Xylella fastidiosa is a xylem-limited phytopathogenic bacterium responsible for severe diseases in many economically important crops. Despite its impact, its metabolism remains poorly characterized due to fastidious growth and the limited availability of defined culture media. Here, we reconstruct the first pangenome-based genome-scale metabolic model for X. fastidiosa, integrating conserved metabolic functions from 18 strains across five subspecies. The resulting consensus model, iXfcore, is manually curated and used to explore the species' metabolic capabilities. Model simulations predict minimal nutritional requirements that guide us in the formulation of defined media to assess biofilm formation in vitro, supporting the utility of the resulting predictions. Network analysis also identifies a previously undescribed model-predicted candidate pathway for acetate assimilation, consistent with genomic evidence but requiring further empirical validation. In addition, the model predicts the overproduction of polyamines, compounds linked to virulence in other phytopathogens. Experimental analyses confirm polyamine production in multiple X. fastidiosa strains in vitro, providing the first evidence of polyamine detection in culture supernatants of this phytopathogen. Overall, iXfcore provides a systems-level framework to investigate X. fastidiosa metabolism, generate testable hypotheses on its physiology and putative virulence-associated traits, and support future strain-specific models and studies of host-pathogen metabolic interactions.
Aspergillus oryzae (koji mold) is a key microorganism in traditional food fermentations including soy sauce, sake, and miso and is important in novel culinary applications and modern biotechnology, such as sustainable meat alternatives and enzyme production. Despite its industrial importance, until recently, the most recent genome-scale metabolic model (GEM) for A. oryzae dated back to 2008 and was limited to a single strain (RIB40). Here, we present pAo, a pan-GEM for A. oryzae, integrating genomic data from 187 strains to capture species-wide metabolic diversity. Our model comprises 2,025 reactions, representing a 52% increase in metabolic coverage over the RIB40-based model and includes previously overlooked pathways, such as cytochrome P450-mediated xenobiotic metabolism and extended amino acid metabolism. Using this pan-GEM, we derived strain-specific GEMs and validated 8 of them through high-throughput phenotypic screening on 285 substrates. Growth experiments on 4 industrially relevant carbon sources revealed substantial interstrain metabolic diversity, although flux balance analysis indicated that this variability originates at the regulatory rather than network-structural level. This resource provides a foundation for informed strain selection for biotechnological applications and future metabolic engineering in A. oryzae.
Jeroen Gilis, C. R. B. van der Luijt, Marilena Feller et al.· Computational and Structural...· 0 citations
A pan-genome of 17 Nannochloropsis species comprising 14,851 gene families is constructed and a distinct genetic architecture for lipid metabolism is defined: Gene families associated with vesicular transport formed a conserved core functional module, whereas the genetic collection for lipid metabolism showed greater plasticity and was primarily classified as part of the soft-core genome.
Pengjuan Zhang, Lijun Miao, Hua Wang et al.· Journal of Phycology· 0 citations
Rec reconstructed genome-scale metabolic models of 44 Pseudomonas strains from various environments and investigated their capabilities to metabolize different carbon sources and metabolic intermediaries, demonstrating how GEM-predicted capabilities can differentiate between strains and that high metabolic versatility is associated with the predicted ability of the strains to remove toxic compounds while maintaining core functionalities.
C. Fócil-Espinosa, Christopher Dalldorf, Diego Martinez et al.· Computational and Structural...· 0 citations
The first comprehensive species-wide pangenomic and systems-level analyses of B. sorokiniana are presented, providing vital insights into the evolutionary architecture of pathogenicity, adaptation, and genome diversification and providing a valuable genomic resource for disease surveillance and functional characterization of virulence determinants.
Anand Kumar Shukla, Narendra Y. Kadoo· bioRxiv· 0 citations
The genetic determinants hypothetically linked to efficient 2KGA synthesis, including glucose metabolism, fatty acid metabolism, and the oxidative phosphorylation system are delineated, which could provide the genomic resource for elucidating high productivity and robustness, and rationally engineering the high-performance chassis cells toward robust 2KGA production.
Lulu Li, Lei Sun, Xin-Yi Zan et al.· Biotechnology for Biofuels a...· 0 citations