Biology subjects

Winzer, K.

Publications and source records attributed to Winzer, K..

4 recordsLinked to original sources

bioRxiv2021

Application of transposon-insertion sequencing to determine gene essentiality in the acetogen Clostridium autoethanogenum

The majority of the genes present in bacterial genomes remain poorly characterised with up to one third of those that are protein encoding having no definitive function. Transposon insertion sequencing represents a high-throughput technique that can help rectify this deficiency. The technology, however, can only be realistically applied to easily transformable species leaving those with low DNA-transfer rates out of reach. Here we have developed a number of approaches that overcome this barrier in the autotrophic species Clostridium autoethanogenum using a mariner-based transposon system. The inherent instability of such systems in the Escherichia coli conjugation donor due to transposition events was counteracted through the incorporation of a conditionally lethal codA marker on the plasmid backbone. Relatively low frequencies of transformation of the plasmid into C. autoethanogenum were circumvented through the use of a plasmid that is conditional for replication coupled with the routine implementation of an Illumina library preparation protocol that eliminates plasmid-based reads. A transposon library was then used to determine the essential genes needed for growth using carbon monoxide as a sole carbon and energy source. IMPORTANCEAlthough microbial genome sequences are relatively easily determined, assigning gene function remains a bottleneck. Consequently, relatively few genes are well characterised, leaving the function of many as either hypothetical or entirely unknown. High-throughput, transposon sequencing can help remedy this deficiency, but is generally only applicable to microbes with efficient DNA-transfer procedures. These exclude many microorganisms of importance to humankind either as agents of disease or as industrial process organisms. Here we developed approaches to facilitate transposon-insertion sequencing in the acetogen Clostridium autoethanogenum, a chassis being exploited to convert single-carbon waste gases, CO and CO2, into chemicals and fuels at an industrial scale. This allowed the determination of gene essentiality under heterotrophic and autotrophic growth providing insights into the utilisation of CO as a sole carbon and energy source. The strategies implemented are translatable and will allow others to apply transposon-insertion sequencing to other microbes where DNA-transfer has until now represented a barrier to progress.

molecular biology↗

bioRxiv2020

Assessing the impact of physicochemical parameters in the predictive capabilities of thermodynamics-based stoichiometric approaches under mesophilic and thermophilic conditions

Metabolic engineering in the post-genomic era is characterised by the development of new methods for metabolomics and fluxomics, supported by the integration of genetic engineering tools and mathematical modelling. Particularly, constraint-based stoichiometric models have been widely studied: (i) flux balance analysis (FBA) (in silico), and (ii) metabolic flux analysis (MFA) (in vivo). Recent studies have enabled the incorporation of thermodynamics and metabolomics data to improve the predictive capabilities of these approaches. However, an in-depth comparison and evaluation of these methods is lacking. This study presents a thorough analysis of two different in silico methods tested against experimental data (metabolomics and 13C-MFA) for the mesophile Escherichia coli. In particular, a modified version of the recently published matTFA toolbox was created, providing a broader range of physicochemical parameters. Validating against experimental data allowed the determination of the best physicochemical parameters to perform the TFA (Thermodynamics-based Flux Analysis). An analysis of flux pattern changes in the central carbon metabolism between 13C-MFA and TFA highlighted the limited capabilities of both approaches for elucidating the anaplerotic fluxes. In addition, a method based on centrality measures was suggested to identify important metabolites that (if quantified) would allow to further constrain the TFA. Finally, this study emphasised the need for standardisation in the fluxomics community: novel approaches are frequently released but a thorough comparison with currently accepted methods is not always performed. Author summaryBiotechnology has benefitted from the development of high throughput methods characterising living systems at different levels (e.g. concerning genes or proteins), allowing the industrial production of chemical commodities. Recently, focus has been placed on determining reaction rates (or metabolic fluxes) in the metabolic network of certain microorganisms, in order to identify bottlenecks hindering their exploitation. Two main approaches are commonly used, termed metabolic flux analysis (MFA) and flux balance analysis (FBA), based on measuring and estimating fluxes, respectively. While the influence of thermodynamics in living systems was accepted several decades ago, its application to study biochemical networks has only recently been enabled. In this sense, a multitude of different approaches constraining well-established modelling methods with thermodynamics has been suggested. However, physicochemical parameters are generally not properly adjusted to the experimental conditions, which might affect their predictive capabilities. In this study, we have explored the reliability of currently available tools by investigating the impact of varying said parameters in the simulation of metabolic fluxes and metabolite concentration values. Additionally, our in-depth analysis allowed us to highlight limitations and potential solutions that should be considered in future studies.

systems biology↗

bioRxiv2018

Gsmodutils: A python based framework for test-driven genome scale metabolic model development

MotivationGenome scale metabolic models (GSMMs) are increasingly important for systems biology and metabolic engineering research as they are capable of simulating complex steady-state behaviour. Constraints based models of this form can include thousands of reactions and metabolites, with many crucial pathways that only become activated in specific simulation settings. However, despite their widespread use, power and the availability of tools to aid with the construction and analysis of large scale models, little methodology is suggested for the continued management of curated large scale models. For example, when genome annotations are updated or new understanding regarding behaviour of is discovered, models often need to be altered to reflect this. This is quickly becoming an issue for industrial systems and synthetic biotechnology applications, which require good quality reusable models integral to the design, build and test cycle.\n\nResultsAs part of an ongoing effort to improve genome scale metabolic analysis, we have developed a test-driven development methodology for the continuous integration of validation data from different sources. Contributing to the open source technology based around COBRApy, we have developed the gsmodutils modelling framework placing an emphasis on test-driven design of models through defined test cases. Crucially, different conditions are configurable allowing users to examine how different designs or curation impact a wide range of system behaviours, minimising error between model versions.\n\nAvailabilityThe software framework described within this paper is open source and freely available from http://github.com/SBRCNottingham/gsmodutils

bioinformatics↗

bioRxiv2017

RNPP-type quorum sensing regulates solvent formation and sporulation in Clostridium acetobutylicum

The strictly anaerobic bacterium Clostridium acetobutylicum is well known for its ability to convert sugars into organic acids and solvents, most notably the potential biofuel butanol. However, the regulation of its fermentation metabolism, in particular the shift from acid to solvent production, remains poorly understood. The aim of this study was to investigate whether cell-cell communication plays a role in controlling the timing of this shift or the extent of solvent formation. Analysis of the available C. acetobutylicum genome sequences revealed the presence of eight putative RNPP-type quorum sensing systems, here designated qssA to qssH, each consisting of RNPP-type regulator gene followed by a small open reading frame encoding a putative signalling peptide precursor. The identified regulator and signal peptide precursor genes were designated qsrA to qsrH and qspA to qspH, respectively. Triplicate regulator mutants were generated in strain ATCC 824 for each of the eight systems and screened for phenotypic changes. The qsrB mutants showed increased solvent formation during early solventogenesis and hence the QssB system was selected for further characterisation. Overexpression of qsrB severely reduced solvent and endospore formation and this effect could be overcome by adding short synthetic peptides to the culture medium representing a specific region of the QspB signalling peptide precursor. In addition, overexpression of qspB increased the production of acetone and butanol and the initial (48-hour) titre of heat-resistant endospores. Together, these findings establish a role for QssB quorum sensing in the regulation of early solventogenesis and sporulation in C. acetobutylicum.

microbiology↗