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

The green seaweed Ulva: tomorrow's "wheat of the sea" in foods, feeds, nutrition, and biomaterials

Ulva, a genus of green macroalgae commonly known as sea lettuce, has long been recognized for its nutritional benefits for food and feed. As the demand for sustainable food and feed sources continues to grow, so does the interest in alternative, plant-based protein sources. With its abundance along coastal waters and high protein content, Ulva spp. have emerged as promising candidates. While the use of Ulva in food and feed has its challenges, the utilization of Ulva in other industries, including in biomaterials, biostimulants, and biorefineries, has been growing. This review aims to provide a comprehensive overview of the current status, challenges and opportunities associated with using Ulva in food, feed, and beyond. Drawing on the expertise of leading researchers and industry professionals, it explores the latest knowledge on Ulva's nutritional value, processing methods, and potential benefits for human nutrition, aquaculture feeds, terrestrial feeds, biomaterials, biostimulants and biorefineries. In addition, it examines the economic feasibility of incorporating Ulva into aquafeed. Through its comprehensive and insightful analysis, including a critical review of the challenges and future research needs, this review will be a valuable resource for anyone interested in sustainable aquaculture and Ulva's role in food, feed, biomaterials, biostimulants and beyond.

Utilization of Macroalgae for the Production of Bioactive Compounds and Bioprocesses Using Microbial Biotechnology

To achieve sustainable development, alternative resources should replace conventional resources such as fossil fuels. In marine ecosystems, many macroalgae grow faster than terrestrial plants. Macroalgae are roughly classified as green, red, or brown algae based on their photosynthetic pigments. Brown algae are considered to be a source of physiologically active substances such as polyphenols. Furthermore, some macroalgae can capture approximately 10 times more carbon dioxide from the atmosphere than terrestrial plants. Therefore, they have immense potential for use in the environment. Recently, macroalgae have emerged as a biomass feedstock for bioethanol production owing to their low lignin content and applicability to biorefinery processes. Herein, we provided an overview of the bioconversion of macroalgae into bioactive substances and biofuels using microbial biotechnology, including engineered yeast designed using molecular display technology.

Smart ECG Biosensor Design with an Improved ANN Performance Based on the Taguchi Optimizer

This paper aims to design a smart biosensor to predict electrocardiogram (ECG) signals in a specific auscultation site from other ECG signals measured from other measurement sites. The proposed design is based on a hybrid architecture using the Artificial Neural Networks (ANNs) model and Taguchi optimizer to avoid the ANN issues related to hyperparameters and to improve its accuracy. The proposed approach aims to optimize the number and type of inputs to be considered for the ANN model. Indeed, different combinations are considered in order to find the optimal input combination for the best prediction quality. By identifying the factors that influence a model’s prediction and their degree of importance via the modified Taguchi optimizer, the developed biosensor improves the prediction accuracy of ECG signals collected from different auscultation sites compared to the ANN-based biosensor. Based on an actual database, the simulation results show that this improvement is significant; it can reach more than 94% accuracy.

Acidolysis as a biorefinery approach to producing advanced bioenergy from macroalgal biomass: A state-of-the-art review

Facing fossil fuels consumption and its accompanying environmental pollution, macroalgae, as a major part of the third-generation (3G) biomass, has great potential for bioenergy development due to its species-abundant, renewable and carbohydrate-rich properties. Diluted acid treatment is one of the most effective approaches to releasing fermentable sugars from macroalgal biomass in a short period, but the optimal conditions need to be explored to maximize the hydrolytic yield for the subsequent microbial conversion. Therefore, this review aims to summarize the latest advances in various acids and other auxiliary methods adopted to increase the hydrolytic efficiency of macroalgae. Following an overview of the strategies of different algal types, methods involved in the bioconversion of biofuels and microbial fuel cells (MFC) from algal hydrolysates are also described. For the 3G biorefinery development, the review further discusses key challenges and trends for future utilizing marine biomass to achieve the large-scale industrial production.

Fourfold daily growth rate in multicellular marine alga Ulva meridionalis

Microalgae with high growth rates have been considered as promising organisms to replace fossil resources with contemporary primary production as a renewable source. However, their microscopic size makes it hard to be harvested for industrial applications. In this regard, multicellular macroalgae are more suitable for harvesting. Here, we show that Ulva meridionalis has the highest growth rate ever reported for a multicellular autotrophic plant. Contrasted to the known bloom-forming species U. prolifera growing at an approximately two-fold growth rate per day in optimum conditions, U. meridionalis grows at a daily rate of over fourfold. The high growth ability of this multicellular alga would provide the most effective method for CO2 fixation and biomass production.

A holistic zero waste biorefinery approach for macroalgal biomass utilization: A review

The growing concerns over the depleting fossil fuels and increase in the release of greenhouse gas emissions have necessitated the search for the potential biomass source for alternative energy generation. In this context, third generation biomass specifically maroalgae has gained a lot of research interest in the recent years for energy and products generation such as ethanol, butanol, alginates, agars, and carrageenans. There are a few reviews available in scientific domain on macroalgal biomass utilization for bioethanol production but none of them has addressed precisely from phenolic precursor compounds to the entire ethanol production process and its bottlenecks. Here, we explained critically the processes involved in bioethanol, value added products and chemicals production utilizing macroalgal biomass as a feedstock along with its zero waste feasibility approach. Apart from this, we have also summarized the major issues linked to the macroalgae based biofuels and bioproducts generation processes and their possible corrective measures. Biorefinery is a promising way to generate multiple products from a single source with short processing time. Thus, this review also focuses on the recent advancement in the macroalgal biomass scaling up and how this could help in the growth of macroalgal biorefinery industry in the near future.

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

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 stover-in 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.

Enhancing the Extraction of Polysaccharides and Antioxidants from Macroalgae Using Sequential Hydrothermal-Assisted Extraction Followed by Ultrasound and Thermal Technologies

Fucose sulphated polysaccharides (FSPs) and glucans have recently attracted the attention of the scientific community due to their wide range of biological activities. Both polysaccharides should ideally be selectively extracted using innovative technologies with high extraction efficiency. This study aims to: (1) Optimise the extraction variables used in hydrothermal-assisted extraction (HAE) to obtain high yields of FSPs, total glucans, and antioxidants from Laminaria hyperborea; (2) to apply these optimised protocols to other brown macroalgae; and (3) to explore the application of ultrasound and thermal technologies to increase the recovery of polysaccharides from the residual biomass. Box-Behnken design (three-factor, four-levels) was employed to optimise the HAE variables, and principal component analysis was used to evaluate the recovery of polysaccharides from the residual biomass. The optimal HAE conditions were 120 °C, 80.9 min, and 12.02 mL/g macroalgae from L. hyperborea. The best sequential application of ultrasound and thermal treatment achieved an additional 2971.7 ± 61.9 mg fucose/100 g dried macroalgal residue (dmr) from Ascophyllum nodosum and 908.0 ± 51.4 mg total glucans/100 g dmr from L. hyperborea macroalgal residues.

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

Background

Synthetic 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.

Results

We 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.

Conclusion

Our 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 material

The online version of this article (10.1186/s12859-018-2341-9) contains supplementary material, which is available to authorized users.

Fused Microknot Optical Resonators in Folded Photonic Tapers for in-Liquid Durable Sensing

Optical microknot fibers (OMFs) serve as localized devices, where photonic resonances (PRs) enable self-interfering elements sensitive to their environment. However, typical fragility and drifting of the knot severely limit the performance and durability of microknots as sensors in aqueous settings. Herein we present the fabrication, electrical fusing, preparation, and persistent detection of volatile liquids in multiple wetting⁻dewetting cycles of volatile compounds and quantify the persistent phase shifts with a simple model relating to the ambient liquid, enabling durable in-liquid sensing employing OMF PRs.