In this study, three Neopestalotiopsis taxa were identified, associated with leaves of Zingiber officinale, Elaeagnus pungens and Salacca zalacca. Based on morphology and multi–gene analyses of the internal transcribed spacer (ITS), beta-tubulin (TUB2) and translation elongation factor 1–alpha (TEF1), the five strains of Neopestalotiopsis represent two novel and one known species. They are introduced with descriptions, illustrations and notes herein.

Two coelomycetous strains with appendage-bearing conidia were collected from diseased leaves of Celtis sinensis (Urticales, Ulmaceae) and Indocalamus tessellatus (Poales, Poaceae) in Yunnan and Hainan provinces, southern China. Both strains produced 4-septate conidia with concolourous median cells, which were similar to Pestalotiopsis and Pseudopestalotiopsis. Based on the comprehensive morphological comparison and multi-gene (ITS, tub2, tef1) phylogenetic analyses, the strains were found to belong to Pseudopestalotiopsis. They represent two novel taxa and are described as Pseudopestalotiopsis celtidis and P. indocalami.

Background/Objectives: Limosilactobacillus fermentum KUB-D18, a heterofermentative lactic acid bacterium with promising probiotic properties, is known for promoting gut health and nutrient absorption. Originally isolated from chicken intestines, this strain demonstrates versatile metabolic capabilities in diverse gastrointestinal environments. However, the metabolic functions and sugar transport-related genes remain largely unexplored. This study thus aimed to dissect metabolic functions and sugar transports of L. fermentum KUB-D18. Methods: Next-generation and third-generation sequencing techniques using integrative genomic platform towards transportome analysis were performed. Results: The complete genome, sized at 2.12 Mbps with a GC content of 51.36%, revealed 2079 protein-encoding genes, of which 1876 protein functions were annotated and identified in top categories involved in amino acids, nucleotide, energy, and carbohydrate transports and metabolisms. Comparative genes analysis identified 50 core and 12 strain-specific genes linked to probiotic properties, e.g., acid resistances and bile tolerances, antioxidant functions, or anti-inflammatory properties. Further, sugar transportome analysis uncovered 57 transporter genes, demonstrating diverse carbon utilization and phosphotransferase (PTS) systems, corroborated by API 50 CHL test results for carbohydrate metabolism profile. Conclusions: These findings enhance the comprehensive metabolic understanding of L. fermentum KUB-D18, supporting its industrial potential and applications in engineered probiotics.

Limosilactobacillus fermentum KUB-D18 is a probiotic strain with significant potential in food fermentation and health promotion, yet the systems-level mechanisms underlying its physiological robustness remain elusive. To elucidate the metabolic remodeling strategies operating across growth phases, we developed an integrated framework combining genome-scale metabolic modeling (GSMM) with transcriptomics. A high-quality metabolic model for L. fermentum KUB-D18, designated iYH640 and comprising 640 genes, 1530 metabolites, and 1922 reactions, was constructed and validated against experimental growth data. Specifically, in vitro assays measuring biomass and glucose concentrations showed a maximum specific growth rate of 0.2696 h⁻¹ and a glucose uptake rate of 11.75 mmol gDCW⁻¹ h⁻¹, providing physiological constraints for the model. Using transcriptome-regulated flux balance analysis (TR-FBA), gene expression profiles from the logarithmic phase (L-phase) and stationary phase (S-phase) were integrated to quantify growth phase-specific metabolic flux distributions. These simulations revealed a distinct transcription-driven metabolic shift, in which the organism moves from a proliferation-oriented metabolic state with active central carbon metabolism and macromolecule synthesis to a maintenance-oriented state. This S-phase is characterized by reduced flux through anabolic pathways together with the selective preservation of redox balance and nucleotide homeostasis. Collectively, these results provide a quantitative explanation of how L. fermentum KUB-D18 balances growth and maintenance, offering a mechanistic basis for improving its stability and functional performance in industrial probiotic applications.

Moniliaceous hyphomycetes were collected from leaves of Houttuynia cordata and Liriope platyphylla in Guang Xi Medicinal Botanical Garden, Guangxi Province, China. Morphological characteristics and multi-gene phylogenetic analyses of the calmodulin (cmdA), RNA polymerase II second largest subunit (rpb2), translation elongation factor 1-alpha (tef1), and β-tubulin (tub2), showed that four Fusarium strains represent two novel species viz. Fusarium houttuyniae and F. liriopes spp. nov and are introduced with full descriptions, illustrations, and notes herein.

The green microalga Chlamydomonas reinhardtii holds substantial promise as a photosynthetic cell factory for sustainable bioproduction, yet strain-specific metabolic responses to environmental stress remain underexplored. Here, we reconstructed a genome-scale metabolic network (GSMN) of the light-tolerant strain C. reinhardtii CC-4414 by combining de novo genome assembly with integrative proteomics. The resulting model, designated iYH2021, comprises 2021 genes, 2601 reactions, and 2089 metabolites, representing the first genome-scale metabolic reconstruction reported for this strain. To elucidate light-driven metabolic remodeling, we integrated quantitative proteomic data from high-light (HL) and low-light (LL) conditions into the model using the iMAT algorithm and performed metabolic flux analysis (MFA). Because these context-specific networks integrate only proteomically supported reactions, flux predictions were evaluated using an objective function that captures photon-handling capacity, providing a direct readout of how the photosynthetic apparatus reallocates flux under each condition. Our predictions revealed that HL conditions significantly enhanced fluxes through photosynthetic electron transport, the Calvin–Benson cycle, glycolysis, and the tricarboxylic acid (TCA) cycle, indicating a reallocation of carbon and energy metabolism toward light-driven pathways, while amino acid metabolism showed a mixed pattern of change. In contrast, LL conditions induced a marked upregulation of purine metabolism, suggesting accelerated nucleotide turnover as an adaptive response to light limitation. A complementary growth-rate analysis using the unconstrained network further indicated a higher maximum growth rate under HL than LL, consistent with the expected benefit of greater light availability. These condition-specific flux redistributions highlight the metabolic plasticity of C. reinhardtii CC-4414 and provide a systems-level understanding of how light intensity shapes carbon and energy allocation. The iYH2021 model thus offers a robust predictive platform for guiding metabolic engineering strategies aimed at optimizing the production of biofuels and high-value bioproducts in this industrially relevant microalga under stress conditions. These findings represent model-derived predictions and have not yet been experimentally validated. We emphasize that this predictive platform requires experimental validation before its use in guiding metabolic engineering decisions.