Drug-induced dedifferentiation towards drug-tolerant persister states is a common mechanism cancer cells exploit to escape therapies, hindering durable responses. How early epigenomic and transcriptomic programs coordinate to initiate these reversible transitions remains largely unexplored. Here we employ high-temporal-resolution multi-omics profiling, information-theoretic approaches, and dynamic system modeling to probe these processes in BRAF-mutant melanoma models and patient specimens. We uncover a hysteretic transition trajectory in response to oncogene inhibition and subsequent release, driven by two tightly coupled transcriptional waves that orchestrate genome-scale chromatin reconfiguration. Modeling of these waves suggests NF-κB/RelA-driven chromatin remodeling as the underlying mechanism of cell-state dedifferentiation, which we validate experimentally. We identify RelA-target genes epigenetically modulated to drive this process and define a quantitative epigenome gauge of melanoma cell-state plasticity that supports targeting epigenetic machineries to potentiate oncogene inhibition. Across additional cancer models, oxidative stress-mediated NF-κB/RelA activation emerges as a common driver of transitions into drug-tolerant persister states, revealing a central role for NF-κB axis in coupling oxidative stress to cancer progression.

A major contributor to poor sensitivity to anti-cancer kinase inhibitor therapy is drug-induced cellular adaptation, whereby remodeling of signaling and gene regulatory networks permits a drug-tolerant phenotype. Here, we resolve the scale and kinetics of critical subcellular events following oncogenic kinase inhibition and preceding cell cycle re-entry, using mass spectrometry-based phosphoproteomics and RNA sequencing (RNA-seq) to monitor the dynamics of thousands of growth- and survival-related signals over the first minutes, hours, and days of oncogenic BRAF inhibition in human melanoma cells. We observed sustained inhibition of the BRAF-ERK axis, gradual downregulation of cell cycle signaling, and three distinct, reversible phase transitions toward quiescence. Statistical inference of kinetically defined regulatory modules revealed a dominant compensatory induction of SRC family kinase (SFK) signaling, promoted in part by excess reactive oxygen species, rendering cells sensitive to co-treatment with an SFK inhibitor in vitro and in vivo, underscoring the translational potential for assessing early drug-induced adaptive signaling. A record of this paper’s transparent peer review process is included in the supplemental information.

Metabolic assays serve as pivotal tools in biomedical research, offering keen insights into cellular physiological and pathological states. While mass spectrometry (MS)-based metabolomics remains the gold standard for comprehensive, multiplexed analyses of cellular metabolites, innovative technologies are now emerging for the targeted, quantitative scrutiny of metabolites and metabolic pathways at the single-cell level. In this review, we elucidate an array of these advanced methodologies, spanning synthetic and surface chemistry techniques, imaging-based methods, and electrochemical approaches. We summarize the rationale, design principles, and practical applications for each method, and underscore the synergistic benefits of integrating single-cell metabolomics (scMet) with other single-cell omics technologies. Concluding, we identify prevailing challenges in the targeted scMet arena and offer a forward-looking commentary on future avenues and opportunities in this rapidly evolving field.

Due to the large abundance, low redox potential, and multivalent properties of calcium (Ca), Ca-ion batteries (CIBs) show promising prospects for energy storage applications. However, current research on CIBs faces the challenges of unsatisfactory cycling stability and capacity, mainly restricted by the lack of suitable electrolytes and electrode materials. Herein, we firstly developed a 3.5 m concentrated electrolyte with a calcium bis(fluorosulfonyl)imide (Ca(FSI)(2)) salt dissolved in carbonate solvents. This electrolyte significantly improved the intercalation capacity for anions in the graphite cathode and contributed to the reversible insertion of Ca2+ in the organic anode. By combining this concentrated electrolyte with the low-cost and environmentally friendly graphite cathode and organic anode, the assembled Ca-based dual-ion battery (Ca-DIB) exhibits 75.4 mAhg(-1) specific discharge capacity at 100 mAg(-1) and 84.7 % capacity retention over 350 cycles, among the best results known for CIBs.

As a novel cost‐effective, high operating voltage, and environmentally friendly energy storage device, the dual‐ion battery (DIB) has attracted much attention recently. Despite a similar energy storage mechanism at the anode side to the traditional “rocking‐chair” batteries like lithium‐ion batteries (LIBs), DIBs commonly featured intercalation of anions at the cathode materials. In addition, the electrolyte in DIBs not only acts as the ion transport medium, it also serves as the active material. As a result, the electrolyte not only determines the Coulombic efficiency and cycling life but also plays a crucial role in capacity and energy density of DIBs. Moreover, although they have similar electrochemical reactions at the anode side to LIBs, to match the fast intercalation kinetics of anions at the cathode side and take into account the quite different electrolyte systems for DIBs, rational design and optimization of anode materials still need to be considered. This review first describes the research development history and working mechanism of DIBs; after that, the research progress in electrolytes, cathode materials, and anode materials for DIBs are summarized, respectively. Finally, the prospects and future research directions of DIBs are also presented based on current understandings.

Owing to the low cost of sodium/potassium resources and similar electrochemical properties of Na+ /K+ to Li+ , sodium-ion batteries (SIBs) and potassium-ion batteries (KIBs) are regarded as promising alternatives to lithium-ion batteries (LIBs) in large-scale energy storage field. However, traditional organic liquid electrolytes bestow SIBs/KIBs with serious safety concerns. In contrast, quasi-/solid-phase electrolytes including polymer electrolytes (PEs) and inorganic solid electrolytes (ISEs) show great superiority of high safety. However, the poor processibility and relatively low ionic conductivity of Na+ and K+ ions limit the further practical applications of ISEs. PEs combine some merits of both liquid-phase electrolytes and ISEs, and present great potentials in next-generation energy storage systems. Considerable efforts have been devoted to improving their overall properties. Nevertheless, there is still a lack of an in-depth and comprehensive review to get insights into mechanisms and corresponding design strategies of PEs. Herein, the advantages of different electrolytes, particularly PEs are first minutely reviewed, and the mechanism of PEs for Na+ /K+ ion transfer is summarized. Then, representative researches and recent progresses of SIBs/KIBs based on PEs are presented. Finally, some suggestions and perspectives are put forward to provide some possible directions for the follow-up researches.

We present a chemical approach to profile fatty acid uptake in single cells. We use azide-modified analogues to probe the fatty acid influx and surface-immobilized dendrimers with dibenzocyclooctyne (DBCO) groups for detection. A competition between the fatty acid probes and BHQ2-azide quencher molecules generates fluorescence signals in a concentration-dependent manner. By integrating this method onto a microfluidics-based multiplex protein analysis platform, we resolved the relationships between fatty acid influx, oncogenic signaling activities, and cell proliferation in single glioblastoma cells. We found that p70S6K and 4EBP1 differentially correlated with fatty acid uptake. We validated that cotargeting p70S6K and fatty acid metabolism synergistically inhibited cell proliferation. Our work provided the first example of studying fatty acid metabolism in the context of protein signaling at single-cell resolution and generated new insights into cancer biology.

D-2-hydroxyglutarate (D2HG) is over-produced as an oncometabolite due to mutations in isocitrate dehydrogenases (IDHs). Accumulation of D2HG can cause the dysfunction of many enzymes and genome-wide epigenetic alterations, which can promote oncogenesis. Quantification of D2HG at single-cell resolution can help understand the phenotypic signatures of IDH-mutant cancers and identify effective therapeutics. In this study, we developed an analytical method to detect D2HG levels in single cancer cells by adapting cascade enzymatic reactions on a resazurin-based fluorescence reporter. The resazurin probe was immobilized to the sensing surface via biotin-streptavidin interaction. This surface chemistry was rationally optimized to translate the D2HG levels to sensitive fluorescence readouts efficiently. This D2HG assay demonstrated good selectivity and high sensitivity toward D2HG, and it was compatible with the previously developed single-cell barcode chip (SCBC) technology. Using the SCBC platform, we performed simultaneous single-cell profiling of D2HG, glucose uptake, and critical oncogenic signaling proteins in single IDH-mutant glioma cells. The results unveiled the complex interplays between metabolic and oncogenic signaling and led to the identification of effective combination targeted therapy against these IDH-mutant glioma cells.

The determination of individual cell trajectories through a high-dimensional cell-state space is an outstanding challenge for understanding biological changes ranging from cellular differentiation to epigenetic responses of diseased cells upon drugging. We integrate experiments and theory to determine the trajectories that single BRAFV600E mutant melanoma cancer cells take between drug-naive and drug-tolerant states. Although single-cell omics tools can yield snapshots of the cell-state landscape, the determination of individual cell trajectories through that space can be confounded by stochastic cell-state switching. We assayed for a panel of signaling, phenotypic, and metabolic regulators at points across 5 days of drug treatment to uncover a cell-state landscape with two paths connecting drug-naive and drug-tolerant states. The trajectory a given cell takes depends upon the drug-naive level of a lineage-restricted transcription factor. Each trajectory exhibits unique druggable susceptibilities, thus updating the paradigm of adaptive resistance development in an isogenic cell population.

Tumor tissue is a multifaceted ecosystem in which tumors cells are surrounded and influenced by a myriad of non-cancerous cells including immune, stromal, vascular, and other cell types.[1] Driven by stochastic genetic mutations, epigenetic modifications, and aberrant gene expression profiles, tumor cells themselves also exhibit extraordinary intratumoral heterogeneity that gives rise to malfunctioning of signaling networks and plays important roles in tumor invasion, proliferation, metastasis, as well as stromal remodeling and immune system suppression.[2, 3] This pronounced cell-to-cell variations make traditional bulk-level profiling far away from an accurate representation of the tumor ecosystem. In this regard, single-cell multi-omics tools provide a great opportunity for researchers to improve the understanding of molecular roles of tumor heterogeneity, thanks to their high spatiotemporal resolutions down to the level of single cells as well as their analytical capacity at the systems scale.[4-6] To date, a panoply of mono-omics technologies have been developed to effectively profile different molecular layers of single cells including genome, epigenome, transcriptome, proteome, metabolome, and so forth.[7-9] The quantification of these molecular signatures of cellular processes at single-cell resolution enables us to ask questions from perspectives previously unattainable and thereby facilitates our understanding of the cause and consequence of tumor heterogeneity in tumorigenesis, metastasis, and immune response. In addition, building on the development of these mono-omics technologies, tools for simultaneous measurement of multiple omic layers from the same single cells have emerged in recent years through the rational design of bio-recognition interface and the leverage of advanced biotechnologies.[10-13] Single-cell multi-omics tools allow for interrogating the links between different classes of biomolecules to resolve the interplays between distinct molecular landscapes. These integrated measurements not only offer a holistic view of cellular compositions and phenotypic states of a given population, but also enable detailed investigations into the developmental history, inter- and intracellular signal transduction, as well as the roles of significant subpopulations or rare cell types in specific physiological or pathological processes across multiple modalities. In the meantime, such measurements pose new challenges in data analysis and interpretation, as different omic layers require different suites of analytical approaches that are not always compatible. While each single cell can provide an anchor to connect different data modalities, computational frameworks that can integrate diverse sets of information from different molecular layers into harmonized atlases for effective visualization, hypothesis generation, and data interpretation are still a pressing need in the field.[14] In this special issue, we have collected current efforts that have been made in the development of novel single-cell technologies as well as their applications in immuno-oncology and cancer systems biology. Liu et al. reported a multiplexed single-cell analytical platform to quantify secreted cytokines from single cells.[15] Secreted cytokines play important roles in mediating cell-cell communications in various physiological and pathological processes. Conventional single-cell cytokine secretion assays are mainly based on the adaption of an enzyme-linked immunosorbent assay which measures single-cell secretion footprint of a given cytokine through transforming the bio-recognitions between the antibodies and cytokines into colorimetric or fluorescence signal readouts. Nevertheless, they are normally limited to three less than five cytokines that can be simultaneously detected due to the fluorescence spectral overlap. To improve the assay multiplexity without the adaption of sophisticated experiment handling or bulky equipment, a high-density polydimethylsiloxane microwell stencil was sandwiched between two antibody-coated glass slides to form periodic compartments for single-cell trapping, culturing, and cytokine secretion profiling. With 5-plexed and 3-fluorescence colors designed for detection antibodies, five or more secreted cytokines from more than 1000 single cells could be simultaneously profiled without the adaption of sophisticated fluid handling system or bulky equipment. Moreover, the authors demonstrated the utility of this single-cell technology through an investigation of secretome heterogeneity of human monocytic U937 cells in response to lipopolysaccharide and phorbol myristate acetate stimulations. The technical simplicity and high throughput make this single-cell secretion assay a unique and informative tool in dissecting cellular heterogeneity in secretome signatures. As an attempt to move forward from basic research to translational and clinical applications, Bowman et al. adapted a highly-multiplexed single-cell proteomic assay (32-plex, IsoLight automation system) to characterize the polyfunctionality of pre-infusion anti-CD19 chimeric antigen receptor (CAR)-T cell products from a cohort of patients with Non-Hodgkin's Lymphoma via quantitatively profiling 30+ cytokines secreted from CD4+ and CD8+ T cells in response to CD19 antigen-specific stimulation.[16] To better resolve the clinical relevance of the CAR-T cell polyfunctionality, a comprehensive visualization toolkit was developed by integrating 3D Uniform Manifold Approximation and Projection and t-distributed stochastic neighbor embedding into a proteomic analysis pipeline which could be further built into the IsoLight system. The combined use of commercial single-cell proteomic assays and the new bioinformatics pipeline developed in this work was envisaged to promote the understanding of underlying mechanisms in cell-based immunotherapies for improved personalized cancer medicine. Single-cell RNA-sequencing (scRNA-seq) has become one of the most widely used single-cell analytical approaches due to its high-throughput, robust performance, and good compatibility to be coupled with other single-cell profiling technologies. Dong et al. recently incorporated scRNA-seq with a rare cell enrichment approach to decipher the intratumoral heterogeneity of disseminated tumor cells (DTCs) derived from liquid biopsy samples.[17] DTCs are tumor cells spreading from primary sites to body fluids, which are considered as an important biomarker for prognostic evaluation of cancer patients because of their critical roles in cancer metastasis. However, the rarity and low viability of DTCs, as well as the co-existence of large amounts of non-cancerous cells, imposes great challenges in transcriptomic profiling of DTCs through scRNA-seq technology. To overcome this obstacle, a CD45 depletion kit was employed to remove the leukocytes in liquid biopsies sampled from malignant pleural effusions (MPE) and resultant cell samples were subsequently processed for scRNA-seq. Five main cell populations including tumor, mesothelial, monocyte, T, and B cells were identified while the DTCs could be further clustered into four subgroups with their distinct functional features characterized. These results demonstrated that the rational combination of rare cell enrichment methods with scRNA-seq technology paved a new avenue to molecular profiling of rare cell types. Most of the single-cell multi-omics tools mainly focus on the measurements of cellular biomolecules which only contain the chemical essence of cellular functions, but overlook important cellular physical information (e.g., cell mass, size, and motility). Recently, Han et al. developed a microfluidic cell trap array that can monitor the motility behavior of single hematopoietic stem/progenitor cells (HSPCs)—a clinically relevant parameter for peripheral blood stem cell transplantation.[18] Following on-chip sorting and selection, collected cells were subjected to RNA-seq to build the links between HSPC motility and stem-cell maintenance. This approach not only offers a novel strategy to decipher motility heterogeneity in HSPCs but facilitates the screening of HSPC mobilization compounds as well. Meanwhile, several reviews in this special issue attempted to portray the field of single-cell multi-omics from different perspectives. Yang et al. comprehensively summarized the principles, developments, advantages, and limitations of recently emerged single-cell proteomic technologies, along with their applications in dissecting cellular heterogeneity.[19] In parallel, Kravchenko-Balasha highlighted the implications of bulk- and single-cell proteomic assays as well as associated computational tools in unveiling and constructing the inter- and intratumoral signaling networks for personalized medicine.[20] Zhu et al. focused on the elaboration of scRNA-seq and associated technologies adapted to the studies of hematological diseases, revealing the history of single-cell omics from basic research to translational and clinical applications.[21] Peng et al. comprehensively reviewed recently developed single-cell multi-omics tools with detailed comparisons of their properties from different perspectives. Meanwhile, their applications in tumor-immune interactions were also highlighted.[22] Single-cell multi-omics is a rapidly growing field that calls for cross-disciplinary efforts ranging from chemistry, physics, biology, engineering, computational science to medicine. We greatly appreciate all contributors to this special issue and their achievements in this exciting field. We encourage more scientists to join us to leverage these powerful single-cell toolkits to gain a systems-level understanding of cellular states, interactions, and behavior in human cancers and transform the development of diagnostic and therapeutic approaches in oncology. The authors declare no conflict of interest.

Abstract Integrated proteomic and metabolic single-cell assays reveal multiple independent adaptive responses to drug tolerance in a BRAF-mutant melanoma cell line Cancers commonly develop resistance against chemotherapeutics or targeted therapies through various types of genetic or non-genetic mechanisms. Non-genetic mechanisms have been shown to occur early on and can provide a latent reservoir of cells for the emergence of various different type of mechanisms, yet very limited understanding of process were resolve main from bulk analysis. Considering the heterogeneous nature of the tumor cells, a single-cell level characterization of the process worth detailed further investigation. Using MAPK inhibition of BRAF-mutant melanomas as a model system, we resolved that cells take different paths to go from drug-sensitive to drug-resistant state. Using a microfludic-based single-cell integrated proteomic and metabolic assay, we assayed for a panel of signaling, phenotypic, and metabolic regulators at four time points during the first five days of drug treatment. Dimensional reduction of the resultant data set, coupled with information theoretic analysis, uncovered a complex cell state landscape and identified two distinct paths connecting drug-naïve and drug-tolerant states. Cells are shown to exclusively traverse one of the two pathways depending on the level of the lineage restricted transcription factor MITF in the drug-naïve cells. The two trajectories are associated with distinct signaling and metabolic susceptibilities, and are independently druggable. Our results update the paradigm of adaptive resistance development in an isogenic cell population and offer insight into the design of more effective combination therapies. Citation Format: Yapeng Su, Guideng Li, Melissa Ko, Hanjun Cheng, Ronghui Zhu, Min Xue, Lidia Robert, Raphael Levine, Antoni Ribas, Garry Nolan, Wei Wei, Sylvia Plevritis, David Baltimore, James R. Heath. Systems biology for investigating drug resistance mechanism of melanoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6585.

We resolved a mechanism connecting tumor epigenetic plasticity with non-genetic adaptive resistance to therapy, with MAPK inhibition of BRAF-mutant melanomas providing the model. These cancer cells undergo multiple, reversible drug-induced cell-state transitions, ultimately yielding a drug-resistant mesenchymal-like phenotype. A kinetic series of transcriptome and epigenome data, collected over two months of drug treatment and release, revealed changing levels of thousands of genes and extensive chromatin remodeling. However, a 3-step computational algorithm greatly simplified the interpretation of these changes, and revealed that the whole adaptive process was controlled by a gene module activated within just three days of treatment, with RelA driving chromatin remodeling to establish an epigenetic program encoding long-term phenotype changes. These findings were confirmed across several patient-derived cell lines and in melanoma patients under MAPK inhibitor treatment. Co-targeting BRAF and histone-modifying enzymes arrests adaptive transitions towards drug tolerance in epigenetically plastic melanoma cells and may be exploited therapeutically.

The determination of individual cell trajectories through a high-dimensional cell-state space is an outstanding challenge, with relevance towards understanding biological changes ranging from cellular differentiation to epigenetic (adaptive) responses of diseased cells to drugging. We report on a combined experimental and theoretic method for determining the trajectories that specific highly plastic BRAF V600E mutant patient-derived melanoma cancer cells take between drug-naïve and drug-tolerant states. Recent studies have implicated non-genetic, fast-acting resistance mechanisms are activated in these cells following BRAF inhibition. While single-cell highly multiplex omics tools can yield snapshots of the cell state space landscape sampled at any given time point, individual cell trajectories must be inferred from a kinetic series of snapshots, and that inference can be confounded by stochastic cell state switching. Using a microfludic-based single-cell integrated proteomic and metabolic assay, we assayed for a panel of signaling, phenotypic, and metabolic regulators at four time points during the first five days of drug treatment. Dimensional reduction of the resultant data set, coupled with information theoretic analysis, uncovered a complex cell state landscape and identified two distinct paths connecting drug-naïve and drug-tolerant states. Cells are shown to exclusively traverse one of the two pathways depending on the level of the lineage restricted transcription factor MITF in the drug-naïve cells. The two trajectories are associated with distinct signaling and metabolic susceptibilities, and are independently druggable. Our results update the paradigm of adaptive resistance development in an isogenic cell population and offer insight into the design of more effective combination therapies.

Understanding the real-time correlation between chemical patterns and neural processes is critical for deciphering brain function. Voltammetry has enabled this task but with a number of challenges for current-based electrolysis in vivo. Herein, we report galvanic redox potentiometry (GRP) potentially as a universal strategy for in vivo monitoring of neurochemicals, with ascorbic acid (AA) as a typical example. The GRP sensor is constructed on a self-driven galvanic cell configuration, where AA is spontaneously oxidized at the indicating single-walled carbon nanotube-modified carbon fiber electrode (SWNT-CFE), while oxygen reduced at the laccase-modified reference CFE (Lac-CFE). At thermodynamic equilibrium, open-circuit potential (OCP) can be a linear indicator of the concentration of AA. The resulting sensor shows a high selectivity to AA dynamics in the presence of coexisting electroactive neurochemicals, which is mainly determined by the driving force for the cell reaction, as suggested by principal investigation. Sensing sensitivity of this OCP-based GRP method is not affected by nonspecific protein adsorption and electrode fouling. Moreover, a micropipette compartment of the reference electrode is designed to suppress mass crossover and prevent disturbance to oxygen reduction through confinement effect. The in vivo application of the GRP sensor is illustrated by measuring the basal level of cortical AA in live rat brain (230 ± 40 μM) and its dynamics during ischemia/reperfusion. The GRP concept is demonstrated as a prominent method for in vivo, real-time, quantitative analysis of brain neurochemistry.

An analytical method is described for profiling lactate production in single cells via the use of coupled enzyme reactions on surface-grafted resazurin molecules. The immobilization of the redox-labile probes was achieved through chemical modifications on resazurin, followed by bio-orthogonal click reactions. The lactate detection was demonstrated to be sensitive and specific. The method was incorporated into a single-cell barcode chip for simultaneous quantification of aerobic glycolysis activities and oncogenic signaling phosphoproteins in cancer. The interplay between glycolysis and oncogenic signaling activities was interrogated on a glioblastoma cell line. Results revealed a drug-induced oncogenic signaling reliance accompanying shifted metabolic paradigms. A drug combination that exploits this induced reliance exhibited synergistic effects in growth inhibition.

Over the past two decades, there has been increasing focus on ascorbic acid (AA) due to its anti-oxidant and neuroprotective properties as well as its neuromodulating capability. Conventional analytical methods for selective in vivo monitoring of AA mainly involve complex procedures, which lower the temporal resolution and throughput of data gathering. Moreover, analytical methods for selective real-time monitoring of AA exocytosis at a single-cell level is still lacking. The lack of effective methods for AA detection in the central nervous system (CNS) has rendered difficulties in better understanding the roles of AA in brain function. AA is, in itself, electrochemically active, and thereby rationally tailoring the structure of an electrode/solution interface would offer an effective approach to selective electrochemical measurements in the CNS. Guided by this, electrochemical methods have been recently established for AA detection by combining selective electrochemical oxidation of AA at functionalized electrodes with microelectrode techniques and with in vivo microdialysis. This review mainly focuses on recent updates on in vivo detection of AA by modulating the electron transfer of AA to achieve the selectivity for its detection in the CNS, an environment with high chemical complexity. Additionally, the practical implications of the methods in selective and sensitive monitoring the dynamics of AA in different brain functions are also reviewed. (C) 2018 Elsevier B.V. All rights reserved.

We present here a novel chemical method to continuously analyze intracellular AKT signaling activities at single-cell resolution, without genetic manipulations. A pair of cyclic peptide-based fluorescent probes were developed to recognize the phosphorylated Ser474 site and a distal epitope on AKT. A Förster resonance energy transfer signal is generated upon concurrent binding of the two probes onto the same AKT protein, which is contingent upon the Ser474 phosphorylation. Intracellular delivery of the probes enabled dynamic measurements of the AKT signaling activities. We further implemented this detection strategy on a microwell single-cell platform, and interrogated the AKT signaling dynamics in a human glioblastoma cell line. We resolved unique features of the single-cell signaling dynamics following different perturbations. Our study provided the first example of monitoring the temporal evolution of cellular signaling heterogeneities and unveiled biological information that was inaccessible to other methods.

Metal-organic framework (MOF) nanosheets are a class of two-dimensional (2D) porous and crystalline materials that hold promise for catalysis and biodetection. Although 2D MOF nanosheets have been utilized for in vitro assays, ways of engineering them into diagnostic tools for live animals are much less explored. In this work, a series of MOF nanosheets are successfully engineered into a highly sensitive and selective diagnostic platform for in vivo monitoring of heparin (Hep) activity. The iron-porphyrin derivative is selected as a ligand to synthesize a series of archetypical MOF nanosheets with intrinsic heme-like catalytic sites, mimicking peroxidase. Hep-specific AG73 peptides as recognition motifs are physically adsorbed onto MOF nanosheets, blocking active sites from nonspecific substrate-catalyst interaction. Because of the highly specific interaction between Hep and AG73, the activity of AG73-MOF nanosheets is restored upon the binding of Hep, but not Hep analogues and other endogenous biomolecules. Furthermore, by taking advantages of biocompatibility and diagnostic property enabled by AG73-MOF nanosheets, the elimination process of Hep in live rats is quantitatively monitored by coupling with microdialysis technology. This work expands the biomedical applications of 2D MOF nanomaterials and provides access to a promising in vivo diagnostic platform.

Gold nanoparticles (AuNPs) with simultaneous plasmonic and biocatalytic properties provide a promising approach to developing versatile bioassays. However, the combination of AuNPs' intrinsic enzyme-mimicking properties with their surface-enhanced Raman scattering (SERS) activities has yet to be explored. Here we designed a peroxidase-mimicking nanozyme by in situ growing AuNPs into a highly porous and thermally stable metal organic framework called MIL-101. The obtained AuNP5@MIL-101 nanozymes acted as peroxidase mimics to oxidize Raman-inactive reporter leucomalachite green into the active malachite green (MG) with hydrogen peroxide and simultaneously as the SERS substrates to enhance the Raman signals of the as-produced MG. We then assembled glucose oxidase (GOx) and lactate oxidase (LOx) onto AuNPs@MIL-101 to form AuNPs@MIL-101@GOx and AuNPs@MIL-101@LOx integrative nanozymes for in vitro detection of glucose and lactate via SERS. Moreover, the integrative nanozymes were further explored for monitoring the change of glucose and lactate in living brains, which are associated with ischemic stroke. The integrative nanozymes were then used to evaluate the therapeutic efficacy of potential drugs (such as astaxanthin for alleviating cerebral ischemic injuries) in living rats. They were also employed to determine glucose and lactate metabolism in tumors. This study not only demonstrated the great promise of combining AuNPs' multiple functionalities for versatile bioassays but also provided an interesting approach to designing nanozymes for biomedical and catalytic applications.