Michael Lewandowski (Boston, MA / US), Shad Morton (Boston, MA / US), Aeronn Bevan (Zurich / CH), Katharina Meyer (Boston, MA / US), Jenny Tam (Boston, MA / US), Ahmad Rushdy (Boston, MA / US), George Church (Boston, MA / US), David Walt (Boston, MA / US), Bogdan Budnik (Boston, MA / US)
Background: Single-cell methodologies have revolutionized biology by allowing us to explore cellular heterogeneity and complexity at unprecedented resolution. The emergence of single-cell proteomics (SCP) over the last five years has helped us understand the function of the cell as a complementary method to deep sequencing and imaging modalities, which have primarily focused on transcriptomics. SCP is a promising tool for studying complex biological processes, such as cell differentiation, drug response, and disease development. It can also provide valuable insights into the role of post-translational modifications in the regulation of cellular function.
Methods: Despite the challenge that proteins cannot be amplified like transcripts, single-cell proteomics has already led to exciting discoveries. Among them are identifying rare cell types, analyzing cellular heterogeneity, and examining signaling pathways. Utilizing small sample volumes remain challenging, necessitating robust statistical methods for data interpretation. To address this issue, we have implemented very precise liquid sample handling robots for the separation of material for two different analytical workflows in order to both transcriptomics and proteomics within the same cell. In addition, it is essential to establish standards for widespread accessibility. By using industry-developed hardware that can be easily integrated into most analytical laboratories worldwide, we advocate rapid problem-solving to integrate SCP into a high-throughput, scalable multi-omics platform for diagnosing and treating diseases.
Conclusion: Integrating single-cell proteomics with transcriptomics provides a more detailed view of cellular function. As we continue to elucidate single cell behavior within the context of the whole cell population, this rapidly evolving technology promises to revolutionize biological research. The relationship between the transcriptome and the proteome machinery in cell function and disease can be fully understood by using and integrating both transcriptomics and proteomics at single-cell resolution.
References:
Ahmad, R., & Budnik, B. (2023). A review of the current state of single-cell proteomics and future perspective. Analytical and Bioanalytical Chemistry, 415(2023), 6889–6899.
Straubhaar, J; D'Souza, A; Niziolek, Z; Budnik, B (2024) Single cell proteomics analysis of drug response shows its potential as a drug discovery platform Molecular Omics Vol1, issue 20, 1-5.
Specht, H., Emmott, E., Petelski, A. A., Huffman, R. G., Perlman, D. H., Serra, M., Kharchenko, P., Koller, A., & Slavov, N. (2021). Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2. Genome Biology, 22, 50.