Tissue Collection and RNA Extraction from the Human Osteoarthritic Knee Joint
July 22nd, 2021
Primary tissues obtained from patients following total knee arthroplasty provide an experimental model for osteoarthritis research with maximal clinical translatability. This protocol describes how to identify, process, and isolate RNA from seven unique knee tissues to support mechanistic investigation in human osteoarthritis.
This protocol encourages the use of primary human tissues as a clinically relevant model for osteoarthritis research. Performing gene expression and histological analyses in these tissues may provide novel mechanistic insights. This technique standardizes methods for the identification and processing of human knee joint components.
It enables the extraction of high quality RNA that meets the requirements for downstream gene expression assays. It is challenging to obtain high quality RNA from diseased joint tissues, so the importance of seemingly insignificant steps, such as keeping everything clean and cool should not be underestimated. Demonstrating the procedure will be Thomas Wilson, a research associate and Navdeep Kaur, a postdoctoral fellow from my laboratory.
Begin by identifying the hard tissues, including cartilage, bone, and meniscus and soft tissues, including infrapatellar fat pad, anterior cruciate ligament, synovium and vastus medialis oblique muscle from the specimen based on the differences in the size, shape, color and texture. Cut each of the tissues into three sections. Rinse the tissue sections with sterile PBS to remove any residue or debris.
For RNA extraction, cut each of the three tissue sections into approximately one to two millimeter cubes. Transfer the smaller pieces to a two milliliter cryo vial. After securing the caps tightly, flash freeze the vials by submerging in liquid nitrogen for 30 seconds, then transfer the vial to the minus 80 degrees Celsius freezer for long-term storage, and repeat this procedure for all the tissues.
Homogenize the hard tissue using a mortar and pestle. Before homogenization, chill the mortar, pestle and spatula using liquid nitrogen to prevent the sample from thawing. Process only one sample at a time.
Transfer the tissue sample to mortar using a chilled spatula. Pour liquid nitrogen on top of the tissue. After the liquid nitrogen evaporates, crush the tissue with a pestle.
Repeatedly add liquid nitrogen while grinding the tissue to obtain fine tissue powder. Transfer the fine tissue powder in a 1.5 milliliter micro centrifuge tube pre-chilled by submerging in liquid nitrogen for 30 seconds. Add one milliliter of the ice-cold acid guanidinium phenol solution to each tube and incubate the tubes on ice for 20 minutes.
Before homogenizing different hard tissue, thoroughly clean the mortar, pestle and spatula with 70%ethanol, then with RNase decontaminant, followed by DEPC treated water. Soak the mortar, pestle and spatula in 70%ethanol, then wipe any residual liquid with a clean, lint-free tissue. Homogenize the soft tissue using the tissue homogenizer.
For disinfecting the homogenizer, wash the probe by running tubes of 70%ethanol and RNase decontaminant for 30 seconds per wash, then wash with DEPC treated water, followed by an additional 70%ethanol, each for 30 seconds. Wipe any residual liquid with a clean, lint-free tissue. Add one milliliter of acid guanidinium phenol solution to pre-labeled, five milliliter round bottom tubes, and transfer the tissue sample into the tube.
Place the tube on ice throughout the procedure and homogenize the tissue for a maximum of five 32nd pulses, or until the tissue is visually dissolved. Incubate the homogenized tissue on ice until all the tissue samples are processed. Disinfect and clean the homogenizer before processing the next tissue sample.
Using sterile forceps, remove any tissue chunk present in the teeth of the probe. Incubate all the homogenized tissue on the ice for additional 20 minutes and then transfer the tissue sample to a pre-labeled, pre-chilled 1.5 milliliter micro centrifuge tube. Seven unique human knee joint tissues obtained from osteoarthritis patients were processed within four hours of surgical removal.
The tissues were identified visually and confirmed by H&E histological staining. The H&E stained hard tissue sections, articular cartilage, subchondral bone and meniscus were visualized at six times magnification and 40 times magnification. Similarly, the H&E stained soft tissue sections, infrapatellar fat pad, anterior cruciate ligament, synovium and vastus medialis oblique muscle were visualized at six times magnification and then at 40 times magnification.
The quality assessment of extracted RNA indicated the presence of high quality samples based on integrity, yield and purity, as well as low quality samples, suggesting that despite using an optimized method, external factors like disease severity may impact the RNA quality across different tissues from the same patient. Correct identification of each tissue type is necessary to enable intra-and inter-tissue comparisons within and across patient samples, especially given the considerable heterogeneity of primary disease tissues. Sequencing technologies are rapidly evolving, and isolation of high quality RNA is a critical prerequisite to using these technologies to unravel underlying tissue-specific mechanisms in complex, chronic diseases like osteoarthritis.
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Overview
This study investigates the extraction of high-quality RNA from primary human knee tissues obtained following total knee arthroplasty to further osteoarthritis research. The method outlined provides a standardized approach to process and isolate RNA from unique knee joint components, facilitating mechanistic analysis in osteoarthritis.
Key Study Components
Research Area
- Osteoarthritis research
- Gene expression analysis
- Histological investigations
Background
- Use of primary human tissues as a relevant model
- Challenges in obtaining quality RNA from diseased tissues
- Importance of methodological precision in RNA extraction
Methods Used
- Isolation of RNA from hard and soft knee tissues
- Human primary tissues from osteoarthritis patients
- Histological staining and quality assessment of RNA
Main Results
- RNA extraction optimized for various knee tissues
- Observed integrity and purity of RNA samples
- Effective identification of tissue types for comparative analysis
Conclusions
- The protocol enhances the understanding of osteoarthritis mechanisms
- Supports further research using high-throughput sequencing technologies
Frequently Asked Questions
Executive Industry Relevance
Isolating high-quality RNA from primary human osteoarthritic tissues enables physiologically relevant gene expression studies that support target validation and mechanistic de-risking in osteoarthritis drug discovery. This approach bridges discovery biology with translational research by providing disease-relevant systems for preclinical target confirmation and biomarker exploration. Standardized tissue processing improves reproducibility across samples, reducing biological variability in downstream assays.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Scientific Value: Enables interrogation of disease mechanisms across multiple joint tissues to validate therapeutic targets in a physiologically relevant context.
- Operational Value: Supports consistent RNA yield and integrity for reliable downstream sequencing and qPCR assays.
Screening & Assay Development
- Scientific Value: Provides standardized tissue homogenization protocols for hard and soft tissues, ensuring comparable inputs for assay development.
- Operational Value: Establishes RNase-free workflows and tissue-specific disruption methods critical for assay standardization.
Translational & Preclinical Research
- Scientific Value: Facilitates cross-tissue comparisons to identify conserved pathways and tissue-specific responses in osteoarthritis.
- Operational Value: Enables biobanking of flash-frozen tissues for longitudinal studies and inter-laboratory reproducibility.
Pipeline & Workflow Integration
The method supports early discovery workflows by generating high-quality RNA from primary human tissues, which informs target selection and pathway analysis prior to lead identification.
- Discovery Biology: Enables hypothesis testing through gene expression profiling of cartilage, bone, synovium, and other joint tissues to clarify disease pathways.
- Screening: Produces standardized RNA inputs suitable for transcriptomic screening and biomarker discovery campaigns.
- Analytics: Delivers quantitative RNA integrity, yield, and purity metrics that allow cross-sample normalization and data comparability.
- Translational Research: Supports biomarker alignment by enabling RNA extraction from clinically relevant tissues obtained during total knee arthroplasty.
- Enterprise Reuse: Establishes a scalable tissue processing framework applicable to multiple osteoarthritis studies and cross-functional teams.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence by reducing mechanistic ambiguity through multi-tissue molecular profiling.
- Operational Value: Enhances reproducibility via standardized cold-chain handling and tissue-specific disruption techniques.
- Strategic Value: Improves go/no-go decisions by providing human-relevant data that de-risks target selection.
- Portfolio Impact: Enables risk-adjusted prioritization of targets based on concordant expression across disease-relevant tissues.
Implementation Considerations
- Requires expertise in tissue dissection, RNA handling, and RNase-free techniques to prevent degradation.
- Needs access to liquid nitrogen, cryogenic storage, and tissue homogenizers or mortar and pestle for sample processing.
- Demands standardization of RNA extraction protocols across hard and soft tissue types to ensure comparability.
- Requires adaptation of disruption methods based on tissue matrix density (e.g., pulverization for cartilage, homogenization for synovium).
- Limited by inter-patient variability in RNA integrity, necessitating donor stratification and quality control thresholds.
