Release date: 2018-02-28
Recently, in a recent study published in the journal Nature Communications, scientists from the New York Genomics Center (NYGC) and New York University (NYU) have successfully developed a low-cost, portable new 3D printed microfluidic device that has been successful. Applied to clinical practice, it further promotes the wide application of single-cell sequencing technology.
In order to verify the practicality of this portable device in the clinical environment, the researchers used this device to perform single-cell sequencing on the synovial tissue of patients with rheumatoid arthritis (RA), which truly realized the low-cost routine of microfluidic technology. application. In addition, the device, together with its electronic and pneumatic components, costs only around $600. And the equipment has a small footprint and is almost the same size as a tissue box.
Currently, single-cell RNA sequencing based on droplet microfluidic technology has become a powerful tool for large-scale parallel cell analysis. In the clinical field, single-cell sequencing has provided a breakthrough in understanding the cellular heterogeneity of diseased tissues, but cost-effectiveness and instrumental friendliness have hampered its widespread use. Commercially available microfluidic instruments are mostly expensive and not available in all laboratories. "To solve this problem, we developed a low-cost 3D printed microfluidic microfluidic device and deployed it in a clinical setting to perform a single-cell transcriptome on the synovial tissue of five rheumatoid arthritis patients. Analysis," the researchers wrote in the paper.
Dr. William Stephenson, senior research and development engineer at the New York Technology Innovation Lab, led the development of the device. He said: "We designed the instrument to include micro-fluidic microdroplets and Drop-seq independent technology for large-scale parallelism. Cellular RNA sequencing needs. In addition, the portability of the device allows clinicians to process patient samples in real time at the surgical site or after surgery, minimizing processing and transportation to optimize sample quality.
According to the paper, the researchers sequenced 20,387 single cells and revealed 13 different cell populations at the transcriptome level. In addition, the researchers identified previously unidentified fibroblast subpopulations and identified their spatial location within the synovium, presenting potential targets for drug development in rheumatoid arthritis. It is noteworthy that single cell sequencing of all patient tissues was performed approximately one hour after surgical resection.
Workflow from operating room to sequencing
According to reports, this study is an important step in the construction of a comprehensive "cell atlas" of RA synovial tissue. Next, the researchers will collect data from more patients with other types of rheumatic key inflammation, with the goal of obtaining patient samples from other arthritic patients, such as psoriatic arthritis and osteoarthritis. In addition, they plan to use CITE-seq (a new genomic tool developed by the NYGC Technology Innovation Lab) to more accurately classify cell types through cell surface proteins outside the transcriptome.
The researchers also said the technology would help portray samples that are difficult to study in standard laboratories, such as highly contagious in bioprotective facilities or samples collected in a field research environment. In order to facilitate the widespread use of technology in the scientific community, the technology has been completely "open source." Instructions and assembly manuals for the instrument can be found in the Metafluidics repository. Dr. Stephenson concluded by saying: "We hope that this device will ultimately solve the barriers to performing single-cell transcriptome analysis in basic research and clinical settings."
Reference materials:
Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low-cost microfluidic instrumentation
Novel Instrument for Low-Cost Single-Cell Analysis Developed
Source: Sequencing China
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