Title: Solvent-free spectroscopic method for high-throughput, quantitative screening of fatty acids in yeast biomass

Abstract

Sustainable biofuels and bioproducts technologies are being developed by fermentation of sugars present and released from pretreated cellulosic biomass to lipids using oleaginous yeasts. Detailed analytical characterization of lipid content through cultivation under different scenarios not only is a bottleneck that slows down development of improved strains and processes, this process also creates significant chemical waste. Since lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum, the use of multivariate linear regression of respective wavelengths can be used for the prediction of intracellular lipid content present in the yeast biomass. In this work, we present data on the multivariate quantitative correlation of NIR spectra with measured lipid content in different oleaginous yeast strains. This work is the first demonstration of the rapid, non-destructive, lipid quantification on as little as 10 mg of yeast biomass in a 96-well format, preventing significant chemical pollution by applying a real-time monitoring process. We demonstrate a distinct correlation of lipid content with the accumulation of select fatty acids of the lipids for 5 different yeast species, among which, for S. cerevisiae and L. starkeyi, in-depth calibration curves were developed from 65 and 154 unique samples, respectively. Laslty, we demonstrate that NIR spectramore » can be used to accurately predict intracellular lipid content using multivariate linear regression analysis in a manner of minutes, avoiding the need for lengthy chemical analyses that are resource intensive.« less

Authors:

Laurens, Lieve M. L.  ^[1];

• Search DOE PAGES for author "Laurens, Lieve M. L."
• Search DOE PAGES for ORCID "0000-0003-4930-3267"

Knoshaug, Eric P.  ^[1];

• Search DOE PAGES for author "Knoshaug, Eric P."
• Search DOE PAGES for ORCID "0000-0002-5709-914X"

Rohrer, Holly ^[1]; Van Wychen, Stefanie  ^[1];

• Search DOE PAGES for author "Van Wychen, Stefanie"
• Search DOE PAGES for ORCID "0000-0001-9321-0741"

Dowe, Nancy  ^[1];

• Search DOE PAGES for author "Dowe, Nancy"
• Search DOE PAGES for ORCID "0000-0002-8909-6082"

Zhang, Min ^[1]

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+ Show Author Affiliations

1. National Renewable Energy Lab. (NREL), Golden, CO (United States)

Publication Date:

Mon Nov 26 00:00:00 EST 2018

Research Org.:

National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Org.:

USDOE Office of Energy Efficiency and Renewable Energy (EERE), Sustainable Transportation Office. Bioenergy Technologies Office (BETO)

OSTI Identifier:

1487324

Alternate Identifier(s):

OSTI ID: 1484395

Report Number(s):

NREL/JA-5100-72973
Journal ID: ISSN 1759-9660; AMNECT

Grant/Contract Number:  

AC36-08GO28308

Resource Type:

Accepted Manuscript

Journal Name:

Analytical Methods

Additional Journal Information:

Journal Volume: 11; Journal Issue: 1; Journal ID: ISSN 1759-9660

Publisher:

Royal Society of Chemistry

Country of Publication:

United States

Language:

English

Subject:

09 BIOMASS FUELS; cellulosic biomass; NIR spectrum; yeast strains; lipid quantification