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Results for “lignocellulose”

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25 records · Page 2Linked to original sources

PubMed2026

Whole-genome sequencing and analysis of the endophytic fungus Alternaria alternata Y-2 from Leymus chinensis.

To explore the genetic basis and functional potential of beneficial symbiosis between the endophytic fungus Alternaria alternata Y-2 and its host Leymus chinensis, we performed Illumina-based draft whole-genome sequencing and systematic bioinformatic analysis. Although this assembly does not reach telomere-to-telomere completeness, it provides high-quality gene-level information for gene prediction, functional annotation, carbohydrate-active enzyme (CAZyme) identification, and secondary metabolite biosynthetic gene cluster analysis. The final genome size of A. alternata Y-2 was 34,383,676 bp with a GC content of 51.0%, containing 12,724 predicted protein-coding genes, 90 tRNAs, and 12 rRNAs. BUSCO assessment showed 98.9% completeness, supporting the high quality of this draft genome. A total of 12,627 genes were successfully annotated in the NCBI NR database, and 17,183 genes were functionally categorized using GO terms. In total, 448 CAZyme genes and 21 secondary metabolite biosynthetic gene clusters were identified, which are potentially involved in lignocellulose degradation, cellular redox homeostasis and biosynthesis of bioactive metabolites. Based on ITS sequence alignment, NR annotation, and phylogenetic analysis of single-copy orthologous genes, the strain was confidently identified as A. alternata. This study firstly reports the draft genome of an endophytic A. alternata strain derived from L. chinensis and provides valuable genetic resources for exploring the endophytic lifestyle, stress tolerance, and bioactive metabolite potential of this fungus.

Alternaria↗

PubMed2026

Cross-domain cooperation drives nutrient acquisition and metabolism in the bark beetle holobiont.

Microbial symbiosis underpins host adaptation, yet mechanisms of metabolic integration in holobionts remain unclear. Using metatranscriptomics, genomics, and metabolic assays, we investigated gut microbiome interactions in the European spruce bark beetle (Ips typographus). We observed metabolic complementarity among symbionts and host, forming cross-domain networks that support nutrient acquisition. Nitrogen recycling revealed strong interdependence: no single partner possessed a complete uric acid degradation pathway, but combined evidence supports a distributed pathway spanning beetle, Bacteria, and fungi. Additionally, bacterial nitrate reduction to ammonia indicates a potential nitrogen influx, making otherwise inaccessible inorganic nitrogen available to the host. Shaped by microbial interactions, symbionts also likely supply specific amino acids, while vitamin metabolism showed cross-domain co-metabolism, with Bacteria as main producers of B vitamins, while host and fungi modulated interconversion. Carbohydrate degradation was highly partitioned; bacteria target xylan and pectin, while fungi contribute to glucan breakdown. Crucially, our data provide indirect evidence that the beetle may contribute to complete cellulose degradation, highlighting an underappreciated host role in lignocellulose processing. In terms of enzymatic functional diversity, the bacteriome emerged as the most important microbiome component-an observation that contrasts with the traditional focus on fungi and underscores the need to consider bacterial contributions in insect symbioses. Despite life-stage variation, core metabolic functions remained stable. Overall, metabolic interdependence, rather than microbial composition alone, structures holobiont function. These results highlight functional redundancy and ecological resilience, emphasizing the importance of microbial cooperation and host-microbe metabolic evolution.

Bark beetle↗

PubMed2026

Upcycling Vegetable Waste Into Functional Food Ingredients via Synergistic Microbial Engineering and Artificial Intelligence.

The escalating generation of global vegetable waste represents a critical loss of bioactive resources, necessitating a paradigm shift from passive disposal to active nutrient upcycling. However, the industrial conversion of this heterogeneous biomass into standardized functional food ingredients is currently impeded by significant techno-economic barriers, primarily structural recalcitrance, compositional inconsistency, and the presence of toxic fermentation inhibitors. This review provides a comprehensive analysis of the synergistic application of microbial engineering and artificial intelligence (AI) to resolve these bioprocessing bottlenecks within a food-to-food closed-loop framework (as shown in the graphical abstract). We evaluate recent advances in engineering food-grade microbial chassis (e.g., Saccharomyces cerevisiae and Escherichia coli) to enhance lignocellulose degradation and stress tolerance. Concurrently, we examine the integration of AI across the entire value chain, covering deep learning-based rational enzyme design, genome-scale metabolic modeling, and intelligent process control for precision fermentation. Current evidence demonstrates that the hardware-software coupling of engineered strains and AI algorithms significantly enhances conversion efficiency and process robustness. Key findings highlight that AI-driven Design-Build-Test-Learn cycles facilitate the de novo creation of enzymes with superior kinetics and strains with adaptive stress response capabilities against toxins. Moreover, dynamic digital twin models effectively mitigate the impact of substrate variability, ensuring the batch-to-batch consistency required for food applications. We conclude that this data-driven synergistic paradigm is pivotal for establishing a resilient circular bioeconomy, enabling the reliable bioconversion of waste into high-value single-cell proteins, natural flavor additives, and sustainable packaging materials.

Artificial Intelligence↗

PubMed2026

The anaerobic fungus Caecomyces churrovis produces H2 via a non-bifurcating NADH-dependent enzyme complex.

UNLABELLED: Hydrogenosomes are mitochondrion-derived organelles that produce ATP and H2 to support energy metabolism in anaerobic eukaryotes. H2 production allows reoxidation of reduced cofactors generated during fermentative metabolism; however, the metabolic mechanisms for H2 production in anaerobic eukaryotes remain incompletely understood. In particular, it remains unclear whether anaerobic fungi (AF) hydrogenosomes use a ferredoxin-dependent pathway or a distinct mechanism to regenerate NAD(P)+ and link electron transfer to H2 formation. Here, by combining genomic search, proteomic analysis, and enzymology, we reveal the molecular mechanism for H2 production in the AF Caecomyces churrovis. Our enzyme assays on the organelle fraction of C. churrovis revealed the activity of H2:NAD+ oxidoreductase but not pyruvate:ferredoxin oxidoreductase, which is usually linked to H2 formation. We identified genes encoding [FeFe] hydrogenase (Hyd) and NADH dehydrogenase subunits E and F (NuoE and NuoF) in C. churrovis and confirmed their expression in the isolated hydrogenosomal fractions by proteomic analysis. Combining the individually purified enzymes, we found Hyd and NuoEF proteins formed H2 directly from NADH independently of ferredoxin, functioning as a non-bifurcating NADH-dependent enzyme rather than an electron-bifurcating enzyme known from anaerobic prokaryotes. We identified homologs of hydrogenosomal NuoE, NuoF, and Hyd in many other AF, indicating this pathway is commonly shared among the AF. This work demonstrates the existence of a non-bifurcating NADH-dependent enzyme complex for H2 production in eukaryotes. Moreover, this complex could potentially be exploited as a target for controlling AF H2 production and altering fungal metabolism. IMPORTANCE: H2 production is a prominent feature of anaerobic energy metabolism, yet our understanding of eukaryotic mechanisms remains limited. Anaerobic fungi (AF) are key decomposers of lignocellulose and contribute to hydrogen flux in anaerobic environments. Although it has been more than 40 years since the H2 production in Neocallimastix was first reported, the molecular mechanism for hydrogenosomal H2 production and redox balance remains unclear. We demonstrate that AF produce H2 from NADH utilizing a non-bifurcating NADH-dependent enzyme complex rather than an electron-bifurcating, ferredoxin-dependent variant. We show that this enzyme complex is conserved across multiple AF lineages and thus demonstrate the occurrence of a non-bifurcating NADH-dependent enzyme in eukaryotes. This discovery expands our understanding of eukaryotic hydrogenosomal metabolism, reveals a previously unknown strategy for redox balancing, and highlights potential targets for manipulating H2 production. These insights have broad implications for microbial energy metabolism, anaerobic ecosystems, and bioengineering of H2-producing systems.

Hydrogen↗

PubMed2026

Integrated functional genomics and safety assessment of plant-growth-promoting Caryophanales from post-maize-cultivation soils.

This study aimed to evaluate six environmental bacterial strains isolated from post-maize cultivation soils as candidates for agricultural biopreparation development, using an integrated functional genomic and safety assessment framework. Building on experimental validation of plant-growth-promoting activities, the analysis included: plant-growth-promoting traits (PGPT-Pred) using PLABase; carbohydrate-active enzymes (CAZymes) relevant for lignocellulosic crop residue degradation (dbCAN3); secondary metabolite profiles (antiSMASH); and screening for virulence factors and antibiotic resistance genes (ABRicate, BTyper3).All analyzed strains possess 1,449-1,617 predicted PGPT-encoding genes (24.1-35.9% of total genes), which are strongly shaped by taxonomic relatedness, as confirmed by congruence testing against ANI-based genomic divergence. Paenibacillus amylolyticus 5mez and Priestia megaterium 7psych showed distinct functional profiles compared to Bacillus spp., while Bacillus subtilis sensu lato strains were most similar to each other. Genomic predictions suggest involvement in nutrient acquisition (N, P, K, Fe) and stress mitigation. Secondary metabolite analysis revealed high biosynthetic potential, with non-Bacillus species harbouring a large proportion of unknown gene clusters, indicating underexplored metabolite diversity. CAZyme profiling identified P. amylolyticus 5mez as the most enzyme-rich strain, while B. cereus s.s. zielonkawy showed ligninolytic potential despite low overall CAZyme abundance. The safety assessment identified B. cereus s.s. zielonkawy as toxigenic and unsuitable for use. Of the remaining strains, P. amylolyticus 5mez and Pr. megaterium 7psych demonstrated the most favourable safety profiles, exhibiting no detectable virulence factors or antibiotic resistance genes, justifying their priority use in agricultural biopreparations, pending phenotypic validation. Given the high-dimensional, low-sample-size nature of multi-trait datasets in applied microbial genomics, tailored statistical approaches, including noise-reduction-validated PCA and distance-based congruence testing, were applied; their rationale and limitations are discussed.

Soil Microbiology↗

PubMed2026

A hybrid and cost-efficient barcoding strategy for full-length 16S rRNA gene nanopore sequencing of environmental samples.

BACKGROUND: Accurate species-level identification of bacteria in complex environmental samples is essential for applications in biotechnology, ecological monitoring, and clinical diagnostics. Short-read platforms such as Illumina frequently truncate the 16S rRNA gene, limiting taxonomic resolution. In this work, we applied Oxford Nanopore Technology (ONT) long-read sequencing to full-length 16S rRNA amplicon in samples from natural soil amended with lignocellulosic biomass and a simplified microbial community derived from cultures grown on selective and differential carboxymethyl cellulose (CMC)-based substrates, with the aim to evaluate the difference in performance between a real, complex community and a less complex system. To reduce consumable costs, we substituted the standard ONT Barcoding kits with an in-house hybrid barcoding workflow. Specifically, PacBio PCR-based barcoding protocol was used for sample indexing, followed by library preparation using the ONT Ligation Sequencing Kit. This simplified approach retained compatibility with MinION and Flongle flow cells and supported accurate downstream demultiplexing while lowering barcode costs substantially. Additionally, a new bioinformatic workflow tailored to ONT data was implemented. RESULTS: Overall, the hybrid protocol significantly reduced per-sample barcoding costs while preserving high sequencing quality and throughput. The sequencing run yielded over 5 Gb of quality-filtered data (Q-score ≥ 10). Furthermore, the new bioinformatic workflow allowed taxonomic assignment at the species level for 49.38% of annotated taxa, compared to just 4.59% using Illumina NovaSeq sequencing of the V3-V4 region. ONT also recovered 2.3 times more genera and 1.3 times more families. Although 16S rRNA gene sequencing often cannot distinguish between closely related species, particularly within taxonomically complex groups, in this work, full-length reads substantially improved both taxonomic resolution and database matching. CONCLUSIONS: These results show that full-length 16S rRNA sequencing with ONT, paired with a low-cost barcoding strategy, enhanced taxonomic resolution compared to short-read workflows. This approach also offers a scalable and cost-effective option for high-resolution microbiome profiling in research and applied settings.

RNA, Ribosomal, 16S↗

PubMed2026

Unlocking the molecular engineering of Geobacillus glycoside hydrolases as a source of industrial biocatalysts.

This review examines Geobacillus sensu stricto as a source of thermostable glycoside hydrolases (GH) for biomass conversion, food processing, and enzyme engineering. Recent peer-reviewed literature was assessed with emphasis on taxonomy, genome-based Carbohydrate-Active Enzymes (CAZyme) prediction, biochemical validation, structural data, and engineering case studies. Taxonomic boundaries were interpreted using current Anoxybacillaceae frameworks, with Parageobacillus treated as a related comparator rather than as Geobacillus. The strongest evidence supports GH13 alpha-amylases, xylan-active systems, beta-xylosidases, and selected accessory enzymes. Recent studies also show that genome mining must be coupled with enzymatic assays and product profiling because CAZyme annotation alone does not prove industrial function. Molecular engineering has improved relevant traits, including the longer thermal half-life of engineered G. stearothermophilus alpha-amylase variants, the increased catalytic efficiency of oligo-alpha-1,6-glucosidase variants, and improved AmyS expression in Bacillus subtilis. Geobacillus glycoside hydrolases are best interpreted as process-specific, engineerable biocatalytic templates. Their translation requires reliable taxonomy, functional validation, structural interpretation, scalable expression and testing on realistic substrates. This synthesis also recognises current limitations: many predicted CAZymes still lack biochemical validation, complete cellulolytic systems remain less mature than xylan- and starch-active systems, and scale-up data remain scarce.

Geobacillus↗