, Barbora; Vasylkivska, Maryna; Jureckova, Katerina; Musilová, Jana; Provazník, Ivo; Sedlář, Karel

doi:10.1016/j.biotechadv.2021.107889

Cited by 13 publications

(10 citation statements)

References 197 publications

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“…In order to gain a better understanding and interpretation of the observed metabolic profiles, several omics technologies could be employed. For instance, transcriptomics techniques such as RT-qPCR or RNA-Seq [ 70 ] could be utilized to monitor the transcription levels of key genes involved in glycerol metabolism, including dhaB1 , dhaB2 , dhaT , dhaD , and dhaK . By comparing the parent strain with the transformed strain, this approach could enable the quantification of the fold increase in expression levels and variations in expression over time.…”

Section: Discussionmentioning

confidence: 99%

Enhancing 1,3-Propanediol Productivity in the Non-Model Chassis Clostridium beijerinckii through Genetic Manipulation

et al. 2023

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Biotechnological processes at biorefineries are considered one of the most attractive alternatives for valorizing biomasses by converting them into bioproducts, biofuels, and bioenergy. For example, biodiesel can be obtained from oils and grease but generates glycerol as a byproduct. Glycerol recycling has been studied in several bioprocesses, with one of them being its conversion to 1,3-propanediol (1,3-PDO) by Clostridium. Clostridium beijerinckii is particularly interesting because it can produce a range of industrially relevant chemicals, including solvents and organic acids, and it is non-pathogenic. However, while Clostridium species have many potential advantages as chassis for synthetic biology applications, there are significant limitations when considering their use, such as their limited genetic tools, slow growth rate, and oxygen sensitivity. In this work, we carried out the overexpression of the genes involved in the synthesis of 1,3-PDO in C. beijerinckii Br21, which allowed us to increase the 1,3-PDO productivity in this strain. Thus, this study contributed to a better understanding of the metabolic pathways of glycerol conversion to 1,3-PDO by a C. beijerinckii isolate. Also, it made it possible to establish a transformation method of a modular vector in this strain, therefore expanding the limited genetic tools available for this bacterium, which is highly relevant in biotechnological applications.

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Section: Discussionmentioning

confidence: 99%

Enhancing 1,3-Propanediol Productivity in the Non-Model Chassis Clostridium beijerinckii through Genetic Manipulation

et al. 2023

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“…Clostridium beijerinckii can use L-rhamnose as the sole carbon source to produce acetic acid, butyric acid [ 32 ], 1,2-propanediol, propionic acid, and n-propanol [ 33 ]. Green macroalgae can be processed into hydrolysates containing D-glucose and L-rhamnose; therefore, they have potential applications as an industrial fermentation strain.…”

Section: Biological Activity and Bioconversion Of Green Macroalgaementioning

confidence: 99%

Utilization of Macroalgae for the Production of Bioactive Compounds and Bioprocesses Using Microbial Biotechnology

Shibasaki

Ueda

2023

Microorganisms

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To achieve sustainable development, alternative resources should replace conventional resources such as fossil fuels. In marine ecosystems, many macroalgae grow faster than terrestrial plants. Macroalgae are roughly classified as green, red, or brown algae based on their photosynthetic pigments. Brown algae are considered to be a source of physiologically active substances such as polyphenols. Furthermore, some macroalgae can capture approximately 10 times more carbon dioxide from the atmosphere than terrestrial plants. Therefore, they have immense potential for use in the environment. Recently, macroalgae have emerged as a biomass feedstock for bioethanol production owing to their low lignin content and applicability to biorefinery processes. Herein, we provided an overview of the bioconversion of macroalgae into bioactive substances and biofuels using microbial biotechnology, including engineered yeast designed using molecular display technology.

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“…To examine sRNAs prediction in a non-model bacterium, we selected C. beijerinckii NRRL B-598, a non-type strain, which is a promising butanol and hydrogen producer. Most importantly, it is a non-type strain with the highest number of RNA-Seq-based transcriptomic studies among solventogenic clostridia [30]. In this study, we used its third complete genome assembly, available at DDBJ/EMBL/GenBank under accession No.…”

Section: Genome and Annotationmentioning

confidence: 99%

Comparison of Stranded and Non-stranded RNA-Seq in Predicting Small RNAs in a Non-model Bacterium

Sedlář

Zimmer

2022

Bioinformatics and Biomedical Engineering

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Thanks to their diversity, non-model bacteria represent an inexhaustible resource for microbial biotechnology. Their utilization is only limited by our lack of knowledge regarding the regulation of processes they are capable to perform. The problem lies in non-coding regulators, for example small RNAs, that are not so widely studied as coding genes. One possibility to overcome this hurdle is to use standard RNA-Seq data, gathered primarily to study gene expression, for the prediction of non-coding elements. Although computational tools to perform this task already exist, they require the utilization of stranded RNA-Seq data that must not be available for non-model organisms. Here, we showed that transencoded small RNAs can be predicted from non-stranded data with comparable sensitivity to stranded data. We used two RNA-Seq datasets of non-type strain Clostridium beijerinckii NRRL B-598, which is a promising hydrogen and butanol producer, and obtained comparable results for stranded and non-stranded datasets. Nevertheless, the non-stranded approach suffered from lower precision. Thus, the results must be interpreted with caution. In general, more benchmarking for tools performing direct prediction of small RNAs from standard RNA-Seq data is needed so these techniques could be adopted for automatic detection.

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Transcriptomic studies of solventogenic clostridia, Clostridium acetobutylicum and Clostridium beijerinckii

Cited by 13 publications

References 197 publications

Enhancing 1,3-Propanediol Productivity in the Non-Model Chassis Clostridium beijerinckii through Genetic Manipulation

Enhancing 1,3-Propanediol Productivity in the Non-Model Chassis Clostridium beijerinckii through Genetic Manipulation

Utilization of Macroalgae for the Production of Bioactive Compounds and Bioprocesses Using Microbial Biotechnology

Comparison of Stranded and Non-stranded RNA-Seq in Predicting Small RNAs in a Non-model Bacterium

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