Biology subjects

Basile, A.

Publications and source records attributed to Basile, A..

10 recordsLinked to original sources

bioRxiv2026

CarveMe-GutMicrobes: Automated Metabolic Model Reconstruction for Gut Microbial Species and Communities

Genome-scale metabolic models (GSMMs) are important aids towards system-level understanding of the metabolic physiology of the gut microbes and for rational microbiome engineering. While large-scale repositories of GSMMs for gut-associated bacteria are available, strain-level variability and the continuous discovery of novel taxa through metagenomics and culturomics underscore the need for scalable, ab initio reconstruction tools. Here, we present CarveMe-GutMicrobes, a client-side framework for rapid reconstruction of metabolic models directly from (meta)genomic input. Building upon the original CarveMe framework, CarveMe-GutMicrobes incorporates an expanded, gut-microbe-centric biochemical database that includes reactions, metabolites, and gene-protein-reaction (GPR) associations curated specifically for Bacteria and Archaea inhabiting the human gut. The tool supports taxonomic restriction of the reference database to improve context-specific accuracy. CarveMe-GutMicrobes models demonstrated high predictive performance performance against gene essentiality and metabolite secretion datasets. By integrating curated resources, extending reaction coverage, and offering new empirical datasets, CarveMe-GutMicrobes provides a scalable platform for high-resolution metabolic reconstruction towards broader adoption of GSMMs in gut microbiome research.

bioinformatics↗

bioRxiv2025

Endocytic control of cell-autonomous and non-cell-autonomous functions of p53

NUMB is an endocytic protein with tumor suppressor activity, largely mediated by its ability to inhibit p53 degradation. This function depends on the inclusion of a short alternatively spliced exon (Ex3) in NUMB, although the mechanistic link between endocytosis and p53 regulation remains unclear. Here, we show that the Ex3-encoded sequence directs NUMB to the plasma membrane, where it forms a complex with the endocytic adaptor SNX9. This complex recruits p53 in a SNX9-dependent manner and is internalized and trafficked to multivesicular bodies, culminating in exosomal secretion, in a process requiring both SNX9 and NUMB. Exosomal p53 is taken up by recipient cells and translocated to the nucleus, where it activates p53-dependent transcriptional and phenotypic programs. These findings suggest that exosome-mediated p53 transfer may contribute to the establishment of a tumor-suppressive microenvironment.

cancer biology↗

bioRxiv2025

Interspecies interactions drive bacterial proteome reorganisation and emergent metabolism

Species in microbial communities must respond to the presence of others to stave off resource competition or to capitalise on new resources that may become available due to additional metabolic activities. Such metabolic interactions manifest in growth effects such as competitive exclusion or cooperative growth boost. However, intra-cellular molecular changes that underpin these responses are very sparsely studied, preventing mechanistic insights into community function and dynamics. Here, we analyse meta-proteomics and metabolomic responses in 104 pairwise co-cultures of 15 diverse gut bacteria in a nutrient-rich medium. These co-cultures span a diversity of ecological interactions with competition, amensalism and exploitation being prominent, and with around one in five positive interactions. The species in co-cultures feature substantial molecular responses, with typically more than 60% of the proteome changing in response to at least one partner. Even closely related species and ortholog proteins show different expression profiles in response to the same partner indicating functional diversification at both protein and species level. We show that the magnitude of these responses is determined by genome size, species abundance, and pH. Small-molecule transport and carbon metabolism are among the most responsive processes indicating pervasive metabolic interactions. Using metabolomics, we identify likely cross-fed metabolites, emergent polyamine metabolism, and niche partitioning in amino acid utilisation. Overall, our study shows how bacteria respond to the presence of other species through extensive remodelling of their proteome and metabolome.

microbiology↗

bioRxiv2024

Emergent metabolic interactions in resistance to Clostridioides difficile invasion

Commensal gut bacteria are key contributors to the resilience against pathogen invasion. This is exemplified by the success of fecal microbiota transplantation in treating recurrent Clostridioides difficile infection. Yet, characteristics of communities that can confer colonization resistance and the underlying mechanisms remain largely unknown. Here we use a synthetic community of 14 commensal gut bacteria to uncover inter-species interactions and metabolic pathways underpinning the emergent resilience against C. difficile invasion. We challenged this synthetic community as well as fecal-matter-derived communities with antibiotic treatment and C. difficile in a continuous flow bioreactor. Using generalized Lotka-Volterra and genome-scale metabolic modelling, we identified interactions between Escherichia coli and Bacteroides/Phocaeicola sp. as key to the pathogens suppression. Metabolomics analysis further revealed that fructooligosaccharide metabolism, vitamin B3 biosynthesis, and competition for Stickland metabolism precursors contribute to suppression. Analysis of metagenomics data from patient cohorts and clinical trials attested the in vivo relevance of the identified metabolic pathways and the ratio between Bacteroides and Escherichia in successful colonization resistance. The latter was found to be a much stronger discriminator than commonly used alpha diversity metrics. Our study uncovers emergent microbial interactions in pathogen resistance with implications for rational design of bacteriotherapies.

systems biology↗

bioRxiv2023

APOLLO: A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites

Computational modelling of microbiome metabolism has proved instrumental to catalyse our understanding of diet-host-microbiome-disease interactions through the interrogation of mechanistic, strain- and molecule-resolved metabolic models. We present APOLLO, a resource of 247,092 human microbial genome-scale metabolic reconstructions spanning 19 phyla and accounting for microbial genomes from 34 countries, all age groups, and five body sites. We explored the metabolic potential of the reconstructed strains and developed a machine learning classifier able to predict with high accuracy the taxonomic strain assignments. We also built 14,451 sample-specific microbial community models, which could be stratified by body site, age, and disease states. Finally, we predicted faecal metabolites enriched or depleted in gut microbiomes of people with Crohns disease, Parkinson disease, and undernourished children. APOLLO is compatible with the human whole-body models, and thus, provide unprecedented opportunities for systems-level modelling of personalised host-microbiome co-metabolism. APOLLO will be freely available under https://www.vmh.life/.

systems biology↗

bioRxiv2023

Multi-OMIC analysis of Huntington disease reveals a neuroprotective astrocyte state

Huntington disease (HD) is an incurable neurodegenerative disease characterized by neuronal loss and astrogliosis. One hallmark of HD is the selective neuronal vulnerability of striatal medium spiny neurons. To date, the underlying mechanisms of this selective vulnerability have not been fully defined. Here, we employed a multi-omic approach including single nucleus RNAseq (snRNAseq), bulk RNAseq, lipidomics, HTT gene CAG repeat length measurements, and multiplexed immunofluorescence on post-mortem brain tissue from multiple brain regions of HD and control donors. We defined a signature of genes that is driven by CAG repeat length and found it enriched in astrocytic and microglial genes. Moreover, weighted gene correlation network analysis showed loss of connectivity of astrocytic and microglial modules in HD and identified modules that correlated with CAG-repeat length which further implicated inflammatory pathways and metabolism. We performed lipidomic analysis of HD and control brains and identified several lipid species that correlate with HD grade, including ceramides and very long chain fatty acids. Integration of lipidomics and bulk transcriptomics identified a consensus gene signature that correlates with HD grade and HD lipidomic abnormalities and implicated the unfolded protein response pathway. Because astrocytes are critical for brain lipid metabolism and play important roles in regulating inflammation, we analyzed our snRNAseq dataset with an emphasis on astrocyte pathology. We found two main astrocyte types that spanned multiple brain regions; these types correspond to protoplasmic astrocytes, and fibrous-like - CD44-positive, astrocytes. HD pathology was differentially associated with these cell types in a region-specific manner. One protoplasmic astrocyte cluster showed high expression of metallothionein genes, the depletion of this cluster positively correlated with the depletion of vulnerable medium spiny neurons in the caudate nucleus. We confirmed that metallothioneins were increased in cingulate HD astrocytes but were unchanged or even decreased in caudate astrocytes. We combined existing genome-wide association studies (GWAS) with a GWA study conducted on HD patients from the original Venezuelan cohort and identified a single-nucleotide polymorphism in the metallothionein gene locus associated with delayed age of onset. Functional studies found that metallothionein overexpressing astrocytes are better able to buffer glutamate and were neuroprotective of patient-derived directly reprogrammed HD MSNs as well as against rotenone-induced neuronal death in vitro. Finally, we found that metallothionein-overexpressing astrocytes increased the phagocytic activity of microglia in vitro and increased the expression of genes involved in fatty acid binding. Together, we identified an astrocytic phenotype that is regionally-enriched in less vulnerable brain regions that can be leveraged to protect neurons in HD.

neuroscience↗

bioRxiv2022

Longitudinal flux balance analyses of a patient with Crohn's disease highlight microbiome metabolic alterations

Inflammatory bowel diseases (IBD) are characterised by episodic inflammation of the gastrointestinal tract. Gut microbial dysbiosis characterises the pathoetiology, but its role remains understudied. We report the first use of constraint-based microbial community modelling on a single individual with IBD, covering seven dates over 16 months, enabling us to identify a number of time-correlated microbial species and metabolites. We find that the individuals dynamical microbial ecology in the disease state drives time-varying in silico overproduction, compared to healthy controls, of more than 24 biologically important metabolites, including oxygen, methane, thiamine, formaldehyde, trimethylamine N-oxide, folic acid, serotonin, histamine, and tryptamine. A number of these metabolites may yield new biomarkers of disease progression. The microbe-metabolite contribution analysis revealed that some genus Dialister species changed metabolic pathways according to the disease phases. At the first time point, characterised by the highest levels of blood and faecal inflammation biomarkers, they produced L-serine or formate. The production of the compounds, through a cascade effect, was mediated by the interaction with pathogenic Escherichia coli strains and Desulfovibrio piger. We integrated the microbial community metabolic models of each time point with a male whole-body, organ-resolved model of human metabolism to track the metabolic consequences of dysbiosis at different body sites. The presence of D. piger in the gut microbiome influenced the sulphur metabolism with a domino effect affecting the liver. These results underline the importance of tracking an individuals gut microbiome along a time course, creating a new analysis framework for self-quantified medicine. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/520975v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@136ef4forg.highwire.dtl.DTLVardef@1993042org.highwire.dtl.DTLVardef@2f795forg.highwire.dtl.DTLVardef@c95a6d_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2022

NEMETEX: a Python software for the visualisation of the network of metabolic exchanges

MotivationMicroorganisms have a pivotal role in ecology and human health and form complex networks where different species can interact and exchange a range of different compounds. Flux balance analysis can offer an insight into the production and the absorption of these metabolic compounds, but frequently results are difficult to visualise and interpret. Additionally, a clear understanding of the roles of microbial species in the community requires the integration of different information sources, including relative abundance, taxonomy and compounds exchange rate. ResultsTo fill-in this gap the command-line tool NEMETEX (NEtwork for METabolic Exchanges) was developed to provide a graphical representation of the metabolites exchanged, joined with interactive visualisation of numerical data. This approach can undoubtedly represent an easy way to investigate high-throughput results obtained from metagenomics and flux balance analysis, providing a more direct interpretation of the data. Availability and implementationThis program, accessory utilities, and their documentation are freely available at https://github.com/palakela/NEMETEX

bioinformatics↗

bioRxiv2022

A specific anti-IFITM2 antibody bars the way to SARS-CoV-2 entry into host cells.

The early steps of viral infection involve protein complexes and structural lipid rearrangements, which mark the characteristic strategies of each virus in entering permissive host cells. Human IFITM proteins have been described as inhibitors of a broad range of viruses. Despite their homology and functional redundancy, recently it has been surprisingly shown that SARS-CoV-2 is able to specifically hijack the IFITM2 protein. Here has been reported the characterization of a newly generated specific anti-IFITM2 mAb able to impair SARS-CoV-2 Spike protein internalization and, consequently, to reduce the SARS-CoV-2 cytopathic effects and syncytia formation. Importantly, as evidence of the more general involvement of IFITM2 in virus entry, the anti-IFITM2 mAb was able to efficiently reduce HSVs- and RSV-dependent cytopathic effects. Hence, IFITM proteins could be promising targets that can foster the development of biological antiviral molecules, or suggest additional therapeutic strategies for the treatment of viral infections. GRAPHICAL ABSTRACT O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

microbiology↗

bioRxiv2019

The anaerobic digestion microbiome: a collection of 1600 metagenome-assembled genomes shows high species diversity related to methane production

BackgroundMicroorganisms in biogas reactors are essential for degradation of organic matter and methane production through anaerobic digestion process. However, a comprehensive genome-centric comparison, including relevant metadata for each sample, is still needed to identify the globally distributed biogas community members and serve as a reliable repository.\n\nResultsHere, 134 publicly available datasets derived from different biogas reactors were used to recover 1,635 metagenome-assembled genomes (MAGs) representing different bacterial and archaeal species. All genomes were estimated to be >50% complete and nearly half were [≥]90% complete with [≤]5% contamination. In most samples, specialized microbial communities were established, while only a few taxa were widespread among the different reactor systems. Metabolic reconstruction of the MAGs enabled the prediction of functional traits related to biomass degradation and methane production from waste biomass. An extensive evaluation of the replication index provided an estimation of the growth rate for microbes involved in different steps of the food chain. The recovery of many MAGs belonging to Candidate Phyla Radiation and other underexplored taxa suggests their specific involvement in the anaerobic degradation of organic matter.\n\nConclusionsThe outcome of this study highlights a high flexibility of the biogas microbiome. The dynamic composition and adaptability to the environmental conditions, including temperatures and a wide range of substrates, were demonstrated. Our findings enhance the mechanistic understanding of anaerobic digestion microbiome and substantially extend the existing repository of genomes. The established database represents a relevant resource for future studies related to this engineered ecosystem.

microbiology↗