Articular cartilage remains the most studied tissue in OA, but the knowledge about the meniscus is still limited. In this study, a comparison of knee articular cartilage and meniscus was made in order to gain new knowledge of its composition and also to evaluate two analytical methods for MS: DDA and DIA. We identified several differences between the articular cartilage and meniscus proteome.
Single protein comparisons
Even though the majority of the selected proteins did not substantially differ in abundance between meniscus and articular cartilage, we detected distinct differences for certain specific proteins. However, lysozyme C was one the proteins that were significantly different between the tissue types, after FDR control, in both the DDA and DIA analysis (Fig.
2b). Similarly, lysozyme C was previously reported to be more abundant in articular cartilage than meniscus [
8,
17]. Already discovered by Flemming in the 1920s, lysozymes are characterized as cationic proteins that primarily has a bacteriolytic function, and their presence in articular cartilage has been suggested to be due to ionic interactions with high levels of anionic aggrecan that would enable protein enrichment [
18‐
20]. Indeed, aggrecan was found to have a lower abundance in meniscus, which could explain the lower abundance of lysozyme C. The exact function of lysozyme C in articular cartilage remains unknown, however it is possible that lysozyme C is part of the intra-articular defence against bacteria [
21].
The other protein that was statistically significantly different in abundance between meniscus and articular cartilage, after FDR control, was BGH3 (Fig.
2b). We found that BGH3 had a 5-fold higher expression in meniscus than articular cartilage. BGH3 is known to be expressed in several tissues and has been suggested to have a negative effect on chondrogenesis [
22]. Although it is not known exactly how BGH3 is incorporated into the ECM, it has been observed to bind to several collagens as well as fibronectin, decorin and biglycan [
22,
23].
Small leucine-rich proteoglycans (SLRPs) is a group of highly abundant ECM proteins in cartilage. They bind to several collagens and have been reported to have effect on various cellular functions, e.g. due to their ability to bind numerous cell surface receptors and growth factors, and in later years they have also been associated with OA pathogenesis [
24]. The group of SLRPs includes 18 members [
25], of which 8 were included in this analysis. Asporin, at the protein level, was first described by Lorenzo et al. in 2001 [
26], and has been reported to be able to inhibit TGFß-mediated chondrogenesis [
27,
28]. In this study, asporin was found to be more abundant in meniscus than in articular cartilage, both in the DDA and DIA analysis with meniscus to articular cartilage ratios of 10.79 and 9.40 respectively (Table
1). A previous study also reported an enrichment of asporin in the meniscus compared to articular cartilage [
8]. Two other members of the SLRP family that exhibited similar trends as asporin in this study was decorin and biglycan, of which both were among the top 10 proteins in both articular cartilage and meniscus (Table
2). Both proteins had a higher intensity in meniscus, however this was not statistically significant.
Aggrecan is the most abundant proteoglycan in articular cartilage and plays a very important role to trap water and make the articular cartilage able to withstand compressive load. In this analysis, the aggrecan level was approximately 10 times higher in articular cartilage than in meniscus (Table
1). This is consistent with previous studies, which have reported that aggrecan mRNA levels are lower in human meniscus than articular cartilage and that total proteoglycan synthesis is lower in bovine fibrochondrocytes of the meniscus than articular chondrocyte-populated constructs [
29,
30]. Furthermore, most of the aggrecan is bound to hyaluronic acid and link proteins [
31], which is probably why the proteoglycan link protein 1 (HPLN1) correlate with aggrecan (Fig.
2b). In contrast, the proteoglycan versican was more abundant in meniscus, both in DDA and DIA (Table
1). Versican was first described as a fibroblast proteoglycan [
32], and in one study comparing aggrecan and versican mRNA levels in chondrocytes and fibroblasts, it was observed that versican mRNA levels were higher in fibroblasts than chondrocytes, while aggrecan could only be detected in chondrocytes [
33]. This could explain the higher abundance of versican in meniscus since it contains both chondrocyte-like cells and fibroblast-like cells [
6]. Aggrecan and versican belong to the same family of hyaluronan-binding proteoglycans [
34], and while the function of aggrecan in articular cartilage is well-known, more research is needed to fully elucidate the role versican plays in the meniscus.
The protein with the highest significant intensity difference in meniscus compared to articular cartilage in this study was dermatopontin, with a meniscus to articular cartilage ratio of approximately 15 and 29 in the DIA and DDA analysis respectively (Table
1). Dermatopontin is an ECM protein that has been associated with promotion of cell attachment and spreading of dermal fibroblasts [
35] and has been reported to have a higher expression in healthy menisci than OA menisci using proteomics [
36]. The presence of fibroblast-like cells in the outer regions of menisci could explain the increased intensity of dermatopontin in our meniscus samples [
37].
Vascularisation
As previously described, the meniscus is partly vascularized, while articular cartilage is avascular [
38,
39]. In this study, we can report that among the proteins with at least two unique peptides, 25 can be classified as blood circulation proteins using the GO accession GO:000815. Of these, 8 were found to be meniscus-specific and none were unique to articular cartilage. Furthermore, serum albumin is the protein with the highest intensity in meniscus in the DDA analysis (Table
2), which further supports the previous reports of a vascularized meniscus. The list of the ten most abundant proteins in meniscus also contains two additional well-known plasma proteins; haemoglobin subunit beta and serotransferrin (Table
2). One protein that significantly differed between meniscus and articular cartilage was alpha-1-antitrypsin (A1AT). This protein is one of the top 20 most abundant proteins in plasma, and it is therefore not surprising that A1AT is on average approximately five times more abundant in meniscus than articular cartilage (Table
1). However, several plasma proteins were identified also in articular cartilage in this study. Since articular cartilage is in contact with synovial fluid in the joint, and synovial fluid is an ultra-filtrate of plasma and therefore contains plasma proteins, the presence of plasma proteins in articular cartilage might be explained by the ability of the cartilage to absorb molecules, in this case plasma proteins, from its surroundings. This could for example be the case for angiogenin, a protein found in the circulation and reported to be angiogenic [
40]. It was significantly more abundant in articular cartilage than meniscus in this study. Angiogenin is a 14 kDa and 123 amino acids long protein that is highly cationic [
41,
42], making it similar to lyzosyme C in both size and charge [
17]. These common traits with lysozyme C, which is enriched in articular cartilage, could explain the presence of angiogenin in articular cartilage despite its avascular phenotype. Similarly, in one study, the authors reported that angiogenesis might be involved in OA, and hypothesised that articular cartilage might be able to take up circulating molecules, e.g. from the vascularised synovium and that there was an invasion of synovium into the articular cartilage [
43]. Furthermore, in a study investigating the role of angiogenesis in hip OA, it was noted that the grade of angiogenesis was related to the cartilage degeneration, hence it could be involved in the degenerative process [
44].
Data-dependent acquisition vs data-independent acquisition
The second aim of this study was to compare DDA and DIA in order to decide which method to use in future studies. First of all, DIA yielded more precise estimates than DDA. As a consequence, many proteins in the DIA analysis were also statistically significant after FDR control, while only a few in the DDA analysis. In addition to this, DIA had no missing values. Out of the 103 proteins that remained after peak selection in Skyline and selected for statistical analysis, we removed 13 from the analysis due to missing values in the DDA analysis. This is due to the fact that DDA randomly measures only the most abundant peptides if too many peptides elute at the same time in one MS1 scan, then the low abundant peptides are therefore missed [
45]. This makes DDA data less reproducible than DIA data, and there is also a risk that the low-abundant proteins are excluded [
45]. This problem is circumvented in DIA, since all precursor ions within a certain m/z range are measured [
9,
13]. Another advantage with DIA is that it is possible to base the quantitation on MS2, which is not possible with DDA. MS2 is also often used for identification and validation with DIA, which is only possible with DDA if MS2 is available. One factor that might be regarded as a disadvantage with DIA is that it is more time-consuming than DDA, as the manual peak selection that needs to be performed before the data can be analysed is tedious [
45]. Another feature is that the DIA data contains more complex MS2 spectra that require a spectral library for extracting the data. Improved software solutions could have a great impact on these drawbacks. The high complexity of the data also results in the need of larger data storage space, which might be a challenge. Even though DIA might be superior to DDA in several ways, on average, both methods, as expected, give similar point estimates of the differences between the two analysed tissues. The higher precision of DIA can probably be explained by the fact that the peptides are manually selected in DIA, resulting in the removal of peptides with worse chromatographic performance. Taken together, the advantages of DIA make it the preferred method of choice.
Limitations
Since this was a pilot analysis, the sample size was limited; hence resulting in a lower power and a higher risk of type 2 errors, i.e. the comparison of single proteins between the tissues should be interpreted with caution. Furthermore, we chose to narrow down the number of included proteins in order to make the analyses less complex e.g. as OA is a disease that markedly affects the ECM, therefore only ECM proteins were included in the analyses. The ECM proteins were filtered by the GO accession term GO:0031012. There are some limitations connected with the usage of GO accession terms e.g. the fact that there are several terms that refer to ECM proteins and that there is a possibility that some ECM proteins might have been lost in the filtration. However, we chose the one we thought would be most suitable for this study and the most common ECM proteins have been included in the analysis, which is sufficient since the main aim of the filtration was to select a number of proteins to include in our method comparison.