NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins

A near chromosome-level genome assembly of a ghost moth (Lepidoptera, Hepialidae)

Ghost moths are an unusual family of primitive moths (Lepidoptera: Hepialidae) known for their large body size and crepuscular adult activity. These moths represent an ancient lineage, frequently have soil dwelling larvae, and are adapted to high elevations, deserts, and other extreme environments. Despite being rather speciose with more than 700 species, there is a dearth of genomic resources for the family. Here, we present the first high quality, publicly available hepialid genome, generated from an Andean species of ghost moth, Druceiella hillmani. Our genome assembly has a length of 2,586 Mbp with contig N50 of 28.1 Mb and N50 of 29, and BUSCO completeness of 97.1%, making it one of the largest genomes in the order Lepidoptera. Our assembly is a vital resource for future research on ghost moth genomics.

RettDb: the Rett syndrome omics database to navigate the Rett syndrome genomic landscape

Rett syndrome (RTT) is a neurodevelopmental disorder occurring almost exclusively in females and leading to a variety of impairments and disabilities from mild to severe. In >95% cases, RTT is due to mutations in the X-linked gene MECP2, but the molecular mechanisms determining RTT are unknown at present, and the complexity of the system is challenging. To facilitate and provide guidance to the unraveling of those mechanisms, we developed a database resource for the visualization and analysis of the genomic landscape in the context of wild-type or mutated Mecp2 gene in the mouse model. Our resource allows for the exploration of differential dynamics of gene expression and the prediction of new potential MECP2 target genes to decipher the RTT disorder molecular mechanisms. Database URL: https://biomedinfo.di.unipi.it/rett-database/.

Genetic analyses of 104 phenotypes in 20,900 Chinese pregnant women reveal pregnancy-specific discoveries

Monitoring biochemical phenotypes during pregnancy is vital for maternal and fetal health, allowing early detection and management of pregnancy-related conditions to ensure safety for both. Here, we conducted a genetic analysis of 104 pregnancy phenotypes in 20,900 Chinese women. The genome-wide association study (GWAS) identified a total of 410 trait-locus associations, with 71.71% reported previously. Among the 116 novel hits for 45 phenotypes, 83 were successfully replicated. Among them, 31 were defined as potentially pregnancy-specific associations, including creatine and HELLPAR and neutrophils and ESR1, with subsequent analysis revealing enrichments in estrogen-related pathways and female reproductive tissues. The partitioning heritability underscored the significant roles of fetal blood, embryoid bodies, and female reproductive organs in pregnancy hematology and birth outcomes. Pathway analysis confirmed the intricate interplay of hormone and immune regulation, metabolism, and cell cycle during pregnancy. This study contributes to the understanding of genetic influences on pregnancy phenotypes and their implications for maternal health.

Loss of heterozygosity of CYP2D6 enhances the sensitivity of hepatocellular carcinomas to talazoparib

BACKGROUND

Loss of heterozygosity (LOH) diminishes genetic diversity within cancer genomes. A tumour arising in an individual heterozygous for a functional and a loss-of-function (LoF) allele of a gene occasionally retain only the LoF allele. This can result in deficiency of specific protein activities in cancer cells, creating unique differences between tumour cells and normal cells of the individual. Such differences may constitute vulnerabilities that can be exploited through allele-specific therapies.

METHODS

To discover frequently lost genes with prevalent LoF alleles, we mined the 1000 Genomes dataset for SNVs causing protein truncation through base substitution, indels or splice site disruptions, resulting in 60 LoF variants in 60 genes. From these, the variant rs3892097 in the liver enzyme CYP2D6 was selected because it is located within a genomic region that frequently undergoes LOH in several tumor types including hepatocellular cancers. To evaluate the relationship between CYP2D6 activity and the toxicities of anticancer agents, we screened 525 compounds currently in clinical use or undergoing clinical trials using cell model systems with or without CYP2D6 activity.

FINDINGS

We identified 12 compounds, AZD-3463, CYC-116, etoposide, everolimus, GDC-0349, lenvatinib, MK-8776, PHA-680632, talazoparib, tyrphostin 9, VX-702, and WZ-3146, using an engineered HEK293T cell model. Of these, talazoparib and MK-8776 demonstrated consistently heightened cytotoxic effects against cells with compromised CYP2D6 activity in engineered hepatocellular cancer cell models. Moreover, talazoparib displayed CYP2D6 genotype dependent effects on primary hepatocellular carcinoma organoids.

INTERPRETATION

Exploiting the loss of drug-metabolizing enzyme gene activity in tumor cells following loss of heterozygosity could present a promising therapeutic strategy for targeted cancer treatment.

FUNDING

This work was funded by Barncancerfonden (T.S, PR2022-0099 and PR2020-0171, X.Z, TJ2021-0111), Cancerfonden (T.S, 211719Pj and D.G, 222449Pj), Vetenskapsrådet (T.S, 2020-02371 and D.G, 2020-04707), and the Erling Persson Foundation (T.S, 2020-0037 and T.S, 2023-0113).

Growth of sulfate-reducing Desulfobacterota and Bacillota at periodic oxygen stress of 50% air-O2 saturation

BACKGROUND

Sulfate-reducing bacteria (SRB) are frequently encountered in anoxic-to-oxic transition zones, where they are transiently exposed to microoxic or even oxic conditions on a regular basis. This can be marine tidal sediments, microbial mats, and freshwater wetlands like peatlands. In the latter, a cryptic but highly active sulfur cycle supports their anaerobic activity. Here, we aimed for a better understanding of how SRB responds to periodically fluctuating redox regimes.

RESULTS

To mimic these fluctuating redox conditions, a bioreactor was inoculated with peat soil supporting cryptic sulfur cycling and consecutively exposed to oxic (one week) and anoxic (four weeks) phases over a period of > 200 days. SRB affiliated to the genus Desulfosporosinus (Bacillota) and the families Syntrophobacteraceae, Desulfomonilaceae, Desulfocapsaceae, and Desulfovibrionaceae (Desulfobacterota) successively established growing populations (up to 2.9% relative abundance) despite weekly periods of oxygen exposures at 133 µM (50% air saturation). Adaptation mechanisms were analyzed by genome-centric metatranscriptomics. Despite a global drop in gene expression during oxic phases, the perpetuation of gene expression for energy metabolism was observed for all SRBs. The transcriptional response pattern for oxygen resistance was differentiated across individual SRBs, indicating different adaptation strategies. Most SRB transcribed differing sets of genes for oxygen consumption, reactive oxygen species detoxification, and repair of oxidized proteins as a response to the periodical redox switch from anoxic to oxic conditions. Noteworthy, a Desulfosporosinus, a Desulfovibrionaceaea, and a Desulfocapsaceaea representative maintained high transcript levels of genes encoding oxygen defense proteins even under anoxic conditions, while representing dominant SRB populations after half a year of bioreactor operation.

CONCLUSIONS

In situ-relevant peatland SRB established large populations despite periodic one-week oxygen levels that are one order of magnitude higher than known to be tolerated by pure cultures of SRB. The observed decrease in gene expression regulation may be key to withstand periodically occurring changes in redox regimes in these otherwise strictly anaerobic microorganisms. Our study provides important insights into the stress response of SRB that drives sulfur cycling at oxic-anoxic interphases. Video Abstract.

Recursive dynamics of GspE through machine learning enabled identification of inhibitors

Type II secretion System has been increasingly recognized as a key driver of virulence in many pathogenic bacteria including Achromobacter xylosoxidans. ATPase GspE is the powerhouse of the T2SS. It powers the entire secretion process by binding with ATP and hydrolyzing it. Therefore, targeting it was thought to have a profound effect on the normal functioning of the whole T2SS. A. xylosoxidans is a Gram-negative bacterium that poses a rising concern to immunocompromised people. It is responsible for many opportunistic infections mostly in people with cystic fibrosis. Due to its intrinsic and acquired resistance mechanisms, it is challenging to treat. In this current study, an extensive machine learning-enabled computational investigation was carried out. Drug libraries were screened using machine learning random forest algorithm trained on non-redundant dataset of 8722 antibacterial compounds with reported IC50 values. Active compounds were then further subjected to molecular docking. To unravel the dynamics and better understand the stability of complexes, the top complexes were subjected to MD Simulations followed by various post-simulation analyses including Trajectory analysis, Atom Contacts, SASA, Hydrogen Bond, RDF, binding free energy calculations, PCA, and AFD analysis. Findings from the study unanimously unveiled Asinex-BAS00263070-28551 as the best inhibitor as it instigated the recursive dynamics of the target by making key hydrogen bond interactions with Walker A motif, suggesting it could serve as the promising drug candidate against GspE. Further experimental in-vivo and in-vitro validation is still required to authenticate the therapeutic effects of these drugs.

Chromosome-level genome assembly of the bay scallop Argopecten irradians

The bay scallop, Argopecten irradians, is a species of major commercial, cultural, and ecological importance. It is endemic to the eastern coast of the United States, but has also been introduced to China, where it supports a significant aquaculture industry. Here, we provide an annotated chromosome-level reference genome assembly for the bay scallop, assembled using PacBio and Hi-C data. The total genome size is 845.9 Mb, distributed over 1,503 scaffolds with a scaffold N50 of 44.3 Mb. The majority (92.9%) of the assembled genome is contained within the 16 largest scaffolds, corresponding to the 16 chromosomes confirmed by Hi-C analysis. The assembly also includes the complete mitochondrial genome. Approximately 36.2% of the genome consists of repetitive elements. The BUSCO analysis showed a completeness of 96.2%. We identified 33,772 protein-coding genes. This genome assembly will be a valuable resource for future research on evolutionary dynamics, adaptive mechanisms, and will support genome-assisted breeding, contributing to the conservation and management of this iconic species in the face of environmental and pathogenic challenges.

Systematic discovery of DNA-binding tandem repeat proteins

Tandem repeat proteins (TRPs) are widely distributed and bind to a wide variety of ligands. DNA-binding TRPs such as zinc finger (ZNF) and transcription activator-like effector (TALE) play important roles in biology and biotechnology. In this study, we first conducted an extensive analysis of TRPs in public databases, and found that the enormous diversity of TRPs is largely unexplored. We then focused our efforts on identifying novel TRPs possessing DNA-binding capabilities. We established a protein language model for DNA-binding protein prediction (PLM-DBPPred), and predicted a large number of DNA-binding TRPs. A subset was then selected for experimental screening, leading to the identification of 11 novel DNA-binding TRPs, with six showing sequence specificity. Notably, members of the STAR (Short TALE-like Repeat proteins) family can be programmed to target specific 9 bp DNA sequences with high affinity. Leveraging this property, we generated artificial transcription factors using reprogrammed STAR proteins and achieved targeted activation of endogenous gene sets. Furthermore, the members of novel families such as MOON (Marine Organism-Originated DNA binding protein) and pTERF (prokaryotic mTERF-like protein) exhibit unique features and distinct DNA-binding characteristics, revealing interesting biological clues. Our study expands the diversity of DNA-binding TRPs, and demonstrates that a systematic approach greatly enhances the discovery of new biological insights and tools.

DeepPBI-KG: a deep learning method for the prediction of phage-bacteria interactions based on key genes

Phages, the natural predators of bacteria, were discovered more than 100 years ago. However, increasing antimicrobial resistance rates have revitalized phage research. Methods that are more time-consuming and efficient than wet-laboratory experiments are needed to help screen phages quickly for therapeutic use. Traditional computational methods usually ignore the fact that phage-bacteria interactions are achieved by key genes and proteins. Methods for intraspecific prediction are rare since almost all existing methods consider only interactions at the species and genus levels. Moreover, most strains in existing databases contain only partial genome information because whole-genome information for species is difficult to obtain. Here, we propose a new approach for interaction prediction by constructing new features from key genes and proteins via the application of K-means sampling to select high-quality negative samples for prediction. Finally, we develop DeepPBI-KG, a corresponding prediction tool based on feature selection and a deep neural network. The results show that the average area under the curve for prediction reached 0.93 for each strain, and the overall AUC and area under the precision-recall curve reached 0.89 and 0.92, respectively, on the independent test set; these values are greater than those of other existing prediction tools. The forward and reverse validation results indicate that key genes and key proteins regulate and influence the interaction, which supports the reliability of the model. In addition, intraspecific prediction experiments based on Klebsiella pneumoniae data demonstrate the potential applicability of DeepPBI-KG for intraspecific prediction. In summary, the feature engineering and interaction prediction approaches proposed in this study can effectively improve the robustness and stability of interaction prediction, can achieve high generalizability, and may provide new directions and insights for rapid phage screening for therapy.

Extensive transcriptome data providing great efficacy in genetic research and adaptive gene discovery: a case study of Elymus sibiricus L. (Poaceae, Triticeae)

Genetic markers play a central role in understanding genetic diversity, speciation, evolutionary processes, and how species respond to environmental stresses. However, conventional molecular markers are less effective when studying polyploid species with large genomes. In this study, we compared gene expression levels in 101 accessions of Elymus sibiricus, a widely distributed allotetraploid forage species across the Eurasian continent. A total of 20,273 high quality transcriptomic SNPs were identified. In addition, 72,344 evolutionary information loci of these accessions of E. sibiricus were identified using genome skimming data in conjunction with the assembled composite genome. The population structure results suggest that transcriptome SNPs were more effective than SNPs derived from genome skimming data in revealing the population structure of E. sibiricus from different locations, and also outperformed gene expression levels. Compared with transcriptome SNPs, the investigation of population-specifically-expressed genes (PSEGs) using expression levels revealed a larger number of locally adapted genes mainly involved in the ion response process in the Sichuan, Inner Mongolia, and Xizang geographical groups. Furthermore, we performed the weighted gene co-expression network analysis (WGCNA) and successfully identified potential regulators of PSEGs. Therefore, for species lacking genomic information, the use of transcriptome SNPs is an efficient approach to perform population structure analysis. In addition, analyzing genes under selection through nucleotide diversity and genetic differentiation index analysis based on transcriptome SNPs, and exploring PSEG through expression levels is an effective method for analyzing locally adaptive genes.

Integrated subtractive genomics and structure-based approach to unravel the therapeutic drug target of Leishmania species

Leishmaniasis is a complex vector-borne disease caused by intracellular protozoan parasites of the Leishmania genus. It presents a significant public health challenge in tropical and subtropical regions globally. As resistance to treatment increases, managing and controlling Leishmaniasis becomes more challenging, necessitating innovative approaches. To address this challenge, our study utilized subtractive genomics and structure-based approaches to identify common drug targets and combat antimicrobial resistance (AMR) across five Leishmania species strains. The subtractive genomics approach unraveled Glutamate Dehydrogenase (GDH) as a promising drug target for treating Leishmania infections. The investigation considered established methodologies observed in analogous studies, orthologous group, and druggability tests. Multiple sequence alignment revealed conserved sequences in GDH, while phylogenetic tree analysis provided insights into the evolutionary origin and close relationships of GDH across Leishmania species. Conserved sequences in GDH along with its function in pathogenicity provided insights into the close relationships of GDH across Leishmania species. Using a structure-based approach, our study showed the molecular interactions between GDH and three ligands-Bithionol, GW5074, and Hexachlorophene-through molecular docking and 100 ns molecular dynamics (MD) simulations. GW5074 exhibited a significant affinity for GDH, as indicated by stable RMSD values, a more compact conformation, and a higher number of hydrogen bonds than Bithionol. MMPBSA analysis confirmed the superior binding energy of the GW5074-GDH complex, emphasizing its potential as a potent ligand for drug development. This comprehensive analysis identified GW5074 as a promising candidate for inhibiting GDH activities in Leishmania species, contributing to the development of effective therapeutics against Leishmania infections.

Identification of the Potential Role of the E4orf4 Protein in Adenovirus A, B, C, and D Groups in Cancer Therapy: Computational Approaches

The human adenovirus (HADV) early region 4 open reading frame 4 (E4orf4) protein plays a regulatory role in promoting viral infection by interacting with various cellular proteins. E4orf4 can induce death in cancer cells. One of the death pathways that is induced by this protein is related to the formation of membrane blebbing following the phosphorylation of tyrosine amino acids. The activation of this pathway requires the interaction of E4orf4 with Src family kinases (SFKs). The modulation mechanism of Src-dependent signaling via E4orf4 is not yet fully understood. However, evidence suggests that a physical association between the Src kinase domain and the arginine-rich motif of E4orf4 is crucial. Physically connecting E4orf4 to Src kinase leads to the deregulation of the Src-related signaling pathway, thereby inducing cytoplasmic death. In this study, we mapped the E4orf4 interaction site in Src to investigate the interaction between E4orf4 and Src in detail. We also compared the binding strength of E4orf4 proteins from different HADV groups. To this end, we performed bioinformatics structural analysis of the Src kinase domain and E4orf4 to identify E4orf4 interaction sites. The group with the lowest binding energy was predicted to be the most likely candidate for the highest cytoplasmic death in tumor cells based on the energy of the E4orf4-Src complex in various HADV groups. These results show that HADV-A and HADV-C have minimal binding energies to the E4orf4-Src complex, while the dissociation constant (Kd) of HADV-A was less than that of HADV-C. According to the obtained results, E4orf4 of the HADV-A group is more effective at triggering cytoplasmic death based on its most robust interaction with the Src kinase domain.

Advancing rational pesticide development against Drosophila suzukii: bioinformatics tools and applications-a systematic review

CONTEXT

Drosophila suzukii (Matsumura, 1931) is a widespread agricultural pest responsible for significant damage to various soft-skinned fruit hosts. The revolutionary potential of bioinformatics in agriculture emerges from its ability to provide extensive information on pests, fungi, chemical resistance, implications of non-target species, and other critical aspects. This wealth of information allows researchers to engage in projects and applied research in diverse agricultural domains that face these challenges. In this context, bioinformatics tools play a fundamental role. The negative impact of pests on crops, resulting in substantial economic losses, has highlighted the importance of in silico methods.

METHODS

To achieve this, we conducted a systematic search in scientific databases using as keywords "Drosophila suzukii," "biopesticides," "simulations computational," and "in-silico." After applying the filters of relevance and publication date, we organized the articles and prioritized those that directly addressed that matched the keywords and the use of bioinformatics tools. Additionally, we included studies focusing on in silico assays of biopesticides, such as molecular docking. Our review aimed to present a collection of recent literature on biopesticides against Drosophila suzukii, emphasizing bioinformatics methods. Through this work, we strive to contribute to the literature of new perspectives on the development and efficiency of biopesticides, along with to advance research that may improve pest control strategies.

RESULTS

In the results of the systematic review, we found 2734 articles related to the selected keywords. Six of these articles directly address Drosophila suzukii and the use of bioinformatics tools in the search for alternatives in pest control. In the selected studies, we observed that two articles tend to focus on phylogenetic approaches, searching for gene sequences, amino acids, and constructing phylogenetic trees. The other three articles used molecular modeling and docking of receptors such as GABA and TRP with plant-derived and synthetic compounds to study intermolecular interactions. However, we identified gaps in these studies that could lead to further research in the biorational development of biopesticides using bioinformatics tools.

Biotransformation of ferulic acid into vanillyl alcohol and vanillic acid employing thermophilic bacterium Caldimonas thermodepolymerans

Caldimonas thermodepolymerans, a Gram-negative, moderately thermophilic bacterium, exhibits a remarkable biotechnological potential. Given the presence of genes in its genome dedicated to the metabolization of ferulic acid (FA), this study aimed to explore the bacterium's capability for biotransforming FA into high-value metabolites. The results unequivocally demonstrate the bacterium's proficiency in the efficient and rapid conversion of FA into vanillyl alcohol (VOH) and vanillic acid (VA). By manipulating key cultivation parameters, such as adjusting initial FA doses and varying cultivation periods, the product profile can be tailored. Higher initial doses and shorter cultivation periods favor the production of VOH, while lower FA doses and extended cultivation periods lead to the predominant formation of VA. Furthermore, the process can be operated in a repeated-batch scenario. This underscores the potential of C. thermodepolymerans for industrial biotransformation of FA, presenting a promising avenue for leveraging its capabilities in practical applications.

Familial Exudative Vitreoretinopathy With and Without Pathogenic Variants of Norrin/β-Catenin Signaling Genes

Purpose

To determine the clinical characteristics of familial exudative vitreoretinopathy (FEVR) associated with or without pathogenic variants of the Norrin/β-catenin genes.

Design

This was a multicenter, cross-sectional, observational, and genetic study.

Subjects

Two-hundred eighty-one probands with FEVR were studied.

Methods

Whole-exome sequence and/or Sanger sequence was performed for the Norrin/β-catenin genes, the FZD4, LRP5, TSPAN12, and NDP genes on blood collected from the probands. The clinical symptoms of the probands with or without the pathogenic variants were assessed as well as differences in the inter Norrin/β-catenin genes.

Main Outcome Measures

The phenotype associated with or without pathogenic variants of the Norrin/β-catenin genes.

Results

One-hundred eight probands (38.4%) had 88 different pathogenic or likely pathogenic variants in the genes: 24 with the FZD4, 42 with the LRP5, 10 with the TSPAN12, and 12 with the NDP gene. Compared with the 173 probands without pathogenic variants, the 108 variant-positive probands had characteristics of familial predisposition (63.9% vs. 37.6%, P < 0.0001), progression during infancy (75.0% vs. 53.8%, P = 0.0004), asymmetrical severity between the 2 eyes (50.0% vs. 37.6%, P = 0.0472), and nonsyndromic characteristics (10.2% vs. 17.3%, P = 0.1185). The most frequent stage at which the more severe eye conditions was present was at stage 4 in both groups (40.7% vs. 34.7%). However, the advanced stages of 3 to 5 in the more severe eye were found more frequently in probands with variants than in those without variants (83.3% vs. 58.4%, P < 0.0001). Patients with rhegmatogenous retinal detachments progressed from stage 1 or 2 were found less frequently in the variant-positive probands (8.3% vs. 17.3%, P = 0.0346). Nine probands with NDP variants had features different from probands with typical Norrin/β-catenin gene variants including the sporadic, symmetrical, and systemic characteristics consistent with Norrie disease.

Conclusions

The results showed that the clinical characteristics of FEVR of patients with variants in the Norrin/β-catenin genes are different from those with other etiologies. We recommend that clinicians who diagnose a child with FEVR perform genetic testing so that the parents can be informed on the prognosis of the vision and general health in the child.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Phycosphere bacterial composition and function in colony and solitary Phaeocystis globosa strains providing novel insights into the algal blooms

Phycosphere bacteria can regulate the dynamics of different algal blooms that impact marine ecosystems. Phaeocystis globosa can alternate between solitary free-living cells and colonies and the latter morphotype is dominate during blooms. The mechanisms underlying the formation of these blooms have received much attention. High throughput sequencing results showed that the bacterial community composition differed significantly between colony and solitary strains in bacterial composition and function. It was found that the genera SM1A02 and Haliea were detected only among the colony strains and contribute to ammonium accumulation in colonies, and the genus Sulfitobacter was abundant among the colony strains that were excellent at producing DMS. In addition, the bacterial communities of the two colony strains exhibited stronger abilities for carbon and sulfur metabolism, energy metabolism, vitamin B synthesis, and signal transduction, providing inorganic and organic nutrients and facilitating tight communication with the host algae, thereby promoting growth and bloom development.

Integration of chromosome locations and functional aspects of enhancers and topologically associating domains in knowledge graphs enables versatile queries about gene regulation

Knowledge about transcription factor binding and regulation, target genes, cis-regulatory modules and topologically associating domains is not only defined by functional associations like biological processes or diseases but also has a determinative genome location aspect. Here, we exploit these location and functional aspects together to develop new strategies to enable advanced data querying. Many databases have been developed to provide information about enhancers, but a schema that allows the standardized representation of data, securing interoperability between resources, has been lacking. In this work, we use knowledge graphs for the standardized representation of enhancers and topologically associating domains, together with data about their target genes, transcription factors, location on the human genome, and functional data about diseases and gene ontology annotations. We used this schema to integrate twenty-five enhancer datasets and two domain datasets, creating the most powerful integrative resource in this field to date. The knowledge graphs have been implemented using the Resource Description Framework and integrated within the open-access BioGateway knowledge network, generating a resource that contains an interoperable set of knowledge graphs (enhancers, TADs, genes, proteins, diseases, GO terms, and interactions between domains). We show how advanced queries, which combine functional and location restrictions, can be used to develop new hypotheses about functional aspects of gene expression regulation.

Exploiting the role of O6-methylguanine-DNA-methyltransferase (MGMT) in gastrointestinal cancers

Gastrointestinal (GI) cancer is a prevalent disease and is recognized as the primary cause of cancer-related mortality globally. Therefore, there is an urgent need for novel diagnostic and treatment approaches for GC. The methylation of the O(6)-methylguanine DNA methyltransferase (MGMT) gene promoter is a significant factor in the development of colorectal cancer (CRC), namely in roughly 30-40% of cases where the cancer has spread. MGMT plays a role in the repair of DNA damage caused by methylating drugs like temozolomide (TMZ) and chloroethylating compounds like carmustine. As a result, it contributes to the resistance of chemotherapy when these agents are utilized. Although MGMT's role in the development of CRC is well established, its prognostic significance remains a subject of debate. Only a limited number of research have been conducted to examine the prognostic significance of MGMT methylation, yielding varying outcomes. This review explores the structural functions and repair processes of MGMT, focusing on the putative structural and functional significance of the N-terminal domain of MGMT. It also investigates the advancement of cancer treatment techniques that specifically target MGMT.

Chromosome-contiguous genome for the Haecon-5 strain of Haemonchus contortus reveals marked genetic variability and enables the discovery of essential gene candidates

Millions of livestock animals worldwide are infected with the haematophagous barber's pole worm, Haemonchus contortus, the aetiological agent of haemonchosis. Despite the major significance of this parasite worldwide and its widespread resistance to current treatments, the lack of a high-quality genome for the well-defined strain of this parasite from Australia, called Haecon-5, has constrained research in a number of areas including host-parasite interactions, drug discovery and population genetics. To enable research in these areas, we report here a chromosome-contiguous genome (∼280 Mb) for Haecon-5 with high-quality models for 19,234 protein-coding genes. Comparative genomic analyses show significant genomic similarity (synteny) with a UK strain of H. contortus, called MHco3(ISE).N1 (abbreviated as "ISE"), but we also discover marked differences in genomic structure/gene arrangements, distribution of nucleotide variability (single nucleotide polymorphisms (SNPs) and indels) and orthology between Haecon-5 and ISE. We used the genome and extensive transcriptomic resources for Haecon-5 to predict a subset of essential single-copy genes employing a "cross-species" machine learning (ML) approach using a range of features from nucleotide/protein sequences, protein orthology, subcellular localisation, single-cell RNA-seq and/or histone methylation data available for the model organisms Caenorhabditis elegans and Drosophila melanogaster. From a set of 1,464 conserved single copy genes, transcribed in key life-cycle stages of H. contortus, we identified 232 genes whose homologs have critical functions in C. elegans and/or D. melanogaster, and prioritised 10 of them for further characterisation; nine of the 10 genes likely play roles in neurophysiological processes, germline, hypodermis and/or respiration, and one is an unknown (orphan) gene for which no detailed functional information exists. Future studies of these genes/gene products are warranted to elucidate their roles in parasite biology, host-parasite interplay and/or disease. Clearly, the present Haecon-5 reference genome and associated resources now underpin a broad range of fundamental investigations of H. contortus and could assist in accelerating the discovery of novel intervention targets and drug candidates to combat haemonchosis.

Distinct horizontal transfer mechanisms for type I and type V CRISPR-associated transposons

CASTs use both CRISPR-associated proteins and Tn7-family transposons for RNA-guided vertical and horizontal transmission. CASTs encode minimal CRISPR arrays but can't acquire new spacers. Here, we report that CASTs can co-opt defense-associated CRISPR arrays for horizontal transmission. A bioinformatic analysis shows that CASTs co-occur with defense-associated CRISPR systems, with the highest prevalence for type I-B and type V CAST sub-types. Using an E. coli quantitative transposition assay and in vitro reconstitution, we show that CASTs can use CRISPR RNAs from these defense systems. A high-resolution structure of the type I-F CAST-Cascade in complex with a type III-B CRISPR RNA reveals that Cas6 recognizes direct repeats via sequence-independent π - π interactions. In addition to using heterologous CRISPR arrays, type V CASTs can also transpose via an unguided mechanism, even when the S15 co-factor is over-expressed. Over-expressing S15 and the trans-activating CRISPR RNA or a single guide RNA reduces, but does not abrogate, off-target integration for type V CASTs. Our findings suggest that some CASTs may exploit defense-associated CRISPR arrays and that this fact must be considered when porting CASTs to heterologous bacterial hosts. More broadly, this work will guide further efforts to engineer the activity and specificity of CASTs for gene editing applications.

Accessing and exploring the unusual chemistry by radical SAM-RiPP enzymes

Radical SAM enzymes involved in the biosynthesis of ribosomally synthesized and post-translationally modified peptides catalyze unusual transformations that lead to unique peptide scaffolds and building blocks. Several natural products from these pathways show encouraging antimicrobial activities and represent next-generation therapeutics for infectious diseases. These systems are uniquely configured to benefit from genome-mining approaches because minimal substrate and cognate modifying enzyme expression can reveal unique, chemically complex transformations that outperform late-stage chemical reactions. This report highlights the main strategies used to reveal these enzymatic transformations, which have relied mainly on genome mining using enzyme-first approaches. We describe the general biosynthetic components for rSAM enzymes and highlight emerging approaches that may broaden the discovery and study of rSAM-RiPP enzymes. The large number of uncharacterized rSAM proteins, coupled with their unpredictable transformations, will continue to be an essential and exciting resource for enzyme discovery.

Full-length agave transcriptome reveals candidate glycosyltransferase genes involved in hemicellulose biosynthesis

Agave species are typical crassulacean acid metabolism (CAM) plants commonly cultivated to produce beverages, fibers, and medicines. To date, few studies have examined hemicellulose biosynthesis in Agave H11648, which is the primary cultivar used for fiber production. We conducted PacBio sequencing to obtain full-length transcriptome of five agave tissues: leaves, shoots, roots, flowers, and fruits. A total of 41,807 genes were generated, with a mean length of 2394 bp and an annotation rate of 97.12 % using public databases. We identified 42 glycosyltransferase genes related to hemicellulose biosynthesis, including mixed-linkage glucan (1), glucomannan (5), xyloglucan (16), and xylan (20). Their expression patterns were examined during leaf development and fungal infection, together with hemicellulose content. The results revealed four candidate glycosyltransferase genes involved in xyloglucan and xylan biosynthesis, including glucan synthase (CSLC), xylosyl transferase (XXT), xylan glucuronyltransferase (GUX), and xylan α-1,3-arabinosyltransferase (XAT). These genes can be potential targets for manipulating xyloglucan and xylan traits in agaves, and can also be used as candidate enzymatic tools for enzyme engineering. We have provided the first full-length transcriptome of agave, which will be a useful resource for gene identification and characterization in agave species. We also elucidated the hemicellulose biosynthesis machinery, which will benefit future studies on hemicellulose traits in agave.

Transcription factor CmHSFA4-CmMYBS3 complex enhances salt tolerance in chrysanthemum by repressing CmMYB121 expression

Excessive soil salinity not only hampers plant growth and development but can also lead to plant death. Previously, we found that heat-shock factor A4 (CmHSFA4) enhances the tolerance of chrysanthemum (Chrysanthemum morifolium) to salt. However, the underlying molecular mechanism remains unclear. In this study, we identified a candidate MYB transcription factor, CmMYB121, which responded to salt stress. We observed that the CmMYB121 transcription is suppressed by CmHSFA4. Moreover, overexpression of CmMYB121 exacerbated chrysanthemum sensitivity to salt stress. CmHSFA4 directly bound to the promoter of CmMYB121 at the heat-shock element. Protein-protein interaction assays identified an interaction between CmHSFA4 and CmMYBS3, a transcriptional repressor, and recruited the corepressor TOPLESS (CmTPL) to inhibit CmMYB121 transcription by impairing the H3 and H4 histone acetylation levels of CmMYB121. Our study demonstrated that a CmHSFA4-CmMYBS3-CmTPL complex modulates CmMYB121 expression, consequently regulating the tolerance of chrysanthemum to salt. The findings shed light on the responses of plants to salt stress.

Genomic and molecular characterization of a cyprinid herpesvirus 2 YC-01 strain isolated from gibel carp

Cyprinid herpesvirus 2 (CyHV-2) is the pathogen of herpesviral hematopoietic necrosis (HVHN), causing the severe economic losses in farmed gibel carp (Carassius gibelio). Further exploration of the genome structure and potential molecular pathogenesis of CyHV-2 through complete genome sequencing, comparative genomics, and molecular characterization is required. Herein, the genome of a CyHV-2 YC-01 strain isolated from diseased gibel carp collected in Yancheng, Jiangsu Province, China was sequenced, then we analyzed the genomic structure, genetic properties, and molecular characterization. First, the complete YC-01 genome comprises 275,367 bp without terminal repeat (TR) regions, with 151 potential open reading frames (ORFs). Second, compared with other representative published strains of the genus Cyvirus, several evident variations are found in YC-01, particularly the orientation and position of ORF25 and ORF25B. ORF107 and ORF156 are considered as potential molecular genetic markers for YC-01. ORF55 (encoding thymidine kinase) might be used to distinguish YC-01 and ST-J1 from other CyHV-2 isolates. Third, phylogenetically, YC-01 clusters with the members of the genus Cyvirus (together with the other six CyHV-2 isolates). Fourth, 43 putative proteins are predicted to be functional and are mainly divided into five categories. Several conserved motifs are found in nucleotide, amino acid, and promoter sequences including cis-acting elements identification of YC-01. Finally, the potential virulence factors and linear B cell epitopes of CyHV-2 are predicted to supply possibilities for designing novel vaccines rationally. Our results provide insights for further understanding genomic structure, genetic evolution, and potential molecular mechanisms of CyHV-2.

The miniature genome of broad mite, Polyphagotarsonemus latus (Tarsonemidae: Acari)

The broad mite, Polyphagotarsonemus latus (Tarsonemidae: Acari) is a highly polyphagous species that damage plant species spread across 57 different families. This pest has developed high levels of resistance to some commonly used acaricides. In the present investigation, we deciphered the genome information of P. latus by PacBio HiFi sequencing. P. latus is the third smallest arthropod genome sequenced so far with a size of 49.1 Mb. The entire genome was assembled into two contigs. A set of 9,286 protein-coding genes were annotated. Its compact genome size could be credited with multiple features such as very low repeat content (5.1%) due to the lack of proliferation of transposable elements, high gene density (189.1/Mb), more intronless genes (20.3%) and low microsatellite density (0.63%).

CpG Island Definition and Methylation Mapping of the T2T-YAO Genome

Precisely defining and mapping all cytosine (C) positions and their clusters, known as CpG islands (CGIs), as well as their methylation status, are pivotal for genome-wide epigenetic studies, especially when population-centric reference genomes are ready for timely application. Here, we first align the two high-quality reference genomes, T2T-YAO and T2T-CHM13, from different ethnic backgrounds in a base-by-base fashion and compute their genome-wide density-defined and position-defined CGIs. Second, by mapping some representative genome-wide methylation data from selected organs onto the two genomes, we find that there are about 4.7%-5.8% sequence divergency of variable categories depending on quality cutoffs. Genes among the divergent sequences are mostly associated with neurological functions. Moreover, CGIs associated with the divergent sequences are significantly different with respect to CpG density and observed CpG/expected CpG (O/E) ratio between the two genomes. Finally, we find that the T2T-YAO genome not only has a greater CpG coverage than that of the T2T-CHM13 genome when whole-genome bisulfite sequencing (WGBS) data from the European and American populations are mapped to each reference, but also shows more hyper-methylated CpG sites as compared to the T2T-CHM13 genome. Our study suggests that future genome-wide epigenetic studies of the Chinese populations rely on both acquisition of high-quality methylation data and subsequent precision CGI mapping based on the Chinese T2T reference.

In-silico study of protein-protein interactions in wheat blast using docking and molecular dynamics simulation approach

Despite advancements in agricultural research and the introduction of modern biotechnological and farming techniques, food security remains a significant issue. Although the efforts of farmers to meet the demands of a growing population, many plant diseases caused by pathogens, through their effects on cell division and tissue growth, lead to the annual loss of countless food crops. The recently emerged wheat blast fungus Magnaporthe oryzae pathotype Triticum (MoT) poses a significant danger to worldwide wheat cultivation. The fungus is a highly varied lineage of the M. oryzae, responsible for causing rice blast disease. In spite of being a significant challenge to successful wheat production in South America since 1985, the underlying biology of the wheat blast pathogen is still not fully understood. The initial outbreak of the wheat blast in South Asia had a severe impact on wheat production, resulting in a complete loss of yield in affected fields. For the purpose of enhancing disease management, it's vital to acquire a comprehensive comprehension of the infection biology of the fungus and its interaction with wheat plants on molecular levels. Host-pathogen protein interactions (HPIs) have the potential to reveal the pathogens' mechanism for overcoming the host organism. The current study delves into the interactions between the host plant wheat and MoT through protein-protein interactions, molecular docking, and 100 ns molecular dynamic simulations. This research uncovers the structural and functional basis of these proteins, leading to improved plant health and production.Communicated by Ramaswamy H. Sarma.

Living in mangroves: a syntrophic scenario unveiling a resourceful microbiome

BACKGROUND

Mangroves are complex and dynamic coastal ecosystems under frequent fluctuations in physicochemical conditions related to the tidal regime. The frequent variation in organic matter concentration, nutrients, and oxygen availability, among other factors, drives the microbial community composition, favoring syntrophic populations harboring a rich and diverse, stress-driven metabolism. Mangroves are known for their carbon sequestration capability, and their complex and integrated metabolic activity is essential to global biogeochemical cycling. Here, we present a metabolic reconstruction based on the genomic functional capability and flux profile between sympatric MAGs co-assembled from a tropical restored mangrove.

RESULTS

Eleven MAGs were assigned to six Bacteria phyla, all distantly related to the available reference genomes. The metabolic reconstruction showed several potential coupling points and shortcuts between complementary routes and predicted syntrophic interactions. Two metabolic scenarios were drawn: a heterotrophic scenario with plenty of carbon sources and an autotrophic scenario with limited carbon sources or under inhibitory conditions. The sulfur cycle was dominant over methane and the major pathways identified were acetate oxidation coupled to sulfate reduction, heterotrophic acetogenesis coupled to carbohydrate catabolism, ethanol production and carbon fixation. Interestingly, several gene sets and metabolic routes similar to those described for wastewater and organic effluent treatment processes were identified.

CONCLUSION

The mangrove microbial community metabolic reconstruction reflected the flexibility required to survive in fluctuating environments as the microhabitats created by the tidal regime in mangrove sediments. The metabolic components related to wastewater and organic effluent treatment processes identified strongly suggest that mangrove microbial communities could represent a resourceful microbial model for biotechnological applications that occur naturally in the environment.

From genome to evolution: investigating type II methylotrophs using a pangenomic analysis

A comprehensive pangenomic approach was employed to analyze the genomes of 75 type II methylotrophs spanning various genera. Our investigation revealed 256 exact core gene families shared by all 75 organisms, emphasizing their crucial role in the survival and adaptability of these organisms. Additionally, we predicted the functionality of 12 hypothetical proteins. The analysis unveiled a diverse array of genes associated with key metabolic pathways, including methane, serine, glyoxylate, and ethylmalonyl-CoA (EMC) metabolic pathways. While all selected organisms possessed essential genes for the serine pathway, Methylooceanibacter marginalis lacked serine hydroxymethyltransferase (SHMT), and Methylobacterium variabile exhibited both isozymes of SHMT, suggesting its potential to utilize a broader range of carbon sources. Notably, Methylobrevis sp. displayed a unique serine-glyoxylate transaminase isozyme not found in other organisms. Only nine organisms featured anaplerotic enzymes (isocitrate lyase and malate synthase) for the glyoxylate pathway, with the rest following the EMC pathway. Methylovirgula sp. 4MZ18 stood out by acquiring genes from both glyoxylate and EMC pathways, and Methylocapsa sp. S129 featured an A-form malate synthase, unlike the G-form found in the remaining organisms. Our findings also revealed distinct phylogenetic relationships and clustering patterns among type II methylotrophs, leading to the proposal of a separate genus for Methylovirgula sp. 4M-Z18 and Methylocapsa sp. S129. This pangenomic study unveils remarkable metabolic diversity, unique gene characteristics, and distinct clustering patterns of type II methylotrophs, providing valuable insights for future carbon sequestration and biotechnological applications.

IMPORTANCE

Methylotrophs have played a significant role in methane-based product production for many years. However, a comprehensive investigation into the diverse genetic architectures across different genera of methylotrophs has been lacking. This study fills this knowledge gap by enhancing our understanding of core hypothetical proteins and unique enzymes involved in methane oxidation, serine, glyoxylate, and ethylmalonyl-CoA pathways. These findings provide a valuable reference for researchers working with other methylotrophic species. Furthermore, this study not only unveils distinctive gene characteristics and phylogenetic relationships but also suggests a reclassification for Methylovirgula sp. 4M-Z18 and Methylocapsa sp. S129 into separate genera due to their unique attributes within their respective genus. Leveraging the synergies among various methylotrophic organisms, the scientific community can potentially optimize metabolite production, increasing the yield of desired end products and overall productivity.

SOFB is a comprehensive ensemble deep learning approach for elucidating and characterizing protein-nucleic-acid-binding residues

Proteins and nucleic-acids are essential components of living organisms that interact in critical cellular processes. Accurate prediction of nucleic acid-binding residues in proteins can contribute to a better understanding of protein function. However, the discrepancy between protein sequence information and obtained structural and functional data renders most current computational models ineffective. Therefore, it is vital to design computational models based on protein sequence information to identify nucleic acid binding sites in proteins. Here, we implement an ensemble deep learning model-based nucleic-acid-binding residues on proteins identification method, called SOFB, which characterizes protein sequences by learning the semantics of biological dynamics contexts, and then develop an ensemble deep learning-based sequence network to learn feature representation and classification by explicitly modeling dynamic semantic information. Among them, the language learning model, which is constructed from natural language to biological language, captures the underlying relationships of protein sequences, and the ensemble deep learning-based sequence network consisting of different convolutional layers together with Bi-LSTM refines various features for optimal performance. Meanwhile, to address the imbalanced issue, we adopt ensemble learning to train multiple models and then incorporate them. Our experimental results on several DNA/RNA nucleic-acid-binding residue datasets demonstrate that our proposed model outperforms other state-of-the-art methods. In addition, we conduct an interpretability analysis of the identified nucleic acid binding residue sequences based on the attention weights of the language learning model, revealing novel insights into the dynamic semantic information that supports the identified nucleic acid binding residues. SOFB is available at https://github.com/Encryptional/SOFB and https://figshare.com/articles/online_resource/SOFB_figshare_rar/25499452 .

Toxin production and transcriptomic response to nitrate concentrations in the toxic dinoflagellate Alexandrium tamarense

The bloom-forming dinoflagellate Alexandrium tamarense is one of the most important producers of paralytic shellfish poisoning toxins. Annually recurrent blooms of this dinoflagellate species is associated with the incremental nitrogen influx, especially excessive nitrate input. However, limited studies have been conducted on the toxin production and underlying molecular regulation mechanisms of A. tamarense under various nitrate (N) conditions. Therefore, toxin production and transcriptomic responses of this species were investigated. The toxin profile of A. tamarense was consistently dominated by the C2-toxins, and the cellular toxicity increased with N concentrations peaking at 9.23 ± 0.03 fmol/cell in the 883 μM N-added group. Under lower N conditions, expressions of two STX-core genes, sxtA and sxtG, were significantly down-regulated, suggesting that N regulated sxt expression and triggered responses related to toxin biosynthesis. Results of this study provided valuable insights into the ecophysiology of A. tamarense, enhancing our understanding of the occurrence of toxification events in natural environments.

Genomic landscape of comprehensive genomic profiling in patients with malignant solid tumors in Japan

BACKGROUND

Comprehensive genomic profiling (CGP) can aid the discovery of clinically useful, candidate antitumor agents; however, the variant annotations sometimes differ among the various types of CGP tests as well as the public database. The aim of this study is to clarify the genomic landscape of evaluating detected variants in patients with a malignant solid tumor.

METHODS

The present, cross-sectional study used data from 57,084 patients with a malignant solid tumor who underwent CGP at the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) between June 1, 2019 and August 18, 2023. The pathogenicity of the variants was annotated using public databases.

RESULTS

As a result of re-annotation of the detected variants, 20.1% were pathogenic and 1.4% were benign. The mean number of pathogenic variants was 4.30 (95% confidence interval: 4.27-4.32) per patient. Of the entire cohort, 5.7% had no pathogenic variant. The co-occurrence of the genes depended on the tumor type. Germline findings were detected in 6.2%, 8.8%, and 15.8% of the patients using a tumor/normal panel, tumor-only panel, and liquid panel, respectively, with the most common gene being BRCA2 followed by TP53 and BRCA1.

CONCLUSIONS

The detected variants should be re-annotated because several benign variants or variants of unknown significance were included in the CGP, and the genomic landscape derived from these results will help researchers and physicians interpret the results of CGP tests. The method of extracting presumptive, germline, pathogenic variants from patients using a tumor-only panel or circulating tumor DNA panel requires improvement.

The Pentameric Ligand-Gated Ion Channel Family: A New Member of the Voltage Gated Ion Channel Superfamily?

In this report we present seven lines of bioinformatic evidence supporting the conclusion that the Pentameric Ligand-gated Ion Channel (pLIC) Family is a member of the Voltage-gated Ion Channel (VIC) Superfamily. In our approach, we used the Transporter Classification Database (TCDB) as a reference and applied a series of bioinformatic methods to search for similarities between the pLIC family and members of the VIC superfamily. These include: (1) sequence similarity, (2) compatibility of topology and hydropathy profiles, (3) shared domains, (4) conserved motifs, (5) similarity of Hidden Markov Model profiles between families, (6) common 3D structural folds, and (7) clustering analysis of all families. Furthermore, sequence and structural comparisons as well as the identification of a 3-TMS repeat unit in the VIC superfamily suggests that the sixth transmembrane segment evolved into a re-entrant loop. This evidence suggests that the voltage-sensor domain and the channel domain have a common origin. The classification of the pLIC family within the VIC superfamily sheds light onto the topological origins of this family and its evolution, which will facilitate experimental verification and further research into this superfamily by the scientific community.

Nutrition, phytochemical profiling, in vitro biological activities, and in silico studies of South Chinese white pitaya (Hylocereus undatus)

Background

White pitaya, a popular tropical fruit, is known for its high nutritional value. It is commercially cultivated worldwide for its potential use in the food and pharmaceutical industries. This study aims to assess the nutritional and phytochemical contents and biological potential of the South Chinese White Pitaya (SCWP) peel, flesh, and seed extracts.

Methods

Extract fractions with increasing polarity (ethyl acetate < acetone < ethanol < methanol < aqueous) were prepared. Antibacterial potential was tested against multidrug-resistant (MDR) bacteria, and antioxidant activity was determined using, 2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-Azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) radical scavenging assays, and cytotoxic activity against human keratinocyte cells using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay. Pharmacological screening and molecular docking simulations were conducted to identify potential antibacterial compounds with druggable characteristics. Molecular dynamics simulation (MDS) was employed to validate the binding stability of the promising ligand-protein complexes.

Results

All parts of the fruit exhibited a substantial amount of crucial nutrients (minerals, sugars, proteins, vitamins, and fatty acids). The ethanol (ET) and acetone (AC) fractions of all samples demonstrated notable inhibitory effects against tested MDR bacteria, with MIC50 ranges of 74-925 μg/mL. Both ET and AC fractions also displayed remarkable antioxidant activity, with MIC50 ranges of 3-39 μg/mL. Cytotoxicity assays on HaCaT cells revealed no adverse effects from the crude extract fractions. LC-MS/MS analyses identified a diverse array of compounds, known and unknown, with antibacterial and antioxidant activities. Molecular docking simulations and pharmacological property screening highlighted two active compounds, baicalein (BCN) and lenticin (LTN), showing strong binding affinity with selected target proteins and adhering to pharmacological parameters. MDS indicated a stable interaction between the ligands (BCN and LTN) and the receptor proteins over a 100-ns simulation period.

Conclusion

Our study provides essential information on the nutritional profile and pharmacological potential of the peel, flesh, and seeds of SCWP. Furthermore, our findings contribute to the identification of novel antioxidants and antibacterial agents that could be capable of overcoming the resistance barrier posed by MDR bacteria.

Chromosome-level genome assembly of the diploid oat species Avena longiglumis

Diploid wild oat Avena longiglumis has nutritional and adaptive traits which are valuable for common oat (A. sativa) breeding. The combination of Illumina, Nanopore and Hi-C data allowed us to assemble a high-quality chromosome-level genome of A. longiglumis (ALO), evidenced by contig N50 of 12.68 Mb with 99% BUSCO completeness for the assembly size of 3,960.97 Mb. A total of 40,845 protein-coding genes were annotated. The assembled genome was composed of 87.04% repetitive DNA sequences. Dotplots of the genome assembly (PI657387) with two published ALO genomes were compared to indicate the conservation of gene order and equal expansion of all syntenic blocks among three genome assemblies. Two recent whole-genome duplication events were characterized in genomes of diploid Avena species. These findings provide new knowledge for the genomic features of A. longiglumis, give information about the species diversity, and will accelerate the functional genomics and breeding studies in oat and related cereal crops.

Integrative metabolomic and transcriptomic analyses reveals the accumulation patterns of key metabolites associated with flavonoids and terpenoids of Gynostemma pentaphyllum (Thunb.) Makino

Gynostemma pentaphyllum (Thunb.) Makino (G. pentaphyllum) is a medicinal and edible plant with multiple functions of liver protection, anti-tumor, anti-inflammation, balancing blood sugar and blood lipids. The nutritional value of the G. pentaphyllum plant is mainly due to its rich variety of biologically active substances, such as flavonoids, terpenes and polysaccharides. In this study, we performed a comprehensive analysis combining metabolomics and root, stem and leaf transcriptomic data of G. pentaphyllum. We used transcriptomics and metabolomics data to construct a dynamic regulatory network diagram of G. pentaphyllum flavonoids and terpenoids, and screened the transcription factors involved in flavonoids and terpenoids, including basic helix-loop-helix (bHLH), myb-related, WRKY, AP2/ERF. Transcriptome analysis results showed that among the DEGs related to the synthesis of flavonoids and terpenoids, dihydroflavonol 4-reductase (DFR) and geranylgeranyl diphosphate synthases (GGPPS) were core genes. This study presents a dynamic image of gene expression in different tissues of G. pentaphyllum, elucidating the key genes and metabolites of flavonoids and terpenoids. This study is beneficial to a deeper understanding of the medicinal plants of G. pentaphyllum, and also provides a scientific basis for further regulatory mechanisms of plant natural product synthesis pathways and drug development.

Proteomic scrutiny of nasal microbiomes: implications for the clinic

INTRODUCTION

The nasal cavity is the initial site of the human respiratory tract and is one of the habitats where microorganisms colonize. The findings from a growing number of studies have shown that the nasal microbiome is an important factor for human disease and health. 16S rRNA sequencing and metagenomic next-generation sequencing (mNGS) are the most commonly used means of microbiome evaluation. Among them, 16S rRNA sequencing is the primary method used in previous studies of nasal microbiomes. However, neither 16S rRNA sequencing nor mNGS can be used to analyze the genes specifically expressed by nasal microorganisms and their functions. This problem can be addressed by proteomic analysis of the nasal microbiome.

AREAS COVERED

In this review, we summarize current advances in research on the nasal microbiome, introduce the methods for proteomic evaluation of the nasal microbiome, and focus on the important roles of proteomic evaluation of the nasal microbiome in the diagnosis and treatment of related diseases.

EXPERT OPINION

The detection method for microbiome-expressed proteins is known as metaproteomics. Metaproteomic analysis can help us dig deeper into the nasal microbiomes and provide new targets and ideas for clinical diagnosis and treatment of many nasal dysbiosis-related diseases.

Functional and Promiscuity Studies of Three-Residue Cyclophane Forming Enzymes Show Nonnative C-C Cross-Linked Products and Leader-Dependent Cyclization

Enzymes catalyzing peptide macrocyclization are important biochemical tools in drug discovery. The three-residue cyclophane-forming enzymes (3-CyFEs) are an emerging family of post-translational modifying enzymes that catalyze the formation of three-residue peptide cyclophanes. In this report, we introduce three additional 3-CyFEs, including ChlB, WnsB, and FnnB, that catalyze cyclophane formation on Tyr, Trp, and Phe, respectively. To understand the promiscuity of these enzymes and those previously reported (MscB, HaaB, and YxdB), we tested single amino acid substitutions at the three-residue motif of modification (Ω1X2X3, Ω1 = aromatic). Collectively, we observe that substrate promiscuity is observed at the Ω1 and X2 positions, but a greater specificity is observed for the X3 residue. Two nonnative cyclophane products were characterized showing a Phe-C3 to Arg-Cβ and His-C2 to Pro-Cβ cross-links, respectively. We also tested the leader dependence of selected 3-CyFEs and show that a predicted helix region is important for cyclophane formation. These results demonstrate the biocatalytic potential of these maturases and allow rational design of substrates to obtain a diverse array of genetically encoded 3-residue cyclophanes.

Genome-wide identification and in silico characterization of major RNAi gene families in date palm (Phoenix dactylifera)

BACKGROUND

Dates contain various minerals that are essential for good health. The major RNA interference (RNAi) gene families play a vital role in plant growth and development by controlling the expression of protein-coding genes against different biotic and abiotic stresses. However, these gene families for date palm are not yet studied. Therefore, this study has explored major RNAi genes and their characteristics in date palm.

RESULTS

We have identified 4 PdDCLs, 7 PdAGOs, and 3 PdRDRs as RNAi proteins from the date palm genome by using AtRNAi genes as query sequences in BLASTp search. Domain analysis of predicted RNAi genes has revealed the Helicase_C, Dicer_dimer, PAZ, RNase III, and Piwi domains that are associated with the gene silencing mechanisms. Most PdRNAi proteins have been found in the nucleus and cytosol associated with the gene silencing actions. The gene ontology (GO) enrichment analysis has revealed some important GO terms including RNA interference, dsRNA fragmentation, and ribonuclease_III activity that are related to the protein-coding gene silencing mechanisms. Gene regulatory network (GRN) analysis has identified PAZ and SNF2 as the transcriptional regulators of PdRNAi genes. Top-ranked 10 microRNAs including Pda-miR156b, Pda-miR396a, Pda-miR166a, Pda-miR167d, and Pda-miR529a have been identified as the key post-transcriptional regulators of PdRNAi genes that are associated with different biotic/abiotic stresses. The cis-acting regulatory element analysis of PdRNAi genes has detected some vital cis-acting elements including ABRE, MBS, MYB, MYC, Box-4, G-box, I-box, and STRE that are linked with different abiotic stresses.

CONCLUSION

The results of this study might be valuable resources for the improvement of different characteristics in date palm by further studies in wet-lab.

ZP2 cleavage blocks polyspermy by modulating the architecture of the egg coat

Following the fertilization of an egg by a single sperm, the egg coat or zona pellucida (ZP) hardens and polyspermy is irreversibly blocked. These events are associated with the cleavage of the N-terminal region (NTR) of glycoprotein ZP2, a major subunit of ZP filaments. ZP2 processing is thought to inactivate sperm binding to the ZP, but its molecular consequences and connection with ZP hardening are unknown. Biochemical and structural studies show that cleavage of ZP2 triggers its oligomerization. Moreover, the structure of a native vertebrate egg coat filament, combined with AlphaFold predictions of human ZP polymers, reveals that two protofilaments consisting of type I (ZP3) and type II (ZP1/ZP2/ZP4) components interlock into a left-handed double helix from which the NTRs of type II subunits protrude. Together, these data suggest that oligomerization of cleaved ZP2 NTRs extensively cross-links ZP filaments, rigidifying the egg coat and making it physically impenetrable to sperm.

Complete genome sequence of deformed wing virus and black queen cell virus isolated from honeybees (Apis mellifera) in Argentina

We report the complete genome sequence of deformed wing virus and black queen cell virus isolated from Argentinean's honeybees. These sequence data will be valuable for future research on the viral variants present in the country and the development of strategies to control the spread of these viruses in apiaries.

bacLIFE: a user-friendly computational workflow for genome analysis and prediction of lifestyle-associated genes in bacteria

Bacteria have an extensive adaptive ability to live in close association with eukaryotic hosts, exhibiting detrimental, neutral or beneficial effects on host growth and health. However, the genes involved in niche adaptation are mostly unknown and their functions poorly characterized. Here, we present bacLIFE ( https://github.com/Carrion-lab/bacLIFE ) a streamlined computational workflow for genome annotation, large-scale comparative genomics, and prediction of lifestyle-associated genes (LAGs). As a proof of concept, we analyzed 16,846 genomes from the Burkholderia/Paraburkholderia and Pseudomonas genera, which led to the identification of hundreds of genes potentially associated with a plant pathogenic lifestyle. Site-directed mutagenesis of 14 of these predicted LAGs of unknown function, followed by plant bioassays, showed that 6 predicted LAGs are indeed involved in the phytopathogenic lifestyle of Burkholderia plantarii and Pseudomonas syringae pv. phaseolicola. These 6 LAGs encompassed a glycosyltransferase, extracellular binding proteins, homoserine dehydrogenases and hypothetical proteins. Collectively, our results highlight bacLIFE as an effective computational tool for prediction of LAGs and the generation of hypotheses for a better understanding of bacteria-host interactions.

Chromosome-level genome assembly of Platycarya strobilacea

Platycarya strobilacea belongs to the walnut family (Juglandaceae), is commonly known as species endemic to East Asia, and is an ecologically important, wind pollinated, woody deciduous tree. To facilitate this ancient tree for the ecological value and conservation of this ancient tree, we report a new high-quality genome assembly of P. strobilacea. The genome size was 677.30 Mb, with a scaffold N50 size of 45,791,698 bp, and 98.43% of the assembly was anchored to 15 chromosomes. We annotated 32,246 protein-coding genes in the genome, of which 96.30% were functionally annotated in six databases. This new high-quality assembly of P. strobilacea provide valuable resource for the phylogenetic and evolutionary analysis of the walnut family and angiosperm.

Integrative systems biology of wheat susceptibility to Fusarium graminearum uncovers a conserved gene regulatory network and identifies master regulators targeted by fungal core effectors

BACKGROUND

Plant diseases are driven by an intricate set of defense mechanisms counterbalanced by the expression of host susceptibility factors promoted through the action of pathogen effectors. In spite of their central role in the establishment of the pathology, the primary components of plant susceptibility are still poorly understood and challenging to trace especially in plant-fungal interactions such as in Fusarium head blight (FHB) of bread wheat. Designing a system-level transcriptomics approach, we leveraged the analysis of wheat responses from a susceptible cultivar facing Fusarium graminearum strains of different aggressiveness and examined their constancy in four other wheat cultivars also developing FHB.

RESULTS

In this study, we describe unexpected differential expression of a conserved set of transcription factors and an original subset of master regulators were evidenced using a regulation network approach. The dual-integration with the expression data of pathogen effector genes combined with database mining, demonstrated robust connections with the plant molecular regulators and identified relevant candidate genes involved in plant susceptibility, mostly able to suppress plant defense mechanisms. Furthermore, taking advantage of wheat cultivars of contrasting susceptibility levels, a refined list of 142 conserved susceptibility gene candidates was proposed to be necessary host's determinants for the establishment of a compatible interaction.

CONCLUSIONS

Our findings emphasized major FHB determinants potentially controlling a set of conserved responses associated with susceptibility in bread wheat. They provide new clues for improving FHB control in wheat and also could conceivably leverage further original researches dealing with a broader spectrum of plant pathogens.

TORC1 is an essential regulator of nutrient-controlled proliferation and differentiation in Leishmania

Leishmania parasites undergo differentiation between various proliferating and non-dividing forms to adapt to changing host environments. The mechanisms that link environmental cues with the parasite's developmental changes remain elusive. Here, we report that Leishmania TORC1 is a key environmental sensor for parasite proliferation and differentiation in the sand fly-stage promastigotes and for replication of mammalian-stage amastigotes. We show that Leishmania RPTOR1, interacts with TOR1 and LST8, and identify new parasite-specific proteins that interact in this complex. We investigate TORC1 function by conditional deletion of RPTOR1, where under nutrient-rich conditions RPTOR1 depletion results in decreased protein synthesis and growth, G1 cell cycle arrest and premature differentiation from proliferative promastigotes to non-dividing mammalian-infective metacyclic forms. These parasites are unable to respond to nutrients to differentiate into proliferative retroleptomonads, which are required for their blood-meal induced amplification in sand flies and enhanced mammalian infectivity. We additionally show that RPTOR1-/- metacyclic promastigotes develop into amastigotes but do not proliferate in the mammalian host to cause pathology. RPTOR1-dependent TORC1 functionality represents a critical mechanism for driving parasite growth and proliferation.

iNucRes-ASSH: Identifying nucleic acid-binding residues in proteins by using self-attention-based structure-sequence hybrid neural network

Interaction between proteins and nucleic acids is crucial to many cellular activities. Accurately detecting nucleic acid-binding residues (NABRs) in proteins can help researchers better understand the interaction mechanism between proteins and nucleic acids. Structure-based methods can generally make more accurate predictions than sequence-based methods. However, the existing structure-based methods are sensitive to protein conformational changes, causing limited generalizability. More effective and robust approaches should be further explored. In this study, we propose iNucRes-ASSH to identify nucleic acid-binding residues with a self-attention-based structure-sequence hybrid neural network. It improves the generalizability and robustness of NABR prediction from two levels: residue representation and prediction model. Experimental results show that iNucRes-ASSH can predict the nucleic acid-binding residues even when the experimentally validated structures are unavailable and outperforms five competing methods on a recent benchmark dataset and a widely used test dataset.

Molecular Identification and Characterization of Hevein Antimicrobial Peptide Genes in Two-Row and Six-Row Cultivars of Barley (Hordeum vulgare L.)

Heveins are one of the most important groups of plant antimicrobial peptides. So far, various roles in plant growth and development and in response to biotic and abiotic stresses have reported for heveins. The present study aimed to identify and characterize the hevein genes in two-row and six-row cultivars of barley. In total, thirteen hevein genes were identified in the genome of two-row and six-row cultivars of barley. The identified heveins were identical in two-row and six-row cultivars of barley and showed a high similarity with heveins from other plant species. The hevein coding sequences produced open reading frames (ORFs) ranged from 342 to 1002 bp. Most of the identified hevein genes were intronless, and the others had only one intron. The hevein ORFs produced proteins ranged from 113 to 333 amino acids. Search for conserved functional domains showed CBD and LYZ domains in barley heveins. All barley heveins comprised extracellular signal peptides ranged from 19 to 35 amino acids. The phylogenetic analysis divided barley heveins into two groups. The promoter analysis showed regulatory elements with different frequencies between two-row and six-row cultivars. These cis-acting elements included elements related to growth and development, hormone response, and environmental stresses. The expression analysis showed high expression level of heveins in root and reproductive organs of both two-row and six-row cultivars. The expression analysis also showed that barley heveins is induced by both biotic and abiotic stresses. The results of antimicrobial activity prediction showed the highest antimicrobial activity in CBD domain of barley heveins. The findings of the current study can improve our knowledge about the role of hevein genes in plant and can be used for future studies.

Bacterial degradation of ctenophore Mnemiopsis leidyi organic matter

Blooms of gelatinous zooplankton, an important source of protein-rich biomass in coastal waters, often collapse rapidly, releasing large amounts of labile detrital organic matter (OM) into the surrounding water. Although these blooms have the potential to cause major perturbations in the marine ecosystem, their effects on the microbial community and hence on the biogeochemical cycles have yet to be elucidated. We conducted microcosm experiments simulating the scenario experienced by coastal bacterial communities after the decay of a ctenophore (Mnemiopsis leidyi) bloom in the northern Adriatic Sea. Within 24 h, a rapid response of bacterial communities to the M. leidyi OM was observed, characterized by elevated bacterial biomass production and respiration rates. However, compared to our previous microcosm study of jellyfish (Aurelia aurita s.l.), M. leidyi OM degradation was characterized by significantly lower bacterial growth efficiency, meaning that the carbon stored in the OM was mostly respired. Combined metagenomic and metaproteomic analysis indicated that the degradation activity was mainly performed by Pseudoalteromonas, producing a large amount of proteolytic extracellular enzymes and exhibiting high metabolic activity. Interestingly, the reconstructed metagenome-assembled genome (MAG) of Pseudoalteromonas phenolica was almost identical (average nucleotide identity >99%) to the MAG previously reconstructed in our A. aurita microcosm study, despite the fundamental genetic and biochemical differences of the two gelatinous zooplankton species. Taken together, our data suggest that blooms of different gelatinous zooplankton are likely triggering a consistent response from natural bacterial communities, with specific bacterial lineages driving the remineralization of the gelatinous OM.IMPORTANCEJellyfish blooms are increasingly becoming a recurring seasonal event in marine ecosystems, characterized by a rapid build-up of gelatinous biomass that collapses rapidly. Although these blooms have the potential to cause major perturbations, their impact on marine microbial communities is largely unknown. We conducted an incubation experiment simulating a bloom of the ctenophore Mnemiopsis leidyi in the Northern Adriatic, where we investigated the bacterial response to the gelatinous biomass. We found that the bacterial communities actively degraded the gelatinous organic matter, and overall showed a striking similarity to the dynamics previously observed after a simulated bloom of the jellyfish Aurelia aurita s.l. In both cases, we found that a single bacterial species, Pseudoalteromonas phenolica, was responsible for most of the degradation activity. This suggests that blooms of different jellyfish are likely to trigger a consistent response from natural bacterial communities, with specific bacterial species driving the remineralization of gelatinous biomass.

Optimized bacterial community characterization through full-length 16S rRNA gene sequencing utilizing MinION nanopore technology

BACKGROUND

Accurate identification of bacterial communities is crucial for research applications, diagnostics, and clinical interventions. Although 16S ribosomal RNA (rRNA) gene sequencing is a widely employed technique for bacterial taxonomic classification, it often results in misclassified or unclassified bacterial taxa. This study sought to refine the full-length 16S rRNA gene sequencing protocol using the MinION sequencer, focusing on the V1-V9 regions. Our methodological enquiry examined several factors, including the number of PCR amplification cycles, choice of primers and Taq polymerase, and specific sequence databases and workflows employed. We used a microbial standard comprising eight bacterial strains (five gram-positive and three gram-negative) in known proportions as a validation control.

RESULTS

Based on the MinION protocol, we employed the microbial standard as the DNA template for the 16S rRNA gene amplicon sequencing procedure. Our analysis showed that an elevated number of PCR amplification cycles introduced PCR bias, and the selection of Taq polymerase and primer sets significantly affected the subsequent analysis. Bacterial identification at genus level demonstrated Pearson correlation coefficients ranging from 0.73 to 0.79 when assessed using BugSeq, Kraken-Silva and EPI2ME-16S workflows. Notably, the EPI2ME-16S workflow exhibited the highest Pearson correlation with the microbial standard, minimised misclassification, and increased alignment accuracy. At the species taxonomic level, the BugSeq workflow was superior, with a Pearson correlation coefficient of 0.92.

CONCLUSIONS

These findings emphasise the importance of careful selection of PCR settings and a well-structured analytical framework for 16S rRNA full-length gene sequencing. The results showed a robust correlation between the predicted and observed bacterial abundances at both the genus and species taxonomic levels, making these findings applicable across diverse research contexts and with clinical utility for reliable pathogen identification.

Telomere-to-telomere gapless genome assembly of the Chinese sea bass (Lateolabrax maculatus)

Chinese sea bass (Lateolabrax maculatus) is a highly sought-after commercial seafood species in Asian regions due to its excellent nutritional value. With the rapid advancement of bioinformatics, higher standards for genome analysis compared to previously published reference genomes are now necessary. This study presents a gapless assembly of the Chinese sea bass genome, which has a length of 632.75 Mb. The sequences were assembled onto 24 chromosomes with a coverage of over 99% (626.61 Mb), and telomeres were detected on 34 chromosome ends. Analysis using Merqury indicated a high level of accuracy, with an average consensus quality value of 54.25. The ONT ultralong and PacBio HiFi data were aligned with the assembly using minimap2, resulting in a mapping rate of 99.9%. The study also identified repeating elements in 20.90% (132.25 Mb) of the genome and inferred 22,014 protein-coding genes. These results establish meaningful groundwork for exploring the evolution of the Chinese sea bass genome and advancing molecular breeding techniques.