Biology subjects

Fondi, M.

Publications and source records attributed to Fondi, M..

6 recordsLinked to original sources

bioRxiv2018

An synthetic microbial loop for modelling heterotroph-phototroph metabolic interactions

Marine ecosystems are characterized by an intricate set of interactions among their representatives. One of the most important occurs through the exchange of dissolved organic matter (DOM) provided by phototrophs and used by heterotrophic bacteria as their main carbon and energy source. This metabolic interaction represents the foundation of the entire ocean food-web.\n\nHere we have assembled a synthetic ecosystem to assist the systems-level investigation of this biological association. This was achieved building an integrated, genome-scale metabolic reconstruction using two model organisms (a diatom Phaeodactylum tricornutum and an heterotrophic bacterium, Pseudoalteromonas haloplanktis) to explore and predict their metabolic interdependencies. The model was initially analysed using a constraint-based approach (Flux Balance Analysis, FBA) and then turned into a dynamic (dFBA) model to simulate a diatom-bacteria co-culture and to study the effect of changes in growth parameters on such a system. Finally, we developed a simpler dynamic ODEs system that, fed with dFBA results, was able to qualitatively describe this synthetic ecosystem and allowed performing stochastic simulations to assess the effect of noise on the overall balance of this co-culture.\n\nWe show that our model recapitulates known metabolic cross-talks of a phototroph-heterotroph system, including mutualism and competition for inorganic ions (i.e. phosphate and sulphate). Further, the dynamic simulation predicts realistic growth rate for both the diatom and the bacterium and a steady state balance between diatom and bacterial cell concentration that matches those determined in experimental co-cultures. This steady state, however, is reached following an oscillatory trend, a behaviour that is typically observed in the presence of metabolic co-dependencies. Finally, we show that, at high diatom/bacteria cell concentration ratio, stochastic fluctuations can lead to the extinction of bacteria from the co-culture, causing the explosion of diatom population. We anticipate that the developed synthetic ecosystem will serve in the future as a basis for the generation of testable hypotheses and as a scaffold for integrating and interpreting-omics data from experimental co-cultures.

systems biology↗

bioRxiv2018

Creation and multi-omics characterization of a genomically hybrid strain in the nitrogen-fixing symbiotic bacterium Sinorhizobium meliloti

Many bacteria, often associated with eukaryotic hosts and of relevance for biotechnological applications, harbour a multipartite genome composed by more than one replicon. Biotechnologically relevant phenotypes are often encoded by genes residing on the secondary replicons. A synthetic biology approach to developing enhanced strains for biotechnological purposes could therefore involve merging pieces or entire replicons from multiple strains into a single genome. Here we report the creation of a genomic hybrid strain in a model multipartite genome species, the plant-symbiotic bacterium Sinorhizobium meliloti. In particular, we moved the secondary replicon pSymA (accounting for nearly 20% of total genome content) from a donor S. meliloti strain to an acceptor strain. The cis-hybrid strain was screened for a panel of complex phenotypes (carbon/nitrogen utilization phenotypes, intra- and extra-cellular metabolomes, symbiosis, and various microbiological tests). Additionally, metabolic network reconstruction and constraint-based modelling were employed for in silico prediction of metabolic flux reorganization. Phenotypes of the cis-hybrid strain were in good agreement with those of both parental strains. Interestingly, the symbiotic phenotype showed a marked cultivar-specific improvement with the cis-hybrid strains compared to both parental strains. These results provide a proof-of-principle for the feasibility of genome-wide replicon-based remodelling of bacterial strains for improved biotechnological applications in precision agriculture.

synthetic biology↗

bioRxiv2018

Metabolic modeling of Pectobacterium parmentieri SCC3193 provides insights into metabolic pathways of plant pathogenic bacteria

Understanding the plant-microbe interactions are crucial for improving plant productivity and plant protection. The latter aspect is particularly relevant for sustainable agriculture and development of new preventive strategies against the spread of plant diseases. Constraint-based metabolic modeling is providing one of the possible ways to investigate the adaptation to different ecological niches and may give insights into the metabolic versatility of plant pathogenic bacteria. In this study, we present a curated metabolic model of the emerging plant pathogenic bacterium Pectobacterium parmentieri SCC3193. Using flux balance analysis (FBA), we predict the metabolic adaptation to two different ecological niches, relevant for the persistence and the plant colonization by this bacterium: soil and rhizosphere. We performed in silico gene deletions to predict the set of core essential genes for this bacterium to grow in such environments. We anticipate that our metabolic model will be a valuable element for defining a set of metabolic targets to control infection and spreading of this plant pathogen and a scaffold to interpret future -omics datasets for this bacterium.

systems biology↗

bioRxiv2017

Tn-Core: context-specific reconstruction of core metabolic models using Tn-seq data

MotivationTn-seq (transposon mutagenesis and sequencing) and constraint-based metabolic modelling represent highly complementary approaches. They can be used to probe the core genetic and metabolic networks underlying a biological process, revealing invaluable information for synthetic biology engineering of microbial cell factories. However, while algorithms exist for integration of -omics data sets with metabolic models, no method has been explicitly developed for integration of Tn-seq data with metabolic reconstructions.\n\nResultsWe report the development of Tn-Core, a Matlab toolbox designed to generate gene-centric, context-specific core reconstructions consistent with experimental Tn-seq data. Extensions of this algorithm allow: i) the generation of context-specific functional models through integration of both Tn-seq and RNA-seq data; ii) to visualize redundancy in core metabolic processes; and iii) to assist in curation of de novo draft metabolic models. The utility of Tn-Core is demonstrated primarily using a Sinorhizobium meliloti model as a case study.\n\nAvailability and implementationThe software can be downloaded from https://github.com/diCenzo-GC/Tn-Core. All results presented in this work have been obtained with Tn-Core v. 1.0.\n\nContactgeorgecolin.dicenzo@unifi.it, marco.fondi@unifi.it\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

systems biology↗

bioRxiv2017

Robustness encoded across essential and accessory replicons in an ecologically versatile bacterium

Bacterial genome evolution is characterized by gains, losses, and rearrangements of functional genetic segments. The extent to which genotype-phenotype relationships are influenced by large-scale genomic alterations 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 contributions of chromosomal genes to 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 modelling. 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 misses over a quarter of wild type metabolism. This work highlights the strong functional dependencies and epistatic relationships that may arise between bacterial replicons and across a genome, while also demonstrating how Tn-seq and metabolic modelling can be used together to yield insights not obtainable by either method alone.

systems biology↗

bioRxiv2017

Constraint-based modeling identifies new putative targets to fight colistin-resistant A. baumannii infections.

Acinetobacter baumannii is a clinical threat to human health, causing major infection outbreaks worldwide. As new drugs against Gram-negative bacteria do not seem to be forthcoming, and due to the microbial capability of acquiring multi-resistance, there is an urgent need for novel therapeutic targets. Here we have derived a list of new potential targets by means of metabolic reconstruction and modelling of A. baumannii ATCC 19606. By integrating constraint-based modelling with gene expression data, we simulated microbial growth in normal and stressful conditions (i.e. following antibiotic exposure). This allowed us to describe the metabolic reprogramming that occurs in this bacterium when treated with colistin (the currently adopted last-line treatment) and identify a set of genes that are primary targets for developing new drugs against A. baumannii, including colistin-resistant strains. It can be anticipated that the metabolic model presented herein will represent a solid and reliable resource for the future treatment of A. baumannii infections.

systems biology↗