Perspective: Multiomics and Machine Learning Help Unleash the Alternative Food Potential of Microalgae

Microalgae growth-promoting bacteria for cultivation strategies: Recent updates and progress

Microalgae growth-promoting bacteria (MGPB), both actinobacteria and non-actinobacteria, have received considerable attention recently because of their potential to develop microalgae-bacteria co-culture strategies for improved efficiency and sustainability of the water-energy-environment nexus. Owing to their diverse metabolic pathways and ability to adapt to diverse conditions, microalgal-MGPB co-cultures could be promising biological systems under uncertain environmental and nutrient conditions. This review proposes the recent updates and progress on MGPB for microalgae cultivation through co-culture strategies. Firstly, potential MGPB strains for microalgae cultivation are introduced. Following, microalgal-MGPB interaction mechanisms and applications of their co-cultures for biomass production and wastewater treatment are reviewed. Moreover, state-of-the-art studies on synthetic biology and metabolic network analysis, along with the challenges and prospects of opting these approaches for microalgal-MGPB co-cultures are presented. It is anticipated that these strategies may significantly improve the sustainability of microalgal-MGPB co-cultures for wastewater treatment, biomass valorization, and bioproducts synthesis in a circular bioeconomy paradigm.

Machine learning: an advancement in biochemical engineering

One of the most remarkable techniques recently introduced into the field of bioprocess engineering is machine learning. Bioprocess engineering has drawn much attention due to its vast application in different domains like biopharmaceuticals, fossil fuel alternatives, environmental remediation, and food and beverage industry, etc. However, due to their unpredictable mechanisms, they are very often challenging to optimize. Furthermore, biological systems are extremely complicated; hence, machine learning algorithms could potentially be utilized to improve and build new biotechnological processes. Gaining insight into the fundamental mathematical understanding of commonly used machine learning algorithms, including Support Vector Machine, Principal Component Analysis, Partial Least Squares and Reinforcement Learning, the present study aims to discuss various case studies related to the application of machine learning in bioprocess engineering. Recent advancements as well as challenges posed in this area along with their potential solutions are also presented.

Can digital twin efforts shape microorganism-based alternative food?

With the continuous increment in global population growth, compounded by post-pandemic food security challenges due to labor shortages, effects of climate change, political conflicts, limited land for agriculture, and carbon emissions control, addressing food production in a sustainable manner for future generations is critical. Microorganisms are potential alternative food sources that can help close the gap in food production. For the development of more efficient and yield-enhancing products, it is necessary to have a better understanding on the underlying regulatory molecular pathways of microbial growth. Nevertheless, as microbes are regulated at multiomics scales, current research focusing on single omics (genomics, proteomics, or metabolomics) independently is inadequate for optimizing growth and product output. Here, we discuss digital twin (DT) approaches that integrate systems biology and artificial intelligence in analyzing multiomics datasets to yield a microbial replica model for in silico testing before production. DT models can thus provide a holistic understanding of microbial growth, metabolite biosynthesis mechanisms, as well as identifying crucial production bottlenecks. Our argument, therefore, is to support the development of novel DT models that can potentially revolutionize microorganism-based alternative food production efficiency.

Microbial Pigments: Major Groups and Industrial Applications

Microbial pigments have many structures and functions with excellent characteristics, such as being biodegradable, non-toxic, and ecologically friendly, constituting an important source of pigments. Industrial production presents a bottleneck in production cost that restricts large-scale commercialization. However, microbial pigments are progressively gaining popularity because of their health advantages. The development of metabolic engineering and cost reduction of the bioprocess using industry by-products opened possibilities for cost and quality improvements in all production phases. We are thus addressing several points related to microbial pigments, including the major classes and structures found, the advantages of use, the biotechnological applications in different industrial sectors, their characteristics, and their impacts on the environment and society.

Harnessing the potential of microalgae-bacteria interaction for eco-friendly wastewater treatment: A review on new strategies involving machine learning and artificial intelligence

In the pursuit of effective wastewater treatment and biomass generation, the symbiotic relationship between microalgae and bacteria emerges as a promising avenue. This analysis delves into recent advancements concerning the utilization of microalgae-bacteria consortia for wastewater treatment and biomass production. It examines multiple facets of this symbiosis, encompassing the judicious selection of suitable strains, optimal culture conditions, appropriate media, and operational parameters. Moreover, the exploration extends to contrasting closed and open bioreactor systems for fostering microalgae-bacteria consortia, elucidating the inherent merits and constraints of each methodology. Notably, the untapped potential of co-cultivation with diverse microorganisms, including yeast, fungi, and various microalgae species, to augment biomass output. In this context, artificial intelligence (AI) and machine learning (ML) stand out as transformative catalysts. By addressing intricate challenges in wastewater treatment and microalgae-bacteria symbiosis, AI and ML foster innovative technological solutions. These cutting-edge technologies play a pivotal role in optimizing wastewater treatment processes, enhancing biomass yield, and facilitating real-time monitoring. The synergistic integration of AI and ML instills a novel dimension, propelling the fields towards sustainable solutions. As AI and ML become integral tools in wastewater treatment and symbiotic microorganism cultivation, novel strategies emerge that harness their potential to overcome intricate challenges and revolutionize the domain.

The potentials and challenges of using fermentation to improve the sensory quality of plant-based meat analogs

Despite the advancements made in improving the quality of plant-based meat substitutes, more work needs to be done to match the texture, appearance, and flavor of real meat. This review aims to cover the sensory quality constraints of plant-based meat analogs and provides fermentation as a sustainable approach to push these boundaries. Plant-based meat analogs have been observed to have weak and soft textural quality, poor mouth feel, an unstable color, and unpleasant and beany flavors in some cases, necessitating the search for efficient novel technologies. A wide range of microorganisms, including bacteria such as Lactobacillus acidophilus and Lactiplantibacillus plantarum, as well as fungi like Fusarium venenatum and Neurospora intermedia, have improved the product texture to mimic fibrous meat structures. Additionally, the chewiness and hardness of the resulting meat analogs have been further improved through the use of Bacillus subtilis. However, excessive fermentation may result in a decrease in the final product's firmness and produce a slimy texture. Similarly, several microbial metabolites can mimic the color and flavor of meat, with some concerns. It appears that fermentation is a promising approach to modulating the sensory profiles of plant-derived meat ingredients without adverse consequences. In addition, the technology of starter cultures can be optimized and introduced as a new strategy to enhance the organoleptic properties of plant-based meat while still meeting the needs of an expanding and sustainable economy.

A critical review of machine-learning for "multi-omics" marine metabolite datasets

During the last decade, genomic, transcriptomic, proteomic, metabolomic, and other omics datasets have been generated for a wide range of marine organisms, and even more are still on the way. Marine organisms possess unique and diverse biosynthetic pathways contributing to the synthesis of novel secondary metabolites with significant bioactivities. As marine organisms have a greater tendency to adapt to stressed environmental conditions, the chance to identify novel bioactive metabolites with potential biotechnological application is very high. This review presents a comprehensive overview of the available "-omics" and "multi-omics" approaches employed for characterizing marine metabolites along with novel data integration tools. The need for the development of machine-learning algorithms for "multi-omics" approaches is briefly discussed. In addition, the challenges involved in the analysis of "multi-omics" data and recommendations for conducting "multi-omics" study were discussed.

Significance of Fermentation in Plant-Based Meat Analogs: A Critical Review of Nutrition, and Safety-Related Aspects

Plant-based meat analogs have been shown to cause less harm for both human health and the environment compared to real meat, especially processed meat. However, the intense pressure to enhance the sensory qualities of plant-based meat alternatives has caused their nutritional and safety aspects to be overlooked. This paper reviews our current understanding of the nutrition and safety behind plant-based meat alternatives, proposing fermentation as a potential way of overcoming limitations in these aspects. Plant protein blends, fortification, and preservatives have been the main methods for enhancing the nutritional content and stability of plant-based meat alternatives, but concerns that include safety, nutrient deficiencies, low digestibility, high allergenicity, and high costs have been raised in their use. Fermentation with microorganisms such as Bacillus subtilis, Lactiplantibacillus plantarum, Neurospora intermedia, and Rhizopus oryzae improves digestibility and reduces allergenicity and antinutritive factors more effectively. At the same time, microbial metabolites can boost the final product's safety, nutrition, and sensory quality, although some concerns regarding their toxicity remain. Designing a single starter culture or microbial consortium for plant-based meat alternatives can be a novel solution for advancing the health benefits of the final product while still fulfilling the demands of an expanding and sustainable economy.

The microbial food revolution

Our current food system relies on unsustainable practices, which often fail to provide healthy diets to a growing population. Therefore, there is an urgent demand for new sustainable nutrition sources and processes. Microorganisms have gained attention as a new food source solution, due to their low carbon footprint, low reliance on land, water and seasonal variations coupled with a favourable nutritional profile. Furthermore, with the emergence and use of new tools, specifically in synthetic biology, the uses of microorganisms have expanded showing great potential to fulfil many of our dietary needs. In this review, we look at the different applications of microorganisms in food, and examine the history, state-of-the-art and potential to disrupt current foods systems. We cover both the use of microbes to produce whole foods out of their biomass and as cell factories to make highly functional and nutritional ingredients. The technical, economical, and societal limitations are also discussed together with the current and future perspectives.

Use of industry 4.0 technologies to reduce and valorize seafood waste and by-products: A narrative review on current knowledge

Fish and other seafood products represent a valuable source of many nutrients and micronutrients for the human diet and contribute significantly to global food security. However, considerable amounts of seafood waste and by-products are generated along the seafood value and supply chain, from the sea to the consumer table, causing severe environmental damage and significant economic loss. Therefore, innovative solutions and alternative approaches are urgently needed to ensure a better management of seafood discards and mitigate their economic and environmental burdens. The use of emerging technologies, including the fourth industrial revolution (Industry 4.0) innovations (such as Artificial Intelligence, Big Data, smart sensors, and the Internet of Things, and other advanced technologies) to reduce and valorize seafood waste and by-products could be a promising strategy to enhance blue economy and food sustainability around the globe. This narrative review focuses on the issues and risks associated with the underutilization of waste and by-products resulting from fisheries and other seafood industries. Particularly, recent technological advances and digital tools being harnessed for the prevention and valorization of these natural invaluable resources are highlighted.