scholarly journals A toolset of constitutive promoters for metabolic engineering ofRhodosporidium toruloides

2019 ◽  
Author(s):  
Luísa Czamanski Nora ◽  
Maren Wehrs ◽  
Joonhoon Kim ◽  
Jan-Fang Cheng ◽  
Angela Tarver ◽  
...  
Keyword(s):  
Metabolic Engineering ◽  
Genetic Engineering ◽  
Strain Engineering ◽  
Pathway Engineering ◽  
Transcriptional Analysis ◽  
Reporter System ◽  
Fluorescent Reporter ◽  
Promoter Sequences ◽  
Engineering Studies ◽  
Over Time

ABSTRACTBackgroundRhodosporidium toruloidesis a promising host for the production of bioproducts from lignocellulosic biomass. A key prerequisite for efficient pathway engineering is the availability of robust genetic tools and resources. However, there is a lack of characterized promoters to drive expression of heterologous genes for strain engineering inR. toruloides.ResultsOur data describes a set of nativeR. toruloidespromoters, characterized over time in four different media commonly used for cultivation of this yeast. The promoter sequences were selected using transcriptional analysis and several of them were found to drive expression bidirectionally. We measured promoter expression strength by flow cytometry using a dual fluorescent reporter system. From these analyses, we found a total of 20 constitutive promoters (12 monodirectional and 8 bidirectional) of potential value for genetic engineering ofR. toruloides.ConclusionsWe present a list of robust and constitutive, native promoters to facilitate genetic engineering ofR. toruloides.This set of thoroughly characterized promoters significantly expands the range of engineering tools available for this yeast and can be applied in future metabolic engineering studies.

scholarly journals Enhanced guide-RNA Design and Targeting Analysis for Precise CRISPR Genome Editing of Single and Consortia of Industrially Relevant and Non-Model Organisms

2017 ◽  
Author(s):  
Brian J. Mendoza ◽  
Cong T. Trinh
Keyword(s):  
Metabolic Engineering ◽  
Synthetic Biology ◽  
Genome Editing ◽  
Population Analysis ◽  
Strain Engineering ◽  
Pathway Engineering ◽  
Model Organisms ◽  
Guide Rna ◽  
Novel Applications ◽  
Rna Design

AbstractMotivationGenetic diversity of non-model organisms offers a repertoire of unique phenotypic features for exploration and cultivation for synthetic biology and metabolic engineering applications. To realize this enormous potential, it is critical to have an efficient genome editing tool for rapid strain engineering of these organisms to perform novel programmed functions.ResultsTo accommodate the use of CRISPR/Cas systems for genome editing across organisms, we have developed a novel method, named CASPER (CRISPR Associated Software for Pathway Engineering and Research), for identifying on- and off-targets with enhanced predictability coupled with an analysis of non-unique (repeated) targets to assist in editing any organism with various endonucleases. Utilizing CASPER, we demonstrated a modest 2.4% and significant 30.2% improvement (F-test, p<0.05) over the conventional methods for predicting on- and off-target activities, respectively. Further we used CASPER to develop novel applications in genome editing: multitargeting analysis (i.e. simultaneous multiple-site modification on a target genome with a sole guide-RNA (gRNA) requirement) and multispecies population analysis (i.e. gRNA design for genome editing across a consortium of organisms). Our analysis on a selection of industrially relevant organisms revealed a number of non-unique target sites associated with genes and transposable elements that can be used as potential sites for multitargeting. The analysis also identified shared and unshared targets that enable genome editing of single or multiple genomes in a consortium of interest. We envision CASPER as a useful platform to enhance the precise CRISPR genome editing for metabolic engineering and synthetic biology applications.

scholarly journals Exp2Ipynb: A general machine-learning workflow for the analysis of promoter libraries

2020 ◽  
Author(s):  
Ulf W. Liebal ◽  
Sebastian Koebbing ◽  
Lars M. Blank
Keyword(s):  
Machine Learning ◽  
Sample Size ◽  
Learning Strategies ◽  
Promoter Sequence ◽  
Strain Engineering ◽  
Reporter System ◽  
Promoter Sequences ◽  
Expression Activity ◽  
Multiple Promoter ◽  
High Throughput Experiments

Strain engineering in biotechnology modifies metabolic pathways in microorganisms to overproduce target metabolites. To modify metabolic pathway activity in bacteria, gene expression is an effective and easy manipulated process, specifically the promoter sequence recognized by sigma factors. Promoter libraries are generated to scan the expression activity of different promoter sequences and to identify sequence positions that predict activity. To maximize information retrieval, a well-designed experimental setup is required. We present a computational workflow to analyse promoter libraries; by applying this workflow to seven libraries, we aim to identify critical design principles. The workflow is based on a Python Jupyter Notebook and covers the following steps: (i) statistical sequence analysis, (ii) sequence-input to expression-output predictions, (iii) estimator performance evaluation, and (iv) new sequence prediction with defined activity. The workflow can process multiple promoter libraries, across species or reporter proteins, and classify or regress expression activity. The strongest predictions in the sample libraries were achieved when the promoters in the library were recognized by a single sigma factor and a unique reporter system. A trade-off between sample size and sequence diversity reduces prediction quality, and we present a relationship to estimate the minimum sample size. The workflow guides the user through analysis and machine-learning training, is open source and easily adaptable to include alternative machine-learning strategies and to process sequence libraries from other expression-related problems. The workflow is a contribution to increase insight to the growing application of high-throughput experiments and provides support for efficient strain engineering.

Advances in Strain Engineering for Improved Bio-fuel Production- a Perspective

2020 ◽  
Vol 7 (1) ◽  
pp. 1-5
Author(s):  
Supriya Ratnaparkhe ◽  
Milind B. Ratnaparkhe
Keyword(s):  
Metabolic Engineering ◽  
Genetic Engineering ◽  
Fossil Fuel ◽  
Strain Engineering ◽  
Research Community ◽  
The Novel ◽  
Fuel Production ◽  
Genetic Manipulations ◽  
Ecologically Sustainable ◽  
Complex Genome

Bio-fuels are ecologically sustainable alternates of fossil fuel and have attracted interest of research community in the last few decades. Microorganisms such as bacteria, fungi and microalgae have important roles to play at various steps of bio-fuel production. And therefore several efforts such as genetic engineering have been made to improve the performance of these microbes to achieve the desired results. Metabolic engineering of organisms has benefitted immensely from the novel tools and technologies that have recently been developed. Microorganisms have the advantage of smaller and less complex genome and hence are best suitable for genetic manipulations. In this perspective, we briefly review a few interesting studies which represent some recent advances in the field of metabolic engineering of microbes.

scholarly journals An outlook on metabolic pathway engineering in crop plants

2020 ◽  
Vol 5 (3) ◽  
pp. 431-434
Author(s):  
Jyoti Prakash Sahoo ◽  
Upasana Mohapatra ◽  
Priyadarshini Mishra
Keyword(s):  
Metabolic Engineering ◽  
Drug Discovery ◽  
Metabolic Pathway ◽  
Pathway Engineering ◽  
Cell Physiology ◽  
Detailed Knowledge ◽  
Protein Protein Interaction ◽  
High Profile ◽  
Engineering Studies ◽  
Metabolic Pathway Engineering

To produce the essential secondary metabolites, plants are the major and important target source materials for conducting the high-profile metabolic engineering studies. Metabolic pathway engineering of both microorganism targets and plants target contribute towards important drug discovery. In order to efficiently work out in advanced plant metabolic pathway engineering techniques, a detailed knowledge and expertise is essentially needed regarding the plant cell physiology and the mechanics of plant metabolism. Mathematical and statistical models to scale and map the genome for integrative metabolic pathway activity, signal transduction mechanism in the genome, gene regulation and the networks of protein-protein interaction can provide the in-depth knowledge to work efficiently on plant metabolic pathway engineering studies. Incorporation of omics data into these statistical and mathematical models is crucial in the case of drug discovery using the plant system. Recently, artificial intelligence concept and approaches are experimentally applied for efficient and accurate metabolic engineering in plants.

scholarly journals Constraint-based metabolic control analysis for rational strain engineering

2020 ◽  
Author(s):  
Sophia Tsouka ◽  
Meric Ataman ◽  
Tuure Hameri ◽  
Ljubisa Miskovic ◽  
Vassily Hatzimanikatis
Keyword(s):  
Metabolic Engineering ◽  
Genome Editing ◽  
Metabolic Control ◽  
Metabolic Flux ◽  
Strain Engineering ◽  
Metabolic Control Analysis ◽  
Physiological Data ◽  
Response Analysis ◽  
Control Analysis ◽  
Wide Range

AbstractThe advancements in genome editing techniques over the past years have rekindled interest in rational metabolic engineering strategies. While Metabolic Control Analysis (MCA) is a well-established method for quantifying the effects of metabolic engineering interventions on flows in metabolic networks and metabolic concentrations, it fails to account for the physiological limitations of the cellular environment and metabolic engineering design constraints. We report here a constraint-based framework based on MCA, Network Response Analysis (NRA), for the rational genetic strain design that incorporates biologically relevant constraints, as well as genome editing restrictions. The NRA core constraints being similar to the ones of Flux Balance Analysis, allow it to be used for a wide range of optimization criteria and with various physiological constraints. We show how the parametrization and introduction of biological constraints enhance the NRA formulation compared to the classical MCA approach, and we demonstrate its features and its ability to generate multiple alternative optimal strategies given several user-defined boundaries and objectives. In summary, NRA is a sophisticated alternative to classical MCA for rational metabolic engineering that accommodates the incorporation of physiological data at metabolic flux, metabolite concentration, and enzyme expression levels.

scholarly journals DnaK response to expression of protein mutants is dependent on translation rate and stability

2021 ◽  
Author(s):  
Signe Christensen ◽  
Sebastian Rämisch ◽  
Ingemar André
Keyword(s):  
Large Degree ◽  
Synthesis Rate ◽  
Protein Synthesis Rate ◽  
Protein Abundance ◽  
Reporter System ◽  
Thermal Stabilities ◽  
Translation Rate ◽  
Fluorescent Reporter ◽  
Unfolded Protein ◽  
Protein Mutants

AbstractChaperones play a central part in the quality control system in cells by clearing misfolded and aggregated proteins. The chaperone DnaK acts as a sensor for molecular stress by recognising short hydrophobic stretches of misfolded proteins. As the level of unfolded protein is a function of protein stability, we hypothesised that the level of DnaK response upon overexpression of recombinant proteins would be correlated to stability. Using a set of mutants of the λ-repressor with varying thermal stabilities and a fluorescent reporter system, the effect of stability on DnaK response and protein abundance was investigated. Our results demonstrate that the initial DnaK response is largely dependent on protein synthesis rate but as the recombinantly expressed protein accumulates and homeostasis is approached the response correlates strongly with stability. Furthermore, we observe a large degree of cell-cell variation in protein abundance and DnaK response in more stable proteins.

scholarly journals Staphylococcal DNA repair is required for infection

2020 ◽  
Author(s):  
Kam Pou Ha ◽  
Rebecca S. Clarke ◽  
Gyu-Lee Kim ◽  
Jane L. Brittan ◽  
Jessica E. Rowley ◽  
...  
Keyword(s):  
Human Blood ◽  
Strand Break ◽  
Double Strand Breaks ◽  
Dna Double Strand Breaks ◽  
Reporter System ◽  
Gram Positive ◽  
Fluorescent Reporter ◽  
Strand Breaks ◽  
Dna Double Strand Break ◽  
Transposon Mutants

AbstractThe repair of DNA damage is essential for bacterial viability and contributes to adaptation via increased rates of mutation and recombination. However, the mechanisms by which DNA is damaged and repaired during infection are poorly understood. Using a panel of transposon mutants, we identified the rexBA operon as important for the survival of Staphylococcus aureus in whole human blood. Mutants lacking rexB were also attenuated for virulence in murine models of both systemic and skin infections. We then demonstrated that RexAB is a member of the AddAB family of helicase/nuclease complexes responsible for initiating the repair of DNA double strand breaks. Using a fluorescent reporter system, we were able to show that neutrophils cause staphylococcal DNA double strand breaks via the oxidative burst, which are repaired by RexAB, leading to induction of the mutagenic SOS response. We found that RexAB homologues in Enterococcus faecalis and Streptococcus gordonii also promoted survival of these pathogens in human blood, suggesting that DNA double strand break repair is required for Gram-positive bacteria to survive in host tissues. Together, these data demonstrate that DNA is a target of host immune cells, leading to double-strand breaks, and that repair of this damage by an AddAB-family enzyme enables the survival of Gram-positive pathogens during infection.

scholarly journals Engineering Bacterial Cellulose by Synthetic Biology

2020 ◽  
Vol 21 (23) ◽  
pp. 9185
Author(s):  
Amritpal Singh ◽  
Kenneth T. Walker ◽  
Rodrigo Ledesma-Amaro ◽  
Tom Ellis
Keyword(s):  
Metabolic Engineering ◽  
Synthetic Biology ◽  
Genetic Engineering ◽  
Bacterial Cellulose ◽  
Engineering Design ◽  
Recent Work ◽  
Material Properties ◽  
Genetic Manipulation ◽  
Change Material ◽  
Production Change

Synthetic biology is an advanced form of genetic manipulation that applies the principles of modularity and engineering design to reprogram cells by changing their DNA. Over the last decade, synthetic biology has begun to be applied to bacteria that naturally produce biomaterials, in order to boost material production, change material properties and to add new functionalities to the resulting material. Recent work has used synthetic biology to engineer several Komagataeibacter strains; bacteria that naturally secrete large amounts of the versatile and promising material bacterial cellulose (BC). In this review, we summarize how genetic engineering, metabolic engineering and now synthetic biology have been used in Komagataeibacter strains to alter BC, improve its production and begin to add new functionalities into this easy-to-grow material. As well as describing the milestone advances, we also look forward to what will come next from engineering bacterial cellulose by synthetic biology.

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