Biological insights into non-model microbial hosts through stable-isotope metabolic flux analysis

Diversity and function of viral AMGs associated with DNA biosynthesis in the Napahai plateau wetland

Viruses play an important role in microbial community structure and biodiversity by lysing host cells, and can also affect host metabolic pathways by expressing auxiliary metabolic genes (AMGs). As a unique low-latitude, high-altitude seasonal plateau wetland in China, Napahai has high research value. However, studies on the genetic diversity of AMGs and viruses associated with DNA biosynthesis have not been reported. Based on metagenomics, with the phylogenetic tree, PCoA, and α diversity analysis, we found that three DNA biosynthesis-related viral AMGs (cobS, mazG, and purM) in the Napahai plateau wetland were rich in genetic diversity, uniqueness, and differences compared with other habitats and host sources. Through the KEGG metabolic pathway and metabolic flow analysis of Pseudomonas mandelii (SW-3) and phage (VSW-3), the AMGs (cobS, mazG, and purM) genes of the three related viruses involved in DNA biosynthesis were upregulated and their expression increased significantly. In general, we systematically described the genetic diversity of AMGs associated with DNA biosynthesis in plateau wetland ecosystems and clarified the contribution of viral AMGs in the Napahai plateau wetland to DNA biosynthesis, as well as the changes of metabolites and genes. It further expands the understanding of phage-host interactions, which is of great significance for further revealing the role of viral AMGs in the biological evolution and biogeochemical cycle of wetland ecosystems.

Emerging nonmodel eukaryotes for biofuel production

Microbial synthesis of biofuels offers a promising solution to the global environmental and energy concerns. However, the main challenge of microbial cell factories is their high fermentation costs. Model hosts, such as Escherichia coli and Saccharomyces cerevisiae, are typically used for proof-of-concept studies of producing different types of biofuels, however, they have a limited potential for biofuel production at an industrially relevant scale due to the weak stability/robustness and narrow substrate scope. With the advancements of synthetic biology and metabolic engineering, nonmodel eukaryotes, with naturally favorable phenotypic and metabolic features, have been emerging as promising biofuel producers. Here, we introduce the emerging nonmodel eukaryotes for the biofuel production and discuss their specific advantages, especially those with the capacity of producing cellulosic ethanol, higher alcohols, and fatty acid-/terpene-derived biofuel molecules. We also propose the challenges and prospects for developing nonmodel eukaryotic as the ideal hosts for future biofuel production.

Engineered Production of Isobutanol from Sugarcane Trash Hydrolysates in Pichia pastoris

Concerns over climate change have led to increased interest in renewable fuels in recent years. Microbial production of advanced fuels from renewable and readily available carbon sources has emerged as an attractive alternative to the traditional production of transportation fuels. Here, we engineered the yeast Pichia pastoris, an industrial powerhouse in heterologous enzyme production, to produce the advanced biofuel isobutanol from sugarcane trash hydrolysates. Our strategy involved overexpressing a heterologous xylose isomerase and the endogenous xylulokinase to enable the yeast to consume both C5 and C6 sugars in biomass. To enable the yeast to produce isobutanol, we then overexpressed the endogenous amino acid biosynthetic pathway and the 2-keto acid degradation pathway. The engineered strains produced isobutanol at a titer of up to 48.2 ± 1.7 mg/L directly from a minimal medium containing sugarcane trash hydrolysates as the sole carbon source. To our knowledge, this is the first demonstration of advanced biofuel production using agricultural waste-derived hydrolysates in the yeast P. pastoris. We envision that our work will pave the way for a scalable route to this advanced biofuel and further establish P. pastoris as a versatile production platform for fuels and high-value chemicals.

Adapting isotopic tracer and metabolic flux analysis approaches to study C1 metabolism

Single-carbon (C1, or one-carbon) substrates are promising feedstocks for sustainable biofuel and biochemical production. Crucial to the goal of engineering C1-utilizing strains for improved production is a quantitative understanding of the organization, regulation and rates of the reactions that underpin C1 metabolism. ¹³C Metabolic flux analysis (MFA) is a well-established platform for interrogating these questions with multi-carbon substrates, and uses the differential labeling of metabolites that results from feeding a substrate with position-specific incorporation of ¹³C in order to infer quantitative fluxes and pathway topology. Adapting isotopic tracer approaches to C1 metabolism, where position-specific substrate labeling is impossible, requires additional experimental considerations. Here we review recent studies that have developed isotopic tracer approaches to overcome the challenge of uniform metabolite labeling and provide quantitative insight into C1 metabolism.

A guide to metabolic flux analysis in metabolic engineering: Methods, tools and applications

The field of metabolic engineering is primarily concerned with improving the biological production of value-added chemicals, fuels and pharmaceuticals through the design, construction and optimization of metabolic pathways, redirection of intracellular fluxes, and refinement of cellular properties relevant for industrial bioprocess implementation. Metabolic network models and metabolic fluxes are central concepts in metabolic engineering, as was emphasized in the first paper published in this journal, "Metabolic fluxes and metabolic engineering" (Metabolic Engineering, 1: 1-11, 1999). In the past two decades, a wide range of computational, analytical and experimental approaches have been developed to interrogate the capabilities of biological systems through analysis of metabolic network models using techniques such as flux balance analysis (FBA), and quantify metabolic fluxes using constrained-based modeling approaches such as metabolic flux analysis (MFA) and more advanced experimental techniques based on the use of stable-isotope tracers, i.e. ¹³C-metabolic flux analysis (¹³C-MFA). In this review, we describe the basic principles of metabolic flux analysis, discuss current best practices in flux quantification, highlight potential pitfalls and alternative approaches in the application of these tools, and give a broad overview of pragmatic applications of flux analysis in metabolic engineering practice.