Euglena gracilis is a metabolically versatile microalga capable of thriving under photoautotrophic (light, no ethanol), mixotrophic (light with 1% v/v ethanol), and heterotrophic (dark with 1% v/v ethanol) conditions. Here, we applied untargeted LC-MS metabolomics (Agilent 1290 LC, 6545XT QTOF-MS; Agilent Technologies, Santa Clara, California, USA) to investigate its trophic-mode-dependent metabolic adaptations and assess its biotechnological potential. Metabolites were separated on a C18 column and analyzed in both positive and negative ion modes. Multivariate analyses (PCA and sPLS-DA) revealed clear and reproducible metabolic separations among growth modes (p < 0.001). Photoautotrophic cultures were enriched in phenolic acids, flavonoids, and lipid classes associated with oxidative stress protection. Mixotrophy induced a broader spectrum of upregulated metabolite classes, including saccharolipids, macrolactams, and triterpenoids, reflecting a hybrid metabolism combining photosynthesis and ethanol utilization. Heterotrophic cultures showed elevated levels of polyamines and amino acids (e.g., putrescine, proline), indicative of redox regulation and stress adaptation in dark, ethanol-rich conditions. Class-level comparisons identified distinct and shared metabolite categories, with photoautotrophy favoring antioxidant biosynthesis and mixotrophy supporting metabolic diversity. These findings provide metabolite-level insights into the extraordinary plasticity of E. gracilis and offer a framework for optimizing cultivation strategies to enhance the targeted production of high-value bioproducts.

Metabolic modelling approaches have become the powerful tools in modern biology. These mathematical models are widely used to predict metabolic phenotypes of the organisms or communities of interest, and to identify metabolic targets in metabolic engineering. Apart from a broad range of industrial applications, the possibility of using metabolic modelling in the contexts of astrobiology are poorly explored. In this mini‐review, we consolidated the concepts and related applications of applying metabolic modelling in studying organisms in space‐related environments, specifically the extremophilic microbes. We recapitulated the current state of the art in metabolic modelling approaches and their advantages in the astrobiological context. Our review encompassed the applications of metabolic modelling in the theoretical investigation of the origin of life within prebiotic environments, as well as the compilation of existing uses of genome‐scale metabolic models of extremophiles. Furthermore, we emphasize the current challenges associated with applying this technique in extreme environments, and conclude this review by discussing the potential implementation of metabolic models to explore theoretically optimal metabolic networks under various space conditions. Through this mini‐review, our aim is to highlight the potential of metabolic modelling in advancing the study of astrobiology.

Bees play a crucial role as pollinators, contributing significantly to ecosystems. However, the honeybee population faces challenges such as global warming, pesticide use, and pathogenic microorganisms. Promoting bee growth using several approaches is therefore crucial for maintaining their roles. To this end, the bacterial microbiota is well-known for its native role in supporting bee growth in several respects. Maximizing the capabilities of these microorganisms holds the theoretical potential to promote the growth of bees. Recent advancements have made it feasible to achieve this enhancement through the application of genetic engineering. In this review, we present the roles of gut symbionts in promoting bee growth and collectively summarize the engineering approaches that would be needed for future applications. Particularly, as the engineering of bee gut symbionts has not been advanced, the dominant gut symbiotic bacteria Snodgrassella alvi and Gilliamella apicola are the main focus of the paper, along with other dominant species. Moreover, we propose engineering strategies that will allow for the improvement in bee growth with listed gene targets for modification to further encourage the use of engineered gut symbionts to promote bee growth.

Acute PM2.5 exposure has been implicated in lung cancer progression, yet its impact on genetically distinct NSCLC cells remains underexplored. This study investigates how mutation-specific transcriptional responses influence susceptibility to PM2.5-induced oncogenic alterations, focusing on A549 and NCI-H1975 cells. This provides preliminary insight into the transcriptomic effects of acute PM2.5 exposure in NSCLC cells with distinct oncogenic mutations (A549 and NCI-H1975), serving as a guide for understanding mutation-specific responses to environmental stress. Cells were exposed to PM2.5 (200 µg/mL, 24 h), followed by RNA sequencing and analysis. Gene ontology and pathway enrichment analyses were conducted to identify key molecular alterations associated with tumour progression. NCI-H1975 cells exhibited a stronger transcriptional response, with a higher fold change in differentially expressed genes (DEGs), indicating greater PM2.5 susceptibility. Upregulated genes were linked to oxidative stress, carcinogen activation, metabolic reprogramming, and therapy resistance, reinforcing tumour survival under PM2.5 stress. Conversely, the downregulation of tumour suppressor genes suggests immune suppression and potential immunotherapy resistance. This study reveals that acute PM2.5 exposure induces mutation-specific transcriptomic alterations in NSCLC, with EGFR-mutant cells exhibiting heightened oxidative stress, metabolic shifts, and immune evasion. The upregulation of key genes highlights the profound molecular impact of short-term exposure, paving the way for future studies on pollution-driven oncogenic mechanisms and resistance pathways.

This study examines the physicochemical and biological changes in meads produced from five honey types sourced from the Mekong region: Tree Marigold (Tithonia diversifolia, Myanmar), Coffee (Coffea canephora, Vietnam), Kapok (Ceiba pentandra, Cambodia), Rubber (Hevea brasiliensis, China), and Mixed Floral (Thailand). Honey musts were fermented with Saccharomyces cerevisiae at 25 °C for two weeks. After fermentation, meads exhibited lighter coloration, a stable pH (3.5–4.5), and varying bioactivities. All meads showed antimicrobial activity against Escherichia coli, while activity against Staphylococcus aureus and Klebsiella pneumoniae varied by honey source and depended on fermentation. Antioxidant activity ranged from 19.25 to 68.11% inhibition, and peaked in Tree Marigold honey after fermentation. Total phenolic and flavonoid contents fluctuated, with Mixed Floral mead showing the highest post-fermentation phenolic levels. The results of a sensory analysis ranked Tree Marigold mead the highest across taste, mouthfeel, aftertaste, and overall preference. These findings underscore the influence of honey origin and fermentation on the physicochemical, antimicrobial, and sensory properties of mead.

Fine particulate matter (PM2.5) is a major air pollutant linked to lung cancer progression. In Southeast Asia, seasonal smoke-haze produces biomass-derived PM2.5, yet its acute effects on genetically diverse lung tumours remain unclear. We investigate how Chiang Mai haze-derived PM2.5 impacts oxidative stress and gene expression in three non-small-cell lung cancer (NSCLC) cell lines: A549 (KRAS-mutant), NCI-H1975 (EGFR-mutant), and NCI-H460 (KRAS/PIK3CA-mutant). Cells were exposed to PM2.5 (0–200 µg/mL) and assessed for viability (MTT), reactive oxygen species (ROS; H₂O₂, •OH) and malondialdehyde (MDA) levels, mitochondrial-associated fluorescence, and whole-transcriptome responses. Acute exposure caused dose- and time-dependent viability loss, with A549 and NCI-H1975 more sensitive than NCI-H460. ROS profiling normalized to viable cells revealed genotype-specific oxidative patterns: cumulative increases in A549, sharp reversible spikes in NCI-H1975, and modest changes in NCI-H460. MitoTracker intensity trended downward without significance, with subtle fluorescence changes and particulate uptake. RNA-seq identified robust induction of xenobiotic metabolism (CYP1A1, CYP1B1), oxidative/metabolic stress mediators (GDF15, TIPARP), and tumour-associated genes (FOSB, VGF), alongside repression of tumour suppressors (FAT1, LINC00472). Pathway enrichment analyses highlighted oxidative stress, IL-17, NF-κB, and immune checkpoint signaling. Together, biomass haze-derived PM2.5 from Northern Thailand drives genotype-dependent oxidative stress and transcriptional remodeling in NSCLC cells.