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[Yunxin Zhu](https://orcid.org/0000-0001-6070-7305), [Guangqi An](https://orcid.org/0000-0003-2726-1369), [Cheng Zhang](https://orcid.org/0000-0001-5221-7461), Guoping Chen, [Yingnan Yang](https://orcid.org/0000-0001-8980-0634)

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[Why do anaerobes like the light stimulation: Enhanced anaerobic digestion at different wavelengths under ammonia stress](https://mdr.nims.go.jp/datasets/a942ea1f-0082-4fc8-8a00-dec558557efc)

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1 1 2 3 4 Why do anaerobes like the light stimulation: Enhanced anaerobic digestion at 5 different wavelengths under ammonia stress 6 7 8 9 10 11 12 Yunxin Zhua, Guangqi Ana, Cheng Zhanga, Guoping Chenb, Yingnan Yanga* 13 aGraduate School of Life and Environmental Science, University of Tsukuba, 1-1-1 14 Tennodai, Tsukuba, Ibaraki 305-8572, Japan 15 bResearch Center of Functional Materials, National Institute for Materials Science,1-16 1 Namiki, Tsukuba, Ibaraki 305-0044, Japan 17 18 * Corresponding author:19 Tel/Fax: +81 29 8534650 20 E-mail address: yo.innan.fu@u.tsukuba.ac.jp (Y.Yang)21 22 https://www2.cloud.editorialmanager.com/cej/viewRCResults.aspx?pdf=1&docID=262619&rev=0&fileID=6931372&msid=5d6727e0-f1f7-40f4-b478-bff4d8f8b2d3https://www2.cloud.editorialmanager.com/cej/viewRCResults.aspx?pdf=1&docID=262619&rev=0&fileID=6931372&msid=5d6727e0-f1f7-40f4-b478-bff4d8f8b2d32 Abstract 23 Strengthening microbes with light during anaerobic digestion (AD) has emerged 24 as a promising approach for effective waste-to-energy conversion, yet the underlying 25 mechanisms remain elusive. This study delved into the complexities of microbial 26 behavior, metabolic pathways, and digestion efficiency to explore the light-27 stimulating effects of various wavelengths (blue, green, red and mixed wavelengths) 28 on AD under ammonia stress. Different light wavelengths induced distinct responses 29 in anaerobic consortia and cell metabolism. Blue and green light impacted the Energy 30 and Methane metabolism, while red light regulated the Cell cycle and motility-related 31 genes. Although Methanosarcina dominance was observed across all the lighted 32 groups, the dominant pathway shifted from hydrogenotrophic to acetoclastic 33 methanogenesis specifically under the mix-color lighting. This characteristic was 34 attributed to the collaborative effects of short and long wavebands, enhancing the 35 diversity of microflora and triggering the cellular processes more effectively. 36 Moreover, the enrichment of syntrophic bacteria and Methanosarcina (91.3% of 37 archaeal community) facilitated the complete degradation of organic acid and 38 outperformed methanation under mixed wavelengths. Furthermore, metagenetic 39 predictions elucidated that critical metabolic processes regulating organic conversion 40 (Carbohydrate metabolism), microbial response (Signal transduction, Membrane 41 transports system) and cross-population cooperation (Quorum sensing) were 42 significantly activated under the mixed wavelengths. Notably, the mixed-wavelength 43 light stimulation upregulated a c-type cytochrome-mediated interspecies 44 3 communication, fostering an energy-conserving bionetwork via electronic signals. 45 From the academic to the practical viewpoint, this study unveiled the mechanisms and 46 potential of a visible light-stimulated system for waste-to-energy conversion, 47 highlighting the feasibility of sustainable sunlight-mediated waste management and 48 energy recovery on a larger scale. 49 Keywords: Visible light stimulation; Spectral effect; Ammonia-rich anaerobic 50 digestion (AD); Metagenomic analysis; Interspecies electron transfer (IET) 51 52 4 1. Introduction53 Global challenges such as environmental deterioration and energy depletion have 54 reached an alarming pace, casting a shadow over human health and societal 55 advancement [1,2]. Sustainable management of waste through anaerobic digestion 56 (AD) holds the promise to minimize pollutant emissions meanwhile harness 57 renewable energy (e.g., H2 and CH4) [3]. AD process involves complex stages—58 namely, hydrolysis, acidogenesis, acetogenesis and methanogenesis—which converts 59 macromolecular compounds into bioenergy with concomitant generation of volatile 60 fatty acids (VFAs) as secondary products. Indeed, the stable operation of AD calls for 61 a delicate balance between the above steps, which necessitates a collaborative effort 62 between diverse bacteria and methanogens for catalyzing the optimal performance [4]. 63 However, multiple inhibitory factors in AD, e.g., ammonia toxicity (when ammonia 64 levels exceed 1500 mg/L) accompanying with inhibited metabolic activity, impaired 65 microbial structure and undesirable VFAs accumulation, generally undermines the 66 efficiency of bioconversion process and waste treatment [5,6]. Thus, searching a 67 pragmatic and efficacious approach to improve the digestion performance stands as a 68 pressing need. 69 The utilization of illumination to stimulate anaerobic microorganisms has 70 recently emerged as an innovative practice to promote the conversion of organics into 71 CH4, which challenges the traditional notion that AD predominantly occurs in 72 darkness. Early studies on light-enhanced AD were conducted by Sawayama et al, 73 who observed that light exposure improved the removal efficiency of total organic 74 5 carbon (TOC) and toxic ions (such as ammonia, phosphate, and sulfate) in up-flow 75 anaerobic sludge blanket [7,8]. Besides, the introduction of incandescent lighting 76 yielded a two-fold enhancement in biogas and CH4 production compared to dark AD 77 [9,10], which were likely due to the photoactivating effect of light [11,12]. Multiple 78 lines of evidence propounded that light stimulation assisted to shorten the lag phases 79 and increase the biogas production, thereby significantly advanced the AD operated in 80 different modes [13–15]. In particular, light stimulation has demonstrated a 81 pronounced efficacy in overcoming ammonia-induced inhibition in AD, due to its 82 effectiveness in activating anaerobes and strengthening the cell-cell syntrophic 83 communication [16–18]. Furthermore, extensive researches have highlighted the 84 practical potential of light stimulation strategies in the context of fostering large-scale 85 waste-to-energy conversion [19–21]. Among the diverse light sources, solar 86 irradiation from nature is an attractive alternative to artificial lighting, as it offers a 87 readily available and environmentally benign option for economically viable scaled-88 up systems. However, the limited knowledge about the sunlight-stimulating effect and 89 the internal mechanisms of light-related microbial nexus in AD necessitates the 90 further exploration. 91 Light plays a vital role in the lifestyles of all living beings on earth. Variations in 92 light conditions (e.g., light intensity, exposure time and wavelength) could regulate 93 microbial behavior and result in the different performances. For instance, light 94 intensity influenced the framework of microbial community [21], while the 95 illumination time exhibited a distinct relation with cell availability and activity [13]. A 96 6 model-based analysis quantitively predicted the effect of light conditions on CH4 97 yield, revealing that light could alter the metabolic pathways, microbial community 98 and sludge properties [20]. However, previous efforts into the role of light have 99 primarily gravitated toward light quantity (namely, intensity and time), while little is 100 known about light quality, specifically, the light wavelength. In fact, wavelengths 101 associated with specific light color might have distinct effects on microbial behavior. 102 Within the board solar spectrum, ultraviolet (UV) light with high photon energy might 103 cause photochemical damage to the cells, while near-infrared/infrared lights 104 associated with long-wave spectrum have significant thermal effects [22]. In contrast, 105 the visible spectrum (400–800 nm), which accounts for a substantial 50% of solar 106 energy, holds the potential to significantly impact the microbes and their propensities 107 for proliferation [20]. As reported, red light could regulate the enzymatic activity in 108 respiratory chain [23] and bacterial proliferation [24]. A beneficial effect of low-109 intensity blue light (390–540 nm) on CH4 production was documented [9], while 110 certain investigations concurrently unveiled its negative impact on specific 111 archaebacteria and enzymes [25,26]. In addition, previous investigations on spectral 112 effect were mostly conducted under distinctive wavelength in pure-culture system, 113 very few studies have been focused on the mixed microflora in ammonia-stressed AD 114 bioprocess. Moreover, the regulated metabolic pathways and syntrophic features of 115 light-activated community in response to different wavelengths remains unknown. 116 Recently, bioinformatics analysis, including taxonomic trees and the Kyoto 117 Encyclopedia of Genes and Genomes (KEGG) pathway could track the changes in 118 7  microbial network [27], which is a potential way for better understanding the 119 mechanisms involved in light-stimulated AD.  120 In this study, the objective was to explore the impact of different wavelengths on 121 light-assisted anaerobic digestion (AD) under ammonia stress. To simulate the diverse 122 wavelengths within the visible solar spectrum, the energy-efficient light-emitting 123 diodes (LEDs) were utilized as a light source. Specifically, this study involved: (1) 124 comparing the performance of AD at short, medium, long, and full visible 125 wavelengths; (2) examining the structure and properties of mixed consortia 126 characterized by various light colors; and (3) delving into the mechanism on the 127 wavelength-regulated metabolic pathways and syntrophic association.  To the best of 128 our knowledge, this is the first study to elucidate the light-stimulating mechanism via 129 metagenomic analysis of microbial profiles and metabolic routes. The obtained results 130 could provide insight into the internal changes in light-assisted anaerobic bioprocesses 131 from academic point, and further contribute to guiding the practical engineering of a 132 solar-integrated bioprocess for the treatment of ammonia-rich feedstock. 133 2. Materials and methods 134 2.1 Seed sludge and substrate 135 Seed anaerobic sludge was obtained from a mesophilic sewage treatment plant in 136 Ibaraki prefecture, Japan. After being collected in an airtight container, sludge was 137 stored at 4ºC for use until no more biogas was produced. Before use, anaerobic pre-138 inoculation under 55 ± 1ºC was conducted in fermentation reactor (500 mL, SIBATA) 139 with collected seed sludge (20 v/v%) and diluted synthetic medium (80 v/v%). During 140 8 two-week preculturing, the synthetic medium consisted of glucose (2.5 g/L), sodium 141 acetate (2.5 g/L), yeast extract (200 mg/L), NH4Cl (200 mg/L) and KH2PO4 (16 mg/L) 142 was dissolved in trace element solution (50 mL/L) and then added into reactor every 143 two days. The chemical composition of trace mineral solution was recorded in a 144 previous study [18]. 145 2.2 Anaerobic fed-batch fermentation under light of different colors 146 In order to assess spectral effects on light-assisted AD, fermentation assays were 147 carried out under LED illumination with different light colors. Blue, green, and red 148 were selected as the three primary light colors to present the short (400−500 nm), 149 medium (500−600 nm), and long (600−800 nm) wavebands of visible light, 150 respectively. Moreover, a polychromatic white LED light (400−800 nm) was 151 employed as a comparative treatment to simulate the entire visible spectrum. 152 According to previous studies [13,17], daily illumination of 60 mins was applied to 153 each reactor with intermittent stirring (100 rpm with 3 mins on and 12 mins off) to 154 ensure the homogenous light stimulation. Each lighted reactor had a light intensity of 155 5 ± 1 W/m2 with monochromatic LEDs (namely, Blue, Green and Red) and 17 ± 2 156 W/m2 with polychromatic LED (namely, Mix), which was the sum of the individual 157 monochromatic lights. After lighting, the reactors were placed in darkness 158 immediately. The control reactor (Dark) was operated in dark, which was wrapped 159 entirely in aluminum foil to keep out all light. The schematic diagram of reactor and 160 spectrum of LED source were depicted in Fig. S1.  161 Sequential fed-batch assay was conducted for three cycles, including the start-up 162 9 period (5 days), cycle 1 (4 days) and cycle 2 (3 days). Each treatment (100 mL) was 163 initially inoculated with acclimatized digested sludge (16 mL) and synthetic medium 164 (64 mL). After adjusting the initial pH to 7.0 ± 0.2, each reactor was then purged with 165 N2 gas for 3 min, sealed immediately to ensure anaerobic condition and then kept in a 166 thermophilic incubator. Biogas production was monitored daily, and when the CH4 167 production ceased, the supernatant liquid was replaced by a new substrate solution. 168 The NH4Cl was adopted into each reactor to maintain an ammonia-stress environment 169 of 2500 mg/L.   170 2.3 Analytical methods 171 The biogas composition was analyzed by gas chromatography (GC-8A, 172 SHIMAZU, Japan). Sampled digestate (2 mL) was centrifuged and filtered with 173 supernatant for the measurement of dissolved organic carbon (DOC), VFAs and pH 174 according to previous study [18,20]. Modified Gompertz model was performed to 175 compare the AD performance under different light conditions, which depicted the 176 correlation between the cumulative CH4 production and the lag phase time using a 177 sigmoid function [28]. Parameters including cumulative CH4 production (Mmax, mL/L) 178 maximum CH4 production rate (Rmax, mL/day) and lag phase time (λ, day) were 179 estimated using the curve fit function in Origin 2021 software. 180 2.4 Microbial community and metagenomic analysis 181 The composition of the microbial community collected from each treatment and 182 inoculum were quick frozen at -80℃ and stored after fed-batch assay. Illumina MiSeq 183 paired-end sequencing (Illumina, USA) of 16S rRNA V4 regions (515F–806R) was 184 10  performed at Bioengineering Lab. Co., Ltd. (Kanagawa, Japan). Briefly, DNA 185 extraction with a two-step, tailed PCR approach was performed for 16S metagenomic 186 sequencing library preparation, according to the manufacturer’s instruction 187 (https://www.gikenbio.com.). The prepared libraries were used for paired-end 188 sequencing with 2 × 300 bp reads and assembled based on QIIME2. Quality filtered 189 reads were assigned to operational taxonomic units (OTUs) (99.7% identity) using 190 taxonomic assignment against the EzBioCloud 16S database 191 (https://www.ezbiocloud.net/) [29]. Diversity analyses were performed using QIIME2 192 with default parameters. Indices of α-diversity for richness comparison (using 193 observed species and Chao1 index) and diversity comparison (using Shannon index 194 and phylogenetic diversity (PD) whole tree) were analyzed based on the size of 195 samples and normalized using sequences (no less than 10000 sequences) obtained 196 among different samples. Phylogenetic Investigation of Communities by 197 Reconstruction of Unobserved States (PICRUSt2) was used to predict the functional 198 gene products in the microbiota based on the taxonomy obtained from the 199 EzBioCloud 16S database. The gene products were classified using KEGG ortholog 200 (KO) and mapped using the KEGG Mapper (https://www.genome.jp/kegg/mapper/). 201 2.5 Statistical analysis  202 All experiments were repeated in triplicate. An analysis of variance (ANOVA) 203 was employed to evaluate the significance of the results, p < 0.05 was considered to 204 be statistically significant and p > 0.05 was considered to be statistically insignificant.  205 https://www.genome.jp/kegg/mapper/11  3. Result and discussion 206 3.1 AD performance under different light spectrum 207 The effects of light stimulation with different colors on AD performance in three-208 cycle fed batch were illustrated in Fig. 1 and modeled by the modified Gompertz 209 equation (Table 1). Due to the ammonia toxicity, Dark group showed the lowest CH4 210 production (Fig. 1a) and unstable CH4 concentration (Fig. 1b), with the longest lag 211 phase of λ = 0.6−2.1 days throughout the cyclic operation (Table 1). While under light 212 stimulation, the cumulative CH4 production (Fig. 1a) from the Blue, Green, Red and 213 Mix groups were 1074 ± 75, 1126 ± 79, 1946 ± 139 and 1875 ± 131 mL/L, 214 respectively, which were 1.77, 1.86, 3.28 and 3.10 times higher than that of Dark 215 control (606 ± 42 mL/L). During the start-up period, Red and Mix groups exhibited 216 the highest CH4 concentration (86.2% and 85.0%, respectively) on day 4, followed by 217 Blue (81.9%) and Green (75.9%) groups (Fig. 1b). While relatively lower level of 218 73.7% (on day 5) was observed in the Dark group. This implicated that visible light 219 exposure could enhance methanogenic productivity under ammonia stress, and the 220 promotion efficacy depended on the specifically spectral properties of light. 221 Especially, Red group exhibited an outcompeting CH4 production among all lighted 222 groups (Fig. 1a), contributing to 4.82 folds of CH4 cumulation (941 mL/L) on day 5 223 compared to the that of Dark group (195 mL/L). Generally, start-up period is 224 considered as the rate-limiting step in ammonia-stressed AD, as it provides a 225 prerequisite phase for the anaerobic microorganisms to acclimate to the new 226 environment [30]. The superior performance under red lighting could be attributed to 227 12 the stimulatory effect of long-wavelength lighting on cell growth and proliferation in 228 start-up [24,31], favoring the microbial acclimatization and CH4 productivity. 229 However, the stimulatory effect of sole red-light was uncapable of further sustaining 230 in the subsequent cycles.  The maximal CH4 concentration of Red group decreased to 231 from cycle 1 (Fig. 1b), and the maximum cumulative CH4 production (Mmax) under 232 red lighting halved from 1014 mL/L (start-up) to 438 mL/L (cycle 1) and 546 mL/L 233 (cycle 2) (Table 1). In contrast, mix-color lighting could steadily maintain the 234 maximal CH4 concentration at 80−85% throughout the operation (Fig. 1b), which led 235 to steadily promoted Mmax (628−797 mL/L) in three cycles (Table 1). Accordingly, the 236 gap of CH4 production between Mix and Red groups gradually minimized in 237 following 2 cycles (Fig. 1a), achieving comparative CH4 accumulation ultimately on 238 day 12. These variations suggested that mix-color lighting showed better 239 sustainability in assisting AD performance under ammonia stress, as compared to 240 exclusive sole-color lighting. On the other hand, reactors under blue- and green-light 241 achieved similar CH4 productions (Fig. 1a), but a sharp decrease in Mmax from 593 242 mL/L (start-up) to 489 mL/L and 123 mL/L (cycle 1 and cycle 2, respectively) was 243 observed in the Blue group. This probably related to the high energy contained by 244 short visible waveband might restrain the enzymatic activity and cell growth [7]. 245 While green lighting might be favorable for improving methanogenic productivity 246 [32], as demonstrated by the steadily increased Mmax (172−489 mL/L) and shorter lag 247 phase (0.2–0.7 day) in the Green group throughout the three-cycle operation (Table 1). 248 These observations illustrated that each light color within visible range might 249 13  stimulate AD performance in different ways, and mix-color lighting ultimately 250 resulted in a superior and stable overall performance. 251 3.2 Influence of light wavelengths on metabolized organic acid  252 As a major class of metabolic byproducts in AD, VFAs play a double-edged role 253 in organics conversion and CH4 production. To further dig the mystery behind the 254 wavelength-regulated enhancement, the variations of VFAs were investigated. During 255 start-up (Fig. 2a), all the light-treated groups exhibited lower acetate levels than that 256 of dark group, implying the accelerated acetate consumption via the light-activated 257 anaerobes under ammonia stress. As a critical precursor for methanogenesis, acetate 258 (contributing to 65–70% of CH4 production) varying in the favorable levels indicates 259 a fine balance between acidification and methanogenesis [33]. Compared to other 260 treatments (Fig. 2a), Red group remained apparently less acetate (807 mg/L) from day 261 3 (when CH4 content > 60% in all treatments), implicating the ability of red-light on 262 pulling the acetate conversion into CH4 in the early stage. However, after three-cycle 263 operation, more acetate remained in Red (476 mg/L) on day 12 among all the groups, 264 indicating that sole red-light stimulation was unsuitable for continuous acetate-to-CH4 265 conversion. This unsustainable effectiveness of red light was in consistence with 266 reduced Mmax in following 2 cycles (Table 1). Additionally, more propionate 267 accumulated in Red (100–161 mg/L) on day 5, 9 and 12 (Fig. 2b), as compared to that 268 of the Dark group (20–99 mg/L). While less propionate, butyrate and lactate were 269 observed in the Blue and Green groups on the ultimate day of each cycle. Generally, 270 propionate often remains unconverted in ammonia-stressed AD, owing to its 271 14 thermodynamically constrained properties and the sensitivity of acid degraders to 272 ammonia [34]. Above findings implicated that compared to red-light stimulation, blue 273 and green ones had better contributions in assisting the degradation of resilient VFAs 274 under ammonia stress.  275 In comparison to single-color lighting, Mix group exhibited a stable acetate 276 conversion efficiency and complete degradation of resilient VFAs throughout the 277 operation. After 5-day acclimatization to mix-color lighting (Fig. 2), negligible acetate 278 (0–18 mL/L) and other VFAs (0–9 mL/L) accumulated at the end of cycle 1 (day 9) 279 and cycle 2 (day 12). This promoted degradation efficiency suggested that mix-color 280 light stimulation had outcompeting ability on stabilizing the organic conversion 281 efficiency under ammonia stress, as compared to other light treatment. This was in 282 accordance with the steadily increased CH4 production (Fig. 1a) in the Mix group 283 throughout the operation. Conclusively, light varies in colors behaved differently in 284 influencing the organic degradation and methanogenic performance, as each light 285 color made distinctive contribution to process efficiency. By benefiting from the 286 synergy of blue-, green- and red-light effects, light-assisted digester with mixed color 287 achieved an efficient and stable organics acid conversion under ammonia stress. 288 3.3 Functional bacterial community under different wavelengths 289 Efficient organic conversion into CH4 depends on the establishment of a delicate 290 metabolic balance and syntrophic interactions between bacterial and archaeal 291 communities. To explore the mystery behind the light-triggered enhancement, the 292 bacterial communities under different light treatments were assessed firstly (Fig. 3a). 293 15 Compared to Inoculum, Dark group exhibited higher abundance of Petrotogals 294 (21.2%), Bacillales (23.8%) and Thermoanaerobacterales (14.8%), Hydrogenispora 295 (2.3%) and Erysipelotrichales (2.0%), which commonly abundant in ammonia-rich 296 AD [35]. While the fractions in Clostridiales (30.1%), Tissierellales (3.1%), 297 Spirochaetales (1.5%), and Anaerolinaeles (0.8%), Cloacamonas (0.5%) reduced, due 298 to their sensitivity to ammonia stress [36]. Under light treatment, above reduced 299 populations could be conserved in different ways. For examples, the abundances of 300 Clostridiales and Tissierellales, which contain efficient acetogens and sugar degraders, 301 increased to 32.3−47.9% and 3.1−4.4% under light conditions, respectively. 302 Especially under sole red-light stimulation, a remarkable enrichment of the 303 Clostridiales (47.9%) was observed. Populations in Clostridiales are characterized as 304 syntrophic acetate oxidizing bacteria (SAOB), which are known for their ability in 305 fast acetate degradation into H2/CO2 and contribution to hydrogenotrophic 306 methanogenesis (HM) under ammonia stress [37]. Those red light-enriched SAOB, 307 dominating approximately half of the bacterial community, could potentially assist the 308 SAO-HM pathway for fast CH4 conversion in the Red group. This discovery 309 harmonized with the rapid degradation of acetate (Fig. 2a) and the accelerated CH4 310 production (Fig. 1a) in the Red group during the start-up period. Besides, mix-color 311 lighting particularly increased populations in Spirochaetales (2.8%), Anaerolinaeles 312 (1.9%) and Cloacamonas (1.0%), accounting for approximately 2-fold abundances of 313 that in the Dark group (Fig. 3a). These visible light-enriched orders comprise 314 proficient syntrophic propionate and butyrate degraders [35,38,39], which agreed with 315 16 the negligible VFAs accumulation in Mix group until the end of cyclic operation (Fig. 316 2b). 317 Since bacteria community (order level) in Blue and Green groups showed 318 insignificant differences (P > 0.1) with Dark group, to unveil the intricate relations 319 between light and bacterial community, a heatmap with cluster analysis on dominant 320 genera was generated. As shown in Fig. 3b, blue light treatment preserved the 321 fermentative genera of Defluviitoga, Coprothermobacter and Haloplasma, which 322 were specialists in hydrolysis and acid degradation during ammonia-rich AD [40–42]. 323 Besides, blue and green light promoted the co-growth of the hydrolytic populations 324 (GU455315, Defluviitalea and Tepidimicrobium), acid-producing bacteria (Bacillus) 325 and H2 producers (DQ887962 from Hydrogenispora). These enriched communities 326 were in alignment with fast VFAs degradation (Fig. 2b) under blue and green light, as 327 compared to that of the Dark group. On the other hand, red light stimulation 328 exclusively activated the genus Thermoclostridium, which was hardly observed under 329 other light treatments (Fig. 3b). Thermoclostridium harbors the ability in degrading 330 various types of sugars into acetate/ethanol and converting the resulting acetate into 331 H2/CO2 [43]. Consequently, the fermentative versatility of Thermoclostridium could 332 expedite the conversion of biogas from organics, which harmonized with the rapid 333 degradation of acetate (Fig. 2a) and surged CH4 production (Fig. 1a) in the Red group 334 during start-up period. However, this advantage in turn restricted the VFAs 335 conversion under red light (Fig. 2b), probably due to the reduced the competitiveness 336 of syntrophic VFAs degrading bacteria. 337 17  Unlike single-color light that enriched specific fermentative bacteria, mix-color 338 light stimulation had better control on balancing the bacterial structure for syntrophic 339 metabolism. In the Mix group (Fig. 3b), the clustered ammonia-repressed genera 340 Tepidimicrobium, AJ009469, AF402980, Cloacamonas, Rectinema and Clostridium 341 encountered a remarkable recovery. Tepidimicrobium (order Tissierellales), which is 342 particularly suited for sugar and protein fermentation into acetate under high ammonia 343 concentrations, commonly associates with the growth of SAOB [33,44]. Genera 344 AJ009469 (order Anaerolinaeles) and Cloacamonas (order Cloacamonas) were well-345 documented as the “semi-syntrophic” microorganisms involving in fermenting VFAs 346 (e.g., propionate and butyrate) into acetate and H2/CO2, and mutually cooperating 347 with HM to produce CH4 [45]. Conventionally, ammonia stress readily inhibits the 348 growth of syntrophic bacteria, leading to VFAs accumulation. Moreover, the 349 thermodynamically unfavorable nature of resilient VFAs can exacerbate acid pressure 350 and lower pH, restraining the methanogenic performance [46,47]. However, mixed-351 color lighting could trigger the revival of these syntrophic bacteria and thus favor the 352 conversion of organic acids, providing ample substrate for methanation. This 353 observation was coincidence with the minimal detection of VFAs in the Mix group at 354 the end of the operation (Fig. 2b). Furthermore, genera AF402980 and Rectinema 355 (both belonging to order Spirochaetes), along with Clostridium (order Clostridiales) 356 are recognized as key SAOB during AD but with high ammonia sensitivity [48]. By 357 combining the strengths of different wavelengths, mix-color lighting provided a 358 comprehensive stimulation on the above SAOB and assisted them in resisting 359 18 ammonia stress. Another intriguing result found in the Mix group was the exclusive 360 enrichment of the genera Anaerobacillus and Lysinibacillus, which showed low 361 abundance in the Dark group. Anaerobacillus is an obligate anaerobic diazotroph 362 capable of nitrogen fixation and growth without external sources [49], and 363 Lysinibacillus exhibits potential as a plant growth bio-stimulant due to its nitrogen 364 bioaccumulation abilities [50]. The substantial enrichment of two genera indicated 365 that mixed-color lighting could facilitate nitrogen utilization and ammonia 366 assimilation. Therefore, the evenly enriched bacterial community in the Mix group, 367 including ammonia-sensitive hydrolyzers, VFAs degraders, acetate oxidizers and 368 ammonia degraders, led to a diversified and balanced bacterial community for 369 effective fermentation. 370 3.4 Effect of different wavelengths on methanogenic microflora 371 The dominant methanogens were characterized to further reveal the visible light-372 induced changes on methanogenic microflora (Fig. 4a). Remarkably, Methanosarcina 373 prevailed across all light-treated groups, as its abundance increased from 49.6% to 374 70.7%, 77.9% and 75.3% in Blue, Green and Red groups, respectively, and reaching 375 an astounding 91.3% in the Mix group. However, the richness of strict 376 hydrogentrophic methanogens (e.g., Methanoculleus thermophilus and 377 Methanothermobacter thermophilus) experienced a sharply decrease under the single-378 color (19.1−26.0%) and mix-color lighting (1.7%), as compared to that of 32.2% in 379 the Dark group. Generally, hydrogenotrophic methanogens often dominate in 380 ammonia-stressed AD, and they could cooperate with SAOB for the utilization of 381 19  acetate-derived H2/CO2 into CH4 [51]. However, the energetically unfavorable feature 382 (ΔG0’ = + 104.6 kJ/mol) of SAO pathway usually results in limited CH4 productivity, 383 as compared to conventional acetoclastic methanogenesis (Table 2) [52]. In contrast, 384 the light-induced enrichment of Methanosarcina spp. might be favorable to relieve 385 this limitation. This methanogenic genus employs various pathways (acetoclastic, 386 hydrogentrophic and methylotrophic) for CH4 production, allowing it to thrive under 387 stressful conditions and utilize the remained substrates [53]. Besides, the 388 electroactivity and clustered growth feature of Methanosarcina spp. enhances its 389 competitiveness in syntrophic associations via interspecies electron  transfer (IET), 390 which is a more thermodynamically favorable path compared to the conventional 391 interspecies H2 transfer (IHT) for CH4 production [54]. By capitalizing on these 392 advantageous traits, the substantial enrichment of Methanosarcina under light with 393 different wavelengths contributed to better methanogenic performance, particularly 394 under mix-color lighting. Besides, a marked resurgence of Methanosaeta spp. was 395 demonstrated under mixed-color lighting (from 2.0% in Dark to 4.7% in Mix), which 396 also exhibited low richness (1.6–2.4%) in monochromatic light groups (Fig. 4a). 397 Methanosaeta spp. is known to be highly ammonia-sensitive due to the mono-398 metabolic trait on acetate and rod-shaped cell morphology [55]. While the 399 unprecedented recovery under mix-color lighting highlighted the potent role of 400 mixed-wavelength lighting in photo-reactivation of ammonia-sensitive methanogens. 401 The possibility of methanogens to undergo photo-repair can be attributed to the 402 presence of deazaflavin and its derivatives in archaea, which serves as chromophores 403 20 for the photo-reactivating enzyme [56]. Consequently, the effective recovery of 404 acetoclastic Methanosaeta spp. and predominance of robust Methanosarcina spp. 405 under mix-color light stimulation contributed to diversified methanogenic pathways 406 for outcompeted performance across the light treated groups. 407 Based on the obtained bacterial and archaeal community, light with varying 408 wavelengths contributed differently to microbial diversity and structure. To further 409 prove the above findings, alpha diversity metrics, including observed species, Chao1, 410 PD whole tree and Shannon within the digestate samples were assessed (Fig. 4b−e). 411 As estimators of microbial richness [57], indexes of observed species and Chao1 were 412 found to be highly increased in the Mix group, as compared to that of Dark group (Fig. 413 4b−c). Comparatively, insignificant influence was given by sole-color light. This 414 suggested that mix-color light stimulation had better control on promoting the 415 microbial abundance under ammonia stress. Besides, microbial diversity was also 416 profoundly affected by mix-color lighting, as demonstrated by the higher levels of PD 417 whole tree obtained in the Mix group (65.5) than that of Dark group (Fig. 4d). 418 Moreover, Shannon index that measures the species evenness increased to 4.8–5.0 419 under single-color lighting, and further recovered to 5.1 by mix-color lighting. 420 Generally, higher species evenness implies the robustness and functional stability of 421 biological system to adapt to the undesirable environment [58]. Compared to no light 422 or sole-color light, mix-color light stimulation exerted better control in regulating a 423 balanced microbial structure, resulting in higher diversity and stability for mitigating 424 the ammonia stress. Consequently, the light-activated anaerobic community was 425 21 capable of sustaining a stable and superior AD performance during the three-cycle 426 operation in the Mix group. 427 3.5 Variation of metabolic pathways under different wavelengths 428 3.5.1 Microbial response and behaviors to different light wavelengths 429 To unveil mechanisms behind the augmented light effects, bioinformatic analysis 430 on functional genes was performed with KEGG mapper, and the relative abundance of 431 predominant genes at level 3 was depicted in Fig. 5. Cluster analysis revealed that the 432 Dark group displayed a closer association with the Blue and Green groups, followed 433 by Red and Mix groups. This observation highlighted that the mix-color illumination 434 had a more potent regulatory impact on metabolic pathways compared to the single-435 color light. Specifically, mix-color lighting significantly upregulated the genes 436 encoding processes that involved in organic carbon conversion, including Pyruvate 437 Metabolisms, Propanoate Metabolisms, Butanoate Metabolisms, Fatty acid 438 Biosynthesis and Degradation. Additionally, the Membrane transport, Signal 439 transduction and Quorum sensing (QS) involved genes were highly up-regulated in 440 the Mix group. Phosphotransferase system (PTS) and Bacteria secretion system are 441 crucial for sugar uptake and proteins translocation across membranes [59,60], and 442 Two-component system enables microbes to sense environmental cues and triggers a 443 corresponding response mediated by a regulatory protein [61]. The elevated 444 expression of the above genes indicated that mixed-color activated anaerobes were 445 capable of sensing light signals via membrane-bound enzyme, and thus stimulated the 446 cross-membrane transport for substrate uptake and metabolites release. Moreover, QS 447 22 governing the population-level behavior (e.g., microbial communication, bacterial 448 aggregation and sludge formation), plays an important role in syntrophic community 449 for effective bioconversion [62]. Consequently, mix-color light stimulation not only 450 regulated cell metabolism for carbon conversion, but also the populations’ behaviors 451 for cell-cell communication and syntrophic cooperation. 452 Comparatively, single-color light stimulation distinctively modulated the specific 453 cellular behavior with different wavelengths. Compared to the Dark group, blue and 454 green light stimulation particularly upregulated genes encoding Glycolysis for 455 carbohydrate uptake and Methane metabolism for bioenergy conversion, two critical 456 processes for CH4 production. Moreover, blue and green light with higher photon 457 energy could penetrate deeper into the cell and influence genetic processes, including 458 RNA transcription, DNA replication and Nucleotide excision repair. These processes 459 ensured an efficient genetic information processing for proteins synthesis (e.g., 460 functional enzymes) [47]. On the other hand, red light upregulated genes involved in 461 cellular-level activities, including Cell cycle, Bacterial chemotaxis and Flagellar 462 assembly. Cell cycle governs biomass growth and death, while Bacterial chemotaxis 463 and Flagellar assembly regulate bacterial survival and motility in dynamic 464 environments [62]. Under stressful condition, motile anaerobes could sense changes 465 in chemical surroundings (e.g., light stimuli, ammonia levels, or substrate availability), 466 and then assemble flagella and navigate towards favorable environment [63]. Thus, 467 red light-triggered enhancement of cellular activity and motility might empower 468 anaerobes to rapidly acclimatize and utilize substrate for efficient digestion. This 469 23 further explained the boosted CH4 production and acetate consumption in the Red 470 group during the startup phase. 471 3.5.2 Light-regulated metabolic pathway for CH4 production 472 Among functional categories, Carbohydrate, Energy and Lipid metabolism 473 played a pivotal role in AD, which involves diverse biochemical processes responsible 474 for breaking down organic substances to produce bioenergy. In Carbohydrate 475 metabolism (Fig. S2a), glucose undergoes initial conversion through Glycolysis, and 476 the resulting pyruvate can be either transformed into acetyl coenzyme A (Acetyl-CoA) 477 through Pyruvate metabolism, or into lactate for biomass growth. In most cases, the 478 generated acetyl-CoA may further convert into acetate, butyrate and propionate, 479 depending on the involved microorganisms and environmental conditions. Finally, the 480 syntrophic bacteria degrade the generated VFAs via Butanoate and Propanoate 481 metabolism, leading to the production of acetate and H2/CO2. Compared to Dark 482 group, blue and green light stimulation evidently upregulated genes associated with 483 Glycolysis and Butanoate metabolism (Fig. 5), while higher gene expressions linked 484 to Pyruvate, Propanoate and Butanoate metabolism were detected in the Mix group. 485 These results in aligned with the highly enriched hydrolytic and fermentative bacteria 486 under blue and green light, and significantly recovered VFAs degraders under the 487 mix-color light (Fig. 3b). Despite red light stimulation down-regulated the most488 pathways involved in Carbohydrate metabolism (Fig. 5), it notably increased the 489 genes expression involved in M00579: acetyl-CoA →  acetate (Fig. S2b), which 490 contributed to efficient acetate conversion and degradation. 491 24 The generated fermentative byproducts (e.g., acetate, H2/CO2 and methanol) 492 were then traversed through distinct pathways in Methane metabolism to culminate in 493 CH4 generation (Fig. 6a). Compared to Dark group, Blue and Green groups exhibited 494 a significant upregulation on Methane metabolism, while similar level was observed 495 in the Red and Mix groups (Fig. 5). To delve deeper into short wavelength-enhanced 496 methanogenesis, the abundances of genes encoding pivotal enzymes for each 497 methanogenic pathway were analyzed. Three methanogenic pathways were detected 498 (Fig. S3), including CO2 reduction in HM (M00567), acetate decarboxylation in AM 499 (M00357), methanol conversion in methylotrophic methanogenesis (MM) via 500 M00356 [64]. Within acetate decarboxylation, vital enzymes including acetate kinase 501 (ackA, ①EC:2.7.2.1) and phosphate acetyltransferase (pta, ②EC:2.3.1.8) manage the 502 conversion of acetate to acetyl-CoA (Fig. 6a). Subsequently, acetyl-CoA is 503 transformed into Methyl-HSPT (a key juncture in methanogenesis) via the catalysis of 504 acetyl-CoA decarbonylase/synthase (cdhC, ③EC:2.3.1.169) [64]. Genes coded pta 505 displayed 24% increments under red illumination as compared to the Dark group 506 (Table S1). This result was likely correlated with the prevalence of Methanosarcina, 507 as it is a pathway unique to Methanosarcina which is distinct from acetotrophic 508 Methanosaeta [65]. Strikingly, compared to the Dark group, gene abundance of cdhC 509 increased by 84%, 74%, 14% and 23% in Blue, Green, Red and Mix groups, 510 respectively. The reaction mediated by cdhC presents a pivotal step in acetoclastic 511 methanogenesis and was reported to be highly sensitive to ammonia toxicity [66]. 512 Accordingly, the substantial upregulation of this ammonia-sensitive enzyme under 513 25 visible light stimulation was likely to explain the enhanced CH4 productivity in light-514 assisted system. Since individual wavelength distinctly contributed to activating the 515 acetate decarboxylation pathway, the absence of any wavelength might result in 516 suboptimal methanogenic performance. 517 Generally, acetoclastic methanogens exhibit higher susceptibility to ammonia 518 toxicity, consequently prompting a shifted pathway from AM to HM in methanogenic 519 community. Under blue and green lighting, CO2 reduction (reaction ④−⑦) was 520 further elevated compared to that of Dark (Fig. 6b), potentially due to the ability of 521 light-enriched Methanosarcina's in H2 utilization. In this genus, HM commences with 522 the H2- and MFR-dependent reduction of CO2 to formyl-MFR [65], facilitated by 523 formylmethanofuran dehydrogenase (fmd), a key catalyst for the initial step of H2 524 utilization. Compared to Dark, fmd gene abundance surged by 61% and 35% in the 525 Blue and Green groups, respectively (Table S1). Successively, the formyl group 526 transfers to H4SPT, progressing a stepwise reduction to yield methyl-H4SPT, which 527 powered by the electron (e-) derive from reduced F420 (F420H2). In parallel, enzymes 528 like methenyltetrahydromethanopterin cyclohydrolase (mch), 529 methylenetetrahydromethanopterin dehydrogenase (mtd), and coenzyme F420-530 dependent 5,10-methylenetetrahydromethanopterin reductase (mer) experienced a 531 respective gene expression increase of 54%, 64% and 50% in the Blue group, and 532 28%, 35% and 18% in the Green group, respectively (Table S1). On the other hand, 533 members in Methanosarcina are capable of metabolizing methylated C1 compounds 534 (e.g., methanol and methylamines) in the absence of H2 [67], known as MM. In this 535 26 pathway, corrinoid protein mediates the transfer of methyl groups from methylated C1 536 compounds to HS-CoM, yielding Methtyl-CoM (reactions ⑧–⑨, Fig. 6b). Due to the 537 lower abundance of Methanosarcina in Dark, gene abundance linked to MM-involved 538 enzymes remained modest (Fig. 6b), whereas light stimulation markedly upregulated 539 these genes. This observation affirmed the effectiveness of visible light stimulation in 540 driving H2- and methanol-utilizing methanogenesis, probably associated with light-541 enriched Methanosarcina. 542 At the intersection of AM and HM (Fig. 6a), methyl group of Methyl-HSPT is 543 transferred to HS-CoM via mtr (a membrane-bound methyltransferase), generating 544 Methtyl-CoM (⑩EC: 2.1.1.86). Subsequently, the reduction of methyl-CoM to CH4 545 occurs via mcr (⑪EC: 2.8.4.1), accompanied with mixed disulfide formation (CoM-546 S-S-CoB) and e- receipt from coenzyme B [68]. Reversely, the CoM-S-S-CoB could547 be transformed back to coenzyme M and coenzyme B by a composite heterodisulfide 548 reductase (hdr) with the assistance of F420 (⑫EC: 1.8.98.1). Both of mtr, mcr and hdr 549 experienced a remarkable upregulation by 59%, 39% and 58% in Blue, and 34%, 8% 550 and 37% in Green, respectively (Table S1). This pronounced impact of light 551 stimulation concentrated in the range of 400–500 nm (blue-green wavelength) likely 552 related to the light-absorbing ability of methanogenic chromophores. There are at 553 least two known chromophores absorbing visible light found in methanogens: 554 coenzyme F430 (a mcr cofactor), a novel nickel-containing corphin that peaks at 430 555 nm [69], and coenzyme F420 (an electrons carrier), a deazaflavin that maximally 556 absorbs at 420 nm [25]. As shown in Fig. S3, blue and green light could effectively 557 27 excite genes coding for F420 biosynthesis compared to the dark control. Moreover, this 558 excitation suggested that the higher energy inherent in short bands photons not only 559 activated the membrane-bound enzymes (e.g., hdr), but also traversed the cell 560 membrane to excite the cofactor in cytoplasm (e.g., coenzyme F420). Thus, the 561 efficacy of light stimulation, particularly in short visible wavelengths, conferred 562 significant advantages in activating methanogenic process and augmented 563 performance under ammonia stress. 564 In summary, diverse light colors facilitated the carbon compound acidification in 565 different manners, yielding ample precursors for various methanogenic pathways. 566 Particularly, mix-color lighting robustly triggered enzymes that were pivotal for VFAs 567 degradation, and thus assisted to mitigate acid accumulation in ammonia-stressed AD. 568 Additionally, the light-enriched Methanosarcina, adept at utilizing triple substrates 569 (acetate, H2/CO2 and methanol), showed their power in Methane metabolism. Blue 570 and green lighting optimally stimulate key enzymes and cofactors across all 571 methanogenic pathways, while red lighting selectively activates the acetate-utilizing 572 pta enzyme. This underscored differential contributions of short and long wavelengths 573 within the visible light spectrum in regulating methanogenic activity, thereby leading 574 to a well-performed CH4 conversion under ammonia stress. 575 3.5.3 Energy conservation in light-assisted bionetwork 576 Efficient organic conversion into CH4 relies on the intricate syntrophic 577 cooperation and complex biochemical reactions among bacterial and archaeal 578 communities, which are driven by intracellular energy (ATP) and e-. Energy yield is 579 28 commonly derived from the substrate phosphorylation and oxidative phosphorylation 580 [70]. The core ATP-producing pathway, Oxidative phosphorylation, relies on the 581 transmembrane gradient of Na+/H+ and e- transfer, catalyzing the conversion of ADP 582 to ATP through ATPase [B]. Genes involved in Oxidative phosphorylation showed 583 higher abundance in Dark group compared to the lighted groups (Fig. 5), implying 584 that the ammonia-stressed microbes in darkness required more energy in sustaining 585 biochemical productivity than light-assisted anaerobes. In order to prove the 586 hypothesis, gene abundances of the key enzymes involved in respiratory chain, 587 including Complex Ⅰ (NADH: quinone oxidoreductase), Complex Ⅱ (succinate 588 dehydrogenase), Complex Ⅲ (cytochrome bc1 complex) and Complex Ⅳ (cytochrome 589 c oxidase) and ATPase (F-type and V/A type) were analyzed. As shown in Fig. 7a, e- 590 generated from substrate uptake is transferred to NAD+ to produce NADH, which 591 then diffuses to the cytoplasmic membrane and transports e- to complex I. As e- 592 travels through the complex Ⅰ to Ⅳ, H+ simultaneously transfers across the membrane, 593 forming a proton motive force for ATP synthesis. Typically, bacteria primarily express 594 genes encoding F-type ATPase for ATP synthesis, while V/A-type ATPase is 595 employed by both bacteria and archaea to hydrolyze ATP and harness energy [71]. 596 Compared to Dark group, lower gene expression coding for complex Ⅰ−Ⅳ and F-type 597 ATPase (ATP synthase) was observed under single-color lighting (Fig. 7b), indicating 598 less ATP generation via oxidative phosphorylation under monochromatic light 599 stimulation. Instead, more energy may be yielded via substrate phosphorylation (e.g. 600 light up-regulated glycolysis), given that 1 mol of glucose phosphorylation yields 2 601 29  ATP molecules (Table 2) [72]. Additionally, it has been reported that ATP synthesis is 602 associated with Energy-converting hydrogenase (Ech), acting as precursors to 603 Complex I [73]. Ech fuels H2 production by utilizing the reduced ferredoxin (Fdrex) as 604 e- donor and coupling with NADH to reduce H+, and the resulting H+ force favors ATP 605 generation [33]. Compared to Dark group, a 48% elevation in Ech-coding gene 606 abundance was observed in the Blue and Green groups (Fig. 7c), suggesting an Ech-607 mediated energy conservation occurred under short-wavelength lighting. Besides, the 608 generated H2 could diffuse via IHT and participate in HM. Thus, short wavelengths 609 lighting might assist H2 metabolism, preserving energy for cell anabolism under 610 ammonia stress. 611 Comparatively, the Mix group displayed relatively higher gene abundances 612 coding for Complex Ⅲ and Ⅳ (Fig. 7b), with a notable c-type cytochrome (Cyt C) 613 upregulation (Fig. 7c). In anaerobic respiratory, Cyt C serves dual roles: transferring 614 intermembrane e- from Complex III to terminal acceptors (e.g., intracellular nitrate 615 and sulfate) [74] or shuttling e- to extracellular acceptors (e.g., electroactive 616 methanogens) via IET [54]. According to Table 2, the syntrophic oxidation of VFAs 617 (propionate, butyrate and lactate) facilitated by IET was more thermodynamically 618 favorable (ΔG0' ˂ 0) than that via traditional IHT (utilize H2 as the e- carrier). 619 Consequently, the Mix group exhibited lower gene expression encoding for V/A type-620 ATPase (Fig. 7b), which hydrolyzes ATP and utilizes the released energy for energy-621 dependent biochemical processes. The less energy demand in the Mix group might be 622 associated with the potentially formed IET pathway, in which the coenzyme F420 in 623 30 electroactive methanogens could directly accept the extracellular e- and H+ from acid-624 producing bacteria via Cyt C [74]. In contrast, the conventional IHT pathway for CH4 625 production relies on a series of endergonic reactions to oxidize H2/reduce CO2 [68]. 626 Thus, the bionetwork (acid degraders and methanogens) under mix-color light 627 followed an energy-conserving metabolic pathway (Fig. 7a): the enriched syntrophic 628 bacteria could harness the surplus e- that generated from complex Ⅲ and Ⅳ 629 (respiratory chain) and VFAs oxidation, transferring them to electroactive 630 methanogens (Methanosarcina and Methanoseata) via energy-efficient association 631 using Cyt C. This enhanced energy conservation and intercellular electronic 632 cooperation potentially alleviated the metabolic imbalance between acid-producing 633 bacteria and methanogens, addressing the VFAs accumulation in ammonia-inhibited 634 AD. Moreover, the substantially upregulated QS for community association, cross-635 membrane transport and signal transduction in the Mix group (Fig. 5) also signified 636 the activated extracellular metabolites export and communication within light-637 stimulated microflora. This aligned with prior studies reported that the incandescent 638 light (400–800 nm) could elevate biomass activity [16,19], promote sludge 639 conductivity [17] and favor the sludge colonization [20]. Moreover, the overexpressed 640 Cyt C might also channel e- to other energy-dependent pathways. For example, the 641 other processes in energy metabolism (Nitrogen and Sulfur metabolism) were up-642 regulated under mix-color lighting (Fig. 5). This suggested that visible light 643 stimulation had more advantages on optimizing the energy utilization in anaerobic 644 community, which is fundamental for ensuring the active cell proliferation and 645 31 bioconversion efficiency during ammonia-stressed AD. 646 In summary, light regulated energy metabolism and syntrophic cooperation in a 647 more energy-conserving way. Blue and green light stimulated the Ech activity, 648 coupling the H2 metabolism for energy generation, and subsequently favored the H2-649 utilizing methanogenesis. Comparatively, mix-color lighting triggered the cross-650 membrane e-generation with upregulated Cty C level, enhancing collaboration 651 between e- donating and accepting anaerobes. Therefore, mix-color lighting shifted 652 the cell-cell collaboration towards exergonic IET under ammonia stress, saving more 653 energy and redox equivalents for methanogenesis. 654 3.6 Proposed mechanism of light-triggered metabolic enhancement 655 By establishing connections among microbial structure, metabolic pathways, 656 cell-cell interactions and digestion performance, the roles of light in different 657 wavelengths were elucidated. Under single-color lighting, microbial abundance and 658 diversity shared the similarity with the Dark group (Fig. 4b−e), characterized by 659 lower levels of syntrophic VFAs oxidizers (Fig. 3a). However, relatively abundant 660 sugar degraders, acidogenic bacteria, SAOB, and Methanosarcina contributed to 661 improved performance under single-color lighting (Fig. 3b and Fig. 4a). Notably, light 662 colors also exerted varying effects on metabolism. Glycolysis, Energy metabolism 663 (e.g., sulfur and nitrogen metabolism), and Genetic information processing (e.g., 664 Transcription and DNA replication) were influenced by blue and green light (Fig. 8a). 665 Particularly, gene encoding key enzymes involved in AM, HM and MM were 666 stimulated by blue and green lighting. These could be the main reasons for the similar 667 32  community with dark control, but better digestion performance observed in the Blue 668 and Green groups. Whereas anaerobes in the Red group equipped with upregulated 669 Two-component system, could directly sense red light signals and excite the cell cycle 670 and motility (Fig. 8b). Consequently, red-light activated bacteria gained advantages in 671 biomass growth and substrate uptake, facilitating rapid adaptation in shorten lag time 672 (Fig. 1a) and accelerated acetate utilization (Fig. 2a).  673 While versatile Methanosarcina dominated in all the illuminated groups, the 674 prevalences of HM (42–45%, calculated based on Fig. S3) were observed under 675 single-color lighting. However, in the Mix group, both Methanosarcina and 676 Methanosaeta experienced a maximal enrichment (Fig. 4a), and AM (42%) became 677 the dominant methanogenic pathway (Fig. 8c). Mix-color lighting evenly enriched the 678 diverse fermentative bacteria functioning in ammonia assimilation, sugar fermentation, 679 VFAs degradation, and acetate oxidation (Fig. 3b). This could be attributed to the 680 synergistic strengths of full wavelengths in mixed-color light, contributing not only to 681 the enhanced microflora diversity, but also the activated cellular metabolism. 682 Proposed mechanisms for mixed visible light-induced activation were outlined (Fig. 683 8c): (1) Microbes with different functions in the Mix group might catch the light 684 signals (probably the long red waveband) via Signal transduction (Two-component 685 system) on membrane firstly. (2) Light signals then might stimulate the cross-686 membrane transport system (PTS, bacterial secretion system), altering substrate 687 uptake, carbohydrate metabolism, and metabolite export. (3) Membrane-associated 688 respiratory chain units for e- transport (complexes III, IV, and Cyt C) and energy 689 33 generation (ATPase) were regulated, leading to conservation of redox equivalents (e-) 690 and energy (ATP) for cellular activity.  (4) Excess e- generated cross the membrane 691 could engage in intracellular ATP-dependent metabolisms (Nitrogen and Sulfur 692 metabolism) or participate in extracellular electronic flux through Cyt C. (5) 693 Sufficient Cyt C could channel e- to electroactive methanogens in close proximity, 694 favoring IET-associated methanogenesis. (6) The electroactive methanogens 695 (Methanosaeta and Methanosarcina) directly utilized the extracellular redox 696 equivalents in respiration and Methane metabolism, which was particularly stimulated 697 by blue and green light (short wavelengths). (7) The IET-facilitated electronic 698 connections might enhance community-level QS systems, bolster cell-cell networks 699 and aggregation for synergistic organic conversion. Unlike the single-color lighting, 700 mix-color lighting could modulate the microbial behaviors at both the cell and701 population levels, diversify the functional microbes and thus strengthen the 702 bioconversion of glucose → VFAs → acetate → CH4 under ammonia stress.  703 3.7 Novelty and implications 704 Although employing light stimulation to enhance AD performance has gained 705 attention, the underlying mechanisms governing photoactivation within anaerobic 706 consortia remain largely unexplored. This study presented a novel focus on analyzing 707 the effects of light quality (light wavelengths) on ammonia-stressed AD from 708 comprehensive perspectives. Key findings included: (1) Irrespective of the light 709 wavelength, the dominance of Methanosarcina within the archaeal community 710 indicated an unprecedented affinity of these methanogens to light stimulation under 711 34 ammonia stress. (2) Light-enriched Methanosarcina behaved differently when 712 exposed to diverse wavelengths. Under single-color lighting, they were metabolically 713 active via CO2 reduction pathway with an IHT-associated syntrophic bacteria 714 community. This H2-dependent methanogenesis was highly associated with the 715 upregulated Ech and enzymes involved in HM under blue and green light, and the 716 enriched syntrophic SAOB under red light. However, when exposed to mixed visible 717 light, Methanosarcina preferred the acetate decarboxylation pathway for CH4 718 conversion, which was facilitated by a more energy-efficient syntrophic network via 719 IET. Consequently, the growth and metabolism of anaerobes via electronic 720 collaboration were faster and more robust than conventional IHT, contributing to the 721 steadily increased CH4 production and complete organic conversion under mixed 722 visible lighting. Notably, this study stands as the first to elucidate light-triggered 723 improvement by linking the gene abundance involved in cellular-level metabolism 724 with population-wide cell-cell networks. These novel discoveries could bridge the gap 725 to reveal the mystery of visible light stimulation on anaerobic bioprocess and guide 726 the practical transformation from lab scale to engineering scale. 727 From a long-term energy recovery and stability perspective, harnessing natural 728 visible light is a more environmentally friendly alternative to artificial LED lighting. 729 According to a 2-month semi-continuous study (Fig. S4), solar lighting within visible 730 wavelengths (370–800 nm) outperformed conventional dark AD across varying 731 ammonia inhibition levels (2500–5000 mg/L). This outcome underscored the 732 practical viability of establishing a solar-assisted bioconversion system for waste 733 35  treatment and renewable energy generation. In this system, no additional chemicals or 734 complex processes are required. And the input ammonia-rich feedstock (e.g., livestock 735 waste, blackwater and waste sludge) could be efficiently converted by naturally 736 derived anaerobes into clean, carbon-neutral biogas under sunlight.  Furthermore, 737 bioinformatic analysis on microbial communities and metagenomic predictions 738 suggested that specific metabolic byproducts (e.g., raw H2 and commercial VFAs) can 739 be generated by filtering specific wavelengths during fermentation. Consequently, the 740 scientific novelty coupled with practical implications of solar-assisted system 741 proposed by this study may pave the path for the future development of economically 742 feasible and environmentally friendly waste-to-energy system on a large scale. 743 4. Conclusion 744 This study pioneered a comprehensive exploration on the role of visible light 745 with different wavelengths in enhancing the ammonia-stressed anaerobic digestion. 746 Intricate relationships between light wavelengths and anaerobic consortium responses 747 were revealed based on the linkage among digestion performance, microbial structure 748 and metagenetic prediction. Short wavebands in blue and green light excited genes 749 encoding Energy metabolism and Methane metabolism, while long wavebands in red 750 light upregulated the Cell growth and Cell motility. Benefiting from the combined 751 strengths of short and long wavelengths, mix-color lighting outperformed the 752 digestion efficiency by forming a Methanosarcina-dominant microflora (90% of 753 methanogenic community) with optimal CH4 generation pathways. The specifically 754 upregulated syntrophic acid oxidizing bacteria, electroactive methanogens and 755 36 extracellular electron transport system (c-type cytochrome and Quorum sensing) 756 facilitated the cell-cell associations for fast and stable organic conversion into CH4 757 under mixed visible light. This novel insight highlighted the potential of harnessing 758 natural visible light to assist the organic bioconversion in practice, presenting a 759 promising approach for ammonia-rich waste treatment and renewable energy 760 production. This research collectively bridges knowledge gaps, providing insights into 761 the profound influence of visible light on anaerobic bioprocesses, and offers a 762 practical path toward sustainable waste-to-energy management in practical 763 commercialization. 764 Acknowledgement 765 This research was supported by Scientific Research (B) 22H03778 and Grant-in-766 Aid for Exploratory Research 21k19628 from Japan Society for the Promotion of 767 Science. 768 References 769 [1] H.Y. Leong, C.K. Chang, K.S. Khoo, K.W. Chew, S.R. Chia, J.W. Lim, J.S.770 Chang, P.L. Show, Waste biorefinery towards a sustainable circular771 bioeconomy: a solution to global issues, Biotechnol. Biofuels. 14 (2021) 1–15.772 https://doi.org/10.1186/s13068-021-01939-5.773 [2] R. Ochieng, A. Gebremedhin, S. Sarker, Integration of Waste to Bioenergy774 Conversion Systems: A Critical Review, Energies. 15 (2022).775 https://doi.org/10.3390/en15072697.776 [3] R. Bedoić, L. Čuček, B. Ćosić, D. Krajnc, G. Smoljanić, Z. Kravanja, D.777 37 Ljubas, T. Pukšec, N. Duić, Green biomass to biogas – A study on anaerobic 778 digestion of residue grass, J. Clean. Prod. 213 (2019) 700–709. 779 https://doi.org/10.1016/J.JCLEPRO.2018.12.224. 780 [4] G. Li, F. Xu, T. Yang, X. Wang, T. Lyu, Z. Huang, Microbial Behavior and781 Influencing Factors in the Anaerobic Digestion of Distiller: A Comprehensive 782 Review, Fermentation. 9 (2023) 1–29. 783 https://doi.org/10.3390/fermentation9030199. 784 [5] J. Liu, J. Luo, J. Zhou, Q. Liu, G. Qian, Z.P. Xu, Inhibitory effect of high-785 strength ammonia nitrogen on bio-treatment of landfill leachate using EGSB 786 reactor under mesophilic and atmospheric conditions, Bioresour. Technol. 113 787 (2012) 239–243. https://doi.org/10.1016/j.biortech.2011.11.114. 788 [6] M. Czatzkowska, M. Harnisz, E. Korzeniewska, I. Koniuszewska, Inhibitors of789 the methane fermentation process with particular emphasis on the 790 microbiological aspect: A review, Energy Sci. Eng. 8 (2020) 1880–1897. 791 https://doi.org/10.1002/ese3.609. 792 [7] S. Sawayama, K. Tsukara, T. Yagishita, Water treatment, Poly-b- 793 hydroxybutyrate production using lighted upflow anaerobic sludge blanket 794 method, J. Biosci. Bioeng. 87 (1999) 683–689. 795 [8] S. Sawayama, K. Tsukahara, T. Yagishita, S. Hanada, Characterization of796 lighted upflow anaerobic sludge blanket (LUASB) method under sulfate-rich 797 conditions, J. Biosci. Bioeng. 91 (2001) 195–201. 798 https://doi.org/10.1016/S1389-1723(01)80065-7. 799 38 [9] C. Tada, S. Sawayama, Photoenhancement of biogas production from 800 thermophilic anaerobic digestion, J. Biosci. Bioeng. 98 (2004) 387–390. 801 https://doi.org/10.1016/s1389-1723(04)00301-9. 802 [10] C. Tada, K. Tsukahara, S. Sawayama, Illumination enhances methane803 production from thermophilic anaerobic digestion, Appl. Microbiol. Biotechnol. 804 71 (2006) 363–368. https://doi.org/10.1007/s00253-005-0146-z. 805 [11] A. Kiener, R. Gall, T. Rechsteiner, T. Leisinger, Photoreactivation in806 Methanobacterium thermoautotrophicum, Arch. Microbiol. 143 (1985) 147–807 150. https://doi.org/10.1007/BF00411038.808 [12] K.D. Olson, C.W. Mcmahon, R.S. Wolfe, Photoactivation of the 2-809 (methylthio)ethanesulfonic acid reductase from Methanobacterium, Proc. Natl. 810 Acad. Sci. U. S. A. (1991). https://doi.org/10.1073/pnas.88.10.4099. 811 [13] Y. Yang, K. Tsukahara, Z. Zhang, N. Sugiura, S. Sawayama, Optimization of812 illumination time for the production of methane using carbon felt fluidized bed 813 bioreactor in thermophilic anaerobic digestion, Biochem. Eng. J. 44 (2009) 814 131–135. https://doi.org/10.1016/j.bej.2008.11.009. 815 [14] Y. Yang, K. Tsukahara, R. Yang, Z. Zhang, S. Sawayama, Enhancement on816 biodegradation and anaerobic digestion efficiency of activated sludge using a 817 dual irradiation process, Bioresour. Technol. 102 (2011) 10767–10771. 818 https://doi.org/10.1016/j.biortech.2011.09.018. 819 [15] M.S. Majeed, R.Q. Nafil, R.K. Fakher Alfahed, Laser improves biogas820 production by anaerobic digestion of cow dung, Baghdad Sci. J. 15 (2018) 821 39  324–327. https://doi.org/10.21123/bsj.2018.15.3.0324. 822 [16] N. Zhang, M.S. Stanislaus, X. Hu, C. Zhao, Q. Zhu, D. Li, Y. Yang, Strategy of 823 mitigating ammonium-rich waste inhibition on anaerobic digestion by using 824 illuminated bio-zeolite fixed-bed process, Bioresour. Technol. 222 (2016) 59–825 65. https://doi.org/10.1016/j.biortech.2016.09.053. 826 [17] H. Zheng, A. Sharma, Q. Ma, C. Zhang, T. Hiranuma, Y. Chen, G. Chen, Y. 827 Yang, Development of an oyster shell and lignite modified zeolite (OLMZ) 828 fixed bioreactor coupled with intermittent light stimulation for high efficient 829 ammonium-rich anaerobic digestion process, Chem. Eng. J. 398 (2020) 161. 830 https://doi.org/10.1016/j.cej.2020.125637. 831 [18] Y. Zhu, N. Zhang, Z. Liu, N. Liu, A. Sharma, G. Chen, Y. Yang, Photon 832 number based anaerobic digestion process for efficient bio-methane conversion 833 from ammonium-rich feedstock: Performance evaluation and practical potential, 834 Energy Convers. Manag. 238 (2021) 114155. 835 https://doi.org/10.1016/J.ENCONMAN.2021.114155. 836 [19] Z. Liu, Y. Zhu, C. Zhao, C. Zhang, J. Ming, A. Sharma, G. Chen, Y. Yang, 837 Light stimulation strategy for promoting bio-hydrogen production: Microbial 838 community, metabolic pathway and long-term application, Bioresour. Technol. 839 350 (2022) 126902. https://doi.org/10.1016/j.biortech.2022.126902. 840 [20] Y. Zhu, Z. Liu, C. Zhang, J. Ming, G. Chen, Y. Yang, Light triggers green 841 recovery: Boosted biomethane production from ammonia-stressed anaerobic 842 digestion through optimized illuminated bioreactor, Chem. Eng. J. 450 (2022) 843 40 138173. https://doi.org/10.1016/j.cej.2022.138173. 844 [21] J. Qian, Y. Zhang, P. Wang, B. Lu, Y. He, S. Tang, Z. Yi, Light alters845 microbiota and electron transport: Evidence for enhanced mesophilic digestion 846 of municipal sludge, Water Res. 217 (2022) 118447. 847 https://doi.org/10.1016/j.watres.2022.118447. 848 [22] P. Sowa, J. Rutkowska-Talipska, K. Rutkowski, B. Kosztyła-Hojna, R.849 Rutkowski, Optical radiation in modern medicine, Postep. Dermatologii i 850 Alergol. 30 (2013) 246–251. https://doi.org/10.5114/pdia.2013.37035. 851 [23] T. Karu, L. Pyatibrat, G. Kalendo, Irradiation with He-Ne laser increases ATP852 level in cells cultivated in vitro, J. Photochem. Photobiol. B Biol. 27 (1995) 853 219–223. 854 [24] T.J. Karu, O.A. Tiphlova, V.S. Letokhov, V. V. Lobko, Stimulation of E. coli855 growth by laser and incoherent red light, Nuovo Cim. D 1983 24. 2 (1983) 856 1138–1144. https://doi.org/10.1007/BF02457148. 857 [25] K.D. Olson, C.W. McMahon, R.S. Wolfe, Light sensitivity of methanogenic858 archaebacteria, Appl. Environ. Microbiol. 57 (1991) 2683–2686. 859 https://doi.org/https://doi.org/10.1128/aem.57.9.2683-2686.1991. 860 [26] E.J. Lyon, S. Shima, G. Buurman, S. Chowdhuri, A. Batschauer, K. Steinbach,861 R.K. Thauer, UV-A/blue-light inactivation of the “metal-free” hydrogenase 862 (Hmd) from methanogenic archaea: The enzyme contains functional iron after 863 all, Eur. J. Biochem. 271 (2004) 195–204. https://doi.org/10.1046/j.1432-864 1033.2003.03920.x. 865 41 [27] J. Zhang, L. Mao, L. Zhang, K.C. Loh, Y. Dai, Y.W. Tong, Metagenomic866 insight into the microbial networks and metabolic mechanism in anaerobic 867 digesters for food waste by incorporating activated carbon, Sci. Rep. 7 (2017) 868 11293. https://doi.org/10.1038/s41598-017-11826-5. 869 [28] S. Yang, Z. Chen, Q. Wen, Impacts of biochar on anaerobic digestion of swine870 manure: Methanogenesis and antibiotic resistance genes dissemination, 871 Bioresour. Technol. 324 (2021) 124679. 872 https://doi.org/10.1016/J.BIORTECH.2021.124679. 873 [29] S.H. Yoon, S.M. Ha, S. Kwon, J. Lim, Y. Kim, H. Seo, J. Chun, Introducing874 EzBioCloud: A taxonomically united database of 16S rRNA gene sequences 875 and whole-genome assemblies, Int. J. Syst. Evol. Microbiol. 67 (2017) 1613–876 1617. https://doi.org/10.1099/ijsem.0.001755. 877 [30] S. Poirier, C. Madigou, T. Bouchez, O. Chapleur, Improving anaerobic878 digestion with support media: Mitigation of ammonia inhibition and effect on 879 microbial communities, Bioresour. Technol. 235 (2017) 229–239. 880 https://doi.org/10.1016/j.biortech.2017.03.099. 881 [31] S. Passarella, E. Casamassima, S. Molinari, D. Pastore, E. Quagliariello, I.M.882 Catalano, A. Cingolani, Increase of proton electrochemical potential and ATP 883 synthesis in rat liver mitochondria irradiated in vitro by helium-neon laser, 884 FEBS Lett. 175 (1984) 95–99. https://doi.org/10.1016/0014-5793(84)80577-3. 885 [32] E. Abdelsalam, M. Samer, M.A. Abdel-Hadi, H.E. Hassan, Y. Badr, Influence886 of laser irradiation on rumen fluid for biogas production from dairy manure, 887 42 Energy. 163 (2018) 404–415. https://doi.org/10.1016/J.ENERGY.2018.08.118. 888 [33] X. Pan, L. Zhao, C. Li, I. Angelidaki, N. Lv, J. Ning, G. Cai, G. Zhu, Deep889 insights into the network of acetate metabolism in anaerobic digestion: 890 focusing on syntrophic acetate oxidation and homoacetogenesis, Water Res. 891 190 (2021) 116774. https://doi.org/10.1016/j.watres.2020.116774. 892 [34] M. Felchner-Zwirello, Propionic acid degradation by syntrophic bacteria during893 anaerobic biowaste digestion, 2014. https://doi.org/10.5445/KSP/1000037825. 894 [35] S. Poirier, E. Desmond-Le Quéméner, C. Madigou, T. Bouchez, O. Chapleur,895 Anaerobic digestion of biowaste under extreme ammonia concentration: 896 Identification of key microbial phylotypes, Bioresour. Technol. 207 (2016) 92–897 101. https://doi.org/10.1016/J.BIORTECH.2016.01.124.898 [36] M. Yan, L. Treu, S. Campanaro, H. Tian, X. Zhu, B. Khoshnevisan, P.899 Tsapekos, I. Angelidaki, I.A. Fotidis, Effect of ammonia on anaerobic digestion 900 of municipal solid waste: Inhibitory performance, bioaugmentation and 901 microbiome functional reconstruction, Chem. Eng. J. 401 (2020). 902 https://doi.org/10.1016/j.cej.2020.126159. 903 [37] Y. Yan, M. Yan, G. Ravenni, I. Angelidaki, D. Fu, I.A. Fotidis, Novel904 bioaugmentation strategy boosted with biochar to alleviate ammonia toxicity in 905 continuous biomethanation, Bioresour. Technol. 343 (2022) 126146. 906 https://doi.org/10.1016/J.BIORTECH.2021.126146. 907 [38] X. Wang, P. Wang, X. Meng, L. Ren, Performance and metagenomics analysis908 of anaerobic digestion of food waste with adding biochar supported nano zero-909 43 valent iron under mesophilic and thermophilic condition, Sci. Total Environ. 910 820 (2022) 153244. https://doi.org/10.1016/j.scitotenv.2022.153244. 911 [39] S. Esquivel-Elizondo, P. Parameswaran, A.G. Delgado, J. Maldonado, B.E.912 Rittmann, R. Krajmalnik-Brown, Archaea and bacteria acclimate to high total 913 ammonia in a methanogenic reactor treating swine waste, Archaea. (2016) 914 4089684. https://doi.org/10.1155/2016/4089684. 915 [40] D. Ho, P. Jensen, M.L. Gutierrez-Zamora, S. Beckmann, M. Manefield, D.916 Batstone, High-rate, high temperature acetotrophic methanogenesis governed 917 by a three population consortium in anaerobic bioreactors, PLoS One. 11 (2016) 918 e0159760. https://doi.org/10.1371/JOURNAL.PONE.0159760. 919 [41] Z. Wang, Y. Guo, W. Wang, L. Chen, Y. Sun, T. Xing, X. Kong, Effect of920 biochar addition on the microbial community and methane production in the 921 rapid degradation process of corn straw, Energies. 14 (2021) 2223. 922 https://doi.org/10.3390/en14082223. 923 [42] R. Arthur, S. Antonczyk, S. Off, P.A. Scherer, Mesophilic and thermophilic924 anaerobic digestion of wheat straw in a CSTR system with ‘synthetic manure’: 925 impact of nickel and tungsten on methane yields, cell count, and microbiome, 926 Bioengineering. 9 (2022) 13. https://doi.org/10.3390/bioengineering9010013. 927 [43] A. Poehlein, V. V. Zverlov, R. Daniel, W.H. Schwarz, W. Liebl, Complete928 genome sequence of Clostridium stercorarium subsp. stercorarium strain DSM 929 8532, a thermophilic degrader of plant cell wall fibers, Genome Announc. 1 930 (2013) 8–9. https://doi.org/10.1128/genomeA.00073-13. 931 44 [44] X. Dai, H. Yan, N. Li, J. He, Y. Ding, L. Dai, B. Dong, Metabolic adaptation of 932 microbial communities to ammonium stress in a high solid anaerobic digester 933 with dewatered sludge, Sci. Rep. 6 (2016) 1–10. 934 https://doi.org/10.1038/srep28193. 935 [45] G. Lembo, S. Rosa, V.M. Miritana, A. Marone, G. Massini, M. Fenice, A.936 Signorini, Thermophilic anaerobic digestion of second cheese whey: microbial 937 community response to H2 addition in a partially immobilized anaerobic hybrid 938 reactor, Process. 2021, Vol. 9, Page 43. 9 (2020) 43. 939 https://doi.org/10.3390/PR9010043. 940 [46] H. Tian, E. Mancini, L. Treu, I. Angelidaki, I.A. Fotidis, Bioaugmentation941 strategy for overcoming ammonia inhibition during biomethanation of a 942 protein-rich substrate, Chemosphere. 231 (2019) 415–422. 943 https://doi.org/10.1016/j.chemosphere.2019.05.140. 944 [47] C. Liu, Y. Chen, H. Huang, X. Duan, L. Dong, Improved anaerobic digestion945 under ammonia stress by regulating microbiome and enzyme to enhance VFAs 946 bioconversion: The new role of glutathione, Chem. Eng. J. 433 (2022) 134562. 947 https://doi.org/10.1016/J.CEJ.2022.134562. 948 [48] S. Wainaina, Lukitawesa, M. Kumar Awasthi, M.J. Taherzadeh,949 Bioengineering of anaerobic digestion for volatile fatty acids, hydrogen or 950 methane production: A critical review, Bioengineered. 10 (2019) 437–458. 951 https://doi.org/10.1080/21655979.2019.1673937. 952 [49] D.G. Zavarzina, T.P. Tourova, T. V. Kolganova, E.S. Boulygina, T.N. Zhilina,953 45 Description of Anaerobacillus alkalilacustre gen. nov., sp. nov.—Strictly 954 anaerobic diazotrophic bacillus isolated from soda lake and transfer of Bacillus 955 arseniciselenatis, Bacillus macyae, and Bacillus alkalidiazotrophicus to 956 Anaerobacillus as the new combinations A. arseniciselenatis comb. nov., A. 957 macyae comb. nov., and A. alkalidiazotrophicus comb. nov., Microbiol. 2009 958 786. 78 (2009) 723–731. https://doi.org/10.1134/S0026261709060095.959 [50] N. Ahsan, M. Shimizu, Lysinibacillus species: Their potential as effective960 bioremediation, biostimulant, and biocontrol agents, Rev. Agric. Sci. 9 (2021) 961 103–116. https://doi.org/10.7831/RAS.9.0_103. 962 [51] H. Tian, I.A. Fotidis, E. Mancini, L. Treu, A. Mahdy, M. Ballesteros, C.963 González-Fernández, I. Angelidaki, Acclimation to extremely high ammonia 964 levels in continuous biomethanation process and the associated microbial 965 community dynamics, Bioresour. Technol. 247 (2018) 616–623. 966 https://doi.org/10.1016/J.BIORTECH.2017.09.148. 967 [52] Q. Niu, T. Kobayashi, Y. Takemura, K. Kubota, Y.Y. Li, Evaluation of968 functional microbial community’s difference in full-scale and lab-scale 969 anaerobic digesters feeding with different organic solid waste: Effects of 970 substrate and operation factors, Bioresour. Technol. 193 (2015) 110–118. 971 https://doi.org/10.1016/j.biortech.2015.05.107. 972 [53] X. Zhu, S. Campanaro, L. Treu, R. Seshadri, N. Ivanova, P.G. Kougias, N.973 Kyrpides, I. Angelidaki, Metabolic dependencies govern microbial syntrophies 974 during methanogenesis in an anaerobic digestion ecosystem, Microbiome. 8 975 46 (2020) 1–14. https://doi.org/10.1186/S40168-019-0780-9/FIGURES/6.976 [54] L. Li, Y. Xu, X. Dai, L. Dai, Principles and advancements in improving977 anaerobic digestion of organic waste via direct interspecies electron transfer, 978 Renew. Sustain. Energy Rev. 148 (2021) 111367. 979 https://doi.org/10.1016/J.RSER.2021.111367. 980 [55] Y. Jiang, E. McAdam, Y. Zhang, S. Heaven, C. Banks, P. Longhurst, Ammonia981 inhibition and toxicity in anaerobic digestion: A critical review, J. Water 982 Process Eng. 32 (2019). https://doi.org/10.1016/j.jwpe.2019.100899. 983 [56] T.L. Netzel, Electron transfer reactions in methanogens, J. Chem. Educ. 74984 (1997) 646–651. https://doi.org/10.1021/ed074p646. 985 [57] B. Müller, L. Sun, M. Westerholm, A. Schnürer, Bacterial community986 composition and fhs profiles of low- and high-ammonia biogas digesters reveal 987 novel syntrophic acetate-oxidising bacteria, Biotechnol. Biofuels. 9 (2016) 48. 988 https://doi.org/10.1186/S13068-016-0454-9. 989 [58] S.J. Haig, C. Quince, R.L. Davies, C.C. Dorea, G. Collinsa, The relationship990 between microbial community evenness and function in slow sand filters, 991 MBio. 6 (2015) e00729-15. https://doi.org/10.1128/mBio.00729-15. 992 [59] W. Zhang, X. Li, Y. He, X. Xu, H. Chen, A. Zhang, Y. Liu, G. Xue, J. Makinia,993 Ammonia amendment promotes high rate lactate production and recovery from 994 semi-continuous food waste fermentation, Bioresour. Technol. 302 (2020) 995 122881. https://doi.org/10.1016/J.BIORTECH.2020.122881. 996 [60] T.R.D. Costa, C. Felisberto-Rodrigues, A. Meir, M.S. Prevost, A. Redzej, M.997 47 Trokter, G. Waksman, Secretion systems in Gram-negative bacteria: structural 998 and mechanistic insights, Nat. Rev. Microbiol. 2015 136. 13 (2015) 343–359. 999 https://doi.org/10.1038/nrmicro3456. 1000 [61] T. Zhang, P. Zhang, Z. Hu, Q. Qi, Y. He, J. Zhang, New insight on Fe-1001 bioavailability: Bio-uptake, utilization and induce in optimizing methane 1002 production in anaerobic digestion, Chem. Eng. J. 441 (2022) 136099. 1003 https://doi.org/10.1016/J.CEJ.2022.136099. 1004 [62] M. Wang, X. Zhang, H. Huang, Z. Qin, C. Liu, Y. Chen, Amino Acid1005 Configuration Affects Volatile Fatty Acid Production during Proteinaceous 1006 Waste Valorization: Chemotaxis, Quorum Sensing, and Metabolism, Cite This 1007 Environ. Sci. Technol. 2022 (2022) 8711. 1008 https://doi.org/10.1021/acs.est.1c07894. 1009 [63] L.L. Barton, Structural and Functional Relationships in Prokaryotes, Springer-1010 Verlag, 2005. https://doi.org/10.1007/b138652. 1011 [64] Z. Zhao, J. Wang, Y. Li, T. Zhu, Q. Yu, T. Wang, S. Liang, Y. Zhang, Why do1012 DIETers like drinking: Metagenomic analysis for methane and energy 1013 metabolism during anaerobic digestion with ethanol, Water Res. 171 (2020) 1014 115425. https://doi.org/10.1016/j.watres.2019.115425. 1015 [65] J. Cheng, H. Li, L. Ding, J. Zhou, W. Song, Y.Y. Li, R. Lin, Improving1016 hydrogen and methane co-generation in cascading dark fermentation and 1017 anaerobic digestion: The effect of magnetite nanoparticles on microbial 1018 electron transfer and syntrophism, Chem. Eng. J. 397 (2020) 125394. 1019 48  https://doi.org/10.1016/j.cej.2020.125394. 1020 [66] N. Zhang, H. Peng, Y. Li, W. Yang, Y. Zou, H. Duan, Ammonia determines 1021 transcriptional profile of microorganisms in anaerobic digestion, Brazilian J. 1022 Microbiol. 49 (2018) 770–776. https://doi.org/10.1016/j.bjm.2018.04.008. 1023 [67] S. Dyksma, L. Jansen, C. Gallert, Syntrophic acetate oxidation replaces 1024 acetoclastic methanogenesis during thermophilic digestion of biowaste, 1025 Microbiome. 8(1) (2020) 1–14. https://doi.org/10.1186/s40168-020-00862-5. 1026 [68] C. Welte, U. Deppenmeier, Bioenergetics and anaerobic respiratory chains of 1027 aceticlastic methanogens, Biochim. Biophys. Acta - Bioenerg. 1837 (2014) 1028 1130–1147. https://doi.org/10.1016/j.bbabio.2013.12.002. 1029 [69] F. Mahlert, C. Bauer, B. Jaun, R.K. Thauer, E.C. Duin, The nickel enzyme 1030 methyl-coenzyme M reductase from methanogenic archaea: In vitro induction 1031 of the nickel-based MCR-ox EPR signals from MCR-red2, J. Biol. Inorg. 1032 Chem. 7 (2002) 500–513. https://doi.org/10.1007/s00775-001-0325-z. 1033 [70] P. Mitchell and J. Moyle., Evidence discriminating between the Chemical and 1034 the Chemiosmotic Mechanisms of Electron Transport Phosphorylation, Nature. 1035 208 (1965) 1205–1206. https://doi.org/https://doi.org/10.1038/2081205a0. 1036 [71] L.J. Bird, V. Bonnefoy, D.K. Newman, Bioenergetic challenges of microbial 1037 iron metabolisms, Trends Microbiol. 19 (2011) 330–340. 1038 https://doi.org/10.1016/J.TIM.2011.05.001. 1039 [72] S. Lenzen, A fresh view of glycolysis and glucokinase regulation: History and 1040 current status, J. Biol. Chem. 289 (2014) 12189–12194. 1041 49 https://doi.org/10.1074/jbc.R114.557314. 1042 [73] M.C. Schoelmerich, V. Müller, Energy-converting hydrogenases: the link1043 between H2 metabolism and energy conservation, Cell. Mol. Life Sci. 77 (2020) 1044 1461–1481. https://doi.org/10.1007/S00018-019-03329-5. 1045 [74] M. Wang, T. Ren, M. Yin, K. Lu, H. Xu, X. Huang, X. Zhang, Enhanced1046 Anaerobic Wastewater Treatment by a Binary Electroactive Material : 1047 Pseudocapacitance / Conductance-Mediated Microbial Interspecies Electron 1048 Transfer, (2023). https://doi.org/10.1021/acs.est.3c01986. 1049 1050 Table 1 Kinetic parameters of modified Gompertz model on lighted AD with different wavelengths Group Parameter Dark Blue Green Red Mix Start up Mmax 228 593 172 1014 797 Rmax 86 253 415 292 91 λ 2.1 2.9 0.7 1.3 0.4 R2 0.990 0.975 0.992 0.978 0.931 Cycle 1 Mmax 158 489 452 438 778 Rmax 141 487 703 420 828 λ 0.6 0.3 0.2 0.1 0.5 R2 0.990 0.993 0.999 0.974 0.999 Cycle 2 Mmax 254 123 489 546 628 Rmax 122 60 523 656 690 λ 0.9 0.8 0.2 0.9 0.7 R2 0.999 0.991 0.997 0.999 0.998 Mmax: maximum cumulative methane production in each cycle, (mL/L) Rmax: maximum methane production rate, (mL/(L·d)) λ: lag-phase time, (d) https://www2.cloud.editorialmanager.com/cej/download.aspx?id=6931375&guid=e2e470b8-cba8-4264-8a25-14cdba77a171&scheme=1https://www2.cloud.editorialmanager.com/cej/download.aspx?id=6931375&guid=e2e470b8-cba8-4264-8a25-14cdba77a171&scheme=1Table 2 Common reactions and thermodynamics of AD via interspecies hydrogen transfer (IHT) and interspecies electron transfer (IET) pathways. Pathway Equation ΔG0’ (kJ/mol) Reference Glycolysis C6H12O6 + 2NAD+ + 2ADP + 2Pi → 2C3H4O3 + 2NADH + 2H+ + 2ATP + 2H2O − 96.0 [72] Acidification Syntrophic propionate oxidation IHT C3H5OO− + 2H2O → CH3COO− + 3H2 + CO2 + 76.5[54] IET C3H5OO−+ 3H2O → CH3COO‾+ HCO3‾+ 7H++ 6e- − 162.5Syntrophic butyrate oxidation IHT C4H7OO− + 2H2O → 2CH3COO− + 2H2 + H+ + 48.0IET C4H7OO− + 2H2O → 2CH3COO‾+ 5H++ 4e- − 111.3Syntrophic lactate oxidation IHT 2C3H5O3− + 2H2O → 2CH3COO− + HCO3‾ + H++ 2H2 − 4.2IET 2C3H5O3− + 2H2O → CH3COO− + + HCO3‾ + 5H++ 4e- − 163.5Syntrophic acetate oxidation CH3COO− + 4H2O → 2HCO3− + 4H2 + H+ + 104.6Methanogenesis Hydrogenotrophic 4H2 + HCO3− + H+ → CH4 + 3H2O − 131.0[52] Acetoclastic CH3COO− + H2O → CH4 + HCO3− − 36.0 Methylotrophic 4CH3OH → 3CH4 + HCO3− + H+ + H2O − 105.0Fig. 1. Effect of light wavelengths on ammonia-rich AD performance of (a) cumulative CH4 production, and (b) daily CH4 concentration during three-cycle feed batch (Error bars presented standard deviations of repeated experiments). Fig. 2. Effect of light wavelengths on variations of organic byproducts of (a) acetate, and (b) lactate, butyrate and propionate during three-cycle during ammonia-rich AD (bars presented standard deviations of repeated experiments). Fig. 3. Variation of bacterial community under dark and light treatments. (a) Relative abundance of bacterial community at order level; (b) heat map with cluster analysis of dominant bacterial genus under each treatment. Fig. 4. (a) Relative abundance of archaeal community at species level under each treatment, and boxplots for microbial richness and diversity with indexes of (b) observed species, (c) Chao1, (d) phylogenetic diversity (PD) whole tree and (e) Shannon (The *** and ** show significant differences (P < 0.05) and relatively different (0.05 < P < 0.1), respectively).Fig. 5. Heatmap of relative gene abundance coding for metabolic pathway at level 3 based on metagenomic analysis (the corresponded functional categories at level 2 were listed on the right y-axis). Fig. 6. (a) Conceptual graph and marker enzymes involved AM, HM and MM pathways, and (b) Heat map of gene abundance coding for key enzymes involved in methanogenic pathways under dark and light treatments. Fig. 7. (a) Conceptual graph of pathways related to Energy Metabolism in bacteria and archaea based on KEGG mapper, (b) relative abundance of genes coding for complex Figureunits in respiratory chain for ATP production, and (c) relative abundance of energy-converting hydrogenase (Ech) and c-type cytochrome (Cyt C). Fig. 8. Mechanisms of light-triggered metabolic enhancement with (a) short wavelength (blue and green light), (b) long wavelength (red light), and (c) mix-color visible light. Figure 1 FigureFigure 2 FigureFigure 3 FigureFigure 4 FigureFigure 5 Figure(a) (b) Figure 6 FigureFigure 7 Figure(a) (b) (c) Figure 8 Figure