Next Article in Journal
The Impact of Fluoride Pollution on Fungal Communities at the Watershed Scale: A Case Study of the Qingshui River, Ningxia
Previous Article in Journal
Chelerythrine-Mediated Growth Inhibition and Resistance Mechanism in Bacillus tropicus
Previous Article in Special Issue
Isolation of ESBL-Producing Enterobacteriaceae in Food of Animal and Plant Origin: Genomic Analysis and Implications for Food Safety
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Microorganisms
Volume 13
Issue 12
10.3390/microorganisms13122732
microorganisms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Brief Report

Serratia nevei in Nigeria: First Report and Global Distribution

by
Ayodele Timilehin Adesoji
1,
Emmanuel Dayo Alabi
1,
Vittoria Mattioni Marchetti
2,* and
Roberta Migliavacca
2,3
1
Department of Microbiology, Federal University, Dutsin-Ma 821101, Katsina State, Nigeria
2
Microbiology and Clinical Microbiology Unit, Scienze Clinico, Chiurgiche, Diagnostiche e Pediatriche Department, University of Pavia, 27100 Pavia, Italy
3
Istituto di Ricovero e Cura a Carattere Scientifico Policlinico S. Matteo, 27100 Pavia, Italy
*
Author to whom correspondence should be addressed.
Microorganisms 2025, 13(12), 2732; https://doi.org/10.3390/microorganisms13122732
Submission received: 29 October 2025 / Revised: 24 November 2025 / Accepted: 25 November 2025 / Published: 29 November 2025
(This article belongs to the Special Issue Food Microorganisms and Genomics, 2nd Edition)
Browse Figures
Versions Notes

Abstract

Serratia species are opportunistic human pathogens found in diverse environmental habitats. Here, we report the first isolation of Serratia nevei from food samples in Nigeria. During a two-month epidemiological surveillance at a local food market in Dutsin-Ma, Katsina State, Nigeria, a total of 180 food samples were collected, and isolation and species identification were performed using chromogenic agar and MicroScan autoSCAN-4, respectively. Antimicrobial susceptibility and minimum inhibitory concentrations (MICs) were determined using the MicroScan autoSCAN-4 system. Strain F129B, recovered from a fresh, unprocessed beef sample, was initially identified as Klebsiella pneumoniae by chromogenic agar and MicroScan autoSCAN-4, and subsequently as Serratia marcescens by MALDI-TOF MS. Only Whole Genome Sequencing (WGS) and bioinformatics analyses confirmed its identity as S. nevei. The strain was then selected for further characterization by Whole Genome Sequencing (WGS) and bioinformatics analyses to confirm its identity. The strain was phenotypically resistant to amoxicillin/clavulanic acid and colistin, with elevated MICs for aztreonam (4 mg/L) and cefuroxime (16 mg/L). In silico analyses of its genome confirmed the isolate as S. nevei, harboring genes conferring resistance to β-lactams (blaSTR-2), aminoglycosides (aac (6′)-Ic), fosfomycin (fosA), streptomycin (satA), and tetracycline (tet (41)). Its virulence repertoire comprises genes associated with adhesion (yidE, yidR, yidQ), colicin tolerance (creA and creD), and heavy metal resistance (czcD, chrBACF operon). These findings underscore the need for genomic characterization for accurate species identification within the Serratia genus. Our findings revealed the emergence of S. nevei in the food supply chain and highlighted its potential for zoonotic transmission. Robust surveillance of the local food supply chain is urgently needed in north-western Nigeria.

1. Introduction

The genus Serratia consists of ubiquitous Gram-negative bacteria and belongs to the Yersiniaceae family [1]. The genus Serratia has been found in diverse environmental niches and comprises more than ten different species [2,3,4,5]. Recently, Serratia nevei was described by Cho and colleagues and included in the taxonomy of Serratia species [6]. In fact, Cho and colleagues recovered S. nevei from fresh farm produce (cucumber and basil) in Germany’s retail market, veterinary samples in Thailand, and clinical samples in Spain [6,7,8]. The impact of Serratia species on antimicrobial resistance has grown substantially over time, with a notable surge in 2020. This impact has been facilitated by plasmid-mediated transmission of genes encoding extended-spectrum beta-lactamases (ESBLs) and carbapenemases from other Enterobacterales [9]. Indeed, S. nevei has been reported to acquire clinically relevant antibiotic resistance traits, including genes conferring resistance to carbapenems. Additionally, colistin-resistant strains have also been documented [8,9]. However, frequent misidentification of species within the Serratia genus complicates surveillance efforts, contributing to persistent gaps in knowledge regarding its spread [10]. Nigeria has recently undertaken epidemiological surveillance studies on antibiotic-resistant Enterobacterales, focusing to a lesser extent on secondary Enterobacterales such as Serratia spp. [11].
Here, we report the first isolation of S. nevei in Nigeria and determine its antibiotic-resistant profiles, resistome, virulome, and its genomic relatedness to other S. nevei strains, thereby, providing insights into the global dissemination patterns of this uncommon species.

2. Materials and Methods

2.1. Strain Isolation, Preliminary Identification, and Antibiotic Suceptibility Tests

An epidemiological study was conducted in Dutsin-Ma town, Katsina State, Nigeria, between October and November 2022, to investigate the circulation of Klebsiella spp. strains within the area. A total of 300 samples were collected from three sampling sites: the Wednesday Market (the main market of the city), Malam Mande General Hospital, and the Comprehensive Health Care Centre. Of the total samples, 180 were obtained from food and animal sources, while 120 were collected from human clinical specimens. The food samples comprised locally processed ready-to-eat products, including balangu meat (n = 15) and suya meat (n = 15), as well as tubers (cassava, n = 10), fruits (garden egg, n = 10), and vegetables (cabbage, n = 20; spinach, n = 20; cucumber, n = 10). Animal samples consisted of raw beef meat (n = 55) and goat meat (n = 25) [12].
Bacterial isolation was performed on the collected samples using MacConkey and CHROM agar (Scharlab Italia s.r.l., Lodi, Italy). The bacterial isolates were subsequently shipped to the Department of Clinical-Surgical, Diagnostic, and Pediatric Sciences, Unit of Microbiology and Clinical Microbiology, at the University of Pavia, Italy, for further analysis.
At Pavia, species identification and analysis of the antimicrobial susceptibility patterns of the bacterial isolates were performed using the MicroScan autoSCAN-4 (Beckman Coulter, Brea, CA, USA) semi-automated system. The identified species were further confirmed using MALDI-TOF MS (Bruker Daltonics GmbH, Billerica, MA, USA) and analyzed using BioTyper version 3.0. The minimum inhibitory concentrations (MICs) obtained were interpreted following EUCAST breakpoints (2024).

2.2. Whole Genome Sequencing and Bioinformatics Analysis

One of the isolates (Strain ID: F129B), recovered on 27 October 2022, from beef, which was initially identified as Klebsiella pneumonia with MicroScan autoSCAN-4 but later identified as Serratia marcescens by MALDI-TOF-MS, was further analyzed for identity confirmation with Whole Genome Sequencing (WGS) and bioinformatic analysis due to this diagnostic discrepancy. The genomic DNA of F129B was extracted using the DNeasy Blood & Tissue kit (Qiagen, Hilden, Germany) and sequenced on an Illumina HiSeq PE150 platform (Illumina Inc., San Diego, CA, USA) with 350 bp paired-end sequencing, following library preparation with the Nextera XT library preparation kit. Reads were assembled within the Shovill pipeline, discharging short contigs with low coverage or pure homopolymers (https://github.com/tseemann/shovill, accessed on 12 September 2025). Assembled sequences were annotated using Rapid Annotation using Subsystems Technology (RAST server) [13]. The resistome and plasmid replicon content were determined by uploading the assembled sequences to ResFinder 4.1 and PlasmidFinder v2.1, respectively, available on the Center for Genomic Epidemiology website (https://www.genomicepidemiology.org/, accessed on 12 September 2025). Virulence determinants were evaluated using the SEED viewer, available on the RAST server [13]. To understand the virulome evolution and the potential of F129B in causing infections, evaluation of phage sequences was obtained using the online tool PHASTER (PHAge Search Tool Enhanced Release) (https://phaster.ca, accessed on 12 September 2025), while the phage classification was assessed through the online tool PhaBOX 2.0v [14,15,16]. Part-of-whole graphs and timeline depictions were represented using GraphPad Prism version 10.0.0 for Macintosh, GraphPad Software, Boston, MA, USA (www.graphpad.com, accessed on 12 September 2025). A Sankey diagram was created using SankeyMATIC (https://sankeymatic.com/about/, accessed on 12 September 2025).

2.3. Genomic Species Identification

Average nucleotide identity (ANI) analysis was performed using the FastANI tool (https://github.com/ParBLiSS/FastANI, accessed on 12 September 2025), whereas the digital DNA-DNA hybridization (dDDH) values were calculated using formula 2 in the Genome-to-Genome Distance Calculator version 2.1 [4,17,18].

2.4. Phylogenetic Analysis

Phylogenetic relationships were determined for the studied strain using the available 163 genomes of S. nevei retrieved from the NCBI database. SNP-based phylogeny was depicted using Parsnp v 2.0.5 (https://github.com/marbl/parsnp, accessed on 12 September 2025) using S. nevei LMG 31536 (GCA_037948395.1) as the reference genome [19]. Metadata on the 163 genomes are available in Supplementary Table S1. Clonality cut-off was set at SNPs ≤ 25 [20]. A graphic illustration of the trees was built with the Interactive Tree Of Life (iTOL) (https://itol.embl.de/, accessed on 12 September 2025). Clustering of the genetic sequences was performed on the total pool of S. nevei using the FastBaps algorithm [21]. The resistome of the 163 genomes was identified using ResFinder 4.1.

2.5. Data Availability

The nucleotide sequence of F129B was deposited and is available in GenBank under the Bioproject PRJNA1135675 (Biosample: SAMN42488087).

3. Results

Among the 180 food samples collected, 30 (16.7%) were recovered as presumptive Klebsiella pneumoniae isolates through preliminary species characterization using the MicroScan Autoscan system [10]. In detail, 20/30 were classified as K. pneumoniae, 5/30 Klebsiella quasipneumoniae subsp. similipneumoniae, 3/30 Klebsiella variicola subsp. variicola, 1/30 Klebsiella michiganensis, and the remaining 1/30 were K. pneumoniae but at lower ID values (ID < 85%). The isolate F129B underwent further investigation.
Unexpectedly, FI29B was later identified to belong to the S. marcescens species by MALDI-TOF MS with a low confidence score (<2.0). The prevalence of Serratia spp. was 0.6% (1/180) among all the samples collected. The antibiotic susceptibility profiles of the selected isolate (F129B) revealed resistance (R) to amoxicillin/clavulanic acid (>32 mg/L) and colistin (>4 mg/L R). Colistin resistance was expected as an intrinsic trait of Serratia spp. Additionally, increased MIC values were observed for aztreonam (4 mg/L) and cefuroxime (16 mg/L).

3.1. WGS and In Silico Analysis

The assembled genome of strain F129B comprises 5,369,846 bp with a genome coverage of 120×, and contains 5019 protein-coding genes, with a G+C content of 59.7%. Interestingly, the bioinformatic evaluation pointed out a different species. In fact, the highest FastANI and dDDH4 values for F129B were established with the reference genomes S. nevei LMG 31536 (GCA_037948395.1) (98.77% and 90.6%, respectively), instead of S. marcescens. F129B possessed a narrow resistome composed of aminoglycoside (aac (6′)-Ic), β-lactam (blaSTR-2), fosfomycin (fosA), streptomycin (satA), and tetracycline (tet (41)) resistance genes, confirming the antimicrobial susceptibility profile obtained (Figure 1A). Moreover, F129B harbored resistance traits to chromium compounds (chrBACF operon) and cadmium–zinc–cobalt (czcD). No acquired genes for the colistin resistance phenotype were pointed out. The resistome identified did not explain the susceptibility profile obtained. Its virulome included genes associated with adhesion (yidE, yidR, yidQ, which are involved in hyper-adhesion and biofilm formation), tolerance to colicin E2 (creA and creD, producing periplasmic and inner membrane protein), copper homeostasis (scsABCD, cutADEF, copC, and copD), and the 16 kDa Heat shock protein A/B (Figure 1A). No plasmid elements were detected. Interestingly, four phage regions were detected within the F129B chromosome: a 43.8 kb region carrying the virulence genes copC and copD and showing similarities with the Salmonella phage SEN34 (GenBank accession number: NC_028699.1), a 41.1 kb region with identities with the phage Enterobacter phage Arya (GenBank Accession number: NC_031048.1), a 9.3 kb and a 9.5 kb regions similar to Salmonella SPN3UB (NC_019545.1), and Klebsiella phage ST13-OXA48phi12.1 (GenBank Accession number: NC_ 049453.1). The phage classification indicated a temperate phage for all regions, except for the 9.5 kb region which was assigned as virulent (Figure 1A).

3.2. Genomic Relatedness

The SNP-based phylogenetic tree and the FastBaps algorithm revealed that S. nevei is globally structured in four distinct clusters (CL1-4) (Figure 1B). F129B fell within CL4 and clustered with GCA_039409615.1 and GCA_038444875.1, both collected in 2022 from human samples in Thailand and Spain, respectively. This clustering was confirmed by SNP count, with the lowest values observed for GCA_039409615.1 (SNPs n = 9301) and GCA_038444875.1 (SNPs n = 9513). F129B itself revealed identity with other S. nevei genomes, supported by the high number of SNPs (>9000). However, it exhibited the highest relatedness with GCA_029960205.1 (SNPs n = 9609), collected in 2022 from a human sample in Ecuador, as well as with GCA_008364245.1 (SNPs n = 9832), GCA_037948395.1 (SNPs n = 9832), GCA_008011825.1 (SNPs n = 9833), and GCA_008364335.1 (SNPs n = 9833), all isolated in 2015 from food samples in Germany (Figure 1B). These similarities suggest widespread dissemination of the infrequent S. nevei, highlighting its ability to adapt to both animal and human niches.
Evaluation of the S. nevei resistome revealed diverse compositions of antimicrobial resistance genes across the four clusters. Specifically, the S. nevei population was primarily associated with resistance to aminoglycosides, β-lactams, and tetracyclines, while CL3 showed a high propensity for acquiring carbapenem and sulphonamide resistance genes (Figure 1B), a trait scarce or absent in the remaining clusters.
Across the entire S. nevei population, the four clusters exhibited differences in their genomic size and geographic distribution. Numerically, CL3 (n = 84) and CL2 (n = 42) are the dominant clusters, followed by CL4 (n = 23), and then CL1 (n = 15). Geographically, CL3 showed a heterogeneous distribution, occurring in Australia, the USA, Japan, Spain, and Thailand. Similarly, CL4 was detected in Nigeria (in this study), as well as in Germany, Uruguay, Brazil, Ecuador, the USA, Spain, and Thailand. In contrast, CL1 and CL2 exhibit a more homogeneous distribution, primarily restricted to Spain, with sporadic occurrence in the USA (Figure 2A).
Temporally, CL3 emerged in 2002 and persisted steadily until 2022, while CL4 appeared sporadically in 2006 before increasing in prevalence in 2015, 2021, and 2022 (Figure 2B).
Microorganisms 13 02732 g001aMicroorganisms 13 02732 g001b
Figure 1. (A) Sankey diagram picturing resistome, virulome, and phage content of F129B. Diagram created using SankeyMATIC (https://sankeymatic.com/about/, accessed on 12 September 2025). Aac(6′)-Ic = aminoglycoside resistance gene, blaSTR-2 = β-lactam resistance gene, fosA = fosfomycin resistance gene, satA = streptomycin, tet(41) = tetracycline resistance gene. (B) iTOL v6 representation of SNPs-based phylogeny for the 164 available genomes, obtained by parsnp v 2.0.5, and the related origin and resistome. F129B is colored in red. AMR = antimicrobial resistance genes (grouped and colored by classes of antibiotics). The AMR refers to the presence of at least one resistance gene of the corresponding antibiotic class in the resistome.
Figure 1. (A) Sankey diagram picturing resistome, virulome, and phage content of F129B. Diagram created using SankeyMATIC (https://sankeymatic.com/about/, accessed on 12 September 2025). Aac(6′)-Ic = aminoglycoside resistance gene, blaSTR-2 = β-lactam resistance gene, fosA = fosfomycin resistance gene, satA = streptomycin, tet(41) = tetracycline resistance gene. (B) iTOL v6 representation of SNPs-based phylogeny for the 164 available genomes, obtained by parsnp v 2.0.5, and the related origin and resistome. F129B is colored in red. AMR = antimicrobial resistance genes (grouped and colored by classes of antibiotics). The AMR refers to the presence of at least one resistance gene of the corresponding antibiotic class in the resistome.
Microorganisms 13 02732 g001aMicroorganisms 13 02732 g001b
Microorganisms 13 02732 g002
Figure 2. (A) epidemiological map of S. nevei spread. In the pie chart: purple = cluster 1 (CL1); light blue = cluster 2 (CL2); green = cluster 3 (CL3); yellow = cluster 4 (CL4). The countries are colored based on the number of S. nevei genomes retrieved from NCBI. Pie charts elucidate the precise number of genomes related and the number of different clusters is expressed in percentage. (B) distribution of S. nevei genomes based on the year of isolation (n = 144/164). Purple = cluster 1 (CL1); light blue = cluster 2 (CL2); green = cluster 3 (CL3); yellow = cluster 4 (CL4). In the present graph, strains with no available metadata on the year of isolation have not been included (n = 13/20). Genomes with unknown metadata are not included in the depiction (n = 7/20). Timeline created by GraphPad v10.3.1.
Figure 2. (A) epidemiological map of S. nevei spread. In the pie chart: purple = cluster 1 (CL1); light blue = cluster 2 (CL2); green = cluster 3 (CL3); yellow = cluster 4 (CL4). The countries are colored based on the number of S. nevei genomes retrieved from NCBI. Pie charts elucidate the precise number of genomes related and the number of different clusters is expressed in percentage. (B) distribution of S. nevei genomes based on the year of isolation (n = 144/164). Purple = cluster 1 (CL1); light blue = cluster 2 (CL2); green = cluster 3 (CL3); yellow = cluster 4 (CL4). In the present graph, strains with no available metadata on the year of isolation have not been included (n = 13/20). Genomes with unknown metadata are not included in the depiction (n = 7/20). Timeline created by GraphPad v10.3.1.
Microorganisms 13 02732 g002

4. Discussion

S. nevei is an uncommon pathogen that has been reported in specific geographic regions, including Spain and Germany, in both clinical and environmental settings [6,7]. Here, we report the first recovery of S. nevei from beef in Nigeria. Strain F129B exhibited low antimicrobial resistance traits, but possessed significant virulence factors, particularly related to adhesion, resistance to heavy metals, and copper homeostasis. Additionally, the 16 kDa heat shock proteins A and B harbored by the strain play a role in stress response, virulence, and defense in Serratia sp. TEL [22]. The presence of virulence gene-mediating pathways involving adhesion and copper homeostasis highlights the capacity and possibility of S. nevei emerging as a moderately virulent microorganism. Studies on the actual virulence of S. nevei are absent from the literature and require further investigation.
The apparent absence of mobile elements, such as plasmids, suggest that F129B has a limited propensity to acquire additional external traits, such as resistance and virulence genes. However, phage regions were identified within the F129B chromosome. Phages, also known as bacteriophages, are viruses that can infect bacteria. Phages that are classified as temperate can integrate within the bacterium’s host chromosome, whereas virulent phages can immediately induce bacterium cell destruction through lysis [23]. Temperate phages may provide a mutual evolutionary advantage to the bacteria by allowing the introduction of additional genes, such as virulence and antibiotic resistance genes [24]. The presence of phage elements in S. nevei suggests a certain plasticity of its genome, with the possibility of acquiring new, evolutionarily favorable traits.
The absence of genes encoding ESBL does not diminish the clinical relevance of S. nevei, as the isolate carries the chromosomal β-lactamase-encoding gene blaSRT-2. In S. marcescens, blaSRT-2 is often found alongside other β-lactam resistance genes, including blaCTX-M-3, blaTEM-1, blaKPC-2, and the aminoglycoside resistance gene aac(6′)-Ic [25,26,27]. The S. nevei strain we characterized in this study harbored only aac(6′)-Ic with blaSRT-2, but cases of carbapenemase-producing S. nevei have been already reported in the scientific literature. During wastewater treatment plant surveillance in Georgia, USA, Hassan and coauthors identified seven high-level colistin-resistant S. nevei strains carrying mcr-9 resistance genes [27]. Moreover, pan-drug-resistant S. nevei has recently been reported in veterinary settings. Leelapsawas and co-authors were the first to describe the occurrence of the clinically relevant carbapenemase OXA-181 in two S. nevei strains of canine origin, highlighting the species’ ability to acquire relevant antimicrobial-resistant traits [7]. Furthermore, an emerging S. nevei and VIM producer has been highlighted in a large Intensive Care Unit (ICU) in Spain. Over the last 20 years, it has been identified as a source of ESBL outbreaks and carbapenemase-producing Enterobacterales [8]. The precise effect of S. nevei on humans is unclear and needs further investigation. However, its ability to adapt to human, veterinary, and aquatic environments may pose a challenge to global public health due to its propensity to acquire antimicrobial resistance and virulence factors.
The phylogenetic and clustering analysis highlighted a heterogeneous feature within the S. nevei population. F129B fell in cluster CL4, which showed a global circulation, but to a lesser extent than when compared to CL3, which seemed to be the most representative cluster. Moreover, F129B had a narrow resistome, excluding carbapenemase genes, which were common within CL4. These findings demonstrate the genomic differences within the S. nevei population, potentially allowing for the development of MDR or PDR phenotypes and their implication in infectious diseases in both animals and humans. However, these speculations require confirmation through further analyses and specific virulence assessment experiments.
Definitive species identification undoubtedly makes the overall characterization of S. nevei difficult. To date (21 November 2025), in the scientific literature there are a total of 14 papers available reporting on S. nevei strains in different niches (Table 1). As reported in the literature, precise identification and species differentiation is only possible through molecular approaches along with the use of bioinformatics tools. As in this study, precise identification is achieved using omics techniques such as WGS, while routine systems based on culture growth or mass spectrometry have proved to be inadequate. The frequent misidentification of S. nevei as S. marcescens further complicates efforts to track its spread, resulting in persistent gaps in knowledge about its dissemination.

5. Conclusions

In conclusion, this report confirms the first isolation of S. nevei from food in Nigeria and highlights the importance of WGS, not only for definitive identification but also for revealing important virulence genes and phage elements. These findings further highlight the importance of improved species identification and molecular characterization within the Serratia genus, due to its epidemiological and clinically relevant features. In the context of the One-Health approach, bacterial species previously considered minor require surveillance to prevent their evolution into reservoirs of emerging (new) infectious diseases, as environmental, animal, and human interactions can facilitate pathogen spillover and adaptation. Given that only a single isolate of S. nevei was incidentally recovered during the surveillance of Klebsiella species in the local food supply chain, the findings do not provide a comprehensive representation of this species’ distribution in the region. This limitation is acknowledged in the study. In order to better understand the real distribution of S. nevei, this microorganism should be included in passive surveillance programs within different ecological niches.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/microorganisms13122732/s1, Table S1: Metadata on the 163 S. nevei genomes retrieved from NCBI database.

Author Contributions

A.T.A.: Conceptualization, sample collection, writing—original draft, writing—review and editing. E.D.A.: Sample collection, writing—original draft, writing—review and editing. V.M.M.: Conceptualization, investigation, formal analysis, data curation, writing—original draft, writing—review and editing. R.M.: Funding acquisition, supervision, validation, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by EU funding within the Next Generation EU-MUR PNRR Extended Partnership initiative on Emerging Infectious Diseases (Project no: P E00000007, INF-ACT) and Committee for International Cooperation and Development (CICOPS), University of Pavia, Italy.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethical Review Committee of Katsina State Ministry of Health (protocol code Nigeria MOH/ADM/SUB/1152/1/654; date: 27 September 2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are openly available in the GenBank repository at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1135675 (accessed on 25 September 2025), reference number SAMN42488087.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Zhu, W.; Chen, X.; Shen, H.; Wei, M.; Yang, C.; Gu, L. Genomic diversity, antimicrobial resistance and dissemination of Serratia marcescens complex in patients admitted to ICUs. Front. Cell. Infect. Microbiol. 2025, 15, 1672468. [Google Scholar] [CrossRef] [PubMed]
  2. Matilla, M.A.; Udaondo, Z.; Salmond, G.P. Genome sequence of the Oocydin A-producing rhizobacterium Serratia plymuthica 4Rx5. Microbiol. Resour. Announc. 2018, 7, e00997-18. [Google Scholar] [CrossRef]
  3. Chen, S.; Blom, J.; Walker, E.D. Genomic, physiologic, and symbiotic characterization of Serratia marcescens strains isolated from the mosquito Anopheles stephensi. Front. Microbiol. 2017, 8, 1483. [Google Scholar] [CrossRef]
  4. Williams, D.J.; Grimont, P.A.; Cazares, A.; Grimont, F.; Ageron, E.; Pettigrew, K.A.; Cazares, D.; Njamkepo, E.; Weill, F.X.; Heinz, E.; et al. The genus Serratia revisited by genomics. Nat. Commun. 2022, 13, 5195. [Google Scholar] [CrossRef] [PubMed]
  5. Tavares-Carreon, F.; De Anda-Mora, K.; Rojas-Barrera, I.C.; Andrade, A. Serratia marcescens antibiotic resistance mechanisms of an opportunistic pathogen: A literature review. PeerJ 2023, 11, e14399. [Google Scholar] [CrossRef]
  6. Cho, G.S.; Stein, M.; Brinks, E.; Rathje, J.; Lee, W.; Suh, S.H.; Franz, C.M.A.P. Serratia nevei sp. nov. and Serratia bockelmannii sp. nov., isolated from fresh produce in Germany and reclassification of Serratia marcescens subsp. sakuensis Ajith Kumar et al. 2003 as a later heterotypic synonym of Serratia marcescens subsp. marcescens. Syst. Appl. Microbiol. 2020, 43, 126055, Erratum in Syst. Appl. Microbiol. 2020, 43, 126082. [Google Scholar] [CrossRef]
  7. Leelapsawas, C.; Sroithongkham, P.; Payungporn, S.; Nimsamer, P.; Yindee, J.; Collaud, A.; Perreten, V.; Chanchaithong, P. First report of blaOXA-181-carrying IncX3 plasmids in multidrug-resistant Enterobacter hormaechei and Serratia nevei recovered from canine and feline opportunistic infections. Microbiol. Spectr. 2024, 12, e0358923. [Google Scholar] [CrossRef]
  8. Aracil-Gisbert, S.; Fernández-De-Bobadilla, M.D.; Guerra-Pinto, N.; Serrano-Calleja, S.; Pérez-Cobas, A.E.; Soriano, C.; de Pablo, R.; Lanza, V.F.; Pérez-Viso, B.; Reuters, S.; et al. The ICU environment contributes to the endemicity of the “Serratia marcescens complex” in the hospital setting. mBio 2024, 15, e0305423. [Google Scholar] [CrossRef]
  9. Pérez-Viso, B.; Hernández-García, M.; Rodríguez, C.M.; Fernández-de-Bobadilla, M.D.; Serrano-Tomás, M.I.; Sánchez-Díaz, A.M.; Avendaño-Ortiz, J.; Coque, T.M.; Ruiz-Garbajosa, P.; Del Campo, R.; et al. A long-term survey of Serratia spp. bloodstream infections revealed an increase of antimicrobial resistance involving adult population. Microbiol. Spectr. 2024, 12, e02762-23, Erratum in Microbiol. Spectr. 2024, 12, e02425-24. [Google Scholar] [CrossRef]
  10. Harch, S.A.; Jenkins, F.; Farhat, R.; van Hal, S.J. Complexities in species identification for Serratia marcescens complex for the modern microbiology laboratory. Microbiol. Spectr. 2025, 13, e01361-24. [Google Scholar] [CrossRef] [PubMed]
  11. Uzeh, R.E.; Imafidon, S. The occurrence of antibiotic-resistant enteric bacteria in Selected Nigerian traditional dairy products. Afr. Health Sci. 2022, 22, 619–626. [Google Scholar] [CrossRef]
  12. Adesoji, A.T.; Marchetti, V.M.; Cortimiglia, C.; Piscopiello, F.; Petrizzi, I.; Piazza, A.; Alabi, E.D.; Cocconcelli, P.S.; Migliavacca, R. Antibiotic resistance and novel Sequence Types of Klebsiella spp. in human, animal, and food sources: A One Health perspective from Northern Nigeria. Curr. Res. Microb. Sci. 2025, 9, 100458. [Google Scholar] [CrossRef]
  13. Aziz, R.K.; Bartels, D.; Best, A.A.; DeJongh, M.; Disz, T.; Edwards, R.A.; Formsma, K.; Gerdes, S.; Glass, E.M.; Kubal, M.; et al. The RAST Server: Rapid annotations using subsystems technology. BMC Genom. 2008, 9, 75. [Google Scholar] [CrossRef]
  14. Arndt, D.; Grant, J.; Marcu, A.; Sajed, T.; Pon, A.; Liang, Y.; Wishart, D.S. PHASTER: A better, faster version of the PHAST phage search tool. Nucleic Acids Res. 2016, 44, W16–W21. [Google Scholar] [CrossRef]
  15. Zhou, Y.; Liang, Y.; Lynch, K.H.; Dennis, J.J.; Wishart, D.S. PHAST: A fast phage search tool. Nucleic Acids Res. 2011, 39, W347–W352. [Google Scholar] [CrossRef] [PubMed]
  16. Shang, J.; Peng, C.; Liao, H.; Tang, X.; Sun, Y. PhaBOX: A web server for identifying and characterizing phage contigs in metagenomic data. Bioinform. Adv. 2023, 3, vbad101. [Google Scholar] [CrossRef] [PubMed]
  17. Jain, C.; Rodriguez-R, L.M.; Phillippy, A.M.; Konstantinidis, K.T.; Aluru, S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat. Commun. 2018, 9, 5114. [Google Scholar] [CrossRef]
  18. Treangen, T.J.; Ondov, B.D.; Koren, S.; Phillippy, A.M. The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biol. 2014, 15, 524. [Google Scholar] [CrossRef] [PubMed]
  19. Tonkin-Hill, G.; Lees, J.A.; Bentley, S.D.; Frost, S.D.W.; Corander, J. Fast hierarchical Bayesian analysis of population structure. Nucleic Acids Res. 2019, 47, 5539–5549. [Google Scholar] [CrossRef]
  20. Coll, F.; Raven, K.E.; Knight, G.M.; Blane, B.; Harrison, E.M.; Leek, D.; Enoch, D.A.; Brown, N.M.; Parkhill, J.; Peacock, S.J. Definition of a genetic relatedness cutoff to exclude recent transmission of meticillin-resistant Staphylococcus aureus: A genomic epidemiology analysis. Lancet Microbe 2020, 1, e328–e335. [Google Scholar] [CrossRef]
  21. Guo, C.; Wu, J.Y. Pathogen Discovery in the Post-COVID Era. Pathogens 2024, 13, 51. [Google Scholar] [CrossRef]
  22. Thompson, S.A.; Maani, E.V.; Lindell, A.H.; King, C.J.; McArthur, J.V. Novel tetracycline resistance determinant isolated from an environmental strain of Serratia marcescens. Appl. Environ. Microbiol. 2007, 73, 2199–2206. [Google Scholar] [CrossRef]
  23. Gummalla, V.S.; Zhang, Y.; Liao, Y.T.; Wu, V.C.H. The Role of Temperate Phages in Bacterial Pathogenicity. Microorganisms 2023, 11, 541. [Google Scholar] [CrossRef]
  24. Wu, L.T.; Tsou, M.F.; Wu, H.J.; Chen, H.E.; Chuang, Y.C.; Yu, W.L. Survey of CTX-M-3 extended-spectrum β-lactamase (ESBL) among cefotaxime-resistant Serratia marcescens at a medical center in middle Taiwan. Diagn. Microbiol. Infect. Dis. 2004, 49, 125–129. [Google Scholar] [CrossRef]
  25. Yu, W.L.; Ko, W.C.; Cheng, K.C.; Chen, H.E.; Lee, C.C.; Chuang, Y.C. Institutional spread of clonally related Serratia marcescens isolates with a novel AmpC cephalosporinase (S4): A 4-year experience in Taiwan. Diagn. Microbiol. Infect. Dis. 2008, 61, 460–467. [Google Scholar] [CrossRef] [PubMed]
  26. Srinivasan, V.B.; Rajamohan, G. Genome analysis of urease positive Serratia marcescens, co-producing SRT-2 and AAC (6′)-Ic with multidrug efflux pumps for antimicrobial resistance. Genomics 2019, 111, 653–660. [Google Scholar] [CrossRef] [PubMed]
  27. Hassan, J.; Osman, M.; Xu, T.; Naas, T.; Schiff, S.J.; Mann, D.; Esseili, M.A.; Deng, X.; Kassem, I.I. Monitoring sewage and effluent water is an effective approach for the detection of the mobile colistin resistance genes (mcr) and associated bacterial hosts in the human population and environment in the USA. Environ. Pollut. 2025, 366, 125515. [Google Scholar] [CrossRef]
  28. Abreo, E.; Valle, D.; González, A.; Altier, N. Control of damping-off in tomato seedlings exerted by Serratia spp. strains and identification of inhibitory bacterial volatiles in vitro. Syst. Appl. Microbiol. 2021, 44, 126177. [Google Scholar] [CrossRef]
  29. Yaikhan, T.; Suwannasin, S.; Singkhamanan, K.; Chusri, S.; Pomwised, R.; Wonglapsuwan, M.; Surachat, K. Genomic Characterization of Multidrug-Resistant Enterobacteriaceae Clinical Isolates from Southern Thailand Hospitals: Unraveling Antimicrobial Resistance and Virulence Mechanisms. Antibiotics 2024, 13, 531. [Google Scholar] [CrossRef] [PubMed]
  30. Ota, Y.; Chen, F.; Prah, I.; Mahazu, S.; Watanabe, K.; Kinoshita, T.; Gu, Y.; Nukui, Y.; Saito, R. Metatranscriptomic Analysis Reveals Actively Expressed Antimicrobial-Resistant Genes and Their Hosts in Hospital Wastewater. Antibiotics 2024, 13, 1122. [Google Scholar] [CrossRef]
  31. Kang, M.; Harjadi, D.; Hoover, E.; Dan, H.; Adam, B.; Huang, H. Complete genome sequences of six Serratia strains with multiple resistance genes isolated from food products in Canada. Microbiol. Resour. Announc. 2025, 14, e0030125. [Google Scholar] [CrossRef] [PubMed]
  32. Liu, X.; Liu, Z.; Yu, K.; Huang, Z.; Gao, H.; Bai, X.; Sun, Z.; Wei, Q.; Wang, D. Global genomic epidemiology and plasmid-mediated dissemination of blaKPC and blaNDM in the Serratia marcescens complex. Curr. Res. Microb. Sci. 2025, 9, 100436. [Google Scholar] [CrossRef]
  33. Zhu, W.; Chen, X.; Shen, H.; Wei, M.; Gu, L.; Liu, Q. Genomic evolution, antimicrobial resistance, and dissemination of global Serratia spp. unveil increasing species diversity and carbapenemae-resistance: A retrospective and genomic epidemiology study. Curr. Res. Microb. Sci. 2025, 9, 100456. [Google Scholar] [CrossRef]
  34. Peirano, G.; Matsumura, Y.; Pitout, J.D.D. Molecular epidemiology of global carbapenemase-producing Serratia spp. (2015–2017). Eur. J. Clin. Microbiol. Infect. Dis. 2025; Epub ahead of print. [Google Scholar] [CrossRef] [PubMed]
  35. Furlan, J.P.R.; Bueno, G.C.; Sousa-Carmo, R.R.; Silva, R.L.O.; Barbosa, M.R.F.; Sato, M.I.Z.; Lincopan, N.; Schenkman, S. Emergence of Serratia nevei co-producing NDM-1 and CTX-M-15 in urban wastewater. Microbiol Spectr. 2025, e0137825. [Google Scholar] [CrossRef] [PubMed]
Table 1. Information on the S. nevei publications available on 21 November 2025.
Table 1. Information on the S. nevei publications available on 21 November 2025.
AuthorSource of IsolationCountryIdentification MethodDOI
Cho et al., 2020 [6]CucumberGermany16S rRNA, DNA-DNA hybridizationhttps://doi.org/10.1016/j.syapm.2020.126055
Abreo et al., 2021 [28]LocustsUruguaygyrB and ANIhttps://doi.org/10.1016/j.syapm.2020.126177
Pérez-Viso et al., 2024 [9]Bloodstream infectionsSpainTaxonomic Sequence Classification System Kraken and PATO package in R, calculating the MASH distancehttps://doi.org/10.1128/spectrum.02762-23
Leelapsawas et al., 2024 [7]Canine infectionThailandANIhttps://doi.org/10.1128/spectrum.03589-23
Aracil-Gisbert et al., 2024 [8]ICU sink and clinical samplesSpain16S rRNA and DNA-DNA hybridizationhttps://doi.org/10.1128/mbio.03054-23
Yaikhan et al., 2024 [29]Clinical samplesThailandANIhttps://doi.org/10.3390/antibiotics13060531
Hassan et al., 2025 [27]Raw sewage and waterUSAWGShttps://doi.org/10.1016/j.envpol.2024.125515
Ota et al., 2024 [30]Hospital wastewaterJapanGTDB Toolkit Classify v2.1.0https://doi.org/10.3390/antibiotics13121122
Kang et al., 2025 [31]FoodCanadaVITEK MS system (bioMérieux) and
WGS		https://doi.org/10.1128/mra.00301-25
Liu et al., 2025 [32]Clinical samplesUSA, Canada, Romania, China, South Africa, BulgariaMALDI (as S. marcescens) and TYGS platformhttps://doi.org/10.1016/j.crmicr.2025.100436
Zhu et al., 2025 [33]Clinical samples from tertiary teaching hospitalChinadDDH and FastANI v1.34https://doi.org/10.1016/j.crmicr.2025.100456
Peirano et al., 2025 [34]Clinical samplesSouth Africa, RomaniaTYGS and ANIhttps://doi.org/10.1007/s10096-025-05254-x
Furlan et al., 2025 [35]WastewaterBrazilANI and dDDHhttps://doi.org/10.1128/spectrum.01378-25
Zhu et al., 2025 [1]Intensive Unit Care patientsChinaGenome Database Taxonomy (GTDB)https://doi.org/10.3389/fcimb.2025.1672468
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Adesoji, A.T.; Alabi, E.D.; Mattioni Marchetti, V.; Migliavacca, R. Serratia nevei in Nigeria: First Report and Global Distribution. Microorganisms 2025, 13, 2732. https://doi.org/10.3390/microorganisms13122732

AMA Style

Adesoji AT, Alabi ED, Mattioni Marchetti V, Migliavacca R. Serratia nevei in Nigeria: First Report and Global Distribution. Microorganisms. 2025; 13(12):2732. https://doi.org/10.3390/microorganisms13122732

Chicago/Turabian Style

Adesoji, Ayodele Timilehin, Emmanuel Dayo Alabi, Vittoria Mattioni Marchetti, and Roberta Migliavacca. 2025. "Serratia nevei in Nigeria: First Report and Global Distribution" Microorganisms 13, no. 12: 2732. https://doi.org/10.3390/microorganisms13122732

APA Style

Adesoji, A. T., Alabi, E. D., Mattioni Marchetti, V., & Migliavacca, R. (2025). Serratia nevei in Nigeria: First Report and Global Distribution. Microorganisms, 13(12), 2732. https://doi.org/10.3390/microorganisms13122732

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop