Protein phosphorylation introduces post‐genomic diversity to proteins, which plays a crucial role in various cellular activities. Elucidation of system‐wide signaling cascades requires high‐performance tools for precise identification and quantification of dynamics of site‐specific phosphorylation events. Recent advances in phosphoproteomic technologies have enabled the comprehensive mapping of the dynamic phosphoproteomic landscape, which has opened new avenues for exploring cell type‐specific functional networks underlying cellular functions and clinical phenotypes. Here, we provide an overview of the basics and challenges of phosphoproteomics, as well as the technological evolution and current state‐of‐the‐art global and quantitative phosphoproteomics methodologies. With a specific focus on highly sensitive platforms, we summarize recent trends and innovations in miniaturized sample preparation strategies for micro‐to‐nanoscale and single‐cell profiling, data‐independent acquisition mass spectrometry (DIA‐MS) for enhanced coverage, and quantitative phosphoproteomic pipelines for deep mapping of cell and disease biology. Each aspect of phosphoproteomic analysis presents unique challenges and opportunities for improvement and innovation. We specifically highlight evolving phosphoproteomic technologies that enable deep profiling from low‐input samples. Finally, we discuss the persistent challenges in phosphoproteomic technologies, including the feasibility of nanoscale and single‐cell phosphoproteomics, as well as future outlooks for biomedical applications.

Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.

Compared to advancements in single-cell proteomics, phosphoproteomics sensitivity has lagged behind due to low abundance, complex sample preparation, and substantial sample input requirements. We present a simple and rapid one-pot phosphoproteomics workflow (SOP-Phos) integrated with data-independent acquisition mass spectrometry (DIA-MS) for microscale phosphoproteomic analysis. SOP-Phos adapts sodium deoxycholate based one-step lysis, reduction/alkylation, direct trypsinization, and phosphopeptide enrichment by TiO₂ beads in a single-tube format. By reducing surface adsorptive losses via utilizing n-dodecyl β-d-maltoside precoated tubes and shortening the digestion time, SOP-Phos is completed within 3-4 h with a 1.4-fold higher identification coverage. SOP-Phos coupled with DIA demonstrated >90% specificity, enhanced sensitivity, lower missing values (<1%), and improved reproducibility (8%-10% CV). With a sample size-comparable spectral library, SOP-Phos-DIA identified 33,787 ± 670 to 22,070 ± 861 phosphopeptides from 5 to 0.5 μg cell lysate and 30,433 ± 284 to 6,548 ± 21 phosphopeptides from 50,000 to 2,500 cells. Such sensitivity enabled mapping key lung cancer signaling sites, such as EGFR autophosphorylation sites Y1197/Y1172 and drug targets. The feasibility of SOP-Phos-DIA was demonstrated on EGFR-TKI sensitive and resistant cells, revealing the interplay of multipathway Hippo-EGFR-ERBB signaling cascades underlying the mechanistic insight into EGFR-TKI resistance. Overall, SOP-Phos-DIA is an efficient and robust protocol that can be easily adapted in the community for microscale phosphoproteomic analysis.

Protein phosphorylation plays a crucial role in regulating disease phenotypes and serves as a key target for drug development. Mapping nanoscale‐to‐single‐cell samples can unravel the heterogeneity of cellular signaling events. However, it remains a formidable analytical challenge due to the low detectability, abundance, and stoichiometry of phosphorylation sites. Here, we present a Chip‐DIA strategy, integrating a microfluidic‐based phosphoproteomic chip (iPhosChip) with data‐independent acquisition mass spectrometry (DIA‐MS) for ultrasensitive nanoscale‐to‐single‐cell phosphoproteomic profiling. The iPhosChip operates as an all‐in‐one station that accommodates both quantifiable cell capture/imaging and the entire phosphoproteomic workflow in a highly streamlined and multiplexed manner. Coupled with a sample size‐comparable library‐based DIA‐MS strategy, Chip‐DIA achieved ultra‐high sensitivity, detecting 1076±158 to 15869±1898 phosphopeptides from 10±0 to 1013±4 cells, and revealed the first single‐cell phosphoproteomic landscape comprising druggable sites and basal phosphorylation‐mediated networks in lung cancer. Notably, the sensitivity and coverage enabled the illumination of heterogeneous cytoskeleton remodeling and cytokeratin signatures in patient‐derived cells resistant to third‐generation EGFR therapy, stratifying mixed‐lineage adenocarcinoma‐squamous cell carcinoma subtypes, and identifying alternative targeted therapy for late‐stage patients. With flexibility in module design and functionalization, Chip‐DIA can be adapted to other PTM‐omics to explore dysregulated PTM landscapes, thereby guiding therapeutic strategies toward precision oncology.

Single‐Cell Phosphoproteomic Analysis