Profiling the effect of nafcillin on HA-MRSA D592 using bacteriological and physiological media

Staphylococcus aureus is a leading human pathogen associated with both hospital-acquired and community-acquired infections. The bacterium has steadily gained resistance to β-lactams and other important first-line antibiotics culminating in its categorization as an urgent threat by the U.S. Centers for Disease Control and Prevention. Observations of a varying response to antimicrobial exposure as a function of media type has revealed that clinical susceptibility testing performed in standard bacteriological media might not adequately represent pharmacological responses in the patient. Such observations have encouraged research designed to identify media types that more closely mimic the in vivo environment. In this study, we examine the response of a hospital-acquired USA100 lineage methicillin-resistant, vancomycin-intermediate S. aureus (MRSA/VISA) strain (D592) to nafcillin in a bacteriological compared to a more physiological tissue culture-based medium. We performed multi-dimensional analysis including growth and bacterial cytological profiling, RNA sequencing, and exo-metabolomics measurements (both HPLC and LC/MS) to shed light on the media-dependent activity of the commonly prescribed β-lactam antibiotic nafcillin.


Abstract
Staphylococcus aureus is a leading human pathogen associated with both hospital-acquired and community-acquired infections. The bacterium has steadily gained resistance to β-lactams and other important first-line antibiotics culminating in its categorization as an urgent threat by the U.S. Centers for Disease Control and Prevention. Observations of a varying response to antimicrobial exposure as a function of media type has revealed that clinical susceptibility testing performed in standard bacteriological media might not adequately represent pharmacological responses in the patient. Such observations have encouraged research designed to identify media types that more closely mimic the in vivo environment. In this study, we examine the response of a hospital-acquired USA100 lineage methicillin-resistant, vancomycin-intermediate S. aureus (MRSA/VISA) strain (D592) to nafcillin in a bacteriological compared to a more physiological tissue culture-based medium. We performed multi-dimensional analysis including growth and bacterial cytological profiling, RNA sequencing, and exo-metabolomics measurements (both HPLC and LC/MS) to shed light on the media-dependent activity of the commonly prescribed β-lactam antibiotic nafcillin.  4,5 . Decreased vancomycin susceptibility is also attributed to the high-inoculum effect, in which vancomycin binds to false targets, namely the D-alanyl-D-alanine residue in the peptidoglycan layer 6 . As such, vancomycin is depleted in the peptidoglycan layer before it reaches its true target in the cytoplasm, an effect that is exacerbated as cell numbers increase. An alternative hypothesis postulates that the extensive use of vancomycin to treat methicillin-resistant strains predisposes them to step-wise polygenic mutations in genes encoding molecules involved in cell wall biosynthesis, increasing the probability of vancomycin resistance 3 .
Here, we study a hospital-acquired USA100 lineage VISA strain, D592, isolated from a patient prior to vancomycin and daptomycin treatment 7,8 . We examine the sensitivity of D592 to nafcillin in two different media types: 1) cation-adjusted Mueller-Hinton Broth (CA-MHB), the standard growth medium for antimicrobial testing in the clinical laboratory whose composition is poorly defined 9 , and 2) Roswell Park Memorial Institute 1640 (RPMI), a chemically-defined standard mammalian cell culture medium better mimicking physiological conditions in vivo 10,11 . However, S. aureus strains do not reliably grow on RPMI alone, despite the fact that RPMI contains all nutrients required to support growth in silico 12,13 . Therefore, MIC was tested in RPMI supplemented with 10% Luria Bertani broth (RPMI+10%LB). Minimal growth requirements for S. aureus were recently uncovered 13 . However, transcriptional regulation plays an important role in coordinating metabolic activity 14 and results in condition-specific metabolic requirements 15 . Therefore, the inability of S. aureus strains to grow on RPMI alone could be a result of transcriptional regulation.
We previously reported a similar data set for strain D712, which was collected from the same patient after daptomycin treatment 16 . S. aureus strains exhibited different nafcillin susceptibility in these two media types 10 . This data set was thus generated to study media-specific antibiotic susceptibility and how it is influenced by various environmental factors. Here, we investigate the response to nafcillin of VISA strain D592 in both bacteriological (CA-MHB) and physiological media (RPMI+10%LB). Between these two media the MIC value decreased from 256 g/ml in CA-MHB to 1 g/ml in RPMI+10%LB. We measured the effect of nafcillin at various sub-inhibitory concentrations using optical density measurements, bacterial cytological profiling (BCP), transcriptomic sequencing (RNAseq), and high throughput exo-metabolomics (HPLC and LC/MS) experiments. BCP was performed to identify cytological parameters that change in response to antibiotic treatment, while RNAseq and metabolomics were used to measure changes in gene expression and secreted metabolites in response to the presence of nafcillin.

Methods
The methodology used to generate this data set re-adapted from and similar to that used for our previously published articles 16,17 .

Culture and Growth Conditions
Standard bacteriological media MHB (Sigma-Aldrich) was supplemented with 25 mg/L Ca 2+ and 12.5 mg/L Mg2+ (CA-MHB). Eukaryotic cell culture media RPMI 1640 (Thermo Fisher Scientific) was supplemented with 10% LB (R10LB). Broth microdilution was performed to determine the nafcillin MIC in each media condition. On the day of the experiment, overnight cultures of HA-MRSA D592 were diluted to a starting OD600 of 0.01 into fresh media and grown at 37°C with stirring to OD600 0.4. This preculture was then diluted back to OD600 0.01 into fresh media containing no drug or sub-inhibitory concentrations of nafcillin relative for each media type. Growth was monitored by obtaining OD600 readings every 45 min for 6 h. Three biological replicates were collected for the study, each derived from different colonies and overnight culture. Growth curves for all culture conditions are shown in Fig. 1 .

Bacterial Cytological Profiling
At the 3 h mark, samples were taken for fluorescence microscopy as previously described with minor modifications [18][19][20] . In brief, 8 µL cells were added to 2 µL dye mix containing 10 µg/mL DAPI, 2.5 µM SYTOX Green, and 60 µg/mL FM4-64 in 1x T-base. The sample was then transferred to a glass slide containing an agarose pad (20% media, 1.2% agarose) and imaged on an Applied Precision DV Elite epifluorescence microscope with a CMOS camera. The exposure times for each wavelength were as follows, TRITC/Cy-5 = 0.025s, FITC/FITC = 0.01s, DAPI/DAPI = 0.015s, and were kept constant for all images.
Deconvolved images were adjusted using FIJI (ImageJ 1.51w) and Adobe Photoshop (2015.1) to remove background in WGA and DAPI channels and to ensure that cell and DNA objects are within the highest intensity quartile. These images were then processed using a custom CellProfiler 3.0 pipeline that individually threshold and filtered WGA and DAPI channels to obtain segmentation masks for the cell wall, DNA and entire cell. Objects identified in this manner were further processed in CellProfiler to obtain a total of 5,285 features 21,22 . Prior to analysis, feature selection was necessary to create a subset of relevant features so as to minimize redundancy within the dataset. The summary of processing steps is presented in Fig. 2 .

DNA sequencing and genome assembly
The reference genome of D592 was sequenced using an Illumina Hiseq 4000 (paired end, 100/100 bp reads) and Nanopore MinION to 50x coverage. For Illumina sequencing genomic DNA was prepared using a Zymo Research Quick-DNA Fungal/Bacterial Microprep Kit, and libraries were prepared using a Kapa Biosystems HyprePlus kit. For MinION sequencing, high molecular weight genomic DNA was prepared using a CTAB method and libraries were prepared using an Oxford Nanopore Rapid Barcoding Kit. Prior to assembly, the quality control steps were performed to remove unincorporated primers, adaptors, and detectable PCR primers. The genome was then assembled into 2 contigs (genome and plasmid) using Unicycler 0.4.2 in "default" mode for hybrid assemblies and annotated using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) v4.11. The sequencing reads show an average Phred quality score of >32, which corresponds to a base calling accuracy of 99.99%. The reads were submitted to NCBI under accession number SRP258107 and the complete record was deposited at NCBI as NZ_CP035791.1. The final chromosomal genome size was 2,820,117 base pairs, while the final plasmid size was 27,267 base pairs.

cDNA library preparation and RNA sequencing
After 3 hours of growth (at mid-log phase), 3 mL samples were taken for RNA sequencing and added to tubes containing 6 mL RNAprotect. After incubation, they were centrifuged to remove the supernatant. RNA was extracted from the pelleted cells using a 'Quick RNA Fungal/Bacterial Microprep' kit developed by Zymo Research. Cells were mechanically lysed with a Roche MagNa Lyser instrument and DNA was removed with DNase I during the RNA purification. RNA quality was checked with an Agilent Bioanalyzer instrument and ribosomal RNA was removed using an Illumina Ribo-Zero kit. Remaining RNA was used to build a cDNA library for sequencing using a KAPA Stranded RNA-seq Library Preparation Kit. The kit was used for RNA fragmentation, sequencing adapter ligation, and library amplification. Generated cDNA libraries were sent for Illumina sequencing on a HiSeq 4000.

RNA sequencing analysis
The phred quality scores for illumina sequencing were generated using Fastqc package 23 . Bowtie2 was used to align the raw reads to the D592 genome and to calculate alignment percentage, FastQC 24 . The aligned reads were then normalized to transcripts per million (TPM) with DESeq2. The ComBat module within the sva package of R was used to correct for batch effects 25,26 . Distance matrices for hierarchical clustering were calculated with sklearn package 27 . The summary steps are provided in Fig. 2 .

Untargeted Liquid Chromatography Mass Spectrometry Data Acquisition
Following dilution of the preculture of HA-MRSA USA100 D592 into fresh media, approximately 400 µL of liquid media containing cells were collected at 45 min intervals (at the same time as samples for OD600 measurements) from each of the samples. Growth media was syringe-filtered through 0.22 µm disc filters (Millex-GV, MilliporeSigma) to remove cells. The filtered growth media was collected and stored at −80 °C until analysis by liquid chromatography mass spectrometry (LC/MS). For LC/MS analysis, samples were subjected to chromatographic separation using an UltiMate 3000 UHPLC system (Thermo Scientific). Chromatographic separations were achieved using a 50 mm × 2.1 mm Kinetex 2.6 micron polar-C18 column (Phenomenex) held at a fixed temperature of 30 °C within an actively heated column compartment. Samples were injected onto the LC column via thermostatted autosampler maintained at 4 °C. For samples containing RPMI + 10% LB media the injection volume was 5 µl, while the injection volume was 2 µl for samples containing CA-MHB to prevent excessive oversaturation of the mass spectrometer detector due to the higher concentrations of many molecules in the CA-MHB media.
After injection, the sample components were eluted from the LC column into the mass spectrometer using a flow rate of 0.5 mL/min and the following mobile phases: Mobile phase A was LC/MS grade water with 0.1% formic acid (v/v) and mobile phase B was LC/MS grade acetonitrile with 0.1% formic acid (v/v). The LC gradient program was as follows: 0-1.0 min 5%B, 1.0-5.0 min 5-35%B, 5.0-5.5 min 35-100%B, 5.5-6.0 min 100%B, and 6.0-6.5 min 100-5%B followed by 5 minutes of re-equilibration at 5%B. Mass spectrometric data was acquired using a Bruker Daltonics maXis Impact quadrupole-time-of-flight (qTOF) mass spectrometer equipped with an Apollo II electrospray ionization (ESI) source and controlled via otofControl v4.0.15 and Hystar v3.2 software packages (Bruker Daltonics). The mass accuracy of the maXis instrument was first externally calibrated using a calibration solution of sodium formate which provided >21 reference m/z's between 50-1500 m/z of the mass spectrum in both positive and negative polarities (reference m/z list provided within instrument control software).
Sodium formate solution was prepared using 9.9 ml of 50/50% isopropanol/water, plus 0.2% formic acid, and 100 μl of 1 M NaOH. During infusion of all samples, the mass accuracy of the instrument was maintained to <10 ppm via constant introduction of an internal calibrant, or "lock mass", in the form of hexakis (1H,1H,2H-difluoroethoxy)-phosphazene (SynQuest Labs, Inc.). During positive polarity runs the lock mass compound was detected as the ion m/z 622.028960 (C12H19F12N3O6P3+) and in negative polarity the lock mass compound formed the ion m/z 556.001951 (C10H15F10N3O6P3−).
Instrument source parameters were set as follows: nebulizer gas (Nitrogen) pressure, 2 Bar; Capillary voltage, 3,500 V; ion source temperature, 200 °C; dry gas flow, 9 L/min. The global mass spectral acquisition rate was set at 3 Hz. The instrument transfer optics were tuned as follows: Following acquisition of the LC/MS data, lock mass calibration was applied to all data files to apply a linear correction calibration to all m/z values recorded in each mass spectrum. The application of this mass correction was applied automatically via the Bruker Daltonics Compass Data Analysis software (ver. 4.3.110), using the m/z of the hexakis (1H,1H,2H-difluoroethoxy) phosphazene as the reference lock mass calibration compound. Following lock mass re-calibration of the data, all files were converted from the Bruker Daltonics proprietary format (.d) and exported to an open data format known as .mzXML. All data herein was deposited to MassIVE 28 . The brief methodology is provided in Fig. 2 .

Targeted High-Performance Liquid Chromatography
For organic acid and carbohydrate detection, samples were collected every 45 min and filtered as described above. The filtered samples were loaded onto a 1260 Infinity series (Agilent Technologies) high-performance liquid chromatography (HPLC) system with an Aminex HPX-87H column (Bio-Rad Laboratories) and a refractive index detector. The system was operated using ChemStation software. The HPLC was run with a single mobile phase composed of HPLC grade water buffered with 5 mM sulfuric acid (H2SO4). The flow rate was held at 0.5 mL/min, the sample injection volume was 10 μL, and the column temperature was maintained at 45 °C. The identities of compounds were determined by retention time comparison to standard curves of acetate, ethanol, glucose, lactate, pyruvate, and succinate. The peak area integration and resulting chromatograms were generated within ChemStation and compared to that of the standard curves in order to determine the concentration of each compound in the samples. These final concentration values were deposited to MassIVE database 28 . The procedure of HPLC is depicted in Fig. 2 and measured concentrations for three carbon sources are shown in Fig. 3 .

Data Records
The

Technical Validation
Bacterial Cytological profiling The technical validation of BCP was done through manual screening during the image segmentation process in CellProfiler. Accurate cell and object traces and measurements were verified manually for representative images. The cell outlines were matched with corresponding related structures e.g., DNA through "parent" tags. Finally, the output files for the cellular features were uploaded to MassIVE repository 28 . A representation of the image analysis pipeline for BCP data is provided in Fig. 4 .

Untargeted Liquid Chromatography Mass Spectrometry data acquisition
For each sample, the base peak chromatogram (BPCs) and multiple extracted ion chromatograms (EICs) were compared to evaluate the reproducibility of global retention time and ion intensity. The reproducibility of retention time and peak intensity were obtained by comparing the BPCs of each experimental triplicate. The EICs of the molecules were evaluated using retention time drift and peak area of <0.1 min and <15% correspondingly.

RNA sequencing
The alignment of reads with the reference genome gives an average alignment score of 97.47% . Because the number of samples was large, their processing was done in three different batches. Batch effects were corrected using the ComBat module of the SVA package in R. As a result, expression profiles showed a Spearman's correlation coefficient >0.975 between biological replicates. The RNAseq results are shown in Fig. 5 .

Code availability
The complete RNAseq pipeline used in analysis of RNAseq data is available on Figshare 31 . The script to remove batch effects from RNAseq data is also available on Figshare 35 .     . Each sample point is color coded by nafcillin concentration to which the cultures were exposed and shaped according to the culture media type.