mSystems最新文献

Genome-scale metabolic models (GSMMs) can mechanistically explain phenotypic differences among closely related bacterial strains. However, high-throughput multi-strain reconstructions of GSMMs are still challenging: reference-based methods inherit curated information while missing new contents; alternatively (universe-based), reference-free methods could cover strain-specific reactions, but they disregard curated information. Ideally, references should be curated pan-GSMMs for species (or genus), but their reconstruction is extremely demanding, making them still rare in the literature. Here, Gempipe is presented, a computational tool streamlining the multi-strain reconstruction and analysis of GSMMs, going through the production of a pan-GSMM. Its reconstruction method is hybrid; as an optional reference, GSMM is automatically expanded with extra reactions taken from a reference-free reconstruction. Gempipe also downloads, filters, and annotates genomes; performs in-depth gene recovery; annotates models' contents; and predicts strain-specific capabilities. The companion programming interface includes functions ranging from the (pan-)GSMMs' curation to the multi-strain analysis. Gempipe was validated using multi-strain data sets, showing improved accuracy when compared with state-of-the-art tools. Moreover, metabolic diversities within Limosilactobacillus reuteri were explored, grouping strains into metabolically coherent clusters and systematically predicting health-related metabolites' biosynthesis.IMPORTANCEAvailable genome-scale metabolic model (GSMM) reconstruction tools present major limitations in the context of multi-strain modeling. Gempipe surpasses these limitations by implementing a novel, hybrid reconstruction strategy. Not only does it produce more accurate strain-specific GSMMs, but it also produces pan-GSMMs when the only available reference is a manually curated model for a single strain, which is currently the most common case. With the vast availability of genome sequences, the high-throughput, multi-strain GSMM reconstruction and analysis approach provided by Gempipe will facilitate large-scale studies of exploration and bioprospecting of strain-level bacterial metabolic diversity, moving a step forward in strains' screening and rational selection.

Phototrophic Gemmatimonadota represent a unique group of phototrophic bacteria that acquired a complete set of photosynthetic genes via horizontal gene transfer and later evolved independently. Gemmatimonas (Gem.) phototrophica contains photosynthetic complexes with two concentric light-harvesting antenna rings that absorb at 816 and 868 nm, allowing it to better exploit the light conditions found deeper in the water column. The closely related species Gem. groenlandica, with highly similar photosynthetic genes, harvests infrared light using a single 860 nm absorption band. The cryo-electron microscopy structure of the Gem. groenlandica photosynthetic complex reveals that the outer antenna lacks monomeric bacteriochlorophylls, resulting in a smaller optical antenna cross-section. The Gem. groenlandica spectrum is red-shifted relative to Gem. phototrophica due to the formation of a H-bond enabled by a different rotamer conformation of αTrp³¹ in the outer ring. This H-bond forms with a neighboring bacteriochlorophyll and increases the intra-dimer exciton coupling, affecting the exciton localization probability within the rings and increasing exciton cooperativity between the complexes. The functional consequences of the spectral shift, caused solely by a subtle conformational change of a single residue, represent a novel mechanism in which phototrophic organisms adjust their antennae for particular light conditions and enable Gem. groenlandica to grow higher in the water column where more photons are available.IMPORTANCEThe photoheterotrophic species of the phylum Gemmatimonadota employ unique photosynthetic complexes with two concentric antenna rings around a central reaction center. In contrast to other phototrophic species, these organisms have not evolved any regulatory systems to control the expression of their photosynthetic apparatus under different light conditions. Despite the overall similarity, the complexes present in Gemmatimonas phototrophica and Gemmatimonas groenlandica have different absorption properties in the near-infrared region of the spectrum that make them more suitable for low or medium light, respectively. The main difference in absorption depends on the conformation of a single tryptophan residue that can form an H-bond with a neighboring bacteriochlorophyll. The presence or absence of this H-bond affects how the protein scaffold interacts with the bacteriochlorophylls, which in turn determines how light energy is transferred within and between the photosynthetic complexes.

The escalating crisis of global plastic pollution has prompted increasing efforts toward the identification of plastic-degrading microorganisms as environmentally sustainable solutions. Despite marine ecosystems being the most affected, the systematic exploration of culturable plastic-degrading microorganisms remains critically underexplored. Here, we established the largest marine microbial repository for plastic biodegradation, comprising 1,377 bacterial and 202 fungal strains isolated through optimized culture strategies targeting 13 plastic polymers. Methodological benchmarking revealed selective enrichment combined with carbon-supplemented dual-layer plating as the most effective isolation approach. Plastic substrate specificity drove phylogenetic divergence among degraders, with Bacillus altitudinis emerging as the dominant polyurethane (PU)-degrading lineage. Comprehensive functional screening identified five polyethylene terephthalate (PET)-degrading strains (Cerrena sp., Hortaea werneckii, Streptomyces badius, Streptomyces cinereoruber, Cladosporium sp.), five polyethylene (PE) degraders (Qipengyuania citrea, Gordonia mangrovi, Penicillium oxalicum, Penicillium aethiopicum, Streptomyces pluricolorescens), and 130 polyester-based PU-degrading strains spanning Bacillus, Psychrobacter, Priestia, and Cladosporium genera. This work provides both a foundational microbial resource for plastic biodegradation and establishes a methodological framework for the targeted isolation of plastic-degrading pure cultures.IMPORTANCEMarine plastic pollution presents a significant global challenge, with millions of tons entering the oceans each year, threatening marine life and ecosystem integrity. Microbial degradation offers a promising, sustainable solution by leveraging natural biological processes to break down plastics. This study makes a substantial contribution to the field by systematically examining 13 plastic types and establishing the largest known marine microbial resource for plastic degradation. Over 1,500 bacterial and fungal strains were isolated from diverse marine environments through optimized culturing strategies. Key microorganisms capable of degrading commonly used plastics-such as polyethylene terephthalate (bottles), polyurethane (foams), and polyethylene (packaging)-were identified. These findings lay a critical foundation for the development of microbial-based technologies to mitigate plastic pollution, offering scalable and environmentally friendly solutions to protect marine ecosystems.

The archaeal domain contains organisms that are well-adapted to extreme conditions and changes in their habitat. Post-transcriptional regulation plays a key role in environmental adaptation, including rapid molecular responses to stress conditions. To understand the importance of RNA-based post-transcriptional regulation for these processes, a comprehensive analysis of the presence and processing of regulatory RNAs, as well as their interactions with other RNAs and proteins, is indispensable. Here, we combine the analysis of several RNA sequencing approaches to reveal the presence of a set of novel non-coding RNAs (ncRNAs), their expression in various conditions, processing, and molecular interactions in the transcriptome of Sulfolobus acidocaldarius, a model organism for Archaea. We expand its annotation by 102 intergenic ncRNAs (sRNAs) and 1,048 antisense RNAs (asRNAs), add the location and motifs of over 6,000 transcript processing sites, and determine the interaction of transcripts with Sm-like archaeal proteins (SmAPs), known RNA chaperones involved in RNA-based regulatory systems. We determined the correlation between the expression patterns of asRNAs and their cognate mRNAs, suggesting transcript-based regulation patterns in gene expression, particularly in response to changing environmental conditions. Additionally, we observed differential binding preferences of SmAP1 and SmAP2 toward mRNA and ncRNAs, suggesting a distribution of regulating roles of these chaperones. Finally, we provide an overview of our post-transcriptional data analysis results, optimized for custom exploration, in the form of a web-based transcriptome atlas (https://vicentebr.github.io/Sulfolobus_atlas/).

Importance: Post‑transcriptional regulation is a key control layer in gene expression. Yet, resources integrating antisense RNAs (asRNAs), RNA processing sites, and RNA-protein interactions are scarce for archaeal organisms. Here, we combine multiple RNA‑seq strategies and RIP‑seq to expand the Sulfolobus acidocaldarius transcriptome with 1,048 asRNAs, thousands of transcript processing sites, and the interactomes of the essential RNA chaperones Sm-like archaeal protein (SmAP)1 and SmAP2. Integrating the novel generated data for the re‑analysis of heat‑shock transcriptomics reveals a consistent upregulation of asRNAs and antagonistic expression profiles with their cognate mRNAs. Moreover, our publicly accessible web atlas provides a community platform to explore these datasets and assist in the formulation of new hypotheses about archaeal RNA regulation.

Liquid biopsies are transforming oncology, enabling earlier diagnosis, dynamic treatment guidance, and personalized precision medicine, yet current approaches focusing mainly on circulating host cell-free DNA (cfDNA) neglect crucial information within co-existing microbial cell-free DNA (mcfDNA). This review argues for the combined potential of simultaneously analyzing host and microbial signals from samples like blood, specifically focusing on circulating tumor DNA (ctDNA) as the key host component. While ctDNA analysis is already used to guide treatment decisions, the detection of mcfDNA-although present in smaller amounts compared to total cfDNA-offers a distinct and complementary opportunity to identify disease-causing microbes and investigate the host-associated microbiome in the context of cancer. Leveraging machine learning strategies is essential to integrate these multi-view data sets and realize their full potential for enhancing liquid biopsy applications, particularly in early cancer detection.

In microbial ecosystems, metabolic interactions are key determinants of species' relative abundance and activity. Given the immense number of possible interactions in microbial communities, their experimental characterization is best guided by testable hypotheses generated through computational predictions. However, widely adopted software tools-such as those utilizing microbial co-occurrence-typically fail to highlight the pathways underlying these interactions. Bridging this gap will require methods that utilize microbial activity data to infer putative target pathways for experimental validation. In this study, we explored a novel approach by applying cross-species co-expression to predict interactions from microbial co-culture RNA-sequencing data. Specifically, we investigated the extent to which co-expression between genes and pathways of different bacterial species can predict competition, cross-feeding, and specialized metabolic interactions. Our analysis of the Mucin and Diet-based Minimal Microbiome (MDb-MM) data yielded results consistent with previous findings and demonstrated the method's potential to identify pathways that are subject to resource competition. Our analysis of the Hitchhikers of the Rhizosphere (THOR) data showed links between related specialized functions, for instance, between antibiotic and multidrug efflux system expression. Additionally, siderophore co-expression and further evidence suggested that increased siderophore production of the Pseudomonas koreensis koreenceine BGC deletion-mutant drives siderophore production in the other community members. In summary, our findings confirm the feasibility of using cross-species co-expression to predict pathways potentially involved in microbe-microbe interactions. We anticipate that the approach will also facilitate the discovery of novel gene functions through their association with other species' metabolic pathways, for example, those involved in antibiotic response.IMPORTANCEAn improved mechanistic understanding of microbial interactions can guide targeted interventions or inform the rational design of microbial communities to optimize them for applications such as pathogen control, food fermentation, and various biochemical processes. Existing methodologies for inferring the mechanisms behind microbial interactions often rely on complex model-building and are, therefore, sensitive to the introduction of biases from the incorporated existing knowledge and model-building assumptions. We highlight the microbial interaction prediction potential of cross-species co-expression analysis, which contrasts with these methods by its data-driven nature. We describe the utility of cross-species co-expression for various types of interactions and thereby inform future studies on use-cases of the approach and the opportunities and pitfalls that can be expected in its application.

Pseudomonas aeruginosa is a predominant colonizer of airways in non-cystic fibrosis bronchiectasis (NCFB), yet its adaptive mechanisms remain poorly understood. This study investigates the genetic characteristics, virulence variation, and resistance mechanisms of 66 P. aeruginosa isolates derived from NCFB patients. Whole-genome sequencing revealed extensive genetic diversity, encompassing 53 sequence types and a predominance of the O6 serotype (30/66, 45.5%). Phylogenetic analysis indicated that most NCFB isolates were acquired independently, with limited evidence of transmission. Extensive loss-of-function mutations were identified, with mucA mutations present in 90.6% (29/32) of mucoid and 67.6% (23/34) of non-mucoid isolates. Most mucA mutations were frameshift variants, predominantly at codon 144 (Ala144fs), indicating the selective advantage of this site in driving alginate overproduction during chronic airway infection. Virulence gene profiling demonstrated a highly conserved core repertoire but considerable variability in type VI secretion and pyoverdine systems. Notably, mucoid isolates exhibited significantly higher cefiderocol MICs compared to non-mucoid isolates (P = 0.0073), along with enhanced biofilm formation (P < 0.0001) but reduced virulence in the Galleria mellonella infection model. Mechanistic studies revealed that cefiderocol resistance in mucoid P. aeruginosa was driven by synergistic interactions between alginate overproduction and mutations in iron-uptake regulatory genes, particularly Gly132 frameshift in pirR. Disruption of alginate biosynthesis (ΔalgD) and complementation of pirR in mucoid strains markedly restored cefiderocol susceptibility. These findings highlight the remarkable genomic diversity and adaptive resistance mechanisms of P. aeruginosa in NCFB, providing important insights into its persistence and therapeutic challenges in chronic airway infection.IMPORTANCEUnderstanding the adaptive mechanisms of Pseudomonas aeruginosa in non-cystic fibrosis bronchiectasis (NCFB) is critical for improving treatment strategies. This study reveals substantial genomic diversity and highlights alginate overproduction as a key feature of chronic adaptation. Notably, we uncover a novel resistance mechanism involving synergistic interactions between alginate production and mutations in iron-uptake regulators, particularly pirR. These findings underscore the complex evolutionary pressures shaping P. aeruginosa persistence in NCFB and provide valuable insights into its resistance and virulence balance, offering potential targets for more effective therapeutic interventions.

This study aimed to assess the impact of a high-fiber/low-fat agrarian diet (AD) on inflammation and metabolic outcomes in HIV-positive men who have sex with men (MSM). Since the gut microbiomes of MSM resemble those of individuals in agrarian cultures, including being Prevotella-rich and Bacteroides-poor, we hypothesized that they would have particularly strong health benefits from consumption of a diet matched to their microbiome type. Sixty-six participants, including 36 HIV-positive MSM [HIV(+)MSM], 21 HIV-negative MSM, and 9 HIV-negative men who have sex with women, were randomized to either an AD or a high-fat/low-fiber western diet (WD) for 4 weeks. Plasma, fecal, and colonic biopsy samples were obtained. Metabolic and inflammatory markers were measured in plasma. 16S ribosomal RNA sequencing was performed on fecal and biopsy samples, and shotgun metagenomic sequencing was performed on fecal samples. The AD reduced plasma low-density lipoprotein cholesterol (LDL-C) in HIV(+)MSM, with median reductions of 0.4138 mmoL/L at 2 weeks and 0.2845 mmol/L at 4 weeks. Greater LDL-C reductions were predicted by Prevotella-rich/Bacteroides-poor microbiomes with increased starch utilization potential, emphasizing the importance of personalized microbiome-dietary matching. The AD also reduced T cell exhaustion and pro-inflammatory intermediate monocytes and altered host transcription in the colonic mucosa.

Importance: Our findings suggest tailoring diet interventions to baseline microbiome types can promote metabolic health in Prevotella-rich/Bacteroides-poor MSM, a significant portion of people living with HIV at risk for metabolic syndrome.This study was registered at NCT02610374.