Microbial Genomes Research Articles

Mechanism of improving anaerobic fermentation performance of kitchen waste pretreated by ionizing irradiation-part 1: rice.

Ionizing irradiation, as a new pretreatment method for the anaerobic fermentation of organic pollutants, is featured with fast reaction speed, good treatment effect, no need to add any chemical reagents, and no secondary pollution. This study explores the mechanism of improving anaerobic fermentation performance of rice samples pretreated by cobalt-60 gamma irradiation through the influence on fermentation substrate, acidogenic phase and methanogenic phase. The results reveal that the soluble chemical oxygen demand of the irradiated rice sample at an absorbed dose of 9.6 kGy increases by 12.4 times due to the dissolution of small molecules of fat-soluble organic matter. The yield of biogas in the acidogenic phase increases by 22.2% with a slight increase in hydrogen gas content. The yield of biogas and methane gas content in the methanogenic phase increases by 27.3% and 15%, respectively. Microbial genome analysis, performed with MiSeq high-throughput sequencing and metagenomic methods, suggests the microbial abundance and metabolic functions in the anaerobic fermentation process change significantly as a result of the pretreatment by gamma irradiation.

Mining Biosynthetic Gene Clusters of Pseudomonas vancouverensis Utilizing Whole Genome Sequencing.

Natural product (NP)-based pesticides have emerged as a compelling alternative to traditional chemical fungicides, attracting substantial attention within the agrochemical industry as the world is pushing toward sustainable and environmentally friendly approaches to safeguard crops. Microbes, both bacteria and fungi, are a huge source of diverse secondary metabolites with versatile applications across pharmaceuticals, agriculture, and the food industry. Microbial genome mining has been accelerated for pesticide/drug discovery and development in recent years, driven by advancements in genome sequencing, bioinformatics, metabolomics/metabologenomics, and synthetic biology. Here, we isolated and identified Pseudomonas vancouverensis that had shown antifungal activities against crop fungal pathogens Colletotrichum fragariae, Botrytis cinerea, and Phomopsis obscurans in a dual-plate culture and bioautography assay. Further, we sequenced the whole bacterial genome and mined the genome of this bacterium to identify secondary metabolite biosynthetic gene clusters (BGCs) using antiSMASH 7.0, PRISM 4, and BAGEL 4. An in-silico analysis suggests that P. vancouverensis possesses a rich repertoire of BGCs with the potential to produce diverse and novel NPs, including non-ribosomal peptides (NRPs), polyketides (PKs), acyl homoserine lactone, cyclodipeptide, bacteriocins, and ribosomally synthesized and post-transcriptionally modified peptides (RiPPs). Bovienimide-A, an NRP, and putidacin L1, a lectin-like bacteriocin, were among the previously known predicted metabolites produced by this bacterium, suggesting that the NPs produced by this bacterium could have biological activities and be novel as well. Future studies on the antifungal activity of these compounds will elucidate the full biotechnological potential of P. vancouverensis.

Emerging applications of artificial intelligence in pathogen genomics

The analysis of microbial genomes has long been recognised as a complex and data-rich domain where artificial intelligence (AI) can assist. As AI technologies have matured and expanded, pathogen genomics has also contended with exponentially larger datasets and an expanding role in clinical and public health practice. In this mini-review, we discuss examples of emerging applications of AI to address challenges in pathogen genomics for precision medicine and public health. These include models for genotyping whole genome sequences, identifying novel pathogens in metagenomic next generation sequencing, modelling genomic information using approaches from computational linguistics, phylodynamic estimation, and using large language models to make bioinformatics more accessible to non-experts. We also examine factors affecting the adoption of AI into routine laboratory and public health practice and the need for a renewed vision for the potential of AI to assist pathogen genomics practice.

Ancient Genomes From Bronze Age Remains Reveal Deep Diversity and Recent Adaptive Episodes for Human Oral Pathobionts.

Ancient microbial genomes can illuminate pathobiont evolution across millenia, with teeth providing a rich substrate. However, the characterization of prehistoric oral pathobiont diversity is limited. In Europe, only preagricultural genomes have been subject to phylogenetic analysis, with none compared to more recent archaeological periods. Here, we report well-preserved microbiomes from two 4,000-year-old teeth from an Irish limestone cave. These contained bacteria implicated in periodontitis, as well as Streptococcus mutans, the major cause of caries and rare in the ancient genomic record. Despite deriving from the same individual, these teeth produced divergent Tannerella forsythia genomes, indicating higher levels of strain diversity in prehistoric populations. We find evidence of microbiome dysbiosis, with a disproportionate quantity of S. mutans sequences relative to other oral streptococci. This high abundance allowed for metagenomic assembly, resulting in its first reported ancient genome. Phylogenetic analysis indicates major postmedieval population expansions for both species, highlighting the inordinate impact of recent dietary changes. In T. forsythia, this expansion is associated with the replacement of older lineages, possibly reflecting a genome-wide selective sweep. Accordingly, we see dramatic changes in T. forsythia's virulence repertoire across this period. S. mutans shows a contrasting pattern, with deeply divergent lineages persisting in modern populations. This may be due to its highly recombining nature, allowing for maintenance of diversity through selective episodes. Nonetheless, an explosion in recent coalescences and significantly shorter branch lengths separating bacteriocin-carrying strains indicate major changes in S. mutans demography and function coinciding with sugar popularization during the industrial period.

Pro-SMP finder-A systematic approach for discovering small membrane proteins in prokaryotes.

Prokaryotic chromosomes contain numerous small open reading frames (ORFs) of less than 200 bases. Since high-throughput proteomics methods often miss proteins containing fewer than 60 amino acids, it is difficult to decern if they encode proteins. Recent studies have revealed that many small proteins are membrane proteins with a single membrane-anchoring α-helix. As membrane anchoring or transmembrane motifs are accurately identifiable with high confidence using computational algorithms like Phobius and TMHMM, small membrane proteins (SMPS) can be predicted with high accuracy. This study employed a systematic approach, utilizing well-verified algorithms such as Orfipy, Phobius, and Blast to identify SMPs in prokaryotic organisms. Our main search parameters targeted candidate SMPs with an open reading frame between 60-180 nucleotides, a membrane-anchoring or transmembrane region 15 and 30 amino acids long, and sequence conservation among other microorganisms. Our findings indicate that each prokaryote possesses many SMPs, with some identified in the intergenic regions of currently annotated chromosomes. More extensively studied microorganisms, such as Escherichia coli and Bacillus subtilis, have more SMPs identified in their genomes compared to less studied microorganisms, suggesting the possibility of undiscovered SMPs in less studied microorganisms. In this study, we describe the common SMPs identified across various microorganisms and explore their biological roles. We have also developed a software pipeline and an accompanying online interface for discovering SMPs (http://cs.indstate.edu/pro-smp-finder). This resource aims to assist researchers in identifying new SMPs encoded in microbial genomes of interest.

Deficient butyrate metabolism in the intestinal microbiome is a potential risk factor for recurrent kidney stone disease.

Intestinal microbiome dysbiosis is a known risk factor for recurrent kidney stone disease (KSD) with prior data suggesting a role for dysfunctional metabolic pathways other than those directly utilizing oxalate. To identify alternative mechanisms, the current study analyzed differences in the metabolic potential of intestinal microbiomes of patients (n = 17) and live-in controls (n = 17) and determined their relevance to increased risk for KSD using shotgun metagenomic sequencing. We found no differences in the abundance of genes associated with known oxalate degradation pathways, supporting the notion that dysfunction in other metabolic pathways plays a role in KSD. Further analysis showed decreased abundance of key enzymes involved in butyrate biosynthesis in patient intestinal microbiomes. Furthermore, de novo construction of microbial genomes showed that the majority of genes significantly enriched in non-stone formers are affiliated with Faecalibacterium prausnitzii, a major butyrate producer. Specifically pertaining to butyrate metabolism, the majority of abundant genes mapped back to F. prausnitzii, Alistipes spp., and Akkermansia muciniphila. No differences were observed in ascorbate or glyoxylate metabolic pathways. Collectively, these data suggest that impaired bacterial-associated butyrate metabolismmay be an oxalate-independent mechanism that contributes to an increased risk for recurrent KSD. This indicates that the role of the intestinal microbiome in recurrent KSD is multi-factorial, which is representative of the highly intertwined metabolic nature of this complex environment.Future bacteria-based treatments must not be restricted to targeting only oxalate metabolism.

Antimicrobial Peptide Screening from Microbial Genomes in Sludge Based on Deep Learning

As the issue of traditional antibiotic resistance continues to worsen, exploring new antimicrobial substances has become crucial to addressing this challenge. Antimicrobial peptides (AMPs), recognized for their low resistance levels and minimal bacterial mutation frequencies, have garnered significant attention from researchers. However, traditional screening methods for AMPs are inefficient and costly. This study proposes a combined AMP screening model based on long short-term memory (LSTM) neural networks with an attention mechanism. By analyzing the characteristics of peptide segments, which are simulated enzymatic hydrolysis products of proteins expressed in sludge microbial genomes, the model accurately identifies peptide segments with potential antimicrobial activity. Molecular docking and dynamic simulation results validate three potential antimicrobial peptide candidates: LLPRLLARRY, GVREIHGLNPGGCLHTVRLVCR, and FRTTLAPHVLTRLLAPCW. These candidates exhibit high binding stability and affinity with target proteins, confirming the efficiency of the proposed AMP screening model.

An Overview of Bioinformatics and its Application: A Ray of Hope towards Microbial Biotechnology

A new era in the analysis of biological data has been sparked by the revolutionary development in processing speed and memory capacity. With the sequencing of hundreds of microbial and numerous eukaryotic genomes—including a clearer draft of the human genome—better control over microbes is anticipated. The objectives are very high and include the creation of sensible medications and antimicrobial agents, the creation of novel, improved bacterial strains for bioremediation and pollution control, the creation of more effective vaccines that are simple to administer, the creation of protein biomarkers for a variety of bacterial diseases, and a deeper comprehension of the interactions between hosts and bacteria to prevent bacterial infections. Bioinformatics research currently being conducted on the basis of Genomics, Proteomics, cell visualization and application to the development of drugs and antimicrobial agents. The main contributions of bioinformatics research include automated genome sequencing, automated development of integrated genomics and proteomics databases, automated genome comparisons to determine the function of the genome, automated metabolic pathway derivation, automated gene expression analysis to determine regulatory pathways, automated statistical technique development, data mining and clustering techniques to determine protein-protein and protein-DNA interactions, modeling of 3D protein structure and 3D docking between proteins and biochemicals for rational drug design, and analysis of differences between pathogenic and non-pathogenic strains to identify candidate genes for vaccines and anti-microbial agents.

Increasing transposase abundance with ocean depth correlates with a particle-associated lifestyle.

Transposases are mobile genetic elements that move within and between genomes, promoting genomic plasticity in microorganisms. In marine microbial communities, the abundance of transposases increases with depth, but the reasons behind this trend remain unclear. Our analysis of metagenomes from the Tara Oceans and Malaspina Expeditions suggests that a particle-associated lifestyle is the main covariate for the high occurrence of transposases in the deep ocean, and this trend holds true for individual genomes as well as in a community-wide sense. We observed a strong and depth-independent correlation between transposase abundance and the presence of biofilm-associated genes, as well as the prevalence of secretory enzymes. This suggests that mobile genetic elements readily propagate among microbial communities within crowded biofilms. Furthermore, we show that particle association positively correlates with larger genome size, which is in turn associated with higher transposase abundance. Cassette sequences associated with transposons are enriched with genes related to defense mechanisms, which are more highly expressed in the deep sea. Thus, while transposons spread at the expense of their microbial hosts, they also introduce novel genes and potentially benefit the hosts in helping to compete for limited resources. Overall, our results suggest a new understanding of deep ocean particles as highways for gene sharing among defensively oriented microbial genomes.IMPORTANCEGenes can move within and between microbial genomes via mobile genetic elements, which include transposases and transposons. In the oceans, there is a puzzling increase in transposase abundance in microbial genomes as depth increases. To gain insight into this trend, we conducted an extensive analysis of marine microbial metagenomes and metatranscriptomes. We found a significant correlation between transposase abundance and a particle-associated lifestyle among marine microbes at both the metagenome and genome-resolved levels. We also observed a link between transposase abundance and genes related to defense mechanisms. These results suggest that as microbes become densely packed into crowded particles, mobile genes are more likely to spread and carry genetic material that provides a competitive advantage in crowded habitats. This may enable deep sea microbes to effectively compete in such environments.

Codon-tRNA Coadaptation Bias for Identifying Strong Native Promoters in Komagataella phaffii.

Promoters are crucial elements for engineering microbial production strains used in bioprocesses. For the increasingly popular chassis Komagataella phaffii (formerly Pichia pastoris), a limited number of well-characterized promoters constrain the data-driven engineering of production strains. Here, we present an in silico approach for condition-independent de novo identification of strong native promoters. The method relies on tRNA-codon coadaptation of coding sequences in the K. phaffii genome and is based on two complementary scores: the number of effective codons and the tRNA adaptation index. Genes with high codon bias are expected to be translated efficiently and, thus, also be under control of strong promoters. Using this approach, we identified promising strong promoter candidates and experimentally assessed their activity using fluorescent reporter assays characterizing 50 promoters spanning a 76-fold difference in expression levels in a glucose medium. Overall, we report several promoters that should be added to the molecular toolbox for engineering of K. phaffii and present an approach for identifying promoters in microbial genomes.

Microbial composition and function in reclaimed mine sites along a reclamation chronosequence become increasingly similar to undisturbed reference sites

Mine reclamation historically focuses on enhancing plant coverage to improve below and aboveground ecology. However, there is a great need to study the role of soil microorganisms in mine reclamation, particularly long-term studies that track the succession of microbial communities. Here, we investigate the trajectory of microbial communities of mining sites reclaimed between three and 26 years. We used high-throughput amplicon sequencing to characterize the bacterial and fungal communities. We quantified how similar the reclaimed sites were to unmined, undisturbed reference sites and explored the trajectory of microbial communities along the reclamation chronosequence. We also examined the ecological processes that shape the assembly of bacterial communities. Finally, we investigated the functional potential of the microbial communities through metagenomic sequencing. Our results reveal that the reclamation age significantly impacted the community compositions of bacterial and fungal communities. As the reclamation age increases, bacterial and fungal communities become similar to the unmined, undisturbed reference site, suggesting a favorable succession in microbial communities. The bacterial community assembly was also significantly impacted by reclamation age and was primarily driven by stochastic processes, indicating a lesser influence of environmental properties on the bacterial community. Furthermore, our read-based metagenomic analysis showed that the microbial communities' functional potential increasingly became similar to the reference sites. Additionally, we found that the plant richness increased with the reclamation age. Overall, our study shows that both above- and belowground ecological properties of reclaimed mine sites trend towards undisturbed sites with increasing reclamation age. Further, it demonstrates the importance of microbial genomics in tracking the trajectory of ecosystem reclamation.

Annotating microbial functions with ProkFunFind.

Analyzing microbial genomes has become an essential part of microbiology research, giving valuable insights into the functions and evolution of microbial species. Identifying genes of interest and assigning putative annotations to those genes is a central task in genome analysis, and a plethora of tools and approaches have been developed for this task. The ProkFunFind tool was developed to bridge the gap between these various annotation approaches, providing a flexible and customizable search approach to annotate microbial functions. ProkFunFind is designed around hierarchical definitions of biological functions, where individual genes can be identified using heterogeneous search terms consisting of sequences, profile hidden Markov models, protein domains, and orthology groups. This flexible and customizable search approach allows for searches to be tailored to specific biological functions, and the search results are output in multiple formats to facilitate downstream analyses. The utility of the ProkFunFind search tool was demonstrated through its application in searching for bacterial flagella, which are complex organelles composed of multiple genes. Overall, ProkFunFind provides an accessible and flexible way to integrate multiple types of annotation and sequence data while annotating biological functions in microbial genomes.IMPORTANCEGenome sequencing and analysis are increasingly important parts of microbiology, providing a way to predict metabolic functions, identify virulence factors, and understand the evolution of microbes. The expanded use of genome sequencing has also brought an abundance of search and annotation methods, but integrating the information from these different methods can be challenging and is often done through ad hoc approaches. To bridge the gap between different types of annotations, we developed ProkFunFind, a flexible and customizable search tool incorporating multiple search approaches and annotation types to annotate microbial functions. We demonstrated the utility of ProkFunFind by searching for gene clusters encoding flagellar genes using a combination of different annotation types and searches. Overall, ProkFunFind provides a reproducible and flexible way to identify gene clusters of interest, facilitating the meaningful analysis of new and existing microbial genomes.

Longitudinal gut microbiome changes in immune checkpoint blockade-treated advanced melanoma

Multiple clinical trials targeting the gut microbiome are being conducted to optimize treatment outcomes for immune checkpoint blockade (ICB). To improve the success of these interventions, understanding gut microbiome changes during ICB is urgently needed. Here through longitudinal microbiome profiling of 175 patients treated with ICB for advanced melanoma, we show that several microbial species-level genome bins (SGBs) and pathways exhibit distinct patterns from baseline in patients achieving progression-free survival (PFS) of 12 months or longer (PFS ≥12) versus patients with PFS shorter than 12 months (PFS <12). Out of 99 SGBs that could discriminate between these two groups, 20 were differentially abundant only at baseline, while 42 were differentially abundant only after treatment initiation. We identify five and four SGBs that had consistently higher abundances in patients with PFS ≥12 and <12 months, respectively. Constructing a log ratio of these SGBs, we find an association with overall survival. Finally, we find different microbial dynamics in different clinical contexts including the type of ICB regimen, development of immune-related adverse events and concomitant medication use. Insights into the longitudinal dynamics of the gut microbiome in association with host factors and treatment regimens will be critical for guiding rational microbiome-targeted therapies aimed at enhancing ICB efficacy.

Draft genome sequence of Exiguobacterium sp. strain MMG028 isolated from a salt marsh.

Here, we report the draft genome sequence of Exiguobacterium sp. strain MMG028, isolated from Rose Creek, San Diego, CA, USA, assembled and analyzed by undergraduate students participating in a marine microbial genomics course. A genomic comparison suggests that MMG028 is a novel species, providing a resource for future microbiology and biotechnology investigations.

Bacterial cytochrome P450s: a bioinformatics odyssey of substrate discovery.

Bacterial P450 cytochromes (BacCYPs) are versatile heme-containing proteins responsible for oxidation reactions on a wide range of substrates, contributing to the production of valuable natural products with limitless biotechnological potential. While the sequencing of microbial genomes has provided a wealth of BacCYP sequences, functional characterization lags behind, hindering our understanding of their roles. This study employs a comprehensive approach to predict BacCYP substrate specificity, bridging the gap between sequence and function. We employed an integrated approach combining sequence and functional data analysis, genomic context exploration, 3D structural modeling with molecular docking, and phylogenetic clustering. The research begins with an in-depth analysis of BacCYP sequence diversity and structural characteristics, revealing conserved motifs and recurrent residues in the active site. Phylogenetic analysis identifies distinct groups within the BacCYP family based on sequence similarity. However, our study reveals that sequence alone does not consistently predict substrate specificity, necessitating additional perspectives. The study delves into the genetic context of BacCYPs, utilizing neighboring gene information to infer potential substrates, a method proven very effective in many cases. Molecular docking is employed to assess BacCYP-substrate interactions, confirming potential substrates and providing insights into selectivity. Finally, a comprehensive strategy is proposed for predicting BacCYP substrates, involving all the evaluated approaches. The effectiveness of this strategy is demonstrated with two case studies, highlighting its potential for substrate discovery.

Recent advances in degradation of N,N-diethyl-3-toluamide (DEET)-an emerging environmental contaminant: a review.

N,N-Diethyl-3-toluamide (DEET) is a commonly used insect repellent, which acts as an organic chemical contaminant in water and considered as an emerging contaminant which has been observed worldwide. It gets discharged into the environment through sewage waste. The various methods have been used to degrade DEET, such as UV based, ozonation, photocatalytic degradation, and biodegradation (based on the metabolic activity of fungi and bacteria). However, less research has been done on the degradation of DEET by deploying nanoparticles. Therefore, biodegradation and nanotechnology-based methods can be the potential solution to remediate DEET from the environment. This review is an attempt to analyze the routes of entry of DEET into the atmosphere and its environmental health consequences and to explore physical, chemical, and biological methods of degradation. Furthermore, it focuses on the various methods used for the biodegradation of the DEET, including their environmental consequences. Future research is needed with the application of biological methods for the degradation of DEET. Metabolic pathway for biodegradation was explored for the new potent microbial strains by the application of physical, chemical, and microbial genomics; molecular biology; genetic engineering; and genome sequencing methods.

Predictions of rhizosphere microbiome dynamics with a genome-informed and trait-based energy budget model

Soil microbiomes are highly diverse, and to improve their representation in biogeochemical models, microbial genome data can be leveraged to infer key functional traits. By integrating genome-inferred traits into a theory-based hierarchical framework, emergent behaviour arising from interactions of individual traits can be predicted. Here we combine theory-driven predictions of substrate uptake kinetics with a genome-informed trait-based dynamic energy budget model to predict emergent life-history traits and trade-offs in soil bacteria. When applied to a plant microbiome system, the model accurately predicted distinct substrate-acquisition strategies that aligned with observations, uncovering resource-dependent trade-offs between microbial growth rate and efficiency. For instance, inherently slower-growing microorganisms, favoured by organic acid exudation at later plant growth stages, exhibited enhanced carbon use efficiency (yield) without sacrificing growth rate (power). This insight has implications for retaining plant root-derived carbon in soils and highlights the power of data-driven, trait-based approaches for improving microbial representation in biogeochemical models.

A designer synthetic chromosome fragment functions in moss.

Rapid advances in DNA synthesis techniques have enabled the assembly and engineering of viral and microbial genomes, presenting new opportunities for synthetic genomics in multicellular eukaryotic organisms. These organisms, characterized by larger genomes, abundant transposons and extensive epigenetic regulation, pose unique challenges. Here we report the in vivo assembly of chromosomal fragments in the moss Physcomitrium patens, producing phenotypically virtually wild-type lines in which one-third of the coding region of a chromosomal arm is replaced by redesigned, chemically synthesized fragments. By eliminating 55.8% of a 155 kb endogenous chromosomal region, we substantially simplified the genome without discernible phenotypic effects, implying that many transposable elements may minimally impact growth. We also introduced other sequence modifications, such as PCRTag incorporation, gene locus swapping and stop codon substitution. Despite these substantial changes, the complex epigenetic landscape was normally established, albeit with some three-dimensional conformation alterations. The synthesis of a partial multicellular eukaryotic chromosome arm lays the foundation for the synthetic moss genome project (SynMoss) and paves the way for genome synthesis in multicellular organisms.

New Genomic Techniques applied to food cultures: a powerful contribution to innovative, safe, and sustainable food products.

Nontransgenic New Genomic Techniques (NGTs) have emerged as a promising tool for food industries, allowing food cultures to contribute to an innovative, safe, and more sustainable food system. NGTs have the potential to be applied to microorganisms, delivering on challenging performance traits like texture, flavour, and an increase of nutritional value. This paper brings insights on how nontransgenic NGTs applied to food cultures could be beneficial to the sector, enabling food industries to generate innovative, safe, and sustainable products for European consumers. Microorganisms derived from NGTs have the potentials of becoming an important contribution to achieve the ambitious targets set by the European 'Green Deal' and 'Farm to Fork' policies. To encourage the development of NGT-derived microorganisms, the current EU regulatory framework should be adapted. These technologies allow the introduction of a precise, minimal DNA modification in microbial genomes resulting in optimized products carrying features that could also be achieved by spontaneous natural genetic evolution. The possibility to use NGTs as a tool to improve food safety, sustainability, and quality is the bottleneck in food culture developments, as it currently relies on lengthy natural evolution strategies or on untargeted random mutagenesis.

Unveiling the hidden diversity and functional role of Chloroflexota in full-scale wastewater treatment plants through genome-centric analyses

Abstract The phylum Chloroflexota has been found to exhibit high abundance in the microbial communities from wastewater treatment plants (WWTPs) in both aerobic and anaerobic systems. However, its metabolic role has not been fully explored due to the lack of cultured isolates. To address this gap, we use publicly available metagenome datasets from both activated sludge (AS) and methanogenic (MET) full-scale wastewater treatment reactors to assembled genomes. Using this strategy, 264 dereplicated, medium- and high-quality metagenome-assembled genomes (MAGs) classified within Chloroflexota were obtained. Taxonomic classification revealed that AS and MET reactors harbored distinct Chloroflexota families. Nonetheless, the majority of the annotated MAGs (166 MAGs with &amp;gt;85% completeness and &amp;lt; 5% contamination) shared most of the metabolic potential features, including the ability to degrade simple sugars and complex polysaccharides, fatty acids and amino acids, as well as perform fermentation of different products. While Chloroflexota MAGs from MET reactors showed the potential for strict fermentation, MAGs from AS harbored the potential for facultatively aerobic metabolism. Metabolic reconstruction of Chloroflexota members from AS unveiled their versatile metabolism and suggested a primary role in hydrolysis, carbon removal and involvement in nitrogen cycling, thus establishing them as fundamental components of the ecosystem. Microbial reference genomes are essential resources for understanding the potential functional role of uncultured organisms in WWTPs. Our study provides a comprehensive genome catalog of Chloroflexota for future analyses aimed at elucidating their role in these ecosystems.