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ValveCCI-seq: An Advanced Microfluidic Approach for Deciphering Cell-Cell Interactions
Mingsheng Wang1,2, Jingyu Qi2,3, Shiyu Wang4
1School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China.
Insights
We developed ValveCCI-seq, a new method to study cell-cell interactions. This high-throughput platform preserves cell identities, enabling better understanding of immune responses and advancing cell therapy.
Area of Science:
- Biotechnology
- Immunology
- Genomics
Background:
- Immunotherapy efficacy relies on precise immune cell interaction modulation.
- Current cell-cell interaction analysis methods have limitations in throughput, efficiency, and preserving cell identity.
Purpose of the Study:
- To develop a high-resolution platform for profiling cell-cell interactions while preserving cell identities.
- To overcome the limitations of existing transcriptome-based methods for analyzing cell-cell interactions.
Main Methods:
- Developed ValveCCI-seq, a microfluidic platform integrating deterministic cell-pairing and in situ sequencing.
- Achieved high throughput (32,000 cell pairs/hour) and efficiency (>86%) with broad cell compatibility.
- Enabled direct transcriptome profiling of co-encapsulated cell pairs within droplets, preserving cell-pair identities.
Main Results:
- ValveCCI-seq revealed gene expression signatures linked to T-cell activation using Jurkat and T2 cells.
- Demonstrated precise identification of tumor antigens and cognate T-cell receptor (TCR) sequences.
- Preserved interacting cell identities and enabled high-throughput analysis.
Conclusions:
- ValveCCI-seq offers a robust framework for advancing cell therapy development.
- Facilitates systematic studies of cellular interactions in clinical samples.
- Supports parallel TCR screening across multiple antigens.
Abstract:
Immunotherapy eliminates diseased cells by precisely activating or enhancing the patient's immune responses, with its efficacy critically dependent on the accurate modulation of immune cell interaction networks with disease-relevant targets. However, existing methodologies for analyzing cell-cell interactions face inherent trade-offs among throughput, efficiency, and cellular compatibility, and transcriptome-based methods for probing interaction states often result in the loss of cell-pair identities. To address these limitations, we have developed ValveCCI-seq, a microfluidic platform that integrates a deterministic cell-pairing module with an in situ sequencing module for high-resolution profiling of cell-cell interactions. The pairing module achieves a throughput of up to 32,000 cell pairs per hour with an efficiency exceeding 86% and is broadly compatible with diverse cell types. The sequencing module enables direct transcriptome profiling of coencapsulated cell pairs within droplets, eliminating the need for postinteraction demulsification and thereby preserving the identities of both interacting cells. Utilizing Jurkat and T2 cells as a model system, ValveCCI-seq revealed gene expression signatures associated with T-cell activation and demonstrated its capability for the precise identification of tumor antigens and their cognate T-cell receptor (TCR) sequences. In conclusion, ValveCCI-seq preserves interacting cell identities and enables high-throughput analysis, potentially facilitating systematic studies of cellular interactions in clinical samples, supporting parallel TCR screening across multiple antigens, and providing a robust framework to advance cell therapy development.
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