Genetic and process engineering for polyhydroxyalkanoate production from pre- and post-consumer food waste.

Biopolymers produced as microbial carbon storage systems, such as polyhydroxyalkanoates (PHAs), offer potential to be used in place of petrochemically derived plastics. Low-value organic feedstocks, such as food waste, have been explored as a potential substrate for the microbial production of PHAs. In this review, we discuss the biosynthesis, composition and producers of PHAs, with a particular focus on the genetic and process engineering efforts to utilise non-native substrates, derived from food waste from across the entire supply chain, for microbial growth and PHA production. We highlight a series of studies that have achieved impressive advances and discuss the challenges of producing PHAs with consistent composition and properties from mixed and variable food waste and by-products.

Sustainable biosynthetic pathways to value-added bioproducts from hydroxycinnamic acids.

The biorefinery concept, in which biomass is utilized for the production of fuels and chemicals, emerges as an eco-friendly, cost-effective, and renewable alternative to petrochemical-based production. The hydroxycinnamic acid fraction of lignocellulosic biomass represents an untapped source of aromatic molecules that can be converted to numerous high-value products with industrial applications, including in the flavor and fragrance sector and pharmaceuticals. This review describes several biochemical pathways useful in the development of a biorefinery concept based on the biocatalytic conversion of the hydroxycinnamic acids ferulic, caffeic, and p-coumaric acid into high-value molecules. KEY POINTS: • The phenylpropanoids bioconversion pathways in the context of biorefineries • Description of pathways from hydroxycinnamic acids to high-value compounds • Metabolic engineering and synthetic biology advance hydroxycinnamic acid-based biorefineries.

arfA antisense RNA regulates MscL excretory activity.

Excretion of cytoplasmic protein (ECP) is a commonly observed phenomenon in bacteria, and this partial extracellular localisation of the intracellular proteome has been implicated in a variety of stress response mechanisms. In response to hypoosmotic shock and ribosome stalling in Escherichia coli, ECP is dependent upon the presence of the large-conductance mechanosensitive channel and the alternative ribosome-rescue factor A gene products. However, it is not known if a mechanistic link exists between the corresponding genes and the respective stress response pathways. Here, we report that the corresponding mscL and arfA genes are commonly co-located on the genomes of Gammaproteobacteria and display overlap in their respective 3' UTR and 3' CDS. We show this unusual genomic arrangement permits an antisense RNA-mediated regulatory control between mscL and arfA, and this modulates MscL excretory activity in E. coli These findings highlight a mechanistic link between osmotic, translational stress responses and ECP in E. coli, further elucidating the previously unknown regulatory function of arfA sRNA.

Directed Evolution of Transcription Factor-Based Biosensors for Altered Effector Specificity.

Transcription factor-based biosensors are important tools in Synthetic Biology for the sensing of industrially valuable molecules and clinically important metabolites, therefore presenting applications in the bioremediation, industrial biotechnology, and biomedical fields. The directed evolution of allosteric transcription factors (aTFs) with the aim of altering effector specificity has the potential for the development of new biosensors to detect natural and nonnatural molecules, expanding the scope of available aTF-based biosensors. In this chapter, we delineate a general method for the directed evolution of aTFs. The theory of library design is discussed, along with the detailed methodology for an improved transformation of combined libraries, and the experimental search space by counterselection using fluorescence-activated cell sorting (FACS) is presented.

Genetic and process engineering strategies for enhanced recombinant N-glycoprotein production in bacteria.

BACKGROUND: The production of N-linked glycoproteins in genetically amenable bacterial hosts offers great potential for reduced cost, faster/simpler bioprocesses, greater customisation, and utility for distributed manufacturing of glycoconjugate vaccines and glycoprotein therapeutics. Efforts to optimize production hosts have included heterologous expression of glycosylation enzymes, metabolic engineering, use of alternative secretion pathways, and attenuation of gene expression. However, a major bottleneck to enhance glycosylation efficiency, which limits the utility of the other improvements, is the impact of target protein sequon accessibility during glycosylation. RESULTS: Here, we explore a series of genetic and process engineering strategies to increase recombinant N-linked glycosylation, mediated by the Campylobacter-derived PglB oligosaccharyltransferase in Escherichia coli. Strategies include increasing membrane residency time of the target protein by modifying the cleavage site of its secretion signal, and modulating protein folding in the periplasm by use of oxygen limitation or strains with compromised oxidoreductase or disulphide-bond isomerase activity. These approaches achieve up to twofold improvement in glycosylation efficiency. Furthermore, we also demonstrate that supplementation with the chemical oxidant cystine enhances the titre of glycoprotein in an oxidoreductase knockout strain by improving total protein production and cell fitness, while at the same time maintaining higher levels of glycosylation efficiency. CONCLUSIONS: In this study, we demonstrate that improved protein glycosylation in the heterologous host could be achieved by mimicking the coordination between protein translocation, folding and glycosylation observed in native host such as Campylobacter jejuni and mammalian cells. Furthermore, it provides insight into strain engineering and bioprocess strategies, to improve glycoprotein yield and titre, and to avoid physiological burden of unfolded protein stress upon cell growth. The process and genetic strategies identified herein will inform further optimisation and scale-up of heterologous recombinant N-glycoprotein production.

Structural basis of terephthalate recognition by solute binding protein TphC.

Biological degradation of Polyethylene terephthalate (PET) plastic and assimilation of the corresponding monomers ethylene glycol and terephthalate (TPA) into central metabolism offers an attractive route for bio-based molecular recycling and bioremediation applications. A key step is the cellular uptake of the non-permeable TPA into bacterial cells which has been shown to be dependent upon the presence of the key tphC gene. However, little is known from a biochemical and structural perspective about the encoded solute binding protein, TphC. Here, we report the biochemical and structural characterisation of TphC in both open and TPA-bound closed conformations. This analysis demonstrates the narrow ligand specificity of TphC towards aromatic para-substituted dicarboxylates, such as TPA and closely related analogues. Further phylogenetic and genomic context analysis of the tph genes reveals homologous operons as a genetic resource for future biotechnological and metabolic engineering efforts towards circular plastic bio-economy solutions.

Multi-omic Directed Discovery of Cellulosomes, Polysaccharide Utilization Loci, and Lignocellulases from an Enriched Rumen Anaerobic Consortium.

Lignocellulose is one of the most abundant renewable carbon sources, representing an alternative to petroleum for the production of fuel and chemicals. Nonetheless, the lignocellulose saccharification process, to release sugars for downstream applications, is one of the most crucial factors economically challenging to its use. The synergism required among the various carbohydrate-active enzymes (CAZymes) for efficient lignocellulose breakdown is often not satisfactorily achieved with an enzyme mixture from a single strain. To overcome this challenge, enrichment strategies can be applied to develop microbial communities with an efficient CAZyme arsenal, incorporating complementary and synergistic properties, to improve lignocellulose deconstruction. We report a comprehensive and deep analysis of an enriched rumen anaerobic consortium (ERAC) established on sugarcane bagasse (SB). The lignocellulolytic abilities of the ERAC were confirmed by analyzing the depolymerization of bagasse by scanning electron microscopy, enzymatic assays, and mass spectrometry. Taxonomic analysis based on 16S rRNA sequencing elucidated the community enrichment process, which was marked by a higher abundance of Firmicutes and Synergistetes species. Shotgun metagenomic sequencing of the ERAC disclosed 41 metagenome-assembled genomes (MAGs) harboring cellulosomes and polysaccharide utilization loci (PULs), along with a high diversity of CAZymes. The amino acid sequences of the majority of the predicted CAZymes (60% of the total) shared less than 90% identity with the sequences found in public databases. Additionally, a clostridial MAG identified in this study produced proteins during consortium development with scaffoldin domains and CAZymes appended to dockerin modules, thus representing a novel cellulosome-producing microorganism.IMPORTANCE The lignocellulolytic ERAC displays a unique set of plant polysaccharide-degrading enzymes (with multimodular characteristics), cellulosomal complexes, and PULs. The MAGs described here represent an expansion of the genetic content of rumen bacterial genomes dedicated to plant polysaccharide degradation, therefore providing a valuable resource for the development of biocatalytic toolbox strategies to be applied to lignocellulose-based biorefineries.

Development of High-Performance Whole Cell Biosensors Aided by Statistical Modeling.

Whole cell biosensors are genetic systems that link the presence of a chemical, or other stimulus, to a user-defined gene expression output for applications in sensing and control. However, the gene expression level of biosensor regulatory components required for optimal performance is nonintuitive, and classical iterative approaches do not efficiently explore multidimensional experimental space. To overcome these challenges, we used a design of experiments (DoE) methodology to efficiently map gene expression levels and provide biosensors with enhanced performance. This methodology was applied to two biosensors that respond to catabolic breakdown products of lignin biomass, protocatechuic acid and ferulic acid. Utilizing DoE we systematically modified biosensor dose-response behavior by increasing the maximum signal output (up to 30-fold increase), improving dynamic range (>500-fold), expanding the sensing range (∼4-orders of magnitude), increasing sensitivity (by >1500-fold), and modulated the slope of the curve to afford biosensors designs with both digital and analogue dose-response behavior. This DoE method shows promise for the optimization of regulatory systems and metabolic pathways constructed from novel, poorly characterized parts.

Contemporary Tools for Regulating Gene Expression in Bacteria.

Insights from novel mechanistic paradigms in gene expression control have led to the development of new gene expression systems for bioproduction, control, and sensing applications. Coupled with a greater understanding of synthetic burden and modern creative biodesign approaches, contemporary bacterial gene expression tools and systems are emerging that permit fine-tuning of expression, enabling greater predictability and maximisation of specific productivity, while minimising deleterious effects upon cell viability. These advances have been achieved by using a plethora of regulatory tools, operating at all levels of the so-called 'central dogma' of molecular biology. In this review, we discuss these gene regulation tools in the context of their design, prototyping, integration into expression systems, and biotechnological application.

Directed evolution of the PcaV allosteric transcription factor to generate a biosensor for aromatic aldehydes.

BACKGROUND: Transcription factor-based biosensors are useful tools for the detection of metabolites and industrially valuable molecules, and present many potential applications in biotechnology and biomedicine. However, the most common approach to develop biosensors relies on employing a limited set of naturally occurring allosteric transcription factors (aTFs). Therefore, altering the ligand specificity of aTFs towards the detection of new effectors is an important goal. RESULTS: Here, the PcaV repressor, a member of the MarR aTF family, was used to develop a biosensor for the detection of hydroxyl-substituted benzoic acids, including protocatechuic acid (PCA). The PCA biosensor was further subjected to directed evolution to alter its ligand specificity towards vanillin and other closely related aromatic aldehydes, to generate the Van2 biosensor. Ligand recognition of Van2 was explored in vitro using a range of biochemical and biophysical analyses, and extensive in vivo genetic-phenotypic analysis was performed to determine the role of each amino acid change upon biosensor performance. CONCLUSIONS: This is the first study to report directed evolution of a member of the MarR aTF family, and demonstrates the plasticity of the PCA biosensor by altering its ligand specificity to generate a biosensor for aromatic aldehydes.

Genetically encoded biosensors for lignocellulose valorization.

Modern society is hugely dependent on finite oil reserves for the supply of fuels and chemicals. Moving our dependence away from these unsustainable oil-based feedstocks to renewable ones is, therefore, a critical factor towards the development of a low carbon bioeconomy. Lignin derived from biomass feedstocks offers great potential as a renewable source of aromatic compounds if methods for its effective valorization can be developed. Synthetic biology and metabolic engineering offer the potential to synergistically enable the development of cell factories with novel biosynthetic routes to valuable chemicals from these sustainable sources. Pathway design and optimization is, however, a major bottleneck due to the lack of high-throughput methods capable of screening large libraries of genetic variants and the metabolic burden associated with bioproduction. Genetically encoded biosensors can provide a solution by transducing the target metabolite concentration into detectable signals to provide high-throughput phenotypic read-outs and allow dynamic pathway regulation. The development and application of biosensors in the discovery and engineering of efficient biocatalytic processes for the degradation, conversion, and valorization of lignin are paving the way towards a sustainable and economically viable biorefinery.

Tuning recombinant protein expression to match secretion capacity.

BACKGROUND: The secretion of recombinant disulfide-bond containing proteins into the periplasm of Gram-negative bacterial hosts, such as E. coli, has many advantages that can facilitate product isolation, quality and activity. However, the secretion machinery of E. coli has a limited capacity and can become overloaded, leading to cytoplasmic retention of product; which can negatively impact cell viability and biomass accumulation. Fine control over recombinant gene expression offers the potential to avoid this overload by matching expression levels to the host secretion capacity. RESULTS: Here we report the application of the RiboTite gene expression control system to achieve this by finely controlling cellular expression levels. The level of control afforded by this system allows cell viability to be maintained, permitting production of high-quality, active product with enhanced volumetric titres. CONCLUSIONS: The methods and systems reported expand the tools available for the production of disulfide-bond containing proteins, including antibody fragments, in bacterial hosts.

Rationalizing Context-Dependent Performance of Dynamic RNA Regulatory Devices.

The ability of RNA to sense, regulate, and store information is an attractive attribute for a variety of functional applications including the development of regulatory control devices for synthetic biology. RNA folding and function is known to be highly context sensitive, which limits the modularity and reuse of RNA regulatory devices to control different heterologous sequences and genes. We explored the cause and effect of sequence context sensitivity for translational ON riboswitches located in the 5' UTR, by constructing and screening a library of N-terminal synonymous codon variants. By altering the N-terminal codon usage we were able to obtain RNA devices with a broad range of functional performance properties (ON, OFF, fold-change). Linear regression and calculated metrics were used to rationalize the major determining features leading to optimal riboswitch performance, and to identify multiple interactions between the explanatory metrics. Finally, partial least squared (PLS) analysis was employed in order to understand the metrics and their respective effect on performance. This PLS model was shown to provide good explanation of our library. This study provides a novel multivariant analysis framework to rationalize the codon context performance of allosteric RNA-devices. The framework will also serve as a platform for future riboswitch context engineering endeavors.

Lignolytic-consortium omics analyses reveal novel genomes and pathways involved in lignin modification and valorization.

BACKGROUND: Lignin is a heterogeneous polymer representing a renewable source of aromatic and phenolic bio-derived products for the chemical industry. However, the inherent structural complexity and recalcitrance of lignin makes its conversion into valuable chemicals a challenge. Natural microbial communities produce biocatalysts derived from a large number of microorganisms, including those considered unculturable, which operate synergistically to perform a variety of bioconversion processes. Thus, metagenomic approaches are a powerful tool to reveal novel optimized metabolic pathways for lignin conversion and valorization. RESULTS: The lignin-degrading consortium (LigMet) was obtained from a sugarcane plantation soil sample. The LigMet taxonomical analyses (based on 16S rRNA) indicated prevalence of Proteobacteria, Actinobacteria and Firmicutes members, including the Alcaligenaceae and Micrococcaceae families, which were enriched in the LigMet compared to sugarcane soil. Analysis of global DNA sequencing revealed around 240,000 gene models, and 65 draft bacterial genomes were predicted. Along with depicting several peroxidases, dye-decolorizing peroxidases, laccases, carbohydrate esterases, and lignocellulosic auxiliary (redox) activities, the major pathways related to aromatic degradation were identified, including benzoate (or methylbenzoate) degradation to catechol (or methylcatechol), catechol ortho-cleavage, catechol meta-cleavage, and phthalate degradation. A novel Paenarthrobacter strain harboring eight gene clusters related to aromatic degradation was isolated from LigMet and was able to grow on lignin as major carbon source. Furthermore, a recombinant pathway for vanillin production was designed based on novel gene sequences coding for a feruloyl-CoA synthetase and an enoyl-CoA hydratase/aldolase retrieved from the metagenomic data set. CONCLUSION: The enrichment protocol described in the present study was successful for a microbial consortium establishment towards the lignin and aromatic metabolism, providing pathways and enzyme sets for synthetic biology engineering approaches. This work represents a pioneering study on lignin conversion and valorization strategies based on metagenomics, revealing several novel lignin conversion enzymes, aromatic-degrading bacterial genomes, and a novel bacterial strain of potential biotechnological interest. The validation of a biosynthetic route for vanillin synthesis confirmed the applicability of the targeted metagenome discovery approach for lignin valorization strategies.

Translation Stress Positively Regulates MscL-Dependent Excretion of Cytoplasmic Proteins.

The apparent mislocalization or excretion of cytoplasmic proteins is a commonly observed phenomenon in both bacteria and eukaryotes. However, reports on the mechanistic basis and the cellular function of this so-called "nonclassical protein secretion" are limited. Here we report that protein overexpression in recombinant cells and antibiotic-induced translation stress in wild-type Escherichia coli cells both lead to excretion of cytoplasmic protein (ECP). Condition-specific metabolomic and proteomic analyses, combined with genetic knockouts, indicate a role for both the large mechanosensitive channel (MscL) and the alternative ribosome rescue factor A (ArfA) in ECP. Collectively, the findings indicate that MscL-dependent protein excretion is positively regulated in response to both osmotic stress and arfA-mediated translational stress.IMPORTANCE Protein translocation is an essential feature of cellular organisms. Bacteria, like all single-cell organisms, interact with their environment by translocation of proteins across their cell membranes via dedicated secretion pathways. Proteins destined for secretion are directed toward the secretion pathways by the presence of specific signal peptides. This study demonstrates that under conditions of both osmotic stress and translation stress, E. coli cells undergo an excretion phenomenon whereby signal peptide-less proteins are translocated across both the inner and outer cell membranes into the extracellular environment. Confirming the presence of alternative translocation/excretion pathways and understanding their function and regulation are thus important for fundamental microbiology and biotechnology.

Optimization of Membrane Protein Production Using Titratable Strains of E. coli.

The heterologous expression of membrane proteins driven by T7 RNA polymerase in E. coli is often limited by a mismatch between the transcriptional and translational rates resulting in saturation of the Sec translocon and non-insertion of the membrane protein. In order to optimize the levels of folded, functional inserted protein, it is important to correct this mismatch. In this protocol, we describe the use of titratable strains of E. coli where two small-molecule inducers are used in a bi-variate analysis to optimize the expression levels by fine tuning the transcriptional and translational rates of an eGFP-tagged membrane protein.

Partial Least Squares with Structured Output for Modelling the Metabolomics Data Obtained from Complex Experimental Designs: A Study into the Y-Block Coding.

Partial least squares (PLS) is one of the most commonly used supervised modelling approaches for analysing multivariate metabolomics data. PLS is typically employed as either a regression model (PLS-R) or a classification model (PLS-DA). However, in metabolomics studies it is common to investigate multiple, potentially interacting, factors simultaneously following a specific experimental design. Such data often cannot be considered as a "pure" regression or a classification problem. Nevertheless, these data have often still been treated as a regression or classification problem and this could lead to ambiguous results. In this study, we investigated the feasibility of designing a hybrid target matrix Y that better reflects the experimental design than simple regression or binary class membership coding commonly used in PLS modelling. The new design of Y coding was based on the same principle used by structural modelling in machine learning techniques. Two real metabolomics datasets were used as examples to illustrate how the new Y coding can improve the interpretability of the PLS model compared to classic regression/classification coding.

Development and substrate specificity screening of an in vivo biosensor for the detection of biomass derived aromatic chemical building blocks.

Measuring substrate and/or product concentration can create a major bottleneck for synthetic and biosynthetic processes. Here we report the development and substrate screening of a whole cell biosensor to detect biomass-derived aromatic chemical building blocks, supporting the use of sustainable feedstocks in the bulk and fine chemical industries.

Metabolomic analysis of riboswitch containing E. coli recombinant expression system.

In this study we have employed metabolomics approaches to understand the metabolic effects of producing enhanced green fluorescent protein (eGFP) as a recombinant protein in Escherichia coli cells. This metabolic burden analysis was performed against a number of recombinant expression systems and control strains and included: (i) standard transcriptional recombinant expression control system BL21(DE3) with the expression plasmid pET-eGFP, (ii) the recently developed dual transcriptional-translational recombinant expression control strain BL21(IL3), with pET-eGFP, (iii) BL21(DE3) with an empty expression plasmid pET, (iv) BL21(IL3) with an empty expression plasmid, and (v) BL21(DE3) without an expression plasmid; all strains were cultured under various induction conditions. The growth profiles of all strains together with the results gathered by the analysis of the Fourier transform infrared (FT-IR) spectroscopy data, identified IPTG-dependent induction as the dominant factor hampering cellular growth and metabolism, which was in general agreement with the findings of GC-MS analysis of cell extracts and media samples. In addition, the exposure of host cells to the synthetic inducer ligand, pyrimido[4,5-d] pyrimidine-2,4-diamine (PPDA), of the orthogonal riboswitch containing expression system (BL21(IL3)) did not display any detrimental effects, and its detected levels in all the samples were at similar levels, emphasising the inability of the cells to metabolise PPDA. The overall results obtained in this study suggested that although the BL21(DE3)-EGFP and BL21(IL3)-EGFP strains produced comparable levels of recombinant eGFP, the presence of the orthogonal riboswitch seemed to be moderating the metabolic burden of eGFP production in the cells enabling higher biomass yield, whilst providing a greater level of control over protein expression.