Immuno-SABER enables highly multiplexed and amplified protein imaging in tissues

Programming Fast DNA Amplifier Circuits with Versatile Toehold Exchange Pathway

DNA amplifier circuits establish powerful tools to dynamically control molecular assembly for computation, sensing, and biological applications. However, the slow reaction speed remains a major barrier to their practical utility. Here, diverse fast DNA amplifier circuits termed toehold exchange polymerization (TEP) and toehold exchange catalysis (TEC) using toehold exchange-mediated assembly as a fundamental mechanism are built. Both TEP and TEC with a duplex and a hairpin can respond within minutes to diverse nucleic acid inputs with high fidelity. In addition, the circuits can amplify live-cell signals for fluorescence imaging target RNA dynamics and discriminating different cell lines. Compared with existing DNA circuits that involve time scales of hours for transducing small signals, TEP and TEC exhibit much faster dynamics, simpler design, and comparable sensitivity. These features make TEP and TEC promising platforms to develop programmable nucleic acid tools and devices and to create fast sensing and processing systems, amenable to wide practical applications.

Proximity labeling expansion microscopy (PL-ExM) evaluates interactome labeling techniques

Understanding protein-protein interactions (PPIs) through proximity labeling has revolutionized our comprehension of cellular mechanisms and pathology. Various proximity labeling techniques, such as HRP, APEX, BioID, TurboID, and μMap, have been widely used to biotinylate PPIs or organelles for proteomic profiling. However, the variability in labeling precision and efficiency of these techniques often results in limited reproducibility in proteomic detection. We address this persistent challenge by introducing proximity labeling expansion microscopy (PL-ExM), a super-resolution imaging technique that combines expansion microscopy with proximity labeling techniques. PL-ExM enabled up to 17 nm resolution with microscopes widely available, providing visual comparison of the labeling precision, efficiency, and false positives of different proximity labeling methods. Our mass spectrometry proteomic results confirmed that PL-ExM imaging is reliable in guiding the selection of proximity labeling techniques and interpreting the proteomic results with new spatial information.

Multiplexed in situ protein imaging using DNA-barcoded antibodies with extended hybridization chain reactions

Antibodies have long served as vital tools in biological and clinical laboratories for the specific detection of proteins. Conventional methods employ fluorophore or horseradish peroxidase-conjugated antibodies to detect signals. More recently, DNA-conjugated antibodies have emerged as a promising technology, capitalizing on the programmability and amplification capabilities of DNA to enable highly multiplexed and ultrasensitive protein detection. However, the nonspecific binding of DNA-conjugated antibodies has impeded the widespread adoption of this approach. Here, we present a novel DNA-conjugated antibody staining protocol that addresses these challenges and demonstrates superior performance in suppressing nonspecific signals compared to previously published protocols. We further extend the utility of DNA-conjugated antibodies for signal-amplified in situ protein imaging through the hybridization chain reaction (HCR) and design a novel HCR DNA pair to expand the HCR hairpin pool from the previously published 5 pairs to 13, allowing for flexible hairpin selection and higher multiplexing. Finally, we demonstrate highly multiplexed in situ protein imaging using these techniques in both cultured cells and tissue sections.

Spatiotemporal omics for biology and medicine

The completion of the Human Genome Project has provided a foundational blueprint for understanding human life. Nonetheless, understanding the intricate mechanisms through which our genetic blueprint is involved in disease or orchestrates development across temporal and spatial dimensions remains a profound scientific challenge. Recent breakthroughs in cellular omics technologies have paved new pathways for understanding the regulation of genomic elements and the relationship between gene expression, cellular functions, and cell fate determination. The advent of spatial omics technologies, encompassing both imaging and sequencing-based methodologies, has enabled a comprehensive understanding of biological processes from a cellular ecosystem perspective. This review offers an updated overview of how spatial omics has advanced our understanding of the translation of genetic information into cellular heterogeneity and tissue structural organization and their dynamic changes over time. It emphasizes the discovery of various biological phenomena, related to organ functionality, embryogenesis, species evolution, and the pathogenesis of diseases.

Ultrasensitive Detection of Cancer Biomarkers Using Photonic-Crystal-Enhanced Single-Molecule Imaging

The rapid and sensitive quantification of low-abundance protein markers holds immense significance in early disease diagnosis and treatment. Single-molecule fluorescence imaging exhibits very high detection sensitivity and thus has great application potential in this area. The single-molecule signal, however, is often susceptible to interference from background noise due to its inherently weak intensity. A variety of signal amplification techniques based on cascading reactions have been developed to improve the signal-to-noise ratio of single-molecule imaging. Nevertheless, the operation of these methods is typically complicated and time-consuming, which limits the clinical application. Herein, we introduce an enzyme-free, photonic-crystal-based single-molecule (PC-SM) biochip for cost-effective, time-efficient, and ultrasensitive detection of disease markers. The PC-SM biochip can enhance the signal-to-noise ratio of single molecules by nearly 3-fold compared with unamplified samples, through coupling of the single-molecule photon energy with the optical band gap of the photonic crystal. We used the PC-SM biochip to detect the low-abundance leukemia inhibitory factor in the blood of pancreatic cancer patients and healthy people and achieved a detection limit of 2.0 pg/L and an AUC of 0.9067. The method exhibits exceptional sensitivity and specificity, showing great application potential in various clinical settings.

Construction of Multiply Guaranteed DNA Sensors for Biological Sensing and Bioimaging Applications

Nucleic acids exhibit exceptional functionalities for both molecular recognition and catalysis, along with the capability of predictable assembly through strand displacement reactions. The inherent programmability and addressability of DNA probes enable their precise, on-demand assembly and accurate execution of hybridization, significantly enhancing target detection capabilities. Decades of research in DNA nanotechnology have led to advances in the structural design of functional DNA probes, resulting in increasingly sensitive and robust DNA sensors. Moreover, increasing attention has been devoted to enhancing the accuracy and sensitivity of DNA-based biosensors by integrating multiple sensing procedures. In this review, we summarize various strategies aimed at enhancing the accuracy of DNA sensors. These strategies involve multiple guarantee procedures, utilizing dual signal output mechanisms, and implementing sequential regulation methods. Our goal is to provide new insights into the development of more accurate DNA sensors, ultimately facilitating their widespread application in clinical diagnostics and assessment.

On-demand expansion fluorescence and photoacoustic microscopy (ExFLPAM)

Expansion microscopy (ExM) is a promising technology that enables nanoscale imaging on conventional optical microscopes by physically magnifying the specimens. Here, we report the development of a strategy that enables i) on-demand labeling of subcellular organelles in live cells for ExM through transfection of fluorescent proteins that are well-retained during the expansion procedure; and ii) non-fluorescent chromogenic color-development towards efficient bright-field and photoacoustic imaging in both planar and volumetric formats, which is applicable to both cultured cells and biological tissues. Compared to the conventional ExM methods, our strategy provides an expanded toolkit, which we term as expansion fluorescence and photoacoustic microscopy (ExFLPAM), by allowing on-demand fluorescent protein labeling of cultured cells, as well as non-fluorescent absorption contrast-imaging of biological samples.

Application of spatial omics in gastric cancer

Gastric cancer (GC), a globally prevalent and lethal malignancy, continues to be a key research focus. However, due to its considerable heterogeneity and complex pathogenesis, the treatment and diagnosis of gastric cancer still face significant challenges. With the rapid development of spatial omics technology, which provides insights into the spatial information within tumor tissues, it has emerged as a significant tool in gastric cancer research. This technology affords new insights into the pathology and molecular biology of gastric cancer for scientists. This review discusses recent advances in spatial omics technology for gastric cancer research, highlighting its applications in the tumor microenvironment (TME), tumor heterogeneity, tumor genesis and development mechanisms, and the identification of potential biomarkers and therapeutic targets. Moreover, this article highlights spatial omics' potential in precision medicine and summarizes existing challenges and future directions. It anticipates spatial omics' continuing impact on gastric cancer research, aiming to improve diagnostic and therapeutic approaches for patients. With this review, we aim to offer a comprehensive overview to scientists and clinicians in gastric cancer research, motivating further exploration and utilization of spatial omics technology. Our goal is to improve patient outcomes, including survival rates and quality of life.

Signal amplification by cyclic extension enables high-sensitivity single-cell mass cytometry

Mass cytometry uses metal-isotope-tagged antibodies to label targets of interest, which enables simultaneous measurements of ~50 proteins or protein modifications in millions of single cells, but its sensitivity is limited. Here, we present a signal amplification technology, termed Amplification by Cyclic Extension (ACE), implementing thermal-cycling-based DNA in situ concatenation in combination with 3-cyanovinylcarbazole phosphoramidite-based DNA crosslinking to enable signal amplification simultaneously on >30 protein epitopes. We demonstrate the utility of ACE in low-abundance protein quantification with suspension mass cytometry to characterize molecular reprogramming during the epithelial-to-mesenchymal transition as well as the mesenchymal-to-epithelial transition. We show the capability of ACE to quantify the dynamics of signaling network responses in human T lymphocytes. We further present the application of ACE in imaging mass cytometry-based multiparametric tissue imaging to identify tissue compartments and profile spatial aspects related to pathological states in polycystic kidney tissues.

Orthogonal DNA Self-Assembly-Based Expansion Microscopy Platform for Amplified, Multiplexed Biomarker Imaging

Expansion microscopy (ExM) facilitates nanoscale imaging under conventional microscopes, but it frequently encounters challenges such as fluorescence losses, low signal-to-noise ratio (SNR), and limited detection throughput. To address these issues, a method of orthogonal DNA self-assembly-based ExM (o-DAExM) platform is developed, which employs hybridization chain reaction instead of conventional fluorescence labeling units, showcasing signal amplification efficacy, enhancement of SNR, and expandable multiplexing capability at any stage of the ExM process. In this work, o-DAExM has been applied to compare with immunofluorescence-based ExM for cellular cytoskeleton imaging, and the resolved nanoscale spatial distributions of cytoskeleton show outstanding performance and reliability of o-DAExM. Furthermore, the study demonstrates the utility of o-DAExM in accurately revealing exosome heterogeneous information and multiplexed analysis of protein targets in single cells, which provides infinite possibilities in super-resolution imaging of cells and other samples. Therefore, o-DAExM offers a straightforward expansion and signal labeling method, highlighting future prospects to study nanoscale structures and functional networks in biological systems.

Multiplexed and Quantitative Imaging of Live-Cell Membrane Proteins by a Precise and Controllable DNA-Encoded Amplification Reaction

Amplifying DNA conjugated affinity ligands can improve the sensitivity and multiplicity of cell imaging and play a crucial role in comprehensively deciphering cellular heterogeneity and dynamic changes during development and disease. However, the development of one-step, controllable, and quantitative DNA amplification methods for multiplexed imaging of live-cell membrane proteins is challenging. Here, we introduce the template adhesion reaction (TAR) method for assembling amplifiable DNA sequences with different affinity ligands, such as aptamers or antibodies, for amplified and multiplexed imaging of live-cell membrane proteins with high quantitative fidelity. The precisely controllable TAR enables proportional amplification of membrane protein targets with variable abundances by modulating the concentration ratios of hairpin templates and primers, thus allowing sensitive visualization of multiple membrane proteins with enhanced signal-to-noise ratios (SNRs) without disturbing their original ratios. Using TAR, we achieved signal-enhanced imaging of six proteins on the same live-cell within 1-2 h. TAR represents an innovative and programmable molecular toolkit for multiplexed profiling of membrane proteins in live-cells.

Multiplexed imaging to reveal tissue dendritic cell spatial localisation and function

Dendritic cells (DCs) play a pivotal role in immune surveillance, acting as sentinels that coordinate immune responses within tissues. Although differences in the identity and functional states of DC subpopulations have been identified through multiparametric flow cytometry and single-cell RNA sequencing, these methods do not provide information about the spatial context in which the cells are located. This knowledge is crucial for understanding tissue organisation and cellular cross-talk. Recent developments in multiplex imaging techniques can now offer insights into this complex spatial and functional landscape. This review provides a concise overview of these imaging methodologies, emphasising their application in identifying DCs to delineate their tissue-specific functions and aiding newcomers in navigating this field.

Spatial Dissection of the Immune Landscape of Solid Tumors to Advance Precision Medicine

Chemotherapeutics, radiation, targeted therapeutics, and immunotherapeutics each demonstrate clinical benefits for a small subset of patients with solid malignancies. Immune cells infiltrating the tumor and the surrounding stroma play a critical role in shaping cancer progression and modulating therapy response. They do this by interacting with the other cellular and molecular components of the tumor microenvironment. Spatial multi-omics technologies are rapidly evolving. Currently, such technologies allow high-throughput RNA and protein profiling and retain geographical information about the tumor microenvironment cellular architecture and the functional phenotype of tumor, immune, and stromal cells. An in-depth spatial characterization of the heterogeneous tumor immune landscape can improve not only the prognosis but also the prediction of therapy response, directing cancer patients to more tailored and efficacious treatments. This review highlights recent advancements in spatial transcriptomics and proteomics profiling technologies and the ways these technologies are being applied for the dissection of the immune cell composition in solid malignancies in order to further both basic research in oncology and the implementation of precision treatments in the clinic.

New tools to study renal fibrogenesis

PURPOSE OF REVIEW

Kidney fibrosis is a key pathological aspect and outcome of chronic kidney disease (CKD). The advent of multiomic analyses using human kidney tissue, enabled by technological advances, marks a new chapter of discovery in fibrosis research of the kidney. This review highlights the rapid advancements of single-cell and spatial multiomic techniques that offer new avenues for exploring research questions related to human kidney fibrosis development.

RECENT FINDINGS

We recently focused on understanding the origin and transition of myofibroblasts in kidney fibrosis using single-cell RNA sequencing (scRNA-seq) [1] . We analysed cells from healthy human kidneys and compared them to patient samples with CKD. We identified PDGFRα+/PDGFRβ+ mesenchymal cells as the primary cellular source of extracellular matrix (ECM) in human kidney fibrosis. We found several commonly shared cell states of fibroblasts and myofibroblasts and provided insights into molecular regulators. Novel single-cell and spatial multiomics tools are now available to shed light on cell lineages, the plasticity of kidney cells and cell-cell communication in fibrosis.

SUMMARY

As further single-cell and spatial multiomic approaches are being developed, opportunities to apply these methods to human kidney tissues expand similarly. Careful design and optimisation of the multiomic experiments are needed to answer questions related to cell lineages, plasticity and cell-cell communication in kidney fibrosis.

Hairpin-Empowered Invasive Reaction Combined with Catalytic Hairpin Assembly Cascade Amplification for the Specific Detection of Single-Nucleotide Polymorphisms

Single-nucleotide polymorphism (SNP) is widely used in the study of disease-related genes and in the genetic study of animal and plant strains. Therefore, SNP detection is crucial for biomedical diagnosis and treatment as well as for molecular design breeding of animals and plants. In this regard, this article describes a novel technique for detecting SNP using flap endonuclease 1 (FEN 1) as a specific recognition element and catalytic hairpin assembly (CHA) cascade reaction as a signal amplification strategy. The mutant target (MT) was hybridized with a biotin-modified upstream probe and hairpin-type downstream probe (DP) to form a specific three-base overlapping structure. Then, FEN 1 was employed for three-base overlapping structure-specific recognition, namely, the precise SNP site identification and the 5' flap of DP dissociation. After dissociation, the hybridized probes were magnetically separated by a streptavidin-biotin complex. Especially, the ability to establish such a hairpin-type DP provided a powerful tool that could be used to hide the cut sequence (CS) and avoid false-positive signals. The cleaved CS initiated the CHA reaction and allowed superior fluorescence signal generation. Owing to the high specificity of FEN 1 for single base recognition, only the MT could be distinguished from the wild-type target and mismatched DNA. Owing to the dual signal amplification, as low as 0.36 fM MT and 1% mutation abundance from the mixtures could be detected, respectively. Furthermore, it could accurately identify SNPs from human cancer cells, as well as soybean leaf genome extracts. This strategy paves the way for the development of more precise and sensitive tools for diagnosing early onset diseases as well as molecular design breeding tools.

Portable Device with Nicking Enzyme Enhanced Special RCA on μPADs toward Sensitive Detection of High-Risk HPV Infection

Development of an accurate, rapid, and cost-effective portable device is in high demand for point-of-care molecular diagnosis toward disease screening. Here we report a one-pot homogeneous isothermal assay that leverages nicking endonuclease and minimum secondary structured rolling circle amplification (N-MSSRCA) for fast and sensitive quantification of nucleic acids on distance microfluidic paper-based analytical devices (dμPAD) by a portable custom-made fluorescence detector. Human papillomavirus (HPV) oncogenic E7 mRNA as the biomarker for cervical cancer was used as the model analyte. N-MSSRCA integrates ligase for target recognition, the nicking enzyme for primer generation, and the dual function of the Phi29 DNA polymerase for both on- and off-loop amplification. The proposed method was capable of detecting 1 and 10 fM of the analyte using the microplate reader and portable detector with dμPAD, respectively, with ∼1 h assay time. A cohort study of 40 cervical swab samples shows N-MSSRCA reached positive and negative predictive values of 87.5% and 93.5% using the portable detector with dμPAD, compared to 91.67% and 100% using the microplate reader. N-MSSRCA demonstrates potential in early screening of high-risk HPV infection as a generic strategy to detect various nucleic acids in point-of-care scenarios.

Combining poly-epitope MoonTags and labeled nanobodies for signal amplification in cell-specific PET imaging in vivo

Immunorecognition provides an excellent basis for targeted imaging techniques covering a wide range from basic research to diagnostics and from single cells to whole organisms. Fluorescence- or radioisotope-labeled antibodies, antibody fragments or nanobodies enable a direct signal readout upon binding and allow for versatile imaging from microscopy to whole-body imaging. However, as the signal intensity directly correlates with the number of labeled antibodies bound to their epitopes (1:1 binding), sensitivity for low-expressing epitopes can be limiting for visualization. For the first time, we developed poly-epitope tags with multiple copies (1 to 7) of a short peptide epitope, specifically the MoonTag, that are recognized by a labeled nanobody and aimed at signal amplification in microscopy and cell-specific PET imaging. In transiently transfected HeLa cells or stably transduced A4573 cells we characterized complex formation and in vitro signal amplification. Indeed, using fluorescently and radioactively labeled nanobodies we found an approximately linear signal amplification with increasing numbers of epitope copies in vitro. To test the poly-epitope approach in vivo, A4573 tumor cells were injected subcutaneously into the shoulder of NSG mice, with A4573 tumor cells expressing a poly-epitope of 7 MoonTags on one side and WT cells on the other side. Using a [68Ga]-labeled NODAGA-conjugated MoonTag nanobody, we performed PET/CT imaging at day 8-9 after tumor implantation. Specific binding of a [68Ga]-labeled NODAGA-conjugated MoonTag nanobody was observed in 7xMoonTag tumors (1.7 ± 0.5%ID/mL) by PET imaging, showing significantly higher radiotracer accumulation compared to the WT tumors (1.1 ± 0.3%ID/mL; p < 0.01). Ex vivo gamma counter measurements confirmed significantly higher uptake in 7xMoonTag tumors compared to WT tumors (p < 0.001). In addition, MoonTag nanobody binding was detected by autoradiography which was spatially matched with histological analysis of the tumor tissues. In conclusion, we expect nanobody-based poly-epitope tag strategies to be widely applicable for multimodal imaging techniques given the advantageous properties of nanobodies and their amenability to genetic and chemical engineering.

Machine learning integrative approaches to advance computational immunology

The study of immunology, traditionally reliant on proteomics to evaluate individual immune cells, has been revolutionized by single-cell RNA sequencing. Computational immunologists play a crucial role in analysing these datasets, moving beyond traditional protein marker identification to encompass a more detailed view of cellular phenotypes and their functional roles. Recent technological advancements allow the simultaneous measurements of multiple cellular components-transcriptome, proteome, chromatin, epigenetic modifications and metabolites-within single cells, including in spatial contexts within tissues. This has led to the generation of complex multiscale datasets that can include multimodal measurements from the same cells or a mix of paired and unpaired modalities. Modern machine learning (ML) techniques allow for the integration of multiple "omics" data without the need for extensive independent modelling of each modality. This review focuses on recent advancements in ML integrative approaches applied to immunological studies. We highlight the importance of these methods in creating a unified representation of multiscale data collections, particularly for single-cell and spatial profiling technologies. Finally, we discuss the challenges of these holistic approaches and how they will be instrumental in the development of a common coordinate framework for multiscale studies, thereby accelerating research and enabling discoveries in the computational immunology field.

DNA-Programmed Four-Bit Quaternary Fluorescence Encoding (FLUCO) Enables 51-Colored Bioimaging Analysis

Color encoding plays a crucial role in painting, digital photography, and spectral analysis. Achieving accurate, target-responsive color encoding at the molecular level has the potential to revolutionize scientific research and technological innovation, but significant challenges persist. Here, we propose a multibit DNA self-assembly system based on computer-aided design (CAD) technology, enabling accurate, target-responsive, amplified color encoding at the molecular level, termed fluorescence encoding (FLUCO). As a model, we establish a quaternary FLUCO system using four-bit DNA self-assembly, which can accurately encode 51 colors, presenting immense potential in applications such as spatial proteomic imaging and multitarget analysis. Notably, FLUCO enables the simultaneous imaging of multiple targets exceeding the limitations of channels using conventional imaging equipment, and marks the integration of computer science for molecular encoding and decoding. Overall, our work paves the way for target-responsive, controllable molecular encoding, facilitating spatial omics analysis, exfoliated cell analysis, and high-throughput liquid biopsy.

Scalable design of orthogonal DNA barcode libraries

Orthogonal DNA barcode library design is an essential task in bioengineering. Here we present seqwalk, an efficient method for designing barcode libraries that satisfy a sequence symmetry minimization (SSM) heuristic for orthogonality, with theoretical guarantees of maximal or near-maximal library size under certain design constraints. Seqwalk encodes SSM constraints in a de Bruijn graph representation of sequence space, enabling the application of recent advances in discrete mathematics1 to the problem of orthogonal sequence design. We demonstrate the scalability of seqwalk by designing a library of >106 SSM-satisfying barcode sequences in less than 20 s on a standard laptop.

Using random forests to uncover the predictive power of distance-varying cell interactions in tumor microenvironments

Tumor microenvironments (TMEs) contain vast amounts of information on patient's cancer through their cellular composition and the spatial distribution of tumor cells and immune cell populations. Exploring variations in TMEs between patient groups, as well as determining the extent to which this information can predict outcomes such as patient survival or treatment success with emerging immunotherapies, is of great interest. Moreover, in the face of a large number of cell interactions to consider, we often wish to identify specific interactions that are useful in making such predictions. We present an approach to achieve these goals based on summarizing spatial relationships in the TME using spatial K functions, and then applying functional data analysis and random forest models to both predict outcomes of interest and identify important spatial relationships. This approach is shown to be effective in simulation experiments at both identifying important spatial interactions while also controlling the false discovery rate. We further used the proposed approach to interrogate two real data sets of Multiplexed Ion Beam Images of TMEs in triple negative breast cancer and lung cancer patients. The methods proposed are publicly available in a companion R package funkycells.

Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine

Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.

Spatial Multi-Omics in Alzheimer's Disease: A Multi-Dimensional Approach to Understanding Pathology and Progression

Alzheimer's Disease (AD) presents a complex neuropathological landscape characterized by hallmark amyloid plaques and neurofibrillary tangles, leading to progressive cognitive decline. Despite extensive research, the molecular intricacies contributing to AD pathogenesis are inadequately understood. While single-cell omics technology holds great promise for application in AD, particularly in deciphering the understanding of different cell types and analyzing rare cell types and transcriptomic expression changes, it is unable to provide spatial distribution information, which is crucial for understanding the pathological processes of AD. In contrast, spatial multi-omics research emerges as a promising and comprehensive approach to analyzing tissue cells, potentially better suited for addressing these issues in AD. This article focuses on the latest advancements in spatial multi-omics technology and compares various techniques. Additionally, we provide an overview of current spatial omics-based research results in AD. These technologies play a crucial role in facilitating new discoveries and advancing translational AD research in the future. Despite challenges such as balancing resolution, increasing throughput, and data analysis, the application of spatial multi-omics holds immense potential in revolutionizing our understanding of human disease processes and identifying new biomarkers and therapeutic targets, thereby potentially contributing to the advancement of AD research.

ARTseq-FISH reveals position-dependent differences in gene expression of micropatterned mESCs

Differences in gene-expression profiles between individual cells can give rise to distinct cell fate decisions. Yet how localisation on a micropattern impacts initial changes in mRNA, protein, and phosphoprotein abundance remains unclear. To identify the effect of cellular position on gene expression, we developed a scalable antibody and mRNA targeting sequential fluorescence in situ hybridisation (ARTseq-FISH) method capable of simultaneously profiling mRNAs, proteins, and phosphoproteins in single cells. We studied 67 (phospho-)protein and mRNA targets in individual mouse embryonic stem cells (mESCs) cultured on circular micropatterns. ARTseq-FISH reveals relative changes in both abundance and localisation of mRNAs and (phospho-)proteins during the first 48 hours of exit from pluripotency. We confirm these changes by conventional immunofluorescence and time-lapse microscopy. Chemical labelling, immunofluorescence, and single-cell time-lapse microscopy further show that cells closer to the edge of the micropattern exhibit increased proliferation compared to cells at the centre. Together these data suggest that while gene expression is still highly heterogeneous position-dependent differences in mRNA and protein levels emerge as early as 12 hours after LIF withdrawal.

Precise immunofluorescence canceling for highly multiplexed imaging to capture specific cell states

Cell states are regulated by the response of signaling pathways to receptor ligand-binding and intercellular interactions. High-resolution imaging has been attempted to explore the dynamics of these processes and, recently, multiplexed imaging has profiled cell states by achieving a comprehensive acquisition of spatial protein information from cells. However, the specificity of antibodies is still compromised when visualizing activated signals. Here, we develop Precise Emission Canceling Antibodies (PECAbs) that have cleavable fluorescent labeling. PECAbs enable high-specificity sequential imaging using hundreds of antibodies, allowing for reconstruction of the spatiotemporal dynamics of signaling pathways. Additionally, combining this approach with seq-smFISH can effectively classify cells and identify their signal activation states in human tissue. Overall, the PECAb system can serve as a comprehensive platform for analyzing complex cell processes.

The broken Alzheimer's disease genome

The complex pathobiology of late-onset Alzheimer's disease (AD) poses significant challenges to therapeutic and preventative interventions. Despite these difficulties, genomics and related disciplines are allowing fundamental mechanistic insights to emerge with clarity, particularly with the introduction of high-resolution sequencing technologies. After all, the disrupted processes at the interface between DNA and gene expression, which we call the broken AD genome, offer detailed quantitative evidence unrestrained by preconceived notions about the disease. In addition to highlighting biological pathways beyond the classical pathology hallmarks, these advances have revitalized drug discovery efforts and are driving improvements in clinical tools. We review genetic, epigenomic, and gene expression findings related to AD pathogenesis and explore how their integration enables a better understanding of the multicellular imbalances contributing to this heterogeneous condition. The frontiers opening on the back of these research milestones promise a future of AD care that is both more personalized and predictive.

Ultrasensitive and Multiplexed Protein Imaging with Clickable and Cleavable Fluorophores

Single-cell spatial proteomic analysis holds great promise to advance our understanding of the composition, organization, interaction, and function of the various cell types in complex biological systems. However, the current multiplexed protein imaging technologies suffer from low detection sensitivity, limited multiplexing capacity, or are technically demanding. To tackle these issues, here, we report the development of a highly sensitive and multiplexed in situ protein profiling method using off-the-shelf antibodies. In this approach, the protein targets are stained with horseradish peroxidase (HRP) conjugated antibodies and cleavable fluorophores via click chemistry. Through repeated cycles of target staining, fluorescence imaging, and fluorophore cleavage, many proteins can be profiled in single cells in situ. Applying this approach, we successfully quantified 28 different proteins in human formalin-fixed paraffin-embedded (FFPE) tonsil tissue, which represents the highest multiplexing capacity among the tyramide signal amplification (TSA) methods. Based on their unique protein expression patterns and their microenvironment, ∼820,000 cells in the tissue are classified into distinct cell clusters. We also explored the cell-cell interactions between these varied cell clusters and observed that different subregions of the tissue are composed of cells from specific clusters.

Codetection of Proteins and RNAs on Extracellular Vesicles for Pancreatic Cancer Early Diagnosis

Tumor-derived extracellular vesicles (EVs) carry tumor-specific proteins and RNAs, thus becoming prevalent targets for early cancer diagnosis. However, low expression of EV cargos and insufficient diagnostic power of individual biomarkers hindered EVs application in clinical practice. Herein, we propose a multiplex Codetection platform of proteins and RNAs (Co-PAR) for EVs. Co-PAR adopted a pair of antibody-DNA probes to recognize the same target protein, which in turn formed a double-stranded DNA. Thus, the target protein could be quantified by detecting the double-stranded DNA via qPCR. Meanwhile, qRT-PCR simultaneously quantified the target RNAs. Thus, with a regular qPCR instrument, Co-PAR enabled the codetection of multiplex proteins and RNAs, with the sensitivity of 102 EVs/μL (targeting CD63) and 1 EV/μL (targeting snRNA U6). We analyzed the coexpressions of three protein markers (CD63, GPC-1, HER2) and three RNA markers (snRNA U6, GPC-1 mRNA, miR-10b) on EVs from three pancreatic cell lines and 30 human plasma samples using Co-PAR. The diagnostic accuracy of the 6-biomarker combination reached 92.9%, which was at least 6.2% higher than that of 3-biomarker combinations and at least 13.5% higher than that of 6 single biomarkers. Co-PAR, as a multiparameter detection platform for EVs, has great potential in early disease diagnosis.

Molecular robotic agents that survey molecular landscapes for information retrieval

DNA-based artificial motors have allowed the recapitulation of biological functions and the creation of new features. Here, we present a molecular robotic system that surveys molecular environments and reports spatial information in an autonomous and repeated manner. A group of molecular agents, termed 'crawlers', roam around and copy information from DNA-labeled targets, generating records that reflect their trajectories. Based on a mechanism that allows random crawling, we show that our system is capable of counting the number of subunits in example molecular complexes. Our system can also detect multivalent proximities by generating concatenated records from multiple local interactions. We demonstrate this capability by distinguishing colocalization patterns of three proteins inside fixed cells under different conditions. These mechanisms for examining molecular landscapes may serve as a basis towards creating large-scale detailed molecular interaction maps inside the cell with nanoscale resolution.

Expanding boundaries - a cell biologist's guide to expansion microscopy

Expansion microscopy (ExM) is a revolutionary novel approach to increase resolution in light microscopy. In contrast to super-resolution microscopy methods that rely on sophisticated technological advances, including novel instrumentation, ExM instead is entirely based on sample preparation. In ExM, labeled target molecules in fixed cells are anchored in a hydrogel, which is then physically enlarged by osmotic swelling. The isotropic swelling of the hydrogel pulls the labels apart from one another, and their relative organization can thus be resolved using conventional microscopes even if it was below the diffraction limit of light beforehand. As ExM can additionally benefit from the technical resolution enhancements achieved by super-resolution microscopy, it can reach into the nanometer range of resolution with an astoundingly low degree of error induced by distortion during the physical expansion process. Because the underlying chemistry is well understood and the technique is based on a relatively simple procedure, ExM is easily reproducible in non-expert laboratories and has quickly been adopted to address an ever-expanding spectrum of problems across the life sciences. In this Review, we provide an overview of this rapidly expanding new field, summarize the most important insights gained so far and attempt to offer an outlook on future developments.

Amplified and Specific Staining of Protein Dimerization on Cell Membrane Catalyzed by Responsively Installed DNA Nanomachines for Cancer Diagnosis

In situ staining of protein dimerization on cell membrane has an important significance in accurate diagnosis during perioperative period, yet facile integration of specific recognition function and local signal conversion/amplification abilities on membrane surface remains a great challenge. Herein, a two-stage catalytic strategy is developed by installing DNA nanomachines and employing. Specifically, dual-aptamer-assisted DNA scaffold perform a "bispecific recognition-then-computing" operation and the output signal initiate a membrane-anchored biocatalysis for self-assembly of DNA catalytic converters, that is, G-quadruplex nanowire/hemin DNAzyme. Then, localized-deposition of chromogenic polydopamine is chemically catalyzed by horseradish peroxidase-mimicking DNAzyme and guided by supramolecular interactions between conjugate rigid plane of G-tetrad and polydopamine oligomer. The catalytic products exhibit nanofiber morphology with a diameter of 80-120 nm and a length of 1-10 µm, and one-to-one localize on DNA scaffold for amplified and specific staining of protein dimers. The bispecific staining leads to a higher (≈3.4-fold) signal intensity than traditional immunohistochemistry, which is beneficial for direct visualization. Moreover, an efficient discrimination ability of the bispecific staining strategy is observed in co-culture model staining. This study provides a novel catalytic method for controlling deposition of chromogens and paves a new avenue to sensitively stain of protein-protein interactions in disease diagnosis.

Recent advances in the synthesis of single-stranded DNA in vitro

Single-stranded DNA (ssDNA) is the foundation of modern biology, with wide applications in gene editing, sequencing, DNA information storage, and materials science. However, synthesizing ssDNA with high efficiency, high throughput, and low error rate in vitro remains a major challenge. Various methods have been developed for ssDNA synthesis, and some significant results have been achieved. In this review, six main methods were introduced, including solid-phase oligonucleotide synthesis, terminal deoxynucleotidyl transferase-based ssDNA synthesis, reverse transcription, primer exchange reaction, asymmetric polymerase chain reaction, and rolling circle amplification. The advantages and limitations of each method were compared, as well as illustrate their representative achievements and applications. Especially, rolling circle amplification has received significant attention, including ssDNA synthesis, assembly, and application based on recent work. Finally, the future challenges and opportunities of ssDNA synthesis were summarized and discussed. Envisioning the development of new methods and significant progress will be made in the near future with the efforts of scientists around the world.

Ultra high content analyses of circulating and tumor associated hybrid cells reveal phenotypic heterogeneity

Persistently high, worldwide mortality from cancer highlights the unresolved challenges of disease surveillance and detection that impact survival. Development of a non-invasive, blood-based biomarker would transform survival from cancer. We demonstrate the functionality of ultra-high content analyses of a newly identified population of tumor cells that are hybrids between neoplastic and immune cells in patient matched tumor and peripheral blood specimens. Using oligonucleotide conjugated antibodies (Ab-oligo) permitting cyclic immunofluorescence (cyCIF), we present analyses of phenotypes among tumor and peripheral blood hybrid cells. Interestingly, the majority of circulating hybrid cell (CHC) subpopulations were not identified in tumor-associated hybrids. These results highlight the efficacy of ultra-high content phenotypic analyses using Ab-oligo based cyCIF applied to both tumor and peripheral blood specimens. The combination of a multiplex phenotypic profiling platform that is gentle enough to analyze blood to detect and evaluate disseminated tumor cells represents a novel approach to exploring novel tumor biology and potential utility for developing the population as a blood-based biomarker in cancer.

Unveiling spatial complexity in solid tumor immune microenvironments through multiplexed imaging

Deciphering cellular components and the spatial interaction network of the tumor immune microenvironment (TIME) of solid tumors is pivotal for understanding biologically relevant cross-talks and, ultimately, advancing therapies. Multiplexed tissue imaging provides a powerful tool to elucidate spatial complexity in a holistic manner. We established and cross-validated a comprehensive immunophenotyping panel comprising over 121 markers for multiplexed tissue imaging using MACSima™ imaging cyclic staining (MICS) alongside an end-to-end analysis workflow. Applying this panel and workflow to primary cancer tissues, we characterized tumor heterogeneity, investigated potential therapeutical targets, conducted in-depth profiling of cell types and states, sub-phenotyped T cells within the TIME, and scrutinized cellular neighborhoods of diverse T cell subsets. Our findings highlight the advantage of spatial profiling, revealing immunosuppressive molecular signatures of tumor-associated myeloid cells interacting with neighboring exhausted, PD1high T cells in the TIME of hepatocellular carcinoma (HCC). This study establishes a robust framework for spatial exploration of TIMEs in solid tumors and underscores the potency of multiplexed tissue imaging and ultra-deep cell phenotyping in unraveling clinically relevant tumor components.

Multiplex protein imaging in tumour biology

Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.

Sequentially-Activated Antibodies Based on Programmable DNA Tags for Rapid Multiplexed Protein Imaging

The achievement of rapid multiplexed protein imaging is limited by the use of stimulating reagents, extensive incubating and washing steps, and the low fluorescence intensity of targets. In this study, sequentially-activated DNA tags are developed and combined them with primary antibodies using signal enhancement strategies to create sequentially-activated antibodies (SAAs). These SAAs enable rapid, wash-free sequential imaging of different protein targets. The samples are pre-processed to label all targets of interest with SAAs simultaneously, and the signal is turned ON for only one target in each stage. The sequential imaging of multiple targets is achieved through wash-free strand displacement reactions that exhibit rapid kinetics with t1/2  < 10 s in a cellular context. Remarkably, this method successfully demonstrates sequential imaging of nine different protein targets within just a few minutes. This all-in-one platform for multiplexed protein imaging holds great promise for diverse applications in immunofluorescence imaging.

Highly sensitive SERS platform for pathogen analysis by cyclic DNA nanostructure@AuNP tags and cascade primer exchange reaction

The capacity to identify small amounts of pathogens in real samples is extremely useful. Herein, we proposed a sensitive platform for detecting pathogens using cyclic DNA nanostructure@AuNP tags (CDNA) and a cascade primer exchange reaction (cPER). This platform employs wheat germ agglutinin-modified Fe3O4@Au magnetic nanoparticles (WMRs) to bind the E. coli O157:H7, and then triggers the cPER to generate branched DNA products for CDNA tag hybridization with high stability and amplified SERS signals. It can identify target pathogens as low as 1.91 CFU/mL and discriminate E. coli O157:H7 in complex samples such as water, milk, and serum, demonstrating comparable or greater sensitivity and accuracy than traditional qPCR. Moreover, the developed platform can detect low levels of E. coli O157:H7 in mouse serum, allowing the discrimination of mice with early-stage infection. Thus, this platform holds promise for food analysis and early infection diagnosis.

HCR spectral imaging: 10-plex, quantitative, high-resolution RNA and protein imaging in highly autofluorescent samples

Signal amplification based on the mechanism of hybridization chain reaction (HCR) provides a unified framework for multiplex, quantitative, high-resolution imaging of RNA and protein targets in highly autofluorescent samples. With conventional bandpass imaging, multiplexing is typically limited to four or five targets owing to the difficulty in separating signals generated by fluorophores with overlapping spectra. Spectral imaging has offered the conceptual promise of higher levels of multiplexing, but it has been challenging to realize this potential in highly autofluorescent samples, including whole-mount vertebrate embryos. Here, we demonstrate robust HCR spectral imaging with linear unmixing, enabling simultaneous imaging of ten RNA and/or protein targets in whole-mount zebrafish embryos and mouse brain sections. Further, we demonstrate that the amplified and unmixed signal in each of the ten channels is quantitative, enabling accurate and precise relative quantitation of RNA and/or protein targets with subcellular resolution, and RNA absolute quantitation with single-molecule resolution, in the anatomical context of highly autofluorescent samples.

Harmonizing the Generation and Pre-publication Stewardship of FAIR Image data

Together with the molecular knowledge of genes and proteins, biological images promise to significantly enhance the scientific understanding of complex cellular systems and to advance predictive and personalized therapeutic products for human health. For this potential to be realized, quality-assured image data must be shared among labs at a global scale to be compared, pooled, and reanalyzed, thus unleashing untold potential beyond the original purpose for which the data was generated. There are two broad sets of requirements to enable image data sharing in the life sciences. One set of requirements is articulated in the companion White Paper entitled "Enabling Global Image Data Sharing in the Life Sciences," which is published in parallel and addresses the need to build the cyberinfrastructure for sharing the digital array data (arXiv:2401.13023 [q-bio.OT], https://doi.org/10.48550/arXiv.2401.13023). In this White Paper, we detail a broad set of requirements, which involves collecting, managing, presenting, and propagating contextual information essential to assess the quality, understand the content, interpret the scientific implications, and reuse image data in the context of the experimental details. We start by providing an overview of the main lessons learned to date through international community activities, which have recently made considerable progress toward generating community standard practices for imaging Quality Control (QC) and metadata. We then provide a clear set of recommendations for amplifying this work. The driving goal is to address remaining challenges, and democratize access to common practices and tools for a spectrum of biomedical researchers, regardless of their expertise, access to resources, and geographical location.

3D Amplified Single-Cell RNA and Protein Imaging Identifies Oncogenic Transcript Subtypes in B-Cell Acute Lymphoblastic Leukemia

Simultaneous in situ detection of transcript and protein markers at the single-cell level is essential for gaining a better understanding of tumor heterogeneity and for predicting and monitoring treatment responses. However, the limited accessibility to advanced 3D imaging techniques has hindered their rapid implementation. Here, we present a 3D single-cell imaging technique, termed 3D digital rolling circle amplification (4DRCA), capable of the multiplexed and amplified simultaneous digital quantification of single-cell RNAs and proteins using standard fluorescence microscopy and off-the-shelf reagents. We generated spectrally distinguishable DNA amplicons from molecular markers through an integrative protocol combining single-cell RNA and protein assays and directly enumerated the amplicons by leveraging an open-source algorithm for 3D deconvolution with a custom-built automatic gating algorithm. With 4DRCA, we were able to simultaneously quantify surface protein markers and cytokine transcripts in T-lymphocytes. We also show that 4DRCA can distinguish BCR-ABL1 fusion transcript positive B-cell acute lymphoblastic leukemia cells with or without CD19 protein expression. The accessibility and extensibility of 4DRCA render it broadly applicable to other cell-based diagnostic workflows, enabling sensitive and accurate single-cell RNA and protein profiling.

Thermal-plex: fluidic-free, rapid sequential multiplexed imaging with DNA-encoded thermal channels

Multiplexed fluorescence imaging is typically limited to three- to five-plex on standard setups. Sequential imaging methods based on iterative labeling and imaging enable practical higher multiplexing, but generally require a complex fluidic setup with several rounds of slow buffer exchange (tens of minutes to an hour for each exchange step). We report the thermal-plex method, which removes complex and slow buffer exchange steps and provides fluidic-free, rapid sequential imaging. Thermal-plex uses simple DNA probes that are engineered to fluoresce sequentially when, and only when, activated with transient exposure to heating spikes at designated temperatures (thermal channels). Channel switching is fast (<30 s) and is achieved with a commercially available and affordable on-scope heating device. We demonstrate 15-plex RNA imaging (five thermal × three fluorescence channels) in fixed cells and retina tissues in less than 4 min, without using buffer exchange or fluidics. Thermal-plex introduces a new labeling method for efficient sequential multiplexed imaging.

Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases

Spatial multi-omic studies have emerged as a promising approach to comprehensively analyze cells in tissues, enabling the joint analysis of multiple data modalities like transcriptome, epigenome, proteome, and metabolome in parallel or even the same tissue section. This review focuses on the recent advancements in spatial multi-omics technologies, including novel data modalities and computational approaches. We discuss the advancements in low-resolution and high-resolution spatial multi-omics methods which can resolve up to 10,000 of individual molecules at subcellular level. By applying and integrating these techniques, researchers have recently gained valuable insights into the molecular circuits and mechanisms which govern cell biology along the cardiovascular disease spectrum. We provide an overview of current data analysis approaches, with a focus on data integration of multi-omic datasets, highlighting strengths and weaknesses of various computational pipelines. These tools play a crucial role in analyzing and interpreting spatial multi-omics datasets, facilitating the discovery of new findings, and enhancing translational cardiovascular research. Despite nontrivial challenges, such as the need for standardization of experimental setups, data analysis, and improved computational tools, the application of spatial multi-omics holds tremendous potential in revolutionizing our understanding of human disease processes and the identification of novel biomarkers and therapeutic targets. Exciting opportunities lie ahead for the spatial multi-omics field and will likely contribute to the advancement of personalized medicine for cardiovascular diseases.

Mosaic-PICASSO: accurate crosstalk removal for multiplex fluorescence imaging

MOTIVATION

Ultra-multiplexed fluorescence imaging has revolutionized our understanding of biological systems, enabling the simultaneous visualization and quantification of multiple targets within biological specimens. A recent breakthrough in this field is PICASSO, a mutual-information-based technique capable of demixing up to 15 fluorophores without their spectra, thereby significantly simplifying the application of ultra-multiplexed fluorescence imaging. However, this study has identified a limitation of mutual information (MI)-based techniques. They do not differentiate between spatial colocalization and spectral mixing. Consequently, MI-based demixing may incorrectly interpret spatially co-localized targets as non-colocalized, leading to overcorrection.

RESULTS

We found that selecting regions within a multiplex image with low-spatial similarity for measuring spectroscopic mixing results in more accurate demixing. This method effectively minimizes overcorrections and promises to accelerate the broader adoption of ultra-multiplex imaging.

AVAILABILITY AND IMPLEMENTATION

The codes are available at https://github.com/xing-lab-pitt/mosaic-picasso.

How spatial omics approaches can be used to map the biological impacts of stress in psychiatric disorders: a perspective, overview and technical guide

Exposure to significant levels of stress and trauma throughout life is a leading risk factor for the development of major psychiatric disorders. Despite this, we do not have a comprehensive understanding of the mechanisms that explain how stress raises psychiatric disorder risk. Stress in humans is complex and produces variable molecular outcomes depending on the stress type, timing, and duration. Deciphering how stress increases disorder risk has consequently been challenging to address with the traditional single-target experimental approaches primarily utilized to date. Importantly, the molecular processes that occur following stress are not fully understood but are needed to find novel treatment targets. Sequencing-based omics technologies, allowing for an unbiased investigation of physiological changes induced by stress, are rapidly accelerating our knowledge of the molecular sequelae of stress at a single-cell resolution. Spatial multi-omics technologies are now also emerging, allowing for simultaneous analysis of functional molecular layers, from epigenome to proteome, with anatomical context. The technology has immense potential to transform our understanding of how disorders develop, which we believe will significantly propel our understanding of how specific risk factors, such as stress, contribute to disease course. Here, we provide our perspective of how we believe these technologies will transform our understanding of the neurobiology of stress, and also provided a technical guide to assist molecular psychiatry and stress researchers who wish to implement spatial omics approaches in their own research. Finally, we identify potential future directions using multi-omics technology in stress research.

PER-CRISPR/Cas14a system-based electrochemical biosensor for the detection of ctDNA EGFR L858R

The detection of epidermal growth factor receptor (EGFR) mutation L858R in circulating tumor DNA (ctDNA) is beneficial for the clinical diagnosis and personalized therapy of non-small cell lung cancer (NSCLC). Herein, for the first time, the combination of the primer exchange reaction (PER) and clustered regularly interspaced short palindromic repeats (CRISPR) and its associated nucleases (Cas) 14a was used in electrochemical biosensor construction for the detection of ctDNA EGFR L858R. EGFR L858R, as the target, induced the isothermal amplification of the PER reaction, and then the CRISPR/Cas14a system was activated; subsequently, the substrate ssDNA-MB was cleaved and the electron on the surface of the gold electrode transferred, resulting in the fluctuation of the electrochemical redox signal on the electrode surface, whereas the electrochemical signal will be stable when EGFR L858R is absent. Therefore, the concentration of EGFR L858R can be quantified by electrochemical signal analysis. The low detection limit is 0.34 fM and the dynamic detection range is from 1 fM to 1 μM in this work. The PER-CRISPR/Cas14a electrochemical biosensor greatly improved the analytical sensitivity. In addition, this platform also exhibited excellent specificity, reproducibility, stability and good recovery. This study provides an efficient and novel strategy for the detection of ctDNA EGFR L858R, which has great potential for application in the diagnosis and treatment of NSCLC.

Decoding the tumor microenvironment with spatial technologies

Visualization of the cellular heterogeneity and spatial architecture of the tumor microenvironment (TME) is becoming increasingly important to understand mechanisms of disease progression and therapeutic response. This is particularly relevant in the era of cancer immunotherapy, in which the contexture of immune cell positioning within the tumor landscape has been proven to affect efficacy. Although single-cell technologies have mostly replaced conventional approaches to analyze specific cellular subsets within tumors, those that integrate a spatial dimension are now on the rise. In this Review, we assess the strengths and limitations of emerging spatial technologies with a focus on their applications in tumor immunology, as well as forthcoming opportunities for artificial intelligence (AI) and the value of integrating multiomics datasets to achieve a holistic picture of the TME.

Design strategies and advanced applications of primer exchange reactions in biosensing: A review

Early disease diagnosis relies on the sensitive detection and imaging of biomarkers. Signal amplification is one of the most commonly used methods to improve detection sensitivity. Primer exchange reaction (PER) is a novel signal amplification technique that has garnered attention because of its simple and sensitive features. The classical PER involves a single catalytic hairpin, which enables the attachment of custom sequences to the primer chain, generating a long repeat sequence that can bind numerous signaling molecules and achieve powerful signal amplification. Currently, numerous PER-based signal amplification strategies are available that can improve detection sensitivity and promote the development of the signal amplification field. This review focuses on the mechanism of typical PER, the diversification of PER, and PER-based biosensors for various targets. Finally, the challenges and prospects of PER development are discussed.

Giotto Suite: a multi-scale and technology-agnostic spatial multi-omics analysis ecosystem

Emerging spatial omics technologies continue to advance the molecular mapping of tissue architecture and the investigation of gene regulation and cellular crosstalk, which in turn provide new mechanistic insights into a wide range of biological processes and diseases. Such technologies provide an increasingly large amount of information content at multiple spatial scales. However, representing and harmonizing diverse spatial datasets efficiently, including combining multiple modalities or spatial scales in a scalable and flexible manner, remains a substantial challenge. Here, we present Giotto Suite, a suite of open-source software packages that underlies a fully modular and integrated spatial data analysis toolbox. At its core, Giotto Suite is centered around an innovative and technology-agnostic data framework embedded in the R software environment, which allows the representation and integration of virtually any type of spatial omics data at any spatial resolution. In addition, Giotto Suite provides both scalable and extensible end-to-end solutions for data analysis, integration, and visualization. Giotto Suite integrates molecular, morphology, spatial, and annotated feature information to create a responsive and flexible workflow for multi-scale, multi-omic data analyses, as demonstrated here by applications to several state-of-the-art spatial technologies. Furthermore, Giotto Suite builds upon interoperable interfaces and data structures that bridge the established fields of genomics and spatial data science, thereby enabling independent developers to create custom-engineered pipelines. As such, Giotto Suite creates an immersive ecosystem for spatial multi-omic data analysis.

Proximity Labeling Expansion Microscopy (PL-ExM) resolves structure of the interactome

Elucidating the spatial relationships within the protein interactome is pivotal to understanding the organization and regulation of protein-protein interactions. However, capturing the 3D architecture of the interactome presents a dual challenge: precise interactome labeling and super-resolution imaging. To bridge this gap, we present the Proximity Labeling Expansion Microscopy (PL-ExM). This innovation combines proximity labeling (PL) to spatially biotinylate interacting proteins with expansion microscopy (ExM) to increase imaging resolution by physically enlarging cells. PL-ExM unveils intricate details of the 3D interactome's spatial layout in cells using standard microscopes, including confocal and Airyscan. Multiplexing PL-ExM imaging was achieved by pairing the PL with immunofluorescence staining. These multicolor images directly visualize how interactome structures position specific proteins in the protein-protein interaction network. Furthermore, PL-ExM stands out as an assessment method to gauge the labeling radius and efficiency of different PL techniques. The accuracy of PL-ExM is validated by our proteomic results from PL mass spectrometry. Thus, PL-ExM is an accessible solution for 3D mapping of the interactome structure and an accurate tool to access PL quality.

Enablers and challenges of spatial omics, a melting pot of technologies

Spatial omics has emerged as a rapidly growing and fruitful field with hundreds of publications presenting novel methods for obtaining spatially resolved information for any omics data type on spatial scales ranging from subcellular to organismal. From a technology development perspective, spatial omics is a highly interdisciplinary field that integrates imaging and omics, spatial and molecular analyses, sequencing and mass spectrometry, and image analysis and bioinformatics. The emergence of this field has not only opened a window into spatial biology, but also created multiple novel opportunities, questions, and challenges for method developers. Here, we provide the perspective of technology developers on what makes the spatial omics field unique. After providing a brief overview of the state of the art, we discuss technological enablers and challenges and present our vision about the future applications and impact of this melting pot.