Date of Award:

8-2020

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Biological Engineering

Committee Chair(s)

David Britt

Committee

David Britt

Committee

Elizabeth Vargis

Committee

Astrid Jacobson

Committee

Joan E. McLean

Abstract

Nanoparticles (NPs) are defined as particles less than 100 nm in at least one dimension. CuO NPs have possible applications in agriculture as micronutrient sources, pesticides, and enhancers of crop stress tolerance. Here, three aspects of CuO NP agricultural applications are studied: 1) the potential of CuO NPs to prevent wheat lodging-when crops irreversibly fall over; 2) CuO NP-induced drought tolerance in wheat seedlings; and 3) the effects of CuO NPs on outer membrane vesicle (OMV) production by Pseudomonas chlororaphis O6 (PcO6), a plant-health promoting bacterium.

Wheat grown 7 d exposed to CuO NPs in the growth matrix exhibited increased lignification, or formation of the plant structural polymer lignin, in wheat sclerenchyma cells which are considered the strengthening cells of the plant. This increased lignification also corresponded with stronger wheat shoots. These results, though conducted on wheat seedlings, show promise for use of CuO NPs in preventing lodging in mature wheat.

Wheat drought tolerance was measured with chlorophyll fluorescence, a method that quantifies the photochemical reactions in a plant. This method showed that these low CuO NPs dosages had no effect on drought tolerance of wheat grown 14 d then exposed to simulated drought for 8 d. However, CuO NPs did not exhibit phytotoxic effects at these controlled dosages showing that these NPs may be used for other agricultural purposes including pesticides and micronutrient sources.

The effects of CuO NPs, an agriculturally relevant NP, and H2O2, a metabolite involved in plant stress responses, on PcO6 and subsequent OMV production were studied with Raman spectroscopy. This spectroscopy method gives a "chemical fingerprint" and with subsequent analysis, Raman spectra can then be used to identify unknown samples. Raman spectroscopy with linear discriminant analysis was able to identify PcO6 cells and isolated OMVs according to the cellular stressor with an 83.3% accuracy and a 71.1% accuracy respectively. OMVs showed unique Raman spectra peaks compared to PcO6 cells, indicating that PcO6 cell components are selectively enriched or excluded from OMVs. These results show the power of Raman spectroscopy in characterizing OMVs according to cell stressor and thus understanding OMV roles in cell stress responses.

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