Evidence map›Paper›PMID 39979844›Full record

ArticleBMC genomics2025

Genetic characterization and in silico serotyping of 62 Salmonella enterica isolated from Korean poultry operations.

Hyunhee Hong, Miseon Kang, Avery Haymowicz, Hoang Ngoc Minh Le, Eiseul Kim, Seung Min Yang, Sang-Do Ha, Hyun Jung Kim, Si Hong Park

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

9 authors.

Hyunhee Hong *Department of Food Science and Technology, Oregon State University, 3051 SW Campus Way, Corvallis, OR, 97331, USA.
Miseon Kang *Department of Food Science and Technology, Oregon State University, 3051 SW Campus Way, Corvallis, OR, 97331, USA.
Avery HaymowiczDepartment of Food Science and Technology, Oregon State University, 3051 SW Campus Way, Corvallis, OR, 97331, USA.
Hoang Ngoc Minh LeDepartment of Food Science and Technology, Oregon State University, 3051 SW Campus Way, Corvallis, OR, 97331, USA.
Eiseul KimDepartment of Food Science and Technology, Oregon State University, 3051 SW Campus Way, Corvallis, OR, 97331, USA.
Seung Min YangDepartment of Food Science and Technology, Oregon State University, 3051 SW Campus Way, Corvallis, OR, 97331, USA.
Sang-Do HaDepartment of Food Science and Technology, Advanced Food Safety Research Group, Brain Korea 21 Plus, Chung-Ang University, Anseong, Republic of Korea.
Hyun Jung KimDepartment of Food Biotechnology, University of Science and Technology, Daejeon, Republic of Korea.
Si Hong ParkDepartment of Food Science and Technology, Oregon State University, 3051 SW Campus Way, Corvallis, OR, 97331, USA. sihong.park@oregonstate.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe conventional method of antigen-based serotyping for Salmonella poses challenges due to the necessity of utilizing over 150 antisera. More recently, in silico Salmonella serotyping has emerged as a predictive alternative. The purpose of this study was to predict the serovars of 62 Salmonella enterica strains isolated from Korean poultry operations and their genetic characteristics using whole genome sequencing. The analysis employed diverse methods, including ribosomal, and core genome multi-locus sequence typing (MLST), based on Salmonella In Silico Typing Resource (SISTR). Pangenome, clusters of orthologous groups (COG) analysis, and identification of virulence and antibiotic resistance genes were conducted.

resultsSalmonella enterica subspecies enterica serovars were observed and clustered based on the pangenome and phylogenetic tree: 21 Salmonella Albany (Albany), 13 Salmonella Bareilly (Bareilly), and 28 Salmonella Mbandaka (Mbandaka). The most frequently observed sequence types for the three serovars were ST292 in Albany, ST203 in Bareilly, and ST413 in Mbandaka. 18 antibiotic resistance genes showed varying presences based on the serovars, including Albany (qacEdelta1, tet(D), CARB-3 (blaCARB-3), and dfrA1) and Bareilly (aac(6')-ly). Intriguingly, a mutated gyrA (Ser83 → Phe, serine to phenylalanine) was observed in all 21 Albany strains, whereas Bareilly and Mbandaka carried the wild-type gyrA. Among 130 virulence genes analyzed, 107 were present in all 62 Salmonella strains, with Mbandaka strains exhibiting a higher prevalence of virulence genes related to fimbrial adherence compared to those of Albany and Bareilly.

conclusionsThe study identified distinct genetic characteristics among the three Salmonella serovars using whole genome sequencing. Albany carried a unique mutation in gyrA, occurring in the quinolone resistance-determining region. Additionally, the virulence gene profile of Mbandaka differed from the other serovars, particularly in fimbrial adherence genes. These findings demonstrate the effectiveness of in silico approaches in predicting Salmonella serovars and highlight genetic differences that may inform strategies for antibiotic resistance and virulence control, such as developing rapid diagnostic tools to detect the AMR (e.g. tet (D), and gyrA) or targeting serovar-specific virulence factors like fimbrial adherence genes in Mbandaka to mitigate pathogenicity.

Indexed as

PoultrySalmonella entericaAnimalsComputer SimulationDrug Resistance, BacterialGenome, BacterialMultilocus Sequence TypingPhylogenyPoultry DiseasesRepublic of KoreaSalmonella Infections, AnimalSerogroupSerotypingVirulenceWhole Genome SequencinggyrA mutantIn silico serotypingSalmonella entericaWhole genome sequencing

Identifiers

PMID39979844
PMCPMC11841271

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.