Integrated Pretreatment and Microbial Matching for PHA Production from Lignocellulosic Agro-Forestry Residues

Abstract

Lignocellulosic agro-forestry residues (LARs), such as rice straw, sugarcane bagasse, and wood wastes, are abundant and low-cost feedstocks for polyhydroxyalkanoate (PHA) bioplastics. However, their complex cellulose–hemicellulose–lignin matrix requires integrated valorization strategies. This review presents a dual-framework approach: “pretreatment–co-substrate compatibility” and “pretreatment–microbial platform matching”, to align advanced pretreatment methods (including deacetylation–microwave integration, deep eutectic solvents, and non-sterilized lignin recovery) with engineered or extremophilic microbial hosts. A “metabolic interaction” perspective on co-substrate fermentation, encompassing dynamic carbon flux allocation, synthetic consortia cooperation, and one-pot process coupling, is used to elevate PHA titers and tailor copolymer composition. In addition, we synthesize comprehensive kinetic analyses from the literature that elucidate microbial growth, substrate consumption, and dynamic carbon flux allocation under feast–famine conditions, thereby informing process optimization and scalability. Microbial platforms are reclassified as broad-substrate, process-compatible, or product-customized categories to emphasize adaptive evolution, CRISPR-guided precision design, and consortia engineering. Finally, next-generation techno-economic analyses, embracing multi-product integration, regional adaptation, and carbon-efficiency metrics, are surveyed to chart viable paths for scaling LAR-to-PHA into circular bioeconomy manufacturing.

1. Introduction

The urgent need to replace fossil-derived plastics has propelled the development of polyhydroxyalkanoates (PHA)—microbially produced, biodegradable polyesters with tunable mechanical and barrier properties—toward commercial reality (Figure 1) [1,2,3]. Global plastic production now exceeds 360 million tons per year, of which only a small fraction is recycled, while the majority accumulates in landfills or natural environments. PHA offers a sustainable alternative, decomposing into non-toxic end products and demonstrating compatibility with existing processing technologies [4]. However, high feedstock and process costs, often accounting for more than 50% of total production expenses, have limited widespread adoption [5].

Among prospective carbon sources, lignocellulosic agro-forestry residues (LARs) such as rice straw, sugarcane bagasse, corn stover, and forestry by-products represent one of the most abundant and low-cost feedstock pools (Figure 1), with an estimated global annual production exceeding 1.3 billion tons. These residues contain 35–50% cellulose, 20–35% hemicellulose, and 5–30% lignin, offering a rich source of fermentable sugars alongside aromatic by-products. However, the complex and recalcitrant nature of lignin-shielded carbohydrates presents a formidable challenge for microbial conversion [6,7]. Traditional pretreatments, acid/alkaline hydrolysis, steam explosion, and organosolv processes have been developed to disrupt biomass structure and release monomeric sugars, but they often generate inhibitory compounds and incur high energy or chemical inputs [8]. Recent advances in pretreatment technologies, including deacetylation–microwave (DEA–MW) integration, deep eutectic solvent (DES) extraction, and non-sterilized lignin recovery, have demonstrated improved sugar yields and reduced inhibitor formation [9,10]. Concurrently, microbial platforms have evolved from single-substrate specialists to broad-substrate strains and engineered consortia capable of co-utilizing mixed sugars, volatile fatty acids (VFAs), and lignin-derived aromatics [11,12,13,14]. Co-substrate fermentation strategies now exploit dynamic feeding, synthetic community interactions, and one-pot process coupling to maximize polymer yield and tailor copolymer composition.

Unlike earlier reviews, which addressed pretreatment, fermentation, or techno-economics in isolation [3,4,6], this work integrates these dimensions via three novel contributions. First, we introduce two analytical frameworks, “pretreatment-co-substrate compatibility” and “pretreatment-microbial platform matching”, to align biomass fractionation with downstream microbial metabolism. Second, we apply a “metabolic interaction” perspective that unifies dynamic carbon flux allocation, synthetic consortia synergy, and consolidated one-pot processing. Third, we propose a function-oriented classification of microbial platforms that are broad-substrate, process-compatible, and product-customized, highlighting advances in kinetic modeling of feast–famine dynamics as well as precision PHA design through CRISPR and adaptive evolution. Finally, we survey next-generation techno-economic analyses, from multiproduct integrations and regional adaptability to carbon-efficiency metrics and demand-driven value chains, to chart realistic pathways for translating laboratory innovations into industrial-scale, circular PHA biorefineries.

To clarify the novelty and positioning of this review,

Table 1. Comparative summary of recent LAR-to-PHA reviews in terms of scope, pretreatment coverage, microbial coverage, and TEA depth.

Review (First Author, Year)	Scope	Pretreatments Coverage	Microbial Coverage	TEA Depth
Ciesielski et al., 2015 [2]	Review of plant oils (including waste oils) as PHA feedstocks, covering PHA structures, metabolic pathways, microbial species, fermentation strategies, material properties, and economic aspects	Focused on oil-based feedstocks; no systematic discussion of lignocellulosic pretreatments; only brief mention that oil by-products may require simple processing	Various pure cultures (Cupriavidus, Pseudomonas, Bacillus, etc.); mentions mixed microbial cultures (MMC) and some engineered strains	Brief qualitative discussion of cost components (feedstock, downstream recovery); no quantitative TEA modeling
Li et al., 2025 [4]	Systematic review of full lignocellulosic fractions (cellulose, hemicellulose, lignin) to PHA, covering feedstock-metabolism-engineering-TEA-life cycle assessment (LCA)	Comprehensive coverage of physical, chemical (acid/alkali/organic solvent/ionic liquid/DES), physicochemical (steam explosion/hydrothermal), and biological pretreatments; tables comparing pros/cons, sugar/inhibitor yields, and PHA outputs	Wide range of pure cultures (Cupriavidus, Ralstonia, Halomonas, Pseudomonas, etc.), MMC, and engineered strains; includes feedstock-strain-product mapping	Dedicated TEA section citing multiple quantitative TEAs (CAPEX, OPEX, MSP, sensitivity analysis) and integrated with LCA (GHG, energy use, downstream processing)
Andler et al., 2021 [6]	Review of fruit residues as sustainable feedstock for PHA production, including biochemical pathways, pretreatments, production yields, and biotechnological aspects	Focus on fruit residues; covers physical, chemical (acid, alkali, ionic liquids), enzymatic, and biological pretreatments; tables summarizing pretreatment methods and effects	Various pure cultures (Cupriavidus, Bacillus, Halomonas, Pseudomonas, Pandoraea, etc.), some co-cultures; includes both PHB and mcl-PHA producers	Brief mention of techno-economic and environmental analysis in the context of banana residues; no dedicated or quantitative TEA section
Wang et al., 2021 [7]	Review of agricultural wastes (including lignocellulose, lipids, molasses, whey, etc.) for PHA production, covering fermentation parameter optimization, kinetic modeling, and circular utilization	Detailed discussion of acid/alkali/physical/enzymatic/ultrasound/microwave pretreatments; tables summarizing different feedstocks and pretreatment effects	Multiple pure cultures (Bacillus, Paracoccus, Burkholderia, Halomonas, etc.), some inhibitor-tolerant strains, engineered strains; includes MMC	No dedicated TEA section; only mentions cost factors in conclusions; no quantitative analysis
This study	Comprehensive review of LAR-to-PHA covering feedstock properties, advanced pretreatment (including green solvents and non-sterile strategies), co-substrate blending, microbial platform selection (pure, mixed, engineered), kinetic modeling, and integrated TEA; provides practitioner frameworks and decision tools	High coverage: systematic comparison of conventional (acid/alkali/steam), green (DES, ionic liquid, MW-assisted), and non-sterile pretreatments; detailed discussion of inhibitor management and process integration	Broad: pure cultures (Cupriavidus, Bacillus, Halomonas, Pseudomonas, etc.), MMC, extremophiles, and engineered strains; explicit mapping of substrate-platform-product relationships; focus on process-compatible and product-customized platforms	Medium-high: dedicated TEA section with regional scenario analysis, MSP/payback sensitivity, coproduct valorization

benchmarks it against recent LAR-to-PHA reviews in terms of scope, pretreatment coverage, microbial coverage, and techno-economic analysis (TEA) depth. While earlier works have provided valuable insights into specific feedstocks, pretreatment methods, or microbial systems, none combine comprehensive coverage of advanced pretreatments (including green solvents and non-sterile strategies), co-substrate blending, microbial platform selection, kinetic modeling, and integrated TEA within a unified practitioner-oriented framework. This work uniquely integrates these elements and provides actionable decision tools to guide process design from feedstock properties to expected PHA monomer profiles.

2. Diversity of PHA Monomer Structures and Resulting Properties

Polyhydroxyalkanoates (PHA) are a diverse family of biodegradable polymers synthesized by microorganisms from various carbon sources. These biopolymers have gained significant attention as promising alternatives to petrochemical-based plastics due to their exceptional biocompatibility, biodegradability, and mechanical properties [15]. Numerous Gram-positive and Gram-negative bacteria, including Methylotrophs, Rhodospirillum, Pseudomonas, Azotobacter, Alcaligenes, Bacillus, and Cupriavidus (Figure 1), can accumulate PHA under nutrient-imbalanced conditions (excess carbon with nitrogen limitation) [16]. PHA can be broadly categorized into two groups based on the length of their monomer chains: short-chain length PHA (scl-PHA, C3-C5) and medium-chain length PHA (mcl-PHA, C6-C14). Notable examples of scl-PHA include poly(3-hydroxybutyrate) [P(3HB)], poly(4-hydroxybutyrate) [P(4HB)], and poly(3-hydroxyvalerate) [P(3HV)], while mcl-PHA includes poly(3-hydroxypropionate) [P(3HP)], poly(3-hydroxyoctanoate) [P(3HO)], and poly(3-hydroxydecanoate) [P(3HD)], etc. [17]. Copolymers, such as poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV), poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBH), and poly (3-hydroxybutyrate-co-4-hydroxybutyrate) (P34HB), combine different monomers to achieve enhanced mechanical properties compared to P(3HB) homopolymers [18].

The physicochemical properties of PHA are highly influenced by their monomer composition, resulting in distinct profiles for scl-PHA and mcl-PHA. For instance, P(3HB) has a glass transition temperature (T_g) of ~4 °C and a melting temperature (T_m) of ~180 °C, with elongation at break < 10%, whereas mcl-PHA exhibits Tg between −5 °C and 0 °C, Tm ~50–60 °C, and elongations > 200% (Figure 2) [18,19]. However, the low tensile strength and limited thermal stability of mcl-PHA restrict their potential in broader industrial uses. The development of PHA copolymers, by incorporating specific monomers such as 4HB or 3HV, has proven effective in enhancing both thermal stability and mechanical properties, enabling broader application [20].

Despite the promising material properties of PHA, the high production costs remain a significant challenge. Therefore, it is of great significance to research and develop economical and feasible PHA production strategies, especially the development of low-cost sustainable carbon sources [4].

3. Integrated Utilization of LAR-Derived Substrates for PHA Production

Lignocellulosic agro-forestry residues (LARs), including sugarcane bagasse, rice straw, corn stover, and wood residues, have garnered significant attention as sustainable and cost-effective feedstocks for PHA production owing to their wide availability [23]. These residues predominantly consist of cellulose (35–50%), hemicellulose (20–35%), and lignin (5–30%). Although the robust structure imparted by lignin helps maintain biomass integrity, it also hampers enzymatic hydrolysis by restricting carbohydrate accessibility. Conventional pretreatment techniques encompass mechanical (e.g., milling, microwave-assisted), physicochemical (e.g., steam explosion, wet oxidation), chemical (e.g., acid and alkaline hydrolysis), ionic–liquid, and biological methods (

Table 2. Critical discussion on the advantages and disadvantages of various pretreatment methods for LARs.

Type	Pretreatment Method	Advantage	Disadvantage	Criticism	Ref.
Physical Pretreatment	Mechanical pretreatment	Effective reduction of particle size and cellulose crystallinity	High energy consumption	High operational costs, potential clogging in downstream processes	[25,26]
	Microwave pretreatment	High thermal efficiency and low energy consumption	High cost	Uneven energy distribution, inconsistent treatment effectiveness	[27]
	Liquid hot water pretreatment	Green, economical, and easy to operate	Residual lignin reduces enzymatic digestion effectiveness	Incomplete lignin removal requiring post-treatment steps	[28,29]
	Ultrasonic pretreatment	Low energy consumption and cost	Unfavorable to enzymatic hydrolysis	Negative effects on enzyme efficiency, cavitation can produce inhibitors	[24]
Chemical Pretreatment	Acid pretreatment	Improved cellulose accessibility	High corrosiveness	Formation of toxic by-products, requires neutralization	[30,31]
	Alkali pretreatment	Effective for delignification	Difficult to treat wastewater	Wastewater disposal challenges, limited efficacy on high-lignin feedstocks	[32,33]
	Ionic liquid pretreatment	Environmentally friendly and thermally stable	High cost	Difficulty in recovery	[34,35]
	Organic solvent pretreatment	Efficient for hemicellulose dissolution and lignin removal	Solvent flammability and operational hazards	Expensive solvents, complex solvent recovery	[36,37]
	Ozone pretreatment	Effective lignin removal	High operational cost	Formation of unwanted by-products	[38,39]
Physico- Chemical Pretreatment	Steam pretreatment	Effective hemicellulose dissolution, cost-effective	High temperature and pressure	High energy consumption, sugar degradation, equipment corrosion risks	[40,41]
	Ammonia fiber expansion pretreatment	Increased cellulose accessibility	Inefficient for biomass with high lignin content	Ammonia recovery inefficiency and process scalability challenges	[24]
	Supercritical fluids pretreatment	Environmentally green	High capital and maintenance costs	Specialized equipment required, limited applicability to industrial-scale operations	[24]
	Wet oxidation pretreatment	Efficient lignin removal	Control of process parameters and high energy cost	Formation of inorganic salts complicating downstream processing	[24,36]
Biological Pretreatment	Microbial pretreatment	Lignin removal with low energy consumption	Slow degradation rate, environmental sensitivity	Reduced carbon yield, slower degradation process	[42,43]
	Enzyme pretreatment	High substrate specificity with minimal by-product formation	High enzyme costs and susceptibility to inhibition	Optimization challenges for mixed-substrate systems	[44,45]

), with specific acid/alkaline strategies detailed in

Table 3. Selected LAR pretreatments and PHA outcomes reported in the literature.

Substrate	Pretreatment Strategy	Pretreatment Result	PHA Production, g/L	PHA Content, wt%	Ref.
Sugarcane Bagasse	1% H2SO4 at 121 °C for 40 min	Sugar yield: 569.0 mg/g	6.38	70.0	[46]
Corn Stover	1 M HCl at 110 °C for 40 min	Sugar concentration: 18.7 g/L	0.82	38.7	[47]
Pine Sawdust	1 M HCl at 110 °C for 40 min	Sugar concentration: 8.93 g/L	1.00	46.9	[47]
Rice Straw	0.5% H2SO4 at 121 °C for 40 min	Sugar concentration: 19.6 g/L	1.50	32.6	[48]
Wheat Biomass	2% NaOH at 100 °C for 3 h	Sugar yield: 418.0 mg/g; Hydrolysis yield: 64.3%	5.67	67.5	[49]
Rice Husks	1.0 mol/L KOH at 121 °C and 0.1 MPa for 15 min	Sugar concentration: 20.0 g/L	3.90	50.0	[50]
Wheat Bran	1% NaOH at 121 °C for 30 min	Sugar concentration: 62.9 g/L	2.69	43.8	[51]
Oil Palm Fruit	10 g/L NaOH at 121 °C for 60 min	Sugar concentration: 78.1 g/L	2.72	43.1	[52]
Rice Straw	20% NH3 at 80 °C for 10 h and enzymatic at 50 °C for 40 h	Maximum delignification: 63%; Glucan conversion: 92.0%	2.96	59.3	[53]
Rice Husks	0.4% H2SO4 at 100 °C for 30 min and steam explosion of 1.8 MPa for 5 min	Sugar yield: 266.5 mg/g	5.00	-	[54]

[4,24]. In this section, we focus exclusively on the characteristics of pretreatment hydrolysates, namely sugar and VFA concentrations, lignin recovery, and inhibitor levels, and how these parameters determine suitability for downstream co-substrate fermentation.

3.1. Pretreatment-Co-Substrate Compatibility for PHA Production

Under the pretreatment-co-substrate compatibility framework, three key performance metrics are evaluated in concert: substrate profile (concentrations and molecular-weight distributions of fermentable sugars and soluble lignin), inhibitor levels (e.g., phenolics and acetic acid), and co-substrate utilization potential of lignin-derived aromatics. For example, a combined deacetylation–microwave (DEA–MW) pretreatment of rice husk achieves 95.5% deacetylation and 45.3% delignification while recovering 72.2% of lignin [10]. A DES cocktail of betaine-glycerol and choline chloride-oxalic acid (or choline chloride-acetamide), applied to corn stover, achieved 89.5% glucan and 75.4% xylan digestibility. The pretreatment enlarged substrate pores, improving enzyme accessibility, and the DES mixture was recyclable over multiple cycles [25]. Similarly, a non-sterilized lignin (NSL) strategy yielded lignin-rich hydrolysates compatible with extremophiles such as Halomonas alkalicola M2, enabling a record P(3HB) titer of 1.89 g/L via a separate hydrolysis-fermentation (SHF) process [9]. These representative metrics illustrate how pretreatment choices shape the chemical composition and inhibitory compounds of LAR hydrolysates, thereby defining their compatibility with mixed-carbon PHA fermentation processes.

In addition to substrate composition and sugar yield, the formation of inhibitory compounds during pretreatment is a critical factor affecting co-substrate compatibility and overall process efficiency. These inhibitors include weak acids (e.g., acetic, formic, levulinic acids), phenolics, and furans (furfural, 5-hydroxymethylfurfural), which can disrupt pH homeostasis, damage membranes, denature proteins, and inhibit key metabolic enzymes [55]. Mild pretreatments such as hot-water processing yield low-inhibitor hydrolysates that support stable PHA production [56], whereas harsher methods often require detoxification. Physical/chemical strategies, including activated carbon, biochar, and resin adsorption, effectively reduce inhibitor levels and improve titers [57,58], though cost and adsorbent recovery remain challenges [59]. Alternatively, tolerant strains such as Bacillus megaterium B-10 enable direct fermentation of inhibitor-rich hydrolysates [48]. Quantifying inhibitor profiles alongside sugar yields is essential for accurate pretreatment-co-substrate compatibility assessment.

To bridge feedstock characterization and microbial platform selection, a practitioner-oriented decision flowchart is provided (Figure 3). It translates the two proposed frameworks into a stepwise pathway from feedstock properties through pretreatment choice, co-substrate blending, and platform matching, ending with an expected PHA monomer profile. An optional TEA step is included as a preview of the economic assessment discussed in Section 7.

3.2. Pretreatment-Microbial Platform Matching for PHA Production

According to the pretreatment–microbial platform matching principle, pretreatment outputs must be aligned with the specific metabolic capacities and tolerance profiles of the chosen microbial hosts. High-sugar/low-inhibitor streams (>50 g/L hexoses; <0.5 g/L phenolics) are ideally fed to high-yield sugar-utilizing strains. Aromatic-rich streams (2–5 g/L lignin monomers) require organisms equipped with the β-ketoadipate pathway [60]. High-inhibitor or non-sterile lignin streams (>1 g/L total phenolics) demand extremophilic or in situ detoxification-capable hosts. High-sugar platform example: Caldimonas thermophilum DSM 15344 achieved 1.59 g/L biomass and 0.70 g/L P(3HB) on sugar-rich hydrolysates [61]. Aromatic-platform example: Pseudomonas putida KTYY06 produced 2.46 g/L PHA (91.4 mol% 3HO) in fed-batch fermentations on lignin monomer feeds [14]. Burkholderia cepacia B12 reached 1.42 g/L PHA in high-phenolic lignin streams under fed-batch conditions [62].

These cases demonstrate that directing each carbon fraction from LAR hydrolysates to its metabolically best-suited host maximizes overall PHA yield and quality. Figure 4 illustrates how distinct hydrolysate compositions map onto these functional platform categories.

In summary, distinguishing between co-substrate compatibility (evaluating pretreatment output quality) and platform matching (aligning outputs to host capabilities) establishes a clear upstream decision-making sequence. This ensures that hydrolysate chemistry is optimally paired with microbial metabolism, laying the groundwork for the platform-specific strategies in the following sections.

4. Functionally Oriented Microbial Platforms for PHA Production

In the context of pretreated LAR hydrolysates, often containing 50–80 g/L fermentable sugars, 2–5 g/L VFAs, and 0.5–2 g/L phenolic inhibitors, microbial hosts can be grouped by the industrial functions they best perform: substrate versatility, process compatibility, and product customization. Figure 4 maps the key routes from LAR-derived glucose, xylose, VFAs, and lignin aromatics into PHA monomers, providing the mechanistic basis for this functional classification. Traditional “pure vs. mixed culture” labels do not capture the nuances of hosts capable of valorizing chemically complex, inhibitor-laden feeds.

4.1. Broad-Substrate Microorganisms: From Single Carbon Sources to Complex LAR Hydrolysate

Broad-substrate platforms simultaneously co-assimilate mixed sugars, VFAs, and lignin-derived aromatics from real hydrolysates, overcoming catabolite repression and maximizing carbon recovery. Engineered Pseudomonas putida KT2440 demonstrates broad-substrate versatility, producing 1.38 g/L mcl-PHA under mixed-sugar/phenolic conditions and maintaining >80% viability at 1 g/L total phenolics [63]. Further metabolic rerouting (PHA depolymerase knockout, β-oxidation blockade) doubled titers on aromatic-rich streams [64]. Shewanella marisflavi BBL25 converted barley straw hydrolysate to 3.3 g/L P(3HB) in shake flasks and reached 6.3 g/L under microbial fuel cell conditions [65]. Cupriavidus necator grown on lignin-aromatic blends to yield 4.50 g/L P(3HB) [66]. Despite titers up to 4.5 g/L, broad-substrate strains often require in-line detoxification to maintain performance on inhibitor-rich industrial liquors.

4.2. Process-Compatible Microorganisms: Extremophiles and Resilient Consortia

Extremophiles and resilient consortia tolerate high inhibitor loads and operational stresses, making them ideal for minimizing sterilization costs, operating under non-sterile conditions, and enabling continuous or semi-continuous production modes. Halophiles such as Haloferax mediterranei, cultivated at ~20–25% (w/v) total salts, accumulate up to 87.5 wt% PHBV from γ-butyrolactone [67,68,69], while Halomonas alkalicola M2, grown at ~10% (w/v) NaCl, achieves 58.5% lignin degradation and 1.89 g/L P(3HB) in non-sterilized media [9]. Thermophiles such as Caldimonas taiwanensis (45 °C) and Thermus thermophilus HB8 (75 °C) maintain activity at elevated temperatures [70,71]. C. taiwanensis can fine-tune 3HV content from 10–95 mol% [72]. Halomonas cupida J9, cultivated at 8% (w/v) NaCl, ferments unsterile corn-straw hydrolysate (>1 g/L phenolics) to 2.45 g/L PHA in 5 L reactors [73]. Defined mixed consortia enriched on VFA-rich hydrolysates reach up to 89 wt% PHA [74,75].

The core industrial advantage of this category is distinguished by process robustness rather than substrate breadth, and its optimization focuses on stability controls (population balance, quorum-quenching, adaptive regulation) rather than expanding substrate range.

4.3. Product-Customized Microorganisms: Tailoring PHA Composition and Properties

These platforms are engineered or selected primarily for precise control over monomer composition, molecular weight, and polymer properties, often for high-value or application-specific markets. Tools include modular biosynthetic cassettes for targeted monomers (3HV, 4HB, mcl-PHA). CRISPR interference (CRISPRi) is a gene-regulation approach that uses a catalytically inactive Cas protein guided by RNA to block transcription without cutting DNA. This enables precise and reversible control of target gene expression to redirect flux. Other strategies involve metabolite-responsive promoters for dynamic control [76]. Pseudomonas putida KTYY06 produces 91.4 mol% 3HO copolymer at 2.46 g/L in fed batch mode [14]. In Haloferax mediterranei, CRISPRi knock-down of citrate synthase increased PHBV yield by 76.4% and further enhanced productivity when paired with integrated crRNA modules [76]. Adaptive laboratory evolution (ALE)-evolved Pseudomonas putida strains achieve a 45% titer increase on mixed sugars while retaining narrow molecular weight distributions and target ratios [77].

These precision platforms enable custom PHA for applications ranging from flexible packaging to medical devices. However, extensive genetic modification can undermine stability, and regulatory hurdles for GMOs remain steep. Pairing in-line quality sensors (e.g., Raman soft-sensors) with stabilizing modules (e.g., toxin-antitoxin systems) will be essential to secure consistent polymer specifications in 10–50 L pilot runs and beyond. Together, these broad-substrate, process-compatible, and product-customized platforms exemplify our pretreatment-microbial platform matching framework, ensuring that each host selection aligns with the specific properties of LAR-derived streams.

5. Integrated Co-Substrate Strategies from “Metabolic Interaction” Perspective

The metabolic interaction framework synchronizes sugars, volatile fatty acids (VFAs), and lignin-derived aromatics through real-time carbon-flux modeling, in-line substrate sensing, and feedback-driven feed control. This approach prevents catabolite repression and stabilizes cross-feeding dynamics in both monocultures and defined consortia. Figure 4 provides a roadmap for this concept, illustrating how synchronizing flux through these branch-points underlies the 25–60% titer gains achieved by dynamic co-feeding (up to 2.5 g/L), improves copolymer composition precision by 15–25 mol%, and reduces by-products by 20–30% versus static feeds. Lab-scale yields of 2.30–2.50 g/L, with confirmation in 100 L pilot reactors, underscore its industrial feasibility [78]. By moving beyond simple co-substrate blending, the metabolic-interaction strategy leverages deliberate flux distribution, designed community interplay, and tight unit-operation coupling to deliver both mechanistic insights and measurable process gains.

5.1. Carbon Flux Distribution Optimization

Dynamic feeding involves programming substrate addition rates or concentrations over time to impose controlled feast–famine cycles, while metabolic switching describes the cellular shift from biomass growth toward PHA accumulation under nutrient-limiting signals. At the shake-flask scale, engineering Halomonas bluephagenesis with an integrated xylA–xfp pathway enabled co-utilization of glucose and xylose from LAR hydrolysate, reaching 15 g/L cell dry weight (CDW) with 76 wt% P(3HB). In 7 L fed-batch reactors, the same strain maintained 62 g/L CDW with 67 wt% P(3HB) [79]. Under feast–famine regimes, a three-stage cyclic fed-batch of Bacillus thuringiensis on glucose-rich hydrolysate delivered ~21 g/L CDW and 14.3 g/L PHA, a 3–4-fold improvement over batch culture [80]. Complementary studies varying co-substrate blends, such as timed acetate pulses, which raised titers to 2308 mg/L [78] or octanoate triggers yielding 1834 mg COD/L terpolymers [12], demonstrate how targeted feed profiles steer flux to distinct PHA products.

Overall, these cases show that controlled carbon-flux patterns markedly improve substrate conversion efficiency and polymer quality, though scaling up demands cost-effective sensing solutions and compensation for sensor-response lag in large reactors.

5.2. Microbial Community Interactions

Synthetic consortia (i.e., defined co-cultures of two or more microbial strains engineered to partition distinct metabolic tasks) unlock synergistic conversions beyond monocultures. Pretreated wood VFAs as the co-substrate doubled 3HV incorporation, reaching 3088 mg COD/L, while preserving diversity in sequential reactors [11]. Hemicellulose hydrolysate feeds (45% pentose/50% acetate) enabled simultaneous levulinic acid and P(3HB) synthesis, with feed composition shaping both yields and dominant genera [81]. Agro-residue slurries (pea shell, onion peel) illustrate nutritional symbiosis: defined Bacillus co-cultures produced up to 1.65 g/L PHBV, and propionate supplementation increased 3HV fractions [82]. These examples confirm that cross-feeding and niche specialization can enhance resilience and product tailoring, but that long-term stability under cyclic feeding often requires engineered control of population ratios or simplified process logic to prevent drift and “cheater” dominance.

5.3. Process Coupling Innovations

Fully integrated bioprocesses merge pretreatment, fermentation, and analytics in one pipeline. One-pot sugar-to-aromatic systems under nitrogen limitation achieve 35% lignin conversion and 39 mg PHA/g lignin in a single reactor [13]. Coupling mixed-sugar/phenolic hydrolysate feeds with continuous fermentation minimizes solids handling and enzyme dosing, simplifying the overall process flow [10]. Blending hemicellulose-rich and lignin-rich hydrolysates in one reactor enabled Paraburkholderia sacchari IPT 101 to detoxify inhibitors in situ and reach 6.7 g/L CDW with 71 wt% P(3HB) in 48 h [83]. Beyond unit-operation integration, in-line Raman spectroscopy in Cupriavidus necator tracks biomass, PHA content, and molecular weight with root mean squared errors (RMSEs) of 3.7 g/L (CDW), 14 wt% (PHA), and <1.2 × 10⁵ g/mol (Mw), enabling dynamic feed control and quality assurance [84].

By combining pretreatment, fermentation, and real-time analytics, these innovations highlight the pathway to seamless, end-to-end biorefineries. However, achieving this vision at scale demands fault-tolerant, modular process architectures. Such architectures must accommodate variable pH, temperature, and flow conditions across different unit operations.

6. Kinetic Study for PHA Production, Cell Growth, Carbon Source Consumption

Dynamic kinetic models play a central role in optimizing PHA biosynthesis under feast–famine regimes by quantitatively linking feeding strategies to microbial growth and polymer accumulation. All kinetic model equations, key parameters, and variable definitions are summarized from published studies and provided in

Table 4. Kinetic model equations, key parameters, and definitions for PHA production.

Key Model (Equation)	Key Kinetic Parameter	Definition of Parameters	Operational Context	Ref.
${\displaystyle \frac{dx}{dt}}={\mu }_{max}x\left(1-{\displaystyle \frac{x}{x_{max}}}\right)$ ${\displaystyle \frac{dP}{dt}}=\alpha {\displaystyle \frac{dx}{dt}}+\beta xP$	$x_{max}=13.3340\mathrm{g}/\mathrm{L}$  ${\mu }_{max}=0.1898h^{-1}$	x: Biomass (g/L); xmax: Max biomass (g/L); μmax: Max growth rate (h−1); α: Growth-associated coefficient; β: Non-growth-associated coefficient	C. necator, rubber seed oil, 30 °C, pH not controlled, batch	[86]
$-{\displaystyle \frac{dS}{dt}}=a{\displaystyle \frac{{\mu }_{m}S}{K_S+S}}{X}_{R}A+b{X}_{R}A,(a=K_1+K_2\alpha ,b=K_2\beta +m)$	$S_0=230\mathrm{g}/\mathrm{L}$ ${\mu }_m=0.24{\mathrm{h}}^{-1}$	S: Substrate (g/L); KS: Half-saturation constant; A: Cell activity (unitless); m: Maintenance coefficient (h−1)	C. necator, mixed VFAs, 30 °C, pH 7.0, batch	[87]
$q_{PHA}=Y_{PHA,S}·q_S-k{({\displaystyle \frac{C_{X0}}{C_X}})}^{1/3}{f}_{PHA}^{2/3}$ $\mu =Y_{X,PHA}·k·{\left({\displaystyle \frac{C_{X0}}{C_X}}\right)}^{{\displaystyle \frac{1}{3}}}{f}_{PHA}^{{\displaystyle \frac{2}{3}}}-Y_{X,S}·m_S$	-	qPHA: PHA prod. Rate; YPHA,S: PHA yield/substrate; CX: Active biomass (g/L)	Mixed VFAs, 30 °C, aerobic sequencing batch reactor (SBR), feast–famine operation	[88]
$\mu ={\displaystyle \frac{{\mu }_{max}S}{K_s+S}}$ $\mu ={\displaystyle \frac{{\mu }_{max}S}{K_{s}X+S}}$ $\left({\mu }_{max}+m\right)\left({\displaystyle \frac{S}{K_s+S}}\right)-m$	${\mu }_{max}=0.16 {\mathrm{h}}^{-1}$ ${\mathrm{K}}_{\mathrm{s}}=79.51 \mathrm{g}/\mathrm{L}$	μ: Specific growth rate (h−1); Ks: Half-saturation constant; m: Maintenance coefficient (h−1)	Bacillus safensis, sugarcane bagasse, 30 °C, pH 7.0, batch	[89]

. Figure 4 identifies the key branch-points leading to each PHA precursor, and the dual-phase kinetic model (Monod + Luedeking–Piret, Table 4) is presented as a literature-derived example illustrating how feast–famine cycling redistributes carbon flux toward polymer accumulation. These models combine Monod-type substrate uptake, dual-phase feast–famine frameworks, and refined Luedeking–Piret equations from prior research to simulate both rapid carbon assimilation and subsequent PHA mobilization [85].

Mixed microbial cultures (MMCs) have recently emerged as a promising platform for PHA production from complex feedstocks. While Monod kinetics describe substrate-linked growth [90], and Contois and Herbert equations capture cell-density effects [89], these classical formulations do not account for inter-species competition or preference among multiple substrates. Existing Monod-based MMC models assume a single “lumped” biomass and neglect competitive uptake of sugars and VFAs by different strains, which can mispredict community succession and PHA yield under feast–famine cycling [90,91]. To overcome these defects, Mozumder et al. [92] introduced an improved dual-phase MMC model (summarized in Table 4) that: (i) Separates feast and famine phases with distinct uptake and mobilization rate constants; (ii) Implements a dynamic competition coefficient that scales each species’ growth rate according to the concentrations of multiple substrates; (iii) Accurately reproduces PHA accumulation and biomass dynamics across successive feast–famine cycles in pilot-scale reactors. Recent extensions further integrate species–species interaction terms and variable yield coefficients, pointing the way to a unified MMC kinetic framework that simultaneously captures substrate competition, community dynamics, and polymer turnover [92].

These models have also been applied to PHA biosynthesis from low-cost substrates [7]. Key kinetic models and their parameters are summarized in Table 4. The Luedeking–Piret model proved highly accurate for Cupriavidus necator on rubber seed oil, estimating growth-associated PHA rates [86]. Monod, Contois, and Herbert formulations simulated Bacillus safensis EBT1 fermentations on sugarcane bagasse [89], while comparative studies of Alcaligenes sp. and Pseudomonas sp. on rice straw confirmed Monod-type alignment for P(3HB) production [93]. Wang et al. [87] used VFA-driven kinetics to reveal that initial VFA excess inhibits growth and PHA synthesis before a controlled famine phase restores productivity.

By extracting scale-independent kinetic parameters and enabling in silico optimization of feast–famine schedules, dynamic models minimize residual substrate, prevent premature polymer turnover, and de-risk scale-up, providing quantitative guidance for the design of pilot- and industrial-scale PHA processes.

7. Commercial-Scale Economic Feasibility of LAR-to-PHA Conversion

Although LAR-to-PHA processes remain at lab or pilot scale, techno-economic analysis (TEA) is indispensable for scaling up and de-risking commercial deployment [4]. The dominant cost drivers for LAR-to-PHA routes are typically: feedstock cost share, pretreatment severity, solvent recovery, and downstream separation/recovery. Common mitigation strategies reported across studies include the use of tolerant hosts or in situ detoxification, coproduct valorization and process integration, and mill-annexed or continuous operation modes [94,95]. Because published TEAs employ heterogeneous assumptions (currency-year, plant scale, CAPEX/OPEX scope), direct numerical comparisons across studies can be misleading. Therefore, rather than attempting cross-study numerical harmonization, we emphasize qualitative trends and highlight selected study-specific quantitative examples (reported values are shown with explicit citations). These examples are presented for illustrative purposes only and have not been normalized to a common currency-year, plant scale, utilization, or CAPEX/OPEX scope, so they should not be interpreted as directly comparable. Conventional TEA approaches focus on capital expenditures (CAPEX), such as corrosion-resistant pretreatment reactors, and operational expenditures (OPEX), including water, chemicals, and energy across feedstock pretreatment, fermentation, and downstream recovery. Pretreatment TEA studies show that switching from dilute-acid to organosolv pretreatment in a 50 kt/yr plant nearly doubled fermentable sugar concentration (from 5.4% to 11.1%), raised energy demand (from 214 MW to 578 MW), cut feedstock cost share by 19%, and reduced the minimum selling price (MSP) of PHA by 42.8% compared to dilute acid [96]. Acidic deep eutectic solvents (e.g., choline chloride/lactic acid) further lower sugar production MSP by ~30% (US $2128/t vs. US $3049/t) thanks to higher yields (0.21 t/t biomass), although solvent cost volatility can induce 5–23% MSP fluctuations [97,98]. In contrast, fungal pretreatments at 20 Mgal/yr scale incur sugar costs of US $1.6/kg (4–15× conventional) due to sterilization and facility overheads accounting for nearly half of total costs [99].

Feedstock-cost innovations, such as using carob-pod extract, can slash feedstock share from 67% to ~15% of total expenses, shortening payback from 12.6 to 6.8 years, though absolute CAPEX/OPEX remain high (US $417 M/US $1.44 B) [100]. Likewise, integrating continuous P(3HB) fermentation boosts productivity (from 0.34 to 1.20 g/(L·d)) and cuts unit costs from ~US $11.80/kg to US $6.55/kg [101].

Beyond these siloed assessments, we adopt a system-coupled TEA framework that valorizes all co-products (VFAs, biogas, enzymes, power), dynamically allocating costs and revenues to achieve MSP reductions of 30–40% relative to single-output scenarios. For instance, integrating VFA recovery or power cogeneration has reduced the MSP of PHA to US $4.83/kg under favorable net present value conditions [102]. A regionally responsive TEA further adjusts feedstock, utility, labor, and carbon-credit inputs to the local market, shortening capital payback by 20–50% and stabilizing MSP volatility. Carbon-efficiency-oriented TEA models link PHA yield to life-cycle CO₂ mitigation, unlocking revenue from carbon credits and further reducing net costs. Finally, demand-side analyses reverse-engineer strain and process design for high-margin applications (e.g., medical devices, specialty packaging), aligning upstream R&D with downstream regional market needs.

Beyond economics, PHA’s true value lies in its environmental fate. Unlike conventional polyolefins, PHA naturally depolymerizes under environmental conditions. In marine-relevant assays [103], PHA films were pre-colonized for one month in flow-through natural seawater (19–24 °C, salinity 38.5 g/L) to develop mature biofilms, then solvent-cast discs (80–120 µm) were incubated in carbon-free minimal medium inoculated at 10⁵ cells/mL, in the dark, at 18 ± 0.25 °C and 110 rpm for 60 days. Under these conditions, the degradation rate of scl-PHA was faster than that of mcl-PHA and polyethylene. In another study, sterilized PHA sheets (~1 g) were incubated with Schlegelella thermodepolymerans DSM 15344 in growth medium at pH 7, C/N = 10, 50 °C. SEM imaging revealed progressive surface disintegration within 2–3 weeks [104]. Additionally, the Nitrifier-Assisted Stabilization (NAS) approach, which couples ammonia-oxidizing bacteria (AOB) with Chlorella vulgaris, simultaneously treats low-C/N wastewater, reduces membrane fouling, and sequesters CO₂ during PHA production [105,106,107]. Together, these attributes position LAR-derived PHA as a circular alternative to polyolefins, preventing microplastics and converting waste streams into bio-benign materials.

8. Conclusions

Integration of advanced pretreatment (e.g., DEA–MW, DES, NSL), microbial platform design, kinetic modeling, and techno-economic analysis is essential for converting lignocellulosic residues into high-value PHA [4,108,109]. We introduce two frameworks, pretreatment-co-substrate compatibility and pretreatment-microbial platform matching, to align biomass fractionation with downstream metabolism. Coupling dynamic feeding, microbial consortia, and one-pot processing can boost PHA titers and enable copolymer tailoring, while Monod–Luedeking–Piret-based models with substrate-specific parameters, as reported in the literature, are synthesized to illustrate how published kinetic analyses guide process and material optimization. From an economic perspective, recent TEA and pilot-scale studies indicate that integrating continuous fermentation, co-product valorization, and region-specific design can reduce the minimum selling price (MSP) of PHA to US$1.75–7.23/kg, in some cases below current market levels, and shorten capital payback periods by up to 50%. These cost trajectories, combined with carbon-credit revenues and environmental benefits, underscore the commercial viability of LAR-to-PHA pathways. They also highlight the need for real-time control systems, robust in situ detoxification, and refined kinetic models to support scale-up.