Harnessing microbial heterogeneity for improved biosynthesis fueled by synthetic biology

Abstract

Metabolic engineering-driven microbial cell factories have made great progress in the efficient bioproduction of biochemical and recombinant proteins. However, the low efficiency and robustness of microbial cell factories limit their industrial applications. Harnessing microbial heterogeneity contributes to solving this. In this review, the origins of microbial heterogeneity and its effects on biosynthesis are first summarized. Synthetic biology-driven tools and strategies that can be used to improve biosynthesis by increasing and reducing microbial heterogeneity are then systematically summarized. Next, novel single-cell technologies available for unraveling microbial heterogeneity and facilitating heterogeneity regulation are discussed. Furthermore, a combined workflow of increasing genetic heterogeneity in the strain-building step to help in screening highly productive strains - reducing heterogeneity in the production process to obtain highly robust strains (IHP-RHR) facilitated by single-cell technologies was proposed to obtain highly productive and robust strains by harnessing microbial heterogeneity. Finally, the prospects and future challenges are discussed.

Keywords: Genetic heterogeneity; Highly productive strains; Highly robust strains; Non-genetic heterogeneity; Single-cell technologies; Synthetic biology.

Graphical abstract

Fig. 1

The origins of microbial heterogeneity. Microbial heterogeneity includes genetic and non-genetic heterogeneity. Genetic heterogeneity can result from plasmid instability, DNA replication error, gene of interest (GOI) inactivation by IS element, DNA deamination of single-strand DNA (ssDNA), and error-prone DNA polymerase (DNAP)-mediated DNA repair. Cellular and environmental variations can both result in non-genetic heterogeneity by influencing gene expression. The cellular variations include gene expression noise, uneven plasmid distribution, and asymmetric cell division. The environmental variations include heterogeneous temperature (T), dissolved oxygen (DO), pH and physical stress, as well as heterogeneity in the availability of nutrients.

Fig. 2

Strategies and tools to increase microbial heterogeneity. A) Mutator strain with mutator gene and fidelity gene controlled by an orthogonal inducible promoter pair. One inducer is added to activate the mutator gene to increase the mutation rate to generate a mutant library. The other inducer can activate the fidelity gene and repress the mutator gene simultaneously to reduce the mutation rate to stably maintain the improved phenotype at the end of evolution. B) Mutator strain with product titer-dependent mutation rate. Product-responsive biosensors have been used to regulate the expression of the mutator gene to adaptively tune mutation rates based on the product titer. In the absence of the target product, the mutator gene is activated to increase the mutation rate to generate diversity in the population and is repressed to reduce the mutation rate when the titer of the target product is high. C) A CRISPR-assisted evolution system with RNA, not DNA, as a repair template. Variants of chimeric donor gRNAs composed of gRNA guiding Cag9/dCas9 and the RNA segment as repair template(temp-cgRNA), which are continuously transcribed by an error-prone T7 RNA polymerase, are used to introduce mutations by RNA-mediated repair. D) A system with an orthogonal DNA polymerase–plasmid pair in yeast. Host DNA polymerase (DNAP) replicates genome and orthogonal DNAP-carrying plasmid stably. Orthogonal DNAP replicates gene of interest (GOI)-carrying plasmid with a high mutation rate. E) A retrotransposon Ty1-based in vivo continuous evolution system. After the transcription of retroelement, the transcript including GOI is converted into cDNA in an error-prone manner. Then, the generated cDNA is re-integrated into the genomic locus, thereby introducing mutations. F) An in vivo evolution platform based on T7RNAP and catalytically dCas9. The platform uses T7RNAP to target mutagenic enzymes (base deaminase, BD) to the target sequence to introduce mutations and uses dCas9 combined with custom-designed crRNAs as a “roadblock” to constrict the size of the mutation window. G) An asymmetry distribution-based synthetic consortium (ADSC) that can coordinate the ratio of production cells and growing cells in the population by asymmetric cell division, thereby improving production by metabolic division of labor. H)A synthetic circuits that divide the population into two cell types, progenitors (responsible for replication and proliferation) and differentiators (responsible for biosynthesis) by terminal differentiation, therefore improving the evolutionary stability of burdensome and toxic functions in E. coli.

Fig. 3

Strategies to reduce microbial heterogeneity. The widely used methods of reducing microbial genetic heterogeneity include maintaining the stability of plasmid, choosing stable DNA sequence and host, using a combinatorial assembly platform to construct and select a stable pathway design, coupling biosynthesis with growth and developing stable chassis with reduced mutation rate. The strategies to address non-genetic heterogeneity include the traditional strategies, such as engineering global gene regulatory, strain and inducer modifications and physiology manipulations, and novel tools and strategies for maintaining homogeneous gene expression. In addition, coupling growth with biosynthesis can also be an efficient and effective strategy to address non-genetic heterogeneity.

Fig. 4

A combined workflow, namely increasing genetic heterogeneity in the step of strain building to help in screening highly productive strains-reducing heterogeneity in the production process to obtain highly robust strains (IHP-RHR). It is promising to obtain highly productive and robust microbial strains using this combined workflow. In the strain-building step, increasing heterogeneity can provide a large library of variants. Then, flow cytometry and microfluidic-based single-cell analysis and isolation technologies can be employed to screen highly productive strains from the large library of variants. After this, reducing heterogeneity in the following fermentation process can help obtain highly productive and robust strains. In addition, novel single-cell analytical technologies can help explore microbial heterogeneity through monitoring and analysis, which can in turn provide novel targets for harnessing biosynthetic heterogeneity to push the workflow.