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Review

Microalgal Metabolomes and Recent Biotechnological Advances for Their Industrial Application

by
Dinesh Kumar Saini
1,
Geetanjali Manchanda
2,*,
Ratiram Gomaji Chaudhary
3 and
Raghvendra Pratap Singh
1,4,*
1
Azoth Biotech Pvt. Ltd., Noida 201306, India
2
Department of Biotechnology, Panjab University, Chandigarh 160014, India
3
Seth Kesarimal Porwal College, Kamptee, Nagpur 441001, India
4
Department of Biotechnology, R&I, Uttaranchal University, Dehradun 48007, India
*
Authors to whom correspondence should be addressed.
Microbiol. Res. 2024, 15(4), 2056-2069; https://doi.org/10.3390/microbiolres15040138
Submission received: 23 August 2024 / Revised: 1 October 2024 / Accepted: 3 October 2024 / Published: 5 October 2024
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Abstract

:
In recent decades, microalgae have emerged as new sustainable resources for the production of various bioactive and biochemical compounds. These organisms are photosynthetic, use CO2 as their sole carbon source, and grow rapidly under different environmental conditions. This makes microalgae a promising source of feedstock for many bio-commodities. However, the economic viability for large-scale production through microalgal cells is limited to certain organisms. Recent advances in omics technologies, along with high-throughput approaches, have provided new insights for understanding microalgal metabolites. With the improvement in metabolomic technology, sensitivity for the detection of cellular metabolites has increased, and it has directly enhanced our understanding of cellular metabolism and the corresponding metabolic pathways. Moreover, these metabolic techniques, along with other omics technologies, help us to characterize the changes in the cellular functioning of the different cells under environmental conditions. Metabolomic research on microalgae explores new metabolites and the understanding of their biosynthesis at the metabolic level. In this review, we discuss how these metabolomics techniques are applied to microalgae to study their metabolic networks. Additionally, we also discuss how integrating other tools of systems biology can improve the productivity of microalgal cells, especially for industrially important commodities.

1. Introduction

Microalgae are oxygenic, photosynthetic microorganisms that regulate key biological gases, such as carbon, oxygen, and nitrogen [1,2]. The first evidence of microalgae is cyanobacteria, which is one of the oldest prokaryotes found in Western Australia from fossilized rock [3]. These prokaryotes gradually evolved into eukaryotic microalgae with specific and defined organelles [4]. Microalgae include prokaryotic cyanobacteria and eukaryotic unicellular microscopic green algae, such as Chlorella, Dunaliella, Haematococcus, Scenedesmus, etc. [5]. These algae have a vital role in carbon fixation, as these organisms can fix approximately 40% of the carbon among all photosynthetic plants. These algal species perform about 50% of global photosynthesis and have a potential role in CO2 fixation [6]. Additionally, microalgae (some cyanobacteria, e.g., Anabaena variabilis) fix nitrogen in agricultural land and are used as biofertilizers [7,8]. These photoautotrophic organisms are well known as natural resources for pigments, vitamins, lipids, bio-fertilizers, biofuels, polysaccharides, bioactive compounds, proteins, bioplastics, mannitols, acetate, etc. [8,9,10]. Microalgae can produce around 30–70% of lipids with respect to their cell dry biomass in certain conditions [11,12]. Recently, microalgae have been used as a potential feedstock source for biofuel production. Due to their high lipid content compared to other plant-based sources, e.g., lipid-based crops (palm, soybean, etc.) and sugar-based crops (sugarcane and corn), microalgae have emerged as a vital feedstock source [13]. Further, microalgae have several advantages, such as a fast growth rate compared to plants, the advantage of being cultivated in non-agricultural land, their role in improved soil fertility, and representing a solution for CO2 emission and global warming [14,15]. Moreover, the photosynthetic efficiency of microalgae with their growth potential can produce more than a barrel of algal oil per hectare through mass culturing theoretically. This is about 100-fold higher than soybean, which is presently the primary source of biodiesel in the USA [16]. Furthermore, compared to plants, the biosynthesis process of microalgal cells is more straightforward, or less complicated; for example, in Arabidopsis, around 600 genes and 120 enzymes are involved in different organs for TAG biosynthesis [17]. Also, remarkable differences in other metabolic pathways, like the glycolytic pathway, are found between plants and microalgae [18]. Microalgae have numerous applications in different fields, such as biofuels, pharmaceuticals, cosmetics, nutraceuticals, food and fodder, and textiles. These are also known to produce various polyunsaturated fatty acids (PUFAs), which have attracted global attention due to their nutritional benefits. However, small size, low biomass, and productivity remain among the main challenges that hinder algal technology from achieving economic feasibility [19,20].
Metabolomics is a branch of omics technology that analyzes various small molecules or metabolites in a specific condition of the organisms and links phenotypes with their corresponding genotypes [21,22]. These small molecules generally include primary and secondary metabolites, proteins, enzymes, hormones, and other cellular constituents, predominately less than the size of 1500 kDa [23]. With the advancement of technology, metabolomics has been used in various studies, such as the comparison of mutants, genetic manipulation, the effect of drugs, cancer studies, assessing the impact of environmental changes, the study of cellular dynamics, etc. [24].
Metabolomics studies have three approaches: (i) metabolite profiling, (ii) targeted analysis, and (iii) metabolic fingerprinting. In metabolite profiling, all metabolite samples are assessed for qualitative and quantitative characteristics to elucidate whole metabolic pathways and networks. This approach provides information regarding the changes in regulating mechanisms due to mutants and alternations in culturing conditions that cannot be observed at the macroscopic level. However, disadvantages include the need for extensive data and data processing, and the unavailability of a database of all metabolites. In the targeted analysis approach, a limited number of metabolites are targeted from purified samples to avoid hindrances caused by the mixture of compounds. This solves the problem of extensive data and processing, but it requires prior knowledge of the desired compounds. Finally, metabolic fingerprinting does not quantify or identify metabolites; rather, it provides profiles or classifies samples based on their biological relevance. The main application of this approach is in the identification of biomarkers and subsequent diagnosis. However, it does not have any application in pathway analysis, as it identifies any metabolite [25]. Every technique has its own advantages and limitations; however, combining different approaches with advanced biotechnological tools provides broader perspectives of metabolomic studies, as shown in Figure 1.
During the past few decades, microalgae have emerged as a promising source for bioactive compounds and are considered cell factories. However, metabolic pathways and the regulation of these important compounds are still in their early stages. Moreover, the production of these compounds is relatively low and economically expensive. Integrating metabolomics tools with other omics technology can overcome these bottlenecks in algal technology [26].
In this review, we discuss the various important compounds extracted from microalgae and their commercial utilization. These compounds include carbohydrates, lipids, fatty acid proteins, and biopigments. This article provides a brief outlook on the application of metabolomics in microalgal studies and the differential regulation of various pathways. Further, we also discuss the integration of systems biology with metabolomics tools for redesigning the metabolic pathways to improve microalgae cells. Finally, future perspectives of metabolic studies on microalgae are also discussed.

2. Industrially Important Microalgal Compounds

2.1. Biofuels

Continuous industrialization and urbanization, combined with a rapidly increasing demand for energy in recent times, has resulted in faster depletion of fossils fuels. Along with the energy crisis, the world is also facing problems such as global warming and an increase in greenhouse gases and pollution caused primarily by the burning of fossil fuels. The survey conducted by the International Energy Agency (IEA) in 2012 showed that global warming can be limited to 2 °C by using clean energy technology on a global scale [27,28]. The renewable energy sources such as solar energy, hydropower plants, wind energy, and nuclear energy are promising alternatives, but all have some drawbacks and only produce electricity and not fuels, and therefore cannot substitute fossil fuels directly. Alternative fossil fuels which are receiving attention are biomass-based biofuels [29].
Biofuels are divided into three generations based on the type of feedstock used for their production. In the first generation, different types of food or oil-based food crops, such as sugarcane, soybean, vegetable oil, and animal oil, are used to produce biofuels. However, there are several disadvantages to using such food-based crops, including food insecurity and the requirement of more arable land. These disadvantages initiated researchers to find new sources of feedstocks. The second generation focuses mainly on non-edible crops or plant residues as a feedstock for biofuel production, such as Jatropha, Eucalyptus, Miscanthus, and the molasses of sugarcane. But production of these biofuels is very costly and requires many modern innovations. The pretreatment of the residues can be achieved in different ways, such as chemically, physically, and biologically. Among various steps, the pretreatment of residues is an expensive and time-consuming process [30,31,32].
Microalgae have come out as promising alternatives, as they are rich in lipid content and carbohydrates. The biosynthetic pathways of lipids are shown in Figure 2.
The lipid content is easily converted into biodiesel, whereas sugars are fermented for bioethanol production. The use of algae has several advantages: they stop conflict over food vs. fuel, require less land for their cultivation, and exhibit fast growth; some species can grow in saline water; wastewater can be used as a nutrient source; etc. [33,34]. In addition, they can produce many beneficial bioactive compounds, such as pigments, proteins, and Poly Hydroxy Butyrate (PHB), and they can be consumed as food and fodder due to their high nutritional value [35,36].
Biodiesel is one of the chief liquid fuels which can be extracted from microalgae. Microalgae produce a diverse range of lipids, such as phospholipids, fatty acids, and triglycerides. These lipids, through a transesterification reaction, are converted into biodiesel along with glycerol as a by-product. The algal biodiesel is a non-toxic, renewable fuel with 78% less CO2 emissions than other fossil fuels, which makes it a profitable and eco-friendly sustainable source of liquid fuel [37]. However, the production of biodiesel highly depends on the productivity of the lipid content from microalgae. There is lots of work ongoing to increase the production of lipids from microalgae.

2.2. Carbohydrates

Microalgae are a rich source of carbohydrates present in different forms which act as storage molecules [38]. The different forms of carbohydrates include glycogen and starch, which are present in cyanobacteria and green microalgae, respectively. Another type of carbohydrate, chrysolaminarin, is primarily found in brown algae; however, it is also reported in some microalgae such as Nannochloropsis and Phaeodactylum. The microalgal carbohydrates comprise less lignin and hemicellulose content, effectively being utilized for bioethanol and biogas production [39,40].
The conversion of algal carbohydrates into simpler sugars is achieved via hydrolysis, using chemical and enzymatic methods. Although the chemical reaction provides a high yield of fermentable sugar, lots of by-products are produced and it requires harsh reaction conditions. The unwanted by-products not only inhibit the fermentation process but also their disposal is quite costly. On the contrary, an enzymatic hydrolysis reaction has a high yield of fermentable sugar under mild reaction conditions without any inhibitory by-products. Moreover, enzymatic hydrolysis is eco-friendly and non-toxic compared to chemical hydrolysis [41]. In a recent report, Constantino et al. successfully demonstrated an alternative chemo-enzymatic hydrolysis strategy. They reported that algal biomass subjected to acid pretreatment followed by incubation with Amyloglucosidase and α-Amylase, which is the opposite order of utilization of these enzymes, improves the yield of reduced sugar from algal carbohydrates [42]. Afterward, these simple sugars are converted into ethanol with the help of microbial strains such as Saccharomyces cerevisiae and Zymomonas mobilis. The microbes primarily use the Embden–Meyerhof–Parnas (EMP) and Entner–Doudoroff (ED) pathways to convert glucose into pyruvate, followed by alcoholic fermentation.
There are several advantages of using microalgae as a feedstock for biofuel production, as we discussed earlier. Moreover, microalgae can simultaneously accumulate polysaccharides and triacylglycerols, making them suitable for biodiesel and bioethanol production. In contrast, cyanobacteria cannot accumulate a similar amount of lipids and is therefore only suitable for bioethanol production [43]. Also, Synechococcus and other cyanobacteria can accumulate a high amount of glycogen which can easily be fermented into ethanol. These have a simple genetic structure and are easily genetically and metabolically engineered to improve their efficacy. The Synechococcus elongatus sp. strain PCC 7942 was modified by the addition of a pyruvate decarboxylase and an alcohol dehydrogenase gene, due to which it can convert pyruvate to ethanol [44].

2.3. Biopigments

Microalgae produce different types of biopigments such as chlorophyll, carotenoids, and phycobiliprotein. Among these pigments, carotenoids and PBPs are well known for their use in industrial and biomedical applications [45]. Carotenoids are lipophilic isoprenoid compounds, containing a C40 long backbone chain that provides structural variation to these pigments via double bonds, cyclization, and oxygenation in the backbone. Approximately 600 different types of carotenoids have been identified, of which the most important pigments are β-carotene, astaxanthin, and lutein. The microalgae such as Dunaliella salina, Chlorella sp., and Haematococcus pluvialis are well known for their production of carotenoids [46].

Astaxanthin

Astaxanthin is a naturally occurring ketocartenoid, gaining popularity globally with its pharmaceutical and nutraceutical applications. This pigment is present in many aquatic animals like salmon, shrimp, etc. However, this pigment is also primarily found in microalgae, such as Chlorella zofingiensis, Chlorella sorokiniana, and Scenedesmus sp., but naturally, its commercial production is limited to Haematococcus pluvialis. As per astaxanthin market demand (2024), the worldwide astaxanthin market is anticipated to attain a market valuation of USD 665.0 million by the year 2034, exhibiting a notable compounded annual growth rate (CAGR) of approximately 9.3% from 2024 to 2034.
Phycobiliproteins are another accessory pigment present in cyanobacteria and some red algae. Based on their absorption maxima, these PBPs are divided into three types, including phycocyanin, phycoerythrin, and allophycocyanin. Within PBPs, phycocyanin and phycoerythrin have high commercial value due to their antioxidant, anti-cancer, and anti-inflammatory properties. These are water-soluble pigments with prominent colors. However, their stability and production are highly regulated by light intensity and quality, pH, and nutrients in a medium [10,47].

3. Applications of Metabolomics in Microalgal Studies

Metabolomic technology allows for the identification of biomarkers to understand molecular mechanisms and subsequent metabolic pathway analysis of the microorganisms [23]. With the advancement of instrumentation, metabolomic studies enable us to identify all of the changes that occur in microalgal cells and metabolic processes induced by stressors. In a report by Willette et al. [48], a combination of gas chromatography and mass spectrometry (GC-MS) was used, which revealed alterations in the level 26 metabolite in Nannochloropsis salina under cold stress. The results show up-regulation in lipid and fatty acid synthesis, which is significantly contributed by altering the TCA cycle [48]. Understanding metabolite synthesis can provide conclusive information regarding the regulation of various cellular processes and metabolic pathways in the cell. Hence, extensive studies of metabolomics can provide useful background knowledge for the remodeling of different pathways to enhance the yield of the desired production of metabolites. In addition, metabolites are indicators or biomarkers of the physiological states of organisms and can be used to diagnose diseases and help predict upcoming responses.
To gain a complete image of a metabolite of microalgae, optimized harvesting, cell disruption, and an extraction protocol is required, along with suitable solvents. Previously, different solvents have been utilized for the extraction of metabolites, e.g., a mixture of water, chloroform, and methanol was used for the extraction of the metabolite from Scendesmus obliques, Chlamydomonas, and Nannochloropsis salina [48,49,50]. Similarly, a mixture of methanol and water was used by Lv et al. (2016) and Vello et al. (2018) for Haematococcus pluvialis and Chlorella sp., respectively [51,52]. In some studies, new extraction techniques, such as pressurized liquid extraction (PLE) and supercritical fluid extraction (SFE), were used for the extraction of different metabolites such carotenoids and lipids from various microalgae [53,54,55].
In metabolomics studies, MS has usually been coupled with other techniques, such as chromatography, to obtain a global profile of organism metabolomes [56]. Generally, the obtained MS data of metabolomes are compared with the metabolite libraries to identify all metabolites in the specific sample and to determine the metabolic pathways involved in producing these metabolites. This type of metabolite detection leads to the discovery of novel pathways and metabolites.
Table 1. Some studies showing the successful integration of metabolomics to study cellular metabolism in microalgae.
Table 1. Some studies showing the successful integration of metabolomics to study cellular metabolism in microalgae.
S.No.OrganismToolsType of StudyInsightsRef.
1.Chlorella sorokinianaGC-MSComparative metabolome profile analysisA comparative study between a single culture of Chlorella sorokiniana and its consortium with bacteria for wastewater treatment. The results conclude with the differential metabolite synthesis of several classes, such as fatty acids, carbohydrates, amino acids, etc.[57]
2.Chlorella vulgaris and Scenedesmus obliquusGC–MS and LC-QTOF/MSUntargeted metabolomics analysisThe toxicity and uptake mechanism of triphenyl phosphate by two microalgae was investigated in this study. The finding suggests an increase in membrane integrity, and a decrease in reactive oxygen species (ROS) was observed in Chlorella vulgaris, whereas there was damage to the cellular integrity and ROS reported in Scenedesmus obliquus.[58]
3.Coccomyxa melkonianii SCCA 048GC–MSMetabolomics analysisThe study revealed changes in metabolite synthesis under stress conditions and the effect of these metabolites in pathways like the ascorbate metabolism pathway, phytic acid biosynthesis, TCA cycle, etc.[59]
4.Nannochloropsis oceanica CASA CC201LC-MSIn this study, the effect of various plant growth-promoting factors, such as gibberellic acid, malic acid, and salicylic acid, on lipid biosynthesis was investigated in Nannochloropsis. The results revealed an increase in the level of cofactor and amino acids for the up-regulation of lipid metabolism in the organisms.[60]
5.Haematococcus pluvialisLC-MSThis study revealed an increase in astaxanthin and lipid production under melatonin stress. The metabolomics analysis shows the up-regulation of glucosamine-6-phosphate, maltose, gluconic acid, isocitric acid, etc., which are the precursors for TCA, astaxanthin, and fatty acid syntheses.[61]
6.Chlorella sp.GC-MSThis study showed the effect of autotrophic cultivation and heterotrophic cultivation on lipid synthesis.[62]
7.Chlorella vulgarisLC-QTOFMetabolomics analysisThis study shows the copper nanoparticle with its microparticles and ions on metabolites of Chlorella vulgaris. The metabolic data conclude with alterations in various pathways such as chlorophyll synthesis and glutathione metabolism and the remodeling of membrane proteins.[63]
8Scenedesmus sp. IITRIND2NMRMetabolomics analysisThis study identified an array of metabolites and provides brief insights regarding changes in metabolic pathways under arsenic stress.[64]
In the metabolomic investigation by Arora et al. (2018), NMR spectroscopy was used to identify various metabolites, such as amino acids, sugars, osmolytes, and organic acids, in Scendesmus sp. IITRIND2 [64]. A few reports are listed in Table 1, highlighting the application of metabolomics in microalgal studies.

4. Integrating Metabolomics with Systems Biology Tools

Microalgae are emerging as a promising and alternative source for biofuel production feedstock and several other bioactive compounds. Synthesis of these compounds is a highly complicated cellular process that involves various genes, enzymes, metabolites, and metabolic pathways. The advancement of metabolomics techniques facilitates identifying different metabolites with an upstream impact that enhance the protein expression and activity of the desired product.
Like other omics technologies, such as genomics, transcriptomics, and proteomics, metabolomics also generates lots of unprocessed data, and analyzing these data is quite challenging. The processing and analyzing of this vast dataset requires specialized mathematical, statistical, computational, and bioinformatics tools. The development of these tools for the analysis of metabolomics data comes under the framework of systems biology. Systems biology also includes data mining, data integration, and mathematical development for the remodeling of metabolic networks [65].
Flux Balance Analysis (FBA) is a “constraint-based” and mathematical approach used to simulate the metabolic network in a steady state of any model organism using its genome-scale metabolic model. FBA has been previously used to predict important enzymes of lipid synthesis by analyzing individual reactions and lipid flux results [66]. Additionally, FBA is well used to understand the relation of lipid production with energy–carbon metabolism under different light regimes, carbon sharing in carbohydrates and lipids, and the flow of carbon under nutrient stress [67]. The integration of high-throughput data of metabolomics in FBA-based metabolic modeling suggested possible changes in metabolic networking under various conditions. These computational methods can predict the metabolic flux of the organism and are helpful in the reconstruction of metabolic networking. Yizhak et al. (2010) proposed a new strategy which includes integrative omics–metabolic analysis (IOMA), utilizing proteomic and metabolomic data with the genome-scale metabolic model to predict metabolic flux distribution [68]. Recently, the role of ribosome biogenesis in plant metabolism has been studied using integrated metabolomics and transcriptomics data with metabolic models. The result deduced an alteration in metabolic pathways in wild-type and double-mutant Arabidopsis Columbia after cold treatment [69].

Metabolomics and Microalgae

With their great potential for creating biofuels and bio-based chemicals through carbon-neutral manufacturing based on biomass, microalgae and cyanobacteria are attractive photosynthetic producers [70]. In numerous microalgal species, metabolomics technologies tailored for photosynthetic organisms have been created and applied. In order to enhance the productivity of various secondary metabolites by using microalgae, optimizing metabolic pathways to improve the production of or to build up the amount of the key metabolites in cells is needed [71,72].
Metabolomics involves comprehensive profiling of the complete set of metabolites present in the biological entity. Metabolomics makes it possible to identify and quantify many metabolites in a sample at the same time. Targeted metabolomics is a crucial step in metabolic engineering processes that attempts to quantify important intermediates of interest [73,74,75]. The preparation of the sample has a major impact on the result of the metabolomics studies. Extraction of various metabolites from different microalgae depends on the nature, chemistry, and solubility of the metabolome of the cells. Cells are quickly quenched to stop metabolism, and then intracellular metabolites are extracted to represent the intracellular metabolic state. Methanol/chloroform extraction and cold methanol quenching are two often used techniques [76,77,78,79,80,81,82]. It has been demonstrated that acidic acetonitrile works well for precisely quantifying redox cofactors. Phenol-based extraction has recently demonstrated potential for accurate cyanobacterial metabolomics [83]. Species-specific considerations may influence the choice of appropriate extraction techniques, requiring specialized sample preparation techniques. For example, Azizan et al. examined the diatom C. calcitrans to determine the dynamic spectrum of metabolites by NMR spectroscopy. Using five distinct solvents (acetone, chloroform, methanol, 70% ethanol, and hexane), a total of 29 metabolites have been identified. Additionally, the recovery of the radical-scavenging DPPH free radical and the inhibitory activities of antioxidant substances, like lutein, fucoxanthin, astaxanthin, violaxanthin, zeaxanthin, and canthaxanthin—which could be crucial functional food ingredients in the mariculture industry—were significantly aided by the chloroform extract [82]. Similarly, Alothman et al. (2024) investigated the diatom Cheatoceros tenuissimus metabolome by extracting metabolites with three solvents, e.g., MeOH, CHCl3, and H2O, using NMR and GC–MS techniques [84].
Metabolomics generally uses spectroscopic instruments, such as NMR or MS, in conjunction with chromatographic instruments, such as liquid or gas chromatography (GC), to detect metabolites [85]. Liquid chromatography–mass spectrometry plays a crucial role in metabolomics studies due to its ability to separate, detect, and identify a wide range of metabolites in biological samples. LC-MS has several benefits, such as high sensitivity and selectivity, broad metabolite coverage, structural elucidation, and quantitative analysis. The field of LC-MS-based metabolomics is continuously evolving, with ongoing advancements in instrumentation, data analysis tools, and experimental workflows [86]. These advancements are expected to further enhance the sensitivity, coverage, and throughput of metabolomics studies, leading to a deeper understanding of biological systems and their responses to various stimuli. LC-MS can detect and quantify metabolites present in very low concentrations, even within complex biological matrices. LC-MS has several applications well established in the fields of disease biomarker discovery, nutritional studies, plant metabolomics, standardization and reproducibility, and metabolite identification [87,88,89,90].
Nuclear Magnetic Resonance spectroscopy has become an invaluable tool in the realm of microalgal research, providing researchers with a comprehensive understanding of the complex biochemical composition and metabolic pathways within these versatile organisms [91]. Microalgae, a diverse group of autotrophic microorganisms, have garnered significant attention due to their remarkable potential as a source of valuable bio-products, ranging from biofuels to high-value compounds such as antioxidants, pigments, and pharmaceuticals [92].
One of the key advantages of NMR-based metabolomics in the study of microalgae is its ability to provide a holistic view of the metabolome, capturing a wide range of molecules simultaneously, including primary metabolites, lipids, and secondary metabolites [93]. This approach has been particularly useful in assessing the physiological responses and growth phases of different microalgal species under various environmental conditions [94]. By combining resonance Raman mapping spectroscopy with multivariate analysis methods, researchers have been able to identify characteristic Raman peaks associated with different growth phases and environmental factors, paving the way for the development of non-invasive monitoring and classification techniques. Furthermore, the application of NMR-based metabolomics has extended beyond the realm of microalgae, with recent advancements in the investigation of metal-based drug effects on cellular metabolism [95].
The preparation of data is usually simple when a limited number of metabolites are found in a focused manner. Generally speaking, vendor-specific tools may be used to quantify the peaks. Analyst (AB Sciex), Mass Hunter (Agilent), and MassLynx (Waters) are a few examples. The quantitation in acquisition software is often rather rudimentary, and companies frequently offer companion programs, like Multi Quant (AB Sciex), Mass Hunter Quant (Agilent), and TASQ (Bruker), for more complex applications. Integrating the proper peak, normalizing to the internal standard, and calibrating to a standard curve are the three primary goals of all of these software programs [96].

5. Bottlenecks and the Future Direction of Metabolomics with Microalgae

Microalgae are emerging as a cell factory to produce various bioactive compounds but have very little commercial success due to the lack of knowledge about these compounds’ metabolic network and regulation. To develop microalgae as a cell factory at the commercial level, continuous efforts are required to develop engineering tools that enhance the multiple traits of organisms, such as high biomass accumulation, high photosynthetic efficiency, and higher CO2 utilization of the desired bioactive compound produced. Hence, more investigations should be performed on metabolomics to understand the regulation and rate-limiting steps for producing a specific compound and how each metabolite synthesis relates to other compounds, biosynthesis, and metabolic pathways [97].
Metabolomics studies integrated with omics technologies are emerging with lots of possibilities and show significant potential in biotechnology, agriculture, and other related areas (Figure 3).
These provide clarification regarding the changes in the metabolome and proteome regulation in response to environmental and physiological stimuli. Moreover, metabolomic techniques like NMR also show their potential role in rapid screening of microalgae strains, identifying and profiling potential metabolites and novel compounds. Even though multiple omics approaches are applied to learn the metabolic system of microalgae, a critical overview is limited to some model organisms with only a few metabolic pathways, especially lipid or fatty acid synthesis [98]. Finally, assessing metabolite synthesis under different conditions would be a decision-making step for producing desired compounds with economic advantages.

6. Conclusions

Metabolomics provides a comprehensive snapshot of all metabolites in a biological sample and is an indispensable tool for genetic and metabolic engineering. It gives a clear picture regarding the physiological status of the cell at a particular time under specific conditions. The advancement of metabolomics techniques, especially in analytical instruments such as mass spectroscopy and integration with other chromatography techniques, can play a vital role in improving microalgal strain production for commercially important compounds. These metabolomics approaches give unbiased information about the differential synthesis and regulation of metabolites in microalgal cells. Hence, this approach can be used in metabolic remodeling of microalgae and enhance yields, along with economic perspectives.

Author Contributions

Conceptualization, D.K.S. and R.P.S.; methodology, D.K.S.; software, G.M.; validation, D.K.S., R.P.S. and G.M.; data curation, D.K.S., R.P.S. and G.M.; writing—original draft preparation, D.K.S.; writing—review and editing, D.K.S., R.P.S., R.G.C. and G.M.; visualization, D.K.S., R.P.S., R.G.C. and G.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

Authors Dinesh Kumar Saini and Raghvendra Pratap Singh were employed by the company Azoth Biotech Pvt. Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Metabolomics application in various sectors.
Figure 1. Metabolomics application in various sectors.
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Figure 2. A systematic representation of the biosynthetic pathways of lipid production in microalgae cells and rate-limiting enzymes (ACCase—Acetyl-CoA carboxylase, PAP—Phosphatidic acid phosphatase, DGAT—Diacyglycerol Acyltranferase, LAAT—Lysophosphatidic Acid Acyltranferase, MAT—Malonyl-CoA ACP Acyltranferase, KAS—3-ketoacyl-ACP synthase, FAT—fatty acyl-ACP thioesterase, TAG—triacylglycerols, and PDH—pyruvate dehydrogenase complex).
Figure 2. A systematic representation of the biosynthetic pathways of lipid production in microalgae cells and rate-limiting enzymes (ACCase—Acetyl-CoA carboxylase, PAP—Phosphatidic acid phosphatase, DGAT—Diacyglycerol Acyltranferase, LAAT—Lysophosphatidic Acid Acyltranferase, MAT—Malonyl-CoA ACP Acyltranferase, KAS—3-ketoacyl-ACP synthase, FAT—fatty acyl-ACP thioesterase, TAG—triacylglycerols, and PDH—pyruvate dehydrogenase complex).
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Figure 3. Illustration of procedure and applications of metabolomics. (LC—Liquid Chromatography; GC—Gas Chromatography, CE—Capillary electrophoresis; QQQ—triple quadrupole; TOF—Time of flight; ORBITOP—Orbitrap Gas Chromatography–Mass Spectrometry).
Figure 3. Illustration of procedure and applications of metabolomics. (LC—Liquid Chromatography; GC—Gas Chromatography, CE—Capillary electrophoresis; QQQ—triple quadrupole; TOF—Time of flight; ORBITOP—Orbitrap Gas Chromatography–Mass Spectrometry).
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Saini, D.K.; Manchanda, G.; Chaudhary, R.G.; Singh, R.P. Microalgal Metabolomes and Recent Biotechnological Advances for Their Industrial Application. Microbiol. Res. 2024, 15, 2056-2069. https://doi.org/10.3390/microbiolres15040138

AMA Style

Saini DK, Manchanda G, Chaudhary RG, Singh RP. Microalgal Metabolomes and Recent Biotechnological Advances for Their Industrial Application. Microbiology Research. 2024; 15(4):2056-2069. https://doi.org/10.3390/microbiolres15040138

Chicago/Turabian Style

Saini, Dinesh Kumar, Geetanjali Manchanda, Ratiram Gomaji Chaudhary, and Raghvendra Pratap Singh. 2024. "Microalgal Metabolomes and Recent Biotechnological Advances for Their Industrial Application" Microbiology Research 15, no. 4: 2056-2069. https://doi.org/10.3390/microbiolres15040138

APA Style

Saini, D. K., Manchanda, G., Chaudhary, R. G., & Singh, R. P. (2024). Microalgal Metabolomes and Recent Biotechnological Advances for Their Industrial Application. Microbiology Research, 15(4), 2056-2069. https://doi.org/10.3390/microbiolres15040138

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