Details

Autor(en) / Beteiligte

• Ulanova, Anna
• Mansfeldt, Cresten

Titel

EcoGenoRisk: Developing a computational ecological risk assessment tool for synthetic biology

Ist Teil von

• Environmental pollution (1987), 2024-04, Vol.346, p.123647-123647, Article 123647

Ort / Verlag

England: Elsevier Ltd

Erscheinungsjahr

2024

Link zum Volltext

Quelle

Elsevier ScienceDirect Journals

Beschreibungen/Notizen

• The expanding field of synthetic biology (synbio) supports new opportunities in the design of targeted bioproducts or modified microorganisms. However, this rapid development of synbio products raises concerns surrounding the potential risks of modified microorganisms contaminating unintended environments. These potential invasion risks require new bioinformatic tools to inform the design phase. EcoGenoRisk is a newly constructed computational risk assessment tool for invasiveness that aims to predict where synbio microorganisms may establish a population by screening for habitats of genetically similar microorganisms. The first module of the tool identifies genetically similar microorganisms and potential ecological relationships such as competition, mutualism, and inhibition. In total, 520 archaeal and 32,828 bacterial complete assembly genomes were analyzed to test the specificity and accuracy of the tool as well as to characterize the enzymatic profiles of different taxonomic lineages. Additionally, ecological relationships were analyzed to determine which would result in the greatest potential overlap between shared functional profiles. Notably, competition displayed the significantly highest overlap of shared functions between compared genomes. Overall, EcoGenoRisk is a flexible software pipeline that assists environmental risk assessors to query large databases of known microorganisms and prioritize follow-up bench scale studies. [Display omitted] •EcoGenoRisk encodes an environmental risk assessment for synbio microorganisms.•The module HazID identifies functional similar microorganisms (NicheOverlap).•HazID identifies likely competitors through shared substrates (CompetitorFind).•Potential substrate or product inhibition modifies this search (PoisInhibitor).•Functionally similar microorganisms display high substrate overlap and competition.