3.
Emergence of community behaviors in the gut microbiota upon drug treatment.
Garcia-Santamarina S,
Kuhn M, Devendran S, Maier L,
Driessen M, Mateus A, Mastrorilli E, Brochado AR, Savitski MM, Patil KR, Zimmermann M,
Bork P, Typas A
Cell.
2024 Sep 19; [Epub ahead of print] PubMed:
39321801.Abstract
Pharmaceuticals can directly inhibit the growth of gut bacteria, but the degree to which such interactions manifest in complex community settings is an open question. Here, we compared the effects of 30 drugs on a 32-species synthetic community with their effects on each community member in isolation. While most individual drug-species interactions remained the same in the community context, communal behaviors emerged in 26% of all tested cases. Cross-protection during which drug-sensitive species were protected in community was 6 times more frequent than cross-sensitization, the converse phenomenon. Cross-protection decreased and cross-sensitization increased at higher drug concentrations, suggesting that the resilience of microbial communities can collapse when perturbations get stronger. By metabolically profiling drug-treated communities, we showed that both drug biotransformation and bioaccumulation contribute mechanistically to communal protection. As a proof of principle, we molecularly dissected a prominent case: species expressing specific nitroreductases degraded niclosamide, thereby protecting both themselves and sensitive community members.
2.
Discovery of antimicrobial peptides in the global microbiome with machine learning.
Santos-Júnior CD, Torres MDT, Duan Y, Rodríguez Del Río Á,
Schmidt TSB, Chong H,
Fullam A,
Kuhn M, Zhu C, Houseman A, Somborski J, Vines A,
Zhao XM,
Bork P,
Huerta-Cepas J, de la Fuente-Nunez C,
Coelho LPCell.
2024 Jul 11; 187(14): 3761-3778.e16. PubMed:
38843834.Abstract
Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine-learning-based approach to predict antimicrobial peptides (AMPs) within the global microbiome and leverage a vast dataset of 63,410 metagenomes and 87,920 prokaryotic genomes from environmental and host-associated habitats to create the AMPSphere, a comprehensive catalog comprising 863,498 non-redundant peptides, few of which match existing databases. AMPSphere provides insights into the evolutionary origins of peptides, including by duplication or gene truncation of longer sequences, and we observed that AMP production varies by habitat. To validate our predictions, we synthesized and tested 100 AMPs against clinically relevant drug-resistant pathogens and human gut commensals both in vitro and in vivo. A total of 79 peptides were active, with 63 targeting pathogens. These active AMPs exhibited antibacterial activity by disrupting bacterial membranes. In conclusion, our approach identified nearly one million prokaryotic AMP sequences, an open-access resource for antibiotic discovery.