0853 - Metabolite and Protein Variation Between Healthy and Degraded Alpaca Cervical Discs Analyzed by High Resolution Mass Spectrometry and Correlated to MR Imaging
Bibliographic record
Abstract
INTRODUCTION: Naturally occurring degeneration of the intervertebral disc (IVD) tissue is a common condition associated with aging adults that has been linked with disability and pain. Much work has been done in evaluating the biomechanics, biotransport, genetics, histology, morphology, cellular variation, and even gene expression in the healthy and degenerated IVD. However, our current understanding of the IVD metabolome and proteome, and their adaptation in response to disc degeneration is primitive and largely based on work done on cartilaginous tissues from other regions of the body. Appropriate human tissue samples for research into this area are difficult to obtain [1]. Spontaneous intervertebral disc degeneration is a rarity in the animal kingdom, and nutrient transport mechanisms in the intervertebral disc have been shown to depend on both size and motion. Alpacas have been introduced as an appropriate large animal model suitable for studying natural disc degeneration from both a cellular and biomechanical perspective [2, 3]. This work presents the first known evaluation of the IVD metabolome and proteome from both the healthy and degenerated IVD using high resolution mass spectrometry of alpaca discs. Additionally, we have spatially correlated the metabolomic and proteomic data of the same IVD tissues with MR diffusion tensor imaging in order to investigate potential mechanisms for identifying which metabolic processes are perturbed between degenerated and healthy disc materials at various stages of degeneration. METHODS: T1, T2, and Diffusion Tensor MRI images of the cervical spines of four alpacas were taken less than 3-hours post-mortem and were used to classify disc degeneration using the Pfirrmann grading system. Following MRI imaging, the alpaca spines were dissected and relevant cervical disc tissues were removed and frozen in a -80u00b0 C freezer. The entire imaging and sample preparation process was completed less than 6-hours post-mortem. Samples of healthy (Pfirrmann grades 2 or 3) and degenerated (grades 4 or 5) IVDs from within the same animal were collected from each alpaca. A 50 mg sample of both the nucleus pulpous and annulus fibrous within each disc were removed. Hydrophobic metabolites were extracted with a modified Bligh and Dyer solvent system (Chloroform: Methanol: Isopropanol) (3: 1: 1.25) (V/V/V) [4] . Extracted hydrophobic metabolites were separated using reverse phase C18 chromatography and analyzed in both positive and negative ionization modes on an Agilent 6520 QTOF (Santa Clara, CA). Separate 5 mg samples of both the nucleus pulpous and annulus fibrous disc tissue for both degenerated and healthy disc tissue were reduced and denatured in 2.5 mM Dithiothreitol and 8 M urea overnight and then diluted and digested with trypsin. Peptides were desalted prior to mass spec analysis on a Thermo Orbitrap Fusion (Waltham, MA). Metabolite data was analyzed with XCMS Online (Scripts, La Jolla CA), and proteins were identified using PEAKS software (Bioinformatics Solutions Inc. Ontario, CA). RESULTS SECTION: XCMS comparison of hydrophobic metabolites between healthy and degenerated IVD tissues identified 26 valuable metabolites - primarily inflammation and oxidative stress lipid response markers - with a 1.5-fold change or greater and 0.05 p-value or less. An additional 45 metabolic features were noted of statistical significance between healthy and degenerated IVD tissues. The protein analysis revealed 1611 protein identifications; however, statistical analysis distilled these proteins into 49 valuable proteins with a p-value < 0.05. DISCUSSION: Inflammation proteins and metabolites give validity to the evidence of observed and expected pain in alpacas. Significant variations in collagen and ubiquitin were clearly noted. This may suggest ongoing restructuring and degeneration of compromised disc tissue. It is interesting to note that histone and methyl transferase proteins were also found. This may suggest evidence of alterations occurring at the DNA coding level related to disc degeneration. This has yet to be elucidated, but may lead to future research opportunities. Limitations of this pilot study include a limited number of alpaca samples, and the potential for inherent differences between alpacas and humans. Furthermore, additional hydrophilic and low level metabolites and proteins may be below the limit of detection. SIGNIFICANCE/CLINICAL RELEVANCE: In order to develop and evaluate strategies and therapeutics for long term prevention and regeneration of intervertebral disc tissues in humans, advances in understanding differences in metabolic pathways between degenerated and healthy disc tissue is crucial. REFERENCES: 1.tDaly, C., et al., A Review of Animal Models of Intervertebral Disc Degeneration: Pathophysiology, Regeneration, and Translation to the Clinic. Biomed Res Int, 2016. 2016: p. 5952165.2.tStolworthy, D.K., et al., MRI evaluation of spontaneous intervertebral disc degeneration in the alpaca cervical spine. J Orthop Res, 2015. 33(12): p. 1776-83.3.tStolworthy, D.K., et al., Biomechanical analysis of the camelid cervical intervertebral disc. J Orthop Translat, 2015. 3(1): p. 34-43.4.tBligh, E.G. and W.J. Dyer, A rapid method of total lipid extraction and purification. Can J Biochem Physiol, 1959. 37(8): p. 911-7.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".