Dataset Information

High-Resolution Lipidomics Reveals Influence of Biomass and Pretreatment Process on the Composition of Extracted Algae Oils As Feedstock for Sustainable Aviation Fuels.

ABSTRACT: The increasing demand for sustainable aviation fuel (SAF) creates a need for innovative biomass and lipid sources with compositions that are compatible with refineries. Algae-derived oils present an opportunity to supply a process-compatible lipid feedstock at yields higher than those of conventional oilseed crops. With few documented reports on chemical composition, the process readiness remains elusive. We present data on extraction efficiency, yield, and purity of lipids from algae with and without the application of a low-concentration sulfuric acid pretreatment of the biomass. The pretreatment process increased the oil yield and positively impacted the quality of the extracted oils. Results from fatty acid and lipidomics analysis revealed that the low-lipid biomass sources extracted 70-80% of the available lipids, and the non-fatty acid co-extractants exceeded 40% of the extracted oils. For a high-lipid algae sample, derived from a genetically engineered strain, we show >90% extraction yield with >85% FAME purity. This work provides insights into the composition of algae-derived oils and quality metrics that are essential to determining the viability of lipid hydroprocessing to SAF.

SUBMITTER: Rowland SM

PROVIDER: S-EPMC11000214 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

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High-Resolution Lipidomics Reveals Influence of Biomass and Pretreatment Process on the Composition of Extracted Algae Oils As Feedstock for Sustainable Aviation Fuels.

Rowland Steven M SM Van Wychen Stefanie S Dong Tao T Leach Roger R Laurens Lieve M L LML

Energy & fuels : an American Chemical Society journal 20240327 7

The increasing demand for sustainable aviation fuel (SAF) creates a need for innovative biomass and lipid sources with compositions that are compatible with refineries. Algae-derived oils present an opportunity to supply a process-compatible lipid feedstock at yields higher than those of conventional oilseed crops. With few documented reports on chemical composition, the process readiness remains elusive. We present data on extraction efficiency, yield, and purity of lipids from algae with and w ...[more]

PMID: 38595993

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Project description:BackgroundEnzymes for plant cell wall deconstruction are a major cost in the production of ethanol from lignocellulosic biomass. The goal of this research was to develop optimized synthetic mixtures of enzymes for multiple pretreatment/substrate combinations using our high-throughput biomass digestion platform, GENPLAT, which combines robotic liquid handling, statistical experimental design and automated Glc and Xyl assays. Proportions of six core fungal enzymes (CBH1, CBH2, EG1, β-glucosidase, a GH10 endo-β1,4-xylanase, and β-xylosidase) were optimized at a fixed enzyme loading of 15 mg/g glucan for release of Glc and Xyl from all combinations of five biomass feedstocks (corn stover, switchgrass, Miscanthus, dried distillers' grains plus solubles [DDGS] and poplar) subjected to three alkaline pretreatments (AFEX, dilute base [0.25% NaOH] and alkaline peroxide [AP]). A 16-component mixture comprising the core set plus 10 accessory enzymes was optimized for three pretreatment/substrate combinations. Results were compared to the performance of two commercial enzymes (Accellerase 1000 and Spezyme CP) at the same protein loadings.ResultsWhen analyzed with GENPLAT, corn stover gave the highest yields of Glc with commercial enzymes and with the core set with all pretreatments, whereas corn stover, switchgrass and Miscanthus gave comparable Xyl yields. With commercial enzymes and with the core set, yields of Glc and Xyl were highest for grass stovers pretreated by AP compared to AFEX or dilute base. Corn stover, switchgrass and DDGS pretreated with AFEX and digested with the core set required a higher proportion of endo-β1,4-xylanase (EX3) and a lower proportion of endo-β1,4-glucanase (EG1) compared to the same materials pretreated with dilute base or AP. An optimized enzyme mixture containing 16 components (by addition of α-glucuronidase, a GH11 endoxylanase [EX2], Cel5A, Cel61A, Cip1, Cip2, β-mannanase, amyloglucosidase, α-arabinosidase, and Cel12A to the core set) was determined for AFEX-pretreated corn stover, DDGS, and AP-pretreated corn stover. The optimized mixture for AP-corn stover contained more exo-β1,4-glucanase (i.e., the sum of CBH1 + CBH2) and less endo-β1,4-glucanase (EG1 + Cel5A) than the optimal mixture for AFEX-corn stover. Amyloglucosidase and β-mannanase were the two most important enzymes for release of Glc from DDGS but were not required (i.e., 0% optimum) for corn stover subjected to AP or AFEX. As a function of enzyme loading over the range 0 to 30 mg/g glucan, Glc release from AP-corn stover reached a plateau of 60-70% Glc yield at a lower enzyme loading (5-10 mg/g glucan) than AFEX-corn stover. Accellerase 1000 was superior to Spezyme CP, the core set or the 16-component mixture for Glc yield at 12 h, but the 16-component set was as effective as the commercial enzyme mixtures at 48 h.ConclusionThe results in this paper demonstrate that GENPLAT can be used to rapidly produce enzyme cocktails for specific pretreatment/biomass combinations. Pretreatment conditions and feedstock source both influence the Glc and Xyl yields as well as optimal enzyme proportions. It is predicted that it will be possible to improve synthetic enzyme mixtures further by the addition of additional accessory enzymes.

Dataset Information

High-Resolution Lipidomics Reveals Influence of Biomass and Pretreatment Process on the Composition of Extracted Algae Oils As Feedstock for Sustainable Aviation Fuels.

Publications

High-Resolution Lipidomics Reveals Influence of Biomass and Pretreatment Process on the Composition of Extracted Algae Oils As Feedstock for Sustainable Aviation Fuels.

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