Advances in proteomics for production strain analysis

Landels, Andrew; Evans, Caroline; Noirel, Josselin; Wright, Phillip C.

doi:10.1016/j.copbio.2015.05.001

Cited by 9 publications

(5 citation statements)

References 64 publications

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“…[109, 114, 115]. Additionally, routine targeted proteomics and metabolomics can be performed to rapidly assess gene expressions and key metabolites accumulation [116–119]. With the technologies developed in the field of synthetic biology for the past 10 years, including computer-aided pathway design algorithms [120–122], DNA assembly and sequencing [123–125], it is now routine to screen a large combinatorial libraries.…”

Section: Pathway and Strain Optimizationmentioning

confidence: 99%

Gas fermentation: cellular engineering possibilities and scale up

2017

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Low carbon fuels and chemicals can be sourced from renewable materials such as biomass or from industrial and municipal waste streams. Gasification of these materials allows all of the carbon to become available for product generation, a clear advantage over partial biomass conversion into fermentable sugars. Gasification results into a synthesis stream (syngas) containing carbon monoxide (CO), carbon dioxide (CO2), hydrogen (H2) and nitrogen (N2). Autotrophy–the ability to fix carbon such as CO2 is present in all domains of life but photosynthesis alone is not keeping up with anthropogenic CO2 output. One strategy is to curtail the gaseous atmospheric release by developing waste and syngas conversion technologies. Historically microorganisms have contributed to major, albeit slow, atmospheric composition changes. The current status and future potential of anaerobic gas-fermenting bacteria with special focus on acetogens are the focus of this review.

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Section: Pathway and Strain Optimizationmentioning

confidence: 99%

Gas fermentation: cellular engineering possibilities and scale up

2017

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“…In general, it is underexplored in metabolic engineering, mainly due to the low throughput and complexity of the data sets. However, recent developments toward targeted proteomics, such as multireaction monitoring (MRM) approaches are generating a change (Landels, Evans, Noirel, & Wright, 2015).…”

Section: Introductionmentioning

confidence: 99%

Unraveling and resolving inefficient glucolipid biosurfactants production through quantitative multiomics analyses of Starmerella bombicola strains

Lodens

Roelants

Ciesielska

et al. 2019

Biotech & Bioengineering

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Glucolipids (GLs) are glycolipid biosurfactants with promising properties. These GLs are composed of glucose attached to a hydroxy fatty acid through a ω and/or ω‐1 glycosidic linkage. Up until today these interesting molecules could only be produced using an engineered Starmerella bombicola strain (∆ugtB1::URA3 G9) producing GLs instead of sophorolipids, albeit with a very low average productivity (0.01 g·L−1·h−1). In this study, we investigated the reason(s) for this via reverse‐transcription quantitative polymerase chain reaction and Liquid chromatography‐multireaction monitoring‐mass spectrometry. We found that all glycolipid biosynthetic genes and enzymes were downregulated in the ∆ugtB1 G9 strain in comparison to the wild type. The underlying reason for this downregulation was further investigated by performing quantitative metabolome comparison of the ∆ugtB1 G9 strain with the wild type and two other engineered strains also tinkered in their glycolipid biosynthetic gene cluster. This analysis revealed a clear distortion of the entire metabolism of the ∆ugtB1 G9 strain compared to all the other strains. Because the parental strain of the former was a spontaneous ∆ura3 mutant potentially containing other “hidden” mutations, a new GL production strain was generated based on a rationally engineered ∆ura3 mutant (PT36). Indeed, a 50‐fold GL productivity increase (0.51 g·L−1·h−1) was obtained with the new ∆ugtB1::URA3 PT36 strain compared with the G9‐based strain (0.01 g·L−1·h−1) in a 10 L bioreactor experiment, yielding 118 g/L GLs instead of 8.39 g/L. Purification was investigated and basic properties of the purified GLs were determined. This study forms the base for further development and optimization of S. bombicola as a production platform strain for (new) biochemicals

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“…We take advantage of three synergistic, accelerating domains of science—systems biology, metabolic engineering, and synthetic biology—to develop a workflow that reconciles systems-level, multi-omics analysis and genome-scale modeling with synthetic pathway engineering. While the collection of targeted omics data has supported a number of metabolic engineering efforts (Alonso-Gutierrez et al, 2015; George et al, 2014; Han et al, 2001, 2003; Kabir and Shimizu, 2003; Landels et al, 2015; Lee et al, 2005), the extraction of biologically meaningful information from highly dimensional multi-omics data sets remains a continual challenge (Kwok, 2010; Nielsen et al, 2014; Palsson and Zengler, 2010). Engineering strategies such as the design–build–test–analyze (DBTA) cycle (Bailey, 1991) attempt to side-step this issue through rapid iteration and strain assessment, but the “analyze” phase of the cycle is often limited by a narrow focus on one or two experimental outputs such as product titer.…”

Section: Introductionmentioning

confidence: 99%

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

et al. 2016

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SUMMARY Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology, provides molecular insight into how the host organism microenvironment changes due to pathway engineering, and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proof-of-concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks.

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Advances in proteomics for production strain analysis

Cited by 9 publications

References 64 publications

Gas fermentation: cellular engineering possibilities and scale up

Gas fermentation: cellular engineering possibilities and scale up

Unraveling and resolving inefficient glucolipid biosurfactants production through quantitative multiomics analyses of Starmerella bombicola strains

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

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