Yi-Tao Long

Lensless imaging offers a new route to substantially alleviate the shackle of space‐bandwidth‐product (SBP) on conventional optical microscopes, thus high resolution and wide field‐of‐view (FOV) can be more easily achieved simultaneously. A series of lensless imaging methods have taken their place in chemical bioimaging due to their advantages of wide FOV and low cost. This review discusses the development of sensor‐proximal contact, incoherent, holographic, and ptychographic imaging and evaluates their applications across cellular phenotyping, particle and molecular sensing, as well as tissue and in vivo imaging. Particular emphasis is placed on interfacial chemical strategies involving affinity reagents, responsive materials, luminescent reactions, and engineered probes. These approaches convert nanoscale chemical events, which cannot be directly resolved by lensless systems, into amplified and spatially resolved optical signals. By combining chemical signal transduction with large‐area imaging, lensless platforms can detect individual cells, particles, and molecular events while simultaneously capturing their temporal dynamics, spatial organization, and collective evolution. This chemistry‐centered minireview highlights future opportunities for extracting multiscale spatiotemporal information from complex chemical and biological systems.

Lensless imaging offers a new route to substantially alleviate the shackle of space‐bandwidth‐product (SBP) on conventional optical microscopes, thus high resolution and wide field‐of‐view (FOV) can be more easily achieved simultaneously. A series of lensless imaging methods have taken their place in chemical bioimaging due to their advantages of wide FOV and low cost. This review discusses the development of sensor‐proximal contact, incoherent, holographic, and ptychographic imaging and evaluates their applications across cellular phenotyping, particle and molecular sensing, as well as tissue and in vivo imaging. Particular emphasis is placed on interfacial chemical strategies involving affinity reagents, responsive materials, luminescent reactions, and engineered probes. These approaches convert nanoscale chemical events, which cannot be directly resolved by lensless systems, into amplified and spatially resolved optical signals. By combining chemical signal transduction with large‐area imaging, lensless platforms can detect individual cells, particles, and molecular events while simultaneously capturing their temporal dynamics, spatial organization, and collective evolution. This chemistry‐centered minireview highlights future opportunities for extracting multiscale spatiotemporal information from complex chemical and biological systems.

Histone acetylation, a post-translational modification, is associated with cancer progression, invasion, and metastasis, serving as a promising biomarker. The accurate discrimination of acetylation sites has strong potential for cancer diagnostics. Herein, we engineered an R220Q aerolysin nanopore to detect isobaric histone acetylations. By exposing the paired negative charge (D222) at the pore entrance, peptides with a higher positive charge density encounter a lower U* for pore entry and subsequent translocation. With the assistance of machine learning, we achieved direct discrimination of isobaric acetylations in histone peptides. Monoacetylated peptides H3K9ac and H3K14ac, as well as diacetylated peptides H3K4acK9ac and H3K4acK14ac were unambiguously identified in mixtures with identification accuracies of 99.4% and 98.8%, respectively. This work offers a label-free approach for analyzing acetylated biomarkers with potential applications in cancer detection and drug target development.

Peptide sensing and sequencing are essential for elucidating sequence-function relationships and evaluating the peptide drug quality. Nanopore electrochemistry enables label-free characterization of peptide composition, structure, and interactions at the single-molecule level through ionic-current fingerprints. However, efficient capture remains challenging for low-abundance peptides with heterogeneous charge and conformational properties. Herein, we study peptide capture by the asymmetric OmpF nanopore and examine the relative contributions of electroosmotic flow (EOF), electrophoretic force (EPF), peptide conformation, and field-gradient-mediated interactions. The laterally heterogeneous charge distribution within OmpF modulates the salt dependence of ionic screening and electroosmotic transport, supporting an efficient EOF-associated peptide capture under high-salt conditions. Atomistic molecular dynamics simulations reveal salt-dependent changes in ionic conductance, water flux, and counterion accumulation within the constriction zone, suggesting that the local counterion accumulation approaches saturation at high ionic strength. This behavior enables OmpF to combine high signal-to-noise ratio with low-concentration peptide detection across net charges from −2 e to +6 e. This OmpF sensor provides a linear detection range spanning more than four orders of magnitude, nanomolar concentration limits, and femtogram-level sample consumption. Furthermore, by utilizing the stereoselective recognition capability of OmpF’s asymmetric constriction zone, this approach was further applied to the identification of chiral impurities in near-neutral peptide drugs. The OmpF-based nanopore sensor provides a sensitive and label-free platform with a broad dynamic range for single-molecule peptide analysis, paving the way for versatile nanopore applications.

Protein oxidation generates diverse chemical states that regulate cellular signaling yet progressively accumulate as molecular damage during aging. However, characterizing oxidation‐state heterogeneity of individual proteins or peptides remains challenging, as conventional ensemble methods average over coexisting species. Here, we report a nanopore strategy based on a confined hydrogen‐bond network to decode oxidation states within individual native peptides. By engineering a constricted recognition region enriched with hydrogen‐bond interactions, the changes induced by diverse oxidation states were specifically recognized. This enables discrimination of closely related oxidative modifications, including proline hydroxylation, methionine oxidation, and tryptophan oxidation, even at ultra‐low abundance. We show that the reversible and regulated oxidation state could be clearly distinguished from irreversible and damaged oxidation with the same mass without separation or purification. Furthermore, we quantified heterogeneous oxidation distributions generated under controlled oxidative conditions. This approach provides a molecular‐level strategy for characterizing oxidation‐state heterogeneity in individual peptides, with potential applications in studying oxidative modifications associated with aging and disease in future biological investigations.

Protein oxidation generates diverse chemical states that regulate cellular signaling yet progressively accumulate as molecular damage during aging. However, characterizing oxidation‐state heterogeneity of individual proteins or peptides remains challenging, as conventional ensemble methods average over coexisting species. Here, we report a nanopore strategy based on a confined hydrogen‐bond network to decode oxidation states within individual native peptides. By engineering a constricted recognition region enriched with hydrogen‐bond interactions, the changes induced by diverse oxidation states were specifically recognized. This enables discrimination of closely related oxidative modifications, including proline hydroxylation, methionine oxidation, and tryptophan oxidation, even at ultra‐low abundance. We show that the reversible and regulated oxidation state could be clearly distinguished from irreversible and damaged oxidation with the same mass without separation or purification. Furthermore, we quantified heterogeneous oxidation distributions generated under controlled oxidative conditions. This approach provides a molecular‐level strategy for characterizing oxidation‐state heterogeneity in individual peptides, with potential applications in studying oxidative modifications associated with aging and disease in future biological investigations.

The direct detection of small hydrophobic biomolecules remains a major challenge for biological nanopores. This is due to the weak interactions provided by the hydrophilic lumens, which result in ultrafast translocation and insufficient molecular recognition. Here, to reconcile the hydrophilicity for ionic flow and hydrophobic interactions for molecule recognition, we engineer a hydrophobic confinement stabilized by an interconnected hydrogen-bond network. By introducing tyrosine and tryptophan into the primary sensing region, a localized hydrophobic environment is established while maintaining nanopore structural stability and low current noise. Molecular dynamics simulations demonstrated the formation of a localized hydrophobic environment stabilized by an interconnected hydrogen-bond network, enabling the direct identification of thyroid hormones, aromatic amino acid-derived hydrophobic biomolecules containing iodinated aromatic structures, through enhanced molecular interactions. We show that the hydrophobic confinement could discriminate single iodine atom differences within diverse thyroid hormones, of which individual events can be automatically classified using an unsupervised clustering algorithm without prior model training. Furthermore, the isobaric triiodothyronine and reverse triiodothyronine could be directly resolved in a mixture. This work establishes hydrophobic confinement engineering as an effective strategy for extending biological nanopores to the direct single-molecule measurement of clinically relevant hydrophobic biomolecules.

Tumor-specific neoantigens have been the most promising targets for TCR-based cancer therapies; however, their detection is greatly hindered by low abundance, sequence variability, and potential modifications. To address these, we developed a digital nanopore framework to unambiguously identify and effectively quantify candidate neoantigens directly in cell samples via event-resolved molecular identification and counting. By engineering a multirecognition-region nanopore and developing a universal water-osmosis driving force, we simultaneously enhanced the detection throughput and specificity. Combined with enriched current signatures and a gradient-boosting decision-tree classifier, the platform identifies individual ovalbumin-derived model neoantigens with single-amino-acid resolution from digitally assigned events in both exogenously incubated and endogenously expressed cell samples. We show that the limit of quantification is improved to the fmol level in native biological environments, enabling the direct identification of neoantigens from as few as 5000 cells within 30 min. We further demonstrate the identification of a native Epstein–Barr virus-associated neoantigen, highlighting the potential of this approach in ultrasensitive analysis of rare biomolecular species directly in biological samples.