Gapped BLAST and PSI-BLAST: a new generation of protein database search programs

Genome-wide identification and analysis of the NF-Y transcription factor family reveal its potential roles in tobacco (Nicotiana tabacum L.)

Nuclear Factor Y (NF-Y) represents a group of transcription factors commonly present in higher eukaryotes, typically consisting of three subunits: NF-YA, NF-YB, and NF-YC. They play crucial roles in the embryonic development, photosynthesis, flowering, abiotic stress responses, and other essential processes in plants. To better understand the genome-wide NF-Y domain-containing proteins, the protein physicochemical properties, chromosomal localization, synteny, phylogenetic relationships, genomic structure, promoter cis-elements, and protein interaction network of NtNF-Ys in tobacco (Nicotiana tabacum L.) were systematically analyzed. In this study, we identified 58 NtNF-Ys in tobacco, respectively, and divided into three subfamilies corresponding to their phylogenetic relationships. Their tissue specificity and expression pattern analyses for leaf development, drought and saline-alkali stress, and ABA response were carried out using RNA-seq or qRT-PCR. These findings illuminate the role of NtNF-Ys in regulating plant leaf development, drought and saline-alkali stress tolerance, and ABA response. This study offers new insights to enhance our understanding of the roles of NtNF-Ys and identify potential genes involved in leaf development, as well as drought and saline-alkali stress tolerance of plants.

Protein targeting to Starch 2 and the plastidial phosphorylase 1 revealed protein-protein interactions with photosynthesis proteins in yeast two-hybrid screenings

Starch metabolism in plants involves a complex network of interacting proteins that work together to ensure the efficient synthesis and degradation of starch. These interactions are crucial for regulating the balance between energy storage and release, adapting to the plant's developmental stage and environmental conditions. Several studies have been performed to investigate protein-protein interactions (PPIs) in starch metabolism complexes, yet it remains impossible to unveil all of the PPIs in this highly regulated process. This study uses yeast-two-hybrid (Y2H) screening against the Arabidopsis leaf cDNA library to explore PPIs, focusing on the starch-granule-initiating protein named Protein Targeting to Starch 2 (PTST2, At1g27070) and the protein involved in starch and maltodextrin metabolism, namely, plastidial phosphorylase 1 (PHS1, EC 2.4.1.1). More than 100 positive interactions were sequenced, and we found chloroplastidial proteins to be putative interacting partners of PTST2 and PHS1. Among them, photosynthetic proteins were discovered. These novel interactions could reveal new roles of PTST2 and PHS1 in the connection between starch metabolism and photosynthesis. This dynamic interplay between starch metabolism and other chloroplast functions highlights the importance of starch as both an energy reservoir and a regulatory component in the broader context of plant physiology and adaptation.

Pseudomonas syringae exacerbates apple replant disease caused by Fusarium

Apple replant disease (ARD) causes significant economic losses globally, including in China. Analyzing the causes of this replant disease from the perspective of rhizosphere microecology is therefore essential. In this study, we examined rhizosphere soils from apple trees subjected to continuous cropping. The mechanisms underlying ARD were elucidated through high-throughput sequencing of the soil microbiome, co-occurrence network analysis using NetShift, and correlation analyses. Core bacterial microbes were isolated, and their roles in altering the microecological environment were verified through reinoculation experiments. The results indicated that the disease indices for apple seedlings cultivated increased in continuously cropped soils. Bacterial diversity decreased in continuously cropped apple orchards for 10 years (R10) and 15 years (R15), but the relative abundance of Pseudomonas increased. In contrast, fungal diversity increased, with the relative abundance of Fusarium also increasing. As a dominant genus, Pseudomonas exhibited significant network variation after 10 years of consecutive cultivation, suggesting that this microorganism may play a key role in the occurrence of ARD. Moreover, the correlation analysis revealed, for the first time, that Pseudomonas is negatively correlated with bacterial diversity but positively correlated with the relative abundance of Fusarium, indicating a close relationship between Pseudomonas and Fusarium in continuously cropped soil. Four key Pseudomonas amplicon sequence variants (ASVs) strains were isolated from the continuously cropped rhizosphere soil of apple trees, and reinoculation experiments verified that introducing Pseudomonas exacerbated the occurrence of replant diseases in both strawberry and apple, with significantly higher disease indices compared to single Fusarium inoculation. The findings of this study provide new and timely insights into the mechanism underlying the occurrence of ARD.

Genomic analysis and metabolic pathway mining of Phallus cremeo-ochraceus

Phallus cremeo-ochraceus is a nutritious edible mushroom. In this study, after tissue isolation, 33 strains were obtained, among which one strain PC7 with rapid mycelial growth and stable passage was obtained. Here, after quality control and assembly, a sequence of 410,647,36 bp was obtained, with 20,218 contigs. 23,184 genes were predicted, 8,092 were repetitive sequences, and 165 were non-coding RNA (ncRNA), which was obtained by the Illumina platform. NCBI Blast+ was used to compare the protein sequences of the genes with several databases, such as NR, KOG, GO, KEGG, CAzy, etc. The NR database annotated 18,159 genes, KOG annotated 6752 genes, GO annotated 5872 genes, and KEGG annotated 3820 genes. Exploration of the terpenoid synthesis pathway of strain PC7 by KEGG, the results revealed that the genome of PC7 has a more complete metabolic pathway regarding terpenoid synthesis. The analysis of amino acid metabolic pathways shows that Phallus cremeo-ochraceus contains 18 genes related to amino acid metabolic pathways. Combined with carbohydrate enzyme annotation and KEGG annotation, the genes related to carbon source, nitrogen source, sulfur source and growth factor of Phallus cremeo-ochraceus were analyzed, which enriched the related genomic research of Phallus cremeo-ochraceus.

Lysosomal TPC2 channels disrupt Ca2+ entry and dopaminergic function in models of LRRK2-Parkinson's disease

Parkinson's disease results from degeneration of dopaminergic neurons in the midbrain, but the underlying mechanisms are unclear. Here, we identify novel crosstalk between depolarization-induced entry of Ca2+ and lysosomal cation release in maintaining dopaminergic neuronal function. The common disease-causing G2019S mutation in LRRK2 selectively exaggerated Ca2+ entry in vitro. Chemical and molecular strategies inhibiting the lysosomal ion channel TPC2 reversed this. Using Drosophila, which lack TPCs, we show that the expression of human TPC2 phenocopied LRRK2 G2019S in perturbing dopaminergic-dependent vision and movement in vivo. Mechanistically, dysfunction required an intact pore, correct subcellular targeting and Rab interactivity of TPC2. Reducing Ca2+ permeability with a novel biased TPC2 agonist corrected deviant Ca2+ entry and behavioral defects. Thus, both inhibition and select activation of TPC2 are beneficial. Functional coupling between lysosomal cation release and Ca2+ influx emerges as a potential druggable node in Parkinson's disease.

Unearthing limestone fungal diversity: Description of seven novel species from Portugal

Stone-built heritages are found worldwide, and despite stony surfaces being considered a stressful environment with challenging conditions to overcome, research has demonstrated that it can support diverse fungal communities, fostering a unique array of peculiar yet crucial species. These species exhibit a dual nature, being both foe and friend. While these fungi play a considerable role in the deterioration of cultural heritage, their mechanisms of adaptation to unfavourable environments hold great promise for biotechnology. Despite their importance, there is limited information available about these stone dwellers in Portugal. During an experimental survey aimed at isolating fungal species thriving in a deteriorated limestone funerary art piece at the Lemos Pantheon, a national monument located in Águeda, Portugal, several fungal specimens were isolated that could not be identified as any currently known species. Through morphological characteristics and multilocus phylogenetic analyses, seven new species (Aspergillus albicolor sp. nov., Banksiophoma dissensa sp. nov., Knufia lusitanica sp. nov., Microascus lausatensis sp. nov., Neodevriesia saximollicula sp. nov., Paramicrodochium filiforme sp. nov. and Talaromyces benedictus sp. nov.) are here proposed, illustrated, and compared to closely related species. These newly discovered fungal taxa form distinct lineages independent of other previously described species and are classified into seven families across six orders within the phylum Ascomycota. This paper also provides additional evidence that stone heritages harbour a diverse range of new species, deserving additional focus in the future. Citation: Paiva DS, Fernandes L, Pereira E, Mesquita N, Tiago I, Trovão J, Portugal A (2025). Unearthing limestone fungal diversity: Description of seven novel species from Portugal Fungal Systematics and Evolution 15: 47-77. doi: 10.3114/fuse.2025.15.02.

Mixed, not stirred: Genomic data confirm the first case of interspecific hybridization in planarian triclads (Platyhelminthes: Tricladida) and raise questions about a possibly novel form of hybrid speciation

Speciation is a complex process where many evolutionary forces interplay. The Mediterranean is acknowledged as one of the most relevant biodiverse areas in the Palearctic region and researchers have long studied the species inhabiting it to pursue the goals of evolutionary biology. Here, we study a complex of freshwater flatworm species of the genus Dugesia from Corsica and Sardinia using restriction site-associated DNA sequencing (specifically, 3RAD) data to unravel their evolutionary history and tackle the processes driving it. We assess the phylogenetic relationships and population structure within the group and evaluate new species boundaries using multispecies coalescent approaches. Furthermore, we offer insights into the environmental niche model of the group and use said model to guide our sampling efforts and collect and present molecular evidence for the first time of Dugesia leporii specimens, endemic from Sardinia last spotted in 1999. Our results indicate that paleoclimatic conditions rather than microplate tectonic dynamics were likely an important driver of diversification for the Corso-Sardinian group. Furthermore, our results warrant the taxonomic re-evaluation of the group as eight primary species candidates are established based on molecular data. Our study also reveals the first case of interspecific natural hybridization reported in Dugesiidae and, to our knowledge, in Tricladida. Finally, we discuss how this hybridization might constitute a new form of hybrid speciation.

ProtCB-bind: Protein-carbohydrate binding site prediction using an ensemble of classifiers

Proteins and carbohydrates are fundamental biomolecules that play crucial roles in life processes. The interactions between these molecules are essential for various biological functions, including immune response, cell activation, and energy storage. Therefore, understanding and identifying protein-carbohydrate binding regions is of significant importance. In this study, we propose ProtCB-Bind, a computational model for predicting protein-carbohydrate interactions. ProtCB-Bind leverages an ensemble of machine learning classifiers and utilizes a common averaging approach to form predictions. The proposed model is trained using a combination of sequence-based and evolutionary-based features of protein sequences, as well as the physicochemical properties of amino acids. To enhance predictive performance, ProtCB-Bind incorporates features derived from recent advancements in transformer-based Natural Language Processing (NLP) for proteins. ProtCB-Bind was designed by systematically identifying the best combination of classifiers and features, and was evaluated using a state-of-the-art benchmark dataset. Its performance was compared against established predictors, including SPRINT-CBH, StackCB-Pred, and StackCB-Embed. ProtCB-Bind outperformed these state-of-the-art predictors, achieving an approximate 3 % improvement in overall performance on benchmark dataset. The sources code for ProtCB-Bind is available at https://github.com/Divnesh/ProtCB-Bind.

The food application of a novel Staphylococcus aureus bacteriophage vB_SA_STAP152 and its endolysin LysP152 with high enzymatic activity under cold temperature

Staphylococcus aureus, a foodborne bacterial pathogen, poses a serious challenge due to antibiotic resistance, highlighting the urgent need for effective and alternative antimicrobial agents. Undoubtedly, bacteriophages and bacteriophage-encoded antibacterial proteins have been considered effective biopreservatives. Herein, we report the isolation and characterization of a novel lytic bacteriophage, vB_SA_STAP152, along with its endolysin LysP152. Morphological and genomic analysis revealed that vB_SA_STAP152 could be considered as a new species in the Rosenblumvirus genus. Stability tests demonstrated that vB_SA_STAP152 can withstand a range of temperatures (∼65 °C) and pH values (4-11). Moreover, we successfully cloned and expressed the bacteriophage-encoded protein, endolysin LysP152, which exhibited optimal activity at temperatures between 4 and 35 °C and within a broad pH range (4-11). The antibacterial spectrum experiments revealed that phage vB_SA_STAP152 effectively targeted 76.15% of S. aureus strains across 14 different sequence types (STs), particularly including community-associated methicillin-resistant S. aureus (CA-MRSA) ST59. Furthermore, endolysin LysP152 demonstrated complete lysis all tested S. aureus strains spanning 17 STs. Subsequently, the efficacy of vB_SA_STAP152 and LysP152 against MRSA in pork was evaluated, revealing a significant reduction of bacterial counts by 4.27-4.42 log10 CFU/mL with phage vB_SA_STAP152 at room temperature and by 3.31 log10 CFU/mL with endolysin LysP152 at refrigerator temperature. Overall, the in-vitro studies and favorable physical and chemical properties suggested that phage vB_SA_STAP152 and endolysin LysP152 have the potential to be developed as antimicrobial agents against S. aureus in the food industry.

Effect of temperature on circadian clock functioning of trees in the context of global warming

Plant survival in a warmer world requires the timely adjustment of biological processes to cyclical changes in the new environment. Circadian oscillators have been proposed to contribute to thermal adaptation and plasticity. However, the influence of temperature on circadian clock performance and its impact on plant behaviour in natural ecosystems are not well-understood. We combined bioinformatics, molecular biology and ecophysiology to investigate the effects of increasing temperatures on the functioning of the circadian clock in two closely related tree species from Patagonian forests that constitute examples of adaptation to different thermal environments based on their altitudinal profiles. Nothofagus pumilio, the species from colder environments, showed a major rearrangement of its transcriptome and reduced ability to maintain rhythmicity at high temperatures compared with Nothofagus obliqua, which inhabits warmer zones. In altitude-swap experiments, N. pumilio, but not N. obliqua, showed limited oscillator function in warmer zones of the forest, and reduced survival and growth. Our findings show that interspecific differences in the influence of temperature on circadian clock performance are associated with preferred thermal niches, and to thermal plasticity of seedlings in natural environments, highlighting the potential role of a resonating oscillator in ecological adaptation to a warming environment.

The coevolutionary landscape of drug resistance in epidermal growth factor receptor: A cancer perspective

Epidermal growth factor receptor (EGFR), the first receptor tyrosine kinase, plays a critical role in neoplastic metastasis, angiogenesis, tumor invasion, and apoptosis, making it a prime target for treating non-small cell lung cancer (NSCLC). Although tyrosine kinase inhibitors (TKIs) have shown high efficacy and promise for cancer patients, resistance to these drugs often develops within a year due to alterations. The present study investigates the compensatory alterations in EGFR to understand the evolutionary process behind drug resistance. Our findings reveal that coevolutionary alterations expand the drug-binding pocket; leading to reduced drug efficacy and suggested that such changes significantly influence the structural adaptation of the EGFR against these drugs. Analysis such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), solvent accessible surface area (SASA), principal component analysis (PCA), and free energy landscape (FEL) demonstrated that structures of wild EGFR docked with gefitinib are more stable which suggests its susceptibility towards drug than coevolution dependent double mutant. The findings were supported by MM-GBSA binding affinity analysis. The insights from this study highlighted the evolution-induced structural changes which contributes to drug resistance in EGFR and may certainly aid in designing more effective drugs.

Predicting C- and S-linked Glycosylation sites from protein sequences using protein language models

Among various post-translational modifications (PTMs), predicting C-linked and S-linked glycosites is an essential task, yet experimental techniques such as Capillary Electrophoresis (CE), Enzymatic Deglycosylation, and Mass Spectrometry (MS) are expensive. Therefore, computational techniques are required to predict these glycosites. Here, different language model embeddings and sequential features were explored. Two separate feature selection methods: Recursive Feature Elimination (RFE) and Particle Swarm Optimization (PSO) were employed and utilized for identifying the optimal feature set. Cross-validation results were generated for choosing the final models. Three sampling strategies to handle imbalanced datasets were examined: Random undersampling, Synthetic Minority Over-sampling Technique (SMOTE) and Adaptive Synthetic Sampling Approach for Imbalanced Learning (ADASYN). In this study, two models: DeepCSEmbed-C and DeepCSEmbed-S are proposed for C-linked and S-linked glycosylation prediction respectively. DeepCSEmbed-C is a dual-branch deep learning model comprising a Feedforward Neural Network (FNN) branch and an Inception branch, coupled with a Random undersampling strategy. DeepCSEmbed-S is a Categorical Boosting (CAT) model with the SMOTE oversampling strategy. DeepCSEmbed-C outperformed available state-of-the-art (SOTA) methods, achieving 92.9% sensitivity, 95.1% F1-score and 90.6% MCC on the Independent dataset. Datasets and python scripts for training and testing the models are provided and made freely accessible at https://github.com/nafcoder/DeepCSEmbed.

A novel endo-1,3-fucanase in glycoside hydrolase family 187 provided a biotechnological tool for preparing sulfated fucan oligosaccharides

Sulfated fucan, an important marine polysaccharide frequently presented in echinoderms and brown algae, has gained growing attention owing to its various biological activities. Fucanases are essential tools for degrading sulfated fucan to produce corresponding oligosaccharides. In this context, an endo-1,3-fucanase (Fun187Al) belonging to the GH187 family was successfully expressed in Escherichia coli. Fun187Al showed the highest activity at 30-40 °C and pH 7.5. It hydrolyzed sulfated fucan in a random endo-acting pattern, and displayed a substrate specificity different from the endo-1,3-fucanases of other glycoside hydrolase family. Analyses of ultra-performance liquid chromatography coupled with high-resolution mass spectrometry revealed that tetrasaccharide with two sulfate groups (Fuc4S2), Fuc4S3, and Fuc4S4 were respectively the major components in the end products of Fun187Al against sulfated fucans from Acaudina molpadioides, Thelonota ananas, and Holothuria tubulosa. The capability of Fun187Al to produce oligosaccharides with different degrees of polymerization and sulfation patterns demonstrated that it could be regarded as a favorable tool for establishing the structure-activity relationships of sulfated fucan and its oligosaccharides.

Copepod phylogenomics supports Canuelloida as a valid order separate from Harpacticoida

Copepods are small crustaceans that are ubiquitous in aquatic environments. They are particularly abundant in marine and freshwater plankton, marine sediments, and as parasites or commensals of other aquatic organisms. Despite their abundance and importance, phylogenetic relationships among copepods are poorly resolved. The validity of higher-level taxa, including several orders, has continued to be controversial throughout the 21st century. This study has two main goals: first, to use phylogenomic data to assess relationships among the four major copepod orders: Calanoida, Cyclopoida, Harpacticoida, and Siphonostomatoida, which together include more than 98 % of copepod species diversity, and second, to test the validity of the recently proposed order Canuelloida. Towards these goals, we sampled 28 copepod transcriptomes and genomes spanning 20 families and 5 orders, including the first transcriptome of a representative of Canuelloida. We identified 2,527 single copy protein coding genes comprising 939,460 amino acid (aa) positions and 530,269 informative sites. All phylogenetic analyses support a monophyletic Podoplea (i.e., the superorder comprising all copepod orders except for Calanoida and Platycopioida) with Calanoida as its sister taxon. We find robust support across all methods for Canuelloida as a distinct order separate from the traditionally recognized Harpacticoida (Oligoarthra). Contrary to several recent studies of smaller sets of nuclear genes or mitochondrial genomes, we recover Cyclopoida and Harpacticoida as sister taxa and find that gene tree discordance analysis rejects the alternative topologies. Transcriptomic data are promising for resolving the backbone of the copepod phylogeny but collecting and sequencing the nearly 15,000 species of copepods, many of which are infrequently encountered and less than 1 mm in size, remains a major hurdle.

Transcriptional Reprogramming Deploys a Compartmentalized 'Timebomb' in Catharanthus roseus to Fend Off Chewing Herbivores

The evolutionary arms race between plants and insects has led to key adaptive innovations that drive diversification. Alkaloids are well-documented anti-herbivory compounds in plant chemical defences, but how these specialized metabolites are allocated to cope with both biotic and abiotic stresses concomitantly is largely unknown. To examine how plants prioritize their metabolic resources responding to herbivory and cold, we integrated dietary toxicity bioassay in insects with co-expression analysis, hierarchical clustering, promoter assay, and protein-protein interaction in plants. Catharanthus roseus, a medicinal plant known for its insecticidal property against chewing herbivores, produces two terpenoid indole alkaloid monomers, vindoline and catharanthine. Individually, they exhibited negligible toxicity against Manduca sexta, a chewing herbivore; their condensed product, anhydrovinblastine; however, was highly toxic. Such a unique insecticidal mode of action demonstrates that terpenoid indole alkaloid 'timebomb' can only be activated when the two spatially isolated monomeric precursors are dimerized by herbivory. Without initial selection pressure and apparent fitness costs, this adaptive chemical defence against herbivory is innovative and sustainable. The biosynthesis of insecticidal terpenoid indole alkaloids is induced by herbivory but suppressed by cold. Here, we identified a transcription factor, herbivore-induced vindoline-gene Expression (HIVE), that coordinates the production of terpenoid indole alkaloids in response to herbivory and cold stress. The HIVE-mediated transcriptional reprogramming allows this herbaceous perennial to allocate its metabolic resources for chemical defence at a normal temperature when herbivory pressure is high, but switches to cold tolerance under a cooler temperature when insect infestation is secondary.

Digestive System Development and Posterior Hox/Parahox Gene Expression During Larval Life and Metamorphosis of the Phoronid Phoronopsis harmeri

Phoronida is a small group of marine animals, most of which are characterized by a long larval period and complex metamorphosis. As a result of metamorphosis, their body changes so much that their true anterior and posterior ends are very close to each other, and the intestine becomes long and U-shaped. Using histology and electron microscopy, we have shown that the elongation and change in shape of the digestive tract that occurs during metamorphosis in Phoronopsis harmeri larvae is accompanied by the formation of new parts and changes in ultrastructure. At the same time, our in situ hybridization data suggest that the posterior markers Cdx and Post2 are expressed in posterior tissues at larval stages, during metamorphosis, and in juveniles, and that changes in their expression correlate with remodeling of the posterior parts of the digestive tract. Our data may shed light on the evolution of body patterning in animals undergoing complex metamorphosis.

SUPERMAGO: Protein Function Prediction Based on Transformer Embeddings

Recent technological advancements have enabled the experimental determination of amino acid sequences for numerous proteins. However, analyzing protein functions, which is essential for understanding their roles within cells, remains a challenging task due to the associated costs and time constraints. To address this challenge, various computational approaches have been proposed to aid in the categorization of protein functions, mainly utilizing amino acid sequences. In this study, we introduce SUPERMAGO, a method that leverages amino acid sequences to predict protein functions. Our approach employs Transformer architectures, pre-trained on protein data, to extract features from the sequences. We use multilayer perceptrons for classification and a stacking neural network to aggregate the predictions, which significantly enhances the performance of our method. We also present SUPERMAGO+, an ensemble of SUPERMAGO and DIAMOND, based on neural networks that assign different weights to each term, offering a novel weighting mechanism compared with existing methods in the literature. Additionally, we introduce SUPERMAGO+Web, a web server-compatible version of SUPERMAGO+ designed to operate with reduced computational resources. Both SUPERMAGO and SUPERMAGO+ consistently outperformed state-of-the-art approaches in our evaluations, establishing them as leading methods for this task when considering only amino acid sequence information.

Genome-wide identification and expression analysis of the TCP transcription factor family and its response to abiotic stress in rapeseed (Brassica napus L.)

The study used 80 BnTCP genes (Brassica napus TCP genes) in rapeseed, which were identified and designated with nomenclature based on their chromosomal locations. A systematic analysis encompassed the evolutionary relationships, classifications, gene structures, motif compositions, chromosome localization, and gene replication events within these BnTCP genes. These 80 BnTCP proteins were categorized into three subfamilies, with the PCF subfamily showing significant expansion during evolution. Segmental duplications were identified as a major driver of TCP family amplification. To comprehensively assess the evolutionary relationships of the TCP family across diverse plant species, nine comparative genomic maps were constructed, elucidating homologous genes between B. napus and representative monocotyledonous and dicotyledonous plants. In the final phase of the study, the gene expression response characteristics of 15 selected BnTCP genes across various biological processes and stress responses were examined. Noteworthy candidates, including BnTCP28, BnTCP30, and BnTCP76, were identified as potentially crucial in tissue development and environmental stress responses.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-025-04273-x.

Precise metabolic modeling in post-omics era: accomplishments and perspectives

Microbes have been extensively utilized for their sustainable and scalable properties in synthesizing desired bio-products. However, insufficient knowledge about intracellular metabolism has impeded further microbial applications. The genome-scale metabolic models (GEMs) play a pivotal role in facilitating a global understanding of cellular metabolic mechanisms. These models enable rational modification by exploring metabolic pathways and predicting potential targets in microorganisms, enabling precise cell regulation without experimental costs. Nonetheless, simplified GEM only considers genome information and network stoichiometry while neglecting other important bio-information, such as enzyme functions, thermodynamic properties, and kinetic parameters. Consequently, uncertainties persist particularly when predicting microbial behaviors in complex and fluctuant systems. The advent of the omics era with its massive quantification of genes, proteins, and metabolites under various conditions has led to the flourishing of multi-constrained models and updated algorithms with improved predicting power and broadened dimension. Meanwhile, machine learning (ML) has demonstrated exceptional analytical and predictive capacities when applied to training sets of biological big data. Incorporating the discriminant strength of ML with GEM facilitates mechanistic modeling efficiency and improves predictive accuracy. This paper provides an overview of research innovations in the GEM, including multi-constrained modeling, analytical approaches, and the latest applications of ML, which may contribute comprehensive knowledge toward genetic refinement, strain development, and yield enhancement for a broad range of biomolecules.

Comparative analysis of STP6 and STP10 unravels molecular selectivity in sugar transport proteins

The distribution of sugars is crucial for plant energy, signaling, and defense mechanisms. Sugar Transport Proteins (STPs) are Sugar Porters (SPs) that mediate proton-driven cellular uptake of glucose. Some STPs also transport fructose, while others remain highly selective for only glucose. What determines this selectivity, allowing STPs to distinguish between compounds with highly similar chemical composition, remains unknown. Here, we present the structure of Arabidopsis thaliana STP6 in an inward-occluded conformational state with glucose bound and demonstrate its role as both a glucose and fructose transporter. We perform a comparative analysis of STP6 with the glucose-selective STP10 using in vivo and in vitro systems, demonstrating how different experimental setups strongly influence kinetic transport properties. We analyze the properties of the monosaccharide binding site and show that the position of a single methyl group in the binding site is sufficient to shuffle glucose and fructose specificity, providing detailed insights into the fine-tuned dynamics of affinity-induced specificity for sugar uptake. Altogether, these findings enhance our understanding of sugar selectivity in STPs and more broadly SP proteins.

Machine learning assessment of zoonotic potential in avian influenza viruses using PB2 segment

BACKGROUND

Influenza A virus (IAV) is a major global health threat, causing seasonal epidemics and occasional pandemics. Particularly, Influenza A viruses from avian species pose significant zoonotic threats, with PB2 adaptation serving as a critical first step in cross-species transmission. A comprehensive risk assessment framework based on PB2 sequences is necessary, which should encompass detailed analyses of specific residues and mutations while maintaining sufficient generality for application to non-PB2 segments.

RESULTS

In this study, we developed two complementary approaches: a regression-based model for accurately distinguishing among risk groups, and a SHAP-based risk assessment model for more meaningful risk analyses. For the regression-based risk models, we compared various methodologies, including tree ensemble methods, conventional regression models, and deep learning architectures. The optimized regression model, combined with SHAP value analysis, identified and ranked individual residues contributing to zoonotic potential. The SHAP-based risk model enabled intra-class analyses within the zoonotic risk assessment framework and quantified risk yields from specific mutations.

CONCLUSION

Experimental analyses demonstrated that the Random Forest regression model outperformed other models in most cases, and we validated the target value settings for risk regression through ablation studies. Our SHAP-based analysis identified key residues (271A, 627K, 591R, 588A, 292I, 684S, 684A, 81M, 199S, and 368Q) and mutations (T271A, Q368R/K, E627K, Q591R, A588T/I/V, and I292V/T) critical for zoonotic risk assessment. Using the SHAP-based risk assessment model, we found that influenza A viruses from Phasianidae showed elevated zoonotic risk scores compared to those from other avian species. Additionally, mutations I292V/T, Q368R, A588T/I, V598A/I/T, and E/V627K were identified as significant mutations in the Phasianidae. These PB2-focused quantitative methods provide a robust and generalizable framework for both rapid screening of avians' zoonotic potential and analytical quantification of risks associated with specific residues or mutations.

HPOseq: a deep ensemble model for predicting the protein-phenotype relationships based on protein sequences

BACKGROUND

Understanding the relationships between proteins and specific disease phenotypes contributes to the early detection of diseases and advances the development of personalized medicine. The acquisition of a large amount of proteomics data has facilitated this process. To improve discovery efficiency and reduce the time and financial costs associated with biological experiments, various computational methods have yielded promising results. However, the lack of rich and reliable protein-related information still presents challenges in this process.

RESULTS

In this paper, we propose an ensemble prediction model, named HPOseq, which predicts human protein-phenotype relationships based only on sequence information. HPOseq establishes two base models to achieve objectives. One directly extracts internal information from amino acid sequences as protein features to predict the associated phenotypes. The other builds a protein-protein network based on sequence similarity, extracting information between proteins for phenotype prediction. Ultimately, an ensemble module is employed to integrate the predictions from both base models, resulting in the final prediction.

CONCLUSION

The results of 5-fold cross-validation reveal that HPOseq outperforms seven baseline methods for predicting protein-phenotype relationships. Moreover, we conduct case studies from the points of phenotype annotation and protein analysis to verify the practical significance of HPOseq.

Mesoporous silica and vegetal extracts combined as sustainable stone heritage protection against biodeterioration

Since biodeterioration is considered one of the main issues related to the conservation of cultural heritage stone materials, an investigation was conducted into preventive sustainable antimicrobial alternatives to protect the stone surfaces. The study focuses on using MCM-41 mesoporous silica particles and vegetal extracts: the mesoporous materials act as nanocontainers encapsulating the extracts, which instead serve as green antimicrobic compounds to inhibit microbiological proliferation. In this way, the antimicrobial features of the extracts are sustained for a more extended period, reducing the evaporation rate and diminishing the quantity required; the amount necessary to achieve the minimum inhibitory concentration was reduced due to the decrease in evaporation. Moreover, since the MCM-41 can host a higher quantity of product than is necessary to exert the antimicrobial effect, the duration of activity is further prolonged, releasing the extracts over time. Specifically, the mesoporous particles were impregnated with the vegetal extract of limonene and the essential oils of thyme and oregano. In vitro microbiological tests were conducted on two fungi (i.e., Aspergillus tubingensis and Penicillium chrysogenum), taken as model microorganisms from real-case scenarios. A combination of mesoporous silica and vegetal extracts was employed to develop a protective coating for stone surfaces, and tests were conducted on marble mock-ups. The promising synergic results show that this system could be of interest for preventing microbiological growth over stone surfaces, avoiding a visible aesthetic impact, being non-toxic for the environment or the operator, and preventing the extract from evaporating but holding it for a controlled release. KEY POINTS: • Green antimicrobial system using porous silica as nanocontainer for plant extracts • Encapsulated vegetal extracts to inhibit microbial growth on stone surfaces • Stable and efficient coating against fungal species in vitro and on marble mock-up.

Interspecies relationships of natural amoebae and bacteria with C. elegans create environments propitious for multigenerational diapause

The molecular and physical communication within the microscopic world underpins the entire web of life as we know it. However, how organisms, such as bacteria, amoebae, and nematodes-all ubiquitous-interact to sustain their ecological niches, particularly how their associations generate and influence behavior, remains largely unknown. In this study, we developed a framework to examine long-term interactions between microbes and animals. From soil samples collected in a temperate, semi-arid climate, we isolated culturable bacterial genera, including Comamonas, Stenotrophomonas, Chryseobacterium, and Rhodococcus, as well as the amoeba, Tetramitus. This microbial ensemble was fed to the nematode C. elegans in experiments spanning over 20 nematode generations to assess developmental rate, dauer entry, fertility, and feeding behavior. Our findings reveal that microbes and nematodes create a stable environment where no species are exhausted, and where nematodes enter diapause after several generations. We have termed this phenomenon dauer formation on naturally derived ensembles (DaFNE). DaFNE occurs across a range of optimal temperatures, from 15°C to 25°C, and is dependent on the nematode's pheromone biosynthesis pathway. The phenomenon intensifies with each passing generation, exhibiting both strong intergenerational and transgenerational effects. Moreover, the RNA interference (RNAi) pathway-both systemic and cell-autonomous-is essential for initiating DaFNE, while heritable RNAi effectors are required for its transgenerational effects. These findings indicate that RNA-mediated communication plays a critical role in bacterially induced behaviors in natural environments.IMPORTANCEMicroscopic nematodes are the most abundant multicellular animals on Earth, which implies they have evolved highly successful relationships with their associated microbiota. However, little is known about how nematode behavior is influenced within complex ecosystems where multiple organisms interact. In this study, we used four bacteria and an amoeba from a natural ecosystem to explore behavioral responses in the nematode Caenorhabditis elegans over an 8 week period. The most striking finding was the nematodes' commitment to a form of hibernation known as diapause. We have termed this phenomenon dauer formation on naturally derived ensembles (DaFNE). Our results suggest that nematodes in nature may frequently enter hibernation as a result of communication with their microbial partners. DaFNE requires the production of nematode pheromones, as well as the RNA interference pathway, indicating that the RNA communication between nematodes and their microbiota may play a critical role. Interestingly, at higher temperatures, fewer animals are needed to trigger DaFNE, suggesting that a mild increase in temperature may promote diapause in natural environments without causing stress to the animals.

Chromosome-level genome assembly and annotation of Chinese herring (Ilisha elongata)

The Chinese herring (Ilisha elongata) is a commercially and scientifically significant fish species. In this study, we conducted high-precision whole-genome sequencing using two high-throughput platforms: second-generation MGI and third-generation PacBio. Hi-C technology assisted in assembling the contig sequences onto 24 chromosomes, resulting in a high-quality chromosome-level genome map with excellent continuity and coverage. The completed genome size was approximately 815 Mb, with a contig N50 of 4.82 Mb, scaffold N50 of 32.61 Mb, and a chromosome mounting rate of 95.32%. SNP and InDel purity rates were 0.003% and 0.012%, respectively, and the genome assembly completeness was 96.68%, assessed by BUSCO. Repetitive sequences were annotated via ab initio and homology predictions, identifying 295.7 Mb of repetitive sequences, constituting 35.08% of the genome. A total of 26,381 protein-coding genes were predicted, with 24,596 functionally annotated.

Manure input propagated antibiotic resistance genes and virulence factors in soils by regulating microbial carbon metabolism

Antibiotic resistance genes (ARGs) and virulence factors (VFs) in soils represent a significant threat to ecological security and human health. The carbon-rich soil formed by manure fertilization provides an energy source for soil microbes. However, we still know little about how microbial-dominated carbon metabolism affects ARGs and VFs proliferation in soils subjected to long-term fertilization and irrigation practices in wheat-maize system. Here, we investigated soil microbial carbon metabolism, ARGs and VFs distribution, and microbial composition in soils under 9-year of different fertilization and irrigation managements during wheat growing period. Results showed that manure (M) increased total abundance of soil ARGs by 5.9%-8.0% and 2.1%-4.8% and VFs by 5.4%-7.5% and 2.0%-4.9% compared to no fertilizer (CK) and NPK fertilizer (C), respectively, regardless of irrigation. M enriched more number of ARGs and VFs types, and increased abundance of host microbes involved in carbon fixation and carbon degradation, such as Streptomyces, Lysobacter and Agromyces. M increased abundance of carbohydrate-active enzymes (CAZymes) and carbon cycle functional pathways, as well as microbial carbon metabolism capacity. Partial least squares path modeling (PLS-PM) and correlation analysis showed that microbial diversity, CAZymes, carbon cycle functional pathways (particularly carbon fixation and degradation) and microbial carbon metabolism capacity of microbial community had direct positive effects on the proliferation and spread of ARGs and VFs. In conclusion, our results highlight the importance of microbial mediated carbon metabolism in driving the dissemination of ARGs and VFs in soils under long-term manure application.

Viral piracy of host RNA phosphatase DUSP11 by avipoxviruses

Proper recognition of viral pathogens is an essential part of the innate immune response. A common viral replicative intermediate and chemical signal that cells use to identify pathogens is the presence of a triphosphorylated 5' end (5'ppp) RNA, which activates the cytosolic RNA sensor RIG-I and initiates downstream antiviral signaling. While 5'pppRNA generated by viral RNA-dependent RNA polymerases (RdRps) can be a potent activator of the immune response, endogenous RNA polymerase III (RNAPIII) transcripts can retain the 5'ppp generated during transcription and induce a RIG-I-mediated immune response. We have previously shown that host RNA triphosphatase dual-specificity phosphatase 11 (DUSP11) can act on both host and viral RNAs, altering their levels and reducing their ability to induce RIG-I activation. Our previous work explored how experimentally altered DUSP11 activity can impact immune activation, prompting further exploration into natural contexts of altered DUSP11 activity. Here, we have identified viral DUSP11 homologs (vDUSP11s) present in some avipoxviruses. Consistent with the known functions of host DUSP11, we have shown that expression of vDUSP11s: 1) reduces levels of endogenous RNAPIII transcripts, 2) reduces a cell's sensitivity to 5'pppRNA-mediated immune activation, and 3) restores virus infection defects seen in the absence of DUSP11. Our results identify a context where DUSP11 activity has been co-opted by viruses to alter RNA metabolism and influence the outcome of infection.

Identification, growth characteristics, and genomic potential analysis of indole-3-acetic acid producing strain D1 in the rhizosphere of ancient tea forests

Chryseobacterium is one of the important beneficial microorganisms groups for protecting plant health. It has the functions of promoting host plant growth, stress resistance, inducing systemic resistance, and resisting pathogens, playing an important role in reducing soil biological barriers, and has broad application prospects. Therefore, screening for IAA producing Chryseobacterium and quickly understanding its genomic potential is of great significance in agricultural production. The unique ecological environment of wild ancient tea forests nurtures rhizosphere microbial resources with unique properties. This study identified the high-yielding indole-3-acetic acid (IAA) producing strain D1 from the rhizosphere of ancient tea forests as a new species of the Chryseobacterium genus, which is closely related to Chryseobacterium aureum and is recommended to be named Chryseobacterium tea sp. nov. Strain D1 exhibits excellent fermentation performance in producing IAA, achieving a maximum IAA yield of 149.24 mg/L after 60 h of fermentation in tryptophan medium. The optimal growth temperature for strain D1 is 25 °C, the optimal growth pH is 6, and the tolerance concentration to sodium chloride is 30 g/L. The genome of strain D1 contains abundant genetic resources for carbohydrate active enzymes, heavy metal resistance, secondary metabolite synthesis gene clusters, and plant pathogen resistance. This study enhances our understanding of the cultivation and genomic function of Chryseobacterium tea sp. nov, as well as the understanding of rhizosphere microorganisms in wild ancient tea forests. It also provides a theoretical basis for the development of Chryseobacterium tea sp. nov as functional fertilizers for crops.

Expanding kinetoplastid genome annotation through protein structure comparison

Kinetoplastids belong to the Discoba supergroup, an early divergent eukaryotic clade. Although the amount of genomic information on these parasites has grown substantially, assigning gene functions through traditional sequence-based homology methods remains challenging. Recently, significant advancements have been made in in-silico protein structure prediction and algorithms for rapid and precise large-scale protein structure comparisons. In this work, we developed a protein structure-based homology search pipeline (ASC, Annotation by Structural Comparisons) and applied it to transfer biological information to all kinetoplastid proteins available in TriTrypDB, the reference database for this lineage. Our pipeline enabled the assignment of structural similarity to a substantial portion of kinetoplastid proteins, improving current knowledge through annotation transfer. Additionally, we identified structural homologs for representatives of 6,700 uncharacterized proteins across 33 kinetoplastid species, proteins that could not be annotated using existing sequence-based tools and databases. As a result, this approach allowed us to infer potential biological information for a considerable number of kinetoplastid proteins. Among these, we identified structural homologs to ubiquitous eukaryotic proteins that are challenging to detect in kinetoplastid genomes through standard genome annotation pipelines. The results (KASC, Kinetoplastid Annotation by Structural Comparison) are openly accessible to the community at kasc.fcien.edu.uy through a user-friendly, gene-by-gene interface that enables visual inspection of the data.

Assessing Structural Classification Using AlphaFold2 Models Through ECOD-Based Comparative Analysis

Identifying homologous proteins is a fundamental task in structural bioinformatics. While AlphaFold2 has revolutionized protein structure prediction, the extent to which structure comparison of its models can reliably detect homologs remains unclear. In this study, we evaluate the feasibility of homology detection using AlphaFold2-predicted structures through structural comparisons. We considered the classification of the ECOD database for experimental structures as the correct standard and obtained their corresponding predicted models from AlphaFoldDB. To ensure blind assessment, we divided the structures into test and train sets according to their release date. Predicted and experimental 3D structures in the test and train sets were compared using 3D structure comparisons (MATRAS, Dali, and Foldseek) and sequence comparisons (BLAST and HHsearch). The results were evaluated based on the homology annotations in the ECOD database. For top-1 accuracy, the performance of structural comparisons was comparable to that of HHsearch. However, when considering metrics that included all structural pairs, including more remote homology, structural comparisons outperformed HHsearch. No significant differences were observed between comparisons of experimental versus experimental, predicted versus experimental, and predicted versus predicted structures with pLDDT (prediction confidence) values greater than 60. We also demonstrate that predicted protein structures, determined by NMR, had lower pLDDT values and contained fewer coils than their experimental counterparts. These findings highlight the potential of AlphaFold2 models in structural classification and suggest that 3D structural searches should be conducted not only against the PDB but also against AlphaFoldDB to identify more potential homologs.

Phylogenetic and ecological drivers of the avian lung mycobiome and its potentially pathogenic component

Vertebrate lungs contain diverse microbial communities, but little is known about the drivers of community composition or consequences for health. Microbiome assembly by processes such as dispersal, coevolution, and host-switching can be probed with comparative surveys; however, few studies exist for lung microbiomes, particularly for the fungal component, the mycobiome. Distinguishing among fungal taxa that are generalist or specialist symbionts, potential pathogens, or incidentally inhaled spores is urgent because of potential for emerging diseases. Here, we characterize the avian lung mycobiome and test the relative influences of environment, phylogeny, and functional traits. We used metabarcoding and culturing from 195 lung samples representing 32 bird species across 20 families. We identified 526 fungal taxa as estimated by distinct sequence types (zOTUs) including many opportunistic pathogens. These were predominantly from the phylum Ascomycota (79%) followed by Basidiomycota (16%) and Mucoromycota (5%). Yeast and yeast-like taxa (Malassezia, Filobasidium, Saccharomyces, Meyerozyma, and Aureobasidium) and filamentous fungi (Cladosporium, Alternaria, Neurospora, Fusarium, and Aspergillus) were abundant. Lung mycobiomes were strongly shaped by environmental exposure, and further modulated by host identity, traits, and phylogenetic affinities. Our results implicate migratory bird species as potential vectors for long-distance dispersal of opportunistically pathogenic fungi.

Identification of EppR, a Second Repressor of Error-Prone DNA Polymerase Genes in Acinetobacter baumannii

Acinetobacter baumannii is an opportunistic pathogen causing several infections that are increasingly difficult to treat due to its ability to rapidly gain antibiotic resistances. These resistances can arise due to mutations through the activity of error-prone DNA polymerases, such as DNA polymerase V (DNA Pol V) in response to DNA damage. The regulation of the DNA damage response (DDR) in A. baumannii is not completely understood; the regulation of genes encoding multiple copies of DNA Pol V is not fully characterized. Through genome-wide mutagenesis, we have identified a novel TetR-like family regulator of the umuDC and umuC genes, which we have named Error-prone polymerase regulator (EppR). We have found that EppR represses the expression of the genes encoding DNA Pol V and itself through direct binding to an EppR motif in their promoters. Lastly, we show that EppR also regulates UmuDAb, previously identified as a regulator of genes encoding DNA Pol V. These two gene products are functionally required to ensure regulation of the expression of the two umuDC, the two umuC genes as well as the regulators umuDAb and eppR genes. With these results, we propose a model in which multiple transcription factors regulate the expression of all these genes.

Fungal Infections Resulting From Prolonged Use of Personal Protective Equipment

This study is the first to investigate fungal infections resulting from prolonged use of personal protective equipment (PPE) among healthcare workers at Kütahya Health Sciences University Evliya Çelebi Training and Research Hospital, during the COVID-19 pandemic. The research aimed to isolate, molecularly type, and assess the antifungal susceptibility of superficial fungal infection agents associated with PPE use. Additionally, the relationship between these fungi and PPE use was evaluated through a questionnaire. Samples were collected from 100 healthcare workers experiencing skin issues. Among them, all N95/FFP2 mask users, 44.3% of glove users, 36.1% of surgical mask users, and 22.9% of hair cap users reported skin reactions, with acne (n = 34) being the most common. Identified fungal isolates included Trametes hirsuta, Penicillium chrysogenum, Aspergillus fumigatus, Rhodotorula sp., Candida sp., Pichia fermentans, and the dermatophyte Microsporum ferrugineum. Antifungal susceptibility tests revealed 47.6% resistance to fluconazole and 76.2% resistance to voriconazole (n = 16). This study provides the first institutional data on PPE-associated fungal infections and antifungal resistance in healthcare settings. These findings highlight the dermatological risks of prolonged PPE use. To mitigate these effects, healthcare institutions should prioritize high-quality materials, establish optimal usage guidelines, and provide continuous training on self-protection.

Identification of a conserved cryptic epitope with cross-immunoreactivity in outer membrane protein K (OmpK) from Vibrio species

Outer membrane protein K (OmpK) has been proven to be an ideal vaccine candidate for broad-spectrum cross-prevention against Vibriosis. However, due to the extensive biological and genetic diversity of Vibrio species, current OmpK subunit vaccines can only target different strains of the same bacterial species or closely related species and have difficulty providing promising cross-immunoprotection against more diverse Vibrio infections. In recent years, the development of epitope-focused vaccines has been described as the latest stage in the development of vaccine formulations, providing new ideas for the development of broad-spectrum Vibrio vaccines. Interestingly, a cryptic epitope (K7) was identified in OmpK from Vibrio species, which is itself immunogenic but is not involved in the immune response to intact OmpK. Epitope K7 is a 15-residue hairpin structure in OmpK predicted to contain a 6-residue extracellular turn region. Interestingly, unlike other highly variable extracellular long loops, epitope K7 is the only conserved extracellular short turn in OmpK, with a similarity of 33 % to 93 %. K7 homologous peptides stimulated the production of specific antibodies, confirming their high immunogenicity. Cross-immunoreactivity between K7 homologous and K7-induced antibodies was evaluated by peptide-based ELISA, western blot, and cell-based ELISA. Flow cytometry and immunofluorescence assay further confirmed that the native epitope K7 in OmpK is surface-exposed and therefore an extracellular target that binds to antibodies. Moreover, an antibody-dependent and complement-mediated serum bactericidal assay suggested that epitope K7-induced antibodies have vibriocidal activity. In conclusion, we identified a conserved cryptic epitope with cross-immunoreactivity in OmpK from Vibrio species. Our results suggest that epitope K7 could be an ideal candidate for the design of epitope-focused vaccines against diverse Vibrio infections.

Gut microbiota dysbiosis triggered by salinity stress enhances systemic inflammation in spotted scat (Scatophagus argus)

As an ecological disturbance, salinity changes substantially impact aquatic organism health. Gut microbiota plays a pivotal role in host health and exhibits heightened sensitivity to environmental salinity stress; however, the potential correlative mechanisms between gut microbiota dysbiosis triggered by salinity changes and host health remain unclear. The present study conducted a 4-week stress experiment to investigate the precise impact of gut microbiota on the inflammatory response in Scatophagus argus under different salinities (0 ‰ [hyposaline group, HO], 25 ‰ [control group, CT], and 40 ‰ [hypersaline group, HE]). Our results revealed that both HO and HE stress significantly changed the relative abundances of Gram-negative bacteria and the impairment of intestinal barrier function. Subsequently, the levels of lipopolysaccharide (LPS) in the serum exhibited a significant increase, and the expression levels of genes (tlrs, myd88, irak1, irak4, and traf6) involving TLRs/MyD88/NF-κB signaling pathway and pro-inflammatory cytokines (il-6, il-8, il-1β, and tnf-α) in the representative immune organs were significantly upregulated. Conversely, the abundance of the anti-inflammatory gene (tgf-β1) and its protein contents in serum were decreased. Transplantation of the gut microbiota from S. argus exposed to varying salinities into germ-free Oryzias latipes resulted in an enhanced inflammatory response. Our results suggested that both HO and HE stress increased the presence of Gram-negative bacteria and disrupted the intestinal barrier, leading to elevated serum LPS and subsequent systemic inflammation in fish. These findings provide innovative insights into the influence of salinity manipulation strategies on the health of aquatic organisms, contributing to the mariculture management in coastal areas.

Bacterial pathogen deploys the iminosugar glycosyrin to manipulate plant glycobiology

The extracellular space (apoplast) in plants is a key battleground during microbial infections. To avoid recognition, the bacterial model phytopathogen Pseudomonas syringae pv. tomato DC3000 produces glycosyrin. Glycosyrin inhibits the plant-secreted β-galactosidase BGAL1, which would otherwise initiate the release of immunogenic peptides from bacterial flagellin. Here, we report the structure, biosynthesis, and multifunctional roles of glycosyrin. High-resolution cryo-electron microscopy and chemical synthesis revealed that glycosyrin is an iminosugar with a five-membered pyrrolidine ring and a hydrated aldehyde that mimics monosaccharides. Glycosyrin biosynthesis was controlled by virulence regulators, and its production is common in bacteria and prevents flagellin recognition and alters the extracellular glycoproteome and metabolome of infected plants. These findings highlight a potentially wider role for glycobiology manipulation by plant pathogens across the plant kingdom.

Zygotic activation of transposable elements during zebrafish early embryogenesis

Although previous studies have shown that transposable elements (TEs) are conservatively activated to play key roles during early embryonic development, the details of zygotic TE activation (ZTA) remain poorly understood. Here, we employ long-read sequencing to precisely identify that only a small subset of TE loci are activated among numerous copies, allowing us to map their hierarchical transcriptional cascades at the single-locus and single-transcript level. Despite the heterogeneity of ZTA across family, subfamily, locus, and transcript levels, our findings reveal that ZTA follows a markedly different pattern from conventional zygotic gene activation (ZGA): ZTA occurs significantly later than ZGA and shows a pronounced bias for nuclear localization of TE transcripts. This study advances our understanding of TE activation by providing a high-resolution view of TE copies and creating a comprehensive catalog of thousands of previously unannotated transcripts and genes that are activated during early zebrafish embryogenesis. Among these genes, we highlight two that are essential for zebrafish development.

Complete genome sequence of Desulfovibrio sp. GTC20076 isolated from a clinical specimen in Japan

Desulfovibrio is a genus of sulfate-reducing, anaerobic bacteria ubiquitously present in the environment. Herein, we report the complete genome sequence of an isolate of a new Desulfovibrio species obtained from a human clinical specimen in Japan. The genome comprised a circular chromosome with a length of 3,213,183 bp.

A geranylgeranyl reductase homolog required for cholesterol production in Myxococcota

Myxococcota is a phylum of sterol-producing bacteria. They exhibit a clade depth for sterol biosynthesis unparalleled in the bacterial domain and produce sterols of a biosynthetic complexity that rivals eukaryotes. Additionally, the sterol biosynthesis pathways found in this phylum have been proposed as a potential source for sterol biosynthesis in the last eukaryotic common ancestor, lending evolutionary importance to our understanding of this pathway in Myxococcota. However, sterol production has only been characterized in a few species, and outstanding questions about the evolutionary history of this pathway remain. Here, we identify two myxobacteria, Minicystis rosea and Sandaracinus amylolyticus, capable of cholesterol biosynthesis. These two myxobacteria possess a cholesterol biosynthesis pathway that differs in both the ordering and enzymes involved in biosynthesis compared with Enhygromyxa salina, a myxobacterium previously demonstrated to produce cholesterol, as well as the canonical pathways found in eukaryotes. We characterize an alternative bacterial reductase responsible for performing C-24 reduction, further delineating bacterial cholesterol production from eukaryotes. Finally, we examine the distribution and phylogenetic relationships of sterol biosynthesis proteins across both cultured and uncultured Myxococcota species, providing evidence for multiple acquisition events and instances of both horizontal and vertical transfer at the family level. Altogether, this work further demonstrates the capacity of myxobacteria to synthesize eukaryotic sterols but with an underlying diversity in the biochemical reactions that govern sterol synthesis, suggesting a complex evolutionary history and refining our understanding of how myxobacterial cholesterol production relates to their eukaryotic counterparts.

IMPORTANCE

Sterols are essential and ubiquitous lipids in eukaryotes, but their significance in bacteria is less understood. Sterol production in Myxococcota, a phylum of developmentally complex predatory bacteria, has provided insight into novel sterol biochemistry and prompted discussion regarding the evolution of this pathway within both the eukaryotic and bacterial domains. Here, we characterize cholesterol biosynthesis in two myxobacteria, providing evidence for distinct pathway organization and identifying a unique protein responsible for C-24 reduction. We couple these results with the phylogenomic analysis of sterol biosynthesis within Myxococcota, revealing a complicated evolutionary history marked by vertical and horizontal transfer. This suggests a mosaic acquisition of this pathway in Myxococcota and highlights the complex role myxobacteria may have had in sterol transfer to eukaryotes.

Complete genome sequence of Planococcus koreensis isolated from soil in Fort Collins, Colorado

The complete genome of Planococcus koreensis was obtained using Nanopore MinION sequencing after isolation from soil in Colorado. The assembled genome contains one circular contig with 3,519,105 bp, 3,606 genes, 419 pseudogenes, and 47.62% guanine-cytosine content. This discovery provides a fully assembled P. koreensis genome available at the National Center for Biotechnology Information.

Biochemical and structural characterization of a family-9 glycoside hydrolase bioprospected from the termite Syntermes wheeleri gut bacteria metagenome

Glycosyl hydrolases (GH) are enzymes involved in the degradation of plant biomass. They are important for biorefineries that aim at the sustainable utilization of lignocellulosic residues to generate value-added products. The termite Syntermes wheeleri gut microbiota showed an abundance of bacteria from the phylum Firmicutes, a phylum with enzymes capable of breaking down cellulose and degrading lignin, facilitating the use of plant materials as a food source for termites. Using bioinformatics techniques, cellobiohydrolases were searched for in the gut metagenome of the termite Syntermes wheeleri, endemic to the Cerrado. After selecting sequences of the target enzymes, termite gut microbiome metatranscriptome data were used as the criteria to choose the GH9 enzyme sequence Exo8574. Here we present the biochemical and structural characterization of Exo8574, a GH9 enzyme that showed activity with the substrate p-nitrophenyl-D-cellobioside (pNPC), consistent with cellobiohydrolase activity. Bioinformatics tools were used to perform phylogeny studies of Exo8574 and to identify conserved families and domains. Exo8574 showed 48.8 % homology to a protein from a bacterium belonging to the phylum Firmicutes. The high-quality three-dimensional (3D) model of Exo8574 was obtained by protein structure prediction AlphaFold 2, a neural network-based method. After the heterologous expression of Exo8574 and its purification, biochemical experiments showed that the optimal activity of the enzyme was at a temperature of 55 ºC and pH 6.0, which was enhanced in the presence of metal ions, especially Fe2 +. The estimated kinetic parameters of Exo8574 using the synthetic substrate p-nithrophenyl-beta-D-cellobioside (pNPC) were: Vmax = 9.14 ± 0.2 x10-5 μmol/min and Km = 248.27 ± 26.35 μmol/L. The thermostability test showed a 50 % loss of activity after 1 h incubation at 55 °C. The secondary structure contents of Exo8574 evaluated by Circular Dichroism were pH dependent, with greater structuring of protein in β-antiparallel and α-helices at pH 6.0. The similarity between the CD results and the Ramachandran plot of the 3D model suggests that a reliable model has been obtained. Altogether, the results of the biochemical and structural characterization showed that Exo8574 is capable of acting on p-nithrophenyl-beta-D-cellobioside (pNPC), a substrate that mimics bonds cleaved by cellobiohydrolases. These findings have significant implications for advancing in the field of biomass conversion while also contributing to efforts aimed at overcoming challenges in developing more efficient cellulase cocktails.

Bioinformatics Analysis Identifies Sequence Determinants of Enzymatic Activity for the PHARC-Associated Lipase ABHD12

In humans, PHARC (polyneuropathy, hearing loss, ataxia, retinitis pigmentosa, and cataract) is an early onset autosomal recessive neurological disorder caused by deleterious mutations to ABHD12 (α/β-hydrolase domain protein # 12). Biochemically, ABHD12 functions as a lipase and catalyzes the hydrolysis of lysophosphatidylserine (lyso-PS) (lyso-PS lipase). By doing so, it controls the concentrations and signaling pathways regulated by this potent signaling lysophospholipid in the mammalian brain. While genetic mapping efforts have identified over 30 mutations in ABHD12 from human PHARC subjects, the biochemical activity of these pathogenic mutants remains unknown. To understand this, here, we performed an exhaustive bioinformatics survey and collated ABHD12 protein sequences from various organisms across evolution. Next, based on sequence alignments and structural modeling, we identified functionally relevant conserved residues in the ABHD12 protein sequence that are potentially important for its enzymatic activity. To validate these in silico findings, we generated numerous mutants of murine ABHD12, including those associated with human PHARC subjects, and assayed them for their enzymatic activity. Taken together, these complementary in silico and biochemical studies provide the first thorough sequence-function relationship for mammalian ABHD12, especially relevant in the context of PHARC. Finally, our evolutionary analysis identified CG15111 as an ABHD12 ortholog in the fruit fly (Drosophila melanogaster), and enzymatic assays indeed confirmed that recombinant CG15111 has robust lyso-PS lipase activity. Flies serve as an excellent animal system to model various human neurological diseases, and the identification of CG15111 as a Drosophila melanogaster ABHD12 ortholog opens new avenues to study PHARC in fly models.

Statistical factorial design for optimum reduction of tellurite and production of tellurium nanostructure by a novel strain Phytobacter diazotrophicus Te1

A tellurite-reducing isolate (Te1) was recovered from a soil sample receiving industrial effluents from Ismailia Canal, Egypt. The isolate exhibited dark black colonies when grown on solid medium containing potassium tellurite, which indicated the reduction of tellurite to black tellurium. The isolate was identified using 16S rRNA gene sequencing and was submitted to GenBank as Phytobacter diazotrophicus strain Te1 (PP724698). The tellurite reduction percentage was 96.5% ± 0.354%. Moreover, energy-dispersive X-ray (EDX) analysis confirmed the presence of tellurium nanostructure, with a 3.7 keV absorption peak along with phosphorus, sulfur, and oxygen, revealing a complex biogenic nature. Fourier-transform infrared (FTIR) spectroscopy identified distinct absorption peaks within the 400-4000 cm-1 range, corresponding to various vibrational modes of chemical bonds, including those of lipids, proteins, polysaccharides, and free radicals. X-ray diffraction (XRD) analysis highlighted the nanoscale crystalline structure of the material, with broad peaks confirming limited crystallite size and structural disorder, and revealed tellurium peaks on a hexagonal phase at 2-theta values of 27.36°, 38.19° and 40.20°. According to the results of the response optimizer and the subsequent validation experiments, complete reduction of tellurium was achieved at a medium pH of 6.8, incubation temperature of 33.5 °C, tellurite concentration of 1375 μM, and agitation speed of 110 rpm for 96 h. Black Te nanostructure was visible intracellularly and extracellularly upon examination using the transmission electron microscope. To the best of the authors' knowledge, this is the first report of tellurite reduction by Phytobacter diazotrophicus.

DeepMFFGO: A Protein Function Prediction Method for Large-Scale Multifeature Fusion

Protein functional studies are crucial in the fields of drug target discovery and drug design. However, the existing methods have significant bottlenecks in utilizing multisource data fusion and Gene Ontology (GO) hierarchy. To this end, this study innovatively proposes the DeepMFFGO model designed for protein function prediction under large-scale multifeature fusion. A fine-tuning strategy using intermediate-level feature selection is proposed to reduce redundancy in protein sequences and mitigate distortion of the top-level features. A hierarchical progressive fusion structure is designed to explore feature connections, optimize complementarity through dynamic weight allocation, and reduce redundant interference. On the CAFA3 data set, the Fmax values of the DeepMFFGO model on the MF, BP, and CC ontologies reach 0.702, 0.599, and 0.704, respectively, which are improved by 4.2%, 2.4%, and 0.07%, respectively, compared with state-of-the-art multisource methods.

Vesicular and non-vesicular extracellular small RNAs direct gene silencing in a plant-interacting bacterium

Extracellular plant small RNAs (sRNAs) and/or double-stranded RNA (dsRNA) precursors act as triggers of RNAi in interacting filamentous pathogens. However, whether any of these extracellular RNA species direct gene silencing in plant-interacting bacteria remains unknown. Here, we show that Arabidopsis transgenic plants expressing sRNAs directed against virulence factors of a Pseudomonas syringae strain, reduce its pathogenesis. This Antibacterial Gene Silencing (AGS) phenomenon is directed by Dicer-Like (DCL)-dependent antibacterial sRNAs, but not cognate dsRNA precursors. Three populations of active extracellular sRNAs were recovered in the apoplast of these transgenic plants. The first one is mainly non-vesicular and associated with proteins, whereas the second one is located inside Extracellular Vesicles (EVs). Intriguingly, the third population is unbound to proteins and in a dsRNA form, unraveling functional extracellular free sRNAs (efsRNAs). Both Arabidopsis transgene- and genome-derived efsRNAs were retrieved inside bacterial cells. Finally, we show that salicylic acid (SA) promotes AGS, and that a substantial set of endogenous efsRNAs exhibits predicted bacterial targets that are down-regulated by SA biogenesis and/or signaling during infection. This study thus unveils an unexpected AGS phenomenon, which may have wider implications in the understanding of how plants regulate microbial transcriptome, microbial community composition and genome evolution of associated bacteria.

Comparative genomics of Elusimicrobiaceae (phylum Elusimicrobiota) and description of the isolates Elusimicrobium simillimum sp. nov., Elusimicrobium posterum sp. nov., and Parelusimicrobium proximum gen. nov. sp. nov

The tree of life comprises many deep-branching lineages with no or only very few cultured representatives. One such lineage is the phylum Elusimicrobiota, which contains only two described species and whose biology has been only poorly explored. We isolated three new species from this phylum from the intestinal tracts of cockroaches. Like their closest relative, Elusimicrobium minutum, the only member of the family Elusimicrobiaceae described to date, they are small, pleomorphic gram-negative rods characterized by a distinct cell cycle, and like all ultramicrobacteria, they pass through a 0.22-μm filter membrane. Physiological characterization of all isolates revealed that they are obligately anaerobic fermenters that lack catalase and cytochrome c oxidase activities but can remove oxygen from their environment in a non-respiratory manner. Their substrate range is limited to a few hexoses, such as d-glucose, d-galactose, and N-acetyl-d-glucosamine, which are fermented to lactate, acetate, ethanol, and hydrogen as major products. Comparative genome analysis, which included more than 100 MAGs of uncultured lineages of Elusimicrobiaceae, revealed the underlying metabolic pathways and outlined a new phylogenomic framework of the family. Based on phylogenomic, physiological, and morphological evidence, we describe the new isolates as Parelusimicrobium proximum gen. nov., sp. nov., Elusimicrobium posterum sp. nov., and Elusimicrobium simillimum sp. nov. under the rules of ICNP. Based on high-quality genomes of all uncultured representatives, we propose a comprehensive taxonomy of all lineages in the family under the rules of SeqCode, including the new genera Avelusimicrobium, Proelusimicrobium, and the candidate genus "Pseudelusimicrobium".

Genome-wide identification and gene expression pattern analysis of the carotenoid cleavage oxygenase gene family in Fagopyrum tataricum

BACKGROUND

Carotenoid cleavage oxygenases (CCOs) convert carotenoids into volatile aromatic compounds implicated in plant growth and development. They affect the synthesis of hormones, including abscisic acid (ABA) and strigolactone (SL). However, the CCO family in Tartary buckwheat remains unelucidated.

RESULTS

We identified the FtCCO gene family based on Tartary buckwheat genomic data and analyzed the biological function of the FtCCO genes using bioinformatics methods and the expression pattern of the gene using fluorescence quantitative PCR. Three pairs of fragment duplication genes were found in FtCCOs, and the motifs were highly conserved within the same subfamily. FtCCO genes are closely related to the dicotyledonous Arabidopsis thaliana, which has the highest number of co-linear genes. The qRT-PCR showed that among the tissue-specific expression patterns of Tartary buckwheat CCO genes, the expression of the FtCCOs was higher in the leaves. In Tartary buckwheat grain development, the relative expression of most FtCCOs was higher at the later stage. The relative expression of many genes was higher in the stems under cold, dark, NaCl, and abiotic stress conditions. However, under the hormone and plant growth regulator treatments, the expression of the nine FtCCOs was relatively low in the stems. Notably, the relative expression of FtNCED4 was extremely high under abiotic stress and hormone induction, indicating that FtNCED4 may be involved in the growth and development of Tartary buckwheat. In this study, the FtCCO family genes of Tartary buckwheat were identified at the genome-wide level, and the gene expression pattern of the FtCCO gene family in different tissues or treatments was determined. This study provides a theoretical basis for further analysis of the functions of theFtCCO family, which is of great significance for the mining of resistance genes and trait improvement.

Deep learning tools predict variants in disordered regions with lower sensitivity

BACKGROUND

The recent AI breakthrough of AlphaFold2 has revolutionized 3D protein structural modeling, proving crucial for protein design and variant effects prediction. However, intrinsically disordered regions-known for their lack of well-defined structure and lower sequence conservation-often yield low-confidence models. The latest Variant Effect Predictor (VEP), AlphaMissense, leverages AlphaFold2 models, achieving over 90% sensitivity and specificity in predicting variant effects. However, the effectiveness of tools for variants in disordered regions, which account for 30% of the human proteome, remains unclear.

RESULTS

In this study, we found that predicting pathogenicity for variants in disordered regions is less accurate than in ordered regions, particularly for mutations at the first N-Methionine site. Investigations into the efficacy of variant effect predictors on intrinsically disordered regions (IDRs) indicated that mutations in IDRs are predicted with lower sensitivity and the gap between sensitivity and specificity is largest in disordered regions, especially for AlphaMissense and VARITY.

CONCLUSIONS

The prevalence of IDRs within the human proteome, coupled with the increasing repertoire of biological functions they are known to perform, necessitated an investigation into the efficacy of state-of-the-art VEPs on such regions. This analysis revealed their consistently reduced sensitivity and differing prediction performance profile to ordered regions, indicating that new IDR-specific features and paradigms are needed to accurately classify disease mutations within those regions.

Developing a crop- wild-reservoir pathogen system to understand pathogen evolution and emergence

Crop pathogens reduce yield and contribute to global malnourishment. Surveillance not only detects presence/absence but also reveals genetic diversity, which can inform our understanding of rapid adaptation and control measures. An often neglected aspect is that pathogens may also use crop wild relatives as alternative hosts. This study develops the beet (Beta vulgaris) rust (Uromyces beticola) system to explore how crop pathogens evolve to evade resistance using a wild reservoir. We test predictions that crop selection will drive virulence gene differentiation and affect rates of sex between crop- and wild-host rust populations. We sequenced, assembled, and annotated the 588 Mb beet rust genome, developed a novel leaf peel pathogen DNA extraction protocol, and analysed genetic diversity in 42 wild and crop isolates. We found evidence for two populations: one containing exclusively wild-host isolates; the other containing all crop-host isolates, plus five wild isolates. Effectors showed greater diversity in the exclusively wild population and greater differentiation between populations. Preliminary evidence suggests the rates of sexual reproduction may differ between populations. This study highlights how differences in pathogen populations might be used to identify genes important for survival on crops and how reproduction might impact adaptation. These findings are relevant to all crop-reservoir systems and will remain unnoticed without comparison to wild reservoirs.

Control of morphogenesis during the Staphylococcus aureus cell cycle

Bacterial cell division is a complex, multistage process requiring septum development while maintaining cell wall integrity. A dynamic, macromolecular protein complex, the divisome, tightly controls morphogenesis both spatially and temporally, but the mechanisms that tune septal progression are largely unknown. By studying conditional mutants of genes encoding DivIB, DivIC, and FtsL, an essential trimeric complex central to cell division in bacteria, we demonstrate that FtsL and DivIB play independent, hierarchical roles coordinating peptidoglycan synthesis across specific septal developmental checkpoints. They are required for the localization of downstream divisome components and the redistribution of peptidoglycan synthesis from the cell periphery to the septum. This is achieved by positive regulation of septum production and negative regulation of peripheral cell wall synthesis. Our analysis has led to a model for the coordination of cell division in Staphylococcus aureus, forming a framework for understanding how protein localization and function are integrated with cell wall structural dynamics across the bacteria.