Anaerobic Digestion of Microalgal–Bacterial Consortia Biomass: Challenges and Prospects for Circular Wastewater Treatment

Abstract

Increasing demands for improved energy efficiency and resource recovery in wastewater management have driven intensified research on microalgal–bacterial consortia (M-BC). This technological approach represents one of the most promising and continuously evolving concepts for integrated wastewater treatment and energy recovery. M-BC systems exploit complementary processes, including photosynthesis, oxygen production, nutrient uptake by microalgae, as well as heterotrophic degradation of organic contaminants and CO₂ generation by bacteria. Laboratory- and pilot-scale studies demonstrate that such integration can substantially reduce energy demand while significantly improving technological performance. Metabolic synergy, metabolite exchange, intercellular communication, and the specific aggregate architecture collectively determine the stability and high productivity of these consortia. Depending on operational conditions, M-BC may occur as suspended cultures, biofilm-based systems, or granules, which differ in process characteristics and biomass recovery potential. Available evidence indicates that M-BC biomass can serve as a highly efficient substrate for anaerobic digestion (AD). The methane production potential of M-BC reaches 350–365 mL CH₄/gVS, and following pretreatment may increase to 530–560 mL CH₄/gVS, exceeding typical ranges reported for conventional sewage sludge. These values were obtained under specific process conditions and depend on biomass characteristics, consortium structure, inoculum type, and operational parameters; therefore, their generalisation should be interpreted with caution. However, practical implementation remains constrained by process-related barriers directly affecting AD performance, including extracellular polymeric substance (EPS)-mediated hydrolysis limitation and nitrogen-associated inhibition linked to low C/N ratios and ammonia accumulation. Additional challenges include seasonal variability in biomass composition and incomplete understanding of M-BC behaviour under anaerobic conditions, particularly at scale. This paper provides a comprehensive and integrative analysis of the structure and biochemistry of M-BC biomass, their ecological mechanisms, technological configurations, and current knowledge regarding their susceptibility to anaerobic digestion. The review identifies the key biological, chemical, and process-related barriers and highlights research directions required for future integration of M-BC into circular wastewater treatment systems and energy-oriented biomass valorisation.

1. Introduction

The transformation of wastewater treatment systems has become one of the key environmental and technological challenges at both the European and global scales [1]. Wastewater treatment plants belong to particularly energy-intensive infrastructure, and in countries with well-developed water and wastewater management they account for 1–3% of the national electricity consumption [2]. In conventional activated sludge systems, intensive aeration of reactor tanks may consume 50–60% of the facility’s operational energy demand, making it one of the most cost-intensive components of wastewater treatment technologies [3]. In the context of increasing climate requirements and global strategies aimed at reducing greenhouse gas (GHG) emissions, there is a growing need to identify solutions that enable energy demand reduction, improved nutrient removal performance, and enhanced recovery of resources and energy from wastewater [4].

In recent years, increasing research interest has been focused on microalgal–bacterial consortia (M-BC). These systems integrate complementary processes, including photosynthesis, oxygen production, nutrient assimilation by microalgae, as well as heterotrophic degradation of organic contaminants and CO₂ generation by bacteria (Figure 1) [5].

This synergy enables a substantial reduction in the external oxygen demand supplied to the system. In high-rate algal pond (HRAP) systems, energy consumption may be as low as 0.02–0.06 kWh/m³, and up to 90% of the oxygen required for oxidation processes can be provided by microalgal photosynthesis [6]. Compared with conventional activated sludge systems, this may translate into a 15–30% reduction in overall energy demand [7]. In addition to energy-related benefits, M-BC also exhibit high wastewater treatment efficiency [8]. Depending on the process configuration, they can remove 70–95% of ammonium nitrogen, 60–90% of total nitrogen, and 60–85% of total phosphorus; in systems optimised for biomass settling, total phosphorus removal may even exceed 90% [9]. This high performance results from the metabolic complementarity between microalgae and bacteria, where bacteria mineralise organic matter into inorganic forms available to photoautotrophs, while microalgae assimilate ammonia and orthophosphates as nutrients [10]. These mechanisms, supported by chemical signalling, metabolite exchange, and interspecies transfer of elements, enhance the ecological stability of the system, improve resistance to fluctuations in pollutant loading, and promote floc formation and wastewater clarification [11]. Consequently, M-BC not only reduce costs associated with wastewater aeration but also provide improved functional robustness, higher treatment quality, and self-regulation capacity, making them one of the most promising directions for the development of circular wastewater management systems [12].

Despite substantial progress in understanding the structure and metabolic cooperation within M-BC, several critical knowledge gaps remain unresolved. In particular, the transition from predominantly aerobic consortium functioning to anaerobic degradation processes is still insufficiently explained at a mechanistic level. Existing studies often analyse ecological interactions and anaerobic digestion performance separately, limiting the ability to establish direct causal links between consortium structure, metabolite exchange dynamics, and methane production efficiency. Moreover, variability in experimental design and reporting standards restricts cross-study comparability and hinders the development of predictive frameworks. Addressing these gaps is essential for translating laboratory-scale observations into robust and scalable technological applications.

M-BC may occur in suspended, biofilm-based, or granular forms, which substantially affects their process performance [13]. Suspended systems achieve biomass productivity at levels of 40–210 gTS/m³·d (TS—total solids), whereas in modern closed photobioreactors these values may reach 200–600 gTS/m³·d [14]. Biofilm- or granule-based M-BC exhibit even higher biomass density and facilitate easier recovery from the medium [15]. The lipid content of M-BC biomass may range from 20 to 40%, and in the presence of quorum sensing signals it can increase by 80–100% relative to the control, making this biomass a valuable substrate for both biodiesel and biogas production [16]. At the same time, complex interactions among metabolites and chemical and trophic signals within consortia affect not only their stability and productivity but also the susceptibility of the biomass to downstream energy conversion pathways [17].

A key aspect of the technological potential of M-BC is their applicability in anaerobic digestion (AD). Although consortium biomass may be more recalcitrant to hydrolysis than microalgal monocultures or activated sludge bacteria due to the presence of extracellular polymeric substances (EPS) and aggregate-forming structures, it may exhibit very high methane potential [18]. Granular M-BC achieve biochemical methane potential (BMP) values of 350–365 mLCH₄/g VS, and following pretreatment these values may increase to 530–560 mLCH₄/g VS [19]. For comparison, reference BMP values for municipal sewage sludge typically range from 200 to 350 mL CH₄/g VS for waste activated sludge and 250–400 mL CH₄/g VS for stabilised sludge [20]. This indicates that under favourable conditions M-BC biomass may generate methane yields comparable to, or even higher than, conventional anaerobic substrates used in wastewater management [21]. To synthetically summarise the circular wastewater-to-bioenergy pathway and highlight the integration of M-BC cultivation with anaerobic digestion and resource recovery, the overall concept is schematically presented in Figure 2.

Despite this potential, numerous mechanisms governing the functioning of M-BC under anaerobic conditions remain insufficiently understood, and their integration with AD processes at full scale requires further in-depth research. The complex EPS structure and diffusion-related phenomena may reduce hydrolysis rates by as much as 30–50%, while seasonal variability and differences in biomass chemical composition affect process repeatability and stability [22]. M-BC biomass, particularly that with a high protein content, may lead to increased ammonia release, reaching levels that inhibit methanogenic activity [23]. An additional limitation involves secondary metabolites released by microalgae and bacteria, including polyphenols, antimetabolites, and compounds with antibacterial properties, whose effects on the microbiology of anaerobic fermentation remain poorly investigated [24]. At present, comprehensive studies integrating the structural and biochemical characterisation of M-BC biomass with its hydrolysis susceptibility, methanogenesis kinetics, and the effectiveness of different pretreatment methods, as well as assessments of long-term operational stability, are still lacking [25].

The aim of this study is to provide a comprehensive review analysing the performance of AD of M-BC biomass across different technological configurations. This work systematises available evidence regarding biomass composition, process-related properties, hydrolysis susceptibility, and BMP values. The review also identifies the most critical biological, chemical, and technological barriers and highlights research areas essential for future integration of M-BC into circular wastewater treatment systems.

2. Bibliometric Analysis and Dynamics of Research Interest

In recent years, M-BC have attracted increasing scientific attention, as reflected by analyses of major bibliographic databases and the growing number of research outputs. In this study, current trends in the field were assessed based on statistics obtained from structured searches using predefined keyword strings. The bibliometric analysis presented in Figure 3 was conducted using the following search queries: “microalgal–bacterial consortia”, “microalgal–bacterial consortia in wastewater treatment”, “microalgal–bacterial consortia for biofuels production”, and “microalgal–bacterial for biogas production”, applied individually within each database for the period 2015–2025. Searches were performed using the default database search engines; where applicable, Boolean operators and phrase searching (quotation marks) were used to maintain consistency of results. No restrictions regarding document type or publication language were imposed, and no manual exclusion criteria were applied; therefore, all records indexed by Google Scholar, Scopus, Scilit, and ScienceDirect were considered. The retrieved outputs reflect the indexing coverage, internal algorithms, and available filters of each database at the time of data collection. Considering the number of records retrieved from these databases, the topic remains highly relevant, and the increasing number of reports related to M-BC confirms sustained interest among researchers, research institutions, and companies worldwide.

It should be noted that the analysed databases differ in their indexing scope, document coverage, and search algorithms; therefore, the absolute number of records retrieved from each source should be interpreted with caution. Platforms such as Google Scholar typically include a broader range of document types, whereas Scopus and ScienceDirect apply more selective indexing criteria. Consequently, the presented results are intended to illustrate general research dynamics and thematic evolution rather than to provide directly comparable quantitative metrics across databases.

The highest number of database records was associated with the term “microalgal–bacterial consortia”, which increased from 197 in 2015 to 1050 in 2025 in Google Scholar, from 10 to 39 in Scopus, from 1 to 15 in Scilit, and from 150 to 1046 in ScienceDirect. Considering the temporal distribution of records across the analysed databases, the results indicate a clear upward trend in scientific activity related to M-BC during the period 2015–2025. Rather than reflecting isolated increases in publication numbers, the observed growth suggests a gradual expansion of research themes, particularly toward wastewater treatment applications, biofuel production, and anaerobic digestion pathways. The consistent rise in database entries across multiple platforms points to the maturation of this research area and the emergence of interdisciplinary collaborations linking environmental biotechnology, bioenergy, and microbial ecology. Such trends highlight not only the quantitative growth of publications but also the evolving thematic focus and diversification of research directions within the M-BC field.

3. Interactions as Mechanisms Underlying the Formation and Functioning of M-BC

During microalgae cultivation using wastewater, diverse and complex microbial communities are formed due to the presence of wastewater-borne microorganisms representing the phyla Proteobacteria, Bacteroidetes, Firmicutes, Synergistetes, and Actinobacteria [26]. Interactions between algae and bacteria encompass a broad spectrum of ecological relationships, ranging from symbiosis and mutualism to commensalism, competition, and parasitism [24,27]. Ecological interactions within M-BC include the exchange of nutrients and substrates (trophic relationships), regulatory and communication mechanisms such as signal transduction and cell-to-cell communication, as well as genetic processes associated with horizontal gene transfer [28].

3.1. Trophic Relationships

Trophic interactions represent the most common type of interaction in M-BC and constitute the basis of symbiotic and mutualistic relationships [29]. In symbiotic consortia, bidirectional exchange of primary and secondary metabolites occurs, in which partners supply each other with compounds essential for proper growth and the maintenance of metabolic activity. This phenomenon results from diverse metabolic strategies and distinct trophic requirements of algae and bacteria [30]. Algae release a fraction of photosynthetically produced organic matter as dissolved organic carbon (DOC), which serves as a substrate for heterotrophic bacteria [31].

Amin et al. [30] described a complex symbiotic nutrient exchange in a mixed diatom–bacterial culture, in which the diatom Pseudo-nitzschia multiseries supplied Sulfitobacter bacteria with organic carbon and organic sulfur molecules, while benefiting from ammonia produced by the bacteria. Other studies examined symbiotic relationships between Chlorella vulgaris and bacteria, where bacteria that utilised DOC were released during microalgal metabolism while simultaneously providing inorganic carbon compounds and low-molecular-weight organic molecules to C. vulgaris [32]. Mutualistic algae–bacteria interactions have also been reported in the presence of diverse metabolic products occurring in the environment, including carbohydrates, amino acids, nucleic acids, polysaccharides, polypeptides, proteins, enzymes, vitamins, mineral components, lipids, and toxic substances [24]. Some of these compounds can be directly assimilated by bacteria and incorporated into cellular biomass, or mineralised into simple inorganic forms that subsequently serve as nutrients for algae [33].

In studies on multispecies bacterial biofilms associated with the microalgae Chlorella vulgaris and Scenedesmus obliquus, bacteria were identified as the main consumers of lipids and fatty acids produced by microalgae [34]. Numerous studies have revealed mutualistic relationships between vitamin B12-dependent algae and heterotrophic bacteria [35,36,37,38]. Biodegradation of organic matter by bacteria generates ammonium compounds, nitrates, and phosphates, which may be utilised by microalgae as nitrogen and phosphorus sources [39]. A mutualistic relationship between nitrifying bacteria and algae involves bacterial oxidation of ammonia to nitrite and subsequently to nitrate, alongside photosynthetic oxygen production by microalgae, which provides the electron acceptor required for nitrification [40]. Kim et al. [41] demonstrated that the presence of bacteria facilitates nitrogen assimilation from wastewater by C. vulgaris. In turn, Suleiman et al. [42] showed that photoautotrophic growth of diatoms can be supported by ammonia produced by bacteria degrading methylamine. Furthermore, nitrogen-fixing bacteria such as Azotobacter vinelandii may supply algae with inorganic nitrogen forms [43].

Such interactions represent a promising strategy for large-scale microalgae cultivation, enabling reductions in costs associated with external nitrogen supplementation. According to Jiang et al. [44], trophic interactions in M-BC include the supply of inorganic phosphate to microalgae by bacteria such as Escherichia coli, Pseudomonas sp., and Bacillus sp. In addition, iron acquisition by algae is strongly conditioned by the presence of bacteria in M-BC. A mutualistic relationship described by Amin et al. [45] involved enhanced iron uptake by algae, intensification of the photochemical redox cycle, and the release of organic molecules required for bacterial growth. Interactions within M-BC also include mutualistic exchange of oxygen produced by algal cells and carbon dioxide as well as HCO₃⁻ generated during bacterial respiration [46].

Nevertheless, mutualistic relationships within M-BC may be altered by disturbances in nutrient balance (N:P ratio) and DOC availability [47]. Cao et al. [48] demonstrated that excessive DOC concentration in the culture medium intensifies competitive interactions, in which rapid bacterial biomass growth suppresses algal growth and productivity. Similarly, substances released by microorganisms may reciprocally inhibit each other’s development [49]. Certain bacterial metabolites, such as quinolone derivatives, chitinases, pyrroles, glucosidases, and derivatives of amino acids, peptides, and alkaloids, exhibit algicidal activity [50,51]. Myxobacter and Cytophaga were reported to release enzymes capable of dissolving cellulose present in algal cell walls, thereby destroying entire cells [52]. Hydroxamate-type siderophores produced by Stenotrophomonas maltophilia negatively affected cyanobacterial growth by limiting iron availability in the environment [53]. Conversely, microalgae belonging to the Prasinophyceae and Bacillariophyceae may secrete antibacterial compounds, including certain fatty acids, glycosides, chlorellin, terpenes, and chlorophyll a derivatives [54]. Interestingly, some algicidal compounds are synthesised from microalgal metabolites during the mutualistic phase of microalgae–bacteria interactions [55]. Therefore, antagonistic interactions between partners in M-BC play an important role in establishing and maintaining microalgae–bacteria symbiosis [56]. Trophic interactions in M-BC are summarised in

Table 1. Examples of trophic interactions in M-BC, including metabolite exchange, ecological effects, and biotechnological relevance.

Type of Interaction	Consortia/Species	Metabolites/Processes	Effect on Microalgae	Effect on Bacteria	Ecological/Biotechnological Relevance	Reference
Mutualism—C/N exchange	Pseudo-nitzschia multiseries—Sulfitobacter	DOC, S-organic compounds ↔ NH3	Improved N availability; enhanced growth	DOC utilisation; heterotrophic growth	Consortium stabilisation; increased productivity	[30]
Mutualism—organic/inorganic C exchange	C. vulgaris—heterotrophic bacteria	DOC ↔ CO2, HCO3−, LMW compounds	Faster growth	Utilisation of microalgal DOC	Improved cultivation efficiency	[32]
Organic matter degradation → remineralisation	Heterotrophic bacteria—microalgae	Hydrolysis/mineralisation → NH4+, NO3−, PO43−	Higher N and P availability	DOC utilisation	Sustained nutrient cycling	[33]
Consumption of microalgal lipids	Bacterial biofilm—Chlorella spp., Scenedesmus spp.	Lipids; fatty acids	Potential limitation of growth	Major carbon source	Biofilm dynamics; lipid turnover	[34]
Mutualism—vitamin B12 dependency	Vitamin B12-dependent microalgae—heterotrophic bacteria	Vitamin B12 ↔ DOC	Growth stimulation; cell division	Carbon source	Evolutionary basis of symbiosis	[35,36,37,38]
Mutualism—nitrification coupling	Nitrifying bacteria—microalgae	NH3 → NO2− → NO3− ↔ O2	Enhanced N assimilation	O2 supply from photosynthesis	Higher wastewater treatment efficiency	[40]
Mutualism—NH4+ supply from methylamine degradation	Methylotrophic bacteria—C. vulgaris	CH3NH2 → NH4+	Enhanced N assimilation	Energy and carbon source	Optimisation of wastewater-based cultivation	[42]
Mutualism—biological N2 fixation	Azotobacter vinelandii—microalgae	N2 → NH4+	Access to inorganic N	DOC utilisation	Reduced need for N fertilisation	[43]
Mutualism—P remineralisation	Escherichia coli, Pseudomonas spp., Bacillus spp.—microalgae	Mineralisation → PO43−	Improved P availability	Utilisation of algal metabolites	Enhanced phosphorus cycling	[44]
Mutualism—Fe acquisition	Pseudoalteromonas—phytoplankton	Siderophores ↔ DOC	Increased Fe uptake; intensified photosynthesis	Organic carbon supply	Increased ecosystem productivity	[45]
Mutualism—gas exchange	Microalgae—bacteria	O2 ↔ CO2, HCO3−	Enhanced photosynthesis	Improved aerobic metabolism	Consortium stabilisation	[46]
Antagonism—excess DOC	Heterotrophic bacteria—microalgae	Excessive nutrient consumption	Inhibited microalgal growth	Rapid bacterial proliferation	Disturbed M-BC balance	[48]
Antagonism—anti-microalgal bacterial metabolites	Myxobacter, Cytophaga, Stenotrophomonas—microalgae	Lytic enzymes; quinolones; siderophores	Cell lysis; growth inhibition	Access to algal cell constituents	Competition; biofilm structuring	[51,52,53]
Antagonism—antibacterial microalgal metabolites	Prasinophyceae; Bacillariophyceae—bacteria	Fatty acids; glycosides; terpenes	Reduced bacterial colonisation	Reduced growth	Microbiome shaping/selection	[54]
Late-stage antagonism	Various consortia	Secondary metabolites (algaecides)	Growth inhibition	Adaptive advantage	Regulation of symbiotic phases	[55,56]

.

Beyond listing individual examples, Table 1 reveals three dominant mechanistic clusters shaping trophic organisation in M-BC systems. First, reciprocal nutrient-exchange loops, particularly involving carbon, nitrogen, phosphorus, iron, and oxygen, constitute the core stabilising mechanism. Photosynthetically derived dissolved organic carbon (DOC) fuels heterotrophic bacterial metabolism, while bacterial mineralisation regenerates inorganic nutrients (NH₄⁺, NO³⁻, PO₄³⁻) and CO₂, thereby sustaining algal growth. This bidirectional flux establishes tightly coupled metabolic circuits that enhance internal nutrient recycling efficiency and reduce external dependency. Second, redox-coupled interactions link oxygenic photosynthesis and bacterial respiration, creating localised redox gradients that regulate electron flow and energy transfer within the consortium. Such coupling supports syntrophic balance, modulates oxidative stress, and facilitates dynamic adaptation to fluctuating environmental conditions. Third, regulatory antagonistic interactions mediated by secondary metabolites function as feedback control mechanisms. Although less frequently reported than mutualistic exchanges, these chemically mediated inhibitory effects prevent excessive proliferation of either partner and contribute to community structuring and resilience. Together, these clusters indicate that M-BC stability does not arise from unidirectional cooperation but from a dynamic equilibrium between metabolic facilitation and regulatory constraint. Trophic organisation in M-BC should therefore be interpreted as an integrated metabolic–regulatory network in which nutrient flux optimisation is counterbalanced by community-level control processes.

3.2. Signal Transduction and Cell-to-Cell Communication

In M-BC, complex interactions based on signal transduction also occur, in which both partners perceive and process environmental chemical cues [57]. This specific form of chemical communication relies on compounds released into the environment by consortium members, whose accumulation enables population density-dependent regulation of gene expression via dedicated receptors coupled to signal transduction pathways [24]. Bacteria are capable of producing and sensing the concentration of autoinducers, referred to as quorum sensing (QS) molecules, allowing them to estimate population density and adjust behaviours such as metabolite production or biofilm formation [58]. Algae may respond to bacterial QS by modifying the expression of their own genes or by releasing additional signalling compounds [46]. These interactions are bidirectional and are mediated by interconnected signalling pathways, enabling dynamic regulation of consortium functioning. Signal transduction plays a key role in stabilising algal-associated microbiomes by controlling adhesion, biofilm development, and nutrient exchange processes [59]. As a result, a functional system emerges in which chemical signals constitute the basis for coordination of metabolic and ecological processes of both partners.

Algae release primary and secondary metabolites, such as sugars, fatty acids, and phenolic compounds, which modulate the activity of bacterial receptors and influence the expression of genes associated with metabolism, cell motility, environmental adaptation, and surface colonisation [31,60]. In turn, bacteria produce signalling molecules, including QS autoinducers, which can be perceived by algal cells and induce changes in their physiology, such as regulation of growth rate, photosynthesis, lipid metabolism, or the synthesis of defensive metabolites [61]. In general, the chemical substances mediating communication in M-BC can be classified into three types: (1) lipid molecules that freely diffuse across cell membranes independently of cellular energy potential; (2) molecules exhibiting structural similarity between their 3D conformation and the functional domains of their regulators; and (3) bacterial signalling molecules N-acyl-homoserine lactones (AHLs), autoinducers (AI-2), autoinducing peptides (AIP), indole-3-acetic acid (IAA) and microalgal allelochemicals (e.g., flavonoids and ectocarpene) with analogous structures and functions [62,63]. Signal transduction-driven interactions have been widely documented in the literature, demonstrating modifications of physiological processes and ecological functions in M-BC, including spatial organisation within the community [64], bacterial motility and chemotaxis [65], cell lysis and defence mechanisms [66], acquisition of nutrients (nitrogen, phosphorus, and iron) [45], biofilm formation [67], development of ecological niches [68], adaptation to extreme environments [69], production of virulence factors and reproductive behaviours [70].

By analysing algal metabolite emissions, Dehwah et al. [71] reported that some algae produced molecular organic matter composed of acidic polysaccharides and high-molecular-weight proteins, occurring mainly in the biopolymer fraction of natural organic matter and promoting coexistence of algae and heterotrophic bacteria. Extracellular polysaccharides (EPS) stabilise the microbial environment, thereby facilitating the formation of balanced microstructures and biofilms, which supports bacterial communication and maintains high concentrations of autoinducers in the vicinity of cells [72]. Phytohormones and their derivatives, such as IAA, may stimulate bacterial growth and cell division, regulate metabolism, and thereby influence biofilm formation, motility, and environmental adaptation [73]. Phenolic and lactone compounds released by algae may affect bacterial histidine sensors and two-component regulatory pathways, altering bacterial perception of environmental conditions [74]. Moreover, algae synthesise compounds structurally similar to bacterial AHL autoinducers, thereby activating bacterial QS systems and regulating, for instance, biofilm formation or metabolism [75]. Substances released by algae often also inhibit bacterial survival and growth. This constitutes a response of microalgae to environmental pressure, such as bacterial competition. For example, secondary metabolites of red algae Laurencia spp., including elatol and isoobtusol, exhibited broad-spectrum antibacterial activity [76]. Microalgae were reported to produce AHL-inactivating enzymes as a defence against harmful bacteria, such as lactonase [77], acylase [78], and oxidase [79]. Chlorellin, an algal metabolite, showed bactericidal activity against Staphylococcus aureus, Bacillus subtilis, Escherichia coli, and Pseudomonas aeruginosa [80]. Lumichrome (a riboflavin derivative) produced by Chlamydomonas reinhardtii (Chlorophyta) acted as a signal mimic by occupying LasR binding sites as an AHL-like compound in Pseudomonas aeruginosa [81].

In turn, bacteria may release micronutrient-related metabolites such as phospholipids, vitamin B12, flavonoids, and phytohormones (IAA, abscisic acid, cytokinins, ethylene, gibberellins), as well as thiamine derivatives and siderophores, which stimulate algal metabolism [29,62]. In algal cells, IAA functions as a signalling molecule influencing interactions with bacteria, whereas tryptophan acts primarily as an IAA precursor [82]. Bacterial strains associated with Scenedesmus sp. promoted algal growth through IAA production, while simultaneously releasing signalling substances that induced IAA synthesis in bacteria, which was amplified in tryptophan-rich environments [82]. Similar observations were reported by Peng et al. [83], who indicated that the bacterium Azospirillum brasilense promoted the growth of Chlorella sorokiniana and Auxenochlorella protothecoides through IAA production. Amin et al. [30] analysed a bacterial–diatom consortium and found that Sulfitobacter intensified diatom cell division through secretion of bacterially synthesised IAA derived from both diatom-released and endogenous tryptophan. Yao et al. [84] described an interaction between heterotrophic bacteria and algae, in which bacteria supplied vitamin B and produced iron-binding siderophores that promoted algal growth, while algae provided bacteria with carbon compounds. Bacterial genera producing high concentrations of IAA, such as Rhizobium and Agrobacterium, increased microalgal biomass productivity by 65–80% compared with the control sample [85]. The production of vitamins and vitamin precursors by bacteria represents one of the most frequent and best-characterised algae–bacteria interactions [86]. Durham et al. [87], in a co-culture of Ruegeria pomeroyi with the diatom Thalassiosira pseudonana, demonstrated that bacteria supplied algae with vitamin B12 in exchange for an organic sulfur compound.

Bacterial autoinducers can affect algal physiology, gene expression, and population behaviour [88]. Algae are capable of perceiving QS chemical mediators, including AHLs, AI-2, and AIP released by bacteria, and interpret this as a cue indicating bacterial presence, thereby modulating their physiological responses—for example by altering the composition of secreted metabolites, growth rate, photosynthesis, or the production of their own oxylipin signals [62]. For instance, in the study by Yang et al. [89], biofilm formation by benthic diatoms Cylindrotheca sp. was induced by exposure to bacterially produced AHLs, which in turn stimulated EPS secretion and increased chlorophyll-a content, ultimately enhancing diatom biomass. Similar relationships were observed by Zhang et al. [90], where higher AHL production contributed to increased EPS production and biofilm formation in M-BC. Zhou et al. [91] reported that Chlorophyta sp. cells remained suspended in the absence of AHLs, whereas they self-aggregated into bioflocs with a diameter of 200 μm and exhibited enhanced settling capacity when AHLs extracted from activated sludge bacteria were added to the medium. The addition of QS molecules extracted from anaerobic sludge to cultures of Chlorella sorokiniana increased algal productivity and lipid content by 2.25 and 1.8 times, respectively [92]. In other studies, lipid productivity increased by 84% as a result of the stimulatory effect of QS molecules on acetyl-CoA enzyme synthesis, a key compound in fatty acid biosynthesis [93]. According to Ji et al. [94], the production of QS mediators by bacteria supported the formation of a stable C. vulgaris–Bacillus licheniformis consortium, in which increased polysaccharide secretion, elevated chlorophyll-a concentration, and enhanced algal biomass production were observed, leading to effective removal of organic contaminants as well as N and P from wastewater. Despite extensive research (

Table 2. Cell-to-cell communication and signal transduction in M-BC.

Signal Type/Mechanism	Consortia/Species	Signalling Molecules/Metabolites	Effect on Microalgae	Effect on Bacteria	Ecological/Biotechnological Relevance	Reference
Quorum sensing (QS)—AHL, AI-2, AIP	Heterotrophic bacteria → microalgae	AHLs, AI-2, AIP peptides	Regulation of growth, photosynthesis, and lipid metabolism; oxylipin production; cell aggregation	Regulation of QS gene expression; biofilm formation; environmental adaptation	Consortium stabilisation; biofilm regulation; coordination of metabolic functions	[46,58]
Microalgal signalling → bacteria	Various microalgae → bacteria	Sugars, fatty acids, phenols, flavonoids, ectocarpene	Modulation of bacterial receptors; altered gene expression	Regulation of motility, biofilm formation, and metabolism	Microbiome maintenance; bacterial community shaping	[31]
Phytohormones and derivatives (IAA, tryptophan)	Chlorella, Auxenochlorella ↔ Azospirillum, Scenedesmus, Sulfitobacter	IAA, tryptophan	Increased lipid and EPS production; stress compensation; higher biomass yield	Growth stimulation; utilisation of algal-derived tryptophan	Strengthened mutualistic interactions; enhanced productivity	[30,82,83]
Mimicry signals (AHL imitation)	Chlamydomonas → Pseudomonas	Lumichrome, AHL analogues	Activation/inhibition of bacterial QS	Disturbed QS perception	Biofilm regulation; microalgal defence	[81]
QS inhibitors produced by microalgae	Various microalgae	Lactonase, acylase, oxidase, chlorellin	Defence against pathogens; antagonism	QS deactivation; reduced virulence	Microbiome control; reduced infection pressure	[77,78,80]
Bacterial metabolites stimulating microalgae	Ruegeria, Azospirillum, Rhizobium → microalgae	Vitamin B12, siderophores, phytohormones	Stimulated growth and photosynthesis; enhanced Fe uptake	Access to DOC	Higher consortium productivity; improved wastewater treatment efficiency	[87]

), algae–bacteria interactions remain insufficiently defined, and investigation of QS mechanisms in microalgae–bacterial consortia is crucial for developing appropriate strategies for full-scale systems.

Table 2 synthesises structural and functional attributes of M-BC systems across cultivation configurations, revealing recurring system-level principles. Three interdependent domains can be distinguished: structural architecture, metabolic complementarity, and environmental modulation. Structural configuration, whether suspended cultures, biofilms, or granules, governs diffusion pathways, substrate accessibility, and spatial segregation of metabolic niches. Aggregated architectures promote close cell-to-cell proximity, facilitating metabolite exchange and quorum sensing, while simultaneously influencing mass-transfer resistance and local microenvironment formation. Metabolic complementarity reflects division of functional roles between phototrophic and heterotrophic partners, enabling parallel processing of organic and inorganic substrates. This division enhances overall resource-use efficiency and buffers environmental fluctuations through metabolic redundancy. Environmental and operational drivers (light intensity, nutrient loading, hydraulic regime) modulate the expression of these traits, altering biomass composition, EPS production, and consortium maturity. Variability observed across studies therefore reflects context-dependent modulation of shared mechanistic foundations rather than fundamentally distinct system types. Accordingly, M-BC functionality should be regarded as an emergent property arising from the interplay between spatial organisation, metabolic flux partitioning, and environmental control parameters.

3.3. Gene Transfer

Another important interaction occurring in M-BC is gene transfer, an evolutionary process in which genes are horizontally exchanged between neighbouring microorganisms. Most functionally relevant genes are transferred laterally from bacteria to eukaryotes, reflecting the vast metabolic diversity of bacteria [95]. This contributes to increased functional diversity of microalgae and, consequently, enhances their capacity to survive under unfavourable environmental conditions [46]. For instance, in diatoms, genes encoding enzymes of the ornithine–urea cycle were most likely acquired from bacteria, facilitating their functioning under nitrogen-limited conditions [96]. The red alga Galdieria sulphuraria is able to persist in hot, toxic, and acidic environments due to metabolic capacities for heterotrophic or photoautotrophic growth acquired through HGT from at least 75 genes originating from diverse bacteria and archaea [97]. The literature also indicates that gene transfer from microalgae to bacteria may occur [98]. Nevertheless, such events are considerably less frequent, as bacteria are metabolically more diverse than microalgae and generally do not require additional sets of functionally linked genes derived from microalgae [58,95].

Horizontal gene transfer (HGT) plays a significant role in shaping M-BC populations in wastewater environments, primarily influencing adaptive capacity, metabolic plasticity, and the long-term functional stability of microorganisms. In the context of M-BC, HGT predominantly affects bacterial populations, indirectly modifying their interactions with microalgae. This was demonstrated by Song et al. [99], who showed that HGT within macroalgal biofilms was dominated by gene exchange among bacteria belonging to the same class or order and frequently involved genes related to nutrient transport, sugar and phlorotannin degradation, as well as stress-response pathways. Consequently, genes optimising metabolic pathways may spread throughout the population, enhancing metabolic stability, resilience to environmental fluctuations, and the dynamics of substrate flux within the consortium through the reinforcement or attenuation of trophic mutualism.

Wastewater environments are characterised by elevated concentrations of selective agents (e.g., antibiotics, heavy metals, and toxic compounds), which impose strong selective pressure favouring the maintenance and dissemination of adaptive genes via HGT. As a result, rapid functional restructuring of microbial communities may occur, alongside the spread of traits that enhance survival and tolerance to environmental stress [100,101]. Within M-BC biofilm structures, close cell-to-cell contact promotes conjugation and transformation processes, while the presence of an EPS matrix increases DNA retention in the surrounding environment, further facilitating gene transfer. These mechanisms are well documented in environmental biofilms and activated sludge systems, highlighting their importance for microbiome adaptation through the expansion of metabolic capabilities and stress-resistance traits within microbial communities [102].

In microalgae–bacteria consortia applied in wastewater treatment, structural and functional stability results from the balance between metabolic, regulatory, and organisational interactions within the microbial community. These mechanisms operate across multiple levels and determine both short-term process stability and the long-term adaptive capacity of microorganisms forming M-BC.

Trophic interactions based on metabolite exchange constitute the primary foundation of M-BC stability. Metabolic complementarity reduces direct competition for nutrients and promotes the development of synergistic and mutualistic relationships. Analyses in the literature indicate that trophic relationships represent the dominant stabilising mechanism in M-BC systems used for wastewater treatment and biomass production [21,54,103]. In contrast, while trophic interactions provide the energetic basis of the consortium, signal transduction and cell-to-cell communication primarily coordinate physiological activity and gene expression patterns. Infochemical compounds regulate and reinforce trophic interactions by controlling microbial succession and functional stability, particularly under fluctuating wastewater loading conditions [46,104]. A structural and protective component contributing to M-BC stability is the extracellular polymeric substance (EPS) matrix. EPS production enhances cell aggregation, granule formation, and biomass retention. These structures increase resistance to variations in pH, light intensity, and organic loading while facilitating efficient metabolite exchange within microniches [105]. Studies on algal–bacterial granulation demonstrate that biofilm stability correlates with improved nitrogen and phosphorus removal efficiency [106]. However, it should be emphasised that the formation of stable algal–bacterial structures is secondary to previously established metabolic and signalling interactions. The adaptive potential of the consortium is additionally influenced by horizontal gene transfer, which enhances functional plasticity under variable wastewater conditions by supporting nitrogen metabolism pathways and increasing tolerance to heavy metals and oxidative stress [102]. Nevertheless, available evidence suggests that gene transfer plays a greater role at the evolutionary scale than in short-term stabilisation of consortium structure.

A major limitation of current research is the scarcity of comparative analyses that clearly define the relative importance of individual interaction mechanisms across reactor configurations and wastewater compositions. Many conclusions are derived from model or short-term studies, which restricts broader generalisation. Despite these limitations, most authors agree that metabolic complementarity and infochemical regulation constitute the central foundation of stability and functionality in algal–bacterial consortia used for wastewater treatment.

4. Characteristics of Major M-BC Types

Depending on environmental parameters such as nutrient availability, light intensity, and technological/operational conditions, M-BC may develop distinct morphological forms. Under favourable conditions, characterised by high nutrient availability and adequate illumination, the microorganisms typically remain in suspended form, which promotes efficient gas exchange and light accessibility [103]. Under nutrient- or light-limited conditions, the community may shift towards attached (sessile) forms, facilitating more effective resource utilisation [107]. In contrast, under specific process conditions (e.g., appropriate mixing and hydrodynamic regime), the microorganisms may develop a granular structure, which enhances system stability and improves the efficiency of biotechnological processes such as water treatment or biomass production [6]. Figure 4 presents a schematic comparison of the three main types of M-BC—suspended, attached (biofilm-based) and granular systems—highlighting their characteristic microarchitecture.

In summary, the differences between suspended, biofilm-based, and granular configurations in M-BC systems arise primarily from the spatial organisation of biomass and the structure and function of the EPS matrix, which determine substrate transport dynamics and the photophysiological conditions experienced by microorganisms.

In suspended systems, algal and bacterial cells function as relatively independent units surrounded by a thin diffusive boundary layer, while the transport of substrates and gases is largely governed by mixing and convection. Diffusion limitations remain minimal, promoting rapid kinetic responses and high photosynthetic performance at low to moderate biomass density. However, the absence of stable redox and substrate gradients makes these systems more sensitive to fluctuations in pollutant loading and structurally less stable. Metabolic heterogeneity within the consortium is limited, and EPS mainly performs protective and signalling roles rather than structural functions, typically occurring in the form of soluble microbial products (SMPs).

In contrast, within biofilms, cells are immobilised in a three-dimensional EPS matrix, resulting in more controlled and slower transport of substrates, light, and gases through the boundary layer and EPS structure compared with suspended cultures, but with enhanced stability. Distinct gradients of oxygen, nitrogen compounds, and light intensity develop, driving spatial differentiation of metabolic functions. Microorganisms located in surface layers maintain high photosynthetic activity, whereas populations inhabiting deeper zones operate under light and/or oxygen limitation, shifting toward mixotrophic or anoxic metabolism. In this configuration, the EPS matrix fulfils structural and regulatory roles by controlling diffusion processes, increasing biomass retention, stabilising microenvironments, and promoting close cell-to-cell interactions that favour stable syntrophic relationships and horizontal gene transfer. The matrix also protects microorganisms from environmental stress.

Granules represent the most complex level of spatial organisation in M-BC systems. These self-supporting aggregates exhibit a layered architecture in which mass transfer follows a radial and strongly gradient-driven pattern. The outer layer is typically oxygen-rich and photosynthetically active, whereas the core may remain anoxic or anaerobic, enabling the coexistence of aerobic and anaerobic processes within a single aggregate. Although diffusion limitations are greatest in granular systems, they promote intense and stable syntrophic organisation and high biomass retention. The EPS matrix serves as the principal structural element ensuring mechanical integrity, while also providing protective and regulatory functions through the formation of redox gradients that govern functional partitioning of microbial populations.

Consequently, in suspended M-BC systems the overall wastewater treatment performance is predominantly kinetically controlled, as metabolic reaction rates are not strongly constrained by mass transport. In contrast, biofilm and granular configurations operate as diffusion-controlled systems, where transport limitations drive spatial heterogeneity of microbial metabolism. With increasing biomass aggregation, microenvironmental heterogeneity and the importance of EPS increase, leading to greater structural stability at the cost of stronger substrate transport limitations.

4.1. Suspended-Grow M-BC Systems

In suspended M-BC systems, microbial cells occur either as single units or as loosely aggregated structures. Flocs formed by algae and bacteria are stabilised by soluble extracellular polymeric substances (EPS), mainly in the form of soluble microbial products (SMP), which participate in the regulation of biological processes but do not create the compact, spatially organised matrix typical of biofilms. Consequently, EPS primarily fulfils protective and communication-related functions in these systems [108]. Consortium structure and microbial succession are regulated by light availability, nutrient loading, oxygen dynamics, and interspecies interactions [109,110,111]. These factors determine carbon partitioning between autotrophic and heterotrophic pathways, thereby shaping biomass composition [112,113,114].

In M-BC, mass transfer between the cell surface and the liquid phase is largely governed by mixing intensity and convective transport, which reduces the importance of diffusion resistance. At low to moderate biomass concentrations, this enables high photosynthetic efficiency and rapid kinetic responses to changes in substrate availability. However, the absence of stable spatial stratification prevents the formation of persistent redox microgradients or metabolically differentiated zones. As a result, the consortium exhibits limited functional heterogeneity, and dominant metabolic processes occur relatively uniformly throughout the reactor volume. Such organisation increases system sensitivity to fluctuations in pollutant loading and environmental variability [115,116], as the lack of spatial differentiation reduces buffering capacity. From the perspective of anaerobic digestion (AD), this structural simplicity enhances biomass accessibility to anaerobic microorganisms. The absence of a compact biofilm structure, the low content of structural EPS in the form of SMP, and weaker metabolic compartmentalization may lead to lower substrate stability during hydrolysis but potentially greater susceptibility to methanogenesis.

In wastewater treatment technologies, suspended algal–bacterial consortia are cultivated in both open and closed photobioreactor systems. In open reactors such as high-rate algal ponds (HRAPs), shallow channel configurations promote strong light–dark gradients and tight coupling between photosynthetic oxygen production and bacterial COD removal [115,116]. Under low photosynthetic activity, nitrogen removal relies mainly on nitrifying–denitrifying bacteria, whereas algae-dominated phases enhance direct assimilation of nitrogen and phosphorus compounds [117]. Operational conditions in HRAPs therefore shift the balance between respiratory and photosynthetic metabolism, influencing EPS production, floc density, and sedimentation processes, which are critical for biomass harvesting and methane potential.

HRAP operation is energy-efficient due to the absence of intensive aeration; however, biomass productivity and stability are constrained by seasonal light availability, geographic latitude, temperature fluctuations, CO₂ transfer limitations, and contamination by competing organisms [118,119,120,121,122,123,124,125,126,127]. These factors alter species composition and may favour filamentous or poorly settling taxa [127], thereby affecting harvesting efficiency and organic matter availability during anaerobic biodegradation of M-BC biomass. Average biomass productivity ranges from 4 to 21 g/m²·d [125], although short-term values up to 50 g/m²·d have been reported [126].

A major limitation of HRAP systems is their large land requirement, along with challenges related to biomass separation [124,128]. HRAP biomass typically consists of microalgae and mixed bacterial populations forming spontaneous flocs of 20–200 μm that only partially sediment without chemical additives [129]. Strategies such as bioflocculation, biomass recycling, or physicochemical separation improve harvesting efficiency but may also drive community succession, thereby modifying the biochemical composition of the consortium and its subsequent anaerobic biodegradability [130,131]. Gutierrez et al. [130] demonstrated that 10% recirculation increased the proportion of settling Stigeoclonium sp. to 16.8% and diatoms to 7.3%, while reducing the dominance of Chlorella sp. from 97.6% to 88.1%. Additional separation techniques include dissolved air flotation (DAF), chemical flocculation using inorganic or organic coagulants, and electro-separation methods [131].

Closed photobioreactors (PBRs), in contrast, allow precise control of light, gas exchange, temperature, and mixing, resulting in higher biomass density and more stable consortia. A higher surface-to-volume ratio improves light utilisation; however, light attenuation at elevated biomass concentrations creates environmental gradients [132] that influence metabolic stratification and the accumulation of carbohydrates and lipids within microbial cells, directly affecting methane productivity from M-BC biomass.

Numerous PBR configurations have been developed, including column, air-lift, flat-plate, stirred tank, tubular, conical, toroidal, and algal-belt systems [133]. Large-scale cultivation commonly employs horizontal tubular reactors, vertical bubble-column reactors, and flat-plate or panel photobioreactors [132]. The high surface-to-volume ratio in PBRs significantly enhances biomass productivity compared with open systems, typically ranging from 20 to 60 g/m²·d depending on reactor type and operational conditions [134]. For example, tubular PBRs have achieved biomass productivities of 13–47.7 g/m²·d, whereas flat-plate PBRs have reported values of 10.2–22.8 g/m²·d [135]. PBR performance depends on efficient light distribution, gas–liquid mass transfer, and hydrodynamic regime [136]. Uneven light distribution results from absorption and scattering within the culture and depends on wavelength, biomass concentration, reactor geometry, and light penetration depth [117]. Light intensity decreases exponentially with distance from the illuminated surface, and at biomass densities above 10 g/L, light penetration is limited to only a few millimetres, reducing growth rates in deeper reactor zones [137]. Excessive biomass density restricts photon penetration, suppressing growth in internal regions and potentially increasing endogenous respiration. Consequently, reactor configuration indirectly shapes the biochemical composition and structural properties of M-BC biomass.

Mixing in PBRs is typically achieved through aeration with compressed air or CO₂, where aeration intensity influences turbulence and biomass growth [117]. Column reactors provide efficient gas–liquid transfer, although their diameter generally should not exceed 0.2 m and height 4 m due to design constraints and shading effects [133]. Various column configurations exist, including bubble column PBR, airlift draft-tube PBR [138], split-airlift PBR [139], and external-loop PBR [140]. In addition to light distribution and mixing, biomass productivity and pollutant removal efficiency are influenced by temperature, pH, CO₂ concentration, nutrient availability, the presence of toxins or inhibitors, and the species composition of the M-BC consortium [141].

Compared with open systems, controlled cultivation of M-BC in closed reactors enables targeted modulation of biomass quality, including metabolite accumulation, which may enhance anaerobic digestion performance. Therefore, reactor configuration (open versus closed) should be interpreted not only in terms of productivity but primarily as a factor shaping microbial interactions, EPS architecture, and the taxonomic and biochemical composition of M-BC, all of which ultimately determine harvesting efficiency and suitability for anaerobic digestion.

4.2. Attached-Growth M-BC Systems

Biofilm-based microalgal biomass production represents an important alternative to suspended cultures, primarily due to the distinct spatial organisation of the consortium and the resulting metabolic consequences [142]. In attached consortia, algal and bacterial cells form an integrated, heterogeneous structure maintained by an EPS matrix with a three-dimensional protein–polysaccharide architecture [143]. This matrix ensures mechanical stability of the M-BC structure, enhances biomass retention, and governs the diffusion of substrates and metabolites. The spatial distribution of microorganisms is not random but is shaped by gradients of light, oxygen, CO₂, and nutrients. Algae, as phototrophic organisms with larger and more rigid cells, act as a structural scaffold, whereas bacteria colonise both algal surfaces and intercellular spaces, forming microcolonies embedded within the EPS matrix [144]. Owing to the light requirement of algae, bacteria typically develop beneath the algal layer. In attached consortia, algal activity is essential for biofilm persistence because bacteria depend on oxygen produced by algal photosynthesis [143].

A defining feature of algal–bacterial biofilms is pronounced functional stratification [145]. Photosynthetic processes and oxygen production dominate in surface layers, whereas deeper regions develop microgradients of O₂, CO₂, pH, and mineral nutrients, leading to the formation of aerobic, anoxic, and anaerobic niches [146]. This organisation supports the concurrent occurrence of heterotrophic processes, nitrification, and denitrification, and under fluctuating illumination also the activity of phosphorus-accumulating bacteria [147,148]. The biofilm thus becomes a multi-reactor system in which photosynthesis, respiration, and nutrient transformations proceed in parallel within distinct microzones. This spatial architecture directly affects the biochemical composition of the biomass (e.g., polysaccharides, lipids, and EPS content) and its susceptibility to hydrolysis during anaerobic digestion.

A key advantage of algal–bacterial biofilms is the ease of biomass harvesting, as cells attached to a carrier can be mechanically removed without the need for intensive flocculation or sedimentation [145,149]. High areal biomass densities in biofilms (5.3–12.2 g/m²·d) reduce the required cultivation volume and can lower dewatering costs and energy demand [150,151]. From the perspective of subsequent anaerobic biodegradation of M-BC, it is important to recognise that increased EPS content and the compact biofilm structure may both stabilise the substrate and limit organic matter accessibility for hydrolytic microorganisms. Therefore, the technological advantages of biofilm cultivation do not necessarily translate into higher methane yields and require qualitative assessment, not solely quantification of biomass production.

M-BC biofilm cultivation systems differ in the mode of biofilm contact with the growth medium and in the type of carriers employed [145,152], which affects mass transfer intensity. In submerged systems, substrate transport occurs across a liquid boundary layer, promoting the formation of stable gradients and increasing metabolic heterogeneity [143,152]. In perfused systems, nutrient supply is more uniform, which may enhance productivity but can attenuate functional stratification [153,154,155]. The use of carriers with different porosities and multilayer structures influences gas and metabolite diffusion and thereby the balance between aerobic and anaerobic processes within the biofilm [156].

In practice, biofilm-based M-BC cultivation is implemented in Algal Turf Scrubber (ATS) systems, membrane reactors, and packed-bed reactors [157,158,159]. In ATS reactors, flow of the cultivation medium over an inclined carrier surface promotes the growth of benthic organisms and filamentous forms, facilitating mechanical biomass harvesting [159]. Variability in hydraulic and light conditions in these systems induces dynamic shifts in consortium structure [160], which may alter the accumulation of storage compounds in microbial cells and influence the methane potential of the biomass. Evidence from the literature indicates that ATS reactors have been successfully applied to the treatment of manure, agricultural drainage, and municipal wastewater [124,161], and that the removal efficiency of organic and nutrient pollutants depends less on reactor construction per se than on the balance between photosynthesis and respiration and the stability of biofilm microgradients [160].

Membrane reactors enable physical retention of biomass within a membrane module. Depending on the membrane type, it is possible to control hydrodynamic conditions, regulate substrate concentrations, and selectively remove metabolic products, which may support high consortium metabolic activity, promote EPS accumulation, and increase biofilm compaction [162]. According to Zahmatkesh et al. [163], daily algal biomass production in algae-based membrane bioreactors (AMBR) ranges from 50 to 100 mg/L, while nitrogen and phosphorus removal efficiencies reach 30–97% and 46–93%, respectively. However, membrane fouling and the need for periodic cleaning can temporarily disrupt the activity of denitrifying and phosphorus-accumulating bacteria, thereby affecting overall system stability [164,165].

In packed-bed reactors, the cultivation medium flows through a fixed bed, most often composed of ceramic granules, sand, or synthetic nonwoven materials that serve as carriers for biofilm growth. These systems provide a large surface area and intensive mass exchange between the biofilm and the medium, supporting high biological activity and efficient pollutant removal [166,167]. Packed beds can promote pronounced spatial partitioning of metabolic processes and increased M-BC heterogeneity. They are used both for wastewater treatment—particularly for the removal of nitrogen, phosphorus, and heavy metals—and for algal biomass production [168]. Reported daily biomass productivity is 54 ± 18 mg/L [169,170]. From an AD perspective, it is important to note that concentrated biomass strongly bound to carriers may require pretreatment or disintegration to increase organic matter accessibility.

4.3. Granular M-BC Systems

Granular M-BC are structured aggregates in which microalgae and bacteria operate in close metabolic interdependence. The granular architecture stabilises the biofilm, facilitates biomass separation from the cultivation medium, and enhances resilience to fluctuating operational conditions, thereby supporting long-term process stability and efficiency in biotechnological wastewater treatment applications [107,171]. Such organisation also promotes metabolic balance between autotrophic and heterotrophic members of the consortium [107]. Bioflocculation of these structures occurs naturally through adhesion of microalgae to bacterial flocs followed by bacterial attachment to algal cells, leading to progressive consortium growth until a dynamic equilibrium is achieved [107].

Within granular structures, EPS play a central role in cell adhesion, aggregate stabilisation, and microbial protection, while simultaneously influencing physicochemical surface properties such as hydrophobicity and charge, which determine granulation efficiency [58,94]. The effectiveness of granule formation and stability depends on species composition, algal-to-bacterial ratios, and operational parameters including light intensity, aeration, hydraulic retention time, and organic loading rate [172]. Species composition of microalgae is particularly critical. For example, Chlorella spp. enhance granule stability through photosynthetic oxygen production, supporting bacterial metabolism and EPS secretion, whereas excessive proliferation of filamentous algae (e.g., Stigeoclonium) or cyanobacteria may destabilise aggregates and promote toxin release [173,174]. Nitrifying bacteria also contribute to granule formation and structural integrity by promoting the development of highly settleable aggregates [175]. Key taxa frequently identified within granular consortia include Pseudomonas, Bacillus, and Nitrosomonas, which support granule architecture and improve wastewater treatment performance [176].

Gradients of oxygen, CO₂, and nutrients within the granule enable simultaneous aerobic and denitrifying processes; however, excessive biomass density or algal dominance may restrict substrate availability for bacteria, disrupting metabolic balance in M-BC systems [177,178,179]. Functional stratification within granules further promotes nitrification processes. Algae can stabilise bacterial populations by limiting light penetration into deeper layers, thereby protecting ammonia- and nitrite-oxidising bacteria from photoinhibition of key electron transport enzymes [180]. Conversely, ammonia-oxidising bacteria may be inhibited because algae located in the outer layers of the biofilm can competitively assimilate ammonium ions, reducing substrate availability for microorganisms inhabiting inner zones [181]. Leong et al. [182] demonstrated that nitrification in symbiotic systems facilitates assimilation of oxidised nitrogen species (NO₂⁻ and NO₃⁻) by Chlorella vulgaris.

Granular M-BC systems exhibit resilience to environmental fluctuations but remain sensitive to sudden changes in organic loading, photoperiod variation, and hydraulic retention time (HRT) instability [182,183]. Ye et al. [183] reported that elevated microalgal concentrations (>4.60 mg Chl/L) inhibited the growth of certain bacterial groups (e.g., Bacteroidetes and Actinobacteria), leading to process destabilisation and granule disintegration. Structural instability may result in EPS degradation, loss of aggregate integrity, and reduced sedimentation efficiency. When considering large-scale cultivation, additional challenges arise, including self-shading, limited light penetration into the granule core, and increased hydrodynamic stress, all of which may disrupt microenvironmental stability and affect nitrifying and denitrifying bacterial activity as well as algal performance. Despite these limitations, granular aggregates synthesise a wide range of valuable products from both energy (methane, hydrogen) and biotechnological (lipids, EPS, phototrophic pigments, carotenoids, amino acids) perspectives, highlighting their multifunctional potential.

Granular M-BC can be cultivated in various reactor configurations, including sequencing batch reactors (SBR) and continuous flow reactors (CFR), which allow control of aeration, mixing, and light availability [184,185]. In SBR systems, cyclic operation promotes selection of highly settleable biomass, enables spatial control of aerobic and anoxic zones, and enhances granule structural stability [173,183]. Tang et al. [186] demonstrated that reducing aeration intensity promoted algal growth by decreasing hydrodynamic shear, thereby strengthening interspecies interactions within the consortium. Light intensity affects both nutrient removal efficiency and microalgal biomass productivity [187]; below the light saturation point, algal growth increases proportionally with irradiance [188]. Photoperiod management is particularly important, as light limitation reduces nitrate and phosphate removal rates while simultaneously supporting bacterial activity under anoxic conditions [184]. Control of microbial composition through inoculum selection and retention time adjustment enables targeted optimisation of consortium structure for specific technological objectives, such as nutrient removal or biomass production. Excessive organic loading may, however, lead to aggregate disintegration [189]. Nevertheless, SBR-based cultivation offers advantages including high biomass concentrations, elimination of secondary settling units, and reduced sludge recirculation requirements [107].

Continuous flow reactors provide lower operational costs and simpler handling but require careful management of hydraulic retention time (HRT), organic loading rate (OLR), and light distribution to prevent granule destabilisation and loss of bioremediation efficiency [107,190]. Comparative studies between granular M-BC and activated sludge have demonstrated higher treatment efficiency for granular consortia [172]. Ahmad et al. [191] reported removal efficiencies of dissolved carbon, nitrogen, and phosphorus of approximately 40%, 60%, and 15%, respectively, compared with 32%, 35%, and 10% achieved by bacterial activated sludge granules. In microalgae-based systems, oxygen supply can be partially sustained by photosynthesis combined with hydrodynamic turbulence, potentially reducing mechanical aeration demand and energy consumption [192,193,194]. However, excessive oxygen production under intense illumination may cause local supersaturation, redox fluctuations, and destabilisation of internal microenvironments, particularly within deeper granule layers.

Overall, granular M-BC represent a stable and efficient biological system, with laboratory- and pilot-scale studies demonstrating promising performance. Nevertheless, industrial-scale implementation requires addressing challenges related to light penetration control, structural stability under variable hydraulic loading, and maintaining balance between photosynthesis and respiration [195]. Currently, this technology remains at an experimental stage, and scale-up is associated with significant engineering and operational uncertainties that may affect process predictability and reproducibility.

Table 3. Major M-BC types: key characteristics and practical implications for AD.

M-BC Type	Typical Form	Representative Systems	Main Advantages	Practical Implications/AD Relevance	References
Suspended M-BC	EPS-stabilised flocs	Open/closed suspended reactors	High nutrient removal; reduced aeration demand	Biomass is typically dilute and requires thickening prior to AD; EPS-rich flocs may reduce hydrolysis rate and slow methane kinetics	[108,109,110,111,112,113,114]
HRAP-based suspended M-BC	Flocs (20–200 μm)	HRAP raceway ponds	Very low energy demand (~0.02 kWh/m3); simple operation	Large land footprint and strong seasonality lead to variable biomass composition and variable BMP; harvesting is a major limitation for AD implementation	[46,115,116,117,118,119,120,121,122,123,124,125,126,127,128]
PBR-based suspended M-BC	Dense suspension	Tubular/flat-plate/column PBR	Controlled conditions; higher productivity	More stable biomass quality improves AD predictability; harvesting/concentration remains necessary and EPS/viscosity may increase mixing demand in AD	[132,133,134,135,136,137,138,139,140,141]
Attached-growth M-BC	Stratified EPS biofilm	ATS, membrane reactors, packed-bed	Easy biomass recovery; reduced need for flocculation/sedimentation	Biomass recovery is operationally favourable for AD; compact structure and EPS matrix impose hydrolysis barriers and often justify pretreatment to increase methane yields	[142,143,144,145,146,147,148,149,150,151,159,160,161,162,163,164,165,166,167,168,169,170]
Granular M-BC	Self-assembled granules	SBR, CFR	Excellent settling and biomass retention; high stability	Natural thickening enables higher OLR (organic load rate) in AD; diffusion limitation inside granules and EPS barrier may constrain hydrolysis, so pretreatment improves methane kinetics and yield	[58,94,171,172,173,174,175,176,190,191,192,193,194,195]

shows the major M-BC types.

Table 3 highlights the diversity of functional outputs associated with M-BC systems, demonstrating that performance indicators depend strongly on system configuration, substrate characteristics, and environmental conditions. The comparative overview underscores that technological potential cannot be evaluated solely on the basis of individual performance metrics, as similar outcomes may arise from distinct mechanistic pathways. Moreover, the heterogeneity of reported parameters points to limited standardisation across studies, which constrains direct benchmarking. Therefore, data should be interpreted as evidence of both the versatility and methodological variability of M-BC applications, reinforcing the need for harmonised reporting frameworks and integrative assessment approaches. From an engineering perspective, this indicates that anaerobic biodegradation of suspended M-BC biomass promotes rapid yet potentially less stable fermentation. Biofilm structures enable more controlled substrate release during hydrolysis, whereas the degradation of granular biomass is typically the most stable, albeit associated with slower hydrolysis rates. Therefore, optimising AD performance requires balancing the structural susceptibility of M-BC biomass to anaerobic breakdown with its biochemical potential and careful control of process conditions, particularly organic loading.

5. Limitations and Barriers in AD of M-BC

AD of M-BC biomass represents a promising approach for sustainable management of organic wastes and biofuel production. Despite encouraging results, this technology faces multiple biological, chemical, and technological barriers that limit its practical implementation at a broader scale. Therefore, a key challenge is the development of effective strategies enabling the use of M-BC biomass as a substrate for anaerobic fermentation under industrial conditions, ensuring optimisation and long-term stability of both biochemical and technological processes.

5.1. Biological Barriers

Depending on environmental conditions, microalgal biomass contains variable proportions of proteins, lipids, carbohydrates, nucleic acids, pigments, and vitamins; however, the mineral composition of the biomass generally meets the nutrient and mineral requirements of the anaerobic microbiota involved in degradation processes [196]. Biological limitations of anaerobic degradation of M-BC biomass arise primarily from the presence of EPS, limited availability of readily biodegradable carbon, and toxic microbial metabolites produced within these consortia [107].

EPS are secreted by microorganisms and are also formed as a result of cell lysis and hydrolysis of macromolecules. They constitute a high-molecular-weight mixture of organic compounds forming a three-dimensional matrix surrounding cells within M-BC structures such as flocs, biofilms, and granules. The main EPS components include polysaccharides and proteins, as well as lipids, nucleic acids, uronic acids, and humic substances. Interactions among these constituents confer gel-like properties, high viscosity, and the capacity to bind ions and organic compounds [197].

Numerous studies indicate that a substantial fraction of EPS proteins and polysaccharides exhibits low susceptibility to enzymatic hydrolysis, which results from their high molecular weight and the presence of cross-linking bonds stabilised by multivalent cations and hydrophobic interactions [198]. EPS contain multiple charged functional groups (including carboxyl, phosphate, and hydroxyl groups), as well as non-polar aromatic and aliphatic fragments with hydrophobic characteristics. Such structure imparts amphoteric properties, enabling interactions with both polar and non-polar molecules. The hydrophilic–hydrophobic behaviour of EPS is closely associated with the relative contribution of protein and carbohydrate fractions [199]. Jorand et al. [200] demonstrated that at least 7% of dissolved carbon and approximately 12% of proteins present in EPS can be classified as hydrophobic, while no carbohydrates were detected in the isolated hydrophobic fraction. According to Dignac et al. [201], the balance between charged and hydrophobic groups determines EPS physicochemical properties. The authors reported that approximately 25% of EPS amino acids carried a negative charge, whereas 24% were classified as hydrophobic.

The presence of EPS in biomass significantly reduces hydrolysis efficiency during anaerobic biodegradation. The EPS matrix constitutes both a physical and chemical barrier, limiting diffusion of hydrolytic enzymes and release of degradation products into the liquid phase, which may reduce hydrolysis efficiency by as much as 30–50% [202]. Consequently, substrate availability for acidogenic and acetogenic bacteria decreases, leading to limited production of volatile fatty acids, and making hydrolysis the rate-limiting step of anaerobic degradation of M-BC biomass [203]. A conceptual scheme illustrating the EPS matrix as a key hydrolysis barrier during anaerobic digestion of M-BC biomass is presented in Figure 5.

EPS may also contain redox-active components such as quinones, humic-like moieties, and cytochrome c, which can modify local redox conditions and influence electron transfer between syntrophic microorganisms and methanogenic archaea [204]. Wang et al. [205] confirmed that EPS contain electrochemically active compounds affecting electron transfer processes in anaerobic degradation and shaping microbial community structure. In biomass with high EPS content, limitation of direct interspecies electron transfer (DIET) is frequently observed, which decreases methanogenesis stability and efficiency [202]. At the same time, recent studies indicate that redox-active EPS constituents may also promote DIET, contributing to improved methane production performance [206].

To increase biomass bioavailability, pretreatment targeting EPS disintegration is applied [207]. Thermal, mechanical, or chemical pretreatment disrupts bonds within the polymeric matrix, increases soluble COD, and releases organic compounds into the liquid phase, thereby directly intensifying hydrolysis and acidogenesis [205]. Hybrid technologies combining, for example, temperature and enzymatic action have proven particularly effective, increasing soluble organic fractions and methane production rates [208]. An alternative strategy involves targeted modification of cell membrane properties and the EPS matrix using supporting additives such as conductive materials (e.g., biochar, magnetite, zero-valent iron) [209]. The presence of such materials affects EPS composition and characteristics and promotes DIET, leading to increased methanogenic activity and stabilisation of the digestion process through facilitated electron transfer [210]. In parallel, biological strategies are being developed, based on inoculation with microbial consortia capable of degrading EPS components [211].

In contrast to conventional anaerobic substrates such as agricultural residues or sewage sludge, M-BC biomass is characterised by high protein content and limited amounts of readily degradable carbon fractions [28]. Therefore, a key limitation of anaerobic biodegradation of this biomass is the low C/N ratio, which in microalgal biomass typically ranges from 4 to 12, whereas the optimal range for stable methane fermentation is approximately 20–30 [196]. Excess nitrogen relative to carbon intensifies amino acid deamination and consequently promotes accumulation of ammoniacal nitrogen [22]. High ammoniacal nitrogen concentrations, whose inhibitory effect increases with rising pH and temperature, exert strong toxicity towards methanogenic microorganisms, particularly acetoclastic methanogens of the genus Methanosaeta [212]. Methanogenesis inhibition leads to accumulation of volatile fatty acids, pH destabilisation, and reduced overall biogas yield [213].

High protein content, reaching 40–60% of dry matter for many microalgal species, may further affect the hydrolysis stage, which is widely regarded as the rate-limiting step of anaerobic biodegradation [19]. In the case of M-BC biomass, protein hydrolysis is slowed both by limited activity of proteolytic enzymes in anaerobic sludge and by physical inaccessibility of the substrate resulting from rigid cell walls and the EPS matrix [205]. Consequently, the release rate of amino acids and subsequent metabolites is insufficient to sustain stable syntrophy among fermentative, acetogenic, and methanogenic bacteria [214]. In turn, low availability of readily assimilable carbon in the form of soluble sugars reduces volatile fatty acid production during acidogenesis, leading to substrate limitation for methanogens and decreased methane yield [215]. To optimise biomass chemical composition and increase the C/N ratio, co-digestion with organic substrates rich in readily biodegradable carbon can be applied, such as sewage sludge, plant residues, or food waste [216]. Improving the C/N ratio reduces the negative effects of excessive ammoniacal nitrogen, resulting in enhanced biogas production efficiency [217].

Anaerobic fermentation of M-BC biomass may also be inhibited by the formation of metabolites that suppress the activity of anaerobic sludge microorganisms. Microalgae and bacteria forming these consortia synthesise a broad spectrum of bioactive compounds, including aromatic compounds, phenolic secondary metabolites, complex humic-like structures, terpenoids, alkaloids, antibacterial peptides, fatty acids, and various antimetabolites, which fulfil defensive, allelopathic, or regulatory functions [63]. Due to their aromatic nature and high ring stability, polyphenolic compounds are resistant to biodegradation under anaerobic conditions, and their degradation is slow and involves specialised metabolic routes such as the benzoyl-CoA pathway and the resorcinol pathway [218]. These processes occur only within a limited group of selectively adapted microorganisms, most commonly denitrifying or sulfate-reducing bacteria [219]. Moreover, phenolic compounds, including aromatic metabolites originating from degradation of algal photosynthetic pigments, can denature enzymatic proteins, destabilise cell membranes, and disrupt electron transport [220]. In anaerobic reactors, such compounds may interact directly with hydrolytic enzymes, leading to deactivation or reduced catalytic activity, thereby limiting the release rate of soluble organic compounds required to sustain subsequent fermentation stages [221]. Acetoclastic and hydrogenotrophic methanogens are particularly sensitive, as their metabolism relies on precisely regulated enzymatic pathways; even relatively low concentrations of selected phenolic compounds may inhibit key enzymes such as methyl-coenzyme M reductase [222]. The impact of secondary metabolites is especially problematic in the context of long-term process stability, as these compounds often show low biodegradability [223]. Their accumulation in the reactor may lead to chronic inhibition of microorganisms even under seemingly optimal operational parameters, ultimately resulting in a gradual decline in methanogenic activity and deterioration in both quantity and quality of produced biogas.

Madigou et al. [224] demonstrated that acclimatisation of anaerobic sludge microorganisms can significantly increase their tolerance to phenolic compounds. The adaptation process promoted selection of resistant archaea of the genus Methanobacterium and bacteria belonging to the orders Clostridiales and Bacteroidales, enabling gradual adjustment of the microbial community to increasing phenolic stress. As a result, the overall phenol inhibition threshold increased from 895 to 1942 mg/L, confirming the importance of adaptive mechanisms in mitigating the negative effects of inhibitors on anaerobic fermentation.

Humic and humic-like compounds containing complex phenolic–aromatic structures exhibit high resistance to biodegradation, primarily due to their high molecular weight and the presence of stable chemical bonds, which markedly hinder enzymatic depolymerisation and further biological conversion [225]. Consequently, they may remain essentially unchanged even during long-term fermentation, leading to gradual accumulation in reactors as highly stable organic matter fractions [226]. Microalgae also produce compounds inhibiting the growth of competing microorganisms, such as short- and medium-chain fatty acids, aldehydes, or peptides with bacteriostatic activity. When released into the reaction environment, these compounds may selectively inhibit hydrolytic and acidogenic bacteria, disrupting microbial balance and weakening syntrophy among functional microbial groups [227].

Analysis of the role of secondary metabolites and the mechanisms of their interactions with anaerobic microorganisms is currently considered one of the key directions for further research on efficient utilisation of M-BC biomass in bioenergy technologies. One of the most promising strategies to minimise the negative effects of these compounds is the selection of resistant strains and inoculum adaptation [228]. This approach involves gradual exposure of anaerobic microbial populations to increasing concentrations of harmful compounds in order to develop metabolic tolerance and resistance to chemical stress, as well as to stimulate the development of neutralisation or detoxification mechanisms [229].

From a technological perspective, however, the barriers described above do not exert equivalent influence on anaerobic digestion performance. Available evidence indicates that structural limitations associated with the EPS matrix and nitrogen-related inhibition resulting from high protein content and low C/N ratios represent the most critical constraints under real process conditions, as they directly determine hydrolysis efficiency, ammonia accumulation, and methanogenic stability. In contrast, the impact of secondary metabolites and redox-active EPS components appears more context-dependent and is frequently demonstrated under controlled laboratory settings rather than full-scale operation. Although these compounds may modify microbial interactions or electron transfer pathways, their effects are often modulatory rather than universally limiting.

Consequently, interpretation of biological barriers in AD of M-BC biomass should follow a hierarchical perspective, in which diffusion-related constraints and nitrogen imbalance constitute primary engineering challenges, whereas metabolite-mediated effects represent secondary factors dependent on consortium structure and environmental conditions. Such an approach improves mechanistic clarity and supports more realistic assessment of process risks and optimisation strategies.

5.2. Chemical Barriers

Chemical limitations of anaerobic degradation of M-BC biomass arise mainly from the chemical structure of the substrate, ammonia accumulation, and the presence of compounds acting as process inhibitors. The biomass of M-BC is characterised by a complex cell wall architecture composed of polymers highly resistant to enzymatic degradation (including cellulose, chitin, and sporopollenin). In some microalgae, e.g., Chlorella strains, the three-layered cell wall contains algaenan, a recalcitrant and non-hydrolysable aliphatic biopolymer, whereas strains lacking the outer TLS layer exhibit higher contents of cellulose and glucosamine [230]. Hydrolytic enzymes produced by anaerobic sludge microorganisms show limited effectiveness in biodegradation of these compounds, which slows hydrolysis and reduces monomer availability in subsequent stages of AD [231]. A similar limitation applies to chitin, which exhibits high crystallinity and low solubility [232]. Although some bacteria produce chitinases capable of degrading chitin fractions, their expression and activity in anaerobic sludge are low and unstable. Consequently, chitin degradation rates remain limited, leading to accumulation of chitosan oligomers and N-acetylglucosamine monomers, which are less bioavailable for subsequent fermentation stages [233]. The most recalcitrant polymer in M-BC biomass is sporopollenin, a highly cross-linked organic macromolecule with exceptional resistance to biodegradation. As a result, sporopollenin is essentially not degraded under anaerobic conditions, contributing to reduced overall substrate bioavailability [234]. According to the literature, algal cell walls typically account for 11–37% of dry matter; therefore, their chemical structure is a key parameter controlling biogas production efficiency [235].

While algaenan, chitin, and sporopollenin differ in molecular architecture and resistance mechanisms, their technological relevance converges at the level of substrate accessibility and process-level trade-offs. Polymer recalcitrance limits enzymatic depolymerisation and shifts anaerobic digestion toward hydrolysis-controlled kinetics, thereby reducing effective substrate availability for downstream fermentative and methanogenic stages. Overcoming this limitation typically requires increasing pretreatment severity through thermal, mechanical, or chemical disruption of cell wall structures. However, intensification of pretreatment simultaneously elevates operational energy demand, may increase capital costs, and in some cases promotes the formation of secondary inhibitory compounds. Consequently, the central issue is not solely polymer resistance itself, but the optimisation threshold at which enhanced biodegradability compensates for additional energy inputs under realistic operational conditions. From a systems perspective, cell wall composition should therefore be interpreted not merely as a structural characteristic, but as a determinant of hydrolysis kinetics, pretreatment feasibility, net energy balance, and ultimately scale-dependent techno-economic viability of M-BC-based anaerobic digestion.

Pretreatment of M-BC biomass markedly increases its availability to anaerobic sludge microorganisms by loosening the polymeric structure and partially solubilising polysaccharides, thereby facilitating subsequent enzymatic degradation by cellulases and hemicellulases [236]. When hydrothermal pretreatment was applied, biomass solubility increased by 8–13%, fermentation rate increased by 30–90%, and methane yield was 17–39% higher than for non-pretreated biomass [237]. The best performance was achieved at 130 °C and a pretreatment time of 15 min, which increased methane yield from 0.12 L CH₄/g VS in the control sample to 0.17 L CH₄/g VS (41%) [237]. According to Mendez et al. [238], hydrothermal pretreatment increased the biodegradability of Chlorella biomass by 50%. Enzymatic pretreatment using cellulases, xylanases, and other hydrolases is also applied, increasing sugar extraction from 40% to 63% [239]. Córdova et al. [240] reported an increase in biogas production of more than 21% from microalgal biomass subjected to enzymatic pretreatment. Although hydrothermal pretreatment and enzymatic hydrolysis increase technological costs and, when excessively intensive, may promote formation of inhibitory compounds, thermo-enzymatic strategies remain among the most effective methods for improving biopolymer degradability [241].

A key chemical factor limiting anaerobic degradation is ammonia accumulation resulting from intensive biodegradation of the protein fraction of M-BC biomass. Undissociated ammonia (NH₃) readily penetrates cell membranes and exerts toxic effects on methanogenic bacteria and archaea by disturbing proton balance and ionic homeostasis, causing potassium deficiency, and inhibiting key enzymatic reactions [22]. Consequently, microbial metabolic activity decreases, intermediate fermentation products accumulate (including volatile fatty acids), pH declines, and the overall anaerobic biodegradation process becomes destabilised [242]. Chen et al. [243] reported that methanogenesis was inhibited at an ammonium ion concentration of 2 g/L, whereas no toxic effects were observed for hydrolysis and acidogenesis. Toxicity thresholds reported in the literature for free ammonia nitrogen (FAN) vary widely, ranging from 50 to 1500 mg N NH₃/L [244]. These differences in inhibition thresholds result from variations in temperature, reactor configuration, operational parameters, and the composition and adaptation level of microbial communities [245]. A range of physical, chemical, and biological methods has been developed to control ammonia levels in anaerobic reactors and improve biological process efficiency. Common approaches include substrate dilution, adjustment of the carbon-to-nitrogen ratio, pH control, and ammonia recovery via membrane distillation [23]. In addition, bioaugmentation and microbial acclimatisation to ammonia [246], mitigation of ammonia toxicity through the addition of auxiliary materials (e.g., activated carbon and magnetite) [245], trace element supplementation [247], and the use of aeration or stripping techniques have also been investigated [248].

Similarly, the presence of heavy metals may significantly disrupt anaerobic biodegradation of M-BC biomass. Metals such as cadmium, lead, and nickel can bind to enzymatic proteins of anaerobic sludge microorganisms, blocking enzyme active sites and inhibiting key metabolic pathways, particularly during hydrolysis and methanogenesis [249]. This mechanism involves coordination of metal ions with functional groups of hydrolytic and oxidoreductase enzymes, resulting in enzyme deactivation and reduced metabolic activity of both bacteria and methanogenic archaea [250]. At the same time, some metals at trace levels act as enzymatic cofactors. For example, low concentrations of Cu²⁺ (0–100 mg/L), Fe²⁺ (50–4000 mg/L), Ni²⁺ (0.8–50 mg/L), Cd²⁺ (0.1–0.3 mg/L), and Zn²⁺ (0–5 mg/kg) enhance biogas production [249]. Copper at 150 mg/kg biomass acted as a cofactor stimulating enzymatic reactions of cellulose hydrolysis [251], while a zinc concentration of 50–100 mg/g intensified protein solubilisation and hydrolysis [252].

An effective method to counteract the inhibition of AD caused by chemical inhibitors is microbial adaptation to the compound and selection of strains capable of its biodegradation [253]. Strain selection can be performed at the inoculum level or through enrichment culture, favouring strains with higher resistance to phenolic and bactericidal compound toxicity. This approach enables maintenance of high hydrolytic and methanogenic activity even in the presence of inhibitors [224]. In addition, inoculum adaptation can be supported by complementary strategies, such as gradual co-digestion with carbon-rich substrates, which not only improves the C/N ratio but also alleviates inhibitor effects through dilution [254].

5.3. Physical Barriers

In the AD of M-BC biomass, physical constraints may represent one of the key groups of factors determining both methane yield and process stability. This is because M-BC biomass is an atypical substrate compared with conventional anaerobic feedstocks, as it is often characterised by a developed aggregation structure [107], high content of EPS [255], species variability, and a specific microarchitecture (biofilms, flocs, granules) [107]. From a technological perspective, this implies that the critical stages of AD—particularly hydrolysis and early acid fermentation—may be limited not only by enzymatic convertibility, but also by mass transport conditions and the physical bioavailability of the substrate. Thus, even if the organic fraction of the biomass exhibits high energy potential measured as total organic carbon (TOC) or volatile solids (VS), the actual methane production may be constrained by a structural barrier, resulting in decreased BMP and impaired process kinetics [256].

The first fundamental barrier is the low solubility and limited substrate accessibility within biofilm and granular structures [257]. In many M-BC systems, microalgal and bacterial cells are strongly aggregated within an EPS matrix composed mainly of polysaccharides, proteins, and humic acids, which may exhibit high resistance to degradation [107]. Such structures display multilevel diffusion resistance. Hydrolytic enzymes and microorganisms have hindered access to the aggregate core, while hydrolysis products (sugars, amino acids, short-chain fatty acids) exhibit limited diffusion into the liquid phase, reducing their utilisation by fermentative bacteria. Consequently, hydrolysis becomes a strongly limiting step, and the AD system shifts into a mode of “kinetic underfeeding” of methanogens due to limited availability of precursors (acetate, hydrogen, and CO₂) reaching the methanogenic phase; as a result, CH₄ production declines despite an apparently high organic load [6]. In practice, this may necessitate extending HRT, which deteriorates design parameters, increases required digester volumes, and reduces economic viability. In addition, under hydrolysis-limited conditions, the concentration of residual organic matter in digestate may increase, thereby reducing substrate mineralisation and digestate stabilisation, which is relevant from both energy and environmental perspectives [258].

Strategies to minimise this barrier focus on increasing substrate bioavailability via disintegration of aggregation structures. Mechanical pretreatment (size reduction, homogenisation, depolymerisation, cavitation) is most frequently indicated due to its scalability and the lack of requirement for chemical dosing. Its mechanism involves increasing biomass specific surface area, breaking flocs, and weakening EPS, which increases the fraction of soluble organic carbon (sCOD) and accelerates hydrolysis rates [107]. The literature emphasises that even moderate mechanical pretreatment can substantially improve AD kinetics (shorter time to methane plateau), which is highly relevant for reactor design with reduced HRT [107]. Nevertheless, it should be underlined that any pretreatment increases energy demand. Therefore, robust energy analyses (energy return on energy invested, EROI) and life cycle assessment (LCA) should be decisive for technology selection.

High viscosity and flocculation of M-BC biomass also play an important role in AD, directly affecting hydrodynamics and mass distribution within the reactor. Substrate viscosity increases with rising total solid (TS)/VS concentration, but also with EPS content, which is responsible for gel-forming and colloidal properties. Elevated viscosity impedes effective mixing, leading to concentration gradients (substrate/VFA/alkalinity) and thermal gradients, and consequently to heterogeneous environmental conditions within the digester [259]. Under non-uniform mixing, “hot spots” of acid fermentation may occur, where locally overloaded zones exhibit rapid volatile fatty acids (VFA) accumulation. Methanogens—particularly acetoclastic taxa—are more sensitive to pH decreases than acidogenic bacteria; therefore, imbalance between acidogenesis and methanogenesis may be reflected by an increased FOS/TAC ratio, pH decline, and transient or permanent inhibition of methanogenesis [260]. This phenomenon may be further intensified by the risk of channelling, particularly in poorly mixed reactors, where medium flow bypasses part of the working volume, reducing the effective contact time between the microbiome and the substrate.

From an engineering perspective, this means that M-BC biomass may not be an optimal feedstock for conventional reactors unless an appropriate mixing strategy and reactor geometry are ensured. Mitigation of this limitation includes optimisation of the mixing regime (continuous vs. intermittent mixing; shear intensity), selection of reactor types more tolerant to high viscosity (e.g., a properly designed CSTR), and in some cases consideration of process staging (e.g., separation of hydrolysis/acidogenesis from methanogenesis) to avoid overloading in single-stage AD systems [107]. The importance of controlling OLR (organic loading rate) in strict relation to substrate rheology has also been highlighted, because for viscous biomass an increase in OLR does not translate linearly into increased biogas production, but may rapidly elevate destabilisation risk [258]. From a comparative engineering perspective, benchmarking against established anaerobic digestion substrates illustrates the scale-related implications of these constraints. In full-scale sewage sludge digestion, total solids (TS) concentrations typically range between 2 and 6%, and mixing energy demand is commonly estimated at approximately 3–8% of the produced biogas energy. Agricultural residues operated under higher TS conditions require even greater mixing intensity and are often associated with increased energy penalties. In contrast, M-BC biomass frequently exhibits lower intrinsic VS concentration combined with elevated apparent viscosity due to EPS-rich matrices and aggregation structures. This implies that, under scale conditions, either intensified mixing or prior thickening would be required to achieve comparable volumetric methane productivity. However, because most AD studies on M-BC have been conducted at laboratory scale, systematic pilot- and full-scale datasets quantifying mixing energy demand, viscosity thresholds, or net energy balance remain unavailable. Therefore, while qualitative evidence indicates that structural aggregation and rheological properties may impose additional energetic constraints, robust feasibility assessment requires scale-validated operational data.

Another important AD barrier characteristic of M-BC biomass is instability of biomass composition resulting from seasonal fluctuations [15]. In open and semi-open systems, as well as in wastewater treatment-linked installations, dominance of microalgal species may change on weekly to monthly timescales, leading to significant variation in biochemical composition [261]. The contribution of the protein fraction (determining potential TAN/FAN emission), lipid fraction (high energy density but risk of inhibition by LCFAs), and carbohydrate fraction (high biodegradability but risk of rapid acidogenesis) may all vary substantially. Such variability implies that maintaining stable AD requires adaptive process control [262]. In systems based on protein-rich M-BC biomass, TAN may increase and—at elevated pH and temperature—the free ammonia fraction (FAN) may also rise, exerting strong inhibitory effects on methanogens. Conversely, high content of readily fermentable sugars or soluble biopolymers may trigger rapid VFA accumulation, overloading methanogenesis and inducing pH decline. As a result, fluctuations in biogas productivity are observed, and in extreme cases, acidification episodes and irreversible destabilisation of the reactor microbiome may occur.

Approaches to minimise seasonality include feedstock quality monitoring, process stabilisation, and inoculum adaptation. Monitoring should cover not only quantitative parameters (TS, VS, OLR), but also, critically, inhibition risk indicators such as C/N, protein fraction contribution, TAN/FAN, lipid content, and ash content. Continuous control of process parameters such as FOS/TAC, alkalinity, conductivity, and VFA profiles is also essential [263]. Inoculum adaptation is regarded as a tool for increasing functional resilience of the microbiome through selection of populations more tolerant to changes in substrate composition. Importantly, microbial consortia with higher metabolic diversity may buffer fluctuations in feedstock quality more effectively; however, this requires maintaining conditions supporting stability of the fermentative ecosystem (avoiding OLR shocks, sudden temperature changes, and abrupt pH drops) [107]. From an implementation perspective, seasonality is one of the main reasons for difficulties in scaling up AD of microalgal–bacterial biomass, as it necessitates integration of biomass storage systems, feedstock quality buffering, and advanced process control.

5.4. Operational and Technological Barriers

Operational and technological barriers in AD of microalgal–bacterial biomass are largely associated with process economics and the feasibility of safe scale-up. Unlike physical barriers, which arise directly from intrinsic material properties, operational barriers relate to limitations in process performance, high unit costs, and poor comparability across the broad ranges of reported research outcomes, which hinders the establishment of optimal technological standards.

A major limitation is the high water content of M-BC biomass, resulting in low VS concentration. In practice, under standard reactor configurations, methane production per unit reactor volume is relatively low because large volumes of water are introduced into the digester with a limited organic load [264]. This constraint is critical from a design perspective because profitability depends not only on BMP (L CH₄/kg VS) but also on volumetric productivity (m³ CH₄/m³ reactor·day). Low VS concentration necessitates either very large reactor volumes (high CAPEX) or increasing OLR through expensive biomass thickening technologies. At the same time, processing diluted streams increases pumping, heating, and mixing costs and, in certain configurations, may reduce system alkalinity, increasing susceptibility to acidification [265].

Thickening and dewatering of biomass prior to AD is the primary strategy to mitigate this barrier; however, it constitutes a separate and highly relevant energy challenge. The literature indicates that simple and low-cost sedimentation increases M-BC biomass concentration only to 1–3% [257]. The application of centrifugation, membrane processes, dewatering presses, filter bags, or chemically assisted flotation increases energy consumption, substantially raises costs, and reduces overall process profitability. Importantly, biomass thickening may increase viscosity, intensifying hydrodynamic barriers and thereby requiring additional investment in mixing systems [107]. Therefore, a review perspective should emphasise the need for integration: optimisation of thickening must be analysed simultaneously with reactor type selection, mixing regime, and OLR control strategy. In industrial applications, it is often suggested that moderate thickening combined with co-digestion provides better outcomes than aggressive dewatering that triggers rheological problems and process destabilisation [266].

A second implementation-relevant barrier is the high cost of pretreatment. For M-BC biomass, pretreatment may be necessary to achieve satisfactory methane yields and substrate mineralisation; however, technologies that intensify biodegradation under anaerobic conditions generate substantial capital and operating costs [264]. In solutions based on chemical methods, hydrothermal depolymerisation, or cavitation processes, an additional risk is associated with the potential formation or introduction of methanogenesis inhibitors into the technological system. Hydrothermal depolymerisation may generate recalcitrant compounds such as melanoidins and humins (products of Maillard reactions and sugar condensation), as well as aromatic lignin-derived compounds/phenols and nitrogen heterocycles. Cavitation-based technologies may also generate strong oxidants, including biocidal hydroxyl radicals. These compounds may be poorly degraded under AD conditions and may inhibit methanogenesis [267]. Chemical methods, in turn, require neutralisation and may increase digestate salinity, limiting its fertiliser applications [268]. Consequently, modern approaches to pretreatment in AD of M-BC biomass should focus on selective optimisation, where the objective is not to maximise SCOD or BMP at any cost, but rather to achieve a positive energy balance for the overall technology. This requires reporting pretreatment energy indicators (kWh/kg TS or kWh/kg VS) and comparing them with the methane yield increment, enabling objective techno-economic assessment [256]. A mitigation strategy involves selecting the “cheapest effective” pretreatment option, for example by integration with waste heat (CHP), as well as development of less cost-intensive methods.

A practically significant technological barrier is the lack of standard operational protocols for different types of M-BC biomass, which limits transferability of research outcomes to a technical scale [107]. The absence of standardisation concerns both substrate preparation (fresh, thickened, dried biomass; different preservation and storage methods) and technological conditions applied during BMP tests and operation of continuous bioreactors. As a result, data from the literature on AD kinetics and performance exhibit substantial variability, hampering the development of predictive models and design guidelines. This is particularly problematic in the context of scaling, as the lack of harmonised datasets constrains accurate selection of HRT, OLR, and process control strategies. Furthermore, differences in reporting biomass quality parameters prevent identification of the drivers responsible for discrepancies in methane yield.

Mitigation strategies include the development of research and reporting standards. It is essential to implement a minimum set of parameters reported in AD studies of M-BC biomass: TS/VS, elemental composition (C, H, N, S), C/N, TOC, pH, biopolymer fractions (protein, lipids, carbohydrates), and information on EPS. In addition, consistent BMP procedures aligned with international guidelines are recommended, along with reporting not only final BMP values but also kinetics (e.g., Gompertz model constants or first-order model parameters), which is crucial for designing HRT in real installations [269]. Standardisation will enable the development of databases, meta-analyses, and models, which is a prerequisite for accelerating technological maturation of this field and supporting its transfer into circular economy frameworks.

Table 4. Biological, chemical, physical, and operational constraints governing anaerobic AD efficiency and stability for M-BC biomass.

Barrier Category	Key Limitation in M-BC	Main Impact on AD	Mitigation Strategies	Ref.
Biological	EPS matrix (enzymatic/diffusion barrier; redox effects/DIET modulation)	Slower hydrolysis (up to 30–50%), reduced BMP and methanogenesis stability	Pretreatment (thermal/mechanical/chemical), conductive additives, EPS-degrading consortia	[197,198,202,203,204,205,206,207,208,209,210,211]
	Low C/N ratio and high protein content	TAN/FAN build-up, methanogen inhibition, VFA accumulation	Co-digestion, C/N adjustment, inoculum adaptation	[22,28,196,212,213,214,215,216,217]
	Inhibitory metabolites (phenolics/humic-like/allelochemicals)	Enzyme inhibition, chronic suppression of methanogenesis	Strain selection and inoculum acclimation (enrichment, adaptation)	[63,218,219,220,221,222,223,224,225,226,227,228,229]
Chemical	Recalcitrant cell wall polymers (algaenan/cellulose/chitin/sporopollenin)	Reduced bioavailability and slow hydrolysis	Hydrothermal and enzymatic pretreatment (thermo-enzymatic strategies)	[230,231,232,233,234,235,236,237,238,239,240,241]
	Ammonia accumulation and metals (inhibitors; sometimes cofactors)	Methanogenesis inhibition and unstable CH4 yield	pH/C:N control, NH3 recovery, additives, microbial adaptation	[22,23,242,243,244,245,246,247,248,249,250,251,252,253]
Physical	Aggregation and high viscosity (biofilm/flocs/granules)	Diffusion resistance, acidogenic “hot spots”, higher HRT and mixing demand	Mechanical disintegration, mixing/reactor optimisation, process staging	[6,107,256,257,258,259,260]
	Seasonal variability of biomass composition	BMP fluctuations and variable inhibition risk (TAN/VFA)	Feedstock monitoring, adaptive control, inoculum adaptation	[15,107,261,262,263]
Operational	High water content, costly thickening/pretreatment, lack of standard protocols	Low volumetric CH4 productivity, risk of negative net energy balance, poor data comparability	Moderate thickening + co-digestion, EROI/LCA-based selection, BMP/reporting standardisation	[107,256,257,264,265,266,267,268,269]

shows the constraints governing anaerobic AD efficiency and stability for M-BC biomass.

Rather than representing isolated constraints, the barriers summarised in Table 4 form an interconnected network of limitations that collectively determine the feasibility of AD of M-BC biomass. Biological factors such as EPS presence, low C/N ratio, and inhibitory metabolites interact with chemical recalcitrance and ammonia dynamics, while physical aggregation and rheological properties further amplify hydrolysis and mass-transfer constraints. These intrinsic substrate-related barriers directly translate into operational challenges, including reduced volumetric methane productivity, higher energy demand for pretreatment and mixing, and increased risk of process instability. Consequently, optimisation of AD of M-BC biomass cannot rely on single mitigation measures but requires an integrated approach combining substrate conditioning, adaptive microbial management, reactor design optimisation, and techno-economic assessment based on net energy balance. Table 4 thus provides not only a structured classification of constraints but also a strategic framework for prioritising interventions that enhance process robustness and scalability.

6. AD of M-BC Biomass

Microalgae–bacteria biomass constitutes a dynamic microbiological environment in which microalgae and bacteria operate under strong metabolic synergy [270]. In recent years, it has become one of the most promising substrates for methane fermentation, particularly within circular wastewater treatment systems [271]. M-BC biomass is characterised by a high organic matter content, substantial contributions of proteins and carbohydrates, production of EPS that promote sedimentation, and the presence of hydrolytic microorganisms, which naturally increases its susceptibility to hydrolysis and methanogenesis compared with axenic microalgal cultures [107]. The performance parameters of AD for different M-BC types—microalgal–bacterial granules (microalgae–bacterial granular sludge, M-BGS), biofilms in ATS systems, suspended algal biomass cultivated in photobioreactors, and biomass subjected to mechanical or thermal pretreatment—depend strongly on consortium maturity, substrate availability, hydrolytic activity of the inoculum, and the applied pretreatment strategy [255].

One of the best investigated examples of M-BC biomass is M-BGS granules developed in hybrid photobioreactors, whose maturation induces clear shifts in chemical composition and microbiological activity. Kazimierowicz et al. [256] showed that as the consortium matured, TOC reduction reached 88.2 ± 7.2%, while COD reduction was 84.1 ± 5.1% [256]. The highest methane potential was recorded for biomass collected after approximately 60 days of cultivation: biogas yield reached 531 ± 38 cm³/gVS with methane content of 66.2 ± 2.7%, corresponding to methane production of approximately 351–365 mL CH₄/gVS. These results exceed typical BMP values reported for monoculture algal biomass, confirming the strong effect of hydrolytic bacteria and mature granular structure on enhanced AD performance.

Although the granular structure of M-BGS is advantageous for biomass thickening, it may limit hydrolysis rates due to diffusion barriers associated with the EPS matrix. Dębowskiego et al. [258] applied ultrasonic disintegration (UD) to increase substrate accessibility. This treatment resulted in more than a six-fold increase in the concentration of sCOD, which translated into a significant increase in methane yield: 534 ± 16 mL CH₄/gVS after 150 s of sonication and 561 ± 17 mL CH₄/gVS after 200 s [258]. Energy balance analysis showed that the optimal UD duration was 150 s, for which the net energy gain reached 1.19 ± 0.18 Wh/gVS. This confirms that disintegration can improve AD efficiency without compromising the overall energy balance. These results clearly demonstrate that mechanical disruption of granule structure reduces the hydrolysis barrier and markedly accelerates substrate conversion to methane. While M-BGS granules and ultrasonic pretreatment are supported by detailed quantitative datasets, their performance should be interpreted within the broader structural spectrum of M-BC systems. Granular architecture enhances biomass retention and promotes close syntrophic proximity between functional groups, which may intensify metabolite exchange and stabilise methanogenesis. However, the same compact structure can introduce diffusion resistance and hydrolysis limitations associated with EPS-rich matrices. Mechanical disintegration reduces these barriers by increasing surface area and releasing soluble organic fractions, but its effectiveness depends on the balance between structural disruption and additional energy input. Thus, the improved methane yields observed in M-BGS systems reflect structural accessibility enhancement rather than intrinsic superiority of granular consortia.

Microalgae–bacteria biofilms developed in ATS systems also exhibit high energy potential. Cheenakula et al. [272] comprehensively assessed AD performance of ATS biofilm for untreated biomass (UAB) and thermally pretreated biomass (PAB). The study examined AD yields of a microalgae–bacteria consortium as a function of anaerobic sludge source used for inoculation of digestion reactors. Anaerobic sludges derived from biogas plants processing pulp and paper waste, agricultural waste co-digestion, sewage sludge, and green waste were tested. The results indicated that inoculum type strongly affected the efficiency of substrate-to-methane conversion. In UAB variants, methane yields were 120 ± 8 mL CH₄/gVS, 154 ± 8 mL CH₄/gVS, 350 mL CH₄/gVS, and 311 mL CH₄/gVS, respectively. The highest methanogenic activity was observed for inocula originating from wastewater treatment plants and green waste, as confirmed by methane flow rate (MFR) values of 0.5 Nm³/d for variant C and 2.8 Nm³/d for variant D. In contrast, inocula A and B exhibited very low methanogenic activity, with MFR values of only 1.5 × 10⁻⁷ Nm³/d and 3.3 × 10⁻⁸ Nm³/d. Thermal pretreatment (105 °C, 2 h) significantly altered the process characteristics. In PAB variants, methane yields increased for inocula A and B, whereas for inocula C and D the values were lower than in UAB and reached 212.2 mL CH₄/gVS and 192.5 mL CH₄/gVS, respectively. The authors did not report BMP values or biogas composition, focusing instead on volumetric methane production and MFR; therefore, these parameters cannot be determined reliably.

Scarcelli et al. [273] analysed an integrated system combining a photobioreactor, AD of microalgae–bacteria biomass, and biological biogas upgrading. The resulting digestate exhibited very low pollutant loads: TOC reduction reached 98.9 ± 1.1%, TN reduction 90.8 ± 8.0%, and TP reduction ranged from 53 to 68%. Biogas upgrading in an algal column enabled CO₂ reduction of 74.7 ± 3.0% and near-complete H₂S removal (99.0 ± 2.8%), demonstrating that algal biomass may function as a biological sorbent and a tool for CH₄ enrichment. In this system, CO₂ generated during fermentation was re-used in the photobioreactor as a substrate for photosynthesis, representing a tangible example of carbon cycle closure.

In contrast, ATS biofilms and PBR-derived suspended biomass represent less densely aggregated configurations, where hydrolysis constraints may be governed more by cell wall composition and consortium maturity than by diffusion limitation alone. Biofilm systems exhibit heterogeneous microenvironments, potentially supporting metabolic stratification, whereas suspended systems are more sensitive to washout and substrate dilution effects. Reported variability in methane yield across inoculum types further indicates that AD performance is strongly influenced by microbial compatibility and prior adaptation. Therefore, differences between ATS, PBR, and granular systems should be interpreted as architecture-driven variations in substrate accessibility, redox microenvironment formation, and inoculum–substrate interaction dynamics, rather than as categorical performance hierarchies.

In review studies, Satiro et al. [107] emphasised the importance of EPS in stabilising M-BC granules and biofilms, as well as its role in coagulation and facilitated biomass thickening prior to AD. The authors indicated that M-BC can remove up to 85–100% of nitrogen compounds and 60–90% of phosphorus from wastewater, producing energy-valuable biomass [107]. Kong et al. [274] demonstrated that M-BC biomass can achieve very high CO₂ assimilation rates of 302 mg CO₂/L·h and that, under appropriate cultivation conditions, it can significantly increase protein and lipid content, thereby supporting higher BMP values [274]. These data confirm that biomass quality directly depends on environmental conditions and wastewater composition, which can be effectively controlled in integrated systems.

Olsson et al. [275] showed that microalgae–bacteria biomass cultivated on municipal wastewater exhibited moderate AD susceptibility, achieving BMP of 180–220 mL CH₄/gVS in mono-digestion, whereas co-digestion with sewage sludge significantly increased both process stability and methane yield. The most favourable substrate proportions (25–50% algal biomass share in the mixture) increased BMP to 250–280 mL CH₄/gVS, corresponding to a 20–35% improvement compared with digestion of algal biomass alone. The authors also reported that an appropriate substrate combination reduced the risk of ammonia inhibition, and OLR values of 2.0–2.5 gVS/L·d ensured stable methanogenesis, as confirmed by low volatile fatty acid concentrations (below 0.8 g/L). These results clearly indicate that wastewater-derived microalgae–bacteria biomass is a compatible and efficient co-substrate for sewage sludge, and that synergistic interactions between both biomasses translate into a higher degree of organic matter degradation and a more favourable energy balance of AD. Co-digestion strategies introduce an additional mechanistic dimension by modifying substrate stoichiometry rather than structural recalcitrance. In protein-rich M-BC biomass, low C/N ratios promote ammonia accumulation and potential methanogenic inhibition. Blending with carbon-rich substrates improves elemental balance, buffers pH fluctuations, and enhances syntrophic stability. Importantly, co-digestion may compensate for biochemical constraints without requiring intensive pretreatment, thereby potentially improving net energy performance. The synergistic methane yield increases reported in mixed-substrate systems likely arise from complementary degradation kinetics and improved microbial resilience rather than from changes in intrinsic biodegradability of M-BC biomass alone.

Taken together, the performance of M-BC biomass in anaerobic digestion cannot be attributed to a single cultivation configuration or pretreatment strategy. Instead, methane productivity emerges from the interplay between structural organisation (granular vs. biofilm vs. suspended), biochemical composition (protein, lipid, carbohydrate fractions), EPS distribution, inoculum compatibility, and operational parameters. Pretreatment primarily modifies structural accessibility, whereas co-digestion alters stoichiometric balance and microbial stability. Consequently, comparative evaluation of M-BC systems requires integrated assessment of hydrolysis kinetics, syntrophic interaction efficiency, and energy input requirements. Rather than indicating dominance of any specific configuration, the available evidence suggests that AD performance of M-BC biomass is system-dependent and governed by structural–biochemical coupling mechanisms.

Although many studies report differences in methane yield and inoculum-dependent performance, detailed mechanistic explanations are often limited by the scope of the original experimental design. Variability in AD efficiency likely reflects differences in microbial adaptation history, prior exposure to protein-rich substrates, tolerance to ammonia and secondary metabolites, and the capacity for effective syntrophic interaction between fermentative bacteria and methanogenic archaea. In addition, structural features of the biomass, including EPS density and cell wall accessibility, may modulate hydrolysis rates and influence substrate availability for downstream microbial groups. However, systematic correlations between microbial community structure, EPS composition, and methane productivity remain insufficiently documented in the current literature. Consequently, reported performance trends should be interpreted within the context of these interacting factors, while recognising that direct mechanistic attribution requires further targeted investigation.

Overall, available evidence suggests that microalgae–bacteria biomass can constitute a highly promising substrate for anaerobic digestion under controlled experimental conditions, with reported methane yields ranging from approximately 311 mL CH₄/gVS for ATS biofilms to 561 mL CH₄/gVS for M-BGS after ultrasonic disintegration. However, these values exhibit considerable variability depending on biomass composition, inoculum characteristics, cultivation conditions, and pretreatment intensity. In particular, improvements achieved through ultrasonic or thermal pretreatment must be interpreted in the context of additional energy inputs and potential impacts on net energy balance. AD performance of M-BC biomass is strongly influenced by inoculum quality, microbial community structure, structural maturity of biofilms or granules, hydrolysis kinetics, EPS-related diffusion constraints, and seasonal variability in protein, lipid, and carbohydrate fractions. While integration of wastewater treatment with energy recovery represents an attractive concept, especially in systems combining nutrient removal, biomass production, and biological biogas upgrading, the practical feasibility of such integration depends on validation under pilot- and full-scale conditions. Therefore, although multi-source evidence indicates that M-BC systems may enhance both environmental and energetic efficiency of wastewater facilities, their role in modern biogas technologies should be regarded as promising but conditional upon optimisation of biomass management, control of inhibitory factors, and demonstration of stable long-term operation at scale.

A comparative examination of

Table 5. Characteristics of M-BC biomass used for AD.

Type of M-BC Consortium	TS/DM	VS (%TS or %DM)	TN	TP	C/TOC	C:N Ratio	pH	Protein (%TS)	Lipids (%TS)	Carbohydrates (%TS)	Other Parameters	References
M-BGS (microalgae–bacterial granular sludge), mature granules	TS 59.0 ± 3.1 g/L	82.3 ± 3.5% TS	30.6 ± 3.4 mg/gTS	13.3 ± 2.9 mg/gTS	TOC 397.4 ± 70 mg/gTS	14.4 ± 2.0	7.53 ± 0.07	19.1 ± 2.1	11.1 ± 1.3	n.d.	Chlorella dominance: 57 ± 9% TS	[256,258]
ATS—microalgae–bacteria biomass (July 2021)	DM 38.3%	VS 6.15% DM	–	–	C 2.74% DM	–	–	n.d.	n.d.	n.d.	Calorific value: 16.3 MJ/kgDM	[272]
ATS—microalgae–bacteria biomass (August 2021)	DM 41.1%	VS 5.72% DM	–	–	C 1.86% DM	–	–	n.d.	n.d.	n.d.	Calorific value: 16.9 MJ/kgDM
ATS—biofilm: fractional composition	DM approx. 7.17%	82.35% VS (DM)	–	–	–	C/N = 7.45	–	42.86	3.97	44.39	General ATS biofilm profile
M-BC biomass from H-PBR/wastewater treatment	–	–	TN 52.9 mg/L	TP 26.8 mg/L	TOC 524 mg/L	–	7.24 ± 0.13	n.d.	n.d.	n.d.	NH4+-N = 46 mg/L	[256]

n.d.—no data.

and

Table 6. Operational conditions and performance of AD of M-BC biomass (inoculum, pretreatment, biogas and methane yields).

M-BC Type	AD Temperature	OLR/AD Mode	Inoculum	Pretreatment	CH4 (mL/gVS)	MFR (Nm3/d)	References
M-BGS M-BGS M-BGS	38 °C	batch BMP; 5.0 gVS/L·d batch BMP batch BMP	Anaerobic sludge from CSTR (microalgae-based system)	none	351–365	n.d. n.d. n.d.	[256]
	37–38 °C 37–38 °C		Anaerobic sludge	Ultrasonic disintegration (150 s)	534 ± 16		[258]
			Anaerobic sludge	Ultrasonic disintegration (200 s)	561 ± 17
ATS–UAB ATS–UAB ATS–UAB ATS–UAB	40 °C	batch BMP batch BMP batch BMP batch BMP batch BMP batch BMP batch BMP batch BMP	Inoculum A	none none none none	120 ± 8	1.5 × 10−7	[272]
			Inoculum B		154 ± 8	3.3 × 10−8
			Inoculum C		350	0.5
			Inoculum D		311	2.8
ATS–PAB ATS–PAB ATS–PAB ATS–PAB			Inoculum A	Thermal pretreatment (105 °C, 2 h) Thermal pretreatment (105 °C, 2 h) Thermal pretreatment (105 °C, 2 h) Thermal pretreatment (105 °C, 2 h)	140.5	n.d. n.d. n.d. n.d. n.d. –
			Inoculum B		165.9
			Inoculum C		212.2
			Inoculum D		192.5
Scarcelli 2021 [273]—integrated AD + algal biogas upgrading	35 °C –	pilot-scale	Anaerobic sludge (WWTP) –	none –	n.d.		[273]
M-BC—microalgae (WWTP)		batch BMP; OLR 2.0–2.5 gVS/L·d			180–220		[275]
ABC—microalgae + sludge					250–280

Inoculum: A—pulp and paper biogas plant; B—agricultural biogas plant; C—WWTP anaerobic sludge; D—green waste digestate. n.d.—no data.

reveals substantial heterogeneity in both biomass characteristics and AD performance across different M-BC systems. Variations in TS, VS, protein and lipid fractions, and C/N ratio are directly reflected in methane yields, which range from moderate values (180–220 mL CH₄/gVS in mono-digestion) to exceptionally high yields exceeding 560 mL CH₄/gVS following ultrasonic disintegration of mature M-BGS granules. However, cross-study comparability remains limited due to inconsistent reporting of key performance indicators, including incomplete BMP data, absence of detailed biogas composition in selected studies, and variability in inoculum origin and acclimation status. The pronounced inoculum dependency observed for ATS biofilms indicates that substrate composition alone does not determine AD efficiency, but rather its interaction with microbial community structure and metabolic competence. In addition, differences in pretreatment intensity and associated energy inputs complicate objective techno-economic assessment of the reported methane enhancements. While the compiled data confirm the high bioenergy potential of M-BC biomass, they simultaneously underscore the necessity for harmonised methodological frameworks and comprehensive reporting of biochemical, kinetic, and operational parameters to enable reliable benchmarking and robust scale-up evaluation.

7. Perspectives and Future Research Directions

The prospects for development of technologies based on M-BC are inseparably linked to the need for a comprehensive understanding of the mechanisms governing their susceptibility to anaerobic fermentation. The AD performance of M-BC biomass results from the coupling of multiple parallel biological, ecological, and technological phenomena that remain insufficiently explored. Future research should therefore focus not on isolated elements of consortium functioning, but rather on their linkage with the mechanisms of hydrolysis, acidogenesis, acetogenesis, and the stability of methanogenesis, which ultimately determine BMP and the overall energy efficiency of the process.

One of the key research priorities is the development of holistic models describing consortium functioning, including metabolite exchange, chemical communication, trophic interactions between microalgae and bacteria, and regulatory processes associated with quorum sensing. These phenomena directly affect biomass composition and structure, EPS content, and the relative contribution of readily and poorly biodegradable fractions, thereby controlling hydrolysis rate as the limiting stage in M-BC fermentation. Models integrating microbial ecology with AD kinetics are essential for predicting methanogenic potential of biomass under variable operational and seasonal conditions. Such modelling frameworks should move beyond conventional first-order or Gompertz-type kinetic descriptions and adopt multi-scale approaches that explicitly couple biomass structure, microbial ecology, and process kinetics. In particular, future models should incorporate hydrolysis rate constants linked to EPS density, diffusion resistance, and cell wall recalcitrance, as well as dynamic coupling between fermentative bacteria and methanogenic archaea. Parametrisation of these models requires high-resolution BMP kinetics, quantitative assessment of soluble COD release during pretreatment, and detailed microbial community profiling, including metagenomic or metatranscriptomic analysis to identify functional guild abundance and metabolic potential. Integration of these datasets would enable explicit modelling of EPS–hydrolysis interactions, ammonia tolerance thresholds, and syntrophic efficiency under variable operational conditions. Ultimately, predictive tools for M-BC systems should combine structural, biochemical, and microbial parameters within a unified framework capable of simulating reactor performance across seasonal and scale-dependent variability. Equally important is standardisation and further development of methods for characterisation of M-BC biomass intended for fermentation. BMP values reported in the literature vary widely, largely due to the lack of consistent analytical protocols that account for EPS content, lipids with different degrees of saturation, protein fractions generating ammonia, and polysaccharides with heterogeneous biodegradability. Without detailed knowledge of biomass chemical structure, it is not possible to predict its susceptibility to hydrolysis and, consequently, to determine the actual methane potential under process conditions. Advanced spectroscopic, microscopic, metagenomic, and metabolomic analyses should become standard in M-BC research, as they provide critical insight into components responsible for methanogenesis inhibition, including algal secondary metabolites, phenolic compounds, fatty acids, and quorum-sensing inhibitors.

To ensure comparability and reproducibility across laboratories, a minimal analytical framework for M-BC biomass intended for AD should include: total solids (TS) and volatile solids (VS) content; elemental composition (C, H, N, S) and calculated C/N ratio; fractionation of major biochemical components (proteins, lipids, carbohydrates); and quantitative assessment of EPS content and soluble COD. Reporting should clearly distinguish between fresh, thickened, or pretreated biomass, and specify storage conditions prior to BMP testing. BMP assays should follow internationally recognised protocols, with explicit reporting of inoculum source, inoculum-to-substrate ratio, temperature regime, mixing conditions, and test duration. In addition to cumulative methane yield (mL CH₄/gVS), kinetic parameters derived from appropriate models (e.g., lag phase duration, maximum methane production rate, first-order hydrolysis constants) should be provided to enable meaningful cross-study comparison. Where possible, integration of microbial community characterisation (e.g., relative abundance of key methanogenic and syntrophic taxa) and inhibition indicators (TAN, FAN, VFA profiles) is recommended to support mechanistic interpretation. Adoption of such minimal reporting standards would facilitate meta-analysis, improve model calibration, and accelerate the transition from laboratory-scale experimentation to scale-relevant process evaluation.

A major challenge is the seasonal variability in biomass produced in open systems such as HRAP, which leads to significant differences in chemical composition, EPS contribution, and protein and lipid contents, thereby affecting predicted methanogenic performance. Biomass produced in summer is often characterised by higher photosynthetic carbon and lower nitrogen content, which favours AD, whereas winter biomass may generate higher ammonia concentrations, inhibiting methanogens. The lack of studies incorporating multi-year measurement series limits assessment of long-term AD stability and the identification of optimal strategies for biomass storage, substrate blending, and co-digestion.

Another key direction involves the development of dedicated pretreatment strategies for M-BC biomass. High EPS content and the compact nature of biofilms and granules slow hydrolysis, substantially reducing both methane production rate and ultimate yield. Physical, chemical, biological, and hybrid pretreatment methods should be designed specifically for M-BC structures, as pretreatment targeting EPS degradation, weakening of algal cell walls, or increasing contact surface area may increase BMP by several tens of percent. However, the energy efficiency of such approaches must be evaluated in the context of the overall energy balance of the installation, to avoid situations where BMP gains do not compensate for the additional energy costs associated with pretreatment.

Significant progress is also required in research on reactor configurations, which strongly determine biomass properties and its behaviour during AD. Suspended, biofilm-based, and granular consortia differ in aggregation degree, EPS content, surface-to-mass ratio, and susceptibility to sedimentation and dewatering. Each of these parameters affects biomass preparation for AD, hydrolysis susceptibility, and the balance between biomass production and its energy conversion. In particular, granular consortia show potential to achieve high BMP values; however, their formation mechanisms, mechanical stability, and tolerance to long-term loading remain insufficiently understood.

One of the most critical gaps is the limited number of pilot-scale studies and the near absence of full-scale operational reports. Pilot and demonstration systems provide essential data on real energy costs of mixing, pumping, maintaining light regimes, biomass harvesting, and integrating M-BC production with methane fermentation. The lack of such evidence introduces substantial uncertainty into energy efficiency estimates, and LCA analyses often require simplifications and assumptions that do not reflect real operational conditions. Only full-scale implementation will enable assessment of whether M-BC technologies can be stably applied in real wastewater treatment plants and whether methane yields reported in laboratory studies are reproducible at operational scale. The absence of pilot- and full-scale validation is particularly critical given that light energy input, mixing demand associated with EPS-rich biomass, and dewatering requirements are likely to represent dominant cost drivers under real operational conditions.

Finally, dedicated studies are needed to reduce factors inhibiting AD, particularly ammonia toxicity and inhibition generated by secondary metabolites. Co-digestion of M-BC biomass with carbon-rich substrates, adaptation of the methanogenic microbiome, pH control, and monitoring of hydrolysis kinetics may substantially enhance process stability. Such approaches are essential to ensure that biomass of variable composition, produced by consortia in wastewater-based systems, becomes a stable and predictable energy substrate.

Table 7. Key research gaps and determinants of M-BC performance affecting biomass characteristics and methane fermentation efficiency.

Research Area	Relevance to M-BC Performance	Extended Linkage to AD Performance (BMP, Process Stability, Hydrolysis)
Microbiological interactions (metabolite exchange, QS, trophic dependencies)	Define mass and energy flows within the consortium; modulate microalgal photosynthetic activity and bacterial heterotrophic metabolism; determine trophic balance affecting biomass production and EPS formation.	Determine the fraction of readily biodegradable compounds and thus hydrolysis rate; modulate lipid production (increasing BMP) and protein accumulation (increasing NH3); QS may enhance EPS biosynthesis, thereby slowing AD; some algae–bacteria interactions generate metabolites inhibiting methanogenesis.
Biomass structure: EPS fraction, biofilm formation, granulation, aggregation	Stabilises the system and facilitates settling and biomass recovery; EPS protects cells against stress but increases viscosity and diffusion resistance; granules develop complex oxygen and nutrient microgradients.	EPS reduces hydrolysis rate by 30–50% and requires intensive pretreatment; biofilms limit access of hydrolytic enzymes to microalgal cells; granules often contain higher lipid fractions, increasing BMP (up to 350–560 mL CH4/g VS); excessive EPS may promote foaming during AD.
Biomass chemical composition (proteins, lipids, polysaccharides)	Depends on environmental conditions, N and P availability, light intensity, and growth phase; directly affects the energy value of biomass.	Lipids strongly enhance BMP (up to 1.5× higher CH4 yields than carbohydrate fractions); proteins lead to NH3 formation, which above ~3–4 g NH3/L may inhibit methanogenesis; polysaccharides hydrolyse more slowly, particularly at high EPS content; compositional variability directly translates into BMP variability.
Seasonal variability and effects of environmental parameters	Causes fluctuations in biomass productivity, pigment content, N/C fractions, and EPS production; summer consortia are typically more productive and lipid-rich.	Winter biomass may generate higher NH3 and a higher inhibition risk; in summer, BMP may increase by 10–40% due to higher carbon content; seasonality hinders stable AD feeding and requires co-digestion and biomass storage strategies; lack of long-term datasets limits BMP modelling.
Pretreatment methods for M-BC biomass	Alter EPS structure, increase enzyme access to cells, disrupt aggregates and granules, and enable controlled release of nutrients.	Can increase BMP by 20–80%, especially for EPS-rich biomass; ultrasonication intensifies hydrolysis but entails high energy costs; PEF and cavitation may be more energy-efficient; enzymatic pretreatment can selectively target EPS; pretreatment effectiveness depends on consortium structure.
Reactor configurations (suspended, biofilm-based, granular)	Determine consortium formation pathways, biomass stability, achievable concentration, and separation efficiency; affect oxygen microgradients, relative CO2 availability, and microbe–microbe interactions.	Granular systems may reach BMP up to 350–560 mL CH4/g VS; biofilms show low hydrolysability without intensive pretreatment; suspended systems produce biomass with higher enzyme-accessible surface area but lower stability; configuration controls EPS abundance and aggregate structure, thereby shaping AD performance.
Secondary metabolites of microalgae and bacteria (phenolics, toxins, QS inhibitors)	Influence interspecies competition, suppress selected microorganisms, and modulate biofilm architecture; production increases under stress conditions.	May inhibit hydrolysis and reduce acetogenic and methanogenic activity; some metabolites can fully destabilise fermentation; under wastewater conditions, metabolite levels are largely unknown, increasing BMP uncertainty.
Ammonia and other inhibitory factors	Mainly result from high protein content and intensive degradation of N-organic fractions; depend on biomass composition and seasonality.	Excess NH3 inhibits methanogenesis above ~3 g/L; mitigation requires C:N adjustment, co-digestion, microbiome adaptation, and pH stabilisation; abrupt NH3 increases may reduce BMP by 30–60%.
Lack of pilot- and full-scale studies	Creates uncertainty regarding consortium stability under operational conditions (load fluctuations, wastewater quality, environmental variability); laboratory setups do not reflect real process costs.	Prevents determination of real BMP, energy losses, and costs of lighting, mixing, and biomass separation; limits verification whether laboratory BMP improvements translate into a positive net energy balance; hampers forecasting of long-term AD stability.
Need for models integrating consortium biology with AD kinetics	Would enable prediction of consortium dynamics, shifts in microalgae/bacteria ratios, and production of EPS and secondary metabolites.	Allow forecasting of BMP, hydrolysis stability, organic loading thresholds, and optimal AD conditions; absence of such models prevents precise system design and scale-up.
Integration of M-BC systems with AD facilities	Requires development of an integrated technological chain (biomass growth, thickening, dewatering, and conversion in AD); design standards remain limited.	Energy losses, optimal mixing parameters, effects of biomass recirculation, and real hydrolysis efficiency remain uncertain; lack of long-term evidence prevents estimating durability and performance of the integrated process.
Need for robust datasets for LCA/TEA	Laboratory data do not capture emissions, process losses, operating costs, or biomass structural variability; they do not represent full-scale performance.	LCA requires real data on energy and methane losses, dewatering efficiency, actual BMP, and operating costs; missing evidence prevents assessment of whether AD of M-BC biomass provides environmental and economic advantages over conventional activated sludge systems.

shows key research gaps and determinants of M-BC performance affecting biomass characteristics and methane fermentation efficiency.

8. Summary and Conclusions

An analysis of the available studies indicates that M-BC systems constitute a potentially valuable biotechnological platform for wastewater treatment and bioenergy integration. Evidence from laboratory and selected pilot-scale investigations suggests that synergistic interactions between microalgae and bacteria can enhance nutrient removal efficiency, particularly for nitrogen and phosphorus, while potentially reducing aeration demand under optimised conditions. These consortia demonstrate substantial capacity for nutrient assimilation, photosynthetic oxygen production, and microbiological stabilisation; however, the extent to which these advantages are maintained under variable operational and full-scale conditions remains to be systematically validated. Importantly, pollutant removal is coupled with biomass generation that may exhibit significant methane potential, offering opportunities for integration of wastewater treatment with energy recovery. Nevertheless, variability in biomass composition, EPS-related hydrolysis constraints, potential inhibitory metabolites, and limited pilot-scale validation indicate that the practical implementation of M-BC systems should be regarded as conditional upon further technological optimisation and scale-relevant verification. Current evidence suggests that consortium structure, including EPS content and spatial organisation, aggregation degree, formation of biofilms or granules, and trophic interactions, plays an important role in treatment stability and in shaping the quality of the produced biomass. The general influence of biomass composition, particularly lipid and protein fractions, as well as seasonal variability and environmental conditions, on fermentation susceptibility and methane production is widely recognised. However, the magnitude of these effects varies across operational contexts and cultivation systems.

Pretreatment methods have been reported to enhance the biodegradability of M-BC biomass, especially in systems characterised by elevated EPS content; nevertheless, improvements in methane yield depend on both structural accessibility and energy input associated with the applied strategy. Similarly, cultivation configuration, whether suspended, biofilm-based, or granular, affects substrate properties and behaviour during AD, but its influence should be interpreted as context-dependent rather than universally predictive. Although several laboratory-scale studies report higher methane potentials for granular biomass, such observations require further validation under pilot- and full-scale conditions before broader generalisation can be made. One of the most important conclusions of this review is that the majority of available evidence originates from laboratory-scale studies, which limits the ability to assess whether the reported benefits in wastewater treatment and energy recovery can be reproduced under real operational conditions. The scarcity of pilot-scale and full-scale investigations hinders systematic evaluation of key performance indicators such as net energy balance, long-term process stability, tolerance to fluctuating organic loading rates (OLR), resilience to seasonal variations in biomass composition, and volumetric methane productivity under continuous operation. Furthermore, scale validation should include assessment of operational energy demand related to mixing, light supply (where applicable), biomass harvesting, dewatering, and pretreatment, as well as monitoring of ammonia accumulation, VFA profiles, and inhibitory metabolite dynamics over extended time periods. The absence of such comprehensive datasets reduces the robustness of LCA and TEA analyses, which currently rely on assumptions regarding process losses, energy consumption, and emissions under real-scale conditions.

In summary, the current state of knowledge confirms that M-BC combine two key features required in modern water and wastewater technologies, high pollutant removal efficiency and the ability to produce biomass with high methane potential, enabling integration of treatment and energy recovery within a single system. This constitutes their main advantage over conventional technologies. At the same time, the literature indicates that full exploitation of their potential requires a transition from laboratory research towards operational-scale validation, as only such evidence will enable comprehensive assessment of the energy, process, and environmental performance of M-BC biomass.