Abstract

The ability to detect and characterize bacteria within a biological sample is crucial for the monitoring of infections and epidemics, as well as for the study of human health and its relationship with commensal microorganisms. To this aim, a commonly used technique is the 16S rRNA gene targeted sequencing. PCR-amplified 16S sequences derived from the sample of interest are usually clustered into the so-called Operational Taxonomic Units (OTUs) based on pairwise similarities. Then, representative OTU sequences are compared with reference (human-made) databases to derive their phylogeny and taxonomic classification. Here, we propose a new reference-free approach to define the phylogenetic distance between bacteria based on protein domains, which are the evolving units of proteins. We extract the protein domain profiles of 3368 bacterial genomes and we use an ecological approach to model their Relative Species Abundance distribution. Based on the model parameters, we then derive a new measurement of phylogenetic distance. Finally, we show that such model-based distance is capable of detecting differences between bacteria in cases in which the 16S rRNA-based method fails, providing a possibly complementary approach , which is particularly promising for the analysis of bacterial populations measured by shotgun sequencing.

Details

Title
Intraspecies characterization of bacteria via evolutionary modeling of protein domains
Author
Budimir, Iva 1 ; Giampieri, Enrico 2 ; Saccenti, Edoardo 3 ; Suarez-Diez, Maria 3 ; Tarozzi, Martina 2 ; Dall’Olio, Daniele 1 ; Merlotti, Alessandra 1 ; Curti, Nico 2 ; Remondini, Daniel 1 ; Castellani, Gastone 2 ; Sala, Claudia 2 

 University of Bologna, Department of Physics and Astronomy ‘Augusto Righi’, Bologna, Italy (GRID:grid.6292.f) (ISNI:0000 0004 1757 1758) 
 University of Bologna, Department of Experimental, Diagnostic and Specialty Medicine, Bologna, Italy (GRID:grid.6292.f) (ISNI:0000 0004 1757 1758) 
 Wageningen University and Research, Laboratory of Systems and Synthetic Biology, Wageningen, The Netherlands (GRID:grid.4818.5) (ISNI:0000 0001 0791 5666) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2721476973
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.