Increased and irreversible matrix breakdown in cartilaginous components is associated with the onset and progression of OA and disc degeneration12,13,14. A variety of small molecules have been discovered to promote cartilage regeneration. For example, kartogenin21,30 and its derivative analogue, KA34, could enhance chondrogenesis and matrix production via nuclear recruitment of the chondrogenic transcription factor CBFb. Its inhibition of matrix degradation and OA progression through induction of IL-10 was also reported31. SM04690, a Wnt pathway inhibitor, was reported to reduce proteoglycan degradation in differentiated chondrocytes32, and a phase 2B trial of SM04690 was conducted to elucidate its efficacy and safety33. Shi et al. demonstrated a modulatory effect of BNTA on extracellular matrices in chondrocytes via SOD3 induction22. These results demonstrated the value of HTS in identifying effective agents to modify musculoskeletal disorders. In this study, we investigated a miniaturized DMMB assay and optimized its adaptation for HTS library screening, aiming to identify modifiers of proteoglycan metabolism. Absorbances at 535 nm and 595 nm are two representative wavelengths for measuring GAGs in the solution sampled from the culture medium or in the digested cells34,35 and correspond to the formation of DMMB-GAG complexes and the consumption of the DMMB reagent in the system. Although via using chondroitin sulfate as substance, we found assay at 595 nm may give resembling absorbance window as that at 535 nm (Fig. 1a), it should be carefully considered that in the real reaction, contaminations from the cell lysate, such as DNA, may also bind with DMMB and interfere the readings at 595 nm23. It is intriguing that at 620 nm, a larger absorbance window was observed. How well this wavelength serves the DMMB assay awaits to be further addressed. A more concentrated DMMB reagent was used to generate a wider linear reading window (0–664 μg/mL, x-coordinate in Fig. 2b) and a larger absorbance scale (0.39–0.66, y-coordinate in Fig. 2b). Overall, several modifications to the conventional assay method that are critical to effective HTS were implemented: (1) Medium refreshment and cell digestion prior to the DMMB reaction were avoided for an efficient high-throughput workflow. (2) A450nm was measured as a reference for A535nm to minimize interferences arising from the plate and buffers. (3) Measurements were acquired 5 min instead of immediately after DMMB addition to obtain more steady readouts, therefore minimizing variation during large batch processing.
We selected porcine costal chondrocytes over cell lines such as ATDC522 or MSC-derived chondrocytes32 for assay development. We reasoned that primary chondrocytes provide a more native phenotype, in particular matrix production, for functional screening. A relatively high seeding density of 3 × 104 cells/cm2 was adopted to maintain the cells in a differentiated state, as indicated by the cobblestone morphology typically observed in mature chondrocytes. Furthermore, assay kinetics were determined to identify midpoints of the linear range for maximizing the detection of both up- and downregulation of GAG production. The MTT assay was optimized to evaluate global metabolism and was applicable as a reference for assessing regulatory specificity in proteoglycan metabolism. However, with longer incubation times, such readings gradually increase, and twenty-four hours seems adequate to maximize the readings.
TGF-β1 is an anabolic regulator of proteoglycans and an inhibitor of their degradation, whereas IL1-α is a catabolic effector25,26. The results from TGF-β1- and IL1-α-treated cells substantiate the capacity of the system to detect up- and downregulation of GAGs. A Z′ score over 0.5 is considered “excellent” for signal-to-noise separation27, and our assay was shown to be unbiased for identifying both positive and negative signals and indicative of HTS compatibility. Based on analysis of the medium controls, our data demonstrated no significant plate-to-plate variation, suggesting the feasibility of cross-plate comparison. In this study, the median from each plate was exploited for normalization to further increase the assay robustness.
A proof-of-concept chemical screening was conducted using the miniaturized DMMB assay, and both positive and negative regulatory candidates were identified from the library. The majority of the 960 compounds (79.69%) showed readouts within 3 × S.D., which were considered insignificant36. Notably, the screening results showed a skewed distribution, and a larger panel of compounds with < 3 × S.D was identified (15.10% vs 5.21%). This is consistent with the known tendency of target inhibition of small molecules. Interestingly, the screening using MTT assay also demonstrated a skewed distribution, but towards positive readouts, implying the intensive bioactivity of the compounds pool (Supplementary Table S3). It should be noted that the library is small, and thus, the screening process is primitive and not considered high throughput. However, the chemical screening was conducted with the automated platform, and as a result could be readily adapted to large-scale study (e.g. 50 k compound library) based on our previous experience37. The hit rate is considered relatively high (20.31%), presumably due to the broad cut-off and false positivity. MTT assay allows evaluating not only cellular toxicity but also global metabolic activity. In this study, evaluation of metabolic viability by MTT assay was implemented to narrow down the hits (4.48% vs 6.04%, enhancers vs repressors) which can specifically regulate proteoglycans production without altering metabolic viability. While top-ranked compounds are usually prioritized based on the primary readouts in HTS, we selected E1 and R1 to better assess the assay reliability in view of their moderate regulatory effect on proteoglycans production among the hit. Besides, they both caused minimal MTT changes, implying a specific instead of global regulation. Sequential screenings are typically required to narrow down the hits, where various concentrations of compounds can be included to evaluate dose-dependency. Moreover, cheminformatic clustering is widely employed to assess the molecular fingerprint similarity of a large panel of compounds and could jointly facilitate the hit selection process. The reproducibility in triplicates is supported by CV values < 10% from 99.1% compounds. False positives, such as due to the compound’s intrinsic colour should be examined and removed in subsequent screening. In this scenario, readings from the compound might not follow a linear relationship with dosage and further sample processing for compound-free validation may be required. Taking our work as an example, GAGs can be purified from culture after treatment and quantified by FACE. Moreover, notwithstanding the significant changes detected in chondroitin sulfate expression, it is not clear whether other types of GAGs was also modulated, such as keratan sulfate, the other major GAG component in aggrecan and SLRP that is highly expressed in chondrocytes. There also might be compounds that alter the GAG composition without changing the total GAG content and therefore not detected by the assay.
Identifying both stimulators and inhibitors of proteoglycan metabolism can have relevant implications. Proteoglycans play critical roles in signalling activation6,8,10, tissue development and morphogenesis3,18,20 and participate in pathological processes other than OA, such as tissue fibrosis38 and outgrowth of dorsal root ganglion (DRG) axons in discogenic pain4. While GAG repressors are likely not relevant to cartilage regeneration, their identification might potentially be beneficial to axonal regeneration for peripheral nerve or spinal cord repair4,39.
In conclusion, we established an enhanced, miniaturized DMMB assay and illustrated its effective integration with HTS platform and chemical screening to identify regulators of GAG expression using chondrocytes as a model. Proteoglycan production is rudimentary to chondrocyte function. GAG-based primary screening may therefore provide a simple way to prioritize leads in a large library for further investigation. Our study serves as a proof-of-principle for quantitative GAG-based HTS screening. Its application may facilitate the identification of new agents for treating OA and intervertebral disc degeneration and possibly other disorders related to proteoglycan misregulation. Furthermore, considering the importance of GAGs in the polymerization and activation of signalling molecules, such as STING10, screening GAG regulators may tap into new resources for manipulating these pathways.
