Exploring Algal Metabolism: Insights from Metabolomics and Computational Approaches ^†

Abstract

Algae, despite being labeled as an underexplored biological source of chemical constituents, remain inadequately studied in terms of their metabolism. Metabolomics has emerged as a high-throughput technology to investigate the full metabolic profile of samples that could aid in the understanding and characterization of algae. By delving into their primary composition, particularly polysaccharides and phycobiliproteins, alongside secondary metabolites like polyphenols and pigments, researchers can uncover not only their rheological and nutritional properties but also their diverse biological activities. Given the growing interest in algae in food and related industries, innovative approaches should be explored to enhance the value of their functional components. In this sense, in the context of contemporary in-silico studies, metabolomics should be paired with computational methodologies, to develop novel techniques for studying biomolecular interactions. Molecular docking has emerged, with the function of predicting the atomic-level interaction between small molecules (ligands) and target proteins (proteins). This synergistic approach integrating both technologies could allow us to characterize algal profiles, evaluate their potential for bioactive properties, and better understand their metabolism. This work explores the development of metabolomic and computational strategies targeted toward the functional characterization of algae. By harnessing these technologies, we can unlock new possibilities for using algae in various industrial applications, paving the way for sustainable and innovative solutions in the future.

1. Introduction

Algae, a varied group of photosynthetic organisms, has been described as an unexplored biological source of chemical ingredients. Despite their potential, our comprehension of their metabolic functions remains incomplete. This is where metabolomics, a high-throughput technology, can provide a new approach. Metabolomics can examine the entire metabolic profile of samples and thus contribute to the understanding and characterization of algae. The primary composition of algae, especially polysaccharides and phycobiliproteins, is of great interest [1]. Polysaccharides, which are complex carbohydrates, are known for their potential health benefits [2]. Phycobiliproteins, on the other hand, are light-harvesting pigments found in cyanobacteria and certain algae [3]. In addition to their primary composition, algae produce secondary metabolites like polyphenols and pigments. Polyphenols are a group of chemicals found in many plant foods and are associated with numerous health benefits, whereas pigments have been used on the industrial level as coloring agents in food products and beverages [4].

Metabolomics, a powerful technology, enables the comprehensive profiling of metabolites within biological samples. Researchers can now delve into algal metabolic pathways, including those associated with polysaccharides, phycobiliproteins, and secondary metabolites. By understanding these components, we can gain insights into the rheological properties, nutritional value, and biological activities of algae [5]. Metabolomics provides a holistic view of the complex biochemical processes occurring within algae cells, explaining their adaptations and responses to environmental changes [6].

To improve our understanding of algae, we propose the combination of metabolomics with computational techniques by computational functional metabolomics [5]. One such approach is molecular docking, a widely used method that predicts how small molecules interact with target proteins. In the context of algae, molecular docking can elucidate interactions at the atomic level, revealing potentially bioactive properties and metabolic pathways. By simulating the binding of ligands to specific proteins, researchers can identify promising compounds for further investigation [7]. This synergistic approach combines experimental data with computational predictions and allows us to explore the functional components of algae more comprehensively.

2. Methodology

To conduct a literature review on metabolomic and computational strategies for the functional characterization of algae, we searched for relevant papers using the PubMed, Scopus, ScienceDirect, Google Scholar, and Web of Science databases. Our search used keywords like “metabolomics”, “computational strategies”, “biomolecular interactions”, and “algae or seaweed”. We included recent studies published in English, focusing on peer-reviewed articles, reviews, and meta-analyses providing new data on metabolomics and computational studies using algae. Titles and abstracts were screened for relevance, followed by a full-text review and data extraction. Findings were synthesized qualitatively and quantitatively.

3. Untargeted Metabolomic Analysis

Untargeted metabolomic analysis is crucial in comprehensive biomarker discovery and understanding complex biological systems, as it enables the identification and quantification of a vast array of metabolites without prior knowledge, providing insights into the metabolic pathways and mechanisms underlying various physiological and pathological states.

Table 1. Recent studies on metabolomic analysis in algae.

Algae	Remarks	Ref.
Laminaria japonica, Undaria pinnatifida Sargassum fusiforme Ascophyllum nodosum	The antioxidant activity was related to the presence of phlorotannins. A. nodosum presented the highest antioxidant activity.	[8]
Lobophora rosacea	Two allelopathic chemicals, lobophorenols B and C, and several oxygenated polyunsaturated fatty acids were identified among the 65 chemomarkers of pH that were targeted.	[9]
Sargassum thunbergii	This study explored male/female differentiation in photosynthetic physiological characteristics and metabolite regulation after UV-B radiation exposure.	[10]
Kappaphycus alvarezii	In total, 34 compounds were tentatively interpreted from the methanolic extract, including Resorcinol sulfoxide: Canavanine and Sulfabenzamide.	[11]
Dictyota dichotoma	This study revealed the presence of 16 diverse putative metabolites.	[12]
Scenedesmus sp.	Metabolites like EPA, DHA, α-Tocopherol, and phytosterols were produced in 5% CO2.	[13]
Euglena gracilis	Cd, Co, and Cu stress triggered adaptive responses in Euglena gracilis. Changes in energy metabolism and amino acid metabolism changes were observed.	[14]
Heterosigma akashiwo	Changes in endogenous metabolites in marine algae were observed. This study clarified the photo-transformation characteristics of common medications in estuary water and the ecological dangers of these substances to marine life.	[15]
Microglena antarctica	M. antarctica increased in PUFA percentages in response to low temperatures. Raising temperatures led to chlorophyll and carotenoid increases.	[16]
Ulva ohnoi	This study investigated metabolic processes in the reproductive phase of Ulva ohnoi in different environmental conditions.	[17]

presents a summary of recent publications on metabolomic analysis in algae.

The work conducted by Shen and colleagues [8] used Q-Exactive HF-X mass spectrometry to explore the variations in polyphenolic compounds and antioxidant activity in four macroalgae species and identified and characterized a total of 12 polyphenolic compounds, including phenolic acids, flavonoids, and phlorotannins. Among the species studied, A. nodosum exhibited the highest total phenolic concentration and antioxidant activity, whereas L. japonica showed the lowest. The study highlighted that polyphenolic compounds, especially phlorotannins, significantly influenced the antioxidant activity of brown macroalgae, suggesting that A. nodosum is a potential source of polyphenols with effective antioxidant properties for future commercial applications and further study of phlorotannins [8]. One study detected a crude drug, Triclofos, an active metabolite of chloral hydrate, which is considered an effective nontoxic sedative [12], within 16 other putative metabolites. The pharmaceutical importance of the compounds found in Kappaphycus alvarezii was considerable, with many annotated compounds such as kinetin, sulphabenzamide, 1-phosphatidyl-1D-myoinositol, and dodecanamide indicating potential for various industrial applications [11]. These findings underscore the untapped potential of seaweed metabolites and the importance of metabolic analysis to assess the occurrence of these compounds.

The potential of metabolome analyses to evaluate changes in response to various endogenous and exogenous stress factors is also evident in the reports of several researchers. In a study, male and female S. thunbergii plants were exposed to UV-B irradiation and showed different responses in terms of their photosynthetic properties and metabolite regulation. Male plants showed better performance in chlorophyll fluorescence parameters under both low and high UV-B irradiation. Metabonomic analyses identified amino acids, organic acids, and sugar nucleotides as important intermediates in key metabolic processes such as glycolysis, the tricarboxylic acid cycle, and the amino acid biosynthetic pathway [10]. In another study, the effects of ocean acidification on the metabolome of Lobophora rosacea using an untargeted metabolomic approach showed significant changes and a decrease in specialized metabolites in L. rosacea under low-pH conditions, but similar bioactivity [9]. Similarly, Euglena gracilis exposed to high levels of cadmium, cobalt, or copper showed metabolic alterations linked to reactive oxygen species [14]. Another study investigated the photodegradation of pharmaceuticals (ciprofloxacin and diclofenac) in simulated estuarine water and found that their transformation products retained persistence, bioaccumulation potential, and toxic effects. The non-targeted metabolomic approach showed that photolyzed diclofenac induced stronger oxidative stress in Heterosigma akashiwo marine algae than the parent compound, highlighting the ecological risks of photolysis-induced transformation products [15]. A 2023 study by Bodar et al. presented the metabolite profiling of Ulva ohnoi in three distinct phases: vegetative, determination, and differentiation [17]. The analysis revealed several common metabolites across the three phases, including lactic acid, oxalic acid, ethanolamine, glycerol, myoinositol, and sucrose. Notably, sucrose levels increased 3.4-fold during the differentiation phase, indicating its potential role in the reproductive processes of the algae.

4. In Silico Analyses and Biomolecular Interactions

Integrating untargeted metabolomics with molecular docking offers several advantages. Firstly, it allows the discovery of enzymatic targets associated with large-scale small-molecule sets, intricately linking them to phenotype changes [7]. Additionally, this approach reduces the cost of exploration and enhances the accuracy of target prediction [18]. A schematic representation of a proposed workflow and a molecular docking example is presented in Figure 1 [19]. Furthermore, combining ion mobility with mass spectrometry and liquid chromatography improves sensitivity, structural specificity, and confidence in metabolite structure assignments during feature annotation [20]. These strategies accelerate drug discovery by investigating potential compounds before in vitro bioassays or chemical modifications [21].

Some examples of these new approaches will now be discussed. For instance, a nanophytosome loaded with a dried hydroalcoholic extract of Spirulina platensis to promote the healing of lacerations was assessed using metabolomic profiling. Thirteen compounds were identified in the S. platensis extract. Molecular docking showed that 12,13-dihydroxy-9Z-octadecenoic acid had the highest docking score on the HMGB-1 protein, indicating a significant interaction and a potential therapeutic effect in wound healing through the modulation of different biochemical signaling pathways [22].

The brown alga Sargassum cinereum was subjected to LC-MS-based metabolomic profiling, and eleven compounds were identified. Subsequent phytochemical analyses led to the discovery of two new aryl cresols and eight known compounds. These metabolites showed moderate antiproliferative activity against the cancer cell lines HepG2, MCF-7, and Caco-2. Pharmacophore-based virtual screening identified 5-LOX and 15-LOX as likely targets, with in vitro enzyme assays showing that the new compounds preferentially inhibited 5-LOX; in silico analyses provided insights into the molecular interactions within the active centers of the enzymes and explained the different inhibitory effects. These results emphasize the therapeutic potential of Sargassum cinereum-derived compounds in cancer treatment through their interaction with specific enzyme pathways [23].

Research conducted on the macroalgae Sargassum cristaefolium, Tricleocarpa cylindrica, and Ulva lactuca to investigate their potential in the treatment of diabetes mellitus and COVID-19 through a combination of antioxidant in vitro, antihyperglycemic in vivo, and metabolomic-integrated in silico approaches identified promising compounds in the lipophilic extracts of these algae. The antioxidant activity of S. cristaefolium was the highest, while T. cylindrica exhibited strong antihyperglycemic activity. GC-MS-based metabolomic analysis followed by molecular docking showed that steroid-derived compounds in T. cylindrica exhibited a higher binding affinity to important targets such as α-amylase, α-glucosidase, ACE2, and TMPRSS2 compared to known ligands. These results suggest that compounds from these macroalgae have favorable drug properties that could be used to develop therapeutics for COVID-19 patients with comorbid diabetes mellitus treatment [24].

5. Conclusions

The integration of metabolomics into computational methodologies presents a promising avenue for unlocking the functional potential of algae. By elucidating their metabolic profiles and understanding biomolecular interactions, we can unlock new possibilities for using algal bioactive properties for various industrial applications, paving the way for sustainable and innovative solutions in the future.