Advances in proteomics for production strain analysis

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

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.

Methodologies and Applications of Proteomics for Study of Yeast Strains: An Update

Yeasts are one of the mostly used microorganisms as models in several studies. A wide range of applications in different processes can be attributed to their intrinsic characteristics. They are eukaryotes and therefore valuable expression hosts that require elaborate post-translational modifications. Their arsenal of proteins has become a valuable biochemical tool for the catalysis of several reactions of great value to the food (beverages), pharmaceutical and energy industries. Currently, the main challenge in systemic yeast biology is the understanding of the expression, function and regulation of the protein pool encoded by such microorganisms. In this review, we will provide an overview of the proteomic methodologies used in the analysis of yeasts. This research focuses on the advantages and improvements in their most recent applications with an understanding of the functionality of the proteins of these microorganisms, as well as an update of the advances of methodologies employed in mass spectrometry.

Gas fermentation: cellular engineering possibilities and scale up

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.

Toxicological proteomic responses of halophyte Suaeda salsa to lead and zinc

The long term (30 days) toxicological effects of environmentally relevant concentrations of Pb²⁺ (20μg/L) and Zn²⁺ (100μg/L) were characterized in Suaeda salsa using proteomics techniques. The responsive proteins were related to metabolism (Krebs cycle and Calvin cycle), protein biosynthesis, stress and defense, energy, signaling pathway and photosynthesis in Pb²⁺, Zn²⁺ and Pb²⁺+ Zn²⁺ exposed groups in S. salsa after exposures for 30 days. The proteomic profiles also showed differential responses in S. salsa to metal exposures. In Pb²⁺-treated group, the proteins were categorized into cystein metabolism and pentose phosphate pathway. The responsive proteins were basically involved in glutathione metabolism, glycolysis, cystein and methane metabolism, and voltage-dependent anion channel in Zn²⁺-treated group. In Pb²⁺+ Zn²⁺-treated group, the proecular mechanism at protein level remtein responses were devided into tyrosine metabolism and glycolysis. Our results showed that the two typical heavy metals, lead and zinc, could induce toxicological effects in halophyte S. salsa at protein level.

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

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.