1. Introduction

Algae are a highly diverse group of photosynthetic organisms that can thrive in various aquatic and soil environments. They are categorized based on their size, with macroalgae being visible to the naked eye and microalgae being microscopic. Macroalgae, also known as seaweed, height can vary from a few cm and can reach up to 53 m in height if present in ideal conditions [1], such as the Ochrophyta genus Sargassum and Macrocystis [2, 3]. Microscopic algae can range from 0.2–200 μm and are further classified into picoalgae (algae size between 2 and 5 μm), and microalgae [4, 5]. Algae can be prokaryotic or eukaryotic, with eukaryotic algae belonging to various phyla such as Rhodophyta (red algae), Chlorophyta (green algae), Glaucophyta, Euglenophyta, Dinoflagellates, Cryptophyta, Heterokonts, Ochrophyta (brown algae), Eustigmatophyta, Bacillariophyta (diatoms), and Haptophyta. Despite algae being tremendously rich with essential by-products that are useful for many industrial applications, only about 30,000 species of algae have been identified and studied due to limitations in research on microalgal biodiversity [6, 7]. The lack of taxonomists and researchers in this field has resulted in inadequate records of microalgae diversity and the loss of their potential uses [8].

Why is it important to study biodiversity? A remarkable feature of our planet Earth is its ability to sustain a great variety of life. However, one of the most prevalent occurring environmental changes is the loss of this biological variation. Scientists have determined that the leading cause of species extinction is due to the drastic anthropogenic changes we currently face [9, 10]. Research indicated that the rate at which different resources are deteriorating is increasing, and water quality is decreasing exponentially with the declining species diversity [11]. The decrease in diversity would eventually lead to the homogenization of an ecosystem and, as a result, would lead to a decrease in the functionality of this ecosystem [12, 13]. The absence of heterogeneity in an ecosystem would further result in the loss of energy fluxes and matter that are essential to all ecological processes, which also includes the loss of control over the abundance, biomass, and distribution of organisms in an ecosystem [10, 14, 15]. For instance, an example of a food chain would include microalgae and picoalgae as the primary producer in an aquatic ecosystem. The absence or abundance of algae can lead to the interruption of this food chain due to the low evenness, which means that the community has a few abundant species that are dominating the community and could consequently result in the loss of the following consumers in the food chain [16]. The functionality of an environment is considered preserved when evenness is high, and the community contains various species that equally exist, with no one species gaining the upper hand and dominating an ecosystem [17, 18, 19].

The United Nations (UN) has expressed concern about the loss of habitats and species, which threatens the functionality of our ecosystem and planet Earth. In response, the UN declared 2010 as the International Year of Biodiversity and developed the Strategic Plan for Biodiversity 2011–2020 (CBD, 2010), which aims to improve the science base and biodiversity-related technologies by 2020. To achieve this goal, biodiversity analysis and studies must be intensified to preserve and protect the remaining biodiversity [20]. This chapter will focus on microalgae and will discuss the different methods used to collect environmental samples and identify microalgae diversity present in their natural environments, which will ultimately facilitate the conservation of biodiversity and preserve the known and unknown potentials of microalgae and their by-products.

2. Microalgae cellular structure importance to microalgae identification

Microalgae are microorganisms that belong to the kingdom Protista. Microalgae have different morphological characteristics that, when observed under the microscope, aid in taxonomic-level identification and classification. However, this is not the case when it comes to picoalgae such as Synechococcus and Chrysochromulina, which are extremely small-sized and are difficult to be identified on a morphological level [21, 22]. Hence, they are mostly classified through ribosomal RNA (rRNA) or other identical tools that do not depend on morphological characteristics.

2.1 Microalgae basic cellular structure

Microalgae cellular organization that can be used to distinguish microalgae includes unicellular (non-motile and motile), colonial (coenobic and non-coenobic), and filamentous (simple, branched, and heterotrichous). A feature that can clearly help in the identification of microalgae is their ability to locomotion [23, 24]. The motility of microalgae is of two types: flagellar motility and gliding motility [25]. Euglena and Pedinomonas are examples of microalgae that have flagella. Microalgae that do not have flagella still have the ability to glide, such as Synechococcus and Oscillatoria [26, 27]. Chlorophyta is the only phylum of microalgae that grows in the form of coenobic colonies (such as Volvox) [28]. While non-coenobic microalgae retain a gelatinous matrix or are found to be attached by a gelatinous stalk [29, 30]. Eukaryotic microalgae cells have organelles that are membrane-bound and unlike bacteria [31]. The prokaryotic cyanobacteria, also known as blue-green algae, are considered photosynthetic bacteria. Their deoxyribonucleic acid (DNA) lies freely in the cytoplasm, yet they, like microalgae, can carry oxygenic photosynthesis (conversion of CO₂ and water to sugars using the energy from light) even though they lack a true chloroplast. In cyanobacteria, photosynthetic electron transport occurs in the thylakoid membranes present in the cytoplasm [32, 33]. Through evolution, eukaryotic microalgae have gained their cellular complexity from cyanobacteria endosymbiosis.

2.2 Plastid evolution and microalgae pigments

The plastid in microalgae originated as a result of endosymbiosis with cyanobacterium (as the primary chloroplast ancestors) [34, 35]. Further evolution of the plastid in microalgae occurred through a series of endosymbiotic events in which the primary endosymbiosis gave rise to the plastid of red algae, green algae, and plants chloroplast [35, 36, 37]. The secondary symbiosis resulted in more diversification and complexity of the plastid of microalgae species. Euglenoids, chlorarachniophytes, and a small group of dinoflagellates have up-taken the green algae chloroplast through the secondary endosymbiosis resulting in the three-membrane plastid [37]. The secondary endosymbiosis of glaucophytes and red algae further resulted in the presence of four-membrane-bound plastids that can be identified in Chlorarachniophytes, Haptophytes, and Heterokonts.

Certain plastid genes have been noted to track the origins of the plastid to cyanobacteria. RuBisCO genes, responsible for the production of ribulose-1,5-bisphosphate carboxylase/oxygenase, a critical enzyme in carbon fixation, have created confusion about the endosymbiotic events and the existence of microalgae from cyanobacteria [38]. Interestingly, some algae groups contained similar non-cyanobacteria enzymes. However, this has been elucidated by confirming that several gene duplications and subsequent gene divergence resulted in the paralogous sequences of the gene that have been transferred through horizontal gene transfer, giving rise to the Rubisco phylogeny [39]. By comparing the genome of cyanobacteria to that of a eukaryotic microalgae plastid, it was found that the number of genes significantly decreased. This is because several plastid genes have been moved to the nucleus, and some genes have been lost due to their redundant function [34]. In addition, there are various heterotrophic microalgae that are non-photosynthesis, including certain lineages of Euglophytes (E. gracilis and E. longa), diatoms (Nitzschia sp. strain NIES-3581), and green algae Polytomella spp. and Helicosporidium sp. Although these microalgae lack genes related to photosynthesis in their plastids, the plastids still play a crucial role in their survival by participating in various biological pathways other than photosynthesis [40, 41, 42].

The type of pigmentation present within the plastids also reflects the plastid lineage and phylogeny of the microalgae. The three major pigment classes present in microalgae are chlorophylls, carotenoids, and phycobiliproteins. The pigments absorb light at different wavelengths making their productivity depend on the light regimen they are exposed to. Microalgae, such as Chlorophyta (green algae), contain chlorophyll a and b pigments that produce absorption peaks at wavelengths between 300 and 700 nm, which is the wavelength of the visible spectrum [43]. Chlorophyll a absorbs light in the red-violet region and is present in all the microalgae phyla, while chlorophyll b absorbs light in the red-blue region, and both reflect green light [44, 45, 46]. Hence, the green appearance of the green microalgae. Cyanobacteria, on the other hand, lack chlorophyll b and favor low light intensities. Even though cyanobacteria lack chlorophyll b, however, the capture of photons is compensated by the presence of Phycobilisomes (PBS) light-harvesting antennae that contain chromophores, also known as phycobilins that are capable of absorbing orange, green, and blue-green light at wavelength 620 nm, 545 nm, and 495 nm, respectively [47, 48]. Carotenoids are terpenoid pigments that play an important role in photosynthesis as they harvest light within 400 and 550 nm and transfer it to chlorophyll a [49]. They also play an important role in protecting the microalgae cell and its photosynthetic machinery from reactive oxygen species (ROS) [50]. Unicellular and multicellular microalgae can have one or more chloroplasts present in a cell. Chloroplast division in microalgae occurs once per cell cycle [51], while in a plant, each cell may have up to 20 chloroplasts in each mesophyll cell of a plant [52]. Microalgae cells under the algae order Chlorococcales and Volvocales follow a cell cycle known as the multiple fission cycle (Cn). Under optimum conditions (in terms of light and temperature), they can divide into 8–16 identical daughter cells in the cell division cycle of about 6–12 h [53, 54].

3. Acquisition of environmental samples for studying algal diversity

Microalgae are typically found in environmental sources such as rivers, lakes, oceans, and soil. To identify the diversity of microalgae in a particular ecosystem, selecting the appropriate sample site is crucial. When choosing a sampling site, certain conditions must be taken into account. The Environmental Protection Authority (EPA) recommends developing a monitoring plan that considers various factors to ensure consistency in sampling. These measures are necessary to maintain sample integrity, as any changes to the conditions may alter the sample and lead to misleading information. Mismanagement of water and soil resources can result from inaccurate analysis of such samples [55, 56].

3.1 Sample collection methods

3.1.1 Manual sampling (grab/hand samples)

Water or soil samples can be collected manually by hand in a collection bottle. Using this method limits sampling to surface sampling. This method is cost-effective and does not eliminate microalgae depending on their size; however, this method limits the collection to microalgae with high buoyancy due to the presence of gas vacuoles that are mainly present in cyanobacteria [57, 58, 59].

3.1.2 Plankton nets

Nets are made up of nylon or silk and have a cylinder or valve attached to the bottom for sample collection. The nets come in different mesh sizes that can range from 10 to 1000 microns [60]. Plankton nets are used to quantitatively and qualitatively identify microalgae present in water sources. The net can be used to collect samples horizontally from a water surface, by adding weights to the net a vertical sample can be collected from the depth of the water source. The mesh size also plays an important role in the identification of microalgae from environmental samples. The size of the mesh selected can lead to the elimination of certain microalgae from the analysis of the environmental sample. Furthermore, the identified microalgae only mirror the filtering capability of the mesh [55]. Small-sized mesh samples are easily clogged, while large-sized mesh leads to the loss of smaller-sized microalgae.

3.1.3 Van Dorn sample bottle

The Van Dorn samplers enable depth sampling of water sources. The sampler consists of a hollow tube that is made up of PVC (Polyvinyl chloride) or acrylic that is connected to a rope. The tube is fitted with a seal at both ends that seals to lock the water collected in. The sampler is deposited in the water source to the desired depth, and the seals are released to lock the water in. The sample volume collected is known and the sample is drained through a drain valve [61]. The Schindler-Patalas trap is a similar tool that combines the Van Dorn and a phytoplankton net. The trap box is fitted with a mesh net at the bottom of the wall of the trap through which the collected sample is filtered after collection.

3.1.4 Van Veen grab sampler

The Van Veen grab sampler can be used to collect samples from soil or sediments. The sampler consists of claws that can grab sediments. Soil samples need to be either soaked in autoclaved distilled water or an enrichment media to extract and enhance the soil microalgae into a liquid media to enable and ease the microalgae identification.

3.2 Sample processing

Sample preservation may be necessary to maintain the integrity of the morphological features of the microalgae collected. Common fixatives used in preserving and fixing microalgae and protists are formaldehyde and Lugol’s iodine solution. Fixative stains at a low concentration can aid in morphological identification. However, the addition of a higher concentration may lead to the loss of flagellum and sometimes cell loss [62] and may hinder the molecular screening process [63].

To isolate a single cell from liquid media, one can use a micropipette or a glass capillary tube. The latter can be made by manually stretching a Pasteur pipette under a flame to create a capillary tube. This technique is useful for isolating single microalgae cells from a small sample drop under an inverted microscope. However, it may require expertise in both the isolation technique and microalgae identification. Another method of microalgae isolation is the streak plating of environmental samples on solid agar, usually a concentration of agar between 0.8 and 2%. This can be directly from an environmental sample or following a serial dilution of the sample. The plating of environmental samples can limit the identification of non-motile microalgae. However, several other methodologies may be involved in the identification of microalgae. Serial dilution is one of the most common methods that includes the preparation of serial dilution of a collected water sample or soaked soil sample with autoclaved distilled water. The dilution factor is maintained at each step [64]. The dilution set created can be cultured on an enrichment liquid or solid media. This method enables isolating single microalgae cells from the environment [65, 66]. The enrichment of a dilution on a liquid enrichment media can enable the identification of motile and non-motile microalgae. Fluorescence-activated cell sorting (FACS) and flow cytometry (FCM) cell sorting are two high-throughput automated isolation and screening techniques. The technique allows isolation and identification of microorganisms based on particle volume, fluorescence, and the cell’s ability to scatter light [67, 68, 69].

3.3 Enrichment of sample by nutrient media

An easy and inexpensive approach that is commonly used for the identification of an environmental sample is the use of culture media to enrich species in an environmental sample, followed by using microscopy to identify and isolate the species observed in the sample or a more advanced identification tool. Even though sample enrichment is considered a “golden tool” to analyze the diversity of an unknown sample, it is similar to the direct identification method, which depends on the resolution of the microscope and the expertise of the workforce [70]. Currently, the enrichment of environmental samples is usually followed up with identification on a molecular level to confirm the phylogenetic classification of the microalgae isolated [66, 71, 72, 73, 74, 75, 76, 77]. Microalgae can either survive as free organisms or co-exist in the presence of other organisms, such as lichens, in which the microalgae are said to live in symbiosis with other fungi and bacteria [78]. Therefore, enriching an environmental sample can help identify species that are not easily observable but are present only in large populations. Hence, optimization of nutrient composition, pH, temperature, and light intensity to enrich microalgae species and mimic the naturalistic conditions is necessary to ensure the identification of maximum diversity enrichment. Commonly used media like Bold’s Basal Media (BBM) and Blue-green media (BG-11) can be used to prevent favoritism toward specific genera or phyla. However, selective enrichment media may also be required to nourish specific microalgae phyla that require extra elements, such as diatoms that need silica [79] found in F/2 nutrient media [80, 81] (Table 1). This section focuses on the different culturing requirements of microalgae since it is important to consider their effects on microalgae identification, growth, and by-product production. Some culturing parameters that may require optimization for improvement of microalgae identification and isolation include the following:

Synthetic media	Main phyla enriched	Illumination	Carbon source	Species enriched	Ref.
BBM	Chlorophyta	25 μmol photons m⁻² day⁻¹ (continuous) Fluorescent lamps-5 Days	5% CO₂ aeration	Desmodesmus sp. Chlamydomonas sp.	[82]
		2000 lx (12:12 h) Fluorescent lamps-10 days	2% CO₂ aeration	Chlorella Parachlorella Desmodesmus sp. Micractinium sp.	[83]
		200 μmol photons m⁻² s⁻¹ (continuous)—14 days	0.5 g L⁻¹ Sodium carbonate (agar media)	Chlorella singularis	[84]
BG-11	Cyanophyta and Chlorophyta	150 μmol photons m⁻² s⁻¹ (continuous)—Fluorescent lamps −14 Ddays	98% air: 2% CO₂ aeration	Chlamydopodium fusiforme (culture maintenance and initiation)	[85]
		75 ± 7 μmol m⁻² s⁻¹ (continuous)—Fluorescent lamps – 3 months (initiation culture)	Shaking 130 rpm for atmospheric CO₂ dissolution (~410 ppm) and sodium carbonate in BG-11 (0.19 mM)	Anabaena sp. strain UTEX 2576 (culture maintenance BG-11 missing nitrogen to maintain heterocyst)	[86]
		125 μE m⁻² s⁻¹ (12:12 h) Fluorescent lamps	Sodium carbonate in BG-11 (0.19 mM)	Ankistrodesmus Botryococcus braunii Botryococcus sudeticus Chlorella vulgaris Nannochloris oculate Scenedesmus dimorphus Anabaena variabilis Synechocystis sp.	[87]
Walne’s medium	Diatoms	1300–2500 lx	Not mentioned	Skeletonema sp.	[88]
Walne’s medium	Diatoms	30 μEm⁻² s⁻¹ (12:12 h) Fluorescent lamps-10 Days	Not mentioned	Amphora sp.	[89]
Guillard’s F/2 medium	Chlorophyta and Diatoms	120 μmol photons m⁻² s⁻¹ (continuous)—Fluorescent lamps	Continuous aeration	Dunaliella tertiolecta Chlorella sp. Tetraselmis sp. Nitzschia sp. Thalassiosira rotula Bacillariophyta sp. Phaeodactylum tricornutum Cylindrotheca Closterium Cymbella sp. Navicula sp.	[90]
		250 μmol photons m⁻² s⁻¹ (12:12 h)—Fluorescent lamps – 14 days	Continuous aeration	Navicula incerta	[91]
		80 μmol photons m⁻² s⁻¹ (continuous)—Fluorescent lamps	Not mentioned	P. tricornutum	[91]
		3000 lx (18 h light:6 h dark) – Fluorescent lamps	Not mentioned	Pennate Diatoms Chlorella sp.	[92]
		90 μmol photons m⁻² s⁻¹ and 200 μmol photons m⁻² s⁻¹—Fluorescent lamps – 8 days	Continuous aeration and Sodium bicarbonate in media	C. vulgaris Scenedesmus sp. Coelastrum sp.	[93]
Jaworski’s medium	Chlorophyta	10.8 μmol photons m⁻² s⁻¹ (continuous)—Fluorescent lamps	Continuous aeration and Sodium bicarbonate in media	Chlorella sp. Scenedesmus sp. Monoraphidium sp. Carteria sp.	[94]
Jaworski’s medium	Chlorophyta	200–250 μmol photons m⁻² s⁻¹ (18 h light:6 h dark)—LED light—20 days	Continuous aeration and Sodium bicarbonate in media and Glycerol	C. vulgaris B. braunii Scenedesmus sp.	[95]

Table 1.

Synthetic nutrient media commonly used for microalgae enrichment.

3.3.1 Light

Microalgae are photosynthetic microorganisms that absorb light energy and convert it to chemical energy in the photosynthetic apparatus, the photosystem. The photosystem complex contains pigments such as chlorophyll or carotenoid that absorb light energy. Light energy is measured in irradiance; photons of light that are used photosynthetically are known as photosynthetically active radiation (PAR). PAR is usually reported in μmol m⁻² s⁻¹ or in μE m⁻² s⁻¹. Light intensity has been vastly studied to increase algae production and growth rates [67, 68, 69]. Artificial light is widely used in photobioreactors, with light-emitting diodes (LEDs) being a common choice. Research has focused on the impact of light color on growth, carbohydrate, protein, and pigment content. For instance, red light has been found to increase biomass, while blue light increases the cell concentration of Chlorella kessleri [96]. In a study by Jin et al., monochromatic red light (660 nm) resulted in decreased biomass and cellular components, leading to reduced carbohydrate, carotenoid, and protein levels in Dunaliella salina. Conversely, monochromatic blue light (445 nm) did not significantly increase biomass production but led to the accumulation of lipids, proteins, and carbohydrates. Combining red and blue light resulted in higher dried biomass and cell content compared to white light [97, 98]. White light increased the cellular productivity and protein content of Isochrysis zhanjiangensis, while red light increased the specific growth rate. Greenlight improved the pigment content of Isochrysis sp. but reduced biomass, and blue light promoted carbohydrate content [99]. In another study, Chlamydomonas reinhardtii exposed to yellow light resulted in the highest biomass concentration, while blue and red light separately resulted in the lowest biomass [100]. The photosynthetic process and growth of microalgae are significantly affected by the duration, wavelength, and intensity of light exposure [101, 102]. Hence, the choice of light color is essential for both microalgae cultivation and the production of specific biochemical by-products, which at the end might favor one species over another, impacting population diversity.

3.3.2 Nutrients

The growth of microalgae and the synthesis of proteins, lipids, and carbohydrates require macronutrients, mainly nitrogen (N), phosphorus (P), and potassium (K). Nitrogen is considered a crucial element as it forms a significant portion of structural molecules in microalgae, including nucleic acid, amines, and is also needed for cell wall components and pigment production [103, 104, 105]. Microalgae can obtain various forms of nitrogen from their surroundings, inorganic nitrogen, such as nitrates, nitrites, ammonium, and the organic nitrogen in the form of urea. Ammonium nitrate is taken up more easily and at a higher rate by microalgae. Nitrates, on the other hand, are converted into ammonium inside the microalgae chloroplast, making ammonium a better option in terms of the energy needed for the nitrate-to-ammonium conversion [106, 107]. However, microalgae exposure to high ammonium concentration can suppress nitrate uptake, possibly due to a negative feedback loop, which may be attributed to the high production of glutamine in the cell upon exposure to ammonium [108]. Hence nitrates are currently being commonly used in synthetic media. Phosphorus is another essential macronutrient that is required by microalgae to produce nucleic acid, phospholipids, and ATP, as well as for cell division and growth [109]. Insufficient phosphorus can result in decreased lipid content [110] and a decline in chlorophyll a levels, as phosphorus is necessary for its production [111]. Even though they are required in minute quantities, vitamins significantly influence the cellular biochemistry of microalgae. Microalgae exist in a mutualistic symbiotic relationship with bacteria, where they obtain vitamin B (cobalamin, thiamine, and biotin) produced by bacteria in exchange for carbon fixation [112]. As microalgae are unable to produce these vitamins de novo, they must be supplemented in synthetic media [113, 114].

3.3.3 Carbon sources

Microalgae require carbon sources for cell growth and the production of necessary primary metabolites such as carbohydrates, lipids, and proteins. Microalgae also can utilize different carbon sources. They can be cultured under autotrophic conditions using inorganic carbon such as carbon dioxide (CO₂) or bicarbonate and light to produce energy through the process of photosynthesis. Yeh et al. (2010) tested the impact of using sodium bicarbonate (NaHCO₃) as a carbon source on Chlorella vulgaris, the higher the concentration of NaHCO₃ (1 g/L), the higher the biomass production along with the optimum light intensity [115]. Microalgae can also be heterotrophs under lightless conditions using organic carbon sources such as glucose or glycerol [116, 117, 118], while microalgae in the presence of light in mixotrophic cultures can use either organic or inorganic carbon sources. Phaeodactylum tricornutum showed an increase in biomass and lipid production when grown in a media with glycerol as a carbon source and 24-h illumination regimen [119]. Similarly, Chlorella sorokiniana [120] and diatom Thalassiosira pseudonana [121] showed better biomass and lipid production when grown on glycerol compared to glucose. Glucose assimilation was considered higher in heterotrophic culture resulting in nine times higher biomass of Auxenochlorella protothecoides when compared to autotrophic mode indicating that the uptake of glucose by A. protothecoides may be inhibited by light [122]. This was also observed when tested on Chlorella and Scenedesmus cultures [123]. Yet, Pavlova lutheri cultured on sucrose showed better biomass and lipid production under mixotrophic conditions when compared to heterotrophic conditions and other carbon sources such as glucose and glycerol [124].

Although the use of an organic carbon source with a light source allows microalgae to function under mixotrophic conditions as an alternative to autotrophic and heterotrophic conditions, the presence of organic carbon reduces the microalgae CO₂ capture efficiency for photosynthesis [125, 126]. Additionally, the presence of inorganic carbon sources or dissolved CO₂ is known to decrease pH due to the dissociation of the inorganic carbon and the release of H⁺ ions, leading to media acidification and reduced microalgae activity [127]. Some algae can utilize both inorganic carbon sources and CO₂ capture, while others only depend on the inorganic carbon sources if present, and this process is pH-dependent. Since the bicarbonate form of inorganic carbon is mainly predominant at pH 9, while at lower pH, both the aqueous form of CO₂ and the bicarbonate form are equally present [128]. Therefore, managing the pH of microalgae culture is crucial as it plays a vital role in making essential elements available for microalgae growth and regulating microalgae biochemical pathways.

3.3.4 pH

pH is one of the important parameters that needs to be maintained to conserve the physiology of microalgae. However, in a natural habitat, pH is quite variable and not necessarily maintained. Therefore, microalgae collected from the environment may have developed tolerance to the pH of the extreme ends. Hence, the need to optimize pH conditions for the enrichment of a complete diversity or specific microalgae depending on the research aim. In a culture media, the presence of the inorganic carbon source bicarbonate is converted to CO₂ by the enzyme carbonic anhydrase to release hydroxyl ions that result in an increase in pH. This increase in pH results in the inhibition of cell growth due to the reduction of nutrient accessibility; an increase in pH will eventually result in a decrease in cell growth [129]. Freshwater microalgae have been reported to tolerate high pH (>10) and extremes of pH in general, while marine algae are limited to growth within the pH range of 8.1–8.3 [129, 130]. An increase of pH (from pH 8.5 to pH >11) in the culture media also leads to the flocculation of algal cells, a desired feature in the industry, and is used to harvest algae, but is troublesome when studying diversity [131].

3.3.5 Temperature

Another parameter that affects microalgae growth is temperature. The optimal temperature for microalgae to carry out cell functions and photosynthesis is generally between 15 and 30°C. Within the optimum temperature, ideally, an increase in temperature has a positive effect on the photosynthetic process and cell division. However, an unfavorable increase above the optimal temperature range can sharply decrease the growth rate of microalgae. This is because enzymatic functions are drastically affected by the high temperatures, hence affecting important enzymes of the electron transport chain, Calvin cycle, and membrane stability, eventually influencing the growth rate of the microalgae [132]. However, this is not always the case in cultures since microalgae are highly adaptive with the potential to adapt to extreme environments such as arid deserts [132, 133, 134, 135]. Furthermore, microalgae can be pre-adapted and acclimatized to certain temperatures depending on their habitat when cultured in the laboratory settings [136].

4. Microalgae identification methods

4.1 Direct morphological identification

The direct identification of microalgae from environmental samples starts by collecting a sample either from water or soil as representative of the habitat. This is followed by direct observation through morphological characteristics of the different microalgae species under the microscope. There are several identification guidelines and keys available to aid in the identification of microalgae [31, 137, 138, 139, 140]. This method depends mainly on the presence of a research-grade microscope.

Scanning and transmission electron microscopes (SEM and TEM) are not options that are readily available in all research labs. However, they are used to study fine ultrastructure details on the species level of microalgae. Moreover, viewing microalgae under SEM and TEM requires specific cell preparation to preserve the ultrastructure of the microalgae. The preparations involve fixation, dehydration, and sputtering of the sample with gold particles [141, 142, 143]. Automated microalgae identification is a modern form of morphological level identification that is currently made available for the taxonomic identification of microalgae from an environmental sample. An automated system depends on machine learning and a training set that consists of a set of captured images of microalgae that a taxonomist has previously identified. This training set is used to train the software to classify the different microalgae genera [144, 145, 146, 147, 148, 149]. Yet, identifying microalgae based on their physical characteristics is challenging as their phenotypic traits are heavily influenced by the environment and their response to stress [150, 151]. To overcome this issue, molecular-based identification has emerged as an essential alternative approach that enables the identification of microalgae irrespective of any changes in their physical or morphological traits.

4.2 Molecular-level identification

Molecular-level identification is the process of identifying microalgae on a genetic level. This process involves various steps and can be categorized into two main approaches: non-polymerase chain reaction (PCR)-based or PCR-based methods. These methods can be applied directly to environmental samples, enriched samples, or isolated species. Additionally, molecular level identification can serve as a confirmation tool for morphological level identification (Figure 1). This section will discuss the technologies utilized in both approaches for identifying microalgae diversity.

Figure 1.
Various methods that can be utilized to identify microalgae in environmental samples.

4.2.1 Non-PCR-based identification

4.2.1.1 Fluorescence in situ hybridization (FISH)

FISH is a technique that depends on the hybridization of a fluorescently labeled DNA sequence to its complementary sequence in a cell, followed by identification using epifluorescence microscopy. FISH has been used and optimized to identify harmful microalgae species mainly. This method has successfully identified dinoflagellates Gambierdiscus spp. [152], Biecheleria baltica [153] and the toxic Alexandrium sp. [154, 155, 156, 157], Chromophyta Heterosigma akashiwo [158].

4.2.1.2 Restriction fragment polymorphism (RFLP)

The identification of different organisms has been facilitated by RFLP, a technique that analyzes specific DNA sequence variations. This involves digesting DNA with restriction endonucleases and observing the digestion pattern through gel electrophoresis. Consequently, RFLP has been widely employed in gene mapping and DNA fingerprinting [159]. However, its use in microalgae identification has been limited [160]. PCR-RFLP or Terminal-RFLP (T-RFLP) are alternative methods to RFLP analysis, and they depend on the combination of PCR for DNA amplification of DNA barcodes and restriction fragment analysis, as discussed next.

4.2.2 PCR-based identification

Polymerase chain reaction (PCR)-based molecular level identification depends on amplifying short conserved nucleic acid sequences known as DNA barcodes. Different DNA barcodes can also be used to identify different phyla of microalgae. For instance, the 16S ribosomal DNA (rDNA) sequence is mainly used for cyanobacteria identification region [161], while the 18S rDNA is used for eukaryotic microalgae by using primers designed to amplify the variable regions or the internal transcribed spacers (ITSs) in addition to the identification of eukaryotic microalgae through plastid genes [162] (Figure 2). The level of identification, whether to the genus or species level, depends on the reference database used for alignment. This method has gained popularity in taxonomical identification and phylogenetic analysis as it eliminates the need for culturing microalgae to confirm their presence, allowing the ease of direct identification from environmental samples. The identification and analysis of DNA barcodes have been facilitated by the development of various biotechnology tools (Table 2). The following are some tools that can be used to identify microalgae through DNA barcodes.

Figure 2.
Schematic diagram representing the ribosomal gene cluster (rDNA) of the (A) 16S and (B) 18S rDNA that are commonly used for the identification of cyanobacteria and eukaryotic microalgae, respectively. The hypervariable regions are denoted with V1-V9 on the 16S and 18S rDNA.

Microalgae phyla	Ref.	DNA barcode*	Genus	Tools
Chlorophyta	[163]	18S rDNA V4 region and rbcL	Scenedesmus sp. Tetradesmus dimorphus Stichococcus sp. Parachlorella kessleri Chloroidium saccharophilum Monoraphidium sp. Chlorococcum sp.	Sanger sequencing
	[162]	16S rDNA (plastid)	Chlorella vulgaris	Sanger sequencing
	[164, 165]	rbcL	Chlorella strains	Sanger sequencing
	[166]	rbcL, ITS, 16S rDNA (plastid) and tufA	Scenedesmus strains	Bidirectional sequencing
Cyanophyta	[167]	16S V5-V6 rDNA and 16S-23S ITS region	Chlorogloeopsis sp. Leptolyngbya boryana Thermoleptolyngbya albertanoae Synechococcus bigranulatus Oculatella sp. Desertifilum sp. Leptolyngbya geysericola Geitlerinema splendidum Cyanobacterium aponinum	454 pyrosequencing and Illumina MiSeq™ platform
	[163]	16S rDNA-ITS region	Synechocystis sp. Aphanocapsa sp. Chroococcidiopsis thermalis Nostoc sp. Cylindrospermopsis raciborskii Pseudanabaena sp.	Sanger sequencing
	[168]	16S rDNA-ITS region	Aphanizomenon sp. Olichospermum sp. Limnoraphis sp. Microcystis sp.	Sanger sequencing
	[169]	16S-23S ITS region	Scytonema hyalinum	Illumina MiSeq™ platform
	[170]	16S rDNA	C. stanieri Prochloron sp. Synechocystis sp. PCC6803	Sanger sequencing
	[171]	16S rDNA	Nostoc strains	Sanger sequencing
	[172]	16S rDNA	Phormidium retzii	RAPD and Sanger sequencing
Bacillariophyta	[173]	COI, rbcL, SSU, and LSU	Asteroplanus karianus Cerataulina pelagica Chaetoceros muellerii Cyclotella sp. Entomoneis sp. Licmophora paradoxa Melosira varians Navicula bottnica Phaeodactylum tricornutum Skeletonema costatum Thalassiosira gravida	Bidirectional sequencing
	[174]	COI, 23S rRNA gene, SSU and LSU	Sellaphora Navicula Nitzschia Fragilariopsis Tragilariopsis Pseudonitzschia	Sanger sequencing
	[175]	18S V4 rDNA	Leptocylindrus Chaetoceros Thalassiosira Skeletonema Pseudonitzschia	454 pyrosequencing
	[176, 177]	COI, rbcL, SSU, and LSU	Frustulia strains	Sanger sequencing
Dinophyta	[178]	COI	Alexandrium Scrippsiella Karlodinium Karenia	Sanger sequencing
	[179]	16S rDNA and 18S rDNA V3-V4 region	Karlodinium veneficum Gyrodinium sp. Gymnodinium sp. Gonyaulax sp. Symbiodinium sp. Amphidiniella sp. Ceratium sp.	Illumina MiSeq™ platform
	[180]	COI, calmodulin, rad24, and actin	Amphidinium carterae Alexandrium tamarense Heterocapsa triquetra Karenia brevis Karlodinium micrum Lingulodinium polyedrum Symbiodinium	Sanger sequencing
	[181]	COI and cob	A. tamarense, Pfiesteria piscicida Karlodinium veneficum Prorocentrum minimum Akashiwo sanguinmea P. micans Prorocentrum nanum D. acuminata Ceratocorys horrida	Sanger sequencing
Haptophyta	[182]	18S rDNA V4 region	Phaeocystis Chrysochromulina Prymnesium Braarudosphaera Gephyrocapsa/Emiliania	Ion torrent (IT) sequencing
	[183]	LSU	Chrysochromulina Umbilicosphaera Calcidiscus Coronosphaera Scyphosphaera Helicosphaera Coccolithus	High-Throughput Sequencing
	[184]	SSU rDNA V4 region	Haptolina fragaria Pleurochrysis pseudoroscoffensis Chrysochromulina Prymnesium polylepis Phaeocystis Emiliania Isochrysis galbana Imantonia rotunda Diacronema ennorea	454 pyrosequencing
Euglenophyta	[185]	COI and 18S rDNA	23 euglenida species	Sanger sequencing
Euglenophyta	[186]	16S V3-V4 (for cyanobacteria) and 18S V4 rDNA (eukaryotic microalgae)	Colacium vesiculosum Discoplastis spathirhyncha Euglena sp. Flexiglena variabilis Lepocinclis sp. Monomorphina pyrum Phacus sp. Trachelomonas sp.	Illumina MiSeq™ platform

Table 2.

Common DNA barcodes utilized for the identification of microalgae.

*

DNA barcode abbreviations: ribulose-1,5-bisphosphate carboxylase/oxygenase (rbcL), large subunit ribosomal DNA (LSU rDNA), small subunit ribosomal DNA (SSU rDNA), cytochrome c oxidase I (COI), encoding elongation factor (tufA gene), internal transcribed spacer region (ITS), cytochrome oxidase B (cob), calcium-modulated protein (calmodulin), damage checkpoint rad24 protein (rad24).

PCR-Restriction Fragment Polymorphism (PCR-RFLP) and Random Amplified Polymorphic DNA (RAPD) are two PCR-based techniques that have been utilized to identify different microalgae species. PCR-RFLP is a method that involves amplifying a DNA barcode before digesting the amplified region with restriction nucleases. This technique has been successfully used for the identification of microalgae such as Stihococcus sp., Nitschia sp., C. vulgaris, and Navicula accomoda through the PCR of 18S rDNA and its digestion [187]. PCR-RFLP has also been used to identify the dinoflagellate Gambierdiscus sp. isolated from the Caribbean Sea and Mexican coast was also identified through the amplification of the LSU rRNA D1-D2 sequences of the 18S rDNA [188]. Random Amplified Polymorphic DNA (RAPD) is another PCR-based technique that is useful for identifying genetic variation in different species [189]. RAPD has been used in the identification of different Chlorella strains [190], Microcystis species [191], Dunaliella species [192, 193], and diatom Chaetoceros species [194]. However, with the emergence of sequencing technology has provided a more reliable and accurate identification method over RAPD.

Sanger sequencing, also known as chain termination sequencing or first-generation sequencing, has been widely used as a confirmatory tool for identifying microalgae post-enrichment and isolation from environmental samples. The effectiveness of this method is dependent on the utilized DNA barcode, with a multiple primer approach often employed for identifying microalgae diversity across various phyla (Table 2). For instance, Ballesteros et al. used 16S rDNA and 16S–23S rDNA regions for cyanobacteria identification and 18S rDNA and ribulose-bisphosphate carboxylase (rbcL) gene for chlorophyta identification [163]. Other DNA barcodes used in identifying eukaryotic microalgae include the mitochondrial gene cytochrome c oxidase subunit 1 (cox1 or COI), ITS (ITS1–5.8S-ITS2), and elongation factor EF-Tu (tufA) gene [195].

Metagenomics involves the direct study of genomes in their natural habitat without isolation, and this is made possible due to the development of next-generation sequencing. Samples can be either directly used for DNA extraction, such as soil samples or water samples can be filtered with the appropriate filter paper followed by DNA extraction, and samples can be sequenced using Illumina MiSeq™ and HiSeq™ platform [186, 196, 197, 198]. Next-generation sequencing provides the best tool to identify the highest microalgal diversity from environmental samples; however, similar to any DNA-based tool, it depends on the sequences available in the database and is not usually combined with single species isolation.

4.3 Biochemical marker for microalgae identification

Several approaches have been employed to identify microalgae based on their pigment, also known as chemotaxonomic markers. Additionally, carbohydrates, lipids, and fatty acids may be used as chemotaxonomic markers. Microalgal photosynthetic pigments constitute a diverse range and are a highly valuable product with a vast array of commercial applications, including the food, cosmetics, and health industries [50, 199, 200, 201]. Despite the variety of chemotaxonomic markers, microalgae are known for their adaptability and plasticity as their cell composition and phenotypic characteristics are influenced by environmental changes such as temperature and nutrient composition [202, 203]. However, these changes can make it challenging to detect microalgae using such markers. Therefore, additional tests are necessary to account for the impact of various environmental conditions on microalgae cells, including limited nutrients, elevated CO₂, and prolonged darkness, which affect cell composition [204, 205]. To address this issue, some research has focused on identifying specific macromolecules for different species [206, 207]. Serive et al. [208] determined that photosynthetic pigments cannot be used as the sole method of identification since the expression of these pigments depends upon various physiological and environmental factors, such as light and nutrients, and hence must be confirmed using other taxonomic identification tools [208].

Despite the fact that chemotaxonomic markers are not reliable in identifying microalgae, quantifying their biochemical composition after identification from their environment is an essential next step. To achieve this, Fourier-transformed infra-red (FTIR) spectroscopy is a powerful tool for the rapid identification of microalgal lipids, carbohydrates, and proteins through biomass characterization via the identification of functional groups [209, 210] (Table 3). However, FTIR is limited for use on environmental samples containing unidentified species, as it can only identify species whose chemical composition is already present in its library [204]. For the identification of fatty acid from microalgae, gas chromatography-flame ionization detection (GC-FID), gas chromatography-mass spectroscopy (GC–MS), and nuclear magnetic resonance (NMR) have been commonly used (Table 3). NMR has also been utilized to identify carbohydrates and pigments from microalgae. Other tools, such as high-performance liquid chromatography (HPLC) and ultraviolet-visible (UV–vis) spectrophotometry, have been employed for pigment analysis, ultimately allowing for the classification of microalgae up to the phyla level based on their pigments [233].

Identification tool	Microalgae biochemical product	Method of identification	Refs.
FTIR	Lipids, Carbohydrates, Proteins	The vibrational energy of functional groups such as CH₂, OH, and C=O induced by the absorption of infrared radiation.	[211, 212, 213, 214, 215]
GC-FID	Fatty acid methyl esters (FAMEs)	GC connected to flame ionization detectors is based on the burning of esterified fatty acids using a hydrogen flame after separation using gas chromatography.	[216, 217]
GC–MS	Fatty acid methyl esters (FAMEs)	GC connected to a mass spectrometer detects FAMEs by measuring ions based on their mass-to-charge ratio.	[218, 219]
HPLC	Fatty acid methyl esters (FAMEs) and pigments	HPLC separates and quantifies components of liquid samples based on the retention time of the sample in the stationary phase of the column.	[220, 221, 222, 223, 224]
HPLC-DAD	Pigments	Combines HPLC and spectrometry, and it identifies compounds based on their absorbance in the ultraviolet-visible spectrum.	[208, 225, 226]
NMR	Fatty acids, amino acids, pigments and carbohydrates	Identification of carbon-hydrogen frameworks within organic molecules based on their absorption of electromagnetic radio waves	[227, 228, 229, 230]
UV–vis spectrometry	Pigments	Depends on the absorption of pigments within the near-UV (180–390 nm) or visible (390–780 nm) radiation spectrum.	[220, 231, 232]

Table 3.

Biochemical identification tools.

Abbreviations: Fourier-transform infrared spectroscopy (FTIR); Gas chromatography-Flame Ionization Detection (GC-FID); Gas chromatography-mass spectroscopy (GC-MS); High-performance liquid chromatography (HPLC); Nuclear magnetic resonance (NMR); HPLC-diode-array detector (HPLC-DAD); Ultraviolet-visible (UV–vis) spectrophotometry.

4.4 Conclusion

Identification of microalgae is important for determining their value. Microalgae are rich in nutrients such as proteins, vitamins, minerals, essential fatty acids, and different pigments, making them a valuable source for human food, animal feed, and various industrial applications. In addition, microalgae are fast-growing and can be easily cultivated up to large scales, which make them a cost-effective solution for environmental clean-up. Different species of microalgae are known to be effective in bioremediation. Hence, researchers are continuously investigating different targeted strategies using such species for cleaning up polluted environments. This can lead to a more sustainable and eco-friendly approach to environmental remediation. By identifying the specific species of microalgae, it is possible to determine the potential health and industrial benefits. Therefore, accurate identification of microalgae is crucial for assessing their nutritional value and potential applications in different industries; additionally, biochemical characterization of microalgae can help in the discovery of new bioactive compounds with potential in various applications.

Identification and isolation of microalgae from their natural habitats are crucial for their utilization and extraction of diverse by-products. Various factors come into play when isolating and maintaining microalgae, such as sample collection, post-collection processing, and identification methods. Direct morphological identification, which involves identifying different phenotypical features of microalgae under the microscope, is a golden method that requires highly qualified taxonomists. To further ease the identification of microalgae from their environmental samples, enrichment of microalgae using different nutrients and optimizing their growth enables the ease of identifying low-density microalgae through enriching them. Molecular level identification is another means of identification that can be used to confirm the morphological level identification of microalgae or can be used to directly identify microalgae without culturing or isolating it. Utilizing several identification methods provides a holistic approach to identifying microalgae from environmental samples. Thus, the need for continuous optimization of the different identification methods and to aid the continuous monitoring of the microalgae diversity in our environment.

Conflict of interest

The authors declare no conflict of interest.

Jana Krivec

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