Microbial Interactions Research Articles

Methan-o-poly: a giant collaborative game to "digest" the microbiology of green biogas production.

In an era of rapid change and global challenges, impactful educational experiences about sustainability become imperative. Especially in organic waste conversion bioprocess such as anaerobic digestion (AD). Here proposed, is a gamified approach to learn AD and hidden microbial interactions, bringing to real-life size an invisible phenomenon. In Methan-o-poly, participants roleplay cooperating microbes within a bioreactor engaged in four sequential mini-games to mimic organic waste degradation and methane production. Perturbations in the activity simulate real challenges, enhancing adaptability and problem-solving skills. Overall, this cooperative game promotes motivation, collaboration, and experiential learning. Its initial implementation received positive feedback across various age groups, enhancing green education initiatives.

The Development of Machine Learning-Assisted Software for Predicting the Interaction Behaviours of Lactic Acid Bacteria and Listeria monocytogenes

Biopreservation technology has emerged as a promising approach to enhance food safety and extend shelf life by leveraging the antimicrobial properties of beneficial microorganisms. This study aims to develop precise predictive models to characterize the growth and interaction dynamics of lactic acid bacteria (LAB) and Listeria monocytogenes, which serve as bioprotective agents in food systems. Using both traditional and machine learning modelling approaches, we analyzed data from previously published growth curves in broth (BHI) and milk under isothermal conditions (4, 10, and 30 °C). The models evaluated mono-culture conditions for L. monocytogenes and LAB, as well as their competitive interactions in co-culture scenarios. The modified Gompertz model demonstrated the best performance for mono-culture simulations, while a combination of the modified Gompertz and Lotka–Volterra models effectively described co-culture interactions, achieving high adjusted R-squared values (adjusted R2 = 0.978 and 0.962) and low root mean square errors (RMSE = 0.324 and 0.507) for BHI and milk, respectively. Machine learning approaches further validated these findings, with improved statistical indices (adjusted R2 = 0.988 and 0.966, RMSE = 0.242 and 0.475 for BHI and milk, respectively), suggesting their potential as robust alternatives to traditional methods. The integration of machine learning-assisted software developed in this work into predictive microbiology demonstrates significant advancements by bypassing the conventional primary and secondary modelling steps, enabling a streamlined, precise characterization of microbial interactions in food products.

Host–Microbe Interactions in Healthy and CSOM-Affected Middle Ears

Chronic suppurative otitis media (CSOM) is a chronic middle ear inflammatory condition due to persistent polymicrobial middle ear infection. The interaction between local immune responses and microbial communities is not well understood, complicating the development of targeted therapies. This study aimed to characterise local immune cell responses and microbial composition in CSOM-affected middle ear mucosa, focusing on Pseudomonas aeruginosa and Staphylococcus aureus. A total of 24 CSOM patients and 22 controls undergoing tympanomastoid surgery participated in this prospective study. Middle ear and mastoid mucosa were collected for histological and microbiological analysis. Bacterial identification was performed using standard culture methods and Vitek MS, while immune cell populations were quantified via immunohistochemistry. Statistical analyses were performed using Kruskal–Wallis and Mann–Whitney tests. Microbiology results identified multiple pathogens in CSOM, including S. aureus and P. aeruginosa, with polymicrobial infections in 10 samples. CSOM patients exhibited significantly elevated immune cells, including CD3+, CD20+, and CD68+ cells, compared to controls. Histological analysis showed Gram-positive bacteria in three mastoid samples, with positive antibody staining for S. aureus (20.8%) and P. aeruginosa (12.5%) in CSOM patients. Controls had no bacterial staining. Intracellular bacteria may evade host defences and reduce antibiotic efficacy, contributing to CSOM persistence. Targeting intracellular pathogens in future treatments, along with studying polymicrobial communities, could improve management strategies.

Advances in metagenomic sequencing for infectious disease management: From pathogen profiling to antibiotic resistance

Metagenomics has revolutionized the study of infectious diseases by enabling the analysis of microbial communities without the need for cultivation. This approach, powered by high-throughput sequencing technologies like 16S rRNA sequencing and shotgun metagenomics, allows the identification of both culturable and unculturable microbes, providing a comprehensive view of pathogens. Metagenomics offers critical insights into microbial diversity and interactions, particularly in polymicrobial infections, respiratory and gastrointestinal infections, and bloodstream infections. Advancements in bioinformatics, artificial intelligence (AI), and machine learning have enhanced the accuracy and speed of metagenomic data interpretation, aiding pathogen detection, antibiotic resistance surveillance, and personalized treatment strategies. Despite challenges such as sample complexity, host DNA interference, and data interpretation difficulties, metagenomics continues to evolve as a crucial tool for diagnostics and therapeutic development. Future research aims to address current gaps, including integrating AI into metagenomics for more precise pathogen profiling and developing targeted therapies based on microbial communities. Ultimately, metagenomics holds the potential to transform infectious disease management, offering real-time diagnostics, better global surveillance, and the promise of personalized medicine in the fight against emerging pathogens.

Labile Carbon Input Mitigates the Negative Legacy Effects of Nitrogen Addition on Arbuscular Mycorrhizal Symbiosis in a Temperate Grassland

Nitrogen (N) deposition and carbon (C) addition significantly influence the dynamics of plant–microbe interactions, particularly altering the symbiotic relationship between plants and arbuscular mycorrhizal fungi (AMF). However, the effects and underlying mechanisms of labile C input on the relationship between AMF and various plant species in a nitrogen-enriched environment remain a knowledge gap. A seven-year field experiment was conducted to examine how six levels of N and three levels of labile C addition impact AMF colonization in four key plant species: Leymus chinensis (Trin. ex Bunge) Tzvelev, Stipa baicalensis Roshev., Thermopsis lanceolata R. Br. and Potentilla bifurca Linn. Our results showed that N and C additions exert significantly different effects on the relationship between AMF and various plant species. Labile C addition mitigated historical N negative effects, particularly for S. baicalensis, enhancing AMF infection and promoting nutrient exchange under high-N and low-C conditions. The relationship between AMF and both L. chinensis and T. lanceolata changed to weak mutualism under low-N and high-C conditions, with significant decreases in vesicular and arbuscular abundance. Plant root stoichiometry plays a critical role in modulating AMF symbiosis, particularly under high-N and -C conditions, as reflected in the increased AMF infection observed in T. lanceolata and P. bifurca. Our findings emphasize the species-specific and nutrient-dependent AMF symbiosis, revealing that targeted C input can mitigate the legacy effects of N enrichment. Effective nutrient management is of crucial importance for ecological restoration efforts in temperate grasslands affected by long-term N enrichment.

Resilience of human gut microbiomes in autism spectrum disorder: measured using stiffness network analysis.

Autism spectrum disorder (ASD) affects an estimated 1%-2% of children worldwide, but its specific etiology remains unclear. In recent years, the gut microbiome's role in ASD pathogenesis has garnered increasing attention. However, the exact relationship between microbiota and ASD-such as which microbial species significantly impact disease onset and progression-remains unresolved, and effective methods to measure microbial interactions are still lacking. In this study, we introduce an innovative stiffness network analysis (SNA) method to quantify changes in microbial network structure and identify disease-specific microbial bacteria theoretically. The SNA method was applied to reanalyze eight ASD gut microbiome data sets, encompassing 898 ASD samples and 467 healthy control (HC) samples from 16S-rRNA sequencing data. Key findings include the following: (i) an "allies" biomarker subgroup consisting of Bacteroides plebeius, Sutterella, Lachnospira, and Prevotella copri was identified; (ii) a profile monitoring score of 0.72 for the biomarker subgroup, indicating significant relationship changes between HC and ASD states, and (iii) a P/N ratio of biomarker subgroup in ASD-associated gut bacteria that was three times higher than that of HC microbiomes. Additionally, we discuss the non-monotonic relationship alterations within microbial sub-communities in the ASD gut microbiome.IMPORTANCEIt is crucial to assess alterations in network structure in different biological states in order to promote health. The stiffness network allows for the exploration of species interactions and the measurement of resilience in complex microbial networks. The objective of this study was to develop a stiffness network analysis (SNA) method for evaluating the contribution of microbial bacteria in differentiating disease samples from healthy control samples by examining changes in network stiffness parameters. Furthermore, the SNA method was employed on both simulated and real autism spectrum disorder gut microbiome data sets to identify potential microbial biomarker subgroups, with a particular focus on the relationship alterations within microbial networks.

Biogeochemical coupling of C/Fe in oil-polluted wetlands associated with iron reduction

Oil contamination in coastal wetlands jeopardizes these ecosystems and worsens climate warming. Here we analyze 87 metagenomic samples from representative Chinese wetland oilfields and find that genes associated with dissimilatory iron reduction respond to hydrocarbon levels. These genes were closely linked to the breakdown of organic matter into carbon dioxide and methane, highlighting the potential of dissimilatory iron reduction for degrading stubborn hydrocarbons and altering electron transfer pathways. Notably, Geobacter, a key genus for dissimilatory iron reduction, showed strong correlation with iron(II) production and hydrocarbon degradation. To validate these findings, a targeted enhancement of dissimilatory iron reduction with external iron oxide and Geobacter maximized carbon removal, transforming organic-bound fraction of iron into carbonate-bound fraction. The intensified iron reduction process reduced methane emissions by 38–40% and strengthened microbial interactions by redirecting electron transfer in carbon flow. Our study innovatively mitigates pollution and reduces methane emissions in oil-contaminated wetlands.

The Microbial Co-infection Interaction Network in Apical Periodontitis with Sinus Tracts

This study aims to characterize the bacterial co-occurrence features and potential interactions associated with the presence of sinus tracts in apical periodontitis in a Chinese population by using 16S rRNA next-generation sequencing (NGS). Thirty-one samples from twenty-six patients were collected from root canals. Following the extraction of the bacterial DNA, the V3-V4 hypervariable regions of the 16S rRNA gene were sequenced. Compositional diversity, prominent taxa and co-occurrence network analysis were compared according to the presence or absence of sinus tracts. The overall microbiota in two groups exhibited distinguished patterns. Actinomyces dominated in samples with sinus tracts while Prevotella was the most abundant in samples without sinus tracts. The major pathogens in sinus tracts exhibited a complex co-occurrence network, in which Pseudomonas formed a distinctive cluster with enriched abundance, and the extensive correlations centered on Desulfovibrio and Pseudoramibacter may suggest novel dependencies. In the network without sinus tracts, the Bacteroidetes and Firmicutes taxa presented close internal associations. The sequencing results confirmed the complexity of the microbiota in AP. The presence of sinus tracts was associated with distinctive infective patterns and complicated microbial co-infection interaction networks. Further investigations should be adopted to elucidate the relationship between the novel interactions and disease progression. Exploring the microbial interactions leads to a better understanding of etiology of apical periodontitis. Utilizing next generation sequencing techniques, our research uncovered the bacterial community structure and observed co-infection networks associated with sinus tracts, providing potential insights for prognosis prediction and targeted therapeutics of persistent inflammation.

Towards microbial consortia in fermented foods for metabolic engineering and synthetic biology.

The fermented foods microbiota, whose community structures evolve through a succession of different microbial groups, play a central role in fermented food production. The texture and flavor, functions, shelf-life and safety, are largely determined by the interactions among bacteria and yeast within these communities. Although much indispensable work has described the microbial composition and succession in various fermentation foods, yet the specific microbial interactions involved are not well understood. Here, we review the current mechanisms of microbial interactions (amensalism, competition, commensalism, and mutualism) existed in the fermented foods. We also examine the function of these interactions. In addition, we provide our perspectives on the future development of functional and novel fermented foods by combining the new starter cultures with the native microbial consortia and applications of these stable and robust microbial consortia for metabolic engineering and synthetic biology.

Porous polymers embedded with iron carbon enhanced densified activated sludge formation and wastewater treatment

Municipal wastewater treatment plants in China face significant challenges in effectively removing pollutants from low-strength wastewater with a low carbon-to-nitrogen (COD/N) ratio. This study proposes a novel approach incorporating porous polymers embedded with iron-carbon (PP-IC) into an activated sludge system to enhance treatment. The PP-IC accelerated the formation of densified activated sludge (DAS), characterized by small particle sizes (<200 μm), excellent settleability (sludge volume index: 61 mL/g), and improved pollutant removal efficiency, with total nitrogen and total phosphorus removal rates increasing by 14.4 % and 57.4 %, respectively. DAS formation was achieved within 7 days and stabilized after 42 days. The enrichment of microorganisms, including unclassified_f_Caldilineaceae, Dechloromonas, and Candidatus Accumulibacter, further enhanced pollutant removal. Additionally, Fe2+, Fe3+ and hydroxyl radical (·OH) produced by iron-carbon micro-electrolysis supported DAS formation. Microbial interactions with the iron shavings sustained the long-term stability of the micro-electrolysis process. This synergistic mechanism significantly improved pollutant removal in wastewater treatment.

Chitosan and its derivatives: A novel approach to gut microbiota modulation and immune system enhancement.

Chitosan, a biopolymer derived from the deacetylation of chitin found in crustacean shells and certain fungi, has attracted considerable attention for its promising health benefits, particularly in gut microbiota maintenance and immune system modulation. This review critically examines chitosan's multifaceted role in supporting gut health and enhancing immunity, beginning with a comprehensive overview of its sources, chemical structure, and its dual function as a dietary supplement and biomaterial. Chitosan's prebiotic effects are highlighted, with a focus on its ability to selectively stimulate beneficial gut bacteria, such as Bifidobacteria and Lactobacillus, while enhancing gut barrier integrity and inhibiting the growth of pathogenic microorganisms. The review delves deeply into chitosan's immunomodulatory mechanisms, including its impact on antigen-presenting cells, cytokine profiles, and systemic immune responses. A detailed comparative analysis assesses chitosan's efficacy relative to other prebiotics and immunomodulatory agents, examining challenges related to bioavailability and metabolic activity. Beyond its role in gut health, this review explores chitosan's potential as a dual-action agent that not only supports gut microbiota but also fortifies immune resilience. It introduces emerging research on novel chitosan derivatives, such as chitooligosaccharides, and evaluates their enhanced bioactivity for functional food applications. Special attention is given to sustainability, with an exploration of alternative, plant-based sources of chitosan and their implications for both health and environmental stewardship. Also, the review identifies new research avenues, such as the growing interest in chitosan's role in the gut-brain axis and its potential mental health benefits through microbial interactions. By addressing these innovative areas, the review aims to shift the focus from basic health effects to chitosan's broader impact on public health. The findings encourage further exploration, particularly through human trials, and emphasize chitosan's untapped potential in revolutionizing health and disease management.

Deciphering the driving mechanism of microbial community for rapid stabilization and lignocellulose degradation during waste semi-aerobic bioreactor landfilling with multifunctional microbial inoculum.

Owing to the massive refractory lignocellulose and leachate-organic loads, the stabilization of municipal solid waste (MSW) landfill is often prolonged, resulting in environmental burdens. Herein, various assembled multifunctional microbial inoculums (MMIs) were introduced into the semi-aerobic bioreactor landfill (SABL) to investigate the bioaugmentation impacts. Compared to control (CK) and other MMIs treatments (G1-G3), LD+LT+DM inoculation (G4) significantly increased volatile solids degradation (9.72-45.03%), while reducing chemical oxygen demand (COD) content (10.34-51.85%) and ammonia nitrogen concentration (80.71-90.95%) in the leachate. G4 also exhibited significantly higher degradation of cellulose and hemicellulose, achieving 0.99 and 1.94 times higher efficiency than CK, respectively. Microbial analysis revealed that LD+LT+DM reshaped microbial communities composition of SABL, with most of the introduced microorganisms (Enterobacter, Sphingobacterium, Streptomyces, etc.) successfully colonizing, and stimulating indigenous functional microbes associated with organic matter decomposition. Additionally, microbial interactions were strengthened in G4, accompanied by the higher abundance of 11 biomarkers and enzymes involved in lignocellulose degradation and ammonia nitrogen conversion. Overall, LD+LT+DM maximized MMI function by reconstructing synergistic core microbes. These findings highlight the superiority of LD+LT+DM in simultaneously regulating the microbial composition of lignocellulose-rich waste landfills, expediting MSW decomposition, improving leachate treatment, and mitigating odor emissions, offering valuable insights for efficient MSW management.

Effect of silver nanoparticles on biological nitrogen removal in sequential batch wastewater treatment process: Microbial communities, functional genes, and interactions

Effect of silver nanoparticles on biological nitrogen removal in sequential batch wastewater treatment process: Microbial communities, functional genes, and interactions

Arbuscular mycorrhizal fungi enhance drought resistance and alter microbial communities in maize rhizosphere soil

Although the benefits of inoculation with arbuscular mycorrhizal fungi (AMF) for mitigating drought stress and enhancing plant growth of host are well‐studied, our understanding of their interactions with soil attributes and rhizosphere microbial communities remains limited. In the present study, we conducted a pot experiment to explore how AMF affects maize growth, antioxidant activity, soil properties, and the rhizosphere microbial communities under drought stress. The results showed that AMF inoculation during drought stress resulted in improved maize seedling growth, significantly increasing plant biomass (42.7%), chlorophyll content (13.4%), and antioxidant capacity. It also enhanced soil nutrient availability and microbial biomass. We observed significant shifts in the structure and composition of the rhizosphere microbial community with AMF inoculation under drought conditions when compared to those under well-watered conditions. Significantly, bacterial diversity and composition showed greater sensitivity to drought stress than fungal communities. This was attributed to plants preferentially reducing the supply of carbon sources to bacterial rather than to fungal communities under drought conditions. AMF inoculation also enhanced the complexity (e.g., degree) and stability of the rhizosphere microbial ecological network, suggesting closer ecological interactions within the soil microbial community. Furthermore, bacterial diversity and richness played a more important role in soil function than those of fungal communities under drought stress, particularly with AMF inoculation. Overall, our findings suggest that AMF inoculation alters soil microbial diversity and interactions, highlighting their key roles in enhancing plant stress tolerance and mitigating the negative effects of drought on agricultural ecosystems.

Chronic Exposure of Adult Zebrafish to Polyethylene and Polyester-based Microplastics: Metabolomic and Gut Microbiome Alterations Reflecting Dysbiosis and Resilience

The study explored the ecotoxicological effects of chronic exposure to microplastic (MP) on adult zebrafish, focusing on environmentally relevant concentrations of polyethylene (PE) beads and polyester (PES). High-throughput untargeted metabolomics via UPLC-QToF-MS and 16S metagenomics for gut microbiota analysis were used to assess ecotoxicity in zebrafish exposed to varying concentrations of PE and PES. The VIP (Variable Importance in Projection) scores indicated PE exposure primarily impacted phospholipids, ceramides, and nucleotide-related compounds, while PES exposure led to alterations in lipid-related compounds, chitin, and amino acid derivatives. From MSEA (Metabolite Set Enrichment Analysis) and Mummichog analyses, PE and PES significantly disrupted key metabolomic pathways associated with inflammation, immune responses, and apoptosis, including leukotriene and arachidonic acid metabolism and the formation of putative anti-inflammatory metabolites from EPA. PE caused physical disruption and inflammation of the epithelial barrier, whereas PES affected gut microbiota interactions, impairing digestion and metabolism. Although alpha diversity within the gut microbiome remained stable, beta diversity analysis revealed significant shifts in microbial composition and structure, suggesting a disruption of functional balance and an increased susceptibility to pathogens. Chronic PE and PES exposures induced shifts in the gut microbial community and interaction network with potential increases in pathogenic bacteria and alteration in commensal bacteria, demonstrating the microbiome’s resilience and adaptability to stressors of MPs exposure. High-throughput metabolomics and 16S metagenomics revealed potential chronic diseases associated with inflammation, immune system disorders, metabolic dysfunction, and gut dysbiosis, highlighting the complex relationship between gut microbiome resilience and metabolic disruption under MP-induced stress, with significant ecological implications.

Dual effect of Se(IV) and bentonite microbial community interactions on the corrosion of copper and Se speciation: Implication on repository safety assessment.

The Deep Geological Repository (DGR) design, the internationally safest option for the long-term disposal of high-level radioactive waste (HLW), features metal canisters encased in compacted bentonite clay and embedded deep within a host rock. Despite presenting a hostile environment for microorganisms, DGRs scenarios with favorable microbial-activity conditions must be considered for the safety assessment of this disposal. This study investigated the impact of Se(IV), as a natural analogue of 79Se present in the HLW, in anoxic microcosms of bentonite slurry spiked with a bacterial consortium and amended with lactate, acetate, and sulfate as electron donors/acceptor. The addition of the bacterial consortium promoted the rate of Se(IV) reduction to Se(0), while the tyndallization (heat-shock) of bentonite slowed this process. Se(IV) reduced the relative abundance of most genera of sulfate-reducing bacteria (SRB), while stimulating the abundance of Se-tolerant bacteria, which played an important role in Se(IV) reduction. Moreover, it was observed that lactate was the preferred electron donor, linking to the production and subsequent consumption of acetate. X-ray absorption spectroscopy (XAS) and high-resolution transmission electron microscopy (HRTEM) revealed the reduction of Se(IV) forming amorphous Se(0) nanospheres. In addition, HRTEM showed that the biogenic Se(0) undergo a biotransformation to more stable crystalline forms, contributing to the immobilization of Se in the case of HLW release. Additionally, the sulfide generated by the activity of SRB reacted with Cu producing corrosion products (CuxS) on the surface of the copper material.

H2S regulation of a host–microbe interaction

H2S regulation of a host–microbe interaction

Comprehensive approaches to heavy metal bioremediation: Integrating microbial insights and genetic innovations.

The increasing contamination of ecosystems with heavy metals (HMs) due to industrial activities raises significant jeopardies to environmental health and human well-being. Addressing this issue, recent advances in the field of bioremediation have highlighted the potential of plant-associated microbiomes and genetically engineered organisms (GEOs) to mitigate HMs pollution. This review explores recent advancements in bioremediation strategies for HMs detoxification, with particular attention to omics technologies such as metagenomics, metabolomics, and metaproteomics in deepening the understanding of microbial interactions and their potential for neutralizing HMs. Additionally, Emerging strategies and technologies in GEOs and microorganism-aided nanotechnology have proven to be effective bioremediation tools, particularly for alleviating HM contamination. Despite the promising strategies developed in laboratory settings, several challenges impede their practical application, including ecological risks, regulatory limitations, and public concerns regarding the practice of genetically modified organisms. A comprehensive approach that involves interdisciplinary research is essential to enhance the efficacy and safety of bioremediation technologies. This approach should be coupled with robust regulatory frameworks and active public engagement to ensure environmental integrity and societal acceptance. This review underscores the importance of developing sustainable bioremediation strategies that align with ecological conservation goals and public health priorities.

Metagenomic insight into the diffusion signal factor mediated social traits of anammox consortia after starvation.

Biomass starvation is common in biological wastewater treatment. As a social trait of microbial community, how quorum sensing (QS) regulated bacterial trade-off through interactions after starvation remains unclear. This study deciphered the mechanism of anaerobic ammonium oxidation (anammox) consortia in response to starvation, including reducing extracellular electron transfer (EET), adenosine 5'-triphosphate (ATP) content and amino acid metabolism. Metagenomic analysis has shown that the addition of the diffusion signal factor (DSF) resulted in a high abundance of antioxidant genes, which contributed to achieving redox balance in anammox bacteria. There was an enrichment of Geobacter and Methanosarcina, which were QS-responsive direct interspecific electron transfer participants. Furthermore, DSF stimulated the nitrogen and carbon metabolism of Ca. Kuenenia_stuttgartiensis, promoting syntrophy of metabolic intermediates within microbial community. This study highlighted the effect of DSF on the microbial interaction patterns and deciphered the QS-based social traits of anammox consortia after starvation, facilitating the stable operation of the anammox process.

Effects of multiple temperature variations on nitrogen removal and microbial community structure in tidal flow constructed wetlands.

Tidal-flow constructed wetlands (TFCWs) provide distinct advantages for nitrogen removal by enhancing microbial activity through dynamic water level fluctuations. However, effects of temperature on nitrogen transformation processes and microbial community dynamics in TFCWs remain unclear. We analyzed the effects of TFCWs on nitrogen transformation and microbial community structure under different temperature conditions (23, 16, 12, and 8 °C) through 140 days of temperature-controlled experiments. The nitrogen removal efficiency was considerably enhanced at 23 °C, with transformation rates for ammonia nitrogen (NH4+-N) and total nitrogen (TN) reaching 9.28 ± 0.06 g/m³/day and 8.35 ± 0.08 g/m³/day, respectively. Conversely, at 8 °C, the nitrogen removal efficiency declined, with NH4+-N and TN transformation rates decreasing to 7.38 ± 0.05 g/m³/day and 6.78 ± 0.05 g/m³/day, respectively. Temperature markedly influenced the microbial diversity and community structure, as evidenced by the considerably higher Shannon diversity indices for bacterial communities at 23 °C (5.12 ± 0.21) compared with those at 8 °C (4.52 ± 0.40). Positive microbial interactions were more prevalent at lower temperatures (12 and 8 °C), leading to stronger symbiotic relationships, although the network complexity diminished. The microbial community composition of taxa such as Firmicutes, Proteobacteria, and Thaumarchaeota exhibited greater resilience at lower temperatures. Changes in dissolved oxygen levels also drove changes in bacterial and archaeal communities. These findings underscore the pivotal role of temperature in regulating ecological function and nitrogen removal efficiency of TFCWs and highlight the importance of accounting for temperature variations in the design and management of wastewater treatment systems.