Search Results (46)

The gut microbiome has emerged as one of the most promising sources of non-invasive biomarkers for colorectal cancer (CRC). Over the past decade, fecal metagenomic studies have consistently identified a core CRC-associated signature enriched with oral-typical, biofilm-forming species, most notably Fusobacterium nucleatum, Parvimonas micra, Peptostreptococcus stomatis, and Bacteroides fragilis. The recent landmark pooled analysis by Piccinno et al., which combined 3741 metagenomes from 18 international cohorts, offers the most methodologically solid confirmation of this signature to date. It achieved a leave-one-dataset-out area under the curve (AUC) of around 0.85 and expanded resolution to previously unclassified species-level genome bins (SGBs) and strain-level phylogenies. In this narrative review, we critically evaluate the evidence supporting current universal CRC microbiome signatures, explore the mechanistic basis of the oral-to-gut microbial axis and the immunometabolic tumor microenvironment, and argue that increasing evidence indicates the field is nearing a point where investigating patient-level heterogeneity could be the most valuable next step. Because a strong average CRC signal has been convincingly established, an important next direction is to examine how much these signatures’ impact varies among individual patients, considering tumor molecular subtype, immune environment, metabolic profile, and host genetics. We review emerging evidence of such patient-level heterogeneity, outline analytical methods to assess it, and discuss its importance for developing microbiome-based screening, prognostics, and therapeutic strategies in CRC. Full article

Artificial freshwater bodies receive elemental inputs and face environmental stressors, posing a risk of wetland pollution that could threaten ecological health. In such an inland backwater, its microbial diversity and functional potentials remain uncharacterized. Here, shotgun metagenomic sequencing was performed on environmental DNA samples collected from the Atoud Dam reservoir in southwestern Saudi Arabia. The taxonomic assignments of the sequencing reads identified Pseudomonadota and Actinomycetota as the dominant phyla, while the most prevalent species was Microcystis aeruginosa. Binning assembled contigs recovered 30 metagenome-assembled genomes representing 11 phyla, suggesting potentially novel bacterial taxa and metabolic functions. Functional analysis of gene-coding sequences identified genes associated with mobile genetic elements and xenobiotic biodegradation pathways as the main factors driving the spread of antibiotic resistance genes. Additionally, a community-wide analysis of enzyme-encoding genes involved in regulating the carbon, nitrogen, and sulfur cycles revealed significant annotation of denitrification and thiosulfate oxidation pathways under anoxic conditions, suggesting early signs of eutrophication and a potential risk of algal blooms. Overall, our study provides detailed insights into the genomic capabilities of the microbial community in this previously understudied ecosystem and establishes baseline data for future assessments of microbial biodiversity in other, less-explored ecosystems, thereby facilitating more effective biomonitoring and discovery. Full article

Microbial communities at Site F cold seep, ubiquitous in both the environment and the associated fauna, demonstrate clear habitat-specific partitioning. Metagenomic sequencing and binning demonstrated a striking partitioning of microbial taxa at the cold seep: whereas the sponge-associated microbiome was distinctly enriched with specialized sulfur- and methane-oxidizing bacteria that were rare in the environment, it simultaneously exhibited a significantly reduced archaeal content, lower α-diversity, and a simpler overall community structure compared to the sediment and seawater communities. Distinct evolutionary lineages and varying abundances were observed among the microbiomes from seawater, sediment, and sponges. Furthermore, their Metagenome-Assembled Genomes (MAGs) exhibited significant differences in genomic features, including genome size and GC content. The sponge-associated microbiome exhibits lower diversity but maintains a high abundance of key functional genes, particularly those involved in sulfur cycling (e.g., apr, dsr, metZ), indicating enhanced metabolic efficiency in energy conservation and nutrient acquisition. This study reveals that the seawater, sediment, and sponge-associated microbiomes exhibit genome simplification and functional specialization in the cold seep environment, with varying lifestyles driving structural optimization and functional remodeling of the symbiotic microbiomes. Full article

Accurate genome binning is essential for resolving microbial community structure and functional potential from metagenomic data. However, existing approaches—primarily reliant on tetranucleotide frequency (TNF) and abundance profiles—often perform sub-optimally in the face of complex community compositions, low-abundance taxa, and long-read sequencing datasets. To address these limitations, we present MBGCCA, a novel metagenomic binning framework that synergistically integrates graph neural networks (GNNs), contrastive learning, and information-theoretic regularization to enhance binning accuracy, robustness, and biological coherence. MBGCCA operates in two stages: (1) multimodal information integration, where TNF and abundance profiles are fused via a deep neural network trained using a multi-view contrastive loss, and (2) self-supervised graph representation learning, which leverages assembly graph topology to refine contig embeddings. The contrastive learning objective follows the InfoMax principle by maximizing mutual information across augmented views and modalities, encouraging the model to extract globally consistent and high-information representations. By aligning perturbed graph views while preserving topological structure, MBGCCA effectively captures both global genomic characteristics and local contig relationships. Comprehensive evaluations using both synthetic and real-world datasets—including wastewater and soil microbiomes—demonstrate that MBGCCA consistently outperforms state-of-the-art binning methods, particularly in challenging scenarios marked by sparse data and high community complexity. These results highlight the value of entropy-aware, topology-preserving learning for advancing metagenomic genome reconstruction. Full article

Peach fruit flesh spongy tissue disorder causes dry, porous, and brown areas in the flesh, severely compromising fruit quality and market value. While soil properties and calcium nutrition have been linked to the disorder, the role of rhizosphere microbial communities in disorder resistance remains unclear. This study investigated both the physicochemical properties and the root-associated microbiomes of disordered (CK) and healthy (TT) peach orchards to explore microbial mechanisms underlying disorder suppression. TT soils exhibited higher pH, greater organic matter, increased exchangeable calcium, and more balanced trace elements compared to CK. Microbial analysis revealed significantly higher diversity and enrichment of beneficial taxa in TT associated with plant growth and disorder resistance. Functional gene prediction showed TT was enriched in siderophore production, auxin biosynthesis, phosphate solubilization, and acetoin–butanediol synthesis pathways. Co-occurrence network analysis demonstrated that TT harbored a more complex and cooperative microbial community structure, with 274 nodes and 6013 links. Metagenomic binning recovered high-quality MAGs encoding diverse resistance and growth-promoting traits, emphasizing the ecological roles of Gemmatimonadaceae, Reyranella, Nitrospira, Bacillus megaterium, and Bryobacteraceae. These findings highlight the combined importance of soil chemistry and microbiome structure in disorder suppression and provide a foundation for microbiome-informed soil management to enhance fruit quality and promote sustainable orchard practices. Full article

Metagenome-assembled genomes (MAGs) have revolutionized microbial ecology by enabling the genome-resolved study of uncultured microorganisms directly from environmental samples. By leveraging high-throughput sequencing, advanced assembly algorithms, and genome binning techniques, researchers can reconstruct microbial genomes without the need for cultivation. These methodological advances have expanded the known microbial diversity, revealing novel taxa and metabolic pathways involved in key biogeochemical cycles, including carbon, nitrogen, and sulfur transformations. MAG-based studies have identified microbial lineages form Archaea and Bacteria responsible for methane oxidation, carbon sequestration in marine sediments, ammonia oxidation, and sulfur metabolism, highlighting their critical roles in ecosystem stability. From a sustainability perspective, MAGs provide essential insights for climate change mitigation, sustainable agriculture, and bioremediation. The ability to characterize microbial communities in diverse environments, including soil, aquatic ecosystems, and extreme habitats, enhances biodiversity conservation and supports the development of microbial-based environmental management strategies. Despite these advancements, challenges such as assembly biases, incomplete metabolic reconstructions, and taxonomic uncertainties persist. Continued improvements in sequencing technologies, hybrid assembly approaches, and multi-omics integration will further refine MAG-based analyses. As methodologies advance, MAGs will remain a cornerstone for understanding microbial contributions to global biogeochemical processes and developing sustainable interventions for environmental resilience. Full article

The microbial community in vinegar has primarily been investigated by analyzing short reads to determine operational taxonomic units, but it is also crucial to identify metagenome-assembled genomes (MAGs). In this study, the microbial diversity and functionality in Sichuan Baoning vinegar were examined through deep metagenomic sequencing and metagenomic binning. Results revealed that the most prevalent phylum was Firmicutes, followed by Proteobacteria and unclassified Bacteria. The most abundant bacterial species was Acetilactobacillus jinshanensis, while Saccharomyces cerevisiae was the most prevalent fungal species. The predominant viral species were Hopescreekvirus LfeInf, Myoviridae sp., and Siphoviridae sp. A total of 1395 MAGs were reconstructed, with 660 of them annotated. The majority of MAGs resolved at the species level were attributed to Firmicutes (n = 308), with Acetilactobacillus jinshanensis being the most abundant. According to the average nucleotide identity values, 223 out of the 660 MAGs might represent novel species. The recovered MAGs exhibited biomarker genes indicative of the genetic potential to encode several important secondary metabolites. This study helps to uncover the microbial composition and functional potential of microbial genomes in Sichuan Baoning vinegar. Full article

Background: Soil microbes play a vital role in the ecosystem as they are able to carry out a number of vital tasks. Additionally, metagenomic studies offer valuable insights into the composition and functional potential of soil microbial communities. Furthermore, analyzing the obtained data can improve agricultural restoration practices and aid in developing more effective environmental management strategies. Methodology: In November 2023, sandy soil samples were collected from ten sites of different geographical areas surrounding natural lakes and artificial water points in the Tubaiq conservation area of King Salman Bin Abdulaziz Royal Natural Reserve (KSRNR), Saudi Arabia. In addition, genomic DNA was extracted from the collected soil samples, and 16S rRNA sequencing was conducted using high-throughput Illumina technology. Several computational analysis tools were used for gene prediction and taxonomic classification of the microbial groups. Results: In this study, sandy soil samples from the surroundings of natural and artificial water resources of two distinct natures were used. Based on 16S rRNA sequencing, a total of 24,563 OTUs were detected. The metagenomic information was then categorized into 446 orders, 1036 families, 4102 genera, 213 classes, and 181 phyla. Moreover, the phylum Pseudomonadota was the most dominant microbial community across all samples, representing an average relative abundance of 34%. In addition, Actinomycetes was the most abundant class (26%). The analysis of clustered proteins assigned to COG categories provides a detailed understanding of the functional capabilities and adaptation of microbial communities in soil samples. Amino acid metabolism and transport were the most abundant categories in the soil environment. Conclusions: Metagenome analysis of sandy soils surrounding natural lakes and artificial water points in the Tubaiq conservation area of KSRNR (Saudi Arabia) has unveils rich microbial activity, highlighting the complex interactions and ecological roles of microbial communities in these environments. Full article

The conventional methods used to produce N-acetyl-β-D-glucosamine (GlcNAc) from seafood waste require pretreatment steps that use acids or bases to achieve the extraction and decrystallization of chitin prior to enzymatic conversion. The development of an enzymatic conversion method that does not require the pretreatment of seafood waste is essential for the efficient and clean production of GlcNAc. In this study, the annotated metagenomic assembly data of domesticated microbiota (XHQ10) were analyzed to identify carbohydrate-active enzymes (CAZymes), and an in-depth analysis of the high-quality genome FS13.1, which was obtained from metagenomic binning, was performed; this enabled us to elucidate the catabolic mechanism of XHQ10 by using shrimp shell chitin as a carbon and nitrogen source. The only β-N-acetylglucosaminidase (named XmGlcNAcase) was cloned from FS13.1 and biochemically characterized. The direct production of GlcNAc from shrimp shell powder (SSP) via the use of a chitin enzyme cocktail was evaluated. Under the action of a chitin enzyme cocktail containing 5% recombinant XmGlcNAcase and a crude XHQ10 enzyme solution, the yield and purity of the final conversion of SSP to GlcNAc were 2.57 g/L and 82%, respectively. This is the first time that metagene-derived GlcNAcase has been utilized to achieve the enzymatic conversion of untreated seafood waste, laying the foundation for the low-cost and sustainable production of GlcNAc. Full article

The Tabuk region is located in the northern part of Saudi Arabia, and it has an area of 117,000 km² between longitudes 26° N and 29° N and latitudes 34° E and 38° E. King Salman Bin Abdulaziz Royal Natural Reserve (KSRNR) is the largest natural reserve in Saudi Arabia and covers about 130,700 km². It represents a new tourist attraction area in the Tabuk region. Human activities around the lake may lead to changes in water quality, with subsequent changes in microenvironment components, including microbial diversity. The current study was designed to assess possible changes in bacterial communities of the water sediment at some natural lakes and artificial waterpoints of KSRNR. Water samples were collected from ten different locations within KSRNR: W1, W2, W3 (at the border of the royal reserve); W4, W5, W6, W7 (at the middle); and W8, W9, and W10 (artificial waterpoints). The total DNA of the samples was extracted and subjected to 16S rRNA sequencing and metagenomic analysis; also, the environmental parameters (temperature and humidity) were recorded for all locations. Metagenomic sequencing yielded a total of 24,696 operational taxonomic units (OTUs), which were subsequently annotated to 193 phyla, 215 classes, 445 orders, 947 families, and 3960 genera. At the phylum level, Pseudomonadota dominated the microbial communities across all samples. At the class level, Gammaproteobacteria, Clostridia, Alphaproteobacteria, Bacilli, and Betaproteobacteria were the most prevalent. The dominant families included Enterobacteriaceae, Pseudomonadaceae, Clostridiaceae, Comamonadaceae, and Moraxellaceae. At the genus level, Pseudomonas, Clostridium, Acinetobacter, Paenibacillus, and Acidovorax exhibited the highest relative abundances. The most abundant species were Hungatella xylanolytica, Pseudescherichia vulneris, Pseudorhizobium tarimense, Paenibacillus sp. Yn15, and Enterobacter sp. Sa187. The observed species richness revealed substantial heterogeneity across samples using species richness estimators, Chao1 and ACE, indicating particularly high diversity in samples W3, W5, and W6. Current study results help in recognizing the structure of bacterial communities at the Tubaiq area in relation to their surroundings for planning for environmental protection and future restoration of affected ecosystems. The findings highlight the dominance of various bacterial phyla, classes, families, and genera, with remarkable species richness in some areas. These results underscore the influence of human activities on microbial diversity, as well as the significance of monitoring and conserving the reserve’s natural ecosystems. Full article

Animals form functional units with their microbial communities, termed metaorganisms. Despite extensive research on some model animals, microbial diversity in many species remains unexplored. Here, we describe the taxonomic profile of the microbes from the outer gut mucus layer from the Northeast Arctic cod using a shotgun DNA sequencing approach. We focused on the mucus to determine if its microbial composition differs from that of the fecal microbiota, which could reveal unique microbial interactions and functions. Metagenomes from six individuals were analyzed, revealing three different taxonomic profiles: Type I is dominated in numbers by Pseudomonadaceae (44%) and Xanthomonadaceae (13%), Type II by Vibrionaceae (65%), and Type III by Enterobacteriaceae (76%). This stands in sharp contrast to the bacterial diversity of the transient gut content (i.e., feces). Additionally, binning of assembled reads followed by phylogenomic analyses place a high-completeness bin of Type I within the Pseudomonas fluorescens group, Type II within the Photobacterium phosphoreum clade, and Type III within the Escherichia/Shigella group. In conclusion, we describe the adherent bacterial diversity in the Northeast Arctic cod’s intestine using shotgun sequencing, revealing different taxonomic profiles compared to the more homogenous transient microbiota. This suggests that the intestine contains two separate and distinct microbial populations. Full article

Metagenomic binning is a crucial step in metagenomic research. It can aggregate the genome sequences belonging to the same microbial species into independent bins. Most existing methods ignore the semantic information of contigs and lack effective processing of tetranucleotide frequency, resulting in insufficient and complex feature information extracted for binning and poor binning results. To address the above problems, we propose CedtBin, a metagenomic binning method based on contig embedding and decomposed tetranucleotide frequency. First, the improved BERT model is used to learn the contigs to obtain their embedding representation. Secondly, the tetranucleotide frequencies are decomposed using a non-negative matrix factorization (NMF) algorithm. After that, the two features are spliced and input into the clustering algorithm for binning. Considering the sensitivity of the DBSCAN clustering algorithm to input parameters, in order to solve the drawbacks of manual parameter input, we also propose an Annoy-DBSCAN algorithm that can adaptively determine the parameters of the DBSCAN algorithm. This algorithm uses Approximate Nearest Neighbors Oh Yeah (Annoy) and combines it with a grid search strategy to find the optimal parameters of the DBSCAN algorithm. On simulated and real datasets, CedtBin achieves better binning results than mainstream methods and can reconstruct more genomes, indicating that the proposed method is effective. Full article

The family Beggiatoaceae is currently represented by 25 genera in the Genome Taxonomy Database, of which only 6 have a definite taxonomic status. Two metagenome-assembled genomes (MAGs), WS_Bin1 and WS_Bin3, were assembled from metagenomes of the sulfur mats coating laminaria remnants in the White Sea. Using the obtained MAGs, we first applied phylogenetic analysis based on whole-genome sequences to address the systematics of Beggiatoaceae, which clarify the taxonomy of this family. According to the average nucleotide identity (ANI) and average amino acid identity (AAI) values, MAG WS_Bin3 was assigned to a new genus and a new species in the family Beggiatoaceae, namely, ‘Candidatus Albibeggiatoa psychrophila’ gen. nov., sp. nov., thus providing the revised taxonomic status of the candidate genus ‘BB20’. Analysis of 16S rRNA gene homology allowed us to identify MAG WS_Bin1 as the only currently described species of the genus ‘Candidatus Parabeggiatoa’, namely, ‘Candidatus Parabeggiatoa communis’, and consequently assign the candidate genus ‘UBA10656’, including four new species, to the genus ‘Ca. Parabeggiatoa’. Using comparative whole-genome analysis of the members of the genera ‘Candidatus Albibeggiatoa’ and ‘Ca. Parabeggiatoa’, we expanded information on the central pathways of carbon, sulfur and nitrogen metabolism in the family Beggiatoaceae. Full article

Staka is a traditional Greek sour cream made mostly from spontaneously fermented sheep milk or a mixture of sheep and goat milk. At the industrial scale, cream separators and starter cultures may also be used. Staka is sometimes cooked with flour to absorb most of the fat. In this study, we employed culture-based techniques, amplicon sequencing, and shotgun metagenomics to analyze the Staka microbiome for the first time. The samples were dominated by Lactococcus or Leuconostoc spp. Most other bacteria were lactic acid bacteria (LAB) from the Streptococcus and Enterococcus genera or Gram-negative bacteria from the Buttiauxella, Pseudomonas, Enterobacter, Escherichia-Shigella, and Hafnia genera. Debaryomyces, Kluyveromyces, or Alternaria were the most prevalent genera in the samples, followed by other yeasts and molds like Saccharomyces, Penicillium, Aspergillus, Stemphylium, Coniospotium, or Cladosporium spp. Shotgun metagenomics allowed the species-level identification of Lactococcus lactis, Lactococcus raffinolactis, Streptococcus thermophilus, Streptococcus gallolyticus, Escherichia coli, Hafnia alvei, Streptococcus parauberis, and Enterococcus durans. Binning of assembled shotgun reads followed by recruitment plot analysis of single reads could determine near-complete metagenome assembled genomes (MAGs). Culture-dependent and culture-independent analyses were in overall agreement with some distinct differences. For example, lactococci could not be isolated, presumably because they had entered a viable but not culturable (VBNC) state or because they were dead. Finally, several LAB, Hafnia paralvei, and Pseudomonas spp. isolates exhibited antimicrobial activities against oral or other pathogenic streptococci, and certain spoilage and pathogenic bacteria establishing their potential role in food bio-protection or new biomedical applications. Our study may pave the way for additional studies concerning artisanal sour creams to better understand the factors affecting their production and the quality. Full article

Sfela is a white brined Greek cheese of protected designation of origin (PDO) produced in the Peloponnese region from ovine, caprine milk, or a mixture of the two. Despite the PDO status of Sfela, very few studies have addressed its properties, including its microbiology. For this reason, we decided to investigate the microbiome of two PDO industrial Sfela cheese samples along with two non-PDO variants, namely Sfela touloumotiri and Xerosfeli. Matrix-assisted laser desorption/ionization–time of flight mass spectrometry (MALDI-TOF MS), 16S rDNA amplicon sequencing and shotgun metagenomics analysis were used to identify the microbiome of these traditional cheeses. Cultured-based analysis showed that the most frequent species that could be isolated from Sfela cheese were Enterococcus faecium, Lactiplantibacillus plantarum, Levilactobacillus brevis, Pediococcus pentosaceus and Streptococcus thermophilus. Shotgun analysis suggested that in industrial Sfela 1, Str. thermophilus dominated, while industrial Sfela 2 contained high levels of Lactococcus lactis. The two artisanal samples, Sfela touloumotiri and Xerosfeli, were dominated by Tetragenococcus halophilus and Str. thermophilus, respectively. Debaryomyces hansenii was the only yeast species with abundance > 1% present exclusively in the Sfela touloumotiri sample. Identifying additional yeast species in the shotgun data was challenging, possibly due to their low abundance. Sfela cheese appears to contain a rather complex microbial ecosystem and thus needs to be further studied and understood. This might be crucial for improving and standardizing both its production and safety measures. Full article