Transcriptomic data for analyzing global gene expression patterns in Methicillin-resistance Staphylococcus aureus in response to spermine and oxacillin stress

Abstract

Methicillin-resistant Staphylococcus aureus (MRSA) is a rapidly emerging bacteria causing infection, which has developed resistance to most of the beta-lactam antibiotics because of newly acquired low-affinity penicillin binding protein (PBP2a), which can continue to build the cell wall when other PBPs are blocked by beta-lactams. Exogenous spermine exerts a dose dependent inhibition effect on the growth of E. coli, Salmonella enterica serovar and Staphylococcus aureus. We have selected an MRSA Mu50 derivative which harbors mutation on PBP2 gene (named as MuM) showing spermine resistance and which confers a complete abolishment of spermine-beta-lactam synergy. A transcriptomic profiling of MuM against Mu50 (wild type) without any treatment, MuM and Mu50 in response to high dose spermine and Mu50 in response to spermine-beta-lactam synergy is provided in this article. These comparisons will enhance our current understanding of mechanisms of spermine-beta-lactam synergy sensitization effects on MRSA.

Specifications table

Subject area	Bioinformatics
More specific subject area	Comparative genomics.
Type of data	Table, Figure, Microarray data
How data was acquired	The cDNA synthesis, fragmentation, and terminal labeling were carried out as per the protocols of the manufacturer (Affymetrix, Massachusetts, USA). Labelled cDNA was hybridized to the GeneChip Staphylococcal aureus genome array. After scanning, the images were processed with GCOS 1.4 software (Affymetrix, Massachusetts, USA).
Data format	Raw, analyzed.
Experimental factors	Treatment with Spermine, Oxacillin and in combination
Experimental features	The experimental features are compared between treatments MuM against Mu50 (wild type) without any treatment, MuM and Mu50 in response to high dose spermine and Mu50 in response to spermine-beta-lactam synergy.
Data source location	Department of Biology, Georgia State University, 33 Gilmer Street SE, 30303 Atlanta, GA, USA
Data accessibility	Data is with this article. Also, the raw data files can be found at the GitHub repository by following the link: https://github.com/spawar2/Transcriptomic-data-for-analyzing-global-gene-expression-patterns-in-MRSA
Related research article	Not applicable

Value of the data

• •The data generated can be used to systematically compare Mu50 (wild type) and MuM strains response to spermine alone (high dose) or in combination with b-lactam (oxacillin) (both at low dosages) using microarrays. A detailed transcriptomic analysis of how MRSA Mu50 derivative harboring mutation on PBP2 gene (named as MuM) showing spermine resistance responds to spermine and spermine-beta-lactam synergy was still unknown, this is the attempt to fulfill this gap.
• •This data can be used to understand Staphylococcus aureus response to spermine and beta-lactams with mutated PBP2 protein. A strong relation between PBP2 protein and general stress sigB response, iron, potassium and polyamine transport systems was observed.
• •The data can be used for future studies on the molecular mechanism of spermine interactions holding great potential for the development of new therapeutics for MRSA infections.

1. Data

In first condition, Mu50 and MuM strains were treated with 1 mM spermine and RNA was isolated at 0, 15, 30 and 60-min time-points with spermine and single 0 min time-point without spermine. In second condition, three treatments of Mu50 strain with 1 mM spermine, 2 ng/μl oxacillin and a combination of 1 mM spermine, 2 ng/μl oxacillin were grown for one hour subsequently followed by RNA isolation. Labelled cDNA was hybridized to the GeneChip Staphylococcal aureus genome array. After scanning, the images were processed with GCOS 1.4 software (Affymetrix, Massachusetts, USA). The raw data files (.CEL) consist of intensity values of more than 10,000 genes with information of perfect and mis-match (PM and MM) probes. Each file is named according to the treatment and its generated time point. The normalization and analysis data is provided in respective Supplementary files with logarithm to base 2 fold changes. The raw files can be read in R using Bioconductor package “Affy” for replication and additions in analysis. List of iron regulation, polyamine and potassium transport genes with their significant fold change expression levels (logarithm to base 2) are provided in Table 1. Table 2 lists the plasmids used in this study. Bar graph with fold changes (logarithm to base 2) for iron regulation, potassium and polyamine transport genes in MuM strain at 15, 30 and 60-min time points with spermine treatment are shown on Fig. 1. MA plots showing differentially expressed genes in Mu50 and MuM treatments are provided in Fig. 2.

Table 1.

List of iron regulation, polyamine and potassium transport genes with their significant fold change expression levels (logarithm to base 2). Comparisons with only genes that satisfy a significant p-value (less than 0.05) threshold are selected.

Gene symbol	Affymetrix ID	MUM.NOSPM.0	MUM.SPM.15	MUM.SPM.30	MUM.SPM.60
fhud	sa c914s711 at	1.39	0	−2.32	−2.33
fhug	sa c7993s6980 at	0	−1.28	−1.56	−1.26
fhua	sa c5423s4693 a at	0	0	−1.2	−1.07
fhub	sa c7989s6976 at	0	−1.2	−1.57	−1.3
htsB	sa c4643s3963 a at	0	−1.13	−1.15	0
htsC	sa c4639s3961 a at	0	0	−1.31	0
sirA	sa c1230s1008 at	0	1.18	0	−1.26
sirB	sa c1172s953 a at	0	0	−1.1	−1.12
NARG	sa c5574s4827 a at	−2.99	0	0	0
NIRD	sa c5580s4836 a at	−1.94	0	0	0
SACOL1640	sa c2711s2285 a at	0	−1.95	0	0
SACOL1810	sa c3357s2894 a at	0	−1.57	−1.61	−1.69
MUTY	sa c3689s3168 a at	0	0	−1.98	−1.8
SDAAB	sa c6092s5283 a at	0	0	−1.99	−2
GLTD	sa c7412s6438 a at	0	0	0	−2.08
SACOL0939	sa c8086s7067 a at	0	1.6	1.56	0
SACOL0770	sa c8202s7182 a at	0	−1.84	0	0
SACOL0706	sa c7993s6980 at	0	0	−1.56	0
SACOL0705	sa c7989s6976 at	0	0	−1.57	0
SACOL0797	sa c8283s7260 a at	0	0	0	−1.65
SACOL0796	sa c8276s7256 a at	0	0	0	−2.09
SACOL0798	sa c5353s4626 a at	0	0	−2.07	−1.58
kdpa	sa c4298s3650 a at	1.88	−1.26	−2.82	−2.8
kdpb	sa c4292s3644 a at	0	−1.74	−2.52	−2.38
kdpc	sa c236s9562 at	1.32	0	−1.54	−1.49
pota	sa c5349s4625 a at	−1.01	−4.01	−3.66	−2.58
potb	sa c9028s7925 a at	−1.97	−4.68	−3.94	−2.7
potc	sa c795s596 a at	−1.36	−4.31	−3.83	−2.48
potD	sa c803s604 a at	−1.69	−3.71	−3.01	−2.06

Table 2.

Plasmids used in this study.

Plasmids	Relevant characteristics	Source or reference
pBAD/HisA	Expression vector, Amp	Invitrogen
pBAD/HisD	Expression vector for producing N terminal His tag fusion, Amp	This study
pBAD/HisE	Expression vector for producing C terminal His fusion, Amp	This study
pH6N-PBP1	pBAD/HisD expressing N-His-PBP1	This study
pH6C-PBP2	pBAD/HisE expressing C-His-PBP2	This study
pH6N-PBP3	pBAD/HisD expressing N-His-PBP3	This study
pH6N-PBP4	pBAD/HisD expressing N-His-PBP4	This study

Fig. 1.

Bar graph with fold changes (logarithm to base 2) for iron regulation, potassium and polyamine transport genes in MuM strain at 15, 30 and 60-min time points with spermine treatment.

Fig. 2.

MA plots showing differentially expressed genes in Mu50 and MuM treatments Fig. 2A.1, 2A.2 and 2A.3: Mu50 at 15, 30 and 60-min time-points with spermine treatment over Mu50 0 min time-point without spermine treatment. Fig. 2B.1, 2B.2, 2B.3: MuM at 15, 30 and 60-min time-points with spermine treatment over MuM 0 min time-point without spermine treatment. Fig. 2C.1, 2C.2, 2 C.3: MuM at 15, 30 and 60-min time-points with spermine treatment over Mu50 0 min time-point without spermine treatment. Red color: Genes with greater than 1.5-fold change expression levels/up-regulated Green color: Genes with less than 1.5-fold change expression levels/down-regulated Black color: Insignificant expression levels Fig. 2A–C were generated with following ratios amongst treatments (/ sign is a ratio): A. Mu50 15-min time point spermine/Mu50 0 min time point without spermine B. Mu50 30-min time point spermine/Mu50 0 min time point without spermine C. Mu50 60-min time point spermine/Mu50 0 min time point without spermine D. MuM 15-min time point spermine/MuM 0 min time point without spermine E. MuM 30-min time point spermine/MuM 0 min time point without spermine F. MuM 60-min time point spermine/MuM 0 min time point without spermine G. MuM 15-min time point spermine/Mu50 0 min time point without spermine H. MuM 30-min time point spermine/Mu50 0 min time point without spermine I. MuM 60-min time point spermine/Mu50 0 min time point without spermine.

2. Experimental design, materials and methods

2.1. Bacterial strains, plasmids, and growth conditions

Staphylococcus aureus Mu50, RN4220 and Escherichia coli DH5 alpha were used for this study. With oxacillin and spermine MIC׳s of 512 μg/ml and 1 mM (pH 8.0), spontaneous mutants of MRSA Mu50 were obtained by spreading 1 × 108 colony forming units (CFU) of log-phase cells on spermine-containing plates with Luria-Bertani (LB) medium (37 °C overnight). One colony found resistant to spermine was labelled as MuM.

Protein cloning, purification and expression: Genes pbp1, pbp2, pbp3, and pbp4 were amplified without N-terminal signal peptide and the transmembrane domain from Mu50 strain. Generated plasmids were then cloned (PstI/EcoRI restriction sites) into pBAD/HisD vector with a hexahistidine tag. Recombinant proteins were then expressed from these plasmids. Proteins PotD and PotR of the potABCD operon were expressed in similar way. Plasmids were expressed in Top10 E. coli strains (30 °C) in LB medium supplemented with arabinose (0.2%). Proteins bound on HisTrap HP column (GE) were eluted by imidazole (500 mM).

2.2. Complementation of pbpB

The pbpB gene is transcribed independently or from its upstream prfA promotor as a polycistronic RNA [1]. Using a shuttle vector pCN38 the PCR product was cloned into the BamHI and NarI sites. Plasmid DNA isolated from strains RN4220 was introduced into Mu50 and MuM strains by electroporation.

Transcriptional profiling conditions: Staphylococcus aureus Mu50 and MuM were grown in Tris-buffered LB (pH 7.5), and treated with the RNA protection reagent followed by harvestation. RNA was isolated at 0, 15, 30 and 60-min time-points with spermine (1 mM) and 0 min time-point without spermine. For oxacillin stress analysis, Mu50 strain was exposed with spermine (1 mM), oxacillin (2 ng/μl) and combinations (1 mM and 2 ng/μl of spermine and oxacillin). We found that the spermine (0.5 mM) can stimulate oxacillin MIC from concentrations 512 μg/ml to 1 μg/ml, so we chose to use 1/4 MIC instead of 1 mM for spermine, and 1/32 MIC instead of 16 μg/ml for oxacillin [2]. Extraction of RNA samples was performed using phenol and digestion with RNase-free DNase I for removing genomic DNA. The Affymetrix GeneChip Staphylococcal aureus genome array chips requires its specific protocols for cDNA synthesis, fragmentation, and terminal labeling, which was followed accordingly for all the samples. The GCOS 1.4 software was used to process images after scanning, and the data was generated for two independent biological replicates.

Microarray analysisMas 5.0 normalization was performed for all the files at 0-min time point for Mu50 and MuM strains and strains with MuM–PBP2 and Mu50–PBP2 complementation plasmid [3]. For calculating upregulated genes, in control of all the P (present) call intensity values were considered for analysis and all the M (marginal) and A (absent) calls were regarded as 100. For treatment, all the genes with intensity values above 500 were considered in the analysis. This rigorous approach gave us significant differences amongst various comparisons avoiding any false positive and false negative results. The exact opposite criteria were applied to find down-regulated genes. Fold changes (> 1.5 and < 1.5) with MuM–Mu50 and (MuM with PBP2)–(Mu50 with PBP2) were taken to find up and down-regulated genes in MuM strain [4]. A similar method was used for comparison of MuM and Mu50 at 15, 30 and 60-min time points with spermine treatment. Up and down-regulated genes were calculated and compared with 0-min time point with no spermine treatment. All the microarray data were analyzed using library ‘Affy’ package [5] on R platform [6]. Heat maps were generated using library ‘gplots’ [7]. Heat maps were developed on Z scores, which were calculated by heatmap.2 function of gplots [Z score = (raw intensity − average)/standard deviation]. MA plots [8] for showing differentially expressed genes were calculated as follows: M = Logarithm to base 2 (Treatment/Control), A = 1/2 × Logarithm to base2 (Treatment × Control). MA plots were made on R platform with ‘plotMA’ limma Bioconductor package [9], [10], [11], [12].

Transparency document. Supplementary material

Supplementary material

Appendix A. Supplementary material

Supplementary material

Supplementary material

Supplementary material

Supplementary material

Supplementary material

Supplementary material