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At least 19 recordsLinked to original sources

PubMed2026

KG-Microbe: Building modular and scalable knowledge graphs for microbiome and microbial sciences.

BACKGROUND: The integration of many disparate forms of data is essential for understanding the microbial world and its interaction with the environment and human health. Doing so is particularly challenging in the context of microbe-host and microbe-microbe interactions that contribute to health or environmental outcomes. There are thousands of relevant microbial species, and millions of interactions among those microbes and with their environment or host. Integrated information (e.g., about host and microbial physiology, genetics, and metabolism) facilitates deeper understanding of complex mechanisms and helps interpret correlative results. RESULTS: The KG-Microbe construction framework is a novel approach to harmonizing bacterial and archaeal data in the form of a findable, accessible, interoperable, reusable and AI-ready knowledge graph (KG). Starting from a core KG with organismal traits, environments, and growth preferences and the integration of established ontologies, the framework generates a hierarchy of related KGs targeting specific use cases, including the human microbiome in the context of disease, or environmental microbiomes. The framework supports customizable taxa subsets representing communities or clades of interest. Evaluations of the KG-Microbe KGs through a series of competency questions demonstrate the accuracy and effectiveness of the data harmonization, and the utility of the resulting KGs in studies of inflammatory bowel disease and Parkinson's disease. Finally, the predictive and environmental capabilities of the KGs are demonstrated by predicting growth preferences using graph features. CONCLUSIONS: The KG-Microbe framework unifies microbial contexts in a single resource to support integrative analyses across biomedical, host, and environmental domains. KG-Microbe is a flexible, modular enabling technology for humans and machine learning methods to uncover candidate mechanistic explanations of microbial associations.

Microbiota↗

PubMed2024

Metagenome-based diversity and functional analysis of culturable microbes in sugarcane.

UNLABELLED: Sugarcane is a key crop for sugar and energy production, and understanding the diversity of its associated microbes is crucial for optimizing its growth and health. However, there is a lack of thorough investigation and use of microbial resources in sugarcane. This study conducted a comprehensive analysis of culturable microbes and their functional features in different tissues and rhizosphere soil of four diverse sugarcane species using metagenomics techniques. The results revealed significant microbial diversity in sugarcane's tissues and rhizosphere soil, including several important biomarker bacterial taxa identified, which are reported to engage in several processes that support plant growth, such as nitrogen fixation, phosphate solubilization, and the production of plant hormones. The Linear discriminant analysis Effect Size (LEfSe) studies identified unique microbial communities in different parts of the same sugarcane species, particularly Burkholderia, which exhibited significant variations across the sugarcane species. Microbial analysis of carbohydrate-active enzymes (CAZymes) indicated that genes related to sucrose metabolism were mostly present in specific bacterial taxa, including Burkholderia, Pseudomonas, Paraburkholderia, and Chryseobacterium. This study improves understanding of the diversities and functions of endophytes and rhizosphere soil microbes in sugarcane. Moreover, the approaches and findings of this study provide valuable insights for microbiome research and the use of comparable technologies in other agricultural fields. IMPORTANCE: This work utilized metagenomics techniques for conducting a comprehensive examination of culturable microbes and their functional characteristics in various tissues and rhizosphere soil of four distinct sugarcane species. This study enhances comprehension of the diversity and functions of endophytes and rhizosphere soil microbes in sugarcane. Furthermore, the methodologies and discoveries of this work offer new perspectives for microbiome investigation and the use of similar technologies in other agricultural fields.

Saccharum↗

PubMed2026

Advancing the Deciphering of Host-Microbe Crosstalk with Spatial Omics: A Mini-Review.

Host-microbe crosstalk refers to the reciprocal influences between a host and its resident or invading microorganisms. This crosstalk plays important roles in maintaining host health, regulating physiological functions, and coordinating responses to infection. The rapid rise of spatial omics is transforming how this crosstalk is studied in both animals and plants. Unlike traditional bulk omics, which homogenize tissues and erase spatial context, spatial methods preserve in situ organization and can simultaneously capture molecular information from hosts and microbes. As a result, researchers can characterize the spatial organization of colonization and infection, identify spatial associations between microbial niches and host cell states, and visualize local host response gradients across intact tissues. Current spatial omics technologies encompass sequencing-based, imaging-based, and hybrid platforms. Spatial multi-omics approaches enable the joint measurement or integration of gene expression, protein abundance, and metabolite distributions. Although spatial association alone does not establish causality, spatial omics provides a high-resolution framework for characterizing host-microbe relationships within intact tissues and generating spatially constrained, testable hypotheses. When combined with perturbation experiments and complementary experimental evidence, these hypotheses can contribute to mechanistic interpretation of host-microbe crosstalk. Here, we review spatial omics technologies, compare their suitability and major trade-offs for host-microbe studies, and discuss computational strategies, analytical challenges, and future prospects.

Multiomics↗

PubMed2025

In silico encounters: harnessing metabolic modelling to understand plant-microbe interactions.

Understanding plant-microbe interactions is vital for developing sustainable agricultural practices and mitigating the consequences of climate change on food security. Plant-microbe interactions can improve nutrient acquisition, reduce dependency on chemical fertilizers, affect plant health, growth, and yield, and impact plants' resistance to biotic and abiotic stresses. These interactions are largely driven by metabolic exchanges and can thus be understood through metabolic network modelling. Recent developments in genomics, metagenomics, phenotyping, and synthetic biology now enable researchers to harness the potential of metabolic modelling at the genome scale. Here, we review studies that utilize genome-scale metabolic modelling to study plant-microbe interactions in symbiotic, pathogenic, and microbial community systems. This review catalogues how metabolic modelling has advanced our understanding of the plant host and its associated microorganisms as a holobiont. We showcase how these models can contextualize heterogeneous datasets and serve as valuable tools to dissect and quantify underlying mechanisms. Finally, we consider studies that employ metabolic models as a testbed for in silico design of synthetic microbial communities with predefined traits. We conclude by discussing broader implications of the presented studies, future perspectives, and outstanding challenges.

Plants↗

PubMed2025

Label-free structural imaging of plant roots and microbes using third-harmonic generation microscopy.

Root biology is pivotal in addressing global challenges including sustainable agriculture and climate change. However, roots have been relatively understudied among plant organs, partly due to the difficulties in imaging root structures in their natural environment. Here we used microfabricated ecosystems (EcoFABs) to establish growing environments with optical access and employed nonlinear multimodal microscopy of third-harmonic generation (THG) and three-photon fluorescence (3PF) to achieve label-free, in situ imaging of live roots and microbes at high spatiotemporal resolution. THG enabled us to observe key plant root structures including the vasculature, Casparian strips, dividing meristematic cells, and root cap cells, as well as subcellular features including nuclear envelopes, nucleoli, starch granules, and putative stress granules. THG from the cell walls of bacteria and fungi also provides label-free contrast for visualizing these microbes in the root rhizosphere. With simultaneously recorded 3PF signal, we demonstrated our ability to investigate root-microbe interactions by achieving single-bacterium tracking and subcellular imaging of fungal spores and hyphae in the rhizosphere.

Plant Roots↗

PubMed2026

Identification of a novel human gut microbes and microbial metabolites related genes signature for prognostic implication in head and neck squamous carcinomas.

BACKGROUND: The gut microbiota acts as a critical driver influencing the pathogenesis, therapeutic response, and clinical outcomes across various cancer types. This study aimed to investigate the prognostic value of human gut microbes and microbial metabolites related genes (HGMMMRGs) in head and neck squamous cell carcinoma (HNSCC). METHODS: We constructed a prognostic risk model comprising 19 core HGMMMRGs using LASSO penalized regression and a multivariate Cox proportional hazards model. The predictive performance of the model was evaluated through Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, nomograms, and concordance index. In addition, functional enrichment analysis was performed on the differentially expressed risk genes. Furthermore, the relationship between the immune microenvironment of HNSCC and the risk diagnostic model was examined. Western blot analysis was used to assess the expression levels of IL10 in both HNSCC tissues and adjacent normal tissues. Finally, the correlation between IL10 and the gut microbiota was explored. RESULTS: This study developed a risk score model integrating 19 HGMMMRG genes, which can serve as a tool to guide prognosis and immune microenvironment assessment in HNSCC patients. Survival analysis showed that patients in the high-risk group had significantly worse outcomes (P < 0.05). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed significant enrichment of differentially expressed genes (DRLs) and immune-related pathways. Western blot analysis further confirmed that IL10 was highly expressed in HNSCC, and the abundance of Faecalibacterium prausnitzii and Enterococcus durans colonies was correlated with IL10 expression. CONCLUSION: We developed a prognostic model for HGMMMRGs that can be effectively used to predict OS in patients with HNSCC. Second, Faecalibacterium prausnitzii and Enterococcus durans can influence the prognosis of patients with HNSCC by mediating the expression IL10 and thereby affecting the prognosis of HNSCC patients. Thus, human gut microbes and microbial metabolite-related genes may be another promising strategy for the treatment of patients with HNSCC.

HNSCC↗

PubMed2024

Dissecting host-microbe interactions with modern functional genomics.

Interrogation of host-microbe interactions has long been a source of both basic discoveries and benefits to human health. Here, we review the role that functional genomics approaches have played in such efforts, with an emphasis on recent examples that have harnessed technological advances to provide mechanistic insight at increased scale and resolution. Finally, we discuss how concurrent innovations in model systems and genetic tools have afforded opportunities to interrogate additional types of host-microbe relationships, such as those in the mammalian gut. Bringing these innovations together promises many exciting discoveries ahead.

Genomics↗

PubMed2026

Endozoicomonas acroporae enhances coral thermal resilience through host-microbe coordination.

Probiotics hold promise for enhancing coral resilience under climate-driven thermal stress, yet their mechanisms remain poorly understood. Although the bacterial genus Endozoicomonas has been proposed to benefit corals, in vivo evidence of beneficial effects on the host remains limited. Here, we establish Endozoicomonas acroporae Acr-14T as a coral probiotic and characterize its effects on the reef-building coral Stylophora pistillata. We show that E. acroporae Acr-14T enhances host thermal tolerance, colonizes coral tissues, and forms coral-associated microbial aggregates. Microbial profiling indicates that probiotic treatment is associated with reduced relative abundances of opportunistic microbes and enrichment of putatively beneficial taxa. To support transcriptomic analyses, we assembled a chromosome-level genome of S. pistillata clade 1 (Pacific lineage) and found that E. acroporae Acr-14T treatment mitigates heat-induced protein-folding stress and apoptotic signaling. Single-cell transcriptomics further revealed altered expression of genes involved in S-adenosylmethionine (SAMe) metabolism and pro-survival signaling in gastrodermal cells of probiotic-treated corals. Together, our results provide a cell-type-resolved view of host responses linked to Endozoicomonas-mediated coral thermal resilience and offer insight into molecular mechanisms implicated in host-microbe interactions under environmental stress.

Animals↗

PubMed2026

Trimethylamine-producing microbe Bacillus megaterium KCTC 3007 promotes antitumor immunity in endometrial cancer via type I interferon response pathways.

BACKGROUND: Endometrial cancer (ECa) is one of the most common gynecologic malignancies, with limited therapeutic responses in metastatic or recurrent cases. The bacterial microbiota has emerged as a key modulator of carcinogenesis and antitumor immunity. However, the role of endometrial microbiota in ECa pathogenesis and prognosis remains poorly understood. METHODS: We performed comprehensive multi-omics analysis integrating metatranscriptomics, transcriptomics, and targeted metabolomics from 60 ECa and 18 benign patients. RNA sequencing enabled simultaneous profiling of active tissue-resident microbiota and host gene expression. Serum metabolomics was conducted on all patients. Identified microbial-metabolite associations were validated through in vitro co-culture experiments using peripheral blood mononuclear cells (PBMCs), cancer cell lines, RNA sequencing, and live cell imaging. RESULTS: ECa patients exhibited significantly altered microbial diversity and composition compared to benign controls. Through integrated multi-omics analysis, we identified Bacillus megaterium (BM) KCTC 3007 as a beneficial microbe associated with prolonged recurrence-free survival. In an exploratory analysis of ECa subtypes, Cupriavidus taiwanensis and Marinomonas primoryensis showed potential links to poor prognosis, although these observations warrant caution due to the limited size of certain subgroups. Tissue BM abundance positively correlated with serum trimethylamine N-oxide (TMAO) levels, particularly in postmenopausal women. In vitro experiments demonstrated that BM KCTC 3007 enhanced antitumor immunity by promoting interleukin and type I interferon expression, expanding CD8 + T cell populations, and increasing immune cell-tumor cell interactions. RNA sequencing revealed activation of interferon alpha response and immune cell proliferation pathways, with IFNAR1 identified as a key upstream regulator. TMAO treatment recapitulated these immune-activating effects, enhancing CD8 + T cell responses and preferentially inducing pyroptotic cancer cell death. CONCLUSIONS: We provide the first evidence that tissue-resident BM KCTC 3007 promotes antitumor immunity in ECa through TMAO production and subsequent type I interferon-mediated immune activation. This integrated multi-omics approach establishes a complete microbe-metabolite-host mechanistic pathway and highlights the therapeutic potential of TMAO-producing probiotic strains for ECa treatment. Video Abstract.

Female↗

PubMed2024

Obesity-enriched gut microbe degrades myo-inositol and promotes lipid absorption.

Numerous studies have reported critical roles for the gut microbiota in obesity. However, the specific microbes that causally contribute to obesity and the underlying mechanisms remain undetermined. Here, we conducted shotgun metagenomic sequencing in a Chinese cohort of 631 obese subjects and 374 normal-weight controls and identified a Megamonas-dominated, enterotype-like cluster enriched in obese subjects. Among this cohort, the presence of Megamonas and polygenic risk exhibited an additive impact on obesity. Megamonas rupellensis possessed genes for myo-inositol degradation, as demonstrated in vitro and in vivo, and the addition of myo-inositol effectively inhibited fatty acid absorption in intestinal organoids. Furthermore, mice colonized with M. rupellensis or E. coli heterologously expressing the myo-inositol-degrading iolG gene exhibited enhanced intestinal lipid absorption, thereby leading to obesity. Altogether, our findings uncover roles for M. rupellensis as a myo-inositol degrader that enhances lipid absorption and obesity, suggesting potential strategies for future obesity management.

Inositol↗

PubMed2025

The application of AI-driven and engineered intratumoral microbes in cancer therapy.

BACKGROUND: Although investigations of the intratumoral microbiota date back thousands of years, breakthrough transformations have only recently been achieved through high-throughput sequencing and multiomic technologies. These advances have revealed diverse and tumor type-specific microbial communities that drive carcinogenesis via immunomodulation, metabolic reprogramming, and genomic instability. Current cornerstones of cancer therapies-including chemotherapy, radiotherapy, immunotherapy, and targeted therapy-are limited by systemic toxicity, localized tissue damage, drug resistance, and low patient response rates. These constraints underscore the urgent need for more effective and precise therapeutic strategies. MAIN BODY: This review comprehensively integrates artificial intelligence (AI) technologies into the characterization of the intratumoral microbiota, facilitating the development of novel computational pipelines for mapping microbe-host crosstalk. We systematically summarize recent advances in engineered microbial therapeutics, including bacteria designed for targeted antitumor activity and engineered microorganisms that enable the localized delivery of therapeutic agents. Furthermore, this review critically evaluates the safety profiles of microbiota-based interventions and discusses key challenges in clinical translation. CONCLUSIONS: By combining cutting-edge computational technologies, biological research, and clinical insights, this review aims to bridge the gap between microbiome science and oncological practice, pioneering innovative strategies for microbiota-guided diagnostics and personalized cancer therapy.

Humans↗

PubMed2025

Microbe-induced gene silencing of fungal gene confers efficient resistance against Fusarium graminearum in maize.

UNLABELLED: Small RNAs (sRNAs), the main effectors of RNA interference (or RNA silencing, RNAi), mediate cell-autonomous and non-cell-autonomous gene silencing. The discoveries of trans-kingdom RNAi and interspecies RNAi have accelerated the development of RNAi-based crop protection technologies. Recently, based on interspecies RNAi, a practical technology termed microbe-induced gene silencing (MIGS) without the need of host genetic modification is developed for crop protection against Verticillium dahliae and Fusarium oxysporum in cotton and rice plants. In this study, we utilized MIGS technology to protect maize against Fusarium graminearum, which is responsible for maize stalk rot. An RNAi-engineered Trichoderma harzianum strain, Th-FgPmt2i, was exploited to generate double-stranded RNAs (dsRNAs) to trigger the silencing of the FgPTM2 gene. Our data verify that sRNAs generated from Th-FgPmt2i can silence the FgPMT2 gene via translational inhibition in F. graminearum. We further demonstrated that Th-FgPmt2i has a stronger capacity than does the T. harzianum chassis for protection of maize against F. graminearum. Coupled with our studies on crop protection against V. dahliae and F. oxysporum, our findings reveal that MIGS can be exploited to protect various crops against distinct fungal pathogens and has extensive applicability. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42994-025-00212-9.

Fusarium graminearum↗

PubMed2024

Protocol to decode the role of transcriptionally active microbes in SARS-CoV-2-positive patients using an RNA-seq-based approach.

The elucidation of the role of microorganisms in human infections has been hindered by difficulties using conventional culture-based techniques. Here, we present a protocol for the investigation of transcriptionally active microbes (TAMs) using an RNA sequencing (RNA-seq)-based approach. We describe the steps for RNA isolation, viral genome sequencing, RNA-seq library preparation, and metatranscriptomic and transcriptomic analysis. This protocol permits a comprehensive evaluation of TAMs' contributions to the differential severity of infectious diseases, with a particular focus on diseases such as COVID-19. For complete details on the use and execution of this protocol, please refer to Devi et al.1.

Humans↗

PubMed2026

Substrate recognition and cleavage by mucin degrading O-glycopeptidases from the gut microbe Bacteroides caccae.

O-glycopeptidases are enzymes that hydrolyze the peptide bonds in glycoproteins by a mechanism that involves specific recognition of O-linked glycans on the substrate. Bacteroides caccae, an accomplished mucin degrader, is a member of the human gut microbiota with sixteen genes encoding putative O-glycopeptidases in the peptidase_M60 family. At present, the diversity of substrate selectivity in O-glycopeptidases is not well-understood, nor is the rationale behind their expansion in bacteria such as B. caccae. Here, we reveal the activity and diversity of the peptidase_M60 O-glycopeptidases encoded in the B. caccae genome. At least thirteen of the sixteen peptidase_M60 encoding genes produce active mucinolytic enzymes. Targeted functional studies by a high-throughput FRET screen combined with detailed kinetic analyses reveal that five examples in an uncharacterized clade of peptidase_M60 proteins are specifically O-glycopeptidases with different substrate selectivities despite their relatively high degree of relatedness. Structural analyses of these enzymes, including bound complexes, reveal new insight into the molecular underpinnings of O-glycopeptidase diversity. This highlights the larger context of how varied the selectivity of peptidase_M60 O-glycopeptidases can be for the glycan moiety and/or the peptide portion of the substrates, and why mucin degraders like B. caccae diversify O-glycopeptidase substrate repertoires to potentially maximize breakdown of this extraordinarily complex polymer.

Mucins↗

PubMed2025

A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites.

Genome-scale modeling of microbiome metabolism enables the simulation of diet-host-microbiome-disease interactions. However, current genome-scale reconstruction resources are limited in scope by computational challenges. We developed an optimized and highly parallelized reconstruction and analysis pipeline to build a resource of 247,092 microbial genome-scale metabolic reconstructions, deemed APOLLO. APOLLO spans 19 phyla, contains >60% of uncharacterized strains, and accounts for strains from 34 countries, all age groups, and multiple body sites. Using machine learning, we predicted with high accuracy the taxonomic assignment of strains based on the computed metabolic features. We then built 14,451 metagenomic sample-specific microbiome community models to systematically interrogate their community-level metabolic capabilities. We show that sample-specific metabolic pathways accurately stratify microbiomes by body site, age, and disease state. APOLLO is freely available, enables the systematic interrogation of the metabolic capabilities of largely still uncultured and unclassified species, and provides unprecedented opportunities for systems-level modeling of personalized host-microbiome co-metabolism.

Humans↗

PubMed2024

Biochemical insights into the biodegradation mechanism of typical sulfonylureas herbicides and association with active enzymes and physiological response of fungal microbes: A multi-omics approach.

The extensive use of sulfonylurea herbicides has raised major concerns regarding their long-term soil residues and agroecological risks despite their role in agricultural protection. Microbial degradation is an important approach to remove sulfonylureas, whereas understanding the associated biodegradation mechanisms, enzymes, and physiological responses remains incomplete. Based on the rapid biodegradation of nicosulfuron by typical fungal isolate Talaromyces flavus LZM1, the dependency on cellular accumulation and environmental conditions, e.g. pH and nutrient supplies, was shown in the study. The biodegradation of nicosulfuron occurred intracellularly and followed the cascade of reactions including hydrolysis, Smile contraction rearrangement, hydroxylation, and opening of the pyrimidine ring. Besides 2-amino-4,6-dimethoxypyrimidine (ADMP) and 2-aminosulfonyl-N,N-dimethylnicotinamide (ASDM), numerous products and intermediates were newly identified and the structural forms of methoxypyrimidine and sulfonylurea bridge contraction rearrangement are predicted to be more toxic than nicosulfuron. The biodegradation should be enzymatically regulated by glycosylphosphatidylinositol transaminase (GPI-T) and P450s, which were manifested with the significant upregulation in proteomics. It is the first time that the hydrolysis of nicosulfuron into ADMP and ASDM have been associated with GPI-T. The integrated pathways of biodegradation were further elucidated through the involvement of various active enzymes. Except for the enzymatic catalysis, the physiological responses verified by metabolo-proteomics were critical not only to regulate material synthesis, uptake, utilization, and energy transfer but also to maintain antioxidant homeostasis, biodegradability, and tolerance of nicosulfuron by the differentially expressed metabolites, such as acetolactate synthase and 3-isopropylmalate dehydratase. The obtained results would help understand the biodegradation mechanism of sulfonylurea from chemicobiology and enzymology and promote the use of fungal biodegradation in pollution rehabilitation.

Herbicides↗

PubMed2026

The global potential of freshwater microbes for plastic degradation.

Plastic pollution is becoming increasingly severe on a global scale, and the potential for biodegradation as a treatment method that is environmentally friendly merits greater attention. A significant number of genes that associated the degradation of plastic (PDAGs) have been identified, however, the distribution of these genes among microorganisms in global inland waters remains to be elucidated. A global-scale meta-analysis was conducted, incorporating approximately 1000 metagenome datasets of inland waters across seven continents. A total of 13,109 metagenome-assembled genomes (MAGs) were obtained by means of metagenomics binning, and 22,621 PDAGs were identified from these. Among these recognized PDAGs, phenylacetaldehyde dehydrogenase (PAD) was the most dominant (n = 16,664), followed by catalase (n = 5931). The predominant hosts for PAD and catalase were identified as Gamma-proteobacteria and Bacteroidia, respectively. The largest number of both PAD and catalase was found in MAGs from North America, while the average gene number in single MAG was highest in MAGs from Oceania. In accordance with the prediction of traits, PDAG-carrying MAGs from Europe demonstrated the fastest growth rate and the lowest optimal growth rate. Furthermore, 25 styrene monooxygenase (StyA) enzymes were identified, which were found to cluster into two distinct groups hosted by Alpha-proteobacteria and Gamma-proteobacteria, respectively. Moreover, 11 MAGs were observed to possess the complete pathway of polystyrene degradation. These results explored the potential of inland water microorganisms as a biological resource for plastic degradation and provided valuable microbial reference information that can be used to develop biological treatment technologies for mitigating plastics.

Plastics↗

PubMed2026

Fantastic microbes and where to find them: evaluating learning-by-doing outcomes in a crowdfunded metagenomics workshop.

Metagenomics offers a powerful framework for authentic, interdisciplinary learning, yet it remains underrepresented in undergraduate education due to technical and infrastructural barriers. We hypothesized that a research-based, learning-by-doing metagenomics workshop supported by accessible bioinformatics tools could enhance students' perceived skills, self-efficacy, and conceptual understanding of metagenomic analysis. To test this hypothesis, we designed and evaluated a hybrid hands-on workshop in which undergraduate and postgraduate students analyzed real environmental shotgun metagenomic datasets generated from soil samples collected during a citizen science initiative. Using the graphical workflow platform KBase, participants completed an end-to-end metagenomic analysis, from quality control and assembly to genome reconstruction, taxonomic classification, functional annotation, and scientific presentation of results. Educational outcomes were assessed through validated retrospective pre-post questionnaires, self-efficacy scales, and an open-ended conceptual understanding task. Participants showed significant increases in perceived metagenomic skills and confidence in performing metagenomic analyses, while gains in perceived learning showed a positive trend. Conceptual understanding improved across educational levels, particularly among participants with limited prior experience. Together, these findings demonstrate that authentic, data-driven metagenomics activities can effectively lower barriers to computational biology and foster meaningful learning through hands-on research experiences.

Metagenomics↗