UPIMAPI, reCOGnizer and KEGGCharter: bioinformatics tools for functional annotation and visualization of (meta)-omics datasets

Outer membrane vesicles of carbapenem-resistant clinical Acinetobacter baumannii isolates protect both the vesicle-producing bacteria and non-resistant bacteria against carbapenems

Infections caused by carbapenem-resistant Acinetobacter baumannii (A. baumannii; CRAb) are associated with high patient morbidity and mortality. The serious threat for human health imposed by CRAb was recently underscored by identification of close-to-untouchable carbapenem- and tetracycline-resistant isolates. Since outer membrane vesicles (OMVs) of Gram-negative bacteria may contribute to antimicrobial resistance, our present study was aimed at investigating OMVs produced by the first two carbapenem- and tetracycline-resistant A. baumannii isolates in Europe. These isolates, denoted CRAb1 and CRAb2, contain large, nearly identical plasmids that specify multiple resistances. Both isolates produce OMVs that were analyzed by differential light scattering, transmission electron microscopy and proteomics. By comparison with OMVs from the plasmid-free non-carbapenem-resistant A. baumannii isolate Ab1, which is an isogenic ancestor of the CRAb1 isolate, we show that plasmid carriage by the CRAb1 and CRAb2 isolates leads to an increased OMV size that is accompanied by increased diversity of the OMV proteome. Our analyses show that OMVs from CRAb1 and CRAb2 are major reservoirs of proteins involved in antimicrobial resistance, including the plasmid-encoded carbapenemases New Delhi metallo-β-lactamase-1 (NDM-1), and carbapenem-hydrolyzing oxacillinase OXA-97 (OXA-97). Here we report that these OMV-borne carbapenemases hydrolyze imipenem and protect otherwise carbapenem-sensitive A. baumannii and Escherichia coli (E. coli) isolates against this antibiotic. In conclusion, our findings demonstrate that OMVs from highly drug-resistant CRAb confer protection against last-resort antibiotics to non-resistant bacterial pathogens.

Comparison of phage and plasmid populations in the gut microbiota between Parkinson's disease patients and controls

The aging population worldwide is on the rise, leading to a higher number of Parkinson's disease (PD) cases each year. PD is presently the second most prevalent neurodegenerative disease, affecting an estimated 7-10 million individuals globally. This research aimed to identify mobile genetic elements in human fecal samples using a shotgun metagenomics approach. We identified over 44,000 plasmid contigs and compared plasmid populations between PD patients (n = 68) and controls (n = 68). Significant associations emerged between groups (control vs PD) based on plasmid alpha and beta diversity. Moreover, the gene populations present on plasmids displayed marked differences in alpha and beta diversity between PD patients and controls. We identified a considerable number of phage contigs that were differentially abundant in the two groups. We also developed a predictive machine learning model based on phage abundance data, achieving a mean Area Under the Curve (AUC) of 0.74 with a standard deviation of 0.105 and a mean F1 score of 0.68 with a standard deviation of 0.14 across cross-validation folds, indicating moderate discriminatory power. Additionally, when tested on external data, the model yielded an AUC of 0.74 and an F1 score of 0.8, further demonstrating the predictive potential of phage populations in Parkinson's disease. Further, we improved the continuity and identification of the protein coding regions of the phage contigs by implementing alternative genetic codes.

A conserved terpene cyclase gene in Sanghuangporus for abscisic acid-related sesquiterpenoid biosynthesis

BACKGROUND

The medicinal mushroom Sanghuangporus is renowned in East Asia for its potent therapeutic properties, attributed in part to its bioactive sesquiterpenoids. However, despite their recognized medicinal potential, the biosynthetic pathways and specific enzymes responsible for sesquiterpenoid production in Sanghuangporus remain unexplored, limiting opportunities to optimize their medicinal applications.

RESULTS

Sesquiterpenoids from four Sanghuangporus species were extracted through targeted isolation using mass spectrometry (MS)-based metabolomics, resulting in the discovery of six known abscisic acid-related compounds and one new compound, whose structure was determined through spectroscopic and computational analysis. We employed a natural product genome mining approach to identify a putative biosynthetic gene cluster (BGC) containing a sesquiterpene synthase gene, ancA, associated with the detected compounds. Biosynthetic pathways for these compounds were proposed based on an integrative approach combining BGC analysis and MS2 fragment-based dereplication. Further analyses revealed that the gene content and synteny of the ancA BGC are relatively well-conserved across Sanghuangporus species but less so outside the genus.

CONCLUSIONS

A sesquiterpene synthase gene, its associated BGC, and the biosynthetic pathway for a group of detected abscisic acid-related sesquiterpenoids in Sanghuangporus were predicted through genomic and metabolic data analyses. This study addresses a critical gap in understanding the genetic basis of sesquiterpenoid production in Sanghuangporus and offers insights for future research on engineering metabolic pathways to enhance sesquiterpenoid production for medicinal use.

Transcriptional Responses of Lacticaseibacillus rhamnosus to TNFα, IL-6, IL-8, and IL-10 Cytokines

The interaction between gut microbiota and the host immune system is a complex and understudied field, with cytokines like TNFα, IL-6, IL-8, and IL-10 playing pivotal roles. Commensal bacteria, including lactobacilli, respond to these cytokines through adaptive mechanisms that support their survival and function within the gut. While the influence of cytokines on pathogenic bacteria is well documented, their impact on commensal bacteria, particularly lactobacilli, remains underexplored. This study investigates the transcriptional responses of Lacticaseibacillus rhamnosus strains K32 and R19-3 to various cytokines using next-generation RNA sequencing (RNA-seq). Our findings reveal that cytokines, especially IL-8 and IL-10, significantly alter the L. rhamnosus transcriptome, affecting genes involved in carbohydrate metabolism, stress response, and transcriptional regulation. Notably, IL-8 and IL-10 induce a significant downregulation of genes related to the phosphotransferase system, suggesting a reduction in metabolic activity in response to inflammatory signals. This study unveils a previously unexplored aspect of L. rhamnosus adaptation, highlighting its intricate response to cytokine signals. By modulating gene expression, L. rhamnosus may mitigate the adverse effects of inflammation and promote gut health. These insights could inform the development of targeted probiotic therapies for inflammatory bowel disease (IBD) and other conditions with altered cytokine levels. Our results suggest that co-evolution between a host and gut microbiota enables bacteria to respond to specific cytokines through gene expression changes, revealing a unique and underexplored facet of the interaction between commensal bacteria and the host organism.

Transcriptomic Response of Rhizobium leguminosarum to Acidic Stress and Nutrient Limitation Is Versatile and Substantially Influenced by Extrachromosomal Gene Pool

Multipartite genomes are thought to confer evolutionary advantages to bacteria by providing greater metabolic flexibility in fluctuating environments and enabling rapid adaptation to new ecological niches and stress conditions. This genome architecture is commonly found in plant symbionts, including nitrogen-fixing rhizobia, such as Rhizobium leguminosarum bv. trifolii TA1 (RtTA1), whose genome comprises a chromosome and four extrachromosomal replicons (ECRs). In this study, the transcriptomic responses of RtTA1 to partial nutrient limitation and low acidic pH were analyzed using high-throughput RNA sequencing. RtTA1 growth under these conditions resulted in the differential expression of 1035 to 1700 genes (DEGs), which were assigned to functional categories primarily related to amino acid and carbohydrate metabolism, ribosome and cell envelope biogenesis, signal transduction, and transcription. These results highlight the complexity of the bacterial response to stress. Notably, the distribution of DEGs among the replicons indicated that ECRs played a significant role in the stress response. The transcriptomic data align with the Rhizobium pangenome analysis, which revealed an over-representation of functional categories related to transport, metabolism, and regulatory functions on ECRs. These findings confirm that ECRs contribute substantially to the ability of rhizobia to adapt to challenging environmental conditions.

MOSCA 2.0: A bioinformatics framework for metagenomics, metatranscriptomics and metaproteomics data analysis and visualization

The analysis of meta-omics data requires the utilization of several bioinformatics tools and proficiency in informatics. The integration of multiple meta-omics data is even more challenging, and the outputs of existing bioinformatics solutions are not always easy to interpret. Here, we present a meta-omics bioinformatics pipeline, Meta-Omics Software for Community Analysis (MOSCA), which aims to overcome these limitations. MOSCA was initially developed for analysing metagenomics (MG) and metatranscriptomics (MT) data. Now, it also performs MG and metaproteomics (MP) integrated analysis, and MG/MT analysis was upgraded with an additional iterative binning step, metabolic pathways mapping, and several improvements regarding functional annotation and data visualization. MOSCA handles raw sequencing data and mass spectra and performs pre-processing, assembly, annotation, binning and differential gene/protein expression analysis. MOSCA shows taxonomic and functional analysis in large tables, performs metabolic pathways mapping, generates Krona plots and shows gene/protein expression results in heatmaps, improving omics data visualization. MOSCA is easily run from a single command while also providing a web interface (MOSGUITO). Relevant features include an extensive set of customization options, allowing tailored analyses to suit specific research objectives, and the ability to restart the pipeline from intermediary checkpoints using alternative configurations. Two case studies showcased MOSCA results, giving a complete view of the anaerobic microbial communities from anaerobic digesters and insights on the role of specific microorganisms. MOSCA represents a pivotal advancement in meta-omics research, offering an intuitive, comprehensive, and versatile solution for researchers seeking to unravel the intricate tapestry of microbial communities.

Metagenome-assembled microbial genomes from Parkinson's disease fecal samples

The human gut microbiome composition has been linked to Parkinson's disease (PD). However, knowledge of the gut microbiota on the genome level is still limited. Here we performed deep metagenomic sequencing and binning to build metagenome-assembled genomes (MAGs) from 136 human fecal microbiomes (68 PD samples and 68 control samples). We constructed 952 non-redundant high-quality MAGs and compared them between PD and control groups. Among these MAGs, there were 22 different genomes of Collinsella and Prevotella, indicating high variability of those genera in the human gut environment. Microdiversity analysis indicated that Ruminococcus bromii was statistically significantly (p < 0.002) more diverse on the strain level in the control samples compared to the PD samples. In addition, by clustering all genes and performing presence-absence analysis between groups, we identified several control-specific (p < 0.05) related genes, such as speF and Fe-S oxidoreductase. We also report detailed annotation of MAGs, including Clusters of Orthologous Genes (COG), Cas operon type, antiviral gene, prophage, and secondary metabolites biosynthetic gene clusters, which can be useful for providing a reference for future studies.

Blending and separating dynamics of RNA-binding proteins develop architectural splicing networks spreading throughout the nucleus

The eukaryotic nucleus has a highly organized structure. Although the spatiotemporal arrangement of spliceosomes on nascent RNA drives splicing, the nuclear architecture that directly supports this process remains unclear. Here, we show that RNA-binding proteins (RBPs) assembled on RNA form meshworks in human and mouse cells. Core and accessory RBPs in RNA splicing make two distinct meshworks adjacently but distinctly distributed throughout the nucleus. This is achieved by mutual exclusion dynamics between the charged and uncharged intrinsically disordered regions (IDRs) of RBPs. These two types of meshworks compete for spatial occupancy on pre-mRNA to regulate splicing. Furthermore, the optogenetic enhancement of the RBP meshwork causes aberrant splicing, particularly of genes involved in neurodegeneration. Genetic mutations associated with neurodegenerative diseases are often found in the IDRs of RBPs, and cells harboring these mutations exhibit impaired meshwork formation. Our results uncovered the spatial organization of RBP networks to drive RNA splicing.

Biocontrol potential of Pseudomonas protegens ML15 against Botrytis cinerea causing gray mold on postharvest tomato (Solanum lycopersicum var. cerasiforme)

Gray mold, caused by Botrytis cinerea is a major cause of post-harvest rot of fresh fruits and vegetables. The utilization of selected microorganisms as biocontrol agents is a promising alternative to effectively control gray mold on tomatoes. The current study was conducted to explore potential biocontrol mechanisms of the Pseudomonas strain to control infections on post-harvest tomatoes. Among the 8 tested bacterial isolates, Pseudomonas protegens ML15 demonstrated antagonistic activity to Botrytis cinerea. Moreover, P. protegens ML15 exhibited the production of siderophores, hydrogen cyanide, ammonia, exopolysaccharides, lipase, biosurfactant, 2,4-diacetylphloroglucinol, and several other antifungal compounds, such as 1-tetradecanol, cyclododecane, 2,4-di-tert-butylphenol, and 2-methyl-1-hexadecanol. A comprehensive genomic analysis of P. protegens ML15 unravels 18 distinct genetic regions with the potential for biosynthesizing secondary metabolites, known for their pivotal role in biocontrol responses against plant pathogens. In vivo, experiments showed that both culture suspension and cell-free supernatant of P. protegens ML15 significantly reduced fungal growth (53.0 ± 0.63%) and mitigated disease development (52.8 ± 1.5%) in cherry tomatoes at four days post-B. cinerea inoculation. During the infection, the application of P. protegens ML15 resulted in the augmentation of total antioxidant, phenolic content, and ascorbic acids content. Thus, our results suggested that P. protegens ML15's role as a biocontrol agent against B. cinerea-induced postharvest tomato decay achieved through the secretion of antifungal substances, induction of tomato defense responses, and inhibition of mycelial growth of B. cinerea. These findings provide a significant contribution to the ongoing search for alternative, eco-friendly methods of controlling gray mold in fresh products. The utilization of P. protegens ML15 as a biocontrol agent could help to reduce the reliance on chemical fungicides and promote sustainable agriculture practices.

Halanaerobium polyolivorans sp. nov.-A Novel Halophilic Alkalitolerant Bacterium Capable of Polyol Degradation: Physiological Properties and Genomic Insights

A search for the microorganisms responsible for the anaerobic degradation of osmoprotectants in soda lakes resulted in the isolation of a novel halophilic and alkalitolerant strain, designated Z-7514T. The cells were Gram-stain-negative and non-endospore-forming rods. Optimal growth occurs at 1.6-2.1 M Na+, pH 8.0-8.5, and 31-35 °C. The strain utilized mainly sugars, low molecular polyols, and ethanolamine as well. The G+C content of the genomic DNA of strain Z-7514T was 33.3 mol%. Phylogenetic and phylogenomic analyses revealed that strain Z-7514T belongs to the genus Halanaerobium. On the basis of phenotypic properties and the dDDH and ANI values with close validly published species, it was proposed to evolve strain Z-7514T within the genus Halanaerobium into novel species, for which the name Halanaerobium polyolivorans sp. nov. was proposed. The type strain was Z-7514T (=KCTC 25405T = VKM B-3577T). For species of the genus Halanaerobium, the utilization of ethylene glycol, propylene glycol, and ethanolamine were shown for the first time. The anaerobic degradation of glycols and ethanolamine by strain Z-7514T may represent a novel metabiotic pathway within the alkaliphilic microbial community. Based on a detailed genomic analysis, the main pathways of catabolism of most of the used substrates have been identified.

Cross-phyla protein annotation by structural prediction and alignment

BACKGROUND

Protein annotation is a major goal in molecular biology, yet experimentally determined knowledge is typically limited to a few model organisms. In non-model species, the sequence-based prediction of gene orthology can be used to infer protein identity; however, this approach loses predictive power at longer evolutionary distances. Here we propose a workflow for protein annotation using structural similarity, exploiting the fact that similar protein structures often reflect homology and are more conserved than protein sequences.

RESULTS

We propose a workflow of openly available tools for the functional annotation of proteins via structural similarity (MorF: MorphologFinder) and use it to annotate the complete proteome of a sponge. Sponges are highly relevant for inferring the early history of animals, yet their proteomes remain sparsely annotated. MorF accurately predicts the functions of proteins with known homology in [Formula: see text] cases and annotates an additional [Formula: see text] of the proteome beyond standard sequence-based methods. We uncover new functions for sponge cell types, including extensive FGF, TGF, and Ephrin signaling in sponge epithelia, and redox metabolism and control in myopeptidocytes. Notably, we also annotate genes specific to the enigmatic sponge mesocytes, proposing they function to digest cell walls.

CONCLUSIONS

Our work demonstrates that structural similarity is a powerful approach that complements and extends sequence similarity searches to identify homologous proteins over long evolutionary distances. We anticipate this will be a powerful approach that boosts discovery in numerous -omics datasets, especially for non-model organisms.

Multi-omics insights into the interplay between gut microbiota and colorectal cancer in the "microworld" age

Colorectal cancer (CRC) is a multifactorial heterogeneous disease largely due to both genetic predisposition and environmental factors including the gut microbiota, a dynamic microbial ecosystem inhabiting the gastrointestinal tract. Elucidation of the molecular mechanisms by which the gut microbiota interacts with the host may contribute to the pathogenesis, diagnosis, and promotion of CRC. However, deciphering the influence of genetic variants and interactions with the gut microbial ecosystem is rather challenging. Despite recent advancements in single omics analysis, the application of multi-omics approaches to integrate multiple layers of information in the microbiome and host to introduce effective prevention, diagnosis, and treatment strategies is still in its infancy. Here, we integrate host- and microbe-based multi-omics studies, respectively, to provide a strategy to explore potential causal relationships between gut microbiota and colorectal cancer. Specifically, we summarize the recent multi-omics studies such as metagenomics combined with metabolomics and metagenomics combined with genomics. Meanwhile, the sample size and sample types commonly used in multi-omics research, as well as the methods of data analysis, were also generalized. We highlight multiple layers of information from multi-omics that need to be verified by different types of models. Together, this review provides new insights into the clinical diagnosis and treatment of colorectal cancer patients.

Meta4P: A User-Friendly Tool to Parse Label-Free Quantitative Metaproteomic Data and Taxonomic/Functional Annotations

We present Meta4P (MetaProteins-Peptides-PSMs Parser), an easy-to-use bioinformatic application designed to integrate label-free quantitative metaproteomic data with taxonomic and functional annotations. Meta4P can retrieve, filter, and process identification and quantification data from three levels of inputs (proteins, peptides, PSMs) in different file formats. Abundance data can be combined with taxonomic and functional information and aggregated at different and customizable levels, including taxon-specific functions and pathways. Meta4P output tables, available in various formats, are ready to be used as inputs for downstream statistical analyses. This user-friendly tool is expected to provide a useful contribution to the field of metaproteomic data analysis, helping make it more manageable and straightforward.

Genomic Analysis of the Rare Slightly Halophilic Myxobacterium "Paraliomyxa miuraensis" SMH-27-4, the Producer of the Antibiotic Miuraenamide A

Halophilic/halotolerant myxobacteria are extremely rare bacteria but an important source of novel bioactive secondary metabolites as drug leads. A slightly halophilic myxobacterium, "Paraliomyxa miuraensis" SMH-27-4, the producer of the antifungal antibiotic miuraenamide A, was considered to represent a novel genus. This study aimed to use the whole-genome sequence of this difficult-to-culture bacterium to provide genomic evidence supporting its taxonomy and to explore its potential as a novel secondary metabolite producer and its predicted gene functions. The draft genome was sequenced and de novo assembled into 164 contigs (11.8 Mbp). The 16S rRNA gene sequence-based and genome sequence-based phylogenetic analyses supported that this strain represents a novel genus of the family Nannocystaceae. Seventeen biosynthetic gene clusters (BGCs) were identified, and only five of them show some degree of similarity with the previously annotated BGCs, suggesting the great potential of producing novel secondary metabolites. The comparative genomic analysis within the family Nannocystaceae revealed the distribution of its members' gene functions. This study unveiled the novel genomic features and potential of the secondary metabolite production of this myxobacterium.

A New Face of the Old Gene: Deletion of the PssA, Encoding Monotopic Inner Membrane Phosphoglycosyl Transferase in Rhizobium leguminosarum, Leads to Diverse Phenotypes That Could Be Attributable to Downstream Effects of the Lack of Exopolysaccharide

The biosynthesis of subunits of rhizobial exopolysaccharides is dependent on glycosyltransferases, which are usually encoded by large gene clusters. PssA is a member of a large family of phosphoglycosyl transferases catalyzing the transfer of a phosphosugar moiety to polyprenol phosphate; thus, it can be considered as priming glycosyltransferase commencing synthesis of the EPS repeating units in Rhizobium leguminosarum. The comprehensive analysis of PssA protein features performed in this work confirmed its specificity for UDP-glucose and provided evidence that PssA is a monotopic inner membrane protein with a reentrant membrane helix rather than a transmembrane segment. The bacterial two-hybrid system screening revealed interactions of PssA with some GTs involved in the EPS octasaccharide synthesis. The distribution of differentially expressed genes in the transcriptome of the ΔpssA mutant into various functional categories indicated complexity of cell response to the deletion, which can mostly be attributed to the lack of exopolysaccharide and downstream effects caused by such deficiency. The block in the EPS biosynthesis at the pssA step, potentially leading to an increased pool of UDP-glucose, is likely to be filtered through to other pathways, and thus the absence of EPS may indirectly affect the expression of proteins involved in these pathways.

Draft Genomes Sequences of 11 Geodermatophilaceae Strains Isolated from Building Stones from New England and Indian Stone Ruins found at historic sites in Tamil Nadu, India

Metagenomic analysis of stone microbiome from samples collected in New England, USA and Tamil Nadu, India identified numerous Actinobacteria including Geodermatphilaceae. A culture-dependent approach was performed as a companion study with this culture-independent metagenomic analysis of these stone samples and resulted in the isolation of eleven Geodermatphilaceae strains (2 Geodermatophilus and 9 Blastococcus strains). The genomes of the 11 Geodermatphilaceae strains were sequenced and analyzed. The genomes for the two Geodermatophilus isolates, DF1-2 and TF2-6, were 4.45 and 4.75 Mb, respectively, while the Blastococcus genomes ranged in size from 3.98 to 5.48 Mb. Phylogenetic analysis, digital DNA:DNA hybridization (dDDH), and comparisons of the average nucleotide identities (ANI) suggest the isolates represent novel Geodermatophilus and Blastococcus species. Functional analysis of the Geodermatphilaceae genomes provides insight on the stone microbiome niche.

Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool

Genome-scale metabolic models (GEMs) are essential tools for in silico phenotype prediction and strain optimisation. The most straightforward GEMs reconstruction approach uses published models as templates to generate the initial draft, requiring further curation. Such an approach is used by BiGG Integration Tool (BIT), available for merlin users. This tool uses models from BiGG Models database as templates for the draft models. Moreover, BIT allows the selection between different template combinations. The main objective of this study is to assess the draft models generated using this tool and compare them BIT, comparing these to CarveMe models, both of which use the BiGG database, and curated models. For this, three organisms were selected, namely Streptococcus thermophilus, Xylella fastidiosa and Mycobacterium tuberculosis. The models’ variability was assessed using reactions and genes’ metabolic functions. This study concluded that models generated with BIT for each organism were differentiated, despite sharing a significant portion of metabolic functions. Furthermore, the template seems to influence the content of the models, though to a lower extent. When comparing each draft with curated models, BIT had better performances than CarveMe in all metrics. Hence, BIT can be considered a fast and reliable alternative for draft reconstruction for bacteria models.