COVID-19: A complex disease with a unique metabolic signature.

Plasma of COVID-19 patients contains a strong metabolomic/lipoproteomic signature, revealed by the NMR analysis of a cohort of >500 patients sampled during various waves of COVID-19 infection, corresponding to the spread of different variants, and having different vaccination status. This composite signature highlights common traits of the SARS-CoV-2 infection. The most dysregulated molecules display concentration trends that scale with disease severity and might serve as prognostic markers for fatal events. Metabolomics evidence is then used as input data for a sex-specific multi-organ metabolic model. This reconstruction provides a comprehensive view of the impact of COVID-19 on the entire human metabolism. The human (male and female) metabolic network is strongly impacted by the disease to an extent dictated by its severity. A marked metabolic reprogramming at the level of many organs indicates an increase in the generic energetic demand of the organism following infection. Sex-specific modulation of immune response is also suggested.

Functional Genomics of a Collection of Gammaproteobacteria Isolated from Antarctica.

Antarctica, one of the most extreme environments on Earth, hosts diverse microbial communities. These microbes have evolved and adapted to survive in these hostile conditions, but knowledge on the molecular mechanisms underlying this process remains limited. The Italian Collection of Antarctic Bacteria (Collezione Italiana Batteri Antartici (CIBAN)), managed by the University of Messina, represents a valuable repository of cold-adapted bacterial strains isolated from various Antarctic environments. In this study, we sequenced and analyzed the genomes of 58 marine Gammaproteobacteria strains from the CIBAN collection, which were isolated during Italian expeditions from 1990 to 2005. By employing genome-scale metrics, we taxonomically characterized these strains and assigned them to four distinct genera: Pseudomonas, Pseudoalteromonas, Shewanella, and Psychrobacter. Genome annotation revealed a previously untapped functional potential, including secondary metabolite biosynthetic gene clusters and antibiotic resistance genes. Phylogenomic analyses provided evolutionary insights, while assessment of cold-shock protein presence shed light on adaptation mechanisms. Our study emphasizes the significance of CIBAN as a resource for understanding Antarctic microbial life and its biotechnological potential. The genomic data unveil new horizons for insight into bacterial existence in Antarctica.

Development of high-copy number plasmids in Pseudoalteromonas haloplanktis TAC125.

The Antarctic bacterium Pseudoalteromonas haloplanktis TAC125 (PhTAC125) is considered an interesting alternative host for the recombinant protein production, that can be explored when the conventional bacterial expression systems fail. Indeed, the manufacture of all the difficult-to-express proteins produced so far in this bacterial platform gave back soluble and active products. Despite these promising results, the low yield of recombinant protein production achieved is hampering the wider and industrial exploitation of this psychrophilic cell factory. All the expression plasmids developed so far in PhTAC125 are based on the origin of replication of the endogenous pMtBL plasmid and are maintained at a very low copy number. In this work, we set up an experimental strategy to select mutated OriR sequences endowed with the ability to establish recombinant plasmids at higher multiplicity per cell. The solution to this major production bottleneck was achieved by the construction of a library of psychrophilic vectors, each containing a randomly mutated version of pMtBL OriR, and its screening by fluorescence-activated cell sorting (FACS). The selected clones allowed the identification of mutated OriR sequences effective in enhancing the plasmid copy number of approximately two orders of magnitude, and the production of the recombinant green fluorescent protein was increased up to twenty times approximately. Moreover, the molecular characterization of the different mutant OriR sequences allowed us to suggest some preliminary clues on the pMtBL replication mechanism that deserve to be further investigated in the future. KEY POINTS: • Setup of an electroporation procedure for Pseudoalteromonas haloplanktis TAC125. • Two order of magnitude improvement of OriR-derived psychrophilic expression systems. • Almost twenty times enhancement in Green fluorescent protein production.

Crossing Bacterial Genomic Features and Methylation Patterns with MeStudio: An Epigenomic Analysis Tool.

DNA methylation is one of the most observed epigenetic modifications. It is present in eukaryotes and prokaryotes and is related to several biological phenomena, including gene flow and adaptation to environmental conditions. The widespread use of third-generation sequencing technologies allows direct and easy detection of genome-wide methylation profiles, offering increasing opportunities to understand and exploit the epigenomic landscape of individuals and populations. Here, we present a pipeline named MeStudio, with the aim of analyzing and combining genome-wide methylation profiles with genomic features. Outputs report the presence of DNA methylation in coding sequences (CDSs) and noncoding sequences, including both intergenic sequences and sequences upstream of the CDS. We apply this novel tool, showing the usage and performance of MeStudio, on a set of single-molecule real-time sequencing outputs from strains of the bacterial species Sinorhizobium meliloti.

Robustness encoded across essential and accessory replicons of the ecologically versatile bacterium Sinorhizobium meliloti.

Bacterial genome evolution is characterized by gains, losses, and rearrangements of functional genetic segments. The extent to which large-scale genomic alterations influence genotype-phenotype relationships has not been investigated in a high-throughput manner. In the symbiotic soil bacterium Sinorhizobium meliloti, the genome is composed of a chromosome and two large extrachromosomal replicons (pSymA and pSymB, which together constitute 45% of the genome). Massively parallel transposon insertion sequencing (Tn-seq) was employed to evaluate the contributions of chromosomal genes to growth fitness in both the presence and absence of these extrachromosomal replicons. Ten percent of chromosomal genes from diverse functional categories are shown to genetically interact with pSymA and pSymB. These results demonstrate the pervasive robustness provided by the extrachromosomal replicons, which is further supported by constraint-based metabolic modeling. A comprehensive picture of core S. meliloti metabolism was generated through a Tn-seq-guided in silico metabolic network reconstruction, producing a core network encompassing 726 genes. This integrated approach facilitated functional assignments for previously uncharacterized genes, while also revealing that Tn-seq alone missed over a quarter of wild-type metabolism. This work highlights the many functional dependencies and epistatic relationships that may arise between bacterial replicons and across a genome, while also demonstrating how Tn-seq and metabolic modeling can be used together to yield insights not obtainable by either method alone.

Multidisciplinary approaches for studying rhizobium-legume symbioses.

The rhizobium-legume symbiosis is a major source of fixed nitrogen (ammonia) in the biosphere. The potential for this process to increase agricultural yield while reducing the reliance on nitrogen-based fertilizers has generated interest in understanding and manipulating this process. For decades, rhizobium research has benefited from the use of leading techniques from a very broad set of fields, including population genetics, molecular genetics, genomics, and systems biology. In this review, we summarize many of the research strategies that have been employed in the study of rhizobia and the unique knowledge gained from these diverse tools, with a focus on genome- and systems-level approaches. We then describe ongoing synthetic biology approaches aimed at improving existing symbioses or engineering completely new symbiotic interactions. The review concludes with our perspective of the future directions and challenges of the field, with an emphasis on how the application of a multidisciplinary approach and the development of new methods will be necessary to ensure successful biotechnological manipulation of the symbiosis.

Comparative genome-scale modelling of Staphylococcus aureus strains identifies strain-specific metabolic capabilities linked to pathogenicity.

Staphylococcus aureus is a preeminent bacterial pathogen capable of colonizing diverse ecological niches within its human host. We describe here the pangenome of S. aureus based on analysis of genome sequences from 64 strains of S. aureus spanning a range of ecological niches, host types, and antibiotic resistance profiles. Based on this set, S. aureus is expected to have an open pangenome composed of 7,411 genes and a core genome composed of 1,441 genes. Metabolism was highly conserved in this core genome; however, differences were identified in amino acid and nucleotide biosynthesis pathways between the strains. Genome-scale models (GEMs) of metabolism were constructed for the 64 strains of S. aureus These GEMs enabled a systems approach to characterizing the core metabolic and panmetabolic capabilities of the S. aureus species. All models were predicted to be auxotrophic for the vitamins niacin (vitamin B3) and thiamin (vitamin B1), whereas strain-specific auxotrophies were predicted for riboflavin (vitamin B2), guanosine, leucine, methionine, and cysteine, among others. GEMs were used to systematically analyze growth capabilities in more than 300 different growth-supporting environments. The results identified metabolic capabilities linked to pathogenic traits and virulence acquisitions. Such traits can be used to differentiate strains responsible for mild vs. severe infections and preference for hosts (e.g., animals vs. humans). Genome-scale analysis of multiple strains of a species can thus be used to identify metabolic determinants of virulence and increase our understanding of why certain strains of this deadly pathogen have spread rapidly throughout the world.

G4PromFinder: an algorithm for predicting transcription promoters in GC-rich bacterial genomes based on AT-rich elements and G-quadruplex motifs.

BACKGROUND: Over the last few decades, computational genomics has tremendously contributed to decipher biology from genome sequences and related data. Considerable effort has been devoted to the prediction of transcription promoter and terminator sites that represent the essential "punctuation marks" for DNA transcription. Computational prediction of promoters in prokaryotes is a problem whose solution is far from being determined in computational genomics. The majority of published bacterial promoter prediction tools are based on a consensus-sequences search and they were designed specifically for vegetative σ70 promoters and, therefore, not suitable for promoter prediction in bacteria encoding a lot of σ factors, like actinomycetes. RESULTS: In this study we investigated the possibility to identify putative promoters in prokaryotes based on evolutionarily conserved motifs, and focused our attention on GC-rich bacteria in which promoter prediction with conventional, consensus-based algorithms is often not-exhaustive. Here, we introduce G4PromFinder, a novel algorithm that predicts putative promoters based on AT-rich elements and G-quadruplex DNA motifs. We tested its performances by using available genomic and transcriptomic data of the model microorganisms Streptomyces coelicolor A3(2) and Pseudomonas aeruginosa PA14. We compared our results with those obtained by three currently available promoter predicting algorithms: the σ70consensus-based PePPER, the σ factors consensus-based bTSSfinder, and PromPredict which is based on double-helix DNA stability. Our results demonstrated that G4PromFinder is more suitable than the three reference tools for both the genomes. In fact our algorithm achieved the higher accuracy (F1-scores 0.61 and 0.53 in the two genomes) as compared to the next best tool that is PromPredict (F1-scores 0.46 and 0.48). Consensus-based algorithms produced lower performances with the analyzed GC-rich genomes. CONCLUSIONS: Our analysis shows that G4PromFinder is a powerful tool for promoter search in GC-rich bacteria, especially for bacteria coding for a lot of σ factors, such as the model microorganism S. coelicolor A3(2). Moreover consensus-based tools and, in general, tools that are based on specific features of bacterial σ factors seem to be less performing for promoter prediction in these types of bacterial genomes.

Subfunctionalization influences the expansion of bacterial multidrug antibiotic resistance.

BACKGROUND: Antibiotic resistance is a major problem for human health. Multidrug resistance efflux pumps, especially those of the Resistance-Nodulation-Cell Division (RND) family, are major contributors to high-level antibiotic resistance in Gram-negative bacteria. Most bacterial genomes contain several copies of the different classes of multidrug resistance efflux pumps. Gene duplication and gain of function by the duplicate copies of multidrug resistance efflux pump genes plays a key role in the expansion and diversification of drug-resistance mechanisms. RESULTS: We used two members of the Burkholderia RND superfamily as models to understand how duplication events affect the antibiotic resistance of these strains. First, we analyzed the conservation and distribution of these two RND systems and their regulators across the Burkholderia genus. Through genetic manipulations, we identified both the exact substrate range of these transporters and their eventual interchangeability. We also performed a directed evolution experiment, combined with next generation sequencing, to evaluate the role of antibiotics in the activation of the expression of these systems. Together, our results indicate that the first step to diversify the functions of these pumps arises from changes in their regulation (subfunctionalization) instead of functional mutations. Further, these pumps could rewire their regulation to respond to antibiotics, thus maintaining high genomic plasticity. CONCLUSIONS: Studying the regulatory network that controls the expression of the RND pumps will help understand and eventually control the development and expansion of drug resistance.

The pangenome of (Antarctic) Pseudoalteromonas bacteria: evolutionary and functional insights.

BACKGROUND: Pseudoalteromonas is a genus of ubiquitous marine bacteria used as model organisms to study the biological mechanisms involved in the adaptation to cold conditions. A remarkable feature shared by these bacteria is their ability to produce secondary metabolites with a strong antimicrobial and antitumor activity. Despite their biotechnological relevance, representatives of this genus are still lacking (with few exceptions) an extensive genomic characterization, including features involved in the evolution of secondary metabolites production. Indeed, biotechnological applications would greatly benefit from such analysis. RESULTS: Here, we analyzed the genomes of 38 strains belonging to different Pseudoalteromonas species and isolated from diverse ecological niches, including extreme ones (i.e. Antarctica). These sequences were used to reconstruct the largest Pseudoalteromonas pangenome computed so far, including also the two main groups of Pseudoalteromonas strains (pigmented and not pigmented strains). The downstream analyses were conducted to describe the genomic diversity, both at genus and group levels. This allowed highlighting a remarkable genomic heterogeneity, even for closely related strains. We drafted all the main evolutionary steps that led to the current structure and gene content of Pseudoalteromonas representatives. These, most likely, included an extensive genome reduction and a strong contribution of Horizontal Gene Transfer (HGT), which affected biotechnologically relevant gene sets and occurred in a strain-specific fashion. Furthermore, this study also identified the genomic determinants related to some of the most interesting features of the Pseudoalteromonas representatives, such as the production of secondary metabolites, the adaptation to cold temperatures and the resistance to abiotic compounds. CONCLUSIONS: This study poses the bases for a comprehensive understanding of the evolutionary trajectories followed in time by this peculiar bacterial genus and for a focused exploitation of their biotechnological potential.

Modelling microbial metabolic rewiring during growth in a complex medium.

BACKGROUND: In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now. RESULTS: We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs). Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of choosing among alternative objective functions on the resulting predictions of fluxes distribution. CONCLUSIONS: Here we provide a time-resolved, systems-level scheme of PhTAC125 metabolic re-wiring as a consequence of carbon source switching in a nutritionally complex medium. Our analyses suggest the presence of a potential efficient metabolic reprogramming machinery to continuously and promptly adapt to this nutritionally changing environment, consistent with adaptation to fast growth in a fairly, but probably inconstant and highly competitive, environment. Also, we show i) how functional partnership and co-regulation features can be predicted by integrating multi-step constraint-based metabolic modelling with fed-batch growth data and ii) that performing simulations under a sub-optimal objective function may lead to different flux distributions in respect to canonical FBA.

Antagonistic interactions between endophytic cultivable bacterial communities isolated from the medicinal plant Echinacea purpurea.

In this work we have studied the antagonistic interactions existing among cultivable bacteria isolated from three ecological niches (rhizospheric soil, roots and stem/leaves) of the traditional natural medicinal plant Echinacea purpurea. The three compartments harboured different taxonomic assemblages of strains, which were previously reported to display different antibiotic resistance patterns, suggesting the presence of differential selective pressure due to antagonistic molecules in the three compartments. Antagonistic interactions were assayed by the cross-streak method and interpreted using a network-based analysis. In particular 'within-niche inhibition' and 'cross-niche inhibition' were evaluated among isolates associated with each compartment as well as between isolates retrieved from the three different compartments respectively. Data obtained indicated that bacteria isolated from the stem/leaves compartment were much more sensitive to the antagonistic activity than bacteria from roots and rhizospheric soil. Moreover, both the taxonomical position and the ecological niche might influence the antagonistic ability/sensitivity of different strains. Antagonism could play a significant role in contributing to the differentiation and structuring of plant-associated bacterial communities.

MeDuSa: a multi-draft based scaffolder.

MOTIVATION: Completing the genome sequence of an organism is an important task in comparative, functional and structural genomics. However, this remains a challenging issue from both a computational and an experimental viewpoint. Genome scaffolding (i.e. the process of ordering and orientating contigs) of de novo assemblies usually represents the first step in most genome finishing pipelines. RESULTS: In this article we present MeDuSa (Multi-Draft based Scaffolder), an algorithm for genome scaffolding. MeDuSa exploits information obtained from a set of (draft or closed) genomes from related organisms to determine the correct order and orientation of the contigs. MeDuSa formalizes the scaffolding problem by means of a combinatorial optimization formulation on graphs and implements an efficient constant factor approximation algorithm to solve it. In contrast to currently used scaffolders, it does not require either prior knowledge on the microrganisms dataset under analysis (e.g. their phylogenetic relationships) or the availability of paired end read libraries. This makes usability and running time two additional important features of our method. Moreover, benchmarks and tests on real bacterial datasets showed that MeDuSa is highly accurate and, in most cases, outperforms traditional scaffolders. The possibility to use MeDuSa on eukaryotic datasets has also been evaluated, leading to interesting results.

Genome-scale metabolic reconstruction and constraint-based modelling of the Antarctic bacterium Pseudoalteromonas haloplanktis†TAC125.

The Antarctic strain Pseudoalteromonas haloplanktis TAC125 is one of the model organisms of cold-adapted bacteria and is currently exploited as a new alternative expression host for numerous biotechnological applications. Here, we investigated several metabolic features of this strain through in silico modelling and functional integration of -omics data. A genome-scale metabolic model of P. haloplanktis TAC125 was reconstructed, encompassing information on 721 genes, 1133 metabolites and 1322 reactions. The predictive potential of this model was validated against a set of experimentally determined growth rates and a large dataset of growth phenotypic data. Furthermore, evidence synthesis from proteomics, phenomics, physiology and metabolic modelling data revealed possible drawbacks of cold-dependent changes in gene expression on the overall metabolic network of P. haloplanktis TAC125. These included, for example, variations in its central metabolism, amino acid degradation and fatty acid biosynthesis. The genome-scale metabolic model described here is the first one reconstructed so far for an Antarctic microbial strain. It allowed a system-level investigation of variations in cellular metabolic fluxes following a temperature downshift. It represents a valuable platform for further investigations on P. haloplanktis TAC125 cellular functional states and for the design of more focused strategies for its possible biotechnological exploitation.

Origin, duplication and reshuffling of plasmid genes: Insights from Burkholderia vietnamiensis G4 genome.

Using a computational pipeline based on similarity networks reconstruction we analysed the 1133 genes of the Burkholderia vietnamiensis (Bv) G4 five plasmids, showing that gene and operon duplication played an important role in shaping the plasmid architecture. Several single/multiple duplications occurring at intra- and/or interplasmids level involving 253 paralogous genes (stand-alone, clustered or operons) were detected. An extensive gene/operon exchange between plasmids and chromosomes was also disclosed. The larger the plasmid, the higher the number and size of paralogous fragments. Many paralogs encoded mobile genetic elements and duplicated very recently, suggesting that the rearrangement of the Bv plastic genome is ongoing. Concerning the "molecular habitat" and the "taxonomical status" (the Preferential Organismal Sharing) of Bv plasmid genes, most of them have been exchanged with other plasmids of bacteria belonging (or phylogenetically very close) to Burkholderia, suggesting that taxonomical proximity of bacterial strains is a crucial issue in plasmid-mediated gene exchange.

Mechanism of resistance to an antitubercular 2-thiopyridine derivative that is also active against Burkholderia cenocepacia.

The discovery of new compounds that are able to inhibit the growth of Burkholderia cenocepacia is of primary importance for cystic fibrosis patients. Here, the mechanism of resistance to a new pyridine derivative already shown to be effective against Mycobacterium tuberculosis and to have good activity toward B. cenocepacia was investigated. Increased expression of a resistance-nodulation-cell division (RND) efflux system was detected in the resistant mutants, thus confirming their important roles in B. cenocepacia antibiotic resistance.

Phenotypic and genomic characterization of the Antarctic bacterium Gillisia sp. CAL575, a producer of antimicrobial compounds.

Microorganisms from Antarctica have evolved particular strategies to cope with cold. Moreover, they have been recently reported as producers of antimicrobial compounds, which inhibit the growth of other bacteria. In this work we characterized from different viewpoints the Gillisia sp. CAL575 strain, a psychrotrophic bacterium that produces microbial volatile organic compounds involved in the growth inhibition of Burkholderia cepacia complex members. Sequencing and analysis of the whole genome of Gillisia sp. CAL575 revealed that it includes genes that are involved in secondary metabolite production, adaptation to cold conditions, and different metabolic pathways for the production of energy. All these features make Gillisia sp. CAL575 a possible tool for biotechnology.

Large-scale analysis of plasmid relationships through gene-sharing networks.

Plasmids are vessels of genetic exchange in microbial communities. They are known to transfer between different host organisms and acquire diverse genetic elements from chromosomes and/or other plasmids. Therefore, they constitute an important element in microbial evolution by rapidly disseminating various genetic properties among different communities. A paradigmatic example of this is the dissemination of antibiotic resistance (AR) genes that has resulted in the emergence of multiresistant pathogenic bacterial strains. To globally analyze the evolutionary dynamics of plasmids, we built a large graph in which 2,343 plasmids (nodes) are connected according to the proteins shared by each other. The analysis of this gene-sharing network revealed an overall coherence between network clustering and the phylogenetic classes of the corresponding microorganisms, likely resulting from genetic barriers to horizontal gene transfer between distant phylogenetic groups. Habitat was not a crucial factor in clustering as plasmids from organisms inhabiting different environments were often found embedded in the same cluster. Analyses of network metrics revealed a statistically significant correlation between plasmid mobility and their centrality within the network, providing support to the observation that mobile plasmids are particularly important in spreading genes in microbial communities. Finally, our study reveals an extensive (and previously undescribed) sharing of AR genes between Actinobacteria and Gammaproteobacteria, suggesting that the former might represent an important reservoir of AR genes for the latter.

Understanding Antimicrobial Resistance Using Genome-Scale Metabolic Modeling.

The urgent necessity to fight antimicrobial resistance is universally recognized. In the search of new targets and strategies to face this global challenge, a promising approach resides in the study of the cellular response to antimicrobial exposure and on the impact of global cellular reprogramming on antimicrobial drugs' efficacy. The metabolic state of microbial cells has been shown to undergo several antimicrobial-induced modifications and, at the same time, to be a good predictor of the outcome of an antimicrobial treatment. Metabolism is a promising reservoir of potential drug targets/adjuvants that has not been fully exploited to date. One of the main problems in unraveling the metabolic response of cells to the environment resides in the complexity of such metabolic networks. To solve this problem, modeling approaches have been developed, and they are progressively gaining in popularity due to the huge availability of genomic information and the ease at which a genome sequence can be converted into models to run basic phenotype predictions. Here, we review the use of computational modeling to study the relationship between microbial metabolism and antimicrobials and the recent advances in the application of genome-scale metabolic modeling to the study of microbial responses to antimicrobial exposure.

Independent origins and evolution of the secondary replicons of the class Gammaproteobacteria.

Multipartite genomes, consisting of more than one replicon, have been found in approximately 10 % of bacteria, many of which belong to the phylum Proteobacteria. Many aspects of their origin and evolution, and the possible advantages related to this type of genome structure, remain to be elucidated. Here, we performed a systematic analysis of the presence and distribution of multipartite genomes in the class Gammaproteobacteria, which includes several genera with diverse lifestyles. Within this class, multipartite genomes are mainly found in the order Alteromonadales (mostly in the genus Pseudoalteromonas) and in the family Vibrionaceae. Our data suggest that the emergence of secondary replicons in Gammaproteobacteria is rare and that they derive from plasmids. Despite their multiple origins, we highlighted the presence of evolutionary trends such as the inverse proportionality of the genome to chromosome size ratio, which appears to be a general feature of bacteria with multipartite genomes irrespective of taxonomic group. We also highlighted some functional trends. The core gene set of the secondary replicons is extremely small, probably limited to essential genes or genes that favour their maintenance in the genome, while the other genes are less conserved. This hypothesis agrees with the idea that the primary advantage of secondary replicons could be to facilitate gene acquisition through horizontal gene transfer, resulting in replicons enriched in genes associated with adaptation to different ecological niches. Indeed, secondary replicons are enriched both in genes that could promote adaptation to harsh environments, such as those involved in antibiotic, biocide and metal resistance, and in functional categories related to the exploitation of environmental resources (e.g. carbohydrates), which can complement chromosomal functions.