Browsing by Author "Lynch, Michael D"

Protein-based drugs are becoming increasingly important both therapeutically and economically. However, these drugs are complex and costly to manufacture, making them difficult to access for many patients and not feasible for disease indications requiring large volumes and low costs. Therefore, advances are needed in protein drug manufacturing and especially in downstream processing, which represents the greatest bottleneck in modern protein drug processes. Here, we present a range of new protein purification methods as well as critical analyses of existing methods, focusing on separations that exploit changes in chemical phase as a low-cost alternative to chromatography. First, we develop a low-cost and highly scalable purification method for the clinical-stage antiviral Griffithsin. We show that the method dramatically improves upon the current process for production of clinical trial material. Second, we extend the Griffithsin purification method by scaling it up and integrating it with an auto-inducible cell lysis method, increasing purification performance enough to enable a complete clinical-quality process without any conventional chromatography. Finally, we conduct a meta-analysis of phase change-based protein purification methods. We show that, contrary to the common assumption in the field, the major barrier to adoption of these methods is cost rather than purification performance, and we identify for the first time the key factors driving purification costs across a wide range of such methods.

Malonyl-CoA (malonyl-CoA) is a platform chemical that serves as a precursor for a wide range of commercial products and pharmaceutical intermediates. In E. coli, malonyl-CoA levels are tightly regulated to remain at low levels. Two Stage Dynamic Metabolic Control (DMC) is a tool previously demonstrated to improve desired metabolite flux for several products. This work leverages DMC to improve malonyl-CoA fluxes. Specifically, we demonstrate coordinated dynamic reductions in the activities of fabI (enoyl-ACP reductase), gltA (citrate synthase), zwf (glucose-6-phosphate dehydrogenase) and glnB (nitrogen regulatory protein PII-1), during stationary phase lead to synergistic improvements in malonyl-CoA flux and the production of malonyl-CoA dependent products, 1,3,6,8-tetrahydroxynaphthalene (THN), Triacetic Lactone (TAL), and Phloroglucinol (PG). We also discuss the unique set of limitations that were observed for both TAL and PG biosynthesis as well as the strategies that were tested to overcome them. Additionally, we provide a historical review of the challenges associated with the production of Phloroglucinol. Finally, we end with a critical review focused on the bioproduction of an Acetyl-CoA and Succinyl-CoA derived product, Adipic Acid, to give perspective to common challenges associated with biobased product development.

Increasing concerns over the environmental impact and long-term sustainability of human economic activity has motivated a search for less resource-intensive methods for the manufacture of chemicals and generation of energy. Bio-based approaches are an alternative to traditional petroleum-based methods with the potential for significantly reducing the environmental impact of these industries. However, there are major challenges to making bio-based manufacture of chemicals cost-competitive with petroleum-based approaches. Optimization of rate, titer, and yield, and predictably transferring results from lab to industrial scales remain iterative processes that are expensive and slow. Development of microbial strains that produce generalizable “platform” metabolites can help address these challenges by allowing for high production of a metabolite that can be converted to multiple chemicals of industrial importance with subsequent minor genetic modifications to the strain. This work describes development of microbes for high production of the platform metabolite malonyl-CoA. It provides a biosynthetic route to industrially important chemicals including fatty acids, waxes, solvents, nutrients and pharmaceticals. Its potential has been recognized for some time, but being the major precursor for growth-essential fatty acid synthase made deleting competition for the substrate challenging.

A recently developed strategy called MOMENTuM (Microbial Optimization via Metabolic Network Minimization) helps address these issues and revisit the platform potential of this metabolite. In it, growth-decoupling of the product pathway is achieved by inducing product biosynthesis in stationary cells with nutrient limitation. Synthetic Metabolic Valves add or remove reactions from the network, leading to a customizable reorganization of metabolic flux. Using this approach, strains for improved malonyl-CoA product generation were identified for compounds of two different chemical classes and downstream uses. This provides supports the platform concept and the generalizability of the SMV-based improvements across products and pathways.

Metabolic engineering is an effective strategy to optimize the biosynthesis of chemical molecules in genetically modified microbes. However, many current metabolic engineering strategies are limited by the requirements for cellular growth. To further optimize cell factories and overcome this limitation, we have applied 2-stage dynamic metabolic control strategies to optimize the biosynthesis of several compounds in E. coli. Using this strategy, cells grow without being impacted by product biosynthesis. We use phosphate depletion as a trigger to both force cells into a stationary production stage and initiate product synthesis. Phosphate depletion also dynamically removes enzymes involved in competitive or inhibitory metabolic pathways. This is accomplished by both inhibiting new transcription with CRISPR interference and degrading existing proteins via DAS+4 degron mediated proteolysis. Through my work, we demonstrate that the implementation of 2-stage dynamic metabolic control can indeed improve the biosynthesis of several small molecule chemicals in engineered E. coli, including: xylitol, citramalate and ethylene glycol. Rates, titers and yields were improved significantly. In addition, my work explored the mechanisms underlying improvements in performance. Specifically, we conclude that dynamic dysregulation of feedback control over central metabolism can lead to greatly improved stationary phase sugar uptake rates and pathway fluxes.

Since being developed as a tool in 2012, CRISPR-Cas9 and other CRISPR systems have revolutionized the way we manipulate biology. CRISPR systems broadly rely on a programmable guide RNA (gRNA) to enable targeted nuclease activity. Additionally, the ability to target a protein to a specific sequence of DNA has enabled a myriad of applications, including transcriptional silencing and/or activation, single base editing and targeted transposase activity. However, there remains a gap in knowledge as to what factors influence the activity of these systems. The gRNA sequence has been shown to at least partially predict activity but the mechanism behind this is not well understood. In addition, other contextual factors such as DNA repair, target accessibility, and others may play a role. Here, we present factors that influence Cas9 activity in E. coli and other organisms. Additionally, we find that gRNA sequence influences activity in large part by determining how fast Cas9 finds the target site. Together, the work presented improves our understanding of Cas9 and could lead to better gRNA prediction algorithms and new routes to improve Cas9 on-target activity.

Targeted protein degradation (TPD) is an emerging therapeutic strategy with the potential to degrade aberrant proteins. However, the most commonly used TPD technologies leverage proximity-induced ubiquitination and rely on the recruitment of cellular degradation machinery. This fundamentally restricts TPD from being applied in vitro and underscores the need for alternative TPD technologies that can catalyze protein degradation without cellular factors. Here we meet this demand by introducing nanobody-targeted proteolytic chimeras (NanoPROCs), a novel class of proteases with highly specific substrate targeting. NanoPROCs harness nanobodies as the basis of their substrate targeting and include a minimal catalytic structure derived from proteases, enabling them to degrade proteins autonomously. In this work, we developed a computational pipeline for the design of novel NanoPROCs, designed a substrate that can be used to assay for novel NanoPROC activity, and explored the interchangeability of NanoPROC components. Our results support the assembly of stable NanoPROCs from multiple nanobodies and proteolytic domains, further suggesting that NanoPROCs can be tailored for desired substrate and cleavage specificities. As such, we predict that NanoPROCs can be more broadly applied to industrial manufacturing, diagnostic development, and therapeutic contexts than current TPD technologies. Specifically, the ability to autonomously degrade proteins enables NanoPROCs to be applied to peptide purification workflows. In a clinical context, the potential for NanoPROCs to autonomously degrade proteins in the extracellular space enables infectious disease oriented applications, such as viral receptor cleavage and bacterial toxin degradation. Overall, the introduction of NanoPROCs represents a significant advancement in the field of targeted protein degradation, offering a versatile and autonomous approach to protein degradation that can be applied across numerous industrial and disease contexts.

HIV infections remain a major public health issue with no current cure: in 2015, the disease led to the deaths of 1.1 million people [1]. A viable preventative is Griffithsin (GRFT), a lectin that binds and neutralizes the HIV viral envelope by blocking glycoproteins that are needed for the virus to recognize target cells. The protein is being studied as a highly effective pre-exposure prophylactic therapy [2]. However for it to become a preventative, particularly in the developing world, product cost and stability are key barriers that need to be resolved before widespread use. We have developed an initial and low cost downstream process that requires three steps to purify GRFT from E. coli fermentations taking advantage of the protein’s unique melting temperature, isoelectric point, and size. SDS-PAGE revealed that the purification steps designed are capable of retaining GRFT while LS/MS/MS proteomics has proven enrichment of GRFT throughout the process. This study also successfully establishes a baseline of what proteins act as contaminants identifying 22 top gene deletion candidates guiding future strain engineering efforts.

Since the inception of recombinant protein expression, this technique has revolutionized our everyday lives with the number of protein products we have at our disposal ranging from household products to pharmaceuticals. E. coli was the first host used for recombinant protein expression and it has remained a mainstay expression host in biotechnology. However, the utility of E. coli as an expression host is limited by challenges that, if addressed, would make it a more suitable host for a wider variety of proteins, and thereby catalyze the translation of more protein products. Here, we address these challenges with dynamic control of the E. coli metabolism. This approach involves decoupling cell growth and protein expression and altering metabolism exclusively in the production phase. With this dynamic tool we have been able to: (1) engineer E. coli to improve the cytoplasmic solubility of redox sensitive proteins that are prone to aggregation, (2) improve the growth robustness of these engineered strains over the current state the art, (3) simply the bioprocess to purify these redox sensitive proteins, (4) identify uncharacterized redox regulation that impacts protein expression. Additionally, we provide a historical overview of biotechnological advances associated with a class of biopharmaceuticals, enzyme-based therapies, which have underutilized potential. Cumulatively, this work analyzes development trends of biologics, recognizes gaps in therapeutic and production capabilities, and provides solutions to challenges associated with redox sensitive protein expression and purification in E. coli.

The market for proteins has been constantly increasing for many different applications, such as protein-based drugs. However, protein production in E. coli, the most widely used recombinant host, has remained fundamentally the same since its inception. Here, we developed from the bottom up, a new expression platform using synthetic biology. The resulting platform reaches high protein titer across scales and allows for autoinduction and autolysis. More importantly, we are able to decouple growth from protein production and show that this platform is easily adaptable to other applications such as (i) reduction of essential housekeeping proteases to enable production of “hard-to-express” proteins and (ii) complete in vivo post-translational modifications.

Understanding and manipulating enzyme specificity are critical to drug development. In the past two decades, directed evolution has been proven a successful methodology to obtain enzyme variants with a desired and oftentimes new-to-nature function. However, most directed evolution strategies aim at a single trait. As a result, even for similar favorable specificities, siloed and repeated evolution efforts in lab are required. Meanwhile, there remains a lack of understanding of how new specificities emerge in evolution and how different specificities trade off. Here, we reviewed protein sequence-activity relationship studies with diversified phenotypic measurements. We tied our studies around R. trifolii MatB, a malonyl-CoA synthetase. We developed multiagent screening, a novel directed evolution strategy that efficiently evolves enzymes toward multiple specificities. Analysis of mutations identified revealed that distant specificity-altering mutations are destabilizing and dissociating side-chain interactions between remote residues. Moreover, we generated a multi-substrate fitness landscape of MatB. The data revealed distinct patterns of substrate-specific effects between active site and surface mutations, which elucidate the mechanism of how MatB accommodates structurally diverse substrates. A comprehensive mapping of evolutionary trajectories also indicated that structurally distinct substrates are more synergistic in multiagent screening. Lastly, we evaluated a few protein language models as variant fitness predictors and sequence representation methods on our data. We highlighted the difficulty of obtaining a model that effectively leverages information from multiple specificities. Together, our study improves understanding of enzyme promiscuity and paves the way for future protein sequence-activity studies with multiple specificities.