Evidence map›Paper›PMID 41477002›Full record

ArticleFrontiers in cellular and infection microbiology2025

NGS-based approach for diagnostically unidentified

Giulia Gatti, Ludovica Ingletto, Giorgio Dirani, Silvia Zannoli, Francesca Taddei, Claudia Colosimo, Laura Dionisi, Anna Marzucco, Maria Sofia Montanari, Agnese Denicolò and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2025. 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
–field-weighted citation impact
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.

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

18 authors.

Giulia Gatti *Department of Medical and Surgical Sciences-DIMEC, Alma Mater Studiorum, University of Bologna, Bologna, Italy.
Ludovica Ingletto *Department of Medical and Surgical Sciences-DIMEC, Alma Mater Studiorum, University of Bologna, Bologna, Italy.
Giorgio DiraniOperative Unit of Microbiology, The Greater Romagna Hub Laboratory, Cesena, Italy.
Silvia ZannoliOperative Unit of Microbiology, The Greater Romagna Hub Laboratory, Cesena, Italy.
Francesca TaddeiOperative Unit of Microbiology, The Greater Romagna Hub Laboratory, Cesena, Italy.
Claudia ColosimoDepartment of Medical and Surgical Sciences-DIMEC, Alma Mater Studiorum, University of Bologna, Bologna, Italy.
Laura DionisiDepartment of Medical and Surgical Sciences-DIMEC, Alma Mater Studiorum, University of Bologna, Bologna, Italy.
Anna MarzuccoOperative Unit of Microbiology, The Greater Romagna Hub Laboratory, Cesena, Italy.
Maria Sofia MontanariOperative Unit of Microbiology, The Greater Romagna Hub Laboratory, Cesena, Italy.
Agnese DenicolòOperative Unit of Microbiology, The Greater Romagna Hub Laboratory, Cesena, Italy.
Francesco CongestrìOperative Unit of Microbiology, The Greater Romagna Hub Laboratory, Cesena, Italy.
Laura GrumiroOperative Unit of Microbiology, The Greater Romagna Hub Laboratory, Cesena, Italy.
Martina BrandoliniDepartment of Medical and Surgical Sciences-DIMEC, Alma Mater Studiorum, University of Bologna, Bologna, Italy.
Massimiliano GuerraOperative Unit of Microbiology, The Greater Romagna Hub Laboratory, Cesena, Italy.
Alessandra Mistral De PascaliDepartment of Medical and Surgical Sciences-DIMEC, Alma Mater Studiorum, University of Bologna, Bologna, Italy.
Alessandra ScagliariniDepartment of Medical and Surgical Sciences-DIMEC, Alma Mater Studiorum, University of Bologna, Bologna, Italy.
Monica CriccaDepartment of Medical and Surgical Sciences-DIMEC, Alma Mater Studiorum, University of Bologna, Bologna, Italy.
Vittorio SambriDepartment of Medical and Surgical Sciences-DIMEC, Alma Mater Studiorum, University of Bologna, Bologna, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The implementation of advanced technologies and algorithms for diagnosis and genome analysis has made a fundamental contribution to pathogens' identification and investigation. Methods: The study of non-tuberculous mycobacteria (NTM) benefited from a next-generation sequencing (NGS) approach, making it possible to describe sequences of rare pathogens. This study identified 20 diagnostically unknown isolates as Results: Principal component analysis on the three genes combined with the mutations' annotation suggests that rpoB may serve as a suitable marker to distinguish Discussion: Our results show that frontier studies performed using NGS can help in overcoming the limits of traditional diagnostic assays and deepen the knowledge on rare and uncommon NTM that are raising clinical concern.

Indexed as

High-Throughput Nucleotide SequencingMycobacterium Infections, NontuberculousNontuberculous MycobacteriaBacterial ProteinsChaperonin 60DNA, BacterialDNA-Directed RNA PolymerasesGenome, BacterialHumansMultilocus Sequence TypingPhylogenyPolymorphism, Single NucleotideRNA, Ribosomal, 16SSaskatchewanBacterial ProteinsChaperonin 60DNA, BacterialDNA-Directed RNA Polymerasesheat-shock protein 65, MycobacteriumRNA, Ribosomal, 16Sbioinformaticsdiagnosismarkernontuberculoussequence analysis

Identifiers

PMID41477002
PMCPMC12748190

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.