<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Dos Santos AR</submitter><funding>Swiss National Science Foundation</funding><funding>European Research Council</funding><pagination>e0023922</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9600862</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>7(5)</volume><pubmed_abstract>Predicting the fate of a microbial community and its member species relies on understanding the nature of their interactions. However, designing simple assays that distinguish between interaction types can be challenging. Here, we performed spent medium assays based on the predictions of a mathematical model to decipher the interactions among four bacterial species: Agrobacterium tumefaciens, Comamonas testosteroni, Microbacterium saperdae, and Ochrobactrum anthropi. While most experimental results matched model predictions, the behavior of &lt;i>C. testosteroni&lt;/i> did not: its lag phase was reduced in the pure spent media of A. tumefaciens and &lt;i>M. saperdae&lt;/i> but prolonged again when we replenished our growth medium. Further experiments showed that the growth medium actually delayed the </pubmed_abstract><journal>mSystems</journal><pubmed_title>Classifying Interactions in a Synthetic Bacterial Community Is Hindered by Inhibitory Growth Medium.</pubmed_title><pmcid>PMC9600862</pmcid><funding_grant_id>PCEGP3_18127</funding_grant_id><funding_grant_id>715097</funding_grant_id><funding_grant_id>181272</funding_grant_id><funding_grant_id>NCCR Microbiomes</funding_grant_id><pubmed_authors>Dos Santos AR</pubmed_authors><pubmed_authors>Mitri S</pubmed_authors><pubmed_authors>Di Martino R</pubmed_authors><pubmed_authors>Testa SEA</pubmed_authors></additional><is_claimable>false</is_claimable><name>Classifying Interactions in a Synthetic Bacterial Community Is Hindered by Inhibitory Growth Medium.</name><description>Predicting the fate of a microbial community and its member species relies on understanding the nature of their interactions. However, designing simple assays that distinguish between interaction types can be challenging. Here, we performed spent medium assays based on the predictions of a mathematical model to decipher the interactions among four bacterial species: Agrobacterium tumefaciens, Comamonas testosteroni, Microbacterium saperdae, and Ochrobactrum anthropi. While most experimental results matched model predictions, the behavior of &lt;i>C. testosteroni&lt;/i> did not: its lag phase was reduced in the pure spent media of A. tumefaciens and &lt;i>M. saperdae&lt;/i> but prolonged again when we replenished our growth medium. Further experiments showed that the growth medium actually delayed the </description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Oct</publication><modification>2025-04-04T11:29:09.521Z</modification><creation>2024-11-20T21:56:55.793Z</creation></dates><accession>S-EPMC9600862</accession><cross_references><pubmed>36197097</pubmed><doi>10.1128/msystems.00239-22</doi></cross_references></HashMap>