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Biology subjects

Lynch, M. D.

Publications and source records attributed to Lynch, M. D..

At least 19 recordsLinked to original sources
bioRxiv2026

Improved Biosynthesis of Ethylene Glycol from Xylose in Engineered E. coli Utilizing Two-Stage Dynamic Control

In this study, we employ a two-stage dynamic metabolic control strategy to enhance the NADPH dependent biosynthesis of ethylene glycol from xylose in engineered E. coli. We evaluated the use of metabolic valves to dynamically reduce the enzymes involved in competitive pathways which compete for substrates with ethylene glycol biosynthesis, as well as regulatory pathways aimed at increasing NADPH fluxes. The performance of our initial strains with limits in pathway expression levels was improved by the addition of competitive valves, but not by increases in NADPH flux. In contrast, improving pathway expression levels, led to strains improved significantly by our regulatory valves which improved NADPH flux, but not by the competitive valves. This is consistent with a central hypothesis that faster pathways in and of themselves can compete with other metabolic fluxes by being faster and are better aided by regulatory changes capable of change rates elsewhere in metabolism. In this case in NADPH flux. Lastly, upon scale up to fed-batch bioreactors, our optimized strain, featuring dynamic control of two regulatory valves produced 140 g/L of EG in 70 hours at 92% of the theoretical yield.

synthetic biology↗
bioRxiv2025

Decoupling Central Metabolism from Catabolite Repression Enables Robust Cellulosic Sugar Co-consumption in E. coli

Lignocellulosic biomass is the most abundant and sustainable carbon source for bioproduction, but its efficient utilization is hampered by the heterogeneous mixture of sugars released upon hydrolysis. Most industrial strains consume these mixed sugars sequentially due to strong regulation and cross-inhibition, leading to complex processes and reduced carbon efficiency. To address this, we leverage a novel central metabolism that decouples central carbon flux from native regulatory feedback by employing a Gluconate-Bypass of glycolysis. We demonstrate that the Gluconate-Bypass effectively alleviates feedback regulation in E. coli, enabling co-consumption of glucose and xylose. Further strain engineering leads to the first robust co-utilization of four major lignocellulosic sugars: glucose, xylose, arabinose, and galactose. By decoupling central carbon flux from native regulatory feedback, this architecture provides a feedstock-agnostic platform that maintains high and robust consumption regardless of extreme fluctuations in sugar composition.

synthetic biology↗
bioRxiv2025

Engineering Orthogonal Carbon Dissimilation: A Gluconate Bypass Platform for Robust Stationary-Phase Biomanufacturing

Two-stage bioprocesses which decouple cell growth from product synthesis are an attractive approach to biomanufacturing. However high levels of production in stationary phase cultures often suffer from a progressive decline in metabolism. We demonstrate that in E. coli pyruvate accumulation, an inevitable consequence of high-flux metabolism, acts as a major inhibitor of stationary-phase glucose uptake. We present a novel central metabolism to optimize stationary phase production, a gluconate-bypass, which circumvents this challenge by rerouting carbon flux around glycolysis. This redesign achieves two critical outcomes: first, it decouples glucose uptake from pyruvate inhibition; second, glucose oxidation intrinsically co-generates the NADPH cofactor. Validated using NADPH-dependent L-alanine as a representative model, the GBP creates a self-regulating host that achieved a record titer of 197 g/L with a 1.6-fold extension of production longevity. This work establishes the GBP as a generalizable platform for robust stationary phase biosynthesis.

synthetic biology↗
bioRxiv2025

A foundation model for microbial growth dynamics

Microbial growth dynamics contain rich information about microbial populations, which support applications from antibiotic testing to microbiome engineering. However, the high dimensionality of growth data and the scarcity of large, task-specific datasets have limited generalizable modeling analysis across systems. Here, we develop a foundation model for microbial growth dynamics. It is a large-scale, self-supervised representation model trained on [~]370,000 experimental and simulated growth curves spanning diverse microbial species, environmental conditions, and community contexts. The model learns lower-dimensional latent embeddings that capture essential dynamical features of raw growth data and enable accurate reconstruction of these data. The concise representations enhance predictive performance in diverse downstream applications. Using these embedding, we achieve few-shot learning for antibiotic classification and concentration prediction, accurate forecasting of simulated and experimental communities, and inference of total abundance from relative-abundance data. By extracting transferable representations from heterogeneous datasets, our model provides a general framework for analyzing and predicting microbial community dynamics from limited measurements.

synthetic biology↗
bioRxiv2025

Pathogenic Keratinocyte States and Fibroblast Niches Define the Tissue Microenvironment in Severe Hidradenitis Suppurativa

Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease characterized by recurrent painful abscesses and tunnels in flexural sites. The mechanisms driving HS pathogenesis, particularly the roles of keratinocytes and fibroblasts in the HS inflammatory microenvironment, remain poorly understood. To characterise the cellular and molecular landscape of HS, we analyzed lesional skin from severe HS patients using single-cell RNA-sequencing and spatial transcriptomics to identify keratinocyte states and patterns of cellular interactions, with a focus on fibroblast-keratinocyte crosstalk. We identified a migratory S100+ pathogenic keratinocyte state enriched in HS lesions and observed spatially distinct fibroblast populations associated with different tissue compartments. COL6A5+ fibroblasts were preferentially co-localised with undifferentiated keratinocyte states, whereas APOD+ fibroblasts with enriched in immune cell-rich regions containing activated B and plasma cells consistent with tertiary lymphoid organ (TLO)-like structures. Ligand-receptor inference and spatial co-localisation analyses predicted extensive fibroblast-keratinocyte and fibroblast-immune interactions within HS lesions. Together, these data define the cellular organisation of the HS tissue microenvironment and identify spatially distinct stromal and epithelial niches associated with severe disease. These findings provide a framework for understanding how epithelial, stromal and immune cell populations coexist within HS lesions and may help to explain the limited efficacy of therapies targeting individual inflammatory pathways in the treatment of HS.

cell biology↗
bioRxiv2023

Precipitation and Extraction Methods for Protein Purification: A Meta-Analysis of Purification Performance and Cost-Effectiveness

For protein drug purification, packed-bed chromatography often remains both the predominant method and a bottleneck for cost and scalability. Accordingly, extensive efforts have been made to develop alternatives, such as precipitation and liquid-liquid extraction. Despite decades of development, such methods have been slow to see adoption in commercial processes. To diagnose the key barriers to implementation and guide future work, we have systematically reviewed studies of protein precipitation and liquid-liquid extraction. We classify the products, methods, and results of 168 publications representing 290 unique purification operations and analyze these operations in terms of both process economics and purification performance. Whereas it is generally assumed that precipitation and extraction methods will have lower costs than chromatography, we find that this is only the case under specific process conditions such as at a large manufacturing scale and low initial sample purity. Furthermore, we find that only a small number of the many precipitation and extraction methods reported to date have shown readiness for implementation in protein drug purification processes. Finally, we identify key factors governing both the economic and purification performance of this class of methods: first, that operating costs are almost entirely predictable by the ratio between the mass of phase-forming materials used and the mass of product protein yielded; second, that use of modern optimization techniques such as Design of Experiments is associated with significantly better purification performance and cost-effectiveness. HighlightsO_LIAlternative separation purification methods are not always cheaper than chromatography C_LIO_LIThe use of a combination of phase separating agents remains largely underexplored/underutilized C_LIO_LILower initial purity and increasing production scale favor phase-separation over chromatography C_LIO_LIThe direct material usage rate is an important predictor of alternative separation cost-effectiveness C_LIO_LICurrent alternative separation method development has largely ignored optimization of direct material usage rate C_LI

bioengineering↗
bioRxiv2023

Scalable, Robust, High-throughput Expression, Purification & Characterization of Nanobodies Enabled by 2-Stage Dynamic Control

Nanobodies are single-domain antibody fragments that have garnered considerable use as diagnostic and therapeutic agents as well as research tools. However, obtaining pure VHHs, like many proteins, can be laborious and inconsistent. High level cytoplasmic expression in E. coli can be challenging due to improper folding and insoluble aggregation caused by reduction of the conserved disulfide bond. We report a systems engineering approach leveraging engineered strains of E. coli, in combination with a two-stage process and simplified downstream purification, enabling improved, robust soluble cytoplasmic nanobody expression, as well as rapid cell autolysis and purification. This approach relies on the dynamic control over the reduction potential of the cytoplasm, in combination with dynamic expression of chaperones and lysis enzymes needed for purification. Collectively, the engineered system results in more robust growth and protein expression, enabling efficient scalable nanobody production, and purification from high throughput microtiter plates, to routine shake flask cultures and larger instrumented bioreactors. We expect this system will expedite VHH development.

synthetic biology↗
bioRxiv2023

Multi-scale spatial mapping of cell populations across anatomical sites in healthy human skin and basal cell carcinoma

Our understanding of how human skin cells differ according to anatomical site and tumour formation is limited. To address this we have created a multi-scale spatial atlas of healthy skin and basal cell carcinoma (BCC), incorporating in vivo optical coherence tomography, single cell RNA sequencing, spatial global transcriptional profiling and in situ sequencing. Computational spatial deconvolution and projection revealed the localisation of distinct cell populations to specific tissue contexts. Although cell populations were conserved between healthy anatomical sites and in BCC, mesenchymal cell populations including fibroblasts and pericytes retained signatures of developmental origin. Spatial profiling and in silico lineage tracing support a hair follicle origin for BCC and demonstrate that cancer-associated fibroblasts are an expansion of a POSTN+ subpopulation associated with hair follicles in healthy skin. RGS5+ pericytes are also expanded in BCC suggesting a role in vascular remodelling. We propose that the identity of mesenchymal cell populations is regulated by signals emanating from adjacent structures and that these signals are repurposed to promote the expansion of skin cancer stroma. The resource we have created is publicly available in an interactive format for the research community. Significance statementSingle cells RNA sequencing has revolutionised cell biology, enabling high resolution analysis of cell types and states within human tissues. Here, we report a comprehensive spatial atlas of adult human skin across different anatomical sites and basal cell carcinoma (BCC) - the most common form of skin cancer - encompassing in vivo optical coherence tomography, single cell RNA sequencing, global spatial transcriptomic profiling and in situ sequencing. In combination these modalities have allowed us to assemble a comprehensive nuclear-resolution atlas of cellular identity in health and disease.

cell biology↗
bioRxiv2022

The Development of 2-stage Microfermentation Protocols for High Throughput Cell Factory Evaluations

Cell based factories can be engineered to produce a wide variety of products. Advances in DNA synthesis and genome editing have greatly simplified the design and construction of these factories. It has never been easier to generate hundreds or even thousands of cell factory strain variants for evaluation. These advances have amplified the need for standardized, higher throughput means of evaluating these designs. Toward this goal, we have previously reported the development of engineered E. coli strains and associated 2-stage production processes to simplify and standardize strain engineering, evaluation and scale up. This approach relies on decoupling growth (stage 1), from production, which occurs in stationary phase (stage 2). Phosphate depletion is used as the trigger to stop growth as well as induce heterologous expression. Here, we describe in detail the development of optimal protocols used for the evaluation of engineered E. coli strains in 2-stage microfermentations. These protocols are readily adaptable to the evaluation of strains producing a wide variety of protein as well as small molecule products. Additionally, the development approach described is adaptable to additional cellular hosts, as well as other 2-stage processes with various additional triggers.

synthetic biology↗
bioRxiv2022

Integrated Autolysis, DNA Hydrolysis and Precipitation Enables an Improved Bioprocess for Q-Griffithsin, a Broad-Spectrum Antiviral and Clinical-Stage anti-COVID-19 Candidate

Across the biomanufacturing industry, innovations are needed to improve efficiency and flexibility, especially in the face of challenges such as the COVID-19 pandemic. Here we report an improved bioprocess for Q-Griffithsin, a broad-spectrum antiviral currently in clinical trials for COVID-19. Q-Griffithsin is produced at high titer in E. coli and purified to anticipated clinical grade without conventional chromatography or the need for any fixed downstream equipment. The process is thus both low-cost and highly flexible, facilitating low sales prices and agile modifications of production capacity, two key features for pandemic response. The simplicity of this process is enabled by a novel unit operation that integrates cellular autolysis, autohydrolysis of nucleic acids, and contaminant precipitation, giving essentially complete removal of host cell DNA as well as reducing host cell proteins and endotoxin by 3.6 and 2.4 log10 units, respectively. This unit operation can be performed rapidly and in the fermentation vessel, such that Q-GRFT is obtained with 100% yield and >99.9% purity immediately after fermentation and requires only a flow-through membrane chromatography step for further contaminant removal. Using this operation or variations of it may enable improved bioprocesses for a range of other high-value proteins in E. coli. HighlightsO_LIIntegrating autolysis, DNA hydrolysis and precipitation enables process simplification C_LIO_LIAutolysis reduces endotoxin release and burden to purification C_LIO_LIQ-Griffithsin recovered from fermentation vessel at >99.9% purity and 100% yield C_LIO_LIQ-Griffithsin purified to anticipated clinical grade without conventional chromatography C_LIO_LIThe resulting bioprocess is 100% disposables-compatible, scalable, and low-cost C_LI

synthetic biology↗
bioRxiv2021

Instant Taq: Rapid Autoinducible Expression and Chromatography-free Purification of Taq polymerase.

DNA modifying enzymes are ubiquitous reagents in synthetic biology. Producing these enzymes often requires large culture volumes, purified nucleases and chromatographic separations to make enzymes of necessary quality. We sought to leverage synthetic biology tools to develop engineered strains allowing for not only the production but rapid purification of these reagents. Toward this goal, we report an E. coli strain enabling the rapid production and purification of Taq polymerase. The method relies on 1) autoinducible expression achieving high protein titers, 2) autolysis and auto DNA/RNA hydrolysis via lysozyme and a mutant benzonase, and 3) heat denaturation under reducing conditions to precipitate contaminating proteins including the mutant benzonase. Taq polymerase is obtained at high purities (>95% pure by SDS-PAGE) and is readily usable in standard reactions. The method takes less than 1 hour of hands-on time, does not require special equipment, expensive reagents or affinity purification. We expect this simple methodology and approach will improve access not only to Taq polymerase but to numerous additional commonly utilized reagent proteins. HighlightsO_LIProtein titers ~ 1g/L achieved in 20 mL shakeflasks. C_LIO_LI4 mg of purified Taq (corresponding to 5,000 Units, or 4,000 PCR reactions) per 20 mL shake flask. C_LIO_LIInstant Taq is equivalent to commercial preparations in routine PCR C_LI

synthetic biology↗
bioRxiv2021

Optimization of Phosphate Limited Autoinduction Broth for 2-Stage Heterologous Protein Expression in E. coli

Autoinducible, 2-stage protein expression leveraging phosphate inducible promoters has been recently shown to enable not only high protein titers but also consistent performance across scales from screening systems (microtiter plates) to instrumented bioreactors. However, to date small scale production using microtiter plates and shake flasks rely on a complex autoinduction broth (AB) that requires making numerous media components, not all amenable to autoclaving. In this report, we develop a simpler media formulation (AB-2) with just a few autoclavable components. We show that AB-2 is robust to small changes in its composition and performs equally, if not better, than AB across different scales. AB-2 will facilitate adoption of phosphate limited 2-stage protein expression protocols.

biochemistry↗
bioRxiv2021

A meta-analysis of gRNA library screens enables an improved understanding of the impact of gRNA folding and structural stability on CRISPR-Cas9 activity.

CRISPR systems are known to be inhibited by unwanted secondary structures that form within the guide RNA (gRNA). The minimum free energy of predicted secondary structures has been used in prediction algorithms. However, the types of structures as well as the degree to which a predicted structure can inhibit Cas9/gRNA activity is not well characterized. Here we perform a meta-analysis of published CRISPR-Cas9 datasets to better understand the role of secondary structures in inhibiting gRNA activity. We identify two inhibitory structures and provide estimated free energy cutoffs at which they become impactful. Further, we identify the prevalence of these structures in existing datasets. The cutoffs provided help to explain conflicting impacts of free energy values in different datasets as well as providing a guideline for future gRNA designs. HighlightsO_LIClearly define two secondary structures that inhibit CRISPR-Cas9 activity C_LIO_LIProvide free energy calculations and cutoffs at which each structure begins to inhibit activity C_LIO_LIEvaluate impact of these structures in published datasets C_LI

synthetic biology↗
bioRxiv2021

An Analysis of gRNA Sequence Dependent Cleavage Highlights the Importance of Genomic Context on CRISPR-Cas Activity

CRISPR-Cas9 is a powerful DNA editing tool. A gRNA directs Cas9 to cleave any DNA sequence with a PAM. However, some gRNA sequences mediate cleavage at higher efficiencies than others. To understand this, numerous studies have screened large gRNA libraries and developed algorithms to predict gRNA sequence dependent activity. These algorithms do not predict other datasets as well as their training dataset and do not predict well between species. To better understand these discrepancies, we retrospectively examine sequence features that impact gRNA activity in 39 published data sets. We find strong evidence that the genomic context, which can be defined as the DNA content outside of the gRNA/target sequence itself, greatly contributes to differences in gRNA dependent activity. Context underlies variation in activity often attributed to differences in gRNA sequence. This understanding will help guide future work to understand Cas9 activity as well as efforts to identify optimal gRNAs and improve Cas9 variants. HighlightsO_LISpecies-specific genomic context drives variability in gRNA activity in a PAM proximal sequence-dependent manner C_LIO_LIIncreased PAM specificity of Cas9 and/or increased Cas9/gRNA expression reduces the impact of species-specific context C_LIO_LICurrent gRNA prediction algorithms trained on species are not expected to predict activity in another species C_LI

synthetic biology↗
bioRxiv2021

"Multi-Agent" Screening Improves the Efficiency of Directed Enzyme Evolution

Enzyme evolution has enabled numerous advances in biotechnology. However, directed evolution programs can still require many iterative rounds of screening to identify optimal mutant sequences. This is due to the sparsity of the fitness landscape, which in turn, is due to "hidden" mutations that only offer improvements synergistically in combination with other mutations. These "hidden" mutations are only identified by evaluating mutant combinations, necessitating large combinatorial libraries or iterative rounds of screening. Here, we report a multi-agent directed evolution approach that incorporates diverse substrate analogues in the screening process. With multiple substrates acting like multiple agents navigating the fitness landscape, we are able to identify "hidden" mutant residues that impact substrate specificity without a need for testing numerous combinations. We initially validate this approach in engineering a malonyl-CoA synthetase for improved activity with a wide variety of non-natural substrates. We found that "hidden" mutations are often distant from the active site, making them hard to predict using popular structure-based methods. Interestingly, many of the "hidden" mutations identified in this case are expected to destabilize interactions between elements of tertiary structure, potentially affecting protein flexibility. This approach may be widely applicable to accelerate enzyme engineering. Lastly, multi-agent system inspired approaches may be more broadly useful in tackling other complex combinatorial search problems in biology. Highlights- "Multi-agent" screening improves directed evolution. - The incorporation of multiple substrates leads to the identification of "hidden" mutations, which can be hard to identify through one substrate. - "Hidden" mutations are often remote from the active site and are expected to interrupt stabilizing side-chain interactions, thus increasing enzyme flexibility.

synthetic biology↗
bioRxiv2020

BioSamplr: An open source, low cost automated sampling system for bioreactors.

Autosampling from bioreactors reduces error, increases reproducibility and offers improved aseptic handling when compared to manual sampling. Additionally, autosampling greatly decreases the hands-on time required for a bioreactor experiment and enables sampling 24 hrs a day. We have designed, built and tested a low cost, open source, automated bioreactor sampling system, the BioSamplr. The BioSamplr can take up to ten samples from a bioreactor at a desired sample interval and cools them to a desired temperature. The device, assembled from low cost and 3D printed components, is controlled wirelessly by a Raspberry Pi, and records all sampling data to a log file. The cost and accessibility of the BioSamplr make it useful for laboratories without access to more expensive and complex autosampling systems.

bioengineering↗
bioRxiv2020

The Bioprocess TEA Calculator: An online techno-economic analysis tool to evaluate the commercial competitiveness of potential bioprocesses

Techno-economic analysis connects R&D, engineering, and business. By linking process parameters to financial metrics, it allows researchers to understand the factors controlling the potential success of their technologies. In particular, metabolic and bioprocess engineering, as disciplines, are aimed at engineering cells to synthesize products with an ultimate goal of commercial deployment. As a result it is critical to be able to understand the potential impact of strain engineering strategies and lab scale results on commercial potential. To date, while numerous techno-economic models have been developed for a wide variety of bioprocesses, they have either required process engineering expertise to adapt and/or use or do not directly connect financial outcomes to potential strain engineering results. Despite the clear value of techno-economic analysis, these challenges have made it inaccessible to many researchers. I have developed this online calculator (https://bioprocesstea.com OR http://bioprocess-tea-calculator.herokuapp.com/) to make the basic capabilities of early-stage techno-economic analysis of bioprocesses readily accessible. The tool, currently focused on aerobic fermentation processes, can be used to understand the impact of fermentation level metrics on the commercial potential of a bioprocess for the production of a wide variety of organic molecules. Using the calculator, I review the commercially relevant targets for an aerobic bioprocess for the production of diethyl malonate. HighlightsO_LIA generalized techno-economic analysis tool for aerobic fermentation based bioprocesses. C_LIO_LIRelates strain and process improvements to projected commercial financial outcomes C_LIO_LICommercial bioprocess targets to produce diethyl malonate are estimated to include fermentation titers >150 g/L, rates > 5g/L-hr and > 90% yield, with downstream purification yields > 90% and purification costs limited to less than 20% of total. C_LI

synthetic biology↗
bioRxiv2020

Two-stage Dynamic Deregulation of Metabolism Improves Process Robustness & Scalability in Engineered E. coli.

We report improved strain and bioprocess robustness as a result of the dynamic deregulation of central metabolism using two-stage dynamic control. Dynamic control is implemented using combinations of CRISPR interference and controlled proteolysis to reduce levels of central metabolic enzymes in the context of a standardized two-stage bioprocesses. Reducing the levels of key enzymes alters metabolite pools resulting in deregulation of the metabolic network. The deregulated network is more robust to environmental conditions improving process robustness, which in turn leads to predictable scalability from high throughput small scale screens to fully instrumented bioreactors as well as to pilot scale production. Additionally, as these two-stage bioprocesses are standardized, a need for traditional process optimization is minimized. Predictive high throughput approaches that translate to larger scales are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology. In this work we demonstrate that the improved robustness of E. coli strains engineered for the improved scalability of the important industrial chemicals alanine, citramalate and xylitol, from microtiter plates to pilot reactors.

synthetic biology↗