Enzyme adaptation to habitat thermal legacy shapes the thermal plasticity of marine microbiomes

Microbial communities respond to temperature with physiological adaptation and compositional turnover. Whether thermal selection of enzymes explains marine microbiome plasticity in response to temperature remains unresolved. By quantifying the thermal behaviour of seven functionally-independent enzyme classes (esterase, extradiol dioxygenase, phosphatase, beta-galactosidase, nuclease, transaminase, and aldo-keto reductase) in native proteomes of marine sediment microbiomes from the Irish Sea to the southern Red Sea, we record a significant effect of the mean annual temperature (MAT) on enzyme response in all cases. Activity and stability profiles of 228 esterases and 5 extradiol dioxygenases from sediment and seawater across 70 locations worldwide validate this thermal pattern. Modelling the esterase phase transition temperature as a measure of structural flexibility confirms the observed relationship with MAT. Furthermore, when considering temperature variability in sites with non-significantly different MATs, the broadest range of enzyme thermal behaviour and the highest growth plasticity of the enriched heterotrophic bacteria occur in samples with the widest annual thermal variability. These results indicate that temperature-driven enzyme selection shapes microbiome thermal plasticity and that thermal variability finely tunes such processes and should be considered alongside MAT in forecasting microbial community thermal response.

Marasco, R., Fusi, M., Coscolín, C., Barozzi, A., Almendral, D., Bargiela, R., Nutschel, C. G. neé, Pfleger, C., Dittrich, J., Gohlke, H., Matesanz, R., Sanchez-Carrillo, S., Mapelli, F., Chernikova, T. N., Golyshin, P. N., Ferrer, M., & Daffonchio, D. (2023). Enzyme adaptation to habitat thermal legacy shapes the thermal plasticity of marine microbiomes. Nature Communications, 14(1). https://doi.org/10.1038/s41467-023-36610-0

We thank Sadaf Umer and Taskeen Begum for their invaluable support in the lab, the Coastal and Marine Resources Core Lab at KAUST for their support in sampling in the Red Sea and the Bioscience Core Lab at KAUST for their support in DNA sequencing. This research was supported by King Abdullah University of Science and Technology through baseline funding to D.D. We thank our partner in the EU project ULIXES for providing sediment samples from the Mediterranean Sea and the Gulf of Aqaba. This study was conducted under the auspices of the FuturEnzyme Project funded by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 101000327 (acknowledged by M.Fe. and P.N.G.). We also acknowledge financial support under Grants PID2020-112758RB-I00 (M.Fe.), PDC2021-121534-I00 (M.Fe.) and TED2021-130544B-I00 (M.Fe.) from the Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación (AEI) (Digital Object Identifier 10.13039/501100011033), Fondo Europeo de Desarrollo Regional (FEDER) and the European Union (“NextGenerationEU/PRTR”), and Grant 2020AEP061 (M.Fe.) from the Agencia Estatal CSIC. P.N.G. acknowledges the Sêr Cymru programme partly funded by ERDF through the Welsh Government for the support of the project BioPOL4Life, the project ‘Plastic Vectors’ funded by the Natural Environment Research Council UK (NERC), Grant No. NE/S004548/N and the Centre for Environmental Biotechnology Project co-funded by the European Regional Development Fund (ERDF) through the Welsh Government. M.Fe. also acknowledges Sergio Ciordia and M. del Carmen Mena, who performed SDS-PAGE and shotgun proteomic analyses at the Proteomics Facility of the Spanish National Center for Biotechnology, ProteoRed, PRB3-ISCIII. Parts of the study were supported by the German Federal Ministry of Education and Research (BMBF) through funding number 031B0837A “LipoBiocat” to H.G. and the state of North-Rhine Westphalia (NRW) and the European Regional Development Fund (EFRE) through funding no. 34-EFRE-0300096 “CLIB-Kompetenzzentrum Biotechnologie (CKB)” to H.G. H.G. is grateful for computational support and infrastructure provided by the “Zentrum für Informations- und Medientechnologie” (ZIM) at the Heinrich Heine University Düsseldorf. H.G. gratefully acknowledges the computing time granted by the John von Neumann Institute for Computing (NIC) and provided on the supercomputer JUWELS at Jülich Supercomputing Centre (JSC) (user IDs: VSK33, lipases).

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