Back

Characterizing biofilm interactions between Ralstonia insidiosa and Chryseobacterium gleum

Foote, A.; Schutz, K.; Zhao, Z.; DiGianivittorio, P.; Korwin-Mihavics, B. R.; LiPuma, J. J.; Wargo, M. J.

2022-10-11 microbiology
10.1101/2022.10.11.511742 bioRxiv
Show abstract

Ralstonia insidiosa and Chryseobacterium gleum are bacterial species commonly found in potable water systems and these two species contribute to the robustness of biofilm formation in a model six-species community from the International Space Station (ISS) potable water system. Here, we set about characterizing the interaction between these two ISS-derived strains and examining the extent to which this interaction extends to other strains and species in these two genera. The enhanced biofilm formation between the ISS strains of R. insidiosa and C. gleum is robust to starting inoculum and temperature, occurs in some but not all tested growth media, and evidence does not support a soluble mediator or co-aggregation mechanism. These findings shed light on the ISS R. insidiosa and C. gleum interaction, though such enhancement is not common between these species based on our examination of other R. insidiosa and C. gleum strains, as well as other species of Ralstonia and Chryseobacterium. Thus, while the findings presented here increase our understanding of the ISS potable water model system, not all our findings are broadly extrapolatable to strains found outside of the ISS. ImportanceBiofilms present in drinking water systems and terminal fixtures are important for human health, pipe corrosion, and water taste. Here we examine the enhanced biofilm of cu-cultures for two very common bacteria from potable water systems, Ralstonia insidiosa and Chryseobacterium gleum. While strains originally isolated on the International Space Station show enhanced dual-species biofilm formation, terrestrial strains do not show the same interaction properties. This study contributes to our understanding of these two species in both dual and mono-culture biofilm formation.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.