Response induced in Mycoplasma gallisepticum under heat shock might be relevant to infection process

Despite the fact the term “proteome” was proposed to characterize a set of proteins in one of mycoplasma species, proteome response to various exposures in this bacteria are still obscure. Commonly, authors studying proteomic response on perturbation models in mycoplasmas use single approach and do not confirm their findings by alternative methods. Consequently, the results of proteomic analysis should be validated by complementary techniques. In this study we utilized three complementary approaches (SWATH, MRM, 2D-DIGE) to assess response of Mycoplasma gallisepticum under heat stress on proteomic level and combined these findings with metabolic response and the results of transcriptional profiling. We divide response into two modes – one is directly related to heat stress and other is triggered during heat stress, but not directly relevant to it. The latter includes accumulation of ATP and shedding of antigens. Both of these phenomena may be relevant to evasion of host’s immune system and dissemination during mycoplasmosis in vivo.

loading solvent and solvent A, the mix of 98.9% water, 1% methanol, 0.1% formic acid (v/v) was used. Solvent B was 99.9% acetonitrile, 0.1% formic acid (v/v). Samples were loaded on a trap column (ChromXP C18, 3 μm, 120 Å 350 μm × 0.5 mm, Eksigent) at a flow rate of 3 μl/min over 10 min and eluted through the separation column (3C18-CL-120, 3 μm, 120 Å 75 μm × 150 mm, Eksigent) at a flow rate of 300 nl/min. The gradient was from 5 to 40% of solvent B in 120 min. The column and the precolumn were regenerated between runs by washing with 95% of solvent B for 7 min and equilibrated with 5% of solvent B for 25 min.
Between the samples to ensure the absence of carryover both the column and the precolumn were thoroughly washed with a blank injection trap-elute gradient that included five 7 minute 5-95-95-5%B waves followed by 25 min 5%B equilibration.
Mass spectra were acquired in a positive ion mode. Information-dependent mass-spectrometer experiment included 1 survey scan followed by 50 dependent fragmentation scans. Survey spectra acquisition parameters were as follows: mass range for analysis and subsequent ion selection for fragmentation was 300-1250 m/z, signal accumulation time was 250 ms. Ions for fragmentation were selected based on intensity with the threshold of 200 cps and the charge state from 2 to 5. Fragmentation spectra acquisition parameters were as follows: resolution of quadrupole was set to Unit (0.7 Da), measurement mass range was 200-1800 m/z, optimization of ion beam focus was to obtain maximal sensitivity, signal accumulation time was 50 ms for each parent ion. Collision activated dissociation was performed with nitrogen gas with collision energy ramping from 25 to 55 V within 50 ms signal accumulation time. Analyzed parent ions were sent to dynamic exclusion list for 15 s in order to get the next fragmentation spectra of the same compound around its chromatographic peak apex (minimum peak width throughout the gradient was about 30 s). Minimal number of fragments that must follow the same trend (i.e. follow reproducible fragmentation pattern) between samples to be used as "reliable" was selected to be 3. After fragment filtering all proteins with less than 3 peptides were excluded. This was followed by renormalization of different LC-MS repeats of same sample and averaging, then by the second normalization and averaging step between technical repeats of trypsinolysis of the same sample (some biological samples were trypsinized in replicates) and the third normalization and averaging step within sample type. To obtain results biological samples 4 were cross scale-normalized based on the assumption that most of the cell proteins in any pair of samples were supposed to be independent (that is the scaling should set the average difference between proteins for a pair of samples to minimum).
To calculate protein fold change results, for all fragment intensities logarithm with the base B (was chosen to obtain the best scaling) was taken. The logarithm results for each fragment were averaged within a sample (LC-MS repeats*trypsinolysis repeats*technical replicates) to obtain peptide logarithm result. Protein result was calculated as a median of its 3 "best flyer" 2 (ones with largest signal) peptide values. Fold change for a protein was calculated as a difference in median values between samples raised to power B.

Metabolomic analysis
The following chemicals were used as standards: sodium pyruvate (100 mg/ml, gallisepticum was prepared in accordance with the KEGG database as described previously 6 and contained all the metabolites associated with the proteins that were annotated for this bacteria. The following parameters were used for the search: range of m/z values (extraction window), 15 ppm m/z; minimum intensity of peak, 1000 a.u.; minimum value of baseline signal intensity ratio, 10.
A pairwise sample comparison of metabolomic data for M. gallisepticum in normal and heat conditions was performed using the XCMS online service, providing a direct comparison of two sample groups. From the resulting features, we selected only those with a p value ≤ 0.05 in order to state that compound concentration is different in two conditions.
Additionally, these compounds were analyzed manually by counting the metabolite identifications among the repetitions of normal and stressed conditions for both acquisition modes. The quantification of an identified metabolite is possible only if it was detected at least three times in both cases. In the case a compound was detected less than three times in all repetitions for same grow condition, only a qualitative comparison is possible, based on the detection of MS counts for this compound in the group.