Noncanonical redox cofactors are attractive low-cost alternatives to nicotinamide adenine dinucleotide (phosphate) (NAD(P)+) in biotransformation. However, engineering enzymes to utilize them is challenging. Here, we present a high-throughput directed evolution platform which couples cell growth to the in vivo cycling of a noncanonical cofactor, nicotinamide mononucleotide (NMN+). We achieve this by engineering the life-essential glutathione reductase in
Noncanonical cofactor biomimetics (NCBs) such as nicotinamide mononucleotide (NMN+) provide enhanced scalability for biomanufacturing. However, engineering enzymes to accept NCBs is difficult. Here, we establish a growth selection platform to evolve enzymes to utilize NMN+-based reducing power. This is based on an orthogonal, NMN+-dependent glycolytic pathway in
- Award ID(s):
- 1847705
- NSF-PAR ID:
- 10382031
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Nature Communications
- Volume:
- 13
- Issue:
- 1
- ISSN:
- 2041-1723
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
Abstract Escherichia coli to exclusively rely on the reduced NMN+(NMNH). Using this system, we develop a phosphite dehydrogenase (PTDH) to cycle NMN+with ~147-fold improved catalytic efficiency, which translates to an industrially viable total turnover number of ~45,000 in cell-free biotransformation without requiring high cofactor concentrations. Moreover, the PTDH variants also exhibit improved activity with another structurally deviant noncanonical cofactor, 1-benzylnicotinamide (BNA+), showcasing their broad applications. Structural modeling prediction reveals a general design principle where the mutations and the smaller, noncanonical cofactors together mimic the steric interactions of the larger, natural cofactors NAD(P)+. -
Abstract Molybdenum (Mo) is a key cofactor in enzymes used for nitrogen (N) fixation and nitrate reduction, and the low availability of Mo can constrain N inputs, affecting ecosystem productivity. Natural atmospheric Mo aerosolization and deposition from sources such as desert dust, sea‐salt spray, and volcanoes can affect ecosystem function across long timescales, but anthropogenic activities such as combustion, motor vehicles, and agricultural dust have accelerated the natural Mo cycle. Here we combined a synthesis of global atmospheric concentration observations and modeling to identify and estimate anthropogenic sources of atmospheric Mo. To project the impact of atmospheric Mo on terrestrial ecosystems, we synthesized soil Mo data and estimated the global distribution of soil Mo using two approaches to calculate turnover times. We estimated global emissions of atmospheric Mo in aerosols (<10 μm in diameter) to be 23 Gg Mo yr−1, with 40%–75% from anthropogenic sources. We approximated that for the top meter of soil, Mo turnover times range between 1,000 and 1,000,000 years. In some industrialized regions, anthropogenic inputs have enhanced Mo deposition 100‐fold, lowering the soil Mo turnover time considerably. Our synthesis of global observational data, modeling, and a mass balance comparison with riverine Mo exports suggest that anthropogenic activity has greatly accelerated the Mo cycle, with potential to influence N‐limited ecosystems.
-
Abstract Tumors exhibit high molecular, phenotypic, and physiological heterogeneity. In this effort, we employ quantitative magnetic resonance imaging (MRI) data to capture this heterogeneity through imaging-based subregions or “habitats” in a murine model of glioma. We then demonstrate the ability to model and predict the growth of the habitats using coupled ordinary differential equations (ODEs) in the presence and absence of radiotherapy. Female Wistar rats (N = 21) were inoculated intracranially with 106C6 glioma cells, a subset of which received 20 Gy (N = 5) or 40 Gy (N = 8) of radiation. All rats underwent diffusion-weighted and dynamic contrast-enhanced MRI at up to seven time points. All MRI data at each visit were subsequently clustered using
k -means to identify physiological tumor habitats. A family of four models consisting of three coupled ODEs were developed and calibrated to the habitat time series of control and treated rats and evaluated for predictive capability. The Akaike Information Criterion was used for model selection, and the normalized sum-of-square-error (SSE) was used to evaluate goodness-of-fit in model calibration and prediction. Three tumor habitats with significantly different imaging data characteristics (p < 0.05) were identified: high-vascularity high-cellularity, low-vascularity high-cellularity, and low-vascularity low-cellularity. Model selection resulted in a five-parameter model whose predictions of habitat dynamics yielded SSEs that were similar to the SSEs from the calibrated model. It is thus feasible to mathematically describe habitat dynamics in a preclinical model of glioma using biology-based ODEs, showing promise for forecasting heterogeneous tumor behavior. -
Enzymes are molecules that catalyze reactions critical to life. These catalysts are often studied in bulk water, where the influence of water volume on reactivity is neglected. Here, we demonstrate rate enhancement of up to two orders of magnitude for enzymes trapped in submicrometer water nanodroplets suspended in 1,2-dichloroethane. When single nanodroplets irreversibly adsorb onto an ultramicroelectrode surface, enzymatic activity is apparent in the amperometric current-time trace if the ultramicroelectrode generates the enzyme cofactor. Nanodroplet volume is easily accessible by integrating the current-time response and using Faraday’s Law. The single nanodroplet technique allows us to plot the enzyme’s activity as a function of nanodroplet size, revealing a strong inverse relationship. Finite element simulations confirm our experimental results and offer insights into parameters influencing single nanodroplet enzymology. These results provide a framework to profoundly influence the understanding of chemical reactivity at the nanoscale.
-
Abstract Many biocatalytic processes inside cells employ substrate channeling to control the diffusion of intermediates for improved efficiency of enzymatic cascade reactions. This inspirational mechanism offers a strategy for increasing efficiency of multistep biocatalysis, especially where the intermediates are expensive cofactors that require continuous regeneration. However, it is challenging to achieve substrate channeling artificially in vitro due to fast diffusion of small molecules. By mimicking some naturally occurring metabolons, nanoreactors are developed using P22 virus‐like particles (VLPs), which enhance the efficiency of nicotinamide adenine dinucleotide (NAD)‐dependent multistep biocatalysis by substrate channeling. In this design, NAD‐dependent enzyme partners are coencapsulated inside the VLPs, while the cofactor is covalently tethered to the capsid interior through swing arms. The crowded environment inside the VLPs induces colocalization of the enzymes and the immobilized NAD, which shuttles between the enzymes for in situ regeneration without diffusing into the bulk solution. The modularity of the nanoreactors allows to tune their composition and consequently their overall activity, and also remodel them for different reactions by altering enzyme partners. Given the plasticity and versatility, P22 VLPs possess great potential for developing functional materials capable of multistep biotransformations with advantageous properties, including enhanced efficiency and economical usage of enzyme cofactors.