Rapid spectrophotometric detection for optimized production of landomycins and characterization of their therapeutic potential.

Microbial-derived natural products remain a major source of structurally diverse bioactive compounds and chemical scaffolds that have the potential as new therapeutics to target drug-resistant pathogens and cancers. In particular, genome mining has revealed the vast number of cryptic or low-yield biosynthetic gene clusters in the genus Streptomyces. However, low natural product yields-improvements to which have been hindered by the lack of high throughput methods-have slowed the discovery and development of many potential therapeutics. Here, we describe our efforts to improve yields of landomycins-angucycline family polyketides under investigation as cancer therapeutics-by a genetically modified Streptomyces cyanogenus 136. After simplifying the extraction process from S. cyanogenus cultures, we identified a wavelength at which the major landomycin products are absorbed in culture extracts, which we used to systematically explore culture medium compositions to improve total landomycin titers. Through correlational analysis, we simplified the culture optimization process by identifying an alternative wavelength at which culture supernatants absorb yet is representative of total landomycin titers. Using the subsequently improved sample throughput, we explored landomycin production during the culturing process to further increase landomycin yield and reduce culture time. Testing the antimicrobial activity of the isolated landomycins, we report broad inhibition of Gram-positive bacteria, inhibition of fungi by landomycinone, and broad landomycin resistance by Gram-negative bacteria that is likely mediated by the exclusion of landomycins by the bacterial membrane. Finally, the anticancer activity of the isolated landomycins against A549 lung carcinoma cells agrees with previous reports on other cell lines that glycan chain length correlates with activity. Given the prevalence of natural products produced by Streptomyces, as well as the light-absorbing moieties common to bioactive natural products and their metabolic precursors, our method is relevant to improving the yields of other natural products of interest.

Specific codons control cellular resources and fitness.

As cellular engineering progresses from simply overexpressing proteins to imparting complex phenotypes through multigene expression, judicious appropriation of cellular resources is essential. Since codon use is degenerate and biased, codons may control cellular resources at a translational level. We investigate how partitioning transfer RNA (tRNA) resources by incorporating dissimilar codon usage can drastically alter interdependence of expression level and burden on the host. By isolating the effect of individual codons' use during translation elongation while eliminating confounding factors, we show that codon choice can trans-regulate fitness of the host and expression of other heterologous or native genes. We correlate specific codon usage patterns with host fitness and derive a coding scheme for multigene expression called the Codon Health Index (CHI, χ). This empirically derived coding scheme (χ) enables the design of multigene expression systems that avoid catastrophic cellular burden and is robust across several proteins and conditions.

Rapid spectrophotometric detection for optimized production of landomycins and characterization of their therapeutic potential.

Microbial derived natural products remain a major source of structurally diverse bioactive compounds and chemical scaffolds that have potential as new therapeutics to target drug resistant pathogens and cancers. In particular, genome mining has revealed the vast number of cryptic or low yield biosynthetic gene clusters in the genus Streptomyces . Here, we describe our efforts to improve yields of landomycins - angucycline family polyketides under investigation as cancer therapeutics - by a genetically modified Streptomyces cyanogenus 136. After simplifying the extraction process from S. cyanogenus cultures, we identified a wavelength at which the major landomycin products absorb in culture extracts, which we used to systematically explore culture medium compositions to improve total landomycin titers. Through correlational analysis, we simplified the culture optimization process by identifying an alternative wavelength at which culture supernatants absorb yet is representative of total landomycin titers. Using the subsequently improved sample throughput, we explored landomycin production during the culturing process to further increase landomycin yield and reduce culture time. Testing the antimicrobial activity of the isolated landomycins, we report broad inhibition of Gram-positive bacteria, inhibition of fungi by landomycinone, and broad landomycin resistance by Gram-negative bacteria that is likely mediated by exclusion of landomycins by the bacterial membrane. Finally, the anticancer activity of the isolated landomycins against A549 lung carcinoma cells agrees with previous reports on other cell lines that glycan chain length correlates with activity. Given the prevalence of natural products produced by Streptomyces , as well as the light-absorbing moieties common to bioactive natural products and their metabolic precursors, our method is relevant to improving the yields of other natural products of interest.

Integration of metabolism and regulation reveals rapid adaptability to growth on non-native substrates.

Engineering synthetic heterotrophy is a key to the efficient bio-based valorization of renewable and waste substrates. Among these, engineering hemicellulosic pentose utilization has been well-explored in Saccharomyces cerevisiae (yeast) over several decades-yet the answer to what makes their utilization inherently recalcitrant remains elusive. Through implementation of a semi-synthetic regulon, we find that harmonizing cellular and engineering objectives are a key to obtaining highest growth rates and yields with minimal metabolic engineering effort. Concurrently, results indicate that "extrinsic" factors-specifically, upstream genes that direct flux of pentoses into central carbon metabolism-are rate-limiting. We also reveal that yeast metabolism is innately highly adaptable to rapid growth on non-native substrates and that systems metabolic engineering (i.e., functional genomics, network modeling, etc.) is largely unnecessary. Overall, this work provides an alternate, novel, holistic (and yet minimalistic) approach based on integrating non-native metabolic genes with a native regulon system.

Towards universal synthetic heterotrophy using a metabolic coordinator.

Engineering the utilization of non-native substrates, or synthetic heterotrophy, in proven industrial microbes such as Saccharomyces cerevisiae represents an opportunity to valorize plentiful and renewable sources of carbon and energy as inputs to bioprocesses. We previously demonstrated that activation of the galactose (GAL) regulon, a regulatory structure used by this yeast to coordinate substrate utilization with biomass formation during growth on galactose, during growth on the non-native substrate xylose results in a vastly altered gene expression profile and faster growth compared with constitutive overexpression of the same heterologous catabolic pathway. However, this effort involved the creation of a xylose-inducible variant of Gal3p (Gal3pSyn4.1), the sensor protein of the GAL regulon, preventing this semi-synthetic regulon approach from being easily adapted to additional non-native substrates. Here, we report the construction of a variant Gal3pMC (metabolic coordinator) that exhibits robust GAL regulon activation in the presence of structurally diverse substrates and recapitulates the dynamics of the native system. Multiple molecular modeling studies suggest that Gal3pMC occupies conformational states corresponding to galactose-bound Gal3p in an inducer-independent manner. Using Gal3pMC to test a regulon approach to the assimilation of the non-native lignocellulosic sugars xylose, arabinose, and cellobiose yields higher growth rates and final cell densities when compared with a constitutive overexpression of the same set of catabolic genes. The subsequent demonstration of rapid and complete co-utilization of all three non-native substrates suggests that Gal3pMC-mediated dynamic global gene expression changes by GAL regulon activation may be universally beneficial for engineering synthetic heterotrophy.

Flow cytometric evaluation of yeast-bacterial cell-cell interactions.

Synthetic cell-cell interaction systems can be useful for understanding multicellular communities or for screening binding molecules. We adapt a previously characterized set of synthetic cognate nanobody-antigen pairs to a yeast-bacteria coincubation format and use flow cytometry to evaluate cell-cell interactions mediated by binding between surface-displayed molecules. We further use fluorescence-activated cell sorting to enrich a specific yeast-displayed nanobody within a mixed yeast-display population. Finally, we demonstrate that this system supports the characterization of a therapeutically relevant nanobody-antigen interaction: a previously discovered nanobody that binds to the intimin protein expressed on the surface of enterohemorrhagic Escherichia coli. Overall, our findings indicate that the yeast-bacteria format supports efficient evaluation of ligand-target interactions. With further development, this format may facilitate systematic characterization and high-throughput discovery of bacterial surface-binding molecules.

A Silk-Based Platform to Stabilize Phenylalanine Ammonia-lyase for Orally Administered Enzyme Replacement Therapy.

Phenylalanine ammonia-lyase (PAL) has gained attention in recent years for the treatment of phenylketonuria (PKU), a genetic disorder that affects ∼1 in 15 000 individuals globally. However, the enzyme is easily degraded by proteases, unstable at room temperature, and currently administered in PKU patients as daily subcutaneous injections. We report here the stabilization of the PAL from Anabaena variabilis, which is currently used to formulate pegvaliase, through incorporation in a silk fibroin matrix. The combination with silk stabilizes PAL at 37 °C. In addition, in vitro studies showed that inclusion in a silk matrix preserves the biological activity of the enzyme in simulated intestinal fluid, which will enable oral administration of PAL to treat PKU.

Cheating the Cheater: Suppressing False-Positive Enrichment during Biosensor-Guided Biocatalyst Engineering.

Transcription factor (TF)-based biosensors are very desirable reagents for high-throughput enzyme and strain engineering campaigns. Despite their potential, they are often difficult to deploy effectively as the small molecules being detected can leak out of high-producer cells, into low-producer cells, and activate the biosensor therein. This crosstalk leads to the overrepresentation of false-positive/cheater cells in the enriched population. While the host cell can be engineered to minimize crosstalk (e.g., by deleting responsible transporters), this is not easily applicable to all molecules of interest, particularly those that can diffuse passively. One such biosensor recently reported for trans-cinnamic acid (tCA) suffers from crosstalk when used for phenylalanine ammonia-lyase (PAL) enzyme engineering by directed evolution. We report that desensitizing the biosensor (i.e., increasing the limit of detection) suppresses cheater population enrichment. Furthermore, we show that, if we couple the biosensor-based screen with an orthogonal prescreen that eliminates a large fraction of true negatives, we can successfully reduce the cheater population during the fluorescence-activated cell sorting. Using the approach developed here, we were successfully able to isolate PAL variants with ∼70% higher kcat after a single sort. These mutants have tremendous potential in phenylketonuria (PKU) treatment and flavonoid production.

In-depth Sequence-Function Characterization Reveals Multiple Pathways to Enhance Enzymatic Activity.

Deep mutational scanning (DMS) has recently emerged as a powerful method to study protein sequence-function relationships but it has not been well-explored as a guide to enzyme engineering and identifying pathways by which their catalytic cycle may be improved. We report such a demonstration in this work using a Phenylalanine ammonia-lyase (PAL), which deaminates L-phenylalanine to trans-cinnamic acid and has widespread application in chemo-enzymatic synthesis, agriculture, and medicine. In particular, the PAL from Anabaena variabilis (AvPAL*) has garnered significant attention as the active ingredient in Pegvaliase®, the only FDA-approved drug treating classical Phenylketonuria (PKU). Although an extensive body of literature exists on the structure, substrate-specificity, and catalytic cycle, protein-wide sequence determinants of function remain unknown, as do intermediate reaction steps that limit turnover frequency, all of which has hindered rational engineering of these enzymes. Here, we created a detailed sequence-function landscape of AvPAL* by performing DMS and revealed 112 mutations at 79 functionally relevant sites that affect a positive change in enzyme fitness. Using fitness values and structure-function analysis, we picked a subset of positions for comprehensive single- and multi-site saturation mutagenesis and identified combinations of mutations that led to improved reaction kinetics in cell-free and cellular contexts. We then performed QM/MM and MD to understand the mechanistic role of the most beneficial mutations and observed that different mutants confer improvements via different mechanisms, including stabilizing transition and intermediate states, improving substrate diffusion into the active site, and decreasing product inhibition. This work demonstrates how DMS can be combined with computational analysis to effectively identify significant mutations that enhance enzyme activity along with the underlying mechanisms by which these mutations confer their benefit.

Analysis of metabolic network disruption in engineered microbial hosts due to enzyme promiscuity.

Increasing understanding of metabolic and regulatory networks underlying microbial physiology has enabled creation of progressively more complex synthetic biological systems for biochemical, biomedical, agricultural, and environmental applications. However, despite best efforts, confounding phenotypes still emerge from unforeseen interplay between biological parts, and the design of robust and modular biological systems remains elusive. Such interactions are difficult to predict when designing synthetic systems and may manifest during experimental testing as inefficiencies that need to be overcome. Transforming organisms such as Escherichia coli into microbial factories is achieved via several engineering strategies, used individually or in combination, with the goal of maximizing the production of chosen target compounds. One technique relies on suppressing or overexpressing selected genes; another involves introducing heterologous enzymes into a microbial host. These modifications steer mass flux towards the set of desired metabolites but may create unexpected interactions. In this work, we develop a computational method, termed Metabolic Disruption Workflow (MDFlow), for discovering interactions and network disruptions arising from enzyme promiscuity - the ability of enzymes to act on a wide range of molecules that are structurally similar to their native substrates. We apply MDFlow to two experimentally verified cases where strains with essential genes knocked out are rescued by interactions resulting from overexpression of one or more other genes. We demonstrate how enzyme promiscuity may aid cells in adapting to disruptions of essential metabolic functions. We then apply MDFlow to predict and evaluate a number of putative promiscuous reactions that can interfere with two heterologous pathways designed for 3-hydroxypropionic acid (3-HP) production. Using MDFlow, we can identify putative enzyme promiscuity and the subsequent formation of unintended and undesirable byproducts that are not only disruptive to the host metabolism but also to the intended end-objective of high biosynthetic productivity and yield. As we demonstrate, MDFlow provides an innovative workflow to systematically identify incompatibilities between the native metabolism of the host and its engineered modifications due to enzyme promiscuity.

A quantitative model for metabolic intervention using gut microbes.

As medicine shifts toward precision-based and personalized therapeutics, utilizing more complex biomolecules to treat increasingly difficult and rare conditions, microorganisms provide an avenue for realizing the production and processing necessary for novel drug pipelines. More so, probiotic microbes can be co-opted to deliver therapeutics by oral administration as living drugs, able to survive and safely transit the digestive tract. As living therapeutics are in their nascency, traditional pharmacokinetic-pharmacodynamic (PK-PD) models for evaluating drug candidates are not appropriate for this novel platform. Using a living therapeutic in late-stage clinical development for phenylketonuria (PKU) as a case study, we adapt traditional oral drug delivery models to properly evaluate and inform the engineering of living therapeutics. We develop the adapted for living therapeutics compartmental absorption and transit (ALT-CAT) model to provide metrics for drug efficacy across nine age groups of PKU patients and evaluate model parameters that are influenced by patient physiology, microbe selection and therapeutic production, and dosing formulations. In particular, the ALT-CAT model describes the mathematical framework to model the behavior of orally delivered engineered bacteria that act as living therapeutics by adapting similar methods that have been developed and widely-used for small molecular drug delivery and absorption.

Engineered lactobacilli display anti-biofilm and growth suppressing activities against Pseudomonas aeruginosa.

Biofilms are an emerging target for new therapeutics in the effort to address the continued increase in resistance and tolerance to traditional antimicrobials. In particular, the distinct nature of the biofilm growth state often means that traditional antimcirobials, developed to combat planktonic cells, are ineffective. Biofilm treatments are designed to both reduce pathogen load at an infection site and decrease the development of resistance by rendering the embedded organisms more susceptible to treatment at lower antimicrobial concentrations. In this work, we developed a new antimicrobial treatment modality using engineered lactic acid bacteria (LAB). We first characterized the natural capacity of two lactobacilli, L. plantarum and L. rhamnosus, to inhibit P. aeruginosa growth, biofilm formation, and biofilm viability, which we found to be dependent upon the low pH generated during culture of the LAB. We further engineered these LAB to secrete enzymes known to degrade P. aeruginosa biofilms and show that our best performing engineered LAB, secreting a pathogen-derived enzyme (PelAh), degrades up to 85% of P. aeruginosa biofilm.

Characterization of a membrane enzymatic complex for heterologous production of poly-γ-glutamate in E. coli.

Poly-γ-glutamic acid (PGA) produced by many Bacillus species is a polymer with many distinct and desirable characteristics. However, the multi-subunit enzymatic complex responsible for its synthesis, PGA Synthetase (PGS), has not been well characterized yet, in native nor in recombinant contexts. Elucidating structural and functional properties are crucial for future engineering efforts aimed at altering the catalytic properties of this enzyme. This study focuses on expressing the enzyme heterologously in the Escherichia coli membrane and characterizing localization, orientation, and activity of this heterooligomeric enzyme complex. In E. coli, we were able to produce high molecular weight PGA polymers with minimal degradation at titers of approximately 13 â€‹mg/L in deep-well microtiter batch cultures. Using fusion proteins, we observed, for the first time, the association and orientation of the different subunits with the inner cell membrane. These results provide fundamental structural information on this poorly studied enzyme complex and will aid future fundamental studies and engineering efforts.

Directed evolution of Anabaena variabilis phenylalanine ammonia-lyase (PAL) identifies mutants with enhanced activities.

There is broad interest in engineering phenylalanine ammonia-lyase (PAL) for its biocatalytic applications in industry and medicine. While site-specific mutagenesis has been employed to improve PAL stability or substrate specificity, combinatorial techniques are poorly explored. Here, we report development of a directed evolution technique to engineer PAL enzymes. Central to this approach is a high-throughput enrichment that couples E. coli growth to PAL activity. Starting with the PAL used in the formulation of pegvaliase for PKU therapy, we report previously unidentified mutations that increase turnover frequency almost twofold after only a single round of engineering.

Quantifying and Engineering Mucus Adhesion of Probiotics.

Mucus in the gastrointestinal (GI) tract is the primary point-of-interaction between humans and their gut microbiota. This intimates that mucus not only ensures protection against endogenous and exogenous opportunists but also provisions for the human microbiota to reside and flourish. With the emergence of living therapeutics, engineered microbes can deliver and produce increasingly complex medicine, and controlling the mucoadhesive properties of different microbial chassis can dictate dose-response in a patient. Here we present a redesigned, in vitro, plate-based assay to measure the mucus adhesion of various probiotics. Cell-mucus interactions were isolated by immobilizing mucus to the plate surface. Binding parameters were derived for each probiotic strain by measuring cell adhesion over a wide range of cell concentrations, providing dose-dependent adhesion metrics. Surface proteins and cell components known to influence mucoadhesion were then heterologously expressed or altered in Lactococcus lactis MG1363 and Escherichia coli Nissle 1917 to control mucus-binding capacity, avidity, and cooperativity.

Galactose to tagatose isomerization at moderate temperatures with high conversion and productivity.

There are many industrially-relevant enzymes that while active, are severely limited by thermodynamic, kinetic, or stability issues (isomerases, lyases, transglycosidases). In this work, we study Lactobacillus sakei L-arabinose isomerase (LsLAI) for D-galactose to D-tagatose isomerization-that is limited by all three reaction parameters. The enzyme demonstrates low catalytic efficiency, low thermostability at temperatures > 40 °C, and equilibrium conversion < 50%. After exploring several strategies to overcome these limitations, we show that encapsulating LsLAI in gram-positive Lactobacillus plantarum that is chemically permeabilized enables reactions at high rates, high conversions, and elevated temperatures. In a batch process, this system enables ~ 50% conversion in 4 h starting with 300 mM galactose (an average productivity of 37 mM h-1), and 85% conversion in 48 h. We suggest that such an approach may be invaluable for other enzymatic processes that are similarly kinetically-, thermodynamically-, and/or stability-limited.

Towards creating an extended metabolic model (EMM) for E. coli using enzyme promiscuity prediction and metabolomics data.

BACKGROUND: Metabolic models are indispensable in guiding cellular engineering and in advancing our understanding of systems biology. As not all enzymatic activities are fully known and/or annotated, metabolic models remain incomplete, resulting in suboptimal computational analysis and leading to unexpected experimental results. We posit that one major source of unaccounted metabolism is promiscuous enzymatic activity. It is now well-accepted that most, if not all, enzymes are promiscuous-i.e., they transform substrates other than their primary substrate. However, there have been no systematic analyses of genome-scale metabolic models to predict putative reactions and/or metabolites that arise from enzyme promiscuity. RESULTS: Our workflow utilizes PROXIMAL-a tool that uses reactant-product transformation patterns from the KEGG database-to predict putative structural modifications due to promiscuous enzymes. Using iML1515 as a model system, we first utilized a computational workflow, referred to as Extended Metabolite Model Annotation (EMMA), to predict promiscuous reactions catalyzed, and metabolites produced, by natively encoded enzymes in Escherichia coli. We predict hundreds of new metabolites that can be used to augment iML1515. We then validated our method by comparing predicted metabolites with the Escherichia coli Metabolome Database (ECMDB). CONCLUSIONS: We utilized EMMA to augment the iML1515 metabolic model to more fully reflect cellular metabolic activity. This workflow uses enzyme promiscuity as basis to predict hundreds of reactions and metabolites that may exist in E. coli but may have not been documented in iML1515 or other databases. We provide detailed analysis of 23 predicted reactions and 16 associated metabolites. Interestingly, nine of these metabolites, which are in ECMDB, have not previously been documented in any other E. coli databases. Four of the predicted reactions provide putative transformations parallel to those already in iML1515. We suggest adding predicted metabolites and reactions to iML1515 to create an extended metabolic model (EMM) for E. coli.

Establishing synthesis pathway-host compatibility via enzyme solubility.

Current pathway synthesis tools identify possible pathways that can be added to a host to produce the desired target molecule through the exploration of abstract metabolic and reaction network space. However, not many of these tools explore gene-level information required to physically realize the identified synthesis pathways, and none explore enzyme-host compatibility. Developing tools that address this disconnect between abstract reactions/metabolic design space and physical genetic sequence design space will enable expedited experimental efforts that avoid exploring unprofitable synthesis pathways. This work describes a workflow, termed Probabilistic Pathway Assembly with Solubility Confidence Scores (ProPASS), which links synthesis pathway construction with the exploration of the physical design space as imposed by the availability of enzymes with predicted characterized activities within the host. Predicted protein solubility propensity scores are used as a confidence level to quantify the compatibility of each pathway enzyme with the host Escherichia coli (E. coli). This study also presents a database, termed Protein Solubility Database (ProSol DB), which provides solubility confidence scores in E. coli for 240,016 characterized enzymes obtained from UniProtKB/Swiss-Prot. The utility of ProPASS is demonstrated by generating genetic implementations of heterologous synthesis pathways in E. coli that target several commercially useful biomolecules.

Pentose Metabolism in Saccharomyces cerevisiae: The Need to Engineer Global Regulatory Systems.

Extending the host substrate range of industrially relevant microbes, such as Saccharomyces cerevisiae, has been a highly-active area of research since the conception of metabolic engineering. Yet, rational strategies that enable non-native substrate utilization in this yeast without the need for combinatorial and/or evolutionary techniques are underdeveloped. Herein, this review focuses on pentose metabolism in S. cerevisiae as a case study to highlight the challenges in this field. In the last three decades, work has focused on expressing exogenous pentose metabolizing enzymes as well as endogenous enzymes for effective pentose assimilation, growth, and biofuel production. The engineering strategies that are employed for pentose assimilation in this yeast are reviewed, and compared with metabolism and regulation of native sugar, galactose. In the case of galactose metabolism, multiple signals regulate and aid growth in the presence of the sugar. However, for pentoses that are non-native, it is unclear if similar growth and regulatory signals are activated. Such a comparative analysis aids in identifying missing links in xylose and arabinose utilization. While research on pentose metabolism have mostly concentrated on pathway level optimization, recent transcriptomics analyses highlight the need to consider more global regulatory, structural, and signaling components.

Synthetic Biology Approaches to Engineer Probiotics and Members of the Human Microbiota for Biomedical Applications.

An increasing number of studies have strongly correlated the composition of the human microbiota with many human health conditions and, in several cases, have shown that manipulating the microbiota directly affects health. These insights have generated significant interest in engineering indigenous microbiota community members and nonresident probiotic bacteria as biotic diagnostics and therapeutics that can probe and improve human health. In this review, we discuss recent advances in synthetic biology to engineer commensal and probiotic lactic acid bacteria, bifidobacteria, and Bacteroides for these purposes, and we provide our perspective on the future potential of these technologies.