Skip to main content

Advertisement

SpringerLink
Log in

Using yeast to sustainably remediate and extract heavy metals from waste waters

  • Article
  • Published:

From Nature Sustainability

View current issue Submit your manuscript

Abstract

Our demand for electronic goods and fossil fuels has challenged our ecosystem with contaminating amounts of heavy metals, causing numerous water sources to become polluted. To counter heavy-metal waste, industry has relied on a family of physicochemical processes, with chemical precipitation being one of the most commonly used. However, the disadvantages of chemical precipitation are vast, including the generation of secondary waste, technical handling of chemicals and need for complex infrastructures. To circumvent these limitations, biological processes to naturally manage waste have been sought. Here, we show that yeast can act as a biological alternative to traditional chemical precipitation by controlling naturally occurring production of hydrogen sulfide (H2S). Sulfide production was harnessed by controlling the sulfate assimilation pathway, where strategic knockouts and culture conditions generated H2S from 0 to over 1,000 ppm (~30 mM). These sulfide-producing yeasts were able to remove mercury, lead and copper from real-world samples taken from the Athabasca oil sands. More so, yeast surface display of biomineralization peptides helped control for size distribution and crystallinity of precipitated metal sulfide nanoparticles. Altogether, this yeast-based platform not only removes heavy metals but also offers a platform for metal re-extraction through precipitation of metal sulfide nanoparticles.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1: Engineering the yeast sulfate assimilation pathway to generate H2S.
Fig. 2: Uptake of Cu, Zn, Cd, Pb and Hg with ΔMET17 sulfide-producing strains.
Fig. 3: Treatment of effluent from the Athabasca oil sands using sulfide-producing yeast.
Fig. 4: Controlled size distribution of cadmium sulfide particles by controlling sulfide production rates.
Fig. 5: Analysis of isolated precipitated cadmium sulfide particles as a function of hexa-amino acid displayed peptides.

Similar content being viewed by others

Data availability

The datasets generated and analysed during the current study are available from the corresponding author upon request. The source data underlying Figs. 1c, 1d, 2a, 3c, 4a–c, 5e and Extended Data 2a, 2c and 3b are provided as a Source Data File.

References

  1. Rucevska, I. et al. Waste Crime–Waste Risks: Gaps in Meeting the Global Waste Challenge (UNEP and GRID-Arendal, 2015); https://go.nature.com/38RZ1cY

  2. Balde, C. P., Forti, V., Gray, V., Kuehr, R. & Stegmann, P. The Global e-Waste Monitor 2017: Quantities, Flows and Resources (United Nations University, International Telecommunication Union and International Solid Waste Association, 2017).

  3. Statistics: All Mining (CDC, 2018); https://www.cdc.gov/niosh/mining/statistics/allmining.html

  4. DeGraff, J. V. in Understanding and Responding to Hazardous Substances at Mine Sites in the Western United States (ed. DeGraff, J. V.) 1–8 (Geological Society of America, 2007).

  5. Fu, F. & Wang, Q. Removal of heavy metal ions from wastewaters: a review. J. Environ. Manage. 92, 407–418 (2011).

    CAS  Google Scholar 

  6. Kang, D. H. P., Chen, M. & Ogunseitan, O. A. Potential environmental and human health impacts of rechargeable lithium batteries in electronic waste. Environ. Sci. Technol. 47, 5495–5503 (2013).

    CAS  Google Scholar 

  7. Song, X., Hu, S., Chen, D. & Zhu, B. Estimation of waste battery generation and analysis of the waste battery recycling system in China. J. Ind. Ecol. 21, 57–69 (2017).

    Google Scholar 

  8. Kurniawan, T. A., Chan, G. Y. S., Lo, W.-H. & Babel, S. Physico–chemical treatment techniques for wastewater laden with heavy metals. Chem. Eng. J. 118, 83–98 (2006).

    CAS  Google Scholar 

  9. Barakat, M. A. New trends in removing heavy metals from industrial wastewater. Arab. J. Chem. 4, 361–377 (2011).

    CAS  Google Scholar 

  10. Gupta, K. V., Ali, I., A. Saleh, T., Nayak, A. & Agarwal, S. Chemical treatment technologies for waste-water recycling—an overview. RSC Adv. 2, 6380–6388 (2012).

    CAS  Google Scholar 

  11. Gavrilescu, M., Demnerová, K., Aamand, J., Agathos, S. & Fava, F. Emerging pollutants in the environment: present and future challenges in biomonitoring, ecological risks and bioremediation. New Biotechnol. 32, 147–156 (2015).

    CAS  Google Scholar 

  12. Singh, A. & Prasad, S. M. Remediation of heavy metal contaminated ecosystem: an overview on technology advancement. Int. J. Environ. Sci. Technol. 12, 353–366 (2015).

    CAS  Google Scholar 

  13. Gadd, G. M. Microbial influence on metal mobility and application for bioremediation. Geoderma 122, 109–119 (2004).

    CAS  Google Scholar 

  14. Wiatrowski, H. A., Ward, P. M. & Barkay, T. Novel reduction of mercury (II) by mercury-sensitive dissimilatory metal reducing bacteria. Environ. Sci. Technol. 40, 6690–6696 (2006).

    CAS  Google Scholar 

  15. Silver, S. & Phung, L. T. Genes and enzymes involved in bacterial oxidation and reduction of inorganic arsenic. Appl. Environ. Microbiol. 71, 599–608 (2005).

    CAS  Google Scholar 

  16. Picard, A., Gartman, A., Clarke, D. R. & Girguis, P. R. Sulfate-reducing bacteria influence the nucleation and growth of mackinawite and greigite. Geochim. Cosmochim. Acta 220, 367–384 (2018).

    CAS  Google Scholar 

  17. Gartman, A. et al. Microbes facilitate mineral deposition in bioelectrochemical systems. ACS Earth Space Chem. 1, 277–287 (2017).

    CAS  Google Scholar 

  18. Jong, T. & Parry, D. L. Removal of sulfate and heavy metals by sulfate reducing bacteria in short-term bench scale upflow anaerobic packed bed reactor runs. Water Res. 37, 3379–3389 (2003).

    CAS  Google Scholar 

  19. Kieu, H. T. Q., Müller, E. & Horn, H. Heavy metal removal in anaerobic semi-continuous stirred tank reactors by a consortium of sulfate-reducing bacteria. Water Res. 45, 3863–3870 (2011).

    CAS  Google Scholar 

  20. Neculita, C.-M., Zagury, G. J. & Bussière, B. Passive treatment of acid mine drainage in bioreactors using sulfate-reducing bacteria. J. Environ. Qual. 36, 1–16 (2007).

    CAS  Google Scholar 

  21. Lovley, D. R. Cleaning up with genomics: applying molecular biology to bioremediation. Nat. Rev. Microbiol. 1, 35–44 (2003).

    CAS  Google Scholar 

  22. Shiratori, T., Inoue, C., Sugawara, K., Kusano, T. & Kitagawa, Y. Cloning and expression of Thiobacillus ferrooxidans mercury ion resistance genes in Escherichia coli. J. Bacteriol. 171, 3458–3464 (1989).

    CAS  Google Scholar 

  23. Wang, C. L., Maratukulam, P. D., Lum, A. M., Clark, D. S. & Keasling, J. D. Metabolic engineering of an aerobic sulfate reduction pathway and its application to precipitation of cadmium on the cell surface. Appl. Environ. Microbiol. 66, 4497–4502 (2000).

    CAS  Google Scholar 

  24. Krämer, U. & Chardonnens, A. The use of transgenic plants in the bioremediation of soils contaminated with trace elements. Appl. Microbiol. Biotechnol. 55, 661–672 (2001).

    Google Scholar 

  25. Sayler, G. S. & Ripp, S. Field applications of genetically engineered microorganisms for bioremediation processes. Curr. Opin. Biotechnol. 11, 286–289 (2000).

    CAS  Google Scholar 

  26. Vieira, É. D., da Graça Stupiello Andrietta, M. & Andrietta, S. R. Yeast biomass production: a new approach in glucose-limited feeding strategy. Braz. J. Microbiol. 44, 551–558 (2013).

    Google Scholar 

  27. Worldwide Beer Production, 2016 (Barth-Haas Group, 2018).

  28. Value of the Yeast Product Market Worldwide from 2016 to 2022 (in Billions U.S. Dollars) (PR Newswire, 2017).

  29. Swiegers, J. H. & Pretorius, I. S. Modulation of volatile sulfur compounds by wine yeast. Appl. Microbiol. Biotechnol. 74, 954–960 (2007).

    CAS  Google Scholar 

  30. Linderholm, A. L., Findleton, C. L., Kumar, G., Hong, Y. & Bisson, L. F. Identification of genes affecting hydrogen sulfide formation in Saccharomyces cerevisiae. Appl. Environ. Microbiol. 74, 1418–1427 (2008).

    CAS  Google Scholar 

  31. Rickard, D. & Luther, G. W. Metal sulfide complexes and clusters. Rev. Mineral. Geochem. 61, 421–504 (2006).

    CAS  Google Scholar 

  32. Bolong, N., Ismail, A. F., Salim, M. R. & Matsuura, T. A review of the effects of emerging contaminants in wastewater and options for their removal. Desalination 239, 229–246 (2009).

    CAS  Google Scholar 

  33. Johnson, D. B. & Hallberg, K. B. Acid mine drainage remediation options: a review. Sci. Total Environ. 338, 3–14 (2005).

    CAS  Google Scholar 

  34. Table of Regulated Drinking Water Contaminants (EPA, 2019).

  35. Secondary Drinking Water Standards: Guidance for Nuisance Chemicals (EPA, 2019).

  36. Sparks, B. D., Kotlyar, L. S., O’Carroll, J. B. & Chung, K. H. Athabasca oil sands: effect of organic coated solids on bitumen recovery and quality. J. Pet. Sci. Eng. 39, 417–430 (2003).

    CAS  Google Scholar 

  37. Kelly, E. N. et al. Oil sands development contributes elements toxic at low concentrations to the Athabasca River and its tributaries. Proc. Natl Acad. Sci. USA 107, 16178–16183 (2010).

    CAS  Google Scholar 

  38. Sakimoto, K. K., Wong, A. B. & Yang, P. Self-photosensitization of nonphotosynthetic bacteria for solar-to-chemical production. Science 351, 74–77 (2016).

    CAS  Google Scholar 

  39. Sweeney, R. Y. et al. Bacterial biosynthesis of cadmium sulfide nanocrystals. Chem. Biol. 11, 1553–1559 (2004).

    CAS  Google Scholar 

  40. DeSilva Tara, M., Gianluigi, Veglia, Fernando, Porcelli, Prantner Andrew, M. & Opella Stanley, J. Selectivity in heavy metal‐ binding to peptides and proteins. Biopolymers 64, 189–197 (2002).

    CAS  Google Scholar 

  41. Kim, J. et al. Effects of various pretreatments for enhanced anaerobic digestion with waste activated sludge. J. Biosci. Bioeng. 95, 271–275 (2003).

    CAS  Google Scholar 

  42. Harrison, R. G., Todd, P., Todd, P. W., Rudge, S. R. & Petrides, D. P. Bioseparations Science and Engineering (Oxford Univ. Press, 2015).

  43. Hoek, P. V., Dijken, J. P. V. & Pronk, J. T. Effect of specific growth rate on fermentative capacity of baker’s yeast. Appl. Environ. Microbiol. 64, 4226–4233 (1998).

    Google Scholar 

  44. Yeasts, Yeast Extracts, Autolysates and Related Products: The Global Market (BCC Research, 2017).

  45. Rugh, C. L. et al. Mercuric ion reduction and resistance in transgenic Arabidopsis thaliana plants expressing a modified bacterial merA gene. Proc. Natl Acad. Sci. USA 93, 3182–3187 (1996).

    CAS  Google Scholar 

  46. Arai, T. et al. Cu-doped ZnS hollow particle with high activity for hydrogen generation from alkaline sulfide solution under visible light. Chem. Mater. 20, 1997–2000 (2008).

    CAS  Google Scholar 

  47. Parveen, A., Agrawal, S. & Azam, A. Band gap tuning and fluorescence properties of lead sulfide Pb0.9A0.1S (A: Fe, Co, and Ni) nanoparticles by transition metal doping. Opt. Mater. 76, 21–27 (2018).

    CAS  Google Scholar 

  48. Bhattacharya, S. & Chakravorty, D. Electrical and magnetic properties of cold compacted iron-doped zinc sulfide nanoparticles synthesized by wet chemical method. Chem. Phys. Lett. 444, 319–323 (2007).

    CAS  Google Scholar 

  49. Selim, H., Gupta, A. K. & Al Shoaibi, A. Effect of reaction parameters on the quality of captured sulfur in Claus process. Appl. Energy 104, 772–776 (2013).

    CAS  Google Scholar 

  50. Minerals Information: Sulfur (USGS, 2018).

  51. Little, B. J., Ray, R. I. & Pope, R. K. Relationship between corrosion and the biological sulfur cycle: a review. CORROSION 56, 433–443 (2000).

    CAS  Google Scholar 

  52. Seligman, A. M., Wasserkrug, H. L. & Hanker, J. S. A new staining method (OTO) for enhancing contrast of lipid-containing membranes and droplets in osmium tetroxide-fixed tissue with osmiophilic thiocarbohydrazide (TCH). J. Cell Biol. 30, 424–432 (1966).

    CAS  Google Scholar 

Download references

Acknowledgements

We thank the Koch Institute Facilities, Center for Material Science Facilities (CMSE), the Whitehead Keck Microscopy Facility, as well as Y. Zhang (CMSE) and N. Watson (Keck) for assisting in TEM sample prep and imaging. We acknowledge the Amon Lab for helpful discussions and advice in setting up basic yeast experiments, specifically C. Brennan and S. Morrill. We also thank N. Eze for insightful discussions and paper editing. This work was supported by the Amar G. Bose Research Grant (G.L.S. and A.M.B.) and the NSF Graduate Fellowship (G.L.S.). Partial support for this research was provided by a core center grant P30-ES002109 from the National Institute of Environmental Health Sciences, National Institutes of Health.

Author information

Authors and Affiliations

  1. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    George L. Sun & Angela M. Belcher

  2. Koch Institute of Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA

    George L. Sun & Angela M. Belcher

  3. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Erin. E. Reynolds

  4. Department of Material Science, Massachusetts Institute of Technology, Cambridge, MA, USA

    Angela M. Belcher

Authors
  1. George L. Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Erin. E. Reynolds
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Angela M. Belcher
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

G.L.S., E.E.R. and A.M.B. conceived the study and designed experiments; G.L.S. performed and E.E.R. helped with experiments; G.L.S. analysed the data and assembled figures; G.L.S., E.E.R. and A.M.B. wrote the manuscript.

Corresponding author

Correspondence to Angela M. Belcher.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Measuring yeast H2S production.

Illustrations left of the images represent H2S detection columns with tick marks indicating the level of sulfide measured in ppm. a, Sulfide detection using 200 pm columns for mutants ΔCYS4, ΔHOM2, ΔMET17, and ΔHM217. b, Sulfide detection using 60 ppm columns for ΔMET17 in cultures of YPD, CSM, and CSM with the addition (+) of methionine (M) or cysteine (C). c, Sulfide detection using 2000 ppm columns for ΔMET17 in CSM cultures lacking (-) methionine or cysteine, or both.

Extended Data Fig. 2 Strain, culture density (OD600), and media composition effects on metal precipitation.

a, Precipitation of copper, zinc, cadmium, lead, and mercury with mutants ΔCYS4, ΔHOM2, ΔMET17, and ΔHM217, and WT as a control, in CSM. b, Effects of removing methionine (M) and/or cysteine (C) from CMS on precipitation efficacy using ΔMET17. Columns represent removal of M while rows represent removal of C from CSM. 1X stands for 100% removal (that is 0.2X = 20% and 0.5X=50%). Annotated values per cell grid represent the percent cadmium removed and standard error. c, Optimal culture density (marked within grey bounds) was determined by titrating cultures of ΔMET17 at different OD600 with copper, zinc, cadmium, lead, and mercury. Metal color coding matches those used in the main text. For all data, the mean ±s.d. of three replicates were taken for each data point.

Source data

Extended Data Fig. 3 Elemental mapping of precipitated metal sulfide particles.

a, Elemental mapping of HRTEM images of cadmium sulfide nanoparticles deposited on the cell wall of ΔMET17. Cadmium was false colored as red, sulfide as blue. Scale bars represent 50 nm. b, Elemental dispersive X-ray (EDX) spectroscopy was performed on purified precipitated copper, cadmium, lead, mercury, and zinc sulfide particles under TEM. Elemental Kα peaks were colored and highlighted as areas under the curve for qualitative comparisons. Metal color coding of spectral plots match those used in the main text.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–11 and Tables 1 and 3.

Reporting Summary

Supplementary Table

Supplementary Table 2.

Source data

Source Data Fig. 1

Growth curve and sulfur production values for several strains at various time points

Source Data Fig. 2

Metal removal of Cu, Zn, Cd, Pb, and Hg with respects to media composition in YPD, CSM, CSM-M, and CSM-C

Source Data Fig. 3

Metal concentrations at different rounds of metal removal taken from the Athabasca oil sands

Source Data Fig. 4

Measured sizes of metal sulfide particles examined under TEM

Source Data Fig. 5

Excitation and emission spectra of several purified metal sulfide nanoparticles

Source Data Extended Data Fig. 2

Effects on strain and culture density on metal precipitation efficiency

Source Data Extended Data Fig. 3

Raw EDX signal of purified metal sulfide nanoparticles examined under TEM

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, G.L., Reynolds, E.E. & Belcher, A.M. Using yeast to sustainably remediate and extract heavy metals from waste waters. Nat Sustain 3, 303–311 (2020). https://doi.org/10.1038/s41893-020-0478-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41893-020-0478-9

  • Springer Nature Limited

This article is cited by

Search

Navigation