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PubMed2026

Algae-to-host horizontal gene transfer in Paramecium bursaria is associated with host adaptation during endosymbiosis.

Paramecium bursaria maintains a stable endosymbiosis with green algae, yet the evolutionary consequences of this association remain unclear. Here, we screened the host genome for algal-derived horizontally transferred genes (HTGs) using a lineage-aware workflow designed to detect horizontal gene transfer (HGT) between two defined lineages. We identified 16 candidate HTGs, including four putative newly transferred genes and 12 homologous transferred genes, most of which were functionally associated with redox homeostasis and metabolism. Five HTGs showed symbiosis-dependent expression. RNAi knockdown of GH32s and SATs reduced host proliferation, total cell area, and motility, while GH32s knockdown also reduced endosymbiont load. Duplication patterns suggest that most transfers may have occurred after the P. bursaria lineage diverged from the sampled Paramecium species but before its lineage-specific whole-genome duplication (WGD). The HTGs also showed host-associated shifts in GC content and gene length, while representative HTGs retained conserved domains and functional motifs. Together, our results support algae-to-host HGT in P. bursaria and suggest that some transferred genes may contribute to metabolic integration during endosymbiosis.

Gene Transfer, Horizontal↗

PubMed2026

Alginate-based edible coating incorporating green tea extract for preserving postharvest quality and safety of white mushrooms (Agaricus bisporus).

This study aimed to evaluate the effects of a sodium alginate based edible coating incorporated with green tea extract (GTE) (Camellia sinensis) on the postharvest quality attributes and antimicrobial activity against Listeria monocytogenes in white mushrooms during refrigerated storage. The phenolic profile of GTE was characterized, and its minimum inhibitory concentration (MIC) against L. monocytogenes (1.6 mg/mL) was determined. Sodium alginate coatings, with (ALG-GTE) or without GTE (ALG) at MIC (1.6 mg/mL), were characterized (functional groups, solubility in water, moisture, thickness, water contact angle and color) for their chemical and physical properties. The effects of ALG-GTE coatings on quality parameters (firmness, weight loss, color, pH, sugars and organic acids), enzymatic activity [polyphenol oxidase (PPO), peroxidase (POD) and pectin methylesterase (PME)], antimicrobial activity against L. monocytogenes (5 log CFU/g), and surface characteristics (3D optical profilometry) were assessed in white mushrooms (Agaricus bisporus) during refrigerated storage (8 days, 4 ± 1 °C, 90-95% RH). The ALG-GTE coatings preserved sugar composition, particularly rhamnose, reduced organic acids accumulation and delayed weight and firmness loss, reduced color changes, and decreased PME activity in coated white mushrooms. L. monocytogenes counts decreased by 1.4 log CFU/g after 1 day, and no viable cells were detected after 2 days (< 1.5 log CFU/g) in ALG-GTE coated white mushrooms. In addition, ALG-GTE coated white mushrooms exhibited smoother surfaces than uncoated samples. These findings highlight the potential of ALG-GTE coatings as a sustainable alternative capable of improving the microbiological safety and delaying the postharvest changes in fresh mushrooms.

Agaricus↗

PubMed2026

Genome-wide insights into the evolutionary and demographic history of the red alga Mazzaella laminarioides: Evidence for speciation with ancient migration along the southeast Pacific coast.

The mechanisms driving lineage divergence in red algae remain unexplored, despite the group's remarkable diversity and ancient evolutionary history. The red alga Mazzaella laminarioides, a Chilean intertidal species complex composed of three parapatric cryptic lineages (North, Center, South), offers a valuable system to evaluate these processes, as its life history combines severe dispersal limitation with a haploid-diploid cycle that may influence the emergence of reproductive barriers. We reconstructed its evolutionary history using whole-genome sequencing and nuclear genome assembly of representative individuals from each lineage. Phylogenomic analyses based on 1,507 single-copy orthologs recovered three deeply divergent lineages with limited nuclear discordance consistent with incomplete lineage sorting. For both splits, demographic modelling was most consistent with an Ancient Migration scenario, although support over strict isolation was moderate, suggesting that divergence may have begun with low asymmetric ancestral gene flow followed by subsequent loss of connectivity, demographic bottlenecks, and later population expansion. Coding sequence analyses revealed lineage-specific dN/dS heterogeneity; only one South-lineage locus passed FDR correction (metaxin-1, mitochondrial protein import), with two further South-lineage candidates in chlorophyll and heme biosynthesis falling below the FDR threshold. Together, these signals suggest that divergent selective pressures on energy acquisition may have contributed to divergence at the southern end of the distribution. These results add to the small but growing body of whole-genome data for red algae and, alongside recent macroalgal studies, suggest that ancestral connectivity could be a recurrent feature of lineage divergence even in marine organisms with extremely restricted dispersal.

Rhodophyta↗

PubMed2026

Innovation-related perception as a key driver of alternative protein acceptance: evidence from an early-stage model for cultivated meat and algae-/microalgae-based alternative protein products in Italy.

Alternative proteins are increasingly considered part of the transition toward more sustainable food systems, yet their diffusion depends critically on consumer acceptance. This study investigates the early-stage acceptance of two alternative protein categories in Italy-cultivated meat and algae-/microalgae-based alternative protein products. Focusing on the first three phases of acceptance, the analysis examines how innovation-related perception (IRP) shapes consumer perceived value (CPV), consumer perceived risk (CPR), and subsequent affective (AFF), cognitive (COG), and conative (CON) responses. Data were collected through an online survey administered to 238 Italian respondents and analysed using partial least squares structural equation modelling (PLS-SEM). The results show that IRP is the main upstream driver of early-stage acceptance in both product domains: more favourable perceptions strongly increase perceived value and reduce perceived risk. In turn, CPV exerts a much stronger influence than CPR on both affective and cognitive attitudes. A tentative cross-model comparison suggests only a descriptive variation in the final transition toward conative acceptance: affective and cognitive responses were both significant in the two models, with a relatively larger affective coefficient for cultivated meat and more balanced coefficients for algae-/microalgae-based products. Overall, the findings support a process-based interpretation of alternative protein acceptance and highlight the central role of innovation-related perception in shaping early consumer responses. These results provide relevant implications for communication strategies, product positioning, and policy actions aimed at improving the acceptability of alternative proteins in food cultures characterised by strong culinary traditions.

Italy↗

PubMed2026

Phylogenomics and female reproductive morphology reframe the classification of the Halymeniales (Rhodophyta).

The red algal order Halymeniales (Rhodophyta) exhibits remarkable morphological and taxonomic diversity but its higher-level relationships remain poorly resolved. Here, we present a comprehensive phylogenomic analysis based on newly generated plastid (170 protein-coding genes), mitochondrial (23 genes), and complete nuclear ribosomal cistron sequences from 56 taxa, complemented with an expanded rbcL dataset encompassing 334 sequences. Our results provide a robust phylogenomic framework for the Halymeniales, offering a taxonomic backbone for future systematic studies. The analyses consistently recover six early-diverging lineages (Acrodiscus, Isabbottia, Norrissia, Pachymenia, Zymurgia, and Tsengia) and two strongly supported larger clades (Halymenia s.l. and Grateloupia s.l.). While most small and recently described genera are monophyletic, several traditional genera (e.g., Halymenia, Cryptonemia, Grateloupia) are poly- or paraphyletic, requiring considerable taxonomic revision. At the family level, the data indicate that reinstatement of the Grateloupiaceae sensu Kim et al. (2021) would entail a revised circumscription of the Halymeniaceae and the recognition of at least five small families to accommodate the early-diverging lineages. Although such a revised classification would result in monophyletic families, it is not supported by morpho-anatomical characters. Instead, we propose a more stable two-family system, recognizing a broadly circumscribed Halymeniaceae that is sister to the Tsengiaceae. Female reproductive characters, particularly the structure of carpogonial and auxiliary cell ampullae, support this two-family system and further characterize many genus-level clades, although substantial convergence across lineages exists.

Phylogeny↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

Comparative effectiveness of torsemide vs furosemide in the management of heart failure patients: Win-ratio reanalysis of the TRANSFORM-HF trial.

BACKGROUND: Loop diuretics are widely used for managing congestion in patients with heart failure (HF). The TRANSFORM-HF trial is a multicenter randomized study that enrolled heart failure patients, comparing a strategy of torsemide vs furosemide. The time-to-event analysis demonstrated neutral effects on all-cause death at 30 months and the composite of all-cause death and first rehospitalization at 12 months. We evaluated whether a hierarchical win-ratio (WR) framework integrating mortality, recurrent hospitalization, and patient-reported health status provides additional interpretive insight. METHODS: This study is a secondary analysis of the pragmatic, multicenter, open-label, randomized TRANSFORM-HF trial, conducted across 60 US hospitals that randomized 2,859 patients hospitalized with HF to torsemide or furosemide. The primary 12-month hierarchical composite outcome was defined as (1) all-cause mortality, (2) recurrent all-cause hospitalizations, and (3) lack of improvement in the Kansas City Cardiomyopathy Questionnaire Clinical Summary Score (KCCQ-CSS). The primary statistical method was a WR analysis adjusting covariates via inverse probability weighting. Subgroup analyses evaluated potential heterogeneity across patient demographics and clinical characteristics. RESULTS: In the primary 12-month intention-to-treat analysis, the adjusted WR was 1.07 (95% CI, 0.98-1.16; P = .13), indicating no significant difference between torsemide and furosemide. A supplementary 30-month analysis with extended mortality follow-up yielded a similar estimate (adjusted WR, 1.06; 95% CI, 0.98-1.16; P = .14); hospitalization and KCCQ-CSS components were assessed through 12 months. As-treated sensitivity analyses were consistent with the neutral primary findings. Exploratory subgroup analyses were not adjusted for multiplicity and should be considered hypothesis-generating. CONCLUSIONS: The overall WR comparison between torsemide and furosemide showed no statistically significant difference in the primary 12-month analysis. The WR framework provided an interpretive decomposition across outcome domains but did not establish superiority of either loop diuretic strategy. All findings should be considered exploratory. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03296813, https://clinicaltrials.gov/study/NCT03296813.

Aged↗

PubMed2026

Integrated assessment of biocontrol potential and genome analysis of endophytic Bacillus velezensis MGL-B1 against mango stem-end rot.

Mango stem-end rot is a globally significant postharvest disease that severely threatens the mango industry, primarily caused by Botryosphaeria dothidea. However, information on biocontrol agents targeting this pathogen in mango remains limited. In this study, we isolated and identified a strain of Bacillus velezensis MGL-B1 from mango leaf tissues for the first time, which exhibited broad-spectrum antifungal activity. Both in vitro and in vivo assays demonstrated that MGL-B1 effectively inhibited the growth of B. dothidea, with an in vivo biocontrol efficacy reaching 83.72 ± 5.10%, comparable to that of the commonly used chemical fungicide thiabendazole. Further mechanistic analysis revealed that MGL-B1 acts by directly disrupting the integrity of the pathogen's mycelial cell membrane. In addition, its released volatile organic compounds (VOCs) also displayed significant antifungal activity, with components such as 2-nonanone, 2-nonanol, and phenylethyl alcohol being confirmed to exert antifungal effects in in vitro fumigation assays. qPCR analysis showed that MGL-B1 treatment significantly upregulated the transcriptional levels of genes involved in plant-pathogen interaction, phenylpropanoid biosynthesis, and antioxidant defense pathways in mango fruits, with upregulation folds of 16.32, 37.19, and 75.93, respectively; meanwhile, the expression of browning-related genes such as polyphenol oxidase (PPO) was markedly suppressed. Whole-genome sequencing further revealed 14 biosynthetic gene clusters for antimicrobial compounds, including five unknown gene clusters. Collectively, B. velezensis MGL-B1 represents a promising biocandidate strain with multiple antifungal mechanisms and excellent control efficacy, providing a valuable resource for green and sustainable management of mango diseases.

Mangifera↗