Mouse experiments and Animal Care
All experiments using animals were approved by the Institutional Animal Care and Use Committee at the University of Illinois at Chicago (protocol # 15-240). Sphk2 knockout mice were originally provided by Dr. Richard Proia (National Institutes of Health, Bethesda, MD). The knockout mice were backcrossed onto the C57BL/6 background for 8 generations. The resultant mixed background of C57BL/6 strain and the original background (F8 hybrid) was used as controls and is referred to hereafter as Wild Type (WT). All in vivo experiments were carried out with age-matched (6-8 weeks) female mice. The mice were housed in the University of Illinois Animal Care Facility.
Anesthesia and euthanasia: The mice were anesthetized using Ketamine (100mg/kg) and Xylazine (5mg/kg). The animals were sacrificed and the lung tissues collected, homogenized and whole cell lysates prepared for further analysis, RNA isolation (superior lobe of right lung), and RNA-Seq studies.
Preparation of Pseudomonas aeruginosa culture
The parent strain P. aeruginosa (PA 103) used for all experiments was provided by Dr. Ruxana Sadikot (Emory University, Atlanta, GA). Preparation of the cultures and determination of colony-forming units (CFU) were carried out as described previously [11, 19]. The bacterial concentration of PA was confirmed by plating out the diluted samples on sheep blood agar plates .
Standardization of Pseudomonas aeruginosa inoculation and validation of bacterial load inoculated
Live PA was titrated overnight on sheep blood agar plate and PA was administered into the trachea of WT and Sphk2-/- mice at a dose of 1x106 CFU/mouse. Following administration of PA, 1.0 ml of ice-cold sterile PBS was injected into the trachea, lungs were lavaged and BAL fluid was collected, and bacterial colony count was performed at 6 or 24 hours, post-inoculation by plating out the BAL samples on sheep blood agar plates.
Pseudomonas aeruginosa infection of mouse lung
Age and weight-matched female WT and Sphk2-/- mice were anesthetized with ketamine as per approved protocol and were administrated a single intratracheal infusion of sterile PBS or PA103 in PBS (1x106 CFU/mouse). Three mice were used for each group. After 24 h of treatment, animals were euthanised; whole lung tissues were collected, and processed. .
Sample processing and RNA-Seq based gene expression analyses
Lungs were perfused with phosphate buffered saline prior to harvesting from the mice and processed immediately. Whole lung tissues were initially collected in RNA later® (Thermo Fischer Scientific, Waltham, MA, Cat no. AM7020) and used to isolate total RNA using microRNeasy® kit (Qiagen, Maryland, Cat no. 74004). RNA samples isolated from individual animals were separately labeled, hybridized, washed/stained and scanned according to the standard WT PLUS labeling protocol recommended by the manufacturer (Thermo Fisher Scientific, Waltham, MA).
RNA Quality control
RNA concentrations and purity were determined on a NanoDrop 1000 (Invitrogen), and RNA integrity was determined on the 2200 TapeStation system using RNA ScreenTape (Agilent, Cat. No. 5067-5576). RNA integrity number (RIN) values ranged from 7.0 to 8.4.
RNA-Seq Library Preparation
Libraries were prepared with the 3’ QuantSeq mRNA-Seq Library Prep Kit REV for Illumina (Lexogen), according to manufacturer's instructions. In brief, 10-500 ug of total RNA was used to make each library. Library generation was initiated by oligo (dT) priming followed by first strand cDNA synthesis, removal of RNA and second strand cDNA synthesis using random priming and DNA polymerase. During these steps Illumina linker sequences and external barcodes were incorporated. Next the libraries were subject to final 20 cycles of PCR amplification.
RNA-Seq Library Validation and Quantification
Quality of the libraries was checked on the 2200 Tape Station system using D1000 ScreenTape (Agilent, Cat. No. 5067-5582), and as expected, peaks ranged from 264 to 294 bp. Libraries were quantified on the Qubit 2.0 Fluorometer with the Qubit dsDNA HS Assay Kit (Life Technologies, Cat. No. Q32854). Individual libraries were pooled in equimolar amounts and concentration of the final pool was determined by PCR quantification method using KAPA Library Quantification Kit (KAPA Biosystems). Sequencing was carried out on NextSeq 500 (Illumina), 1x75 nt reads, high output, to achieve approximately 20x106 clusters per sample.
Collected hybridization signals were processed using Genomics Suite 6.6 statistical package (Partek, Inc., Saint Louis, MO). The parameters applied for hybridization signal processing were as follows: RMA algorithm-based background correction, quantile normalization procedure, and probe set summarization [20, 21].
All processed array files were inspected for the quality metrics such as average signal present, signal intensity of species-specific housekeeping genes, relative signal intensities of labeling controls, absolute signal intensities of hybridization controls, and across-array signal distribution plots . All hybridizations passed quality control according to indicated labeling and hybridization controls.
Identification of differentially expressed transcripts
In order to identify the subset of genes modulated specifically to the infection of WT and Sphk2-/- mice, we performed a two-way ANOVA using the status of PA infection and Sphk2 expression as comparison factors. We compared the following groups: Sphk2-/- PA infected (Sphk2-/- PA), Sphk2-/- control (Sphk2-/- CTRL), Wild Type PA infected (WT PA) and Wild Type control (WT CTRL). ANOVA model was based on Method of Moments  in combination with Fisher's Least Significant Difference (LSD) contrast (Tamhane and Dunlop, 2000). The Fisher’s contrast allowed calculation of direction and magnitude of change for all pair-wise comparisons between the treatment groups and was later validated by RT-PCR. Raw reads were aligned to reference genome using Burroughs-Wheeler Aligner Maximal Exact Matches (BWA-MEM) . Gene expression was quantified using FeatureCounts . Differential expression statistics (fold-change and p-value) were computed using edgeR [26, 27], generalized linear models to model the effect of genotype, infection, and their interaction. We used Globus Genomics  for these analyses. Calculated raw p-values were adjusted for False Discovery Rate (FDR) according to Benjamini-Hochberg (BH) correction procedure [29, 30]. Significant genes were determined based on an FDR threshold of 5% (0.05) and plotted in a heatmap. The FDR incorporates sample size in each group, sequencing depth and gene expression variability. The significance calculated is an output dependent on these factors. In spite of reducing the number in one group to two and comparing with the three in other groups, the data show significant changes in number of genes as shown in the results with FDR set at 0.05. The data and the level of significance presented are independent of human error. Pathway enrichment analysis on differentially expressed genes was performed using the Pathway Maps database in MetaCore. The top 35 genes, based on the interaction term FDR, were plotted in a heatmap. Additionally, we compared the significantly differentially expressed (FDR < 0.05) genes based on genotype, infection, or their interaction in a Venn diagram.
Availability of data and materials
The RNA-Seq datasets supporting the conclusions of this article are available in the National Center for Biotechnology Information Gene Expression Omnibus repository, with unique persistent identifier of NCBI tracking system accession number. The accession number is GSE12359. The hyperlink to the datasets is given below.
Pathway enrichment analyses and data visualization
We performed pathway enrichment analyses (EA) in order to identify the biological factors driving the protective effect observed in Sphk2-/- mice with PA pneumonia. Transcripts identified as differentially expressed in KO animals in response to PA infection in two-way ANOVA test (FDR cut off of 0.05) were imported into MetaCore Genomic Analyses Tool Release 6.22 (Thomson Reuters) for analyses.
Differentially expressed genes were analyzed using the “Pathway Maps” ontology and the top 50 most enriched pathways (PW) were identified. The output of analyses using the tool contained a substantial number of individual PWs that overlap by genes, representing sub-segment of the same PWs and creating redundancy. In order to reduce duplication, we clustered nodal PWs based on their gene content in order to reduce duplication. Complete linkage hierarchical clustering on the Jaccard distance between the complete set of genes in each PW was used to identify closely related individual entities. A measure of the dissimilarity between two PWs (based on their gene sets) with scales from 0 to 1 was used; ‘0’ if the sets are exactly the same, and ‘1’ if they are completely different and have no genes in common. For the purpose of biological interpretations, we considered each cluster of closely related PWs as one unit or mega pathway (dissimilarity cut off of 0.6). We combined all associated differential genes for analyzing gene interactions and creating heatmaps as shown in the Venn diagram (Figure 1) and a dendrogram (Figure 2). The heatmaps for selected mega pathways were created by plotting z-scored normalized expression levels of differentially expressed genes (FDR< 0.05) across all experimental groups (Figures 3, 4, 5, 6, 7,8, 9&10). The z-scored normalized expression level using the color key ranging from dark blue to dark red.
Realtime RT- PCR validation of RNA-Seq results
Total RNA was isolated from mouse lung homogenate using TRIzol® reagent according to the manufacturer's instructions and purified using the RNeasy® Mini Kit according to the manufacturer's protocol (Qiagen, MD, USA). Quantitative RT-PCR was done using iQ SYBR Green Supermix using iCycler by Bio-Rad, USA. 18S rRNA (sense, 5'-GTAACCCGTTGAACCCCATT-3', and antisense, 5'- CCATCCAATCGGTAGTAGCG-3') was used as external control to normalize expression . All primers were designed by inspection of the genes of interest using data from PrimerBank database (Harvard University). The sequence description of mouse primers used are given in Supplementary Table 1. Negative controls, consisting of reaction mixtures containing all components but the target RNA, were included with each of the RT-PCR runs. The representative PCR mixtures for each gene were run in the absence of the RT enzyme after first being cycled to 95°C for 15 min in order to ensure that amplified products did not represent genomic DNA contamination. No PCR products were observed in the absence of reverse transcription. Direct comparison of four groups such as WT control, WT PA, Sphk2-/- control and Sphk2-/- PA was done using ANOVA test, as described earlier. The level of statistical significance was set at p <0.05.
Validation studies were performed in more animals in addition to the cohort used in RNA-Seq studies.