Skip to main content
Journal of Genetic Engineering and Biotechnology
Download PDF

Whole genome sequence and comparative genomics analysis of multidrug-resistant Staphylococcus xylosus NM36 isolated from a cow with mastitis in Basrah city

Journal of Genetic Engineering and Biotechnology volume 21, Article number: 163 (2023) Cite this article

Abstract

Background

Staphylococcus xylosus is a coagulase-negative, gram-positive coccus that is found in the environment and as a commensal organism on the skin and mucosal surfaces of animals. Despite the fact that S. xylosus is considered a nonpathogenic bacterium, several studies have linked S. xylosus to opportunistic infections in both animals and humans. During an investigation of mastitis-causing agents in the governorate of Basrah, Iraq, we identified an antibiotic-resistant strain of S. xylosus NM36 from a milk sample from a cow with chronic mastitis. In addition to robust biofilm formation, multiple antibiotic resistance phenotypes were found. To further understand the genetic background for these phenotypes, the full genome of S. xylosus NM36 was analyzed.

Results

The genome consisted of a single circular 2,668,086 base pairs chromosome containing 32.8% G + C. There were 2454 protein-coding sequences, 4 ribosomal RNA (rRNA) genes, and 50 transfer RNA (tRNA) genes in the genome. In addition, genetic variation was studied by searching sequence data against a representative reference genome. Consequently, single-nucleotide polymorphism analysis was conducted and showed that there were 46,610 single-nucleotide polymorphisms (SNPs), 523 insertions, and 551 deletions. In order to overcome antibiotics, S. xylosus NM36 had been armed with several antibiotic resistance genes from several groups and families. The genome annotation service in PathoSystems Resource Integration Center (PATRIC) and Rapid Annotation using Subsystem Technology (RAST) annotation servers showed that there are multiple antimicrobial resistance elements, including antibiotic inactivation enzymes (BlaZ family, FosB), antibiotic resistance gene clusters (TcaB, TcaB2, TcaR), proteins involved in methicillin resistance (LytH, FmtA, FemC, HmrB, HmrA), TetR family transcriptional regulators, and efflux pumps conferring antibiotic resistance (NorA). In addition, we investigated and categorized the biofilm and quorum-sensing elements of the NM36 strain and found that it has multiple subsets of biofilm regulators, confirming its pathogenic nature.

Conclusions

These findings necessitate a reevaluation of microbial and clinical interventions when dealing with coagulase-negative staphylococci, particularly in the context of studies pertaining to public health. This is the first time, to our knowledge, that the entire genome of S. xylosus has been sequenced in Iraq.

Background

Staphylococcus xylosus are coagulase-negative, gram-positive cocci that are widespread in the environment and are commensal on the skin and mucosal surfaces of animals. Despite the fact that S. xylosus is considered a nonpathogenic bacterium, opportunistic infections in animals and humans have been linked to S. xylosus in several studies. S. xylosus is widespread and could be found in a variety of environments, including contaminated water, meat, fodder, and soil surfaces [4, 15, 19, 27, 29, 31, 34, 36]. It has been shown that coagulase-negative staphylococci (CoNS) can play an important role in bovine intramammary infections and also share mobile genetic elements that carry virulent factors such as antibiotic resistance markers with other family members, including S. aureus [21, 34, 62]. In addition to its clinical relevance, S. xylosus may contribute to the pathogenicity of other staphylococci through horizontal gene transfer of antibiotic resistance elements such as the SCCmec type 11 region and tetracycline resistance [33, 37]. Since S. xylosus is becoming increasingly infectious alongside other staphylococci, it is essential to investigate the genome of this ubiquitous commensal. S. xylosus has been sequenced at the genome level far less frequently than S. aureus in the public domain, and none has been performed in Iraq. Even though previous studies have done genome annotation and analysis of S. xylosus, a thorough exploration of the pathogenicity of this bacterium based on genomic information gained through next-generation sequencing (NGS) is still necessary, particularly for relating data from various geographic regions [29]. During an investigation of mastitis-causing agents in the governorate of Basrah, Iraq, we identified an antibiotic-resistant strain of S. xylosus (coagulase-negative staphylococci (CoNS) from a milk sample of a cow with chronic mastitis. Using disc diffusion method, we found that this isolate was resistant to methicillin, ampicillin, cefoxitin, oxacillin, and tetracycline but was sensitive to vancomycin. In addition, the strain showed notable biofilm-formation capacity. To further understand the genetic background for these phenotypes, Staphylococcus xylosus NM36 whole genome sequencing was undertaken to find variant information and to perform gene annotation on key genes relevant to antibiotics and biofilm formation.

Methods

S. xylosus NM36 was isolated from a clinical mastitis of a cow. Isolation and identification were conducted using standard microbiological procedures. Confirmation was achieved by sequencing the PCR product of the 16 s RNA using universal primers 27F and 1492R [22] and blast analysis using the NCBI database [53]. Genomic DNA was extracted using the QIAamp DNA Mini Kit, Qiagen USA, catalog number 51304, according to the manufacturer’s instructions. DNA samples were sent for whole genome sequencing using the Illumina platform sequencer (Macrogen, Korea). After conducting quality control (QC), samples for library construction were subjected to random DNA fragmentation, followed by 5′ and 3′ adapter ligation. Adapter-ligated fragments were amplified and purified by PCR and gel. The library was fed into a flow cell for cluster generation, where fragments were captured on a lawn of surface-bound oligos that were complementary to the library adapters. By means of bridge amplification, each fragment was amplified into separate clonal clusters. After the generation of clusters, the templates were ready for sequencing. Following sequencing, raw reads were analyzed for overall read quality, total bases, total reads, and GC (%), and basic statistics were calculated. In order to reduce biases in analysis, FastQC [3] and quality-filtering processes were performed. The quality of the produced data was determined by applying the phred quality score at each cycle Q20 (%) and Q30 (%) which helps measure the quality of the identification of the nucleobases generated by automated DNA sequencing [20]. The raw reads were de novo assembled into contigs using the SPAdes v.3.5 bioinformatics tool [6].

Genome analysis and comparison with other genomes

Staphylococcus xylosus NM36’s assembled genome was submitted to PATRIC’s comprehensive genome analysis service, which uses PATRIC’s curated collection of representative antimicrobial resistance (AMR) gene sequence variants [63]. In order to map reads obtained from sequencing, Staphylococcus xylosus was used as a reference genome. Filtered reads were mapped to the reference genome with BWA—Burrows-Wheeler Aligner [35]. After read mapping, Picard and SAMTools were used to remove duplicate reads and find variant information [47]. Broad Institute, [16]. To contrast the mapping results, the assembled genome was further annotated for functional genes in subsystem categories using the classic RAST and RASTtk server [5, 11] and the SEED tool [45]. In all annotation and comparison processes, the similarity threshold was at least 95% identity. The annotated features were further verified and illustrated using the PROKSEE server [25] which was used for identifying conserved and unique sequence features and to generate high-quality maps as previously described [56]. Using the SEED tool, the Staphylococcus xylosus NM36 genome was further compared to other closely related genomes (ANMR00000000.1, CP007208.1, CP008724.1, CP031275.1, CP066721.1).

Genome submissions to NCBI GenBank

The genome sequence of Staphylococcus xylosus NM36 has been deposited at GenBank—DDBJ/ENA/GenBank under the accession number GenBank JARUHN000000000.1. The annotation was added by the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) [57].

SNP and INDEL discovery

The mapped data were examined for single-nucleotide polymorphism (SNPs) and insertion/deletion (INDEL) variations compared to the reference genome. In this analysis, the reference genome is based on RefSeq assembly accession: GCF_000709415.1 (CP008724.1). After removing duplication and finding variants’ information with SAMTools, each variant’s information was gathered and classified by chromosomes or scaffolds.

Phylogenetic analysis

The phylogenic analysis package at PATRIC [63] was used to categorize reference and representative genomes. PATRIC incorporated the reference and representative genomes into the phylogenetic analysis included in the report on Comprehensive Genome Analysis. In summary, Mash/MinHash identified the closest reference and representative genomes. From these genomes, PATRIC global protein families (PGFams) were selected to ascertain the phylogenetic placement of this genome. The nucleotides of these sequences were mapped, and multiple sequence comparison by log expectation (MUSCLE) was used to align the protein sequences of these families. The combined set of amino acid and nucleotide alignments was concatenated into a data matrix, and RaxML was used to analyze this matrix, with rapid bootstrapping used to generate the support values in the tree. In addition, a phylogenetic tree was built based on the 16 s RNA sequence relationship using the NCBI Tree Viewer (TV). For this comparison, we selected only the sequences whose genomes had been fully sequenced and deposited in the NCBI database.

Results

Genome annotation

Based on the annotation data and the contrast to other genomes in PATRIC within the same species, this genome is considered of good quality. This was confirmed by the phred quality score of bases over Q20 and Q30 which were 98.47% and 94.34%, respectively, after read filtering. The Comprehensive Genome Analysis showed that this assembled genome has 73 contigs, with a total length of 2,668,086 bp, 2454 coding proteins (Table 1, Additional file 1: Appendices A: Table S1). Furthermore, the average GC content is 32.8%. A schematic representation for GC content and GC skew analysis is shown in Fig. 1. A subsystem is a set of proteins that together implement a specific biological process or structural complex. The annotation process included an analysis of the subsystems unique to this genome, which revealed that there are 278 subsystems. An overview of the subsystems for this genome is provided in Fig. 2. Single-nucleotide polymorphism (SNP) analysis showed that there were 46,610 SNPs, 523 insertions, and 551 deletions compared to the reference genome (Additional file 1: Appendices B: Table S2).

Table 1 Summary for the genome analysis report of NCBI prokaryotic genome annotation pipeline (PGAP)
Full size table
Fig. 1
figure 1

Circular genome representation of Staphylococcus xylosus NM36 (PROKSEE server). The inner most ring represents chromosome position, and the red-colored ring represents the genome backbone (in contigs). A GC content (black) and GC skew (green represents values greater than the genome average, whereas purple represents value less than the genome average. B The open-reading frames on the forward strand (outside of the backbone) and reverse strands (inside of the backbone)

Full size image
Fig. 2
figure 2

Staphylococcus xylosus NM36 distribution statistics for subsystem categories. Using the Rapid Annotation System Technology (RAST) server, the genome was annotated. The pie chart displayed the number of each subsystem feature, and the SEED viewer displayed the subsystem coverage. The green bar of the subsystem coverage represents the proportion of proteins included in the subsystems, while the blue bar represents the proportion of proteins excluded from the subsystems

Full size image

Phylogenetic analysis

PATRIC provided the reference and representative genomes, which were included in the phylogenetic analysis. The reference and representative genotypes closest to them were determined and illustrated in Fig. 3. It turned out that strains S. xylosus HKUOPL8 and NJ (ANMR00000000.1) have the highest similarity. In addition, a phylogenetic tree was built based on the 16 s RNA sequence relationship using NCBI Tree Viewer (TV) for the sequences for which their genome had been fully sequenced (Fig. 4). This allowed us to select five related genomes for sequence-based comparison by the RAST tool, which revealed that strain NM36 and the other closely related strains possess a high abundance of coding DNA sequences (CDS), mainly coding for carbohydrate and amino acid metabolism (Figs. 2 and 5). In all 5 genomes, there are 1188 genes with the same annotated functions with at least 95–100% identity.

Fig. 3
figure 3

Phylogenic relationship representation of S. xylosus NM36 based on the genome features (using the genome annotation service in PATRIC)

Full size image
Fig. 4
figure 4

16S rRNA sequences distance tree depicting the relationship between S. xylosus NM36 (shown in yellow) and related S. xylosus strains in the NCBI database (strains with complete genome) using NCBI TV

Full size image
Fig. 5
figure 5

Graphical genome comparison map of the NM36 strain (reference) with five closely related species using the Seed Viewer sequence-based comparison tool in the RAST server. From outside to inside rings: (1) strain HKUOPL8 (CP007208.1), (2) strain NJ (ANMR00000000.1), (3) strain SMQ-121 (CP008724.1), (4) strain 2 (CP031275.1), and (5) strain 2.1523 (CP066721.1). From purple (100%) to pale red (10%), the colors represent the similarity of amino acids to the reference genome. The NM36 reference strain’s genome is not depicted in the figure

Full size image

Resistance to antibiotics and toxic compounds

A significant number of the genes annotated have homology to known virulence factors, transporters, drug targets, and antimicrobial resistance genes. To filter the results, we combined and filtered the results from the SEED, PATRIC, and PROKSEE servers into one list. Then we investigated AMR gene sequence variants and assigned to each AMR gene a functional annotation, a drug class, and the specific antibiotic it confers resistance to. A summary of the AMR genes annotated in this genome and the corresponding AMR mechanisms is provided in Table 2.

Table 2 S. xylosus NM36 genome analysis for antibiotics resistance. The annotation was based on the protein domain database [38,39,40,41]
Full size table

Quorum sensing and biofilm formation

Since the biofilm is essential to staphylococcal biology, several regulatory systems that take into account the physiological state of the cell, environmental cues, and the dynamics within the staphylococcal community tightly regulate the formation and disassembly of biofilms. A list for the annotated genes that are involved in biofilm formation in S. xylosus NM36 is listed in Table 3.

Table 3 S. xylosus NM36 genome analysis for genes involved in regulation and cell signaling—quorum sensing and biofilm formation. The annotation was based on the protein domain database [38,39,40,41]
Full size table

Discussion

Despite the fact that S. xylosus is considered a nonpathogenic bacterium, several studies have linked it to opportunistic infections in animals and humans. S. xylosus is widespread and can be found in numerous environments, such as contaminated water, animal feed, and soil surfaces [1, 2, 13, 14, 19, 27, 33, 36, 37, 62]. S. xylosus may contribute to the pathogenicity of other staphylococci via horizontal gene transfer of antibiotic resistance elements, such as the SCCmec type 11 region [37] or tetracycline gene transfer in Staphylococcus xylosus in situ during sausage fermentation, thereby exacerbating the risk of antibiotic resistance and posing a significant risk to public health [33]. In Iraq, there is limited information about Staphylococcus xylosus, which is reported occasionally during clinical investigations [2, 51] and similarly to other coagulase-negative staphylococci, and S. xylosus receives less interest compared to the more focus on S. aureus. The pathogenicity of staphylococci has been primarily linked to their capacity to resist antimicrobials and form biofilms. The initial attachment of bacteria to biotic and abiotic surfaces results in the accumulation of multilayered cell aggregates that constitute biofilm formation. This facilitates the internalization and survival of staphylococci within the host cells [54]. Therefore, strains that facilitate this trait are regarded as more virulent. S. xylosus NM36 possesses a number of virulence determinants that have been associated with the ability of staphylococci to adhere to biotic and abiotic surfaces, as well as the different phases of biofilm formation and antimicrobial resistance summarized in Tables 2 and 3. These results validate the initial phenotypes of multiresistance and biofilm formation observed during the initial isolation. Comparing the NM36 genome of S. xylosus to clinical reference strains revealed its arsenal of antibiotic resistance and virulence genes. In addition, S. xylosus NM36 contains 9 antibiotic resistance determinants responsible for resistance to 10 known antibiotics, including quinolone, methicillin, teicoplanin, bicyclomycin, chloramphenicol, fosfomycin, ampicillin, cefoxitin, oxacillin, and tetracycline. The NM36 genome harbors the ica operon and transcriptional regulator TcaR, both of which have been implicated in biofilm formation in staphylococci. It also contained the global regulators agr (accessory gene regulator), the main autolysin gene atl (autolysin), sarA (staphylococcal accessory regulator), and the two-component system arlRS and srrAB, which are involved in the regulation of adhesion and biofilm formation. Strain HKUOPL8 (CP007208.1) shares the maximum degree of protein similarity with NM36 (Figs. 3 and 5) [36]. According to the genome data on the NCBI website, strain HKUOPL8 (CP007208.1) was isolated from a clinical case (panda feces) [36], strain NJ (ANMR00000000.1) from a nasal swap (human), strain SMQ-121 (CP008724.1) from fermented sausage [31], strain 2 (CP031275.1) from a milker’s hand, and strain 2.1523 (CP066721.1) from fermented sausage. This variation in genome similarity may be attributable to lifestyle and isolation source differences, which may have affected the genetic composition of these isolates [48, 64]. INDELS are a significant source of genetic diversity that can significantly affect the properties or evolvability of a protein [52]. Single-nucleotide polymorphism (SNP) analysis showed that there were 46,610 SNPs, 523 insertions, and 551 deletions compared to the reference genome. Whether some of these mutations are advantageous, guiding the protein onwards towards a point of high fitness to current selective pressures, or not, will require additional research in the future. Similar to conventional molecular typing, it is probable that the genomes of isolates recovered from an outbreak or cluster of infections are closely related and may share pathogenic traits due to horizontal gene transfer [12]. In recent years, the widespread availability of whole genome sequencing (WGS) has made it possible to examine in greater detail patterns of spread, including the detection of previously undocumented transmission. Whole genome sequencing (WGS) can be used to investigate infectious disease epidemics and track the spread of infection, but unlike conventional molecular typing techniques such as spa typing, pulse-field gel electrophoresis (PFGE), and multilocus-sequence typing (MLST), WGS enables the comparison of entire genomes, thereby enhancing the resolution and accuracy of metabolic and subsystem maps [50]. However, the accumulation of genome sequences in the databases has been sporadic, with biased sampling of natural variation motivated primarily by medical and epidemiological priorities. For instance, sequencing epidemic lineages of methicillin-resistant Staphylococcus aureus (MRSA) is favored over sequencing sensitive isolates (methicillin-sensitive S. aureus: MSSA). As more diverse genomes are sequenced, a picture of a highly subdivided species with a limited number of relatively clonal groups (complexes) that dominate in specific geographic regions at any given time emerges, as reviewed by Planet et al. [48]. Our findings support this contention and advocate for whole-genome surveillance of other non-S. aureus populations in animals, which could lead to more accurate predictions of antibiotic resistance and the virulence of emergent clones. Ultimately, this can provide a better understanding of the enigmatic biological aspects that determine the recurrent strain dominance in endemic areas. In our investigation, we sequenced the genome of Staphylococcus xylosus, a coagulase-negative Staphylococcus that is often missed in conventional laboratory exams. Staphylococcus xylosus NM36’s unique virulence traits are a new variable in the complex epidemiology of mastitis in Basrah governorate.

Conclusion

This research represents the first investigation into the genomic characteristics of S. xylosus within the geographical context of Iraq. This observation further underscores the need of using whole genome sequencing and comparative genomics analysis in order to get deeper insights into the origins and testing methodologies of multidrug-resistant isolates. Furthermore, there is a need to reassess microbiological and therapeutic approaches in the management of coagulase-negative staphylococci, especially in the context related to animal illnesses and public health.

Availability of data and materials

The genome sequence of Staphylococcus xylosus NM36 has been deposited at GenBank—DDBJ/ENA/GenBank under the accession number GenBank: JARUHN000000000.1, GenBank assembly accession: GCA_029667155.1. The genome is associated with BioProject PRJNA950481 and BioSample SAMN33999823. The annotation was added by the NCBI Prokaryotic Genome Annotation Pipeline (PGAP https://www.ncbi.nlm.nih.gov/genome/annotation_prok/).

Abbreviations

SCCmec :

Staphylococcal cassette chromosome mec

CoNS:

Coagulase-negative staphylococci

AMR:

Antimicrobial resistant

NCBI:

The National Center for Biotechnology Information

SNP:

Single-nucleotide polymorphism

INDEL:

Insertion/deletion

MDR:

Multidrug resistant

MFS:

The major facilitator superfamily

Contig:

(From contiguous) overlapping DNA segments that together represent a consensus region of DNA

PATRIC:

PathoSystems Resource Integration Center

RAST:

Rapid Annotation using Subsystem Technology

PFGE:

Pulse-field gel electrophoresis

MLST:

Multilocus-sequence typing

PGAP:

NCBI Prokaryotic Genome Annotation Pipeline

QC:

Quality control

TV:

NCBI Tree Viewer

CDS:

Coding DNA sequence

MUSCLE:

Multiple sequence comparison by log expectation

MSSA:

Methicillin-sensitive S. aureus

SBS:

Illumina sequencing by synthesis technology (Illumina HiSeq)

References

  1. Akhaddar A, Elouennass M, Naama O, Boucetta M (2010) Staphylococcus xylosus isolated from an otogenic brain abscess in an adolescent. Surg Infect (Larchmt) 11:559–561. https://doi.org/10.1089/sur.2010.010

    Article  Google Scholar 

  2. Al-Mathkhury HJF (2008) Pathological study on Staphylococcus xylosus isolated from patients with urinary tract infections. J Al-Nahrain Univ Sci. 11:123–130. https://doi.org/10.22401/JNUS.11.2.18

    Article  Google Scholar 

  3. Andrews S (2010) Babraham Bioinformatics - FastQC a quality control tool for high throughput sequence data. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/. Accessed 22 Oct 2021

  4. Asante J, Amoako DG, Abia ALK, Somboro AM, Govinden U, Bester LA, Essack SY (2020) Review of clinically and epidemiologically relevant coagulase-negative staphylococci in Africa. Microb Drug Resist 26:951–970. https://doi.org/10.1089/mdr.2019.0381

    Article  Google Scholar 

  5. Aziz RK, Bartels D, Best A, DeJongh M, Disz T, Edwards RA, Formsma K, Gerdes S, Glass EM, Kubal M, Meyer F, Olsen GJ, Olson R, Osterman AL, Overbeek RA, McNeil LK, Paarmann D, Paczian T, Parrello B, Pusch GD, Reich C, Stevens R, Vassieva O, Vonstein V, Wilke A, Zagnitko O (2008) The RAST server: rapid annotations using subsystems technology. BMC Genomics 9:1–15. https://doi.org/10.1186/1471-2164-9-75

    Article  Google Scholar 

  6. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA (2012) SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455–477. https://doi.org/10.1089/cmb.2012.0021

    Article  MathSciNet  Google Scholar 

  7. Beenken KE, Blevins JS, Smeltzer MS (2003) Mutation of sarA in Staphylococcus aureus limits biofilm formation. Infect Immun 71:4206–4211. https://doi.org/10.1128/IAI.71.7.4206-4211.2003

    Article  Google Scholar 

  8. Boles BR, Horswill AR (2008) agr-mediated dispersal of Staphylococcus aureus biofilms. PLoS Pathog 4:e1000052. https://doi.org/10.1371/journal.ppat.1000052

    Article  Google Scholar 

  9. Bose JL, Lehman MK, Fey PD, Bayles KW (2012) Contribution of the Staphylococcus aureus Atl AM and GL murein hydrolase activities in cell division, autolysis, and biofilm formation. PLoS ONE 7:e42244. https://doi.org/10.1371/journal.pone.0042244

    Article  Google Scholar 

  10. Brandenberger M, Tschierske M, Giachino P, Wada A, Berger-Bächi B (2000) Inactivation of a novel three-cistronic operon tcaR-tcaA-tcaB increases teicoplanin resistance in Staphylococcus aureus. Biochim Biophys Acta - Gen Subj 1523:135–139. https://doi.org/10.1016/S0304-4165(00)00133-1

    Article  Google Scholar 

  11. Brettin T, Davis JJ, Disz T, Edwards RA, Gerdes S, Olsen GJ, Olson R, Overbeek R, Parrello B, Pusch GD, Shukla M, Thomason JA, Stevens R, Vonstein V, Wattam AR, Xia F (2015) RASTtk: a modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes. Sci Rep 5:8365. https://doi.org/10.1038/srep08365

    Article  Google Scholar 

  12. Capra EJ, Laub MT (2012) Evolution of two-component signal transduction systems. Annu Rev Microbiol 66:325–347. https://doi.org/10.1146/annurev-micro-092611-150039

    Article  Google Scholar 

  13. Carrillo R, Téllez MDLÁ, Salinas S (2000) Staphylococcus xylosus: una bacteria emergente. Rev Medica Del Hosp Gen Mex 63:107–111

    Google Scholar 

  14. Chen M, Li Y, Li S, Cui W, Zhou Y, Qu Q, Che R, Li L, Yuan S, Liu X (2022) Molecular mechanism of Staphylococcus xylosus resistance against tylosin and florfenicol. Infect Drug Resist 15:6165–6176. https://doi.org/10.2147/IDR.S379264

    Article  Google Scholar 

  15. Cheng Q, Xie G, Daligault H, Davenport K, Gleasner C, Jacobs L, Kubicek-Sutherland J, LeCuyer T, Otieno V, Raballah E, Doggett N, McMahon B, Perkins DJ, Mukundan H (2019) Genome sequence of a Staphylococcus xylosus Clinical isolate, strain SMA0341-04 (UGA5), from Siaya County Referral Hospital in Siaya, Kenya. Microbiol Resour Announc 8:7–9. https://doi.org/10.1128/MRA.01625-18

    Article  Google Scholar 

  16. Danecek P, Bonfield JK, Liddle J, Marshall J, Ohan V, Pollard MO, Whitwham A, Keane T, McCarthy SA, Davies RM (2021) Twelve years of SAMtools and BCFtools. Gigascience 10:1–4. https://doi.org/10.1093/gigascience/giab008

    Article  Google Scholar 

  17. Dashtbani-Roozbehani A, Brown MH (2021) Efflux pump mediated antimicrobial resistance by staphylococci in health-related environments: challenges and the quest for inhibition. Antibiotics 10. https://doi.org/10.3390/antibiotics10121502

  18. Deng X, Sun F, Ji Q, Liang H, Missiakas D, Lan L, He C (2012) Expression of multidrug resistance efflux pump gene norA is iron responsive in Staphylococcus aureus. J Bacteriol 194:1753–1762. https://doi.org/10.1128/JB.06582-11

    Article  Google Scholar 

  19. Dordet-Frisoni E, Talon R, Leroy S (2007) Physical and genetic map of the Staphylococcus xylosus C2a chromosome. FEMS Microbiol Lett 266:184–193. https://doi.org/10.1111/j.1574-6968.2006.00538.x

    Article  Google Scholar 

  20. Ewing B, Hillier L, Wendl MC, Green P (1998) Base-calling of automated sequencer traces using Phred. I Accuracy Assessment Genome Res 8:175–185. https://doi.org/10.1101/gr.8.3.175

    Article  Google Scholar 

  21. Fijałkowski K, Struk M, Karakulska J, Paszkowska A, Giedrys-Kalemba S, Masiuk H, Czernomysy-Furowicz D, Nawrotek P (2014) Comparative analysis of superantigen genes in Staphylococcus xylosus and Staphylococcus aureus isolates collected from a single mammary quarter of cows with mastitis. J Microbiol 52:366–372. https://doi.org/10.1007/s12275-014-3436-2

    Article  Google Scholar 

  22. Frank JA, Reich CI, Sharma S, Weisbaum JS, Wilson BA, Olsen GJ (2008) Critical evaluation of two primers commonly used for amplification of bacterial 16S rRNA genes. Appl Environ Microbiol 74:2461–2470. https://doi.org/10.1128/AEM.02272-07

    Article  Google Scholar 

  23. Fujimura T, Murakami K (2008) Staphylococcus aureus clinical isolate with high-level methicillin resistance with an lytH mutation caused by IS1182 insertion. Antimicrob Agents Chemother 52:643–647. https://doi.org/10.1128/AAC.00395-07

    Article  Google Scholar 

  24. Gallegos MT, Schleif R, Bairoch A, Hofmann K, Ramos JL (1997) Arac/XylS family of transcriptional regulators. Microbiol Mol Biol Rev 61:393–410. https://doi.org/10.1128/mmbr.61.4.393-410.1997

    Article  Google Scholar 

  25. Grant JR, Enns E, Marinier E, Mandal A, Herman EK, Chen C, Graham M, Van Domselaar G, Stothard P (2023) Proksee: in-depth characterization and visualization of bacterial genomes. Nucleic Acids Res 1–9. https://doi.org/10.1093/nar/gkad326

  26. Gustafson J, Strassle A, Hachler H, Kayser FH, Berger-Bachi B (1994) The femC locus of Staphylococcus aureus required for methicillin resistance includes the glutamine synthetase operon. J Bacteriol 176:1460–1467. https://doi.org/10.1128/jb.176.5.1460-1467.1994

    Article  Google Scholar 

  27. Hong, (2018) Complete genome sequence of biofilm-producing strain Staphylococcus xylosus S170. Korean J Microbiol 54:167–168. https://doi.org/10.7845/kjm.2018.54.3.308

    Article  Google Scholar 

  28. Jefferson KK, Pier DB, Goldmann DA, Pier GB, Al JET, Acteriol JB (2004) The teicoplanin-associated locus regulator (TcaR) and the intercellular adhesin locus regulator (IcaR) are transcriptional inhibitors of the ica locus in Staphylococcus aureus. 186:2449–2456. https://doi.org/10.1128/JB.186.8.2449

  29. Kaur G, Arora A, Sathyabama S, Mubin N, Verma S, Mayilraj S, Agrewala JN (2016) Genome sequencing, assembly, annotation and analysis of Staphylococcus xylosus strain DMB3-Bh1 reveals genes responsible for pathogenicity. Gut Pathog 8:1–9. https://doi.org/10.1186/s13099-016-0139-8

    Article  Google Scholar 

  30. Kondo N, Kuwahara-Arai K, Kuroda-Murakami H, Tateda-Suzuki E, Hiramatsu K (2001) Eagle-type methicillin resistance: new phenotype of high methicillin resistance under MEC regulator gene control. Antimicrob Agents Chemother 45:815–824. https://doi.org/10.1128/AAC.45.3.815-824.2001

    Article  Google Scholar 

  31. Labrie SJ, El Haddad L, Tremblay DM, Plante PL, Wasserscheid J, Dumaresq J, Dewar K, Corbeil J, Moineau S (2014) First complete genome sequence of Staphylococcus xylosus, a meat starter culture and a host to propagate Staphylococcus aureus phages. Genome Announc 2:10–11. https://doi.org/10.1128/genomeA.00671-14

    Article  Google Scholar 

  32. Lauderdale KJ, Boles BR, Cheung AL, Horswill AR (2009) Interconnections between Sigma B, agr, and proteolytic activity in Staphylococcus aureus biofilm maturation. Infect Immun 77:1623–1635. https://doi.org/10.1128/IAI.01036-08

    Article  Google Scholar 

  33. Leroy S, Christieans S, Talon R (2019) Tetracycline gene transfer in staphylococcus xylosus in situ during sausage fermentation. Front Microbiol 10:1–9. https://doi.org/10.3389/fmicb.2019.00392

    Article  Google Scholar 

  34. Leroy S, Vermassen A, Ras G, Talon R (2017) Insight into the genome of Staphylococcus xylosus, a ubiquitous species well adapted to meat products. Microorganisms 5. https://doi.org/10.3390/microorganisms5030052

  35. Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760. https://doi.org/10.1093/bioinformatics/btp324

    Article  Google Scholar 

  36. Ma APY, Jiang J, Tun HM, Mauroo NF, Yuen CS, Leung FCC (2014) Complete genome sequence of Staphylococcus xylosus HKUOPL8, a potential opportunistic pathogen of mammals. Genome Announc 2:13–14. https://doi.org/10.1128/genomeA.00653-14

    Article  Google Scholar 

  37. Macfadyen AC, Harrison EM, Ellington MJ, Parkhill J, Holmes MA, Paterson GK (2018) A highly conserved mecC -encoding SCC mec type XI in a bovine isolate of methicillin-resistant Staphylococcus xylosus. J Antimicrob Chemother 73:3516–3518. https://doi.org/10.1093/jac/dky333

    Article  Google Scholar 

  38. Marchler-Bauer A, Bo Y, Han L, He J, Lanczycki CJ, Lu S, Chitsaz F, Derbyshire MK, Geer RC, Gonzales NR, Gwadz M, Hurwitz DI, Lu F, Marchler GH, Song JS, Thanki N, Wang Z, Yamashita RA, Zhang D, Zheng C, Geer LY, Bryant SH (2017) CDD/SPARCLE: functional classification of proteins via subfamily domain architectures. Nucleic Acids Res 45:D200–D203. https://doi.org/10.1093/nar/gkw1129

    Article  Google Scholar 

  39. Marchler-Bauer A, Bryant SH (2004) CD-Search: protein domain annotations on the fly. Nucleic Acids Res 32:327–331. https://doi.org/10.1093/nar/gkh454

    Article  Google Scholar 

  40. Marchler-Bauer A, Derbyshire MK, Gonzales NR, Lu S, Chitsaz F, Geer LY, Geer RC, He J, Gwadz M, Hurwitz DI, Lanczycki CJ, Lu F, Marchler GH, Song JS, Thanki N, Wang Z, Yamashita RA, Zhang D, Zheng C, Bryant SH (2015) CDD: NCBI’s conserved domain database. Nucleic Acids Res 43:D222–D226. https://doi.org/10.1093/nar/gku1221

    Article  Google Scholar 

  41. Marchler-Bauer A, Lu S, Anderson JB, Chitsaz F, Derbyshire MK, DeWeese-Scott C, Fong JH, Geer LY, Geer RC, Gonzales NR, Gwadz M, Hurwitz DI, Jackson JD, Ke Z, Lanczycki CJ, Lu F, Marchler GH, Mullokandov M, Omelchenko MV, Robertson CL, Song JS, Thanki N, Yamashita RA, Zhang D, Zhang N, Zheng C, Bryant SH (2011) CDD: a conserved domain database for the functional annotation of proteins. Nucleic Acids Res 39:225–229. https://doi.org/10.1093/nar/gkq1189

    Article  Google Scholar 

  42. Mashruwala AA, Gries CM, Scherr TD, Kielian T, Boyd JM (2017) SaeRS is responsive to cellular respiratory status and regulates fermentative biofilm formation in Staphylococcus aureus. Infect Immun 85:IAI.00157-17. https://doi.org/10.1128/IAI.00157-17

    Article  Google Scholar 

  43. Mashruwala AA, Guchte A van de, Boyd JM (2017b) Impaired respiration elicits SrrAB-dependent programmed cell lysis and biofilm formation in Staphylococcus aureus. Elife 6. https://doi.org/10.7554/eLife.23845

  44. Nikaido H, Takatsuka Y (2009) Mechanisms of RND multidrug efflux pumps. Biochim Biophys Acta - Proteins Proteomics 1794:769–781. https://doi.org/10.1016/j.bbapap.2008.10.004

    Article  Google Scholar 

  45. Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, Edwards RA, Gerdes S, Parrello B, Shukla M, Vonstein V, Wattam AR, Xia F, Stevens R (2014) The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res 42:206–214. https://doi.org/10.1093/nar/gkt1226

    Article  Google Scholar 

  46. Pasqua M, Bonaccorsi di Patti MC, Fanelli G, Utsumi R, Eguchi Y, Trirocco R, Prosseda G, Grossi M, Colonna B (2021) Host - bacterial pathogen communication: the wily role of the multidrug efflux pumps of the MFS family. Front Mol Biosci 8:1–13. https://doi.org/10.3389/fmolb.2021.723274

    Article  Google Scholar 

  47. Picard toolkit (2019) Broad Institute, GitHub repository. http://broadinstitute.github.io/picard/. Accessed 11 Apr 2022.

  48. Planet PJ, Narechania A, Chen L, Mathema B, Boundy S, Archer G, Kreiswirth B (2016) Architecture of a species: phylogenomics of Staphylococcus aureus. Trends Microbiol. https://doi.org/10.1016/j.tim.2016.09.009

    Article  Google Scholar 

  49. Pohl K, Francois P, Stenz L, Schlink F, Geiger T, Herbert S, Goerke C, Schrenzel J, Wolz C (2009) CodY in Staphylococcus aureus: a regulatory link between metabolism and virulence gene expression. J Bacteriol 191:2953–2963. https://doi.org/10.1128/JB.01492-08

    Article  Google Scholar 

  50. Rankin DJ, Rocha EPC, Brown SP (2011) What traits are carried on mobile genetic elements, and why. Heredity (Edinb) 106:1–10

    Article  Google Scholar 

  51. Saadoon AS (2022) Clinical and subclinical mastitis in buffalue in Mosul area, Iraq. Iraqi J Vet Sci 36:177–186. https://doi.org/10.33899/ijvs.2021.129644.1671

    Article  Google Scholar 

  52. Savino S, Desmet T, Franceus J (2022) Insertions and deletions in protein evolution and engineering. Biotechnol Adv 60:108010. https://doi.org/10.1016/j.biotechadv.2022.108010

    Article  Google Scholar 

  53. Sayers EW, Beck J, Brister JR, Bolton EE, Canese K, Comeau DC, Funk K, Ketter A, Kim S, Kimchi A, Kitts PA, Kuznetsov A, Lathrop S, Lu Z, McGarvey K, Madden TL, Murphy TD, O’Leary N, Phan L, Schneider VA, Thibaud-Nissen F, Trawick BW, Pruitt KD, Ostell J (2020) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 48:D9–D16. https://doi.org/10.1093/nar/gkz899

    Article  Google Scholar 

  54. Schilcher K, Horswill AR (2020) Staphylococcal biofilm development: structure, regulation, and treatment strategies. Microbiol Mol Biol Rev 84:1–36. https://doi.org/10.1128/mmbr.00026-19

    Article  Google Scholar 

  55. Sharma-Kuinkel BK, Mann EE, Ahn JS, Kuechenmeister LJ, Dunman PM, Bayles KW (2009) The Staphylococcus aureus LytSR two-component regulatory system affects biofilm formation. J Bacteriol 191:4767–4775. https://doi.org/10.1128/JB.00348-09

    Article  Google Scholar 

  56. Stothard P, Grant JR, Van Domselaar G (2018) Visualizing and comparing circular genomes using the CGView family of tools. Brief Bioinform 20:1576–1582. https://doi.org/10.1093/bib/bbx081

    Article  Google Scholar 

  57. Tatusova T, Dicuccio M, Badretdin A, Chetvernin V, Nawrocki EP, Zaslavsky L, Lomsadze A, Pruitt KD, Borodovsky M, Ostell J (2016) NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res 44. https://doi.org/10.1093/nar/gkw569

  58. Thompson MK, Keithly ME, Goodman MC, Hammer ND, Cook PD, Jagessar KL, Harp J, Skaar EP, Armstrong RN (2014) Structure and function of the genomically encoded fosfomycin resistance enzyme, FosB, from Staphylococcus aureus. Biochemistry 53:755–765. https://doi.org/10.1021/bi4015852

    Article  Google Scholar 

  59. Tiwari N, López-Redondo M, Miguel-Romero L, Kulhankova K, Cahill MP, Tran PM, Kinney KJ, Kilgore SH, Al-Tameemi H, Herfst CA, Tuffs SW, Kirby JR, Boyd JM, McCormick JK, Salgado-Pabón W, Marina A, Schlievert PM, Fuentes EJ (2020) The SrrAB two-component system regulates Staphylococcus aureus pathogenicity through redox sensitive cysteines. Proc Natl Acad Sci U S A 117. https://doi.org/10.1073/pnas.1922523117

  60. Toledo-Arana A, Merino N, Vergara-Irigaray M, Débarbouillé M, Penadés JR, Lasa I (2005) Staphylococcus aureus develops an alternative, ica-independent biofilm in the absence of the arlRS two-component system. J Bacteriol 187:5318–5329. https://doi.org/10.1128/JB.187.15.5318-5329.2005

    Article  Google Scholar 

  61. Trotonda MP, Tamber S, Memmi G, Cheung AL (2008) MgrA represses biofilm formation in Staphylococcus aureus. Infect Immun 76:5645–5654. https://doi.org/10.1128/IAI.00735-08

    Article  Google Scholar 

  62. Vermassen A, de la Foye A, Loux V, Talon R, Leroy S (2014) Transcriptomic analysis of Staphylococcus xylosus in the presence of nitrate and nitrite in meat reveals its response to nitrosative stress. Front Microbiol 5:1–15. https://doi.org/10.3389/fmicb.2014.00691

    Article  Google Scholar 

  63. Wattam AR, Davis JJ, Assaf R, Boisvert S, Brettin T, Bun C, Conrad N, Dietrich EM, Disz T, Gabbard JL, Gerdes S, Henry CS, Kenyon RW, Machi D, Mao C, Nordberg EK, Olsen GJ, Murphy-Olson DE, Olson R, Overbeek R, Parrello B, Pusch GD, Shukla M, Vonstein V, Warren A, Xia F, Yoo H, Stevens RL (2017) Improvements to PATRIC, the all-bacterial bioinformatics database and analysis resource center. Nucleic Acids Res 45:D535–D542. https://doi.org/10.1093/nar/gkw1017

    Article  Google Scholar 

  64. Zarazaga M, Gómez P, Ceballos S, Torres C (2018) Molecular epidemiology of Staphylococcus aureus lineages in the animal–human interface. In: Fetsch A, editors. Staphylococcus aureus. Elsevier, Academic Press. pp 189–214. https://doi.org/10.1016/B978-0-12-809671-0.00010-3

  65. Zhao Y, Verma V, Belcheva A, Singh A, Fridman M, Golemi-Kotra D (2012) Staphylococcus aureus methicillin-resistance factor fmtA is regulated by the global regulator SarA. PLoS ONE 7:e43998. https://doi.org/10.1371/journal.pone.0043998

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank Basrah University for providing us with the resources to fulfil this work.

Funding

All expenses were covered by the authors. The initial work and genomic isolation were conducted at University of Basrah laboratories.

Author information

Authors and Affiliations

  1. Microbiology Department, College of Veterinary Medicine, Basrah University, Basrah, 61004, Iraq

    Hassan M. Al-Tameemi, Murtakab Y. Al-Hejjaj & Haider R. Alrafas

  2. Physiology Department, College of Medicine, Misan University, Amarah, Misan, Iraq

    Husam Al-Hraishawi

  3. Pharmacognosy and Medicinal Plants Department, College of Pharmacy, Basrah University, Basrah, Iraq

    Yessar A. Dawood

Authors
  1. Hassan M. Al-Tameemi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Husam Al-Hraishawi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Murtakab Y. Al-Hejjaj
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Noor S. Abdulah
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Haider R. Alrafas
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yessar A. Dawood
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

(1) HMAT, data curation, formal analysis, investigation, methodology; writing—original draft, review and editing, and software; (2) HAH, funding acquisition and resources; (3) MYAH, validation and visualization; (4) NSA, primary investigation; (5) HRA, project administration; and (6) YAD, revision.

Corresponding author

Correspondence to Hassan M. Al-Tameemi.

Ethics declarations

Ethics approval approval and consent to participate

Sampling from animals was conducted according to the ARRIVE guidelines and in accordance with the UK Animals (Scientific Procedures) Act, 1986, and associated guidelines, EU Directive 2010/63/EU, for animal experiments.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Al-Tameemi, H.M., Al-Hraishawi, H., Al-Hejjaj, M.Y. et al. Whole genome sequence and comparative genomics analysis of multidrug-resistant Staphylococcus xylosus NM36 isolated from a cow with mastitis in Basrah city. J Genet Eng Biotechnol 21, 163 (2023). https://doi.org/10.1186/s43141-023-00606-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s43141-023-00606-6

Keywords