Engineering Pseudomonas putida for Improved Utilization of Syringyl Aromatics

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules ("functional modules"), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida. Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets.

IMPORTANCE

This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

Application of functional genomics for domestication of novel non-model microbes

With the expansion of domesticated microbes producing biomaterials and chemicals to support a growing circular bioeconomy, the variety of waste and sustainable substrates that can support microbial growth and production will also continue to expand. The diversity of these microbes also requires a range of compatible genetic tools to engineer improved robustness and economic viability. As we still do not fully understand the function of many genes in even highly studied model microbes, engineering improved microbial performance requires introducing genome-scale genetic modifications followed by screening or selecting mutants that enhance growth under prohibitive conditions encountered during production. These approaches include adaptive laboratory evolution, random or directed mutagenesis, transposon-mediated gene disruption, or CRISPR interference (CRISPRi). Although any of these approaches may be applicable for identifying engineering targets, here we focus on using CRISPRi to reduce the time required to engineer more robust microbes for industrial applications.

ONE-SENTENCE SUMMARY

The development of genome scale CRISPR-based libraries in new microbes enables discovery of genetic factors linked to desired traits for engineering more robust microbial systems.

Identification of a Phylogenetically Divergent Vanillate O-Demethylase from Rhodococcus ruber R1 Supporting Growth on Meta-Methoxylated Aromatic Acids

Rieske-type two-component vanillate O-demethylases (VanODs) catalyze conversion of the lignin-derived monomer vanillate into protocatechuate in several bacterial species. Currently, VanODs have received attention because of the demand of effective lignin valorization technologies, since these enzymes own the potential to catalyze methoxy group demethylation of distinct lignin monomers. In this work, we identified a phylogenetically divergent VanOD from Rhodococcus ruber R1, only distantly related to previously described homologues and whose presence, along with a 3-hydroxybenzoate/gentisate pathway, correlated with the ability to grow on other meta-methoxylated aromatics, such as 3-methoxybenzoate and 5-methoxysalicylate. The complementation of catabolic abilities by heterologous expression in a host strain unable to grow on vanillate, and subsequent resting cell assays, suggest that the vanAB genes of R1 strain encode a proficient VanOD acting on different vanillate-like substrates; and also revealed that a methoxy group in the meta position and a carboxylic acid moiety in the aromatic ring are key for substrate recognition. Phylogenetic analysis of the oxygenase subunit of bacterial VanODs revealed three divergent groups constituted by homologues found in Proteobacteria (Type I), Actinobacteria (Type II), or Proteobacteria/Actinobacteria (Type III) in which the R1 VanOD is placed. These results suggest that VanOD from R1 strain, and its type III homologues, expand the range of methoxylated aromatics used as substrates by bacteria.

Creative biological lignin conversion routes toward lignin valorization

Lignin, the largest renewable aromatic resource, is a promising alternative feedstock for the sustainable production of various chemicals, fuels, and materials. Despite this potential, lignin is characterized by heterogeneous and macromolecular structures that must be addressed. In this review, we present biological lignin conversion routes (BLCRs) that offer opportunities for overcoming these challenges, making lignin valorization feasible. Funneling heterogeneous aromatics via a 'biological funnel' offers a high-specificity bioconversion route for aromatic platform chemicals. The inherent aromaticity of lignin drives atom-economic functionalization routes toward aromatic natural product generation. By harnessing the ligninolytic capacities of specific microbial systems, powerful aromatic ring-opening routes can be developed to generate various value-added products. Thus, BLCRs hold the promise to make lignin valorization feasible and enable a lignocellulose-based bioeconomy.