Engineering Microbial Metabolite Dynamics and Heterogeneity

Abstract

As yields for biological chemical production in microorganisms approach their theoretical maximum, metabolic engineering requires new tools, and approaches for improvements beyond what traditional strategies can achieve. Engineering metabolite dynamics and metabolite heterogeneity is necessary to achieve further improvements in product titers, productivities, and yields. Metabolite dynamics, the ensemble change in metabolite concentration over time, arise from the need for microbes to adapt their metabolism in response to the extracellular environment and are important for controlling growth and productivity in industrial fermentations. Metabolite heterogeneity, the cell-to-cell variation in a metabolite concentration in an isoclonal population, has a significant impact on ensemble productivity. Recent advances in single cell analysis enable a more complete understanding of the processes driving metabolite heterogeneity and reveal metabolic engineering targets. The authors present an overview of the mechanistic origins of metabolite dynamics and heterogeneity, why they are important, their potential effects in chemical production processes, and tools and strategies for engineering metabolite dynamics and heterogeneity. The authors emphasize that the ability to control metabolite dynamics and heterogeneity will bring new avenues of engineering to increase productivity of microbial strains.

Coupled metabolic‐hydrodynamic modeling enabling rational scale‐up of industrial bioprocesses

“…Tang et al () have reported that global profiles (intracellular, extracellular as well as relevant specific rates) would be in a dynamic concert with glucose availability (feast/famine conditions) induced by feeding strategies (e.g., intermittent feed, feed‐ramp). Thus, new avenues via manipulating metabolite dynamics and cell heterogeneity can be implemented to boost ensemble strain performance (A. C. Schmitz et al, ). Bioreactor scale‐down holds great promise for the generation of actionable knowledge to address the effects of scale‐related factors (Delvigne, Takors, Mudde, van Gulik, & Noorman, ; Wang et al, ).…”

“…This reduction of global productivity can often be ascribed to the formation of a specific subpopulation of cells with vanished or discounted production capacity (Delvigne, Zune, Lara, Al‐Soud, & Sorensen, ). It has been recently reported that this cell‐to‐cell heterogeneity arises from metabolic cooperation (Campbell, Vowinckel, & Ralser, ), and metabolite dynamics in response to the extracellular environment plays a vital role in regulating biomass growth and product formation in industrial practices (A. C. Schmitz, Hartline, & Zhang, ). It is hence indispensable to understand how metabolic fluxes are intricately coordinated by complex regulatory mechanisms such as gene‐metabolite association maps (Zampieri & Sauer, ), posttranslational modifications, for example, enzyme phosphorylation or acetylation (Gerosa & Sauer, ).…”

“…It is hence indispensable to understand how metabolic fluxes are intricately coordinated by complex regulatory mechanisms such as gene‐metabolite association maps (Zampieri & Sauer, ), posttranslational modifications, for example, enzyme phosphorylation or acetylation (Gerosa & Sauer, ). Accordingly, new avenues to further increase industrial‐scale production can be designed by engineering metabolite dynamics and metabolite heterogeneity (A. C. Schmitz et al, ).…”

Resazurin Assay Data for Mycobacterium tuberculosis Supporting a Model of the Growth Accelerated by a Stochastic Non-Homogeneity

“…However, recently, such non-standard features started to attract the attention of the research community involved in an application of dynamical and stochastic systems theory for modeling macroscopic growth dynamics [21][22][23][24]. The key aim of such research is to connect the revealed genetic/metabolic variability of individual microorganisms with the macroscopic dynamics of the whole population.…”

Recent Advances in the Genomic Profiling of Bacterial Epigenetic Modifications

“…Epigenetic modification is adopted as a switch to regulate some phase variation systems without changing the DNA sequence . Identification of the heterogeneity of a population facilitates a better understanding of microbial stress responses in different environments . The previously applied SMRT methodology, which relies on assessments of average inter‐pulse duration (IPD) values across the whole cell population, cannot reveal epigenetic heterogeneity.…”