INORGANIC-BIOLOGICAL HYBRID SYSTEM FOR BIOFUEL PRODUCTION

Information

  • Patent Application
  • 20230227860
  • Publication Number
    20230227860
  • Date Filed
    June 09, 2021
    3 years ago
  • Date Published
    July 20, 2023
    a year ago
Abstract
A system for biofuel production can include a cell, a nanoparticle on a surface of the cell, and an irradiation unit configured to expose the cell to irradiation. A method of producing biofuel can include providing a cell having a nanoparticle on a surface of the cell, exposing the cell to a fuel precursor, irradiating the cell, converting the fuel precursor to a biofuel with the cell, and collecting the biofuel.
Description
SEQUENCE LISTING

A Sequence Listing accompanies this application and is submitted as an ASCII text file of the sequence listing named “MIT_21974_ST25.txt” which is 1 KB in size and was created on Jun. 8, 2021. The sequence listing is electronically submitted via EFS-Web with the application and is incorporated herein by reference in its entirety.


TECHNICAL FIELD

This invention relates to biofuels.


BACKGROUND

Factors such as economic security, environmental protection, and sustainability of resources have driven research pertaining to the production of fuels from renewable resources. See, Eagan, N. M., Kumbhalkar, M. D., Buchanan, J. S., Dumesic, J. A. & Huber, G. W. Chemistries and processes for the conversion of ethanol into middle-distillate fuels. Nat. Rev. Chem. 3, 223-249 (2019), and Dehghani Madvar, M., Aslani, A., Ahmadi, M. H. & Karbalaie Ghomi, N. S. Current status and future forecasting of biofuels technology development. Int. J. Energy Res. 43, 1142-1160 (2019), each of which is incorporated by reference in its entirety. While other sources of renewable energy are useful for electrical power, residential, or commercial purposes, liquid fuels are required for use of the transportation sector. The global demand for a renewable fuel for the transportation sector is expected to increase over the next two decades. See, Outlook for Energy: A perspective to 2040 | ExxonMobil, available at: corporate.exxonmobil.com/Energy-and-environment/Looking-forward/Outlook-for-Energy/Outlook-for-Energy-A-perspective-to-2040 (accessed: 9th January 2020), which is incorporated by reference in its entirety.


SUMMARY

In one aspect, a system for production of a chemical product can include a cell, a nanoparticle on a surface of the cell, and an irradiation unit configured to expose the cell to irradiation.


In another aspect, a method of producing a chemical product can include providing a cell having a nanoparticle on a surface of the cell, exposing the cell to a precursor, irradiating the cell, converting the precursor to a chemical product with the cell, and collecting the chemical product. In certain circumstances, irradiating can include irradiating ultraviolet (UV) light.


In certain circumstances, the chemical product can be a biofuel, for example, ethanol. In certain circumstances, the precursor can include glucose or carbon dioxide.


In certain circumstances, the cell can be a yeast cell.


In certain circumstances, a thiol synthesis pathway can be deleted from the cell. In certain circumstances, the thiol synthesis pathway can include Met17.


In certain circumstances, the nanoparticle can include cadmium. For example, the nanoparticle can include cadmium sulfide.


In certain circumstances, the irradiation unit can include an ultraviolet (UV) light source.


In certain circumstances, the system can include a bioreactor including the irradiation unit configured to irradiate contents of the bioreactor.


Other aspects, embodiments, and features will be apparent from the following description, the drawings, and the claims.





BRIEF DESCRIPTION OF THE DRAWINGS


FIGS. 1A-1F show yeast-nanoparticle hybrid system. FIGS. 1 shows schematic of yeast-hybrid system. FIG. 1B shows a schematic of treating the ΔMet17 strain with cadmium ions (Cd2+) leads to formation of CdS nanoparticles on the cell surface. FIG. 1C shows a TEM image of ΔMet17 cross-section to displaying the localization of CdS nanoparticles on the cell surface. FIG. 1D shows elemental mapping analysis of the TEM image measuring and presenting the location of cadmium in the sample. FIG. 1E shows elemental mapping analysis of the TEM image measuring and presenting the location of sulfur in the sample. FIG. 1F shows elemental mapping analysis measuring and displaying the location of both cadmium (red) and sulfur (blue) in the sample.



FIGS. 2A-2E show analysis of the transcriptomic changes due to ΔMet17 mutation, cadmium ion, and light treatment through RNA Sequencing. FIG. 2A shows principal Component Analysis of RNA Sequencing data. FIG. 2B shows log two fold change volcano plot depicting the effects of the precipitation of cadmium sulfide nanoparticles on the yeast transcriptome. FIG. 2C shows log two fold change volcano plot illustrating the effects of light treatment on the yeast transcriptome. FIG. 2D shows gene set enrichment analysis displaying the effects of light on protein coding genes. FIG. 2E shows gene set enrichment analysis characterizing the effects of cadmium sulfide nanoparticles on protein coding genes.



FIGS. 3A-3C show metabolomic characterization of yeast strains with varied treatment conditions. FIG. 3A shows NAD+ to NADH ratio in W303α and ΔMet17 yeast strains. FIG. 3B shows ATP to ADP ratio in W303α and ΔMet17 yeast strains. FIG. 3C shows LC-MS data analyzing nutrients in the supernatant media displayed with intracellular ethanol concentration in yeast strains with treatment conditions.



FIGS. 4A-4F show deletion of Met17 in another yeast strain and characterizing the effects. FIG. 4A shows a TEM image of Y567 ΔMet17 strain. FIG. 4B shows elemental mapping analysis of the cell surface of Y567 ΔMet17 displays the localization of cadmium in the sample. FIG. 4C shows elemental mapping analysis of the TEM image measures and presents the location of sulfur in the sample. FIG. 4D shows elemental mapping analysis measures and displays the location of both cadmium (red) and sulfur (blue) in the sample. FIG. 4E shows NAD+ to NADH ratio in Y567 and Y567 ΔMet17 yeast strains. FIG. 4F shows ATP to ADP ratio in Y567 and Y567 ΔMet17 yeast strains.



FIGS. 5A-5F show ethanol production through yeast-nanoparticle hybrid system. FIG. 5A shows intracellular ethanol concentration in W303α and ΔMet17 yeast strains. FIG. 5B shows intracellular ethanol concentration in Y567 and Y567 ΔMet17 yeast strains. FIG. 5C shows concentration of ethanol in the supernatant media of W303α and ΔMet17 yeast strains. FIG. 5D shows concentration of ethanol in the supernatant media of Y567 and Y567 ΔMet17 yeast strains. FIG. 5E shows concentration of glucose in the supernatant media of W303α and ΔMet17 yeast strains. FIG. 5F shows concentration of glucose in the supernatant media of Y567 and Y567 ΔMet17 yeast strains.



FIGS. 6A-6D show ΔMet17 treated with Cd2+.FIG. 6A shows a TEM image of ΔMet17 treated with Cd2+. FIG. 6B shows elemental mapping analysis measuring cadmium. FIG. 6C shows elemental mapping analysis measuring sulfur. FIG. 6D shows elemental mapping analysis measuring both cadmium (red) and sulfur (blue).



FIGS. 7A-7B show W303α treated with Cd2+. FIG. 7A shows a TEM image of W303α yeast treated with Cd2+. FIG. 7B shows elemental mapping analysis measuring both cadmium (red) and sulfur (blue) simultaneously.



FIG. 8 shows a TEM image of W303α treated with cadmium ions (Cd2+).



FIG. 9 shows experimental conditions for light/dark experiments.



FIG. 10 shows a heatmap of RNA sequencing data clustered by similarity in gene expression.



FIG. 11 shows total NAD+ and NADH in yeast strains with various treatment conditions.



FIG. 12 shows total ATP and ADP in yeast strains with various treatment conditions. Supplementary



FIG. 13 shows absolute values of excretion and consumption rates through liquid chromatography-mass spectrometry analysis.



FIGS. 14A-14B show Y567 treated with Cd2+. FIG. 14A shows a TEM image of Y567 yeast treated with Cd2+. FIG. 14B shows elemental mapping analysis measuring both cadmium (red) and sulfur (blue) simultaneously



FIG. 15 shows emission at maximum excitation of 350 nm of CdS nanoparticles extracted from Y567 ΔMet17.



FIG. 16 shows carbon dioxide fixation.



FIG. 17 shows a schematic of a bioreactor.



FIGS. 18A-18G show labeling results.





DETAILED DESCRIPTION

Artificially photosynthetic systems can aim to store solar energy and chemically reduce carbon dioxide. These systems can use light to drive processes for carbon fixation into biomass and/or liquid fuels. In particular, a system including a cell decorated with semiconductor nanoparticles that is irradiated can produce a product with a higher yield than without the irradiation.


For example, engineered photosynthetic systems aim to capture solar energy and reduce carbon dioxide. These systems use light to create conditions favorable for net carbon fixation to produce biomass and/or liquid fuels. A hybrid inorganic-biological system is described that combines the light harvesting properties of a semiconductor system that when combined with genetic engineering can alter yeast cell redox state and favor generation of useful products. Here it is shown that this system can be used to increase ethanol production, a common biofuel, through reductive carboxylation stimulated by biologically produced cadmium sulfide nanoparticles and light. This illustrates how use of this system can alter yeast metabolism and allow production of many metabolites.


In general, a system has been developed that harvests light and drives an oxidized cell state. The altered metabolic state favors the system’s increased ability to fix carbon and produce biofuel.


Disclosed herein is a hybrid inorganic-biological system that can utilize an input of toxic waste to drive product formation. In one aspect, the hybrid system can produce a chemical product, such as biomass or a biofuel. In certain embodiments, the biofuel can be ethanol. In certain embodiments, the inorganic system can include nanoparticles. In certain embodiments, the biological system can include cells. For example, a system for production of a chemical product can include a cell, a nanoparticle on a surface of the cell, and an irradiation unit configured to expose the cell to irradiation. A method of production of a chemical product can include providing a cell having a nanoparticle on a surface of the cell, exposing the cell to a fuel precursor, irradiating the cell, converting the precursor to a chemical product with the cell, and collecting the chemical product. In certain embodiments, the cell can be yeast cell. For example, the system endogenously can generate nanoparticles that through light stimulus, activate the yeast. In certain embodiments, the yeast can produce an increased amount of a biofuel, such as ethanol when irradiated compared to when not irradiated.


The hybrid inorganic-biological system can manage both genetically controlled generation of products along with the ability to photoactivate a semiconductor system. For example, an increase in the production of a chemical product such as ethanol, a common biofuel, through the electron transfer can be stimulated by biologically produced nanoparticles and light. In certain embodiments, the nanoparticles can include cadmium. In certain embodiments, nanoparticles can include cadmium sulfide. This system can improve the production of many metabolites and products through endogenously produced nanoparticles.


In one aspect, a system for production of a chemical product can include a cell, a nanoparticle on a surface of the cell, and an irradiation unit configured to expose the cell to irradiation. For example, a method of producing a chemical product can include providing a cell having a nanoparticle on a surface of the cell, exposing the cell to a precursor, irradiating the cell, converting the precursor to a chemical product with the cell, and collecting the chemical product. In certain circumstances, irradiating can include irradiating ultraviolet (UV) light.


The chemical product can form by transformation of a precursor, which can be a biologically-available substrate. For example, the precursor can include glucose or carbon dioxide The chemical product can be an organic molecule or other target, such as a biofuel. For example, the chemical product can be ethanol.


In certain circumstances, the cell can be a yeast cell. For example, the cell can be a transformed cell as described, for example, in PCT/US2018/016576, which is incorporated by reference in its entirety. For example, a thiol synthesis pathway can be deleted from the cell. In certain circumstances, the thiol synthesis pathway can include Met17. Cells with this modification can present a nanoparticle on the surface of a cell.


In certain circumstances, the nanoparticle can include cadmium. For example, the nanoparticle can include cadmium sulfide.


The nanoparticle can be a nanocrystal. In certain circumstances, the nanoparticle can include a semiconductor material. The semiconductor material forming the nanoparticle can include a Group II-VI compound, a Group II-V compound, a Group III-VI compound, a Group III-V compound, a Group IV-VI compound, a Group I-III-VI compound, a Group II-IV-VI compound, or a Group II-IV-V compound, for example, ZnO, ZnS, ZnSe, ZnTe, CdO, CdS, CdSe, CdTe, MgO, MgS, MgSe, MgTe, HgO, HgS, HgSe, HgTe, AlN, AlP, AlAs, AlSb, GaN, GaP, GaAs, GaSb, InN, InP, InAs, InSb, TlN, TlP, TlAs, TlSb, TlSb, PbS, PbSe, PbTe, Cd3As2, Cd3P2 or mixtures thereof.


In certain circumstances, the irradiation unit can include an ultraviolet (UV) light source. The nanoparticle can be irradiated with a wavelength of light, for example, the nanoparticle can be excited with light having a wavelength of 500 nm or shorter, 450 nm or shorter, 400 nm or shorter, or 350 nm or shorter.


The nanoparticles can be formed by exposing the cell to an M-containing salt. Suitable M-containing salts include cadmium acetylacetonate, cadmium iodide, cadmium bromide, cadmium chloride, cadmium hydroxide, cadmium carbonate, cadmium acetate, cadmium myristate, cadmium oleate, cadmium oxide, zinc acetylacetonate, zinc iodide, zinc bromide, zinc chloride, zinc hydroxide, zinc carbonate, zinc acetate, zinc myristate, zinc oleate, zinc oxide, magnesium acetylacetonate, magnesium iodide, magnesium bromide, magnesium chloride, magnesium hydroxide, magnesium carbonate, magnesium acetate, magnesium myristate, magnesium oleate, magnesium oxide, mercury acetylacetonate, mercury iodide, mercury bromide, mercury chloride, mercury hydroxide, mercury carbonate, mercury acetate, mercury myristate, mercury oleate, aluminum acetylacetonate, aluminum iodide, aluminum bromide, aluminum chloride, aluminum hydroxide, aluminum carbonate, aluminum acetate, aluminum myristate, aluminum oleate, gallium acetylacetonate, gallium iodide, gallium bromide, gallium chloride, gallium hydroxide, gallium carbonate, gallium acetate, gallium myristate, gallium oleate, indium acetylacetonate, indium iodide, indium bromide, indium chloride, indium hydroxide, indium carbonate, indium acetate, indium myristate, indium oleate, thallium acetylacetonate, thallium iodide, thallium bromide, thallium chloride, thallium hydroxide, thallium carbonate, thallium acetate, thallium myristate, or thallium oleate.


The nanoparticle can have a size of less than 150 Å, for example, average diameters in the range of 10 Å to 125 Å.


The cell can be mutated to be sensitive for a metal, which can lead to nanoparticle formation. For example, the cells can be were screened by subjecting libraries to 100 µM metal ions in culture and fractionated based on density changes. See, for example, PCT/US2018/016576, which is incorporated by reference in its entirety. The cell can be decorated with the nanoparticle by exposing the cell to the M-contained salt.


In certain circumstances, the system can include a bioreactor including the irradiation unit configured to irradiate contents of the bioreactor. The cell, decorated with a nanoparticle, can be used in a bioreactor to produce a chemical product when irradiated. Referring to FIG. 17, the system 10 can include a bioreactor 25 including an irradiation source 20. Bioreactor 25 can include a suspension 30 of the cell which is exposed to a precursor in the bioreactor. The precursor and/or the cell can be introduced into the bioreactor though inlet 40. Product can be removed through outlet 50.


The precursor can be a chemical species that is transformed by a biochemical reaction performed by the cell. The biochemical reaction performance can be enhanced by irradiation of the decorated cell. For example, carbon dioxide and glucose can be transformed into ethanol with a cadmium nanoparticle decorated yeast.


The most prominent biologically derived fuel around the world is ethanol. See, Short-Term Energy Outlook - U.S. Energy Information Administration (EIA), available at: https://www.eia.gov/outlooks/steo/ (accessed: 9th January 2020), which is incorporated by reference in its entirety. Currently, ethanol is mainly produced by fermentation of sugars from sugar cane or corn. See, Eagan, N. M., Kumbhalkar, M. D., Buchanan, J. S., Dumesic, J. A. & Huber, G. W. Chemistries and processes for the conversion of ethanol into middle-distillate fuels. Nat. Rev. Chem. 3, 223-249 (2019), which is incorporated by reference in its entirety. Enzymatic or thermocatalytic upgrading of synthetic gas has also resulted in ethanol production. See, Warner, E., Schwab, A. & Bacovsky, D. 2016 Survey of Non-Starch Alcohol and Renewable Hydrocarbon Biofuels Producers. (2015), which is incorporated by reference in its entirety. Ethanol currently used in the US is blended with gasoline levels of around 10% (compared to Brazil at 27%). See, Brazil: Biofuels Annual | USDA Foreign Agricultural Service, available at: https://www.fas.usda.gov/data/brazil-biofuels-annual-4 (accessed: 9th January 2020), which is incorporated by reference in its entirety. Adding ethanol to gasoline fuels has been shown to be beneficial for decreasing carbon monoxide and hydrocarbon emissions while increasing the octane number. See, Hsieh, W. D., Chen, R. H., Wu, T. L. & Lin, T. H. Engine performance and pollutant emission of an SI engine using ethanol-gasoline blended fuels. Atmos. Environ. 36, 403-410 (2002), and Agarwal, A. K. Biofuels (alcohols and biodiesel) applications as fuels for internal combustion engines. Progress in Energy and Combustion Science 33, 233-271 (2007), each of which is incorporated by reference in its entirety.


Artificially photosynthetic systems aim to chemically reduce carbon dioxide. See, Blankenship, R. E. et al. Comparing photosynthetic and photovoltaic efficiencies and recognizing the potential for improvement. Science 332, 805-9 (2011), which is incorporated by reference in its entirety. These processes can be imitated by hybrid inorganic-biological systems that have been developed to use light as a stimulus to drive product formation from carbon based molecules into liquid fuels. See, Guo, J. et al. Light-driven fine chemical production in yeast biohybrids. Science 362, 813-816 (2018), Sakimoto, K. K., Wong, A. B. & Yang, P. Self-photosensitization of nonphotosynthetic bacteria for solar-to-chemical production. Science 351, 74-7 (2016), Gust, D., Moore, T. A. & Moore, A. L. Solar Fuels via Artificial Photosynthesis. Acc. Chem. Res. 42, 1890-1898 (2009), Liu, C., Colón, B. C., Ziesack, M., Silver, P. A. & Nocera, D. G. Water splitting-biosynthetic system with CO2 reduction efficiencies exceeding photosynthesis. Science 352, 1210-3 (2016), Liu, C. et al. Nanowire-Bacteria Hybrids for Unassisted Solar Carbon Dioxide Fixation to Value-Added Chemicals. Nano Lett. 15, 3634-3639 (2015), and Torella, J. P. et al. Efficient solar-to-fuels production from a hybrid microbial-water-splitting catalyst system. Proc. Natl. Acad. Sci. 112, 2337-2342 (2015), each of which is incorporated by reference in its entirety. US 8,227,237 describes engineered CO2 fixing microorganisms.


Cadmium is a heavy metal with high toxicity even at very low exposure levels. Cadmium’s water solubility enables its circulation in the environment, mobility, and bioavailability. See, Nordic Council of Ministers Cadmium Review. (2003), which is incorporated by reference in its entirety. Cadmium can accumulate in the human body and cause kidney damage as well as lead to lung cancer and prostate cancer in high exposure settings. See, Fowler, B. A. Monitoring of human populations for early markers of cadmium toxicity: A review. Toxicol. Appl. Pharmacol. 238, 294-300 (2009), which is incorporated by reference in its entirety. Many techniques, such as chemical reduction, electrochemical treatment, ion exchange, precipitation, and absorption have been reported in an effort to clean up the cadmium waste. A biological system can be genetically engineered to uptake cadmium and remove the toxic metal from their environment. In certain embodiments, the biological system can include the yeast. The sequestered cadmium forms light-activatable nanoparticles that support biofuel synthesis. Yeast has been used as hyperaccumulators for heavy metals. Sun G. et al., Designing yeast as plant-like hyperaccumulators for heavy metals, Nature Communications (2019) 10:5080, which is incorporated by reference in its entirety. Yeast is also known to be a good model to study interactions with quantum dots. See, e.g., Pagano L. et al., In Vivo-In Vitro Comparative Toxicology of Cadmium Sulphide Quantum Dots in the Model Organism Saccharomyces cerevisiae (2019) Nanomaterials 9, 512 and Mei J. et al, The interactions between CdSe quantum dots and yeast Saccharomyces cerevisiae: Adhesion of quantum dots to the cell surface and the protection effect of ZnS shell, Chemosphere, October 2014, 112:92-99, each of which is incorporated by reference in its entirety. CN 101264 describes removing cadmium ion from waste water by waste beer yeast absorption, which is incorporated by reference in its entirety.


Microorganisms have been used for biomanufacturing due to their ability to produce higher value chemicals through growth in simple and inexpensive media. See, Sakimoto, K. K., Wong, A. B. & Yang, P. Self-photosensitization of nonphotosynthetic bacteria for solar-to-chemical production. Science 351, 74-7 (2016), and Mohd Azhar, S. H. et al. Yeasts in sustainable bioethanol production: A review. Biochem. Biophys. Reports 10, 52-61 (2017), each of which is incorporated by reference in its entirety. Certain microorganisms have been genetically engineered to convert renewable carbon sources into higher-value chemicals. Sakimoto, K. K., Wong, A. B. & Yang, P. Self-photosensitization of nonphotosynthetic bacteria for solar-to-chemical production. Science 351, 74-7 (2016), which is incorporated by reference in its entirety. Saccharomyces cerevisiae have been used in industrial settings due to the wide range of metabolites, biofuels, drug precursors, and flavors it can be engineered to produce. See, Jouhten, P. et al. Yeast metabolic chassis designs for diverse biotechnological products. Sci. Rep. 6, 29694 (2016), which is incorporated by reference in its entirety. US 8,465,954, US 9,752,164, and US 7,078,201 describe ethanol production by microorganisms, each of which is incorporated by reference in its entirety. Improved ethanol production has been observed in a certain mutant yeast. See, Hu, J. et al., Improved ethanol production in the presence of cadmium ions by a Saccharomyces cerevisiae transformed with a novel cadmium-resistance gene DvCRP1, Environmental Technology, 37:22, 2945-2952, which is incorporated by reference in its entirety. While the extensive genetic studies on this model organism have provided information to better understand and engineer yeast for product formation, the interplay between yeast physiology in an inorganic-biological hybrid remains poorly characterized. Additionally, the use of inorganic-biological hybrid systems can serve as a useful tool to toggle the metabolism of yeast in a rapid manner.


Light’s bioavailability, sustainability, and low cost render it a desirable stimulus in biological applications. Light has been used as an inducible and reversible stimulus to precisely garner biological responses. See, Zhao, E. M. et al. Optogenetic regulation of engineered cellular metabolism for microbial chemical production. Nature 555, 683-687 (2018), and Salinas, F., Rojas, V., Delgado, V., Agosin, E. & Larrondo, L. F. Optogenetic switches for light-controlled gene expression in yeast. Applied Microbiology and Biotechnology 101, 2629-2640 (2017), each of which is incorporated by reference in its entirety. Using a synthetic yeast system for light driven product formation can be an environmentally friendly, sustainable, and regenerable system. See Guo, J. et al. Light-driven fine chemical production in yeast biohybrids. Science 362, 813-816 (2018), which is incorporated by reference in its entirety. Chemically regulated systems have also been used to induce high levels of expression despite the limitations in causing undesired activation of physiological and signaling pathways and imprecise control over protein levels.


Setup and Visual Characterization of the Hybrid System

A yeast-nanoparticle hybrid system involving cadmium sulfide (CdS) nanoparticles was developed through genetic control for endogenous production of hydrogen sulfide (FIG. 1). Deletion of Met17 in Saccharomyces cerevisiae leads to an increase in hydrogen sulfide production, which is shuttled out of the cell. A pathway involved in thiol synthesis, Met17, was deleted from the Saccharomyces cerevisiae (S288C) strain, W303α, which led to an increase in hydrogen sulfide production (FIG. 1A). Treating this strain, W303α ΔMet17::KanMX (ΔMet17) with cadmium ions (Cd2+) results in CdS nanoparticle formation (FIG. 1B). Performing transmission electron microscopy (TEM) of the sample to physically characterize the system displayed that the exposure to Cd2+ causes the precipitation of CdS nanoparticles on the cell surface (FIG. 1C). Elemental mapping analysis measured the presence of cadmium (FIG. 1D) and sulfur (FIG. 1D) in the sample. Measuring both cadmium and sulfur simultaneously confirms the presence of CdS nanoparticles in element dense areas on the cell surface (FIG. 1F). Performing the same microscopy and analysis on an uncut ΔMet17 Cd2+ treated sample displays the same properties of cadmium and sulfur on the cell surface (FIG. 6). When W303α was treated with the same dose of Cd2+, no formation of nanoparticles was observed (FIG. 7, FIG. 8). CdS nanoparticles were extracted and isolated in order to characterize their excitation and emission properties. The nanoparticles have a maximum excitation at 350 nm with an emission of 415 nm.


Transcriptomic Characterization of the Hybrid System

To elucidate the effects of the mutation, Cd2+ treatment, and ultraviolet light at 350 nm (light) treatment on gene expression, the transcriptome was characterized (FIG. 2). Both W303α and ΔMet17 were tested in the untreated, cadmium only, light only, and cadmium and light treatments (FIG. 9). Principal component analysis of the RNA sequencing data determined that the strongest variations in gene expression were caused by the implementation of the Met17 gene deletion and light treatment (FIG. 2A, FIG. 10). This analysis captured 48% of the variance due to the deletion and 15% of the variance due to light treatment. Further investigation was performed to reveal the effects due to both cadmium and light treatment through differential gene expression analysis. W303α samples were tested against each other, ΔMet17 samples were tested against each other, and ΔMet17 samples were tested against W303α. The analysis revealed an increase in gene transcripts with a nicotinamide adenine dinucleotide (NAD+) dependency due to the effects of CdS nanoparticles (FIG. 2B). Genes such as HST1, an NAD+ dependent gene, was found upregulated only in the ΔMet17 + Cd2+ + light treated sample when compared to the ΔMet17 + light sample (Table 1). Further investigation into the effects of light treatment revealed an increase in gene expression of transcripts involved in adenosine triphosphate (ATP) synthesis (ATP14, TIM11), as well as the electron transport chain, such as COX9 and QCR8 (FIG. 2C, Table 2). In order to delve deeper into the effects of light and cadmium treatment, gene set enrichment analysis (GSEA) was performed. Gene sets were chosen to include all genes involved in biofuel production, glycolysis, ATP production and regulation, fermentation, respiration, electron transport chain, and other metabolism related genes. Through GSEA, light treatment was shown to upregulate protein coding genes involved in proton pumping and mitochondrial electron transport chain. (FIG. 2D). An upregulation of genes involved in ATP synthesis and production were found. Genes involved in protein folding, cation transport, and hydrogen ion transmembrane transport were also found (Table 3). Upregulated genes involved in proton shuttling and proton transport suggest that electron transport and membrane potential were altered with a potential mechanism for shuttling electrons. Treatment with cadmium and precipitation of CdS nanoparticles was correlated with an upregulation of genes in involved in translation, DNA strand elongation, and proton transport (FIG. 2E). Genes involved in glycolysis were found to be upregulated. Certain genes, such as PMA1, COR1, and QCR3 were found to also be involved in glycolysis and production of metabolites used in respiration or fermentation (Table 4).


Characterizing the Redox Properties of the Hybrid System

Further mechanistic investigation involved inquiry into metabolite concentrations in yeast strains. This was performed by characterizing the redox potential of cells through the NAD+:NADH ratio and the ATP:ADP ratio (FIG. 3). Intracellular NAD+ and NADH concentrations were measured and revealed an increase in the NAD+:NADH ratio in the ΔMet17 strain treated with Cd2+ and light (FIG. 3A). The total amount of NAD+ and NADH in each strain was similar (FIG. 11). As the effects of light displayed an increase in protein coding genes related to ATP production and regulation, intracellular ATP and ADP concentrations were measured. While the total amount of ATP and ADP was similar in each strain (FIG. 12), a marked difference in the ATP:ADP ratio was found in the ΔMet17 strain treated with Cd2+ and light (FIG. 8B). Liquid chromatography-mass spectrometry (LC-MS) was performed to identify substances within the media sample to determine the intake of nutrients by yeast strains (FIG. 8C). The relative rates of nutrient consumption remained similar across strains and treatment conditions comparted to the control. However, the nutrient consumption of ΔMet17 + Cd2+ + light was found to be lower than other treatments, particularly of arginine and glucose. Product formation through the change of redox potential in the cell was shown through measuring the concentration of ethanol, a biofuel of interest. An increase in the intracellular concentration of ethanol was found in the ΔMet17 strain treated with Cd2+ and light. An increase in ethanol concentration coupled with a decrease in glucose consumption could be indicative of increased efficiency in ethanol production when compared to wild-type. Intracellular metabolite concentrations were normalized to cell size, and flux analyses were normalized to growth rates.


Implementing and Characterizing the Mutation in Another Yeast Strain

To verify the applicability of the Met17 deletion, and Cd2+ and light treatments, the mutation was implemented in another S. cerevisiae strain, Y567. Y567 was engineered to have an increased ethanol production capacity for the beer industry. After deletion, the behavior of the resultant strain, Y567 ΔMet17::KanMX (Y567 ΔMet17) was characterized (FIG. 4). When treated with the same dose of Cd2+ (10 µM) as W303α ΔMet17, Y567 ΔMet17 precipitates CdS nanoparticles on the cell surface (FIG. 4A). Elemental mapping analysis displays the presence of cadmium on the cell surface (FIG. 4B). Elemental mapping analysis measures the presence of sulfur on the cell surface (FIG. 4C). Mapping both sulfur and cadmium shows localization of the CdS nanoparticles (FIG. 4D). TEM and elemental analysis of the Y567 strain treated with the same dose of Cd2+ shows no precipitation of CdS nanoparticles, and is consistent with the behavior of W303α (FIG. 14). The CdS nanoparticles extracted from Y567 ΔMet17 had a maximum excitation at 350 nm with an emission at 415 nm (FIG. 15). Measurements of metabolite concentrations in Y567 ΔMet17 reveal an increased NAD+:NADH ratio (FIG. 4E) and an increase in ATP:ADP ratio (FIG. 9F). The total NAD+ and NADH levels as well as ATP and ADP levels remained similar in all strains independent of cadmium and light treatments (FIG. 11, FIG. 12).


Increased Ethanol Production Through Hybrid System

In other biological-inorganic hybrid system, light harvesting semiconductor particles that were attached to the surface of the cell provided reducing agents to the metabolic processes. A similar mechanism of an excited electron from the CdS nanoparticle flowing to the metabolic processes in the yeast cell was hypothesized in this yeast-inorganic hybrid system. The transcriptomic upregulation in protein coding genes involved in the electron transport chain also supports this hypothesis (FIG. 3C).


In other biological-inorganic hybrid system, light harvesting semiconductor particles that were attached to the surface of the cell provided reducing agents to the metabolic processes. A similar mechanism of an excited electron from the CdS nanoparticle flowing to the metabolic processes in the yeast cell was hypothesized in this yeast-inorganic hybrid system. The reductive carboxylation of the tricarboxylic acid (TCA) metabolite alpha-ketoglutarate into citrate has been reported as a redox responsive pathway that is engaged upon an increase in cellular electron donor availability in various biological systems. Thus, it was hypothesized that this pathway of CO2 reduction can represent a potential light-stimulated reductive processes in the system (FIGS. 18A and 18B). To test this hypothesis, various strains of yeast were cultured with and without light in the presence of C13-labeled CO2 and assessed label incorporation into citrate. Consistent with this hypothesis, it was found that the ΔMet17 W303α and ΔMet17 Y567 strain treated with Cd2+ and light had the greatest fraction of steady-state intracellular citrate labelled by CO2 (FIG. 18D). Importantly, this increase in labelling was not seen in alpha-ketoglutarate, suggesting that the label on citrate is being incorporated through reductive carboxylation of alpha-ketoglutarate and not through other pathways of citrate synthesis (FIGS. 18C and 18E). The increase in M-5 citrate from is on the same order of magnitudes as previously seen reductive carboxylation pathways from alpha-ketoglutarate to citrate in mammalian cells.


Within the yeast cell, yeast fermentation and metabolic processes can drive ethanol production, with a more reduced cell state favoring ethanol production as this pathway is driven by high NADH and allows electron disposal for NAD+ regeneration. An increase in intracellular ethanol concentration was found in the ΔMet17 strain treated with Cd2+ and light when compared with W303α. A 5-fold change in ethanol production was found in the Y567 ΔMet17 strain treated with Cd2+ and light when compared to Y567. The concentration of ethanol in the media was also measured to determine the change in ethanol secreted by the yeast strains over time. FIG. 18F shows concentration of ethanol in the supernatant media of W303α and ΔMet17 yeast strains after cadmium treatment and dark/light experiment. FIG. 18G shows concentration of ethanol in the supernatant media of Y567 and Y567 ΔMet17 yeast strains after cadmium treatment and dark/light experiment Ethanol concentration was higher in ΔMet17 treated with Cd2+ and light when compared to W303α (FIG. 18F). Similarly, the supernatant media of the Y567 ΔMet17 strain treated with Cd2+ and light was higher than the Y567 strain (FIG. 18G). The increase in ethanol in the mutant strains both inside the yeast cell and in its environment suggests a mechanism activated by CdS and light treatment that increases ethanol production. In order to test whether increased ethanol production was accompanied by increased glucose consumption, the glucose concentration of the media was examined. A lower glucose input was required by ΔMet17 (FIG. 18F) and Y567 ΔMet17 (FIG. 18G) strains for a higher yield of ethanol. The hybrid system’s increase in ethanol production and decrease in glucose consumption implies an offset cost in carbon balance that is supported by the CO2 entry to the TCA cycle. This data, along with the observation that these strains are able to perform more reductive carboxylation in the presence of light, suggests this system can enable light-stimulated increased biofuel production from CO2. Within the yeast cell, yeast fermentation and metabolic processes can drive ethanol production, with a potential increase due to the shuttling of electrons to regenerate NADH from NAD+. An increase in intracellular ethanol concentration was found in the ΔMet17 strain treated with Cd2+ and light when compared with W303α (FIG. 5A). This was exemplified with a 5-fold change in ethanol production in the Y567 ΔMet17 strain treated with Cd2+ and light when compared to Y567 (FIG. 5B). The concentration of ethanol in the media was also measured to determine the change in ethanol secreted by the yeast strains. Ethanol concentration was higher in ΔMet17 treated with Cd2+ and light when compared to W303α (FIG. 5C). Similarly, the supernatant media of the Y567 ΔMet17 strain treated with Cd2+ and light was 3-fold higher than the Y567 strain (FIG. 5D). The increase in the ethanol in the mutant strains both inside the yeast cell and in its environment suggests a mechanism caused by CdS and light treatment that increases ethanol production. In order to test whether or not certain strains took up more glucose, the glucose concentration of the media was tested. A lower glucose input was required by ΔMet17 (FIG. 5E, FIG. 3C) and Y567 ΔMet17 (FIG. 5F) for a higher yield of ethanol.


The change in redox potential, the need for a carbon source, and the decrease in glucose consumption lead us to hypothesize that the carbon source may be involved in the Calvin cycle. As part of photosynthesis, the Calvin cycle involves carbon dioxide fixation in the first stage. The second stage involves the donation of electrons from NADPH for the reduction of the carbon source. The net reaction of photosynthesis is photoactivation which releases electrons in the form of NADPH, which are then used to reduce carbohydrates. To test this hypothesis, radiolabeled carbon dioxide can be used. While only plants have rubisco, other organisms do have, carbon fixing enzymes, such as Isocitrate dehydrogenase. Alpha-ketoglutarate is converted to citrate with the input of carbon dioxide and consumes electrons in the form of NADPH. Citrate was observed as a proxy to see if the radiolabeled carbon dioxide is being fixed (FIG. 16). Radiolabeled carbon in citrate was increased in the mutant treated with light and cadmium, which implies that carbon dioxide fixation.


Development of an in-house inorganic-biological hybrid system has the potential to enable the production of higher value products. The production of propane-1,2-diol and propane-1,3-diol, that is already found in yeast, requires the reduction of NADH to NAD+. This work provides a platform to increase the production of fragrances, drug precursors, and other biofuels already produced by yeast. While a larger scale implementation will require the optimization of larger scale cultures and illumination sources, this hybrid-biological system can be tuned to fit various needs. The versatility of this system through the biological production of nanoparticles enables tuning of the yeast strain as well as the nanoparticle’s materials, size, and crystallinity. The intensity of ultraviolet light exposure via lamp at 3×10-6 W/m2/nm in a dark room is lower than atmospheric ultraviolet light levels at 103 W/m2/nm. See, Climate Prediction Center -Stratosphere: UV Index: Nature of UV Radiation, available at: www.cpc.ncep.noaa.gov/products/stratosphere/uv_index/uv_nature.shtml (accessed: 9th January 2020), which is incorporated by reference in its entirety. The wavelength at which to excite the CdS nanoparticle can be tuned based on the size of the nanoparticle. The size of the nanoparticle can be controlled with the nutritional profile of the yeast through monitoring and control of hydrogen sulfide production. The genetic control of the biological production of nanoparticles can be implemented in various strains in addition to the two performed and discussed. A deeper understanding of the electron donation and transport mechanism can lead to further design improvements of the biological-hybrid system. This work provides a platform in which many tools can be tuned to enable efficient and economical production of valuable metabolites and products.


The development of an in vivo multicomponent hybrid system to modulate the redox properties of yeast cells with light and favor ethanol production illustrates how endogenous semiconductor CdS nanoparticle deposition can be used to alter the metabolic state of yeast for potential useful purposes. Here, it was demonstrate that the light induced yeast-CdS system can produce a 5.6x increase in ethanol production and a 9x increase in CO2 incorporation. This system is adaptable to fit many applications, such as altering the nanoparticle’s material and/or optical properties, affecting CO2 influx into yeast biomass, and the choice of yeast strain with or without engineered mutations can enable specific product formation.


The use of yeast in the manufacturing of high value pharmaceuticals, fragrances, and other renewable fuels should be amenable with this system, as many of these pathways are facilitated by a more oxidized NAD+/NADH ratio. The intensity of ultraviolet light exposure via lamp in the experiments at 3×10-6 W/m2/nm in a dark room is lower than atmospheric ultraviolet light levels at 103 W/m2/nm (25), which implies that the light exposure needed to alter metabolic changes might be possible in the natural environment. While a larger scale implementation will require optimization of the culture size and illumination sources, the versatility of this system can be tuned to fit diverse needs. This hybrid system enables endogenous production of CdS nanoparticles, which, upon ultraviolet light treatment, changes the metabolic state of the yeast cell and drives product formation. The composite hybrid system minimizes the amount of handling necessary and integrates the tunability both from the semiconductor system and through the alteration of the metabolic state. This system provides a platform in which one can induce an organism to endogenously grow semiconductor material, collect light, alter redox properties of a living cell, and use the changes in redox potential to increase production of desired molecules, fix carbon dioxide, and reduce waste. This process can be tuned to enable efficient and economical production of other valuable metabolites and small molecule products.


The quantum yield of photosynthesis has been defined as the molar ratio between photons absorbed and oxygen released. Naturally and artificially photosynthetic systems have used the direct correlation between photon consumption and oxygen production as a measurement of efficiency. The hybrid system does not have such a direct correlation between photons absorbed and electrons accepted; however, differences in ethanol production via the hybrid system when compared with the wild-type yeast are seen. The system provides an increased production capacity and efficiency of ethanol.


EXAMPLES
Yeast Strain and Culture

Yeast strains W303α (S288C) and W303α ΔMet17 were available in the lab. Synthetically defined dropout media (SD) was made by dissolving 1.7 g/L yeast nitrogen base without amino acid and ammonium sulfate (YNB, Fischer), 5 g/L ammonium sulfate (Sigma), 0.6 g CSM-HIS-LEU-TRP-URA powder (MP Biologicals), 20 g/L glucose (Sigma), and 10 mL/L of 100X adenine hemisulfate stock (1 g/L, Sigma) in ddH2O. 100X stocks of amino acids were created using the following: uracil (2 g/L, Sigma), histidine (5 g/L, Sigma), leucine (10 g/L, Sigma), and tryptophan (10 g/L, Sigma) were made in ddH2O. They were subsequently filtered and sterilized prior to their use in supplementing cultures. Saccharomyces cerevisiae strain Y567 was acquired from ATCC, Strain: NRRL Y-567). Yeast strains were grown as previously described (19) and had a doubling time of ~140 minutes (Table 6).


Synthetically defined dropout medium was made by combining 1.7 g L-1 yeast nitrogen base (YNB) without ammonium sulfate (Fischer) and amino acid amino acids. 5 g L-1 ammonium sulfate (Sigma), 1.85 g 1-1 dropout mix without cysteine and methionine (US Biological), 20 g L-1 glucose (Sigma) and 10 ml L-1 ×100 adenine hemisulfate stock (1 g 1-1) (Sigma). CSM were combined by adding cysteine and methionine amino acids for a final concentration of 50 mg 1-1 (Sigma). The dropout media and CSM (MP Biologicals) were adjusted to have a pH of 7.0 with addition of NaOH. Mixtures were stirred and filtered through a 0.22 µm filter top (EMD). YPD medium was made by combining 20 g L-1 glucose (Sigma), 10 g L-1 yeast extract, 20 g L-1 peptone (Fisher) and were filter sterilized. Plates were made by adding 20 g L-1 Bacto Agar (Fisher) and sterilization via autoclaving.


Implementing ΔMet17 Mutation

The ΔMet17 mutation was implemented in both W303α and Y567. Met17 was knocked out inW303α and Y567 using the following primers for producing a deletion cassette KanMX:










Name
Primer




del-Met-17-KanMX-fwd
TCAGATACATAGATACAATTCTATTACCCCCATCCATA CAGACATGGAGGCCCAGAATA (SEQ ID NO.: 1)


del-Met-17-KanMX-rev
AAGTAGGTTTATACATAATTTTACAACTCATTACGCAC ACCAGTATAGCGACCAGCATTC (SEQ ID NO.: 2)


seq-MET17-Kan-fwd
GGTTGGCAAATGACTAATTAAG (SEQ ID NO.: 3)


kanMX-rev
CAGTATAGCGACCAGCATTC (SEQ ID NO.: 4)






Competent cells were created and the deletion cassette was transformed into yeast using a kit: Frozen EZ Yeast Transformation II (Zymo Research T2001).


Functionalizing CdS nanoparticles on the yeast cell surface and light experiments 20 mL of yeast culture was grown overnight in CSM media supplemented with all amino acids — leucine, tryptophan, uracil, and histidine. Cultures were grown at 30° C. shaking at 250 rpm. Overnight cultures were diluted down after fourteen hours of growth and resuspended in fresh CSM media supplemented with amino acids to an OD600/mL of 0.2.


Cultures treated with cadmium ions (Cd2+, Sigma) were then treated with 10 uM cadmium for 4 hours, shaking at 250 rpm at 30° C. After cadmium ion treatment, cultures were subjected to UV wavelength light (380 nm, 3×10-6 W/m2/nm, 5.067 mW/cm2) for two hours. After treatment, cultures were spun down at 900xg for 4 minutes, the supernatant was removed, and immediately frozen using liquid nitrogen to preserve the native state.


Transmission Electron Microscopy (TEM) and elemental mapping analysis In all experiments, a non-expressing and non-treated wild-type control was used.


Sample slides of spheroplasted cells were prepared using from a MIT microscopy core. Samples were resuspended in 2 mL of fixative (3% glutaraldehyde, 0.1 M NaCacod pH 7.4, 5 mM CaCl2, 5 mM MgCl2, 2.5% sucrose) for 1 hour at 30° C. with gentle agitation (100 rpm). Cells were spun down at 900xg for 10 minutes.


For the osmium-thiocarbohydrazide-osmium staining: Cells were dispersed them embedded in a 2% ultra-low temperature agarose (made in ddH2O). They were cooled and then cut into 1 mm3 cubes. Cubes were fixed in 1% OsO4/ 1% potassium ferrocyanide in 0.1 M cacodylate/ 5 mM CaCl2, pH 6.8 at room temperature for thirty minutes. Blocks were washed four times in ddH2O for 1 minute each. Blocks were then transferred to 1% thiocarbohydrazide at room temperature for 5 minutes. Blocks were washed four times in ddH2O for 15 minutes each.


Sample slides of non-spheroplasted cells were prepared in-house. Samples were spun down for 15 minutes at 900xg. The supernatant was removed and discarded. Samples were resuspended in 100 uL ddH2O. 10 uL was suspended onto the center of the TEM copper grid. For the wash steps: 1 mL of ddH2O was suspended on the hydrophobic side of parafilm.


Imaging was performed on a JEOL-2100 FEG microscope using the largest area size of the parallel illumination beam with a 100 micron condenser aperture. The microscope was operated at 200 kV with a magnification ranging from 2,000 to 600,000 for assessing the particle shape, particle size, and the atomic arrangement. The images were recorded via a Gatan 2kx2k UltraScan CCD camera. STEM imaging was performed via a high-angle annular dark field (HAADF) detector with a 0.5 nm probe size and 12 cm camera length in order to measure chemical information with energy dispersive X-ray spectroscopy (EDX). Elemental line scanning was performed using EDX via us of an 80 mm2 X-Max detector (Oxford Instrument, UK).


RNA Sequencing and Analysis

RNA extraction: Five OD600 units of cells were collected. Cells were spun down and transferred to 2 mL screw-top Eppendorf tubes. The supernatant was removed then the cells were snap-frozen using liquid nitrogen. The cells were then resuspended in 400 uL TES buffer and 0.2 mL of 400 micron silica beads (OPS Diagnostics) were added. 400 uL of acid phenol (Life Technologies) was added and the samples were left to shake at 65 C for 45 minutes at 1100 rpm in a thermomixer (VWR). The samples were spun down at 14,000xg for 10 minutes. The supernatant was transferred (300 uL) was transferred to 1 mL of ice cold 100% ethanol and 40 uL of 3 M sodium acetate. The samples were mixed and incubated for sixteen hours overnight at 4 C. Pellets were aspirated and dried out in a hood then resuspended in 100 uL ddH2O. They were resupsended on a shaker at 37 C for thirty minutes. A Qiagen RNeasy cleanup cut was used to clean up the sample (Qiagen 74106), with an additional step added to perform an on column DNase digestion (Qiagen 79254). Samples were then eluted with 50 uL of RNase free water. Samples were then transferred to the RNASequencing facility.


Samples were submitted to the BioMicro Center at MIT to be sequenced. All samples were extracted in biological duplicate, and technical triplicate. The entire experiment was done twice.


RNA sequencing data were aligned and summarized using STAR (version 2.5.3a), RSEM (version 1.3.0), SAMtools (version 1.3), and an ENSEMBL gene annotation of S. cerevisiae (3) was used. Differential gene expression analysis was performed with R (version 3.4.4), using DESeq (2_1.18.1). The resulting data were parsed then assembled with Tibco Spotfire Analayst (version 7.11.1). Gene sets for GSEA were procured from GO2MSIG database. All high quality GO annotations were used for Saccharomyces cerevisiae (S288c). Additional sets provided from the Amon Lab at MIT were also used. These sets are called “Gasch_ESR_Rep”, “Gasch_ESR_Ind”, and “TransposableElements”.


Preparing Yeast Cell Lysate for Analysis

Yeast cells were thawed at room temperature and resuspended in 0.5 mg/mL 100T Zymolyase in 1 M Sorbital Citrate buffer at 1 mL per 10 OD600. The resuspended culture was incubated at 30° C. for 1 hour. The resuspended culture was then spun down at 900xg for 15 minutes and the supernatant was removed and kept aside for further analysis. The spheroplasted pellet was resuspended in 3x the volume of the pellet in Yeast Lysis Buffer (Gold Bio, GB-178). The resuspended spheroplasted pellet was incubated on ice for 30 minutes. The lysed cells were centrifuged at 20,000xg for 30 minutes at 4° C. and the clear lysate was collected.


Preparation of Media Supernatant for Analysis

After yeast cultures were grown, they were spun down at 900xg for 15 minutes. The supernatant was removed into new and separate tubes for metabolite analysis. The collected media supernatant was stored at -20° C.


Cell Size Analysis

Cell size was measured using a coulter counter (Multisizer 3 Coulter Counter, Beckmann Coulter). Roughly 200,000 cells were analyzed for cell size in each condition after treatment for six hours - four hours of cadmium treatment and two hours of light/dark treatment.


Measuring Intracellular NAD+/NADH Concentration

Intracellular NAD+ and NADH were measured using Promega’s NAD/NADH Glo Assay (Promega G9072) on the yeast lystates. This luminescent assay works by catalyzing reductase, in the presence of either the metabolite, to reduce a proluciferin reductase substrate to luciferin. The luciferin is proportional to the amount of NAD+ or NADH in the sample. This assay has a detection range of 10 nM to 400 nM.


Measuring Intracellular ATP/ADP Concentration

ATP concentrated was measured using Promega’s CellTiter-Glo Luminescent Assay (Promega G7570) on the yeast lysates. The protocol was not altered. This luminescent assay uses beetle luciferin that is catalyzed to oxyluciferin by the presence of ATP. The tested sensitivity of this assay is between 10-20 and 10-11 moles of luciferase.


Measuring Ethanol Concentration

Intracellular ethanol concentration was measured using Sigma’s Ethanol Assay Kit (Sigma MAK-076) kit on the yeast lysates. The ethanol concentration is determined by a coupled enzyme reaction, with a detection range of 10 uM to 10 nM per well.


Liquid-chromatography Mass-spectrometry (LC/MS) Sample Preparation and Analysis

20 µL of yeast lysate was extracted with 180 µL of 80% methanol containing internal standards. The solution was vortexed for 30 seconds then spun down for ten minutes at 15,000 rpm at 4° C. Relative metabolites abundances were measured using a Dionex UltiMate 3000 ultra-high performance liquid chromatography system connected to a Q Exactive benchtop Orbitrap mass spectrometer equipped with an Ion Max source and a HESI II probe (Thermo Fisher Scientific). To quantify metabolite abundance from resulting, the chromatogram XCalibur QuanBroswer 2.2 (Thermo Fisher Scientific) was used in conjunction with the in-house retention time library of chemical standards.


Measuring Extracellular Glucose Concentration

Extracellular glucose concentration was measured using Sigma’s High Sensitivity Glucose Assay Kit (Sigma MAK-181) on the yeast media supernatant. Glucose concentration is determined by a coupled enzyme assay resulting in a fluorometric readout (λex = 535 nm, λem = 587 nm) that is proportional to glucose concentration. The detection range of this assay is from 20-100 pmole/well.


Measuring Labelled 13C-CO2 incorporation into Intracellular Metabolites through GC-MS

After yeast growth through standard culture, light/dark experiments were performed in a sealed chamber. Within the chamber, 13C-CaCO3 was reacted with HCl to produce 13CO2. Localized atmospheric CO2 was increased to 4%. The incorporation of the labeled CO2 under different conditions was then tested via GC-MS.


500uL of yeast was pelleted and lysed in (4:3:8) methanol:0.88% KCl in water:dichloromethane. The samples were then spun at 15,000 g for 10 minutes, and the polar fraction was collected and dried down under nitrogen gas. Gas-chromatography coupled to mass spectrometry (GCMS) analysis was done as described previously (PMID: 24882210). Dried samples were derivatized with 20µL of methoxamine (MOX) reagent (ThermoFisher TS-45950) and 25µL of N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide with 1% tert-butyldimethylchlorosilane (Sigma 375934). Following derivatization, samples were analyzed using a DB-35MS column ((30 m × 0.25 mm i.d. × 0.25 µm, Agilent J&W Scientific) in an Agilent 7890 gas chromatograph (GC) coupled to an Agilent 5975C mass spectrometer (MS). Data were analyzed and corrected for natural isotope abundance using in-house algorithms.


Statistics

The experimental data are presented with the error bars representing standard deviation. All experiments were done in triplicate. All samples were blinded prior to experiments, resulting in all data being blinded prior to analysis. Statistics were performed using scipy and statsmodels. The chi-squared test and two-way ANOVA test were performed. P values are labelled as: ***P < 0.001, **P < 0.01, *P < 0.05.





TABLE 1






Log fold change gene expression pulling out the differential gene expression caused by the CdS nanoparticles. ΔMet17 + Cd2+ + light versus ΔMet17 + light were tested against each other. Gene names, log fold change values, and p-values are displayed


Gene Name
Log Fold Change
Wald Test P Value




TAR1
0.316585499
2.93356E-52


INO1
0.393514311
0.045219666


BDH2
-0.228409637
0.000199753


PDC1
0.286817387
0.359416135


ERG25
0.438602809
8.21841E-07


ACS1
0.364412318
0.033803006


IRA2
-0.279149068
7.6757E-05


STP3
-0.257057051
0.096040881


ADY2
0.467532171
5.96456E-08


DRE2
-0.352620156
3.66564E-25


JLP1
0.581887841
0.024715494


KGD2
-0.304194935
0.012949936


SSE2
-0.266089633
5.90434E-20


CWP1
0.89002328
3.12072E-63


GAT2
-0.451303045
1.71095E-35


PIG2
-0.297601864
1.30688E-16


YEF3
0.571434423
2.22389E-10


LGE1
-0.439758406
0.006899376


TSL1
-0.378506512
0.000116195


MET4
-0.403292236
1.31778E-06


KRE9
-0.35297309
0.035825782


RPS18A
0.411722848
0.001381963


RPL31A
0.507425214
0.003605124


RPL24A
0.509307931
0.00090274


HUA1
-0.427963179
0.565425426


RPS13
0.457667714
0.265225186


LPD1
-0.427009396
0.070030744


SUR2
-0.476726239
0.44404363


YSY6
0.507622632
0.070289817


RPL43B
0.473806656
0.172731544


RPN1
-0.429161641
0.000484404


DAL80
-0.41560509
0.115844981


GIS3
-0.459162649
0.000120646


ULS1
-0.373723337
3.73215E-06


ARO10
-0.799158441
0.194060763


PET20
-0.593334678
0.017316265


KNS1
-0.409477856
0.008209141


HAA1
-0.392004727
0.003248049


MEP2
-0.670443118
0.844611412


RPS9B
0.63993678
0.047258617


SFT2
-0.416606195
0.000775643


UME6
-0.576219559
0.000167648


MRPS5
0.628380397
0.000357977


MIX14
0.614096785
9.93519E-06


MPM1
-0.513160267
0.035375452


RPL12B
0.608854514
0.002168024


VPS27
-0.457363253
0.249517763


TOS8
-0.35778191
0.000340163


PUF3
-0.453301077
0.589481418


MEP1
-0.703155825
0.689958106


REX2
0.505098981
1.85478E-05


SPT4
0.60626304
0.610491472


TDH2
0.976168323
0.420807637


RPL14A
0.695087541
0.084209561


SDH3
-0.663704792
0.013326403


RPL41B
1.611282088
0.234679145


YIP3
-0.898061543
0.723182711


ENO2
0.823894442
0.001508733


RPL16B
0.6005835
0.138652032


SDP1
-0.534996369
5.65913E-06


PTC3
-0.553134711
0.190948207


CDS1
0.876359493
0.902116534


CAF120
-0.63159292
0.160486145


UGA4
-0.50883639
0.430344122


EXO1
0.813890546
0.001181687


MSB4
0.496464116
0.019087769


NET1
-0.600092224
0.34735793


SRL3
0.72143486
0.79650161


TOK1
-0.521132378
0.183862911


NHP10
-0.572704465
0.657074626


RCR2
-0.660593021
0.001034293


RSM23
0.717105604
0.299376275


ACE2
0.894511096
0.063939462


NOP1
1.056500513
0.294113039


TIF1
-0.902324128
0.000515909


NMA111
-0.732449122
0.011827918


ERD2
0.810005821
0.919542897


SSM4
-0.916692357
0.055119613


RPB7
0.683677225
0.707194342


GUS1
1.032081398
0.011917773


FAU1
0.69625037
0.52104234


MSS2
-0.895652038
0.019147313


ADD37
0.849603986
0.001184318


TCB2
0.635582755
0.796693929


CTR9
-0.74423745
0.848467387


TSR4
-0.674718951
0.501240136


KRR1
0.95817913
0.401397986


RPL33A
0.917343725
0.083293426


RPS22A
0.976411204
0.904347866


MNT4
0.8540384
0.568657495


RPF2
-0.832836868
0.010504341


ATP23
-0.955623416
0.826679846


ASTI
-1.08528461
0.255710519


DMA1
-0.816767181
0.220221411


AAH1
1.146406504
0.383880968


OST5
0.968456005
0.33164699


IMP4

-0.783855887

0.014103337


HEL2
-0.64503454
0.049191843


WSS1
0.941029355
0.975781693


GLY1
-1.349517541
0.145553002


GEP3
0.944575092
0.756124404


SWD1
0.941870129
0.300345848


SKI2
-0.751460348
0.377579773


MPS3
-1.008106684
0.448936774


PKH3
-0.773382811
0.288121693


RIM2
1.037990725
0.320220036


ILS1
-0.952154763
0.308315846


RBL2
1.006317226
0.039032417


CAF130
-0.897127098
0.340951539


RPL22B
1.037657946
0.242623893


UTP10
1.153242764
0.476579373


ARP7
1.136648022
0.088920876


ERG26
1.190852176
0.779702859


MRH4
1.279302519
0.454755115


DDI2
2.300995954
8.86046E-06


NRM1
1.477760327
0.390205386


AIM4
1.442695221
0.882248011


MRE11
1.023299034
0.060650778


DAK2
-1.406147373
0.110060258


SYM1
1.118469015
0.588871853


DCN1
1.234900734
0.194496375


GAS3
1.19533281
0.788984572


SUA5
1.191721783
0.592949197


HEM4
-1.241552917
0.115136363


MDM1
0.900628497
0.703963487


FIRI
-1.257333078
0.311128612


OSW1
1.361725474
0.000390617


PEA2
1.344622629
0.597453941


BUD8
-1.423420634
0.584075378


PHO5
-1.156783335
0.094547619


AVT2
1.230982833
0.345595078


ATP10
-1.2246438
0.584090756


RSA4
1.346038096
0.841032706


RP17B
1.370131812
0.60531762


RAD53
-1.751017412
0.681744345









TABLE 2







Log fold change gene expression pulling out the differential gene expression caused by the UV light treatment. ΔMet17 + Cd2+ + light versus ΔMet17 + Cd2+ were tested against each other. Gene names, log fold change values, and p-values are displayed


Gene Name
Log Fold Change
Wald Test Value
Adjusted P Value (Benjamini-Hochberg)




HXT6
1.956360444
1.13587E-85
1.20288E-82


HSP26
1.507861553
1.72662E-43
3.42842E-41


HSP30
1.2171177
5.28104E-25
4.86315E-23


SPI1
1.383509704
1.57394E-35
2.38114E-33


HSP82
2.401990489
1.28456E-64
5.83009E-62


FIT2
1.164172255
1.68603E-31
1.91304E-29


HSC82
1.823976227
6.448E-61
2.56066E-58


BTN2
2.484071381
1.62463E-74
1.14699E-71


TDH3
1.296717654
1.12007E-32
1.39548E-30


HSP104
2.036397981
4.21151E-75
F 3.345E-72


HAP4
1.20550844
2.94919E-24
2.43366E-22


STI1
2.119467349
1.14353E-61
4.84397E-59


GCN4
1.225903712
1.03528E-24
9.26503E-23


HSP42
1.491985569
1.94095E-39
3.33319E-37


TEF2
1.475221009
7.64279E-46
1.67456E-43


NCE102
1.486833182
1.00959E-58
3.77348E-56


AI1
1.622861063
1.51389E-21
1.0931E-19


PIC2
1.209031549
1.18393E-24
1.04482E-22


HSP78
1.594465432
3.6756E-48
9.3419E-46


PYC1
1.004724491
6.12588E-15
2.9266E-13


SSA4
1.942580683
1.20608E-40
2.25395E-38


ZRT1
2.111514054
2.11975E-90
2.69378E-87


SIS1
2.114090321
2.50332E-71
1.59061E-68


SSC1
1.308340892
4.77304E-22
3.56799E-20


HSP10
1.093157248
7.45922E-14
3.18093E-12


STF2
1.136755594
2.42114E-24
2.05119E-22


HRK1
1.38349281
1.34636E-21
9.83305E-20


CWP2
1.41755554
1.37083E-18
8.88804E-17


STP4
2.874222253
9.0678E-102
1.92056E-98


BDF2
1.497100852
7.81854E-36
1.24198E-33


HTA1
1.342417439
2.35495E-27
2.33802E-25


FES1
2.373704712
3.19922E-50
9.23993E-48


SSE1
2.146770206
3.20839E-69
1.69884E-66


IRA2
1.671009588
6.26667E-34
8.47586E-32


YHB1
1.217842998
6.05111E-12
2.12424E-10


CDC48
1.112884625
1.88546E-20
1.31651E-18


DRE2
1.104358024
1.26593E-14
5.8288E-13


HSP60
1.688338712
1.22068E-46
2.87267E-44


ENO1
1.170534894
7.78197E-17
4.33742E-15


MDJ1
1.443445729
5.19665E-24
4.23327E-22


BAT2
1.056547681
1.04485E-14
4.91777E-13


SSA1
1.76556869
6.32321E-41
1.2175E-38


COX1
1.174773426
1.84439E-16
9.93157E-15


APJ1
1.681666448
4.01894E-33
5.32008E-31


GAP1
1.588740009
5.55607E-35
8.21006E-33


TDH1
1.299616565
5.36105E-24
4.31191E-22


MPC2
1.821922021
9.48664E-32
1.11626E-29


CPR6
1.752872727
9.59266E-48
2.3443E-45


DSE4
1.319798553
1.67172E-16
9.0787E-15


RGI1
1.189270919
1.44934E-16
7.93887E-15


MBF1
1.034957585
3.40785E-11
1.08811E-09


SSE2
1.128539079
7.27249E-16
3.72657E-14


PIN3
1.068582487
1.13751E-12
4.32798E-11


CYT1
1.076396952
7.25928E-17
4.0819E-15


AI2
2.344313048
1.30318E-32
1.59239E-30


ATP16
1.169486335
3.26552E-17
1.88628E-15


GLK1
1.119295036
2.55255E-11
8.27496E-10


HXT7
1.726284159
6.01589E-30
6.47881E-28


PDA1
1.167046412
7.345E-18
4.40284E-16


AATI
2.594379326
3.83466E-70
2.21504E-67


LYS14
1.20878494
1.56441E-17
9.28998E-16


ISF1
1.05641019
1.41961E-15
7.10252E-14


GLN1
1.241916599
4.48058E-13
1.7683E-11


EIS1
1.184453062
4.42306E-11
1.40521E-09


PRC1
1.22656479
2.53359E-18
1.5939E-16


TMA19
1.007216747
6.14189E-11
1.90369E-09


TRR1
1.188474772
5.86958E-14
2.5371E-12


COR1
1.232027998
2.65555E-14
1.19669E-12


NDI1
1.338976739
1.2603E-13
5.20988E-12


SGT2
1.576691742
2.1956E-28
2.28702E-26


UGA1
1.050061414
3.21521E-11
1.03179E-09


LAT1
1.353517596
1.85588E-20
1.31025E-18


HXK1
2.181407991
7.97949E-46
1.69006E-43


PCL5
1.009358852
5.91082E-13
2.30413E-11


CTR1
2.002267708
1.6279E-27
1.64185E-25


LST8
1.251491901
5.10932E-12
1.83416E-10


GUT2
1.158053523
4.87298E-09
1.15966E-07


OYE2
1.556792777
2.08748E-15
1.0203E-13


lXR1
1.339268285
1.99771E-16
1.06668E-14


UBC4
1.202049736
5.73344E-10
1.56353E-08


YDJ1
1.795124378
6.39849E-22
4.72744E-20


BAP3
1.235836361
1.46427E-09
3.7516E-08


UTH1
1.52628255
3.78861E-12
1.3835E-10


ALT1
2.614372661
2.01532E-46
4.57334E-44


SCW4
2.232934737
2.91814E-31
3.25296E-29


YAK1
1.097010779
3.95609E-10
1.13742E-08


COM2
1.575920311
3.49822E-18
2.15803E-16


THI4
1.361045341
1.35588E-08
2.99141E-07


A14
1.305419711
2.54952E-11
8.27496E-10


VHR1
1.079155961
6.17695E-10
1.66306E-08


DAL80
1.410660943
4.97601E-14
2.16559E-12


GIS3
1.274387956
3.18996E-11
1.02888E-09


ACA1
2.600064495
5.24747E-40
9.5264E-38


RTK1
1.235778303
5.44983E-12
1.93454E-10


SNQ2
1.134039254
6.26568E-09
1.46368E-07


REE1
2.573960349
4.03823E-45
8.27707E-43


CAB2
1.41238652
3.34243E-17
1.91331E-15


PMA1
1.858406007
1.2627E-13
5.20988E-12


MEP2
2.17630025
5.75199E-19
3.76785E-17


MTL1
1.122794847
1.24145E-07
2.35468E-06


LEU2
1.271763909
8.44812E-13
3.25329E-11


RPL35B
1.195619715
0.003882638
0.023273853


YAP1801
1.150034571
3.84444E-09
9.32349E-08


PSA1
1.030985195
1.90609E-06
2.90439E-05


ARB1
1.247153863
5.57226E-11
1.74414E-09


ASN1
1.794286386
2.97236E-18
1.8516IE-16


TP03
1.076871609
1.40377E-06
2.22988E-05


AI5_BETA
1.175796615
2.5909E-07
4.78563E-06


RTS3
1.316017431
4.00067E-10
1.13992E-08


FMS1
1.111117259
8.941E-08
1.74803E-06


COQ9
1.076995916
2.32442E-09
5.88422E-08


PDB1
1.232154613
1.07959E-06
1.78639E-05


PST2
1.00680877
1.76335E-08
3.78524E-07


HOM2
1.345379852
6.0056E-07
1.04834E-05


ARG4
1.535205092
2.66015E-09
6.62846E-08


ERO1
2.201900403
2.06005E-16
1.0908E-14


EMI2
1.616886642
1.67517E-17
9.85558E-16


CTH1
1.664419817
7.80902E-16
3.96948E-14


EAF7
1.107144149
6.91746E-07
1.19439E-05


VHS1
1.456331198
4.43101E-12
1.60884E-10


OLA1
1.353739166
2.12293E-13
8.59177E-12


TSA2
1.600127684
6.91418E-16
3.57177E-14


MSN4
1.196137854
6.60251E-06
8.92604E-05


MCM1
1.305831308
2.51186E-08
5.34951E-07


ZPR1
1.875999842
6.03195E-09
1.41428E-07


UTR1
1.066006468
2.35746E-09
5.94417E-08


YRO2
2.436177285
2.86299E-22
2.16565E-20


ZRC1
1.047681442
1.03238E-06
1.71721E-05


SNU13
1.195400142
4.37664E-05
0.000493946


FRE3
1.153647335
5.08089E-10
1.41596E-08


ADE3
1.13221044
2.80213E-06
4.09304E-05


KIN82
1.278952486
5.87925E-10
1.58965E-08


GSP1
1.022127262
0.000222718
0.002013017


YAR1
1.453508427
2.99567E-07
5.45401E-06


OYE3
1.477120456
1.02204E-11
3.47275E-10


ARO1
1.368004705
5.83491E-07
1.02417E-05


RGM1
1.26207715
5.59627E-10
1.53934E-08


GAC1
1.493832249
4.06118E-14
1.80453E-12


PXR1
1.30235573
2.11015E-11
6.9471E-10


BUD27
1.298935286
3.88857E-07
6.921E-06


VMA2
1.067646468
2.95543E-05
0.000347755


KSP1
1.048173315
8.32619E-05
0.000868712


ILV2
1.787795887
1.72874E-10
5.13292E-09


MIT1
1.574936982
5.73547E-18
3.47078E-16


GIS4
1.261440253
1.23489E-07
2.34925E-06


AVT4
1.107692867
1.00744E-05
0.000132806


AVT6
1.206525517
1.69234E-05
0.00021027


MSH3
1.313227856
4.38806E-09
1.06014E-07


NOP16
1.387416032
1.34612E-09
3.47694E-08


PMP2
1.187752565
0.000192814
0.001780729


YFH7
1.040510839
0.000405729
0.003428196


UGA4
1.604647041
8.84336E-10
2.32193E-08


SUC2
1.506267641
2.84815E-08
5.99244E-07


DAL2
1.372682001
9.97602E-09
2.26384E-07


KTI12
1.35488162
1.236E-06
1.99836E-05


BNA6
1.200540926
3.1474E- 07
5.68141E-06


NUP100
1.745531022
1.74648E-10
5.16145E-09


NOP19
1.347422541
3.47294E-06
5.00387E-05


PAB1
1.143399564
6.30959E-06
8.58482E-05


YAP6
1.754624556
5.30459E-12
1.89356E-10


UBX3
1.121419965
1.09226E-06
1.79799E-05


PER33
1.433260147
4.50507E-06
6.29125E-05


STE24
1.379720533
6.77396E-10
1.81611E-08


SPO75
1.41546421
4.55372E-08
9.36386E-07


MRT4
2.346979433
1.19269E-08
2.64976E-07


RKM5
1.071321207
0.000140029
0.001356315


FRE1
1.438547473
4.06837E-06
5.74454E-05


COQ6
1.080486274
6.09252E-05
0.000668599


ARO4
1.536576434
0.000131288
0.001287354


GUS1
1.034993292
0.000515287
0.004197605


ARO80
1.062394328
0.000693478
0.005501071


ERR1
1.173738057
1.36431E-06
2.17264E-05


ERR2
1.173738057
1.36431E-06
2.17264E-05


MAL11
1.315537506
3.56821E-06
5.11792E-05


FAR11
1.017499895
0.003215557
0.019913885


GZF3
1.388280309
1.42927E-06
2.24791E-05


CMR3
2.460321846
9.64098E-14
4.05687E-12


SYP1
1.330455072
1.76233E-06
2.72454E-05


ILV3
1.197357959
0.002701664
0.017349931


APA1
1.304202473
0.000350622
0.003010609


IML2
1.135591154
0.00264674
0.01705617


COS10
1.637676185
8.546E-06
0.000113128


HOL1
1.066441132
0.001095533
0.00806607


YPQ2
1.005105297
0.005778533
0.031955437


PLC1
1.255360718
4.42924E-06
6.19898E-05


SOL1
1.051191216
3.98913E-05
0.000451817


VMA6
1.192932877
1.7985E-05
0.000221467


RPL33A
1.36078849
0.00121483
0.008758464


ARO8
1.364444551
3.30212E-05
0.000382877


KAP95
1.37215159
6.85549E-05
0.000738302


TIP1
1.09847651
0.000199006
0.001827288


RRT13
1.044931214
0.000484246
0.004001169


ARG81
1.700302224
8.21082E-05
0.000859498


DAL3
1.165541421
0.000438638
0.003662451


ABZ1
1.164055084
0.000102692
0.001042345


MKK1
1.653611577
5.22281E-08
1.06025E-06


SNT309
1.547509925
9.83937E-08
1.90028E-06


SIZ1
1.065747542
0.002110132
0.013995591


SEC15
1.090292312
0.000343432
0.002960881


QNS1
1.294625652
5.32319E-05
0.000591321


AOS1
1.182206751
0.000808268
0.006270738


CIT3
1.457322169
5.62709E-06
7.77273E-05


FDC1
1.227017655
0.001606312
0.011166854


PTR2
1.529217751
8.03916E-06
0.000106864


CHC1
1.466886589
3.18931E-05
0.000371152


RPC82
1.095581179
0.001030924
0.007661391


DYN1
1.012201794
0.003829259
0.023062663


BI3
1.393383108
0.000496982
0.004082613


DAN4
1.273044771
0.000225319
0.002030748


DED1
1.389817328
0.000174704
0.001622904


PDP3
1.174180175
0.005349132
0.029945716


NSA2
1.725367765
0.001292743
0.009250099


NUP57
1.042171247
0.005576597
0.031078512


APQ13
1.339125424
0.002660982
0.017126777


IRE1
1.193670147
0.002663087
0.017126777


OAC1
1.45731305
0.009988961
0.049741268


CAN1
1.417674266
0.001508491
0.010556115


GIP1
1.25146408
0.000215244
0.001959403


RRP12
1.379731454
0.00298219
0.018869928


RRB1
1.495099945
0.003964195
0.023673399


DAL5
1.242407747
0.001022029
0.007606339


VAR1
1.691427
0.000285511
0.002509177


PPX1
1.329682598
0.002642836
0.017048306


POP3
1.581887054
0.005423444
0.030281693


VTH1
2.919092817
4.89536E-05
0.000548591


OPT2
1.167032729
0.008986628
0.046385896


GRX4
1.459288808
0.000935294
0.007066416


MMM1
1.311764447
0.004425362
0.025892036


BSC5
1.668584387
0.006602212
0.03585509


LEU9
1.520453839
0.004915174
0.028085443









TABLE 3








Positively enriched genes through GSEA involved in ATP metabolic processes


PROBE
RANK IN GENE LIST
RANK METRIC SCORE
RUNNING ES
CORE ENRICHMENT




ATP16
63
8.436654
0.03682
Yes


ATP4
65
8.406623
0.085863
Yes


CYT1
66
8.342733
0.134733
Yes


COX1
71
8.231789
0.182153
Yes


NDI1
92
7.410284
0.22156
Yes


ATP2
95
7.329973
0.264097
Yes Yes


QCR2
96
7.300665
0.306863
Yes


ATP1
112
6.827048
0.343854
Yes


QCR7
114
6.762463
0.383266
Yes


ATP14
143
6.156174
0.413728
Yes


COX6
164
5.734332
0.443318
Yes


QCR6
171
5.656575
0.475252
Yes


ATP3
180
5.513893
0.505951
Yes


ATP7
181
5.500307
0.538171
Yes


ATP18
208
5.145989
0.563115
Yes


QCR10
351
3.92371
0.557699
Yes


ATP6
358
3.871836
0.579179
Yes


COX9
387
3.676723
0.595116
Yes


COX4
393
3.64507
0.615468
Yes


QCR8
446
3.316365
0.624494
Yes


ATP17
541
2.835934
0.622307
Yes


OLI1
564
2.754525
0.634042
Yes


TIM11
578
2.680261
0.647142
Yes


COX8
587
2.641923
0.661018
Yes


ATP5
596
2.609273
0.674702
Yes


COX5A
660
2.416687
0.676259
Yes


TAZ1
661
2.405348
0.690348
Yes


ATP15
672
2.358564
0.702164
Yes


COX7
812
2.030624
0.686259
No


RIP1
928
1.790093
0.673745
No


COB
1030
1.612267
0.662989
No


SDH4
1100
1.506127
0.658012
No


SDH2
1157
1.416422
0.655109
No


ATP19
1237
1.291178
0.646872
No


SDH1
1412
1.077623
0.618385
No


ATP20
1493
0.981492
0.608134
No


QCR9
1628
0.794693
0.585989
No


COX2
1641
0.775791
0.588133
No


GSM1
1907
0.505049
0.538092
No


SDH3
2038
0.381977
0.514329
No


COX3
2465
0.027086
0.429288
No


COX5B
2543
-0.03951
0.414119
No


CYC7
2633
-0.13394
0.397104
No


ATP8
2685
-0.17228
0.387913
No


CYC1
4439
-2.09115
0.049563
No


SHH4
5032
-12.1954
0.0026
No









TABLE 4








Positively enriched genes through GSEA involved in the generation of metabolite and metabolite precursors


PROBE
RANK IN GENE LIST
RANK METRIC SCORE
RUNNING ES
CORE ENRICHMENT




HXK1
18
14.20967
0.027483
Yes


TDH3
30
11.90459
0.051341
Yes


HAP4
43
10.16136
0.071172
Yes


TDH1
45
10.10294
0.093123
Yes


AI1
50
9.533964
0.113212
Yes


CYT1
66
8.342733
0.128442
Yes


ENO1
67
8.33451
0.146719
Yes


RGI1
69
8.260607
0.16463
Yes


COX1
71
8.231789
0.182477
Yes


ISF1
79
7.983743
0.198554
Yes


COR1
85
7.61409
0.21423
Yes


GAC1
86
7.55902
0.230806
Yes


NDI1
92
7.410284
0.246035
Yes


QCR2
96
7.300665
0.261431
Yes


QCR7
114
6.762463
0.272787
Yes


GLK1
117
6.670315
0.287006
Yes


MDH1
129
6.359677
0.298705
Yes


COX6
164
5.734332
0.304332
Yes


IDH1
170
5.658953
0.31572
Yes


QCR6
171
5.656575
0.328125
Yes


GLC7
172
5.64327
0.3405
Yes


PET10
193
5.338264
0.34812
Yes


TAR1
194
5.333929
0.359817
Yes


PAH1
197
5.303865
0.371039
Yes


FUM1
204
5.234492
0.381292
Yes


ADH3
219
4.989831
0.389373
Yes


KGD1
220
4.98782
0.400311
Yes


CIT1
243
4.777311
0.406292
Yes


GPH1
251
4.712177
0.415195
Yes


CIT3
269
4.539937
0.421677
Yes


PSK1
280
4.469924
0.429436
Yes


GLC8
282
4.45793
0.439008
Yes


IDH2
304
4.20742
0.443943
Yes


ADE16
307
4.182589
0.452707
Yes


QCR10
351
3.92371
0.452525
Yes


REG1
369
3.803018
0.457391
Yes


GDB1
379
3.72335
0.463717
Yes


COX9
387
3.676723
0.470349
Yes


PFK1
388
3.676702
0.478412
Yes


COX4
393
3.64507
0.485588
Yes


GSY2
410
3.517181
0.490032
Yes


AAC1
425
3.42126
0.494674
Yes


QCR8
446
3.316365
0.497859
Yes


GDS1
455
3.256814
0.503367
Yes


ADH5
505
2.963919
0.499854
Yes


BMH2
509
2.961417
0.505735
Yes


COX13
520
2.917452
0.51009
Yes


GIP2
536
2.859262
0.513295
Yes


PCL10
550
2.796241
0.51677
Yes


GCR2
567
2.743029
0.519516
Yes


GSY1
568
2.740006
0.525525
Yes


ATF1
571
2.724546
0.531019
Yes


COX8
587
2.641923
0.53382
Yes


GLG1
640
2.473786
0.528619
Yes


COX5A
660
2.416687
0.530036
Yes


TAZ1
661
2.405348
0.535311
Yes


GLC3
663
2.40101
0.540372
Yes


PFK27
665
2.39152
0.545412
Yes


CSF1
740
2.199048
0.535114
No


NDE1
754
2.148085
0.537168
No


PUF3
761
2.139955
0.540635
No


COX7
812
2.030624
0.534871
No


ADH1
862
1.908086
0.529043
No


ADH4
876
1.870776
0.530489
No


RIP1
928
1.790093
0.523994
No


DLD1
1021
1.626894
0.508763
No


COB
1030
1.612267
0.510664
No


PPG1
1050
1.584502
0.510256
No


IGD1
1095
1.51167
0.504581
No


SDH4
1100
1.506127
0.507066
No


LSC2
1119
1.4488
0.506622
No


TYE7
1122
1.473071
0.509443
No


MBR1
1142
1.440608
0.50872
No


SDH2
1157
1.416422
0.508966
No


PGK1
1193
1.365402
0.504808
No


HAP1
1195
1.360008
0.507586
No


ETR1
1294
1.216719
0.49023
No


SDH1
1412
1.077623
0.468686
No


RIB3
1448
1.032143
0.463798
No


PCL6
1477
1.002301
0.460275
No


RAP1
1490
0.983831
0.45998
No


PFK2
1491
0.983416
0.462137
No


SHP1
1511
0.954816
0.460348
No


YMR31
1513
0.952786
0.462233
No


PCL7
1534
0.925702
0.460177
No


PDC5
1563
0.881775
0.456389
No


QCR9
1628
0.794693
0.445055
No


CDC19
1640
0.778471
0.444514
No


COX2
1641
0.775791
0.446215
No


NCA2
1654
0.765868
0.445443
No


GSM1
1907
0.50549
0.395059
No


SDH3
2038
0.381977
0.369333
No


ALG6
2088
0.32789
0.36004
No


PDC1
2100
0.317477
0.358489
No


HAP2
2103
0.316796
0.358775
No


AAC3
2140
0.294268
0.352064
No


PGI1
2217
0.227661
0.337034
No


MCT1
2277
0.16628
0.325343
No


GCR1
2299
0.144194
0.321368
No


UGP1
2377
0.082331
0.305815
No


COQ10
2403
0.060705
0.30084
No


COX3
2465
0.027086
0.288435
No


COX5B
2543
-0.03951
0.272788
No


YPI1
2561
-0.06379
0.269455
No


PSK2
2616
-0.11901
0.258682
No


CYC7
2633
-0.13394
0.255706
No


PDC2
2694
-0.18021
0.243841
No


COQ5
2744
-0.22164
0.234315
No


FBA1
2764
-0.23768
0.230954
No


PCL8
2806
0.26912
0.223167
No


PGM2
2900
-0.34928
0.20493
No


JAC1
2984
-0.42152
0.188894
No


LSC1
3061
-0.4711
0.174398
No


SGA1
3082
-0.48928
0.171385
No


PPA2
3225
-0.62629
0.143743
No


CBP1
3240
-0.64405
0.142295
No


GPM1
3295
-0.69713
0.13279
No


AAP1
3425
-0.81869
0.108226
No


OAR1
3433
-0.82541
0.108606
No


HXK2
3666
-1.02541
0.063449
No


PET20
3700
-1.06073
0.059033
No


HAP3
3818
-1.17041
0.037692
No


PHO85
3910
-1.28298
0.021912
No


PIG1
3954
-1.33801
0.016059
No


TPI1
3956
-1.33879
0.018791
No


COX20
3971
-1.36016
0.018913
No


MIX14
4007
-1.40728
0.014847
No


MIX17
4018
-1.42181
0.015922
No


SLS1
4110
-1.53682
6.98E-04
No


ATF2
4114
-1.5412
0.003465
No


SDH5
4126
-1.56529
0.00465
No


ALG7
4280
-1.80189
-0.02266
No


PIG2
4293
-1.8148
-0.02113
No


CYC1
4439
-2.09115
-0.04618
No


ENO2
4447
-2.11443
-0.04297
No


PET9
4548
-2.36255
-0.05822
No


RMD9
4549
-2.36316
-0.05304
No


MNP1
4563
-2.40112
-0.05043
No


HAP5
4588
-2.45789
-0.04994
No


ACO1
4640
-2.58321
-0.0547
No


TDH2
4709
-2.83234
-0.06238
No


GLG2
4717
-2.85237
-0.05756
No


RSF1
4722
-2.86983
-0.05208
No


PGM1
4743
-2.97564
-0.04965
No


COX11
4823
-3.40976
-0.05831
No


NDE2
4878
-3.81771
-0.06097
No


SOD1
4886
-3.87253
-0.05391
No


ACS1
4929
-4.40536
-0.05283
No


MAM33
4944
-4.66876
-0.04545
No


BMH1
4967
-5.13864
-0.03868
No


SHH4
5032
-12.1954
-0.02501
No


RGI2
5034
-12.5252
0.002248
No









TABLE 5








Cell size measured via a Coulter counter


Strain
Mean Diameter (µm)
Median
Standard Deviation
Count




W303α
5.747
5.688
1.7
208.181


W303α
5.79
5.708
1.639
180.954


W303α + light
5.797
5.719
1.657
189.964


W303α + Cd + light
5.815
5.734
1.689
201.924









ΔMet17
5.453
5.419
1.609
126.784


ΔMet17 + Cd
5.574
5.549
1.652
141.717


ΔMet17 + light
5.563
5.543
1.649
144.139


ΔMet17 + Cd + light
5.55
5.516
1.687
178.268





Y567
5.669
5.583
1.744
229.242


Y567 + Cd
5.765
5.676
1.683
205.561


Y567 + light
5.807
5.746
1.596
172.302


Y567 + Cd + light
5.81
5.739
1.683
201.655





Y567::ΔMet17
5.533
5.495
1.648
143.732


Y567::ΔMet17 + Cd
5.593
5.561
1.667
163.638


Y567::ΔMet17 + light
5.597
5.561
1.666
163.638


Y567::ΔMet17 + Cd + light
5.603
5.573
1.656
141.52









TABLE 6






Doubling times from growth experiments in synthetic media


Strain Mean
Doubling Time (minutes)
Standard Deviation (minutes)




W303α
1.41
4.26


W303α
140
3.08


W303α + light
143
5.25


W303α + Cd + light
142
3.71





ΔMet17
144
3.44


ΔMet17 + Cd
140
3.82


ΔMet17 + light
145
5.14


ΔMet17 + Cd + light
142
4.71





Y567
137
3.48


Y567 + Cd
142
3.36


Y567 + light
143
4.37


Y567 + Cd + light
140
3.32





Y567::ΔMet17
140
3.56


Y567::ΔMet17 + Cd
141
4.08


Y567::ΔMet17 + light
142
5.16


Y567::ΔMet17 + Cd + light
141
4.44






Other embodiments are within the scope of the following claims.

Claims
  • 1. A system for production of a chemical product comprising: a cell;a nanoparticle on a surface of the cell; andan irradiation unit configured to expose the cell to irradiation.
  • 2. The system of claim 1, wherein the cell is a yeast cell.
  • 3. The system of claim 1, wherein a thiol synthesis pathway is deleted from the cell.
  • 4. The system of claim 3, wherein the thiol synthesis pathway includes Met17.
  • 5. The system of claim 1, wherein the nanoparticle includes cadmium.
  • 6. The system of claim 1, wherein the nanoparticle includes cadmium sulfide.
  • 7. The system of claim 1, wherein the irradiation unit includes an ultraviolet (UV) light source.
  • 8. The system of claim 1, wherein the system includes a bioreactor including the irradiation unit configured to irradiate contents of the bioreactor.
  • 9. A method of producing a chemical product comprising: providing a cell having a nanoparticle on a surface of the cell;exposing the cell to a precursor;irradiating the cell;converting the precursor to a chemical product with the cell; andcollecting the chemical product.
  • 10. The method of claim 9, wherein the cell is a yeast cell.
  • 11. The method of claim 9, wherein a thiol synthesis pathway is deleted from the cell.
  • 12. The method of claim 11, wherein the thiol synthesis pathway includes Met17.
  • 13. The method of claim 9, wherein the nanoparticle includes cadmium.
  • 14. The method of claim 9, wherein the nanoparticle includes cadmium sulfide.
  • 15. The method of claim 9, wherein the irradiating the cell includes irradiating ultraviolet (UV) light.
  • 16. The method of claim 9, wherein the chemical product is a biofuel.
  • 17. The method of claim 9, wherein the chemical product is ethanol.
  • 18. The method of claim 9, wherein the precursor includes glucose.
  • 19. The method of claim 9, wherein the precursor includes carbon dioxide.
PRIORITY CLAIM

This application claims priority to U.S. Provisional Application No. 63/037,546, filed Jun. 10, 2021, which is incorporated by reference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with Government support under Grant No. HR0011-18-2-0049 awarded by the Defense Advanced Research Projects Agency (DARPA). The Government has certain rights in the invention.

PCT Information
Filing Document Filing Date Country Kind
PCT/US2021/036624 6/9/2021 WO
Provisional Applications (1)
Number Date Country
63037546 Jun 2020 US