Evidence map›Paper›PMID 33061983›Full record

ArticleInternational journal of microbiology2020

Evaluation of 16S rRNA Hypervariable Regions for Bioweapon Species Detection by Massively Parallel Sequencing.

Victor H G Dias, Priscila da S F C Gomes, Allan C Azevedo-Martins, Bianca C A Cabral, August E Woerner, Bruce Budowle, Rodrigo S Moura-Neto, Rosane Silva

Abstract read
In one paragraph

Article in International journal of microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

8 authors.

Victor H G DiasInstituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.ORCID https://orcid.org/0000-0003-4113-7639
Priscila da S F C GomesInstituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
Allan C Azevedo-MartinsInstituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
Bianca C A CabralInstituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
August E WoernerCenter for Human Identification, University of North Texas Health Science Center, Fort Worth, Texas 76107, USA.
Bruce BudowleCenter for Human Identification, University of North Texas Health Science Center, Fort Worth, Texas 76107, USA.
Rodrigo S Moura-NetoInstituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
Rosane SilvaInstituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.ORCID https://orcid.org/0000-0002-2998-6999

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular detection and classification of the bacterial groups in a sample are relevant in several areas, including medical research and forensics. Sanger sequencing of the 16S rRNA gene is considered the gold standard for microbial phylogenetic analysis. However, the development of massively parallel sequencing (MPS) offers enhanced sensitivity and specificity for microbiological analyses. In addition, 16S rRNA target amplification followed by MPS facilitates the combined use of multiple markers/regions, better discrimination of sample background, and higher sample throughput. We designed a novel set of 16S rRNA gene primers for detection of bacterial species associated with clinical, bioweapon, and biohazards microorganisms via alignment of 364 sequences representing 19 bacterial species and strains relevant to medical and forensics applications. In silico results indicated that the hypervariable regions (V1V2), (V4V5), and (V6V7V8) support the resolution of a selected group of bacteria. Interspecies and intraspecies comparisons showed 74.23%-85.51% and 94.48%-99.98% sequencing variation among species and strains, respectively. Sequence reads from a simulated scenario of bacterial species mapped to each of the three hypervariable regions of the respective species with different affinities. The minimum limit of detection was achieved using two different MPS platforms. This protocol can be used to detect or monitor as low as 2,000 genome equivalents of bacterial species associated with clinical, bioweapon, and biohazard microorganisms and potentially can distinguish natural outbreaks of pathogenic microorganisms from those occurring by intentional release.

Identifiers

PMID33061983
PMCPMC7533751

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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.