Evidence map›Paper›PMID 36198716›Full record

ArticleScientific reports2022

Intraspecies characterization of bacteria via evolutionary modeling of protein domains.

Iva Budimir, Enrico Giampieri, Edoardo Saccenti, Maria Suarez-Diez, Martina Tarozzi, Daniele Dall'Olio, Alessandra Merlotti, Nico Curti, Daniel Remondini, Gastone Castellani and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 51% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 2 countries.

Iva BudimirDepartment of Physics and Astronomy 'Augusto Righi', University of Bologna, 40127, Bologna, Italy.
Enrico GiampieriDepartment of Experimental, Diagnostic and Specialty Medicine, University of Bologna, 40138, Bologna, Italy.
Edoardo SaccentiLaboratory of Systems and Synthetic Biology, Wageningen University and Research, 6708 WE, Wageningen, The Netherlands.
Maria Suarez-DiezLaboratory of Systems and Synthetic Biology, Wageningen University and Research, 6708 WE, Wageningen, The Netherlands.
Martina TarozziDepartment of Experimental, Diagnostic and Specialty Medicine, University of Bologna, 40138, Bologna, Italy.
Daniele Dall'OlioDepartment of Physics and Astronomy 'Augusto Righi', University of Bologna, 40127, Bologna, Italy.
Alessandra MerlottiDepartment of Physics and Astronomy 'Augusto Righi', University of Bologna, 40127, Bologna, Italy.
Nico CurtiDepartment of Experimental, Diagnostic and Specialty Medicine, University of Bologna, 40138, Bologna, Italy.
Daniel RemondiniDepartment of Physics and Astronomy 'Augusto Righi', University of Bologna, 40127, Bologna, Italy.
Gastone CastellaniDepartment of Experimental, Diagnostic and Specialty Medicine, University of Bologna, 40138, Bologna, Italy. gastone.castellani@unibo.it.
Claudia SalaDepartment of Experimental, Diagnostic and Specialty Medicine, University of Bologna, 40138, Bologna, Italy.
University of Bologna · ITWageningen University & Research · NL

Funding

Marie Curie 721815
6 · The paper itself

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.

Indexed as

BacteriaHumansPhylogenyProtein DomainsRNA, Ribosomal, 16SSequence Analysis, DNARNA, Ribosomal, 16S

Identifiers

PMID36198716
PMCPMC9534902
OpenAlexW4301600145

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.