Thermochemical hydrolysis of macroalgae Ulva for biorefinery: Taguchi robust design method

Jiang, Rui; Linzon, Yoav; Vitkin, Edward; Yakhini, Zohar; Chudnovsky, Alexandra; Golberg, Alexander

doi:10.1038/srep27761

Cited by 25 publications

(14 citation statements)

References 45 publications

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“…For monosaccharide quantification the biomass was hydrolyzed as optimized by Jiang et al (2% sulfuric acid, 1:20 solid to solvent ratio, 30 min, 121°C) in 10 mL Nalgene™ Oak Ridge High‐Speed PPCO centrifuge tubes (Thermo Fisher Scientific, Waltham, MA) in an autoclave (Tuttnauer 2540MLV, Breda, Netherlands). The monosaccharide content in the hydrolysates was quantified by high‐pressure anion‐exchange chromatography coupled with pulsed amperometric detection (HPAEC‐PAD) using a Dionex ICS‐5000 platform (Dionex, Thermo Fischer Scientific) with an analytical column (Aminopack 10) and its corresponding guard column.…”

Section: Offshore Cultivation In Cages With Tumbling Air Mixing and mentioning

confidence: 87%

Feasibility study of Ulva sp. (Chlorophyta) intensive cultivation in a coastal area of the Eastern Mediterranean Sea

Chemodanov

Robin

Jinjikhashvily

et al. 2019

Biofuels Bioprod Bioref

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Increasing biomass production yields is a critical challenge for macroalgae biorefineries. The continuous tumbling and mixing of free‐floating algae through water or airflow has been shown to increase the productivity of algae in land‐based cultivation systems. This approach has not been tested thoroughly in offshore cultivation. We report, here, a field feasibility study on the increase in green macroalga Ulva sp. growth rates in offshore cages, achieved by the combined effect of tumbling and mixing of the algae using influxes of water and air. The experimental system was tested in a shallow coastal area in central Israel, in the eastern Mediterranean Sea. A maximum daily growth rate of 19.2%, areal productivity of 33.72 g dry weight (DW) day−1 m−2, and volumetric yields of 37.78 g DW day−1 m−3, together with 38.47 ± 0.01% ash and 5.28% protein content on a dry matter basis were achieved in the cages with intensified cultivation in the first week of May 2017. Our study shows that cultivation with tumbling and mixing of biomass with air, and water exchange with the environment is a feasible method to increase Ulva sp. biomass productivity offshore. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd

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Section: Offshore Cultivation In Cages With Tumbling Air Mixing and mentioning

confidence: 87%

Feasibility study of Ulva sp. (Chlorophyta) intensive cultivation in a coastal area of the Eastern Mediterranean Sea

Chemodanov

Robin

Jinjikhashvily

et al. 2019

Biofuels Bioprod Bioref

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“…FBA analyzes internal reaction fluxes under the assumption that the modelled organism metabolic network is regulated to maximize some cellular objective under a predefined set of constraints. FBA-based approaches have a wide range of applications including phenotype analysis, bioengineering and metabolic model reconstruction [ 13 , 20 , 47 – 52 ].…”

Section: Methodsmentioning

confidence: 99%

Genome-wide analysis of fitness data and its application to improve metabolic models

et al. 2018

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BackgroundSynthetic biology and related techniques enable genome scale high-throughput investigation of the effect on organism fitness of different gene knock-downs/outs and of other modifications of genomic sequence.ResultsWe develop statistical and computational pipelines and frameworks for analyzing high throughput fitness data over a genome scale set of sequence variants. Analyzing data from a high-throughput knock-down/knock-out bacterial study, we investigate differences and determinants of the effect on fitness in different conditions. Comparing fitness vectors of genes, across tens of conditions, we observe that fitness consequences strongly depend on genomic location and more weakly depend on gene sequence similarity and on functional relationships. In analyzing promoter sequences, we identified motifs associated with conditions studied in bacterial media such as Casaminos, D-glucose, Sucrose, and other sugars and amino-acid sources.We also use fitness data to infer genes associated with orphan metabolic reactions in the iJO1366 E. coli metabolic model. To do this, we developed a new computational method that integrates gene fitness and gene expression profiles within a given reaction network neighborhood to associate this reaction with a set of genes that potentially encode the catalyzing proteins. We then apply this approach to predict candidate genes for 107 orphan reactions in iJO1366. Furthermore - we validate our methodology with known reactions using a leave-one-out approach. Specifically, using top-20 candidates selected based on combined fitness and expression datasets, we correctly reconstruct 39.7% of the reactions, as compared to 33% based on fitness and to 26% based on expression separately, and to 4.02% as a random baseline. Our model improvement results include a novel association of a gene to an orphan cytosine nucleosidation reaction.ConclusionOur pipeline for metabolic modeling shows a clear benefit of using fitness data for predicting genes of orphan reactions. Along with the analysis pipelines we developed, it can be used to analyze similar high-throughput data.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2341-9) contains supplementary material, which is available to authorized users.

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“…CBM approach enables the prediction of organism growth rates based only on reaction stoichiometry and directionality. FBA-based approaches have a wide range of applications including phenotype analysis, bioengineering and metabolic model reconstructions [20][21][22].…”

Section: Serial Biomass Fermentation By Two Organismsmentioning

confidence: 99%

Distributed flux balance analysis simulations of serial biomass fermentation by two organisms

et al. 2020

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Intelligent biorefinery design that addresses both the composition of the biomass feedstock as well as fermentation microorganisms could benefit from dedicated tools for computational simulation and computer-assisted optimization. Here we present the BioLego Vn2.0 framework, based on Microsoft Azure Cloud, which supports large-scale simulations of biomass serial fermentation processes by two different organisms. BioLego enables the simultaneous analysis of multiple fermentation scenarios and the comparison of fermentation potential of multiple feedstock compositions. Thanks to the effective use of cloud computing it further allows resource intensive analysis and exploration of media and organism modifications. We use BioLego to obtain biological and validation results, including (1) exploratory search for the optimal utilization of corn biomasses-corn cobs, corn fiber and corn stoverin fermentation biorefineries; (2) analysis of the possible effects of changes in the composition of K. alvarezi biomass on the ethanol production yield in an anaerobic two-step process (S. cerevisiae followed by E. coli); (3) analysis of the impact, on the estimated ethanol production yield, of knocking out single organism reactions either in one or in both organisms in an anaerobic two-step fermentation process of Ulva sp. into ethanol (S. cerevisiae followed by E. coli); and (4) comparison of several experimentally measured ethanol fermentation rates with the predictions of BioLego.

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Thermochemical hydrolysis of macroalgae Ulva for biorefinery: Taguchi robust design method

Cited by 25 publications

References 45 publications

Feasibility study of Ulva sp. (Chlorophyta) intensive cultivation in a coastal area of the Eastern Mediterranean Sea

Feasibility study of Ulva sp. (Chlorophyta) intensive cultivation in a coastal area of the Eastern Mediterranean Sea

Genome-wide analysis of fitness data and its application to improve metabolic models

Distributed flux balance analysis simulations of serial biomass fermentation by two organisms

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