Systems-level approaches for understanding and engineering of the oleaginous cell factory Yarrowia lipolytica.

Naghmeh Poorinmohammad,Eduard J Kerkhoven

doi:10.1002/bit.27859

Naghmeh Poorinmohammad, Eduard J Kerkhoven

Open Access

https://doi.org/10.1002/bit.27859

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Abstract

Concerns about climate change and the search for renewable energy sources together with the goal of attaining sustainable product manufacturing have boosted the use of microbial platforms to produce fuels and high-value chemicals. In this regard, Yarrowia lipolytica has been known as a promising yeast with potentials in diverse array of biotechnological applications such as being a host for different oleochemicals, organic acid, and recombinant protein production. Having a rapidly increasing number of molecular and genetic tools available, Y. lipolytica has been well studied amongst oleaginous yeasts and metabolic engineering has been used to explore its potentials. More recently, with the advancement in systems biotechnology and the implementation of mathematical modeling and high throughput omics data-driven approaches, in-depth understanding of cellular mechanisms of cell factories have been made possible resulting in enhanced rational strain design. In case of Y. lipolytica, these systems-level studies and the related cutting-edge technologies have recently been initiated which is expected to result in enabling the biotechnology sector to rationally engineer Y. lipolytica-based cell factories with favorable production metrics. In this regard, here, we highlight the current status of systems metabolic engineering research and assess the potential of this yeast for future cell factory design development.

Highlights

Limited fossil fuel resources as well as the growing environmental concerns associated with their extraction necessitate a substitute for the traditional chemical synthesis of valuable chemicals
Various studies have been performed to gain a systems‐level understanding of lipid metabolism with focus on three main questions: the main source of NADPH that lipid accumulation demands; gene regulation that coincides with lipid accumulation; and transcription factor networks that are underlying the expressional changes during lipid accumulation as will be detailed below
In a later model‐based approach, various gene knockouts and overexpression targets for improved TAG biosynthesis were predicted by analyzing a comprehensive genome‐scale metabolic model (GEM) reconstructed by Wei et al (2017) not experimentally verified, gene modification strategies mostly being involved in glycolytic and amino‐acid metabolic pathways were predicted to yield over 55% increase on TAG production

Summary

| INTRODUCTION

Limited fossil fuel resources as well as the growing environmental concerns associated with their extraction necessitate a substitute for the traditional chemical synthesis of valuable chemicals. The functional genomics revolution and increasing ease of omics data generation and computational analysis aids in understanding the mechanisms of complex biological systems and the prediction of their dynamic properties via systems biology This paradigm of studying a cell as a whole is being efficiently implemented to provide a holistic view of the functioning of microbial cell factories with the goal of rational re‐designing or creating new cellular functions in these organisms. Various studies have been performed to gain a systems‐level understanding of lipid metabolism with focus on three main questions: the main source of NADPH that lipid accumulation demands; gene regulation that coincides with lipid accumulation; and transcription factor networks that are underlying the expressional changes during lipid accumulation as will be detailed below In many cases, such studies have expanded our knowledge of various aspects of lipid metabolism, and yielded proposed targets for genetic engineering for improved lipid production. Subsequent transcriptomics as well as multiomics studies confirmed this hypothesis and elucidated the regulatory role of protein and amino acid metabolism in lipogenesis rather than the transcriptional regulation of lipid metabolism itself

Method

Findings

| CONCLUSIONS AND PERSPECTIVES