The World Health Organization has declared the outbreak of a novel coronavirus (SARS-CoV-2 or 2019-nCoV) as a global pandemic. However, the mechanisms behind the coronavirus infection are not yet fully understood, nor are there any targeted treatments or vaccines. In this study, we identified high-binding-affinity aptamers targeting SARS-CoV-2 RBD, using an ACE2 competition-based aptamer selection strategy and a machine learning screening algorithm. The K d values of the optimized CoV2-RBD-1C and CoV2-RBD-4C aptamers against RBD were 5.8 nM and 19.9 nM, respectively. Simulated interaction modeling, along with competitive experiments, suggests that two aptamers may have partially identical binding sites at ACE2 on SARS-CoV-2 RBD. These aptamers present an opportunity for generating new probes for recognition of SARS-CoV-2 and could provide assistance in the diagnosis and treatment of SARS-CoV-2 while providing a new tool for in-depth study of the mechanisms behind the coronavirus infection.

Immunotherapy has revolutionized cancer treatment, but its efficacy is severely hindered by the lack of effective predictors. Herein, we developed a homogeneous, low‐volume, efficient, and sensitive exosomal programmed death‐ligand 1 (PD‐L1, a type of transmembrane protein) quantitation method for cancer diagnosis and immunotherapy response prediction (HOLMES‐ExoPD‐L1). The method combines a newly evolved aptamer that efficiently binds to PD‐L1 with less hindrance by antigen glycosylation than antibody, and homogeneous thermophoresis with a rapid binding kinetic. As a result, HOLMES‐ExoPD‐L1 is higher in sensitivity, more rapid in reaction time, and easier to operate than existing enzyme‐linked immunosorbent assay (ELISA)‐based methods. As a consequence of an outstanding improvement of sensitivity, the level of circulating exosomal PD‐L1 detected by HOLMES‐ExoPD‐L1 can effectively distinguish cancer patients from healthy volunteers, and for the first time was found to correlate positively with the metastasis of adenocarcinoma. Overall, HOLMES‐ExoPD‐L1 brings a fresh approach to exosomal PD‐L1 quantitation, offering unprecedented potential for early cancer diagnosis and immunotherapy response prediction.

The ubiquitous biomembrane interface, with its dynamic lateral fluidity, allows membrane-bound components to rearrange and localize for high-affinity multivalent ligand–receptor interactions in diverse life activities. Inspired by this, we herein engineered a fluidic multivalent nanointerface by decorating a microfluidic chip with aptamer-functionalized leukocyte membrane nanovesicles for high-performance isolation of circulating tumor cells (CTCs). This fluidic biomimetic nanointerface with active recruitment-binding afforded significant affinity enhancement by 4 orders of magnitude, exhibiting 7-fold higher capture efficiency compared to a monovalent aptamer functionalized-chip in blood. Meanwhile, this soft nanointerface inherited the biological benefits of a natural biomembrane, minimizing background blood cell adsorption and maintaining excellent CTC viability (97.6%). Using the chip, CTCs were successfully detected in all cancer patient samples tested (17/17), suggesting the high potential of this fluidity-enhanced multivalent binding strategy in clinical applications. We expect this bioengineered interface strategy will lead to the design of innovative biomimetic platforms in the biomedical field by leveraging natural cell–cell interaction with a natural biomaterial.

The World Health Organization has declared the outbreak of a novel coronavirus (SARS-CoV-2 or 2019-nCoV) as a global pandemic. However, the mechanisms behind the coronavirus infection are not yet fully understand, nor are there any targeted treatments or vaccines. In this study, we identified high-binding-affinity aptamers targeting SARS-CoV-2 RBD, using an ACE2 competition-based aptamer selection strategy and a machine learning screening algorithm. The K_d values of the optimized CoV2-RBD-1C and <a>CoV2-RBD-</a>4C aptamers against RBD were 5.8 nM and 19.9 nM, respectively. Simulated interaction modeling, along with competitive with experiments, suggests that two aptamers may have partially identical binding sites at ACE2 on SARS-CoV-2 RBD. These aptamers present an opportunity for generating new probes for recognition of SARS-CoV-2, and could provide assistance in the diagnosis and treatment of SARS-CoV-2 while providing a new tool for in-depth study of the mechanisms behind the coronavirus infection.

Microfluidic chips with nano-scale structures have shown great potential, but the fabrication and cost issues restrict their application. Herein, we propose a conceptually new "DNA nanolithography in a microfluidic chip" by using sub-10 nm three-dimensional DNA structures (TDNs) as frameworks with a pendant aptamer at the top vertex (ApTDN-Chip). The nano-scale framework ensures that the aptamer is in a highly ordered upright orientation, avoiding the undesired orientation or crowding effects caused by conventional microfluidic interface fabrication processes. Compared with a monovalent aptamer modified chip, the capture efficiency of ApTDN-Chip was enhanced nearly 60 % due to the highly precise dimension and rigid framework of TDNs. In addition, the scaffolds make DNase I more accessible to the aptamer with up to 83 % release efficiency and 91 % cell viability, which is fully compatible with downstream molecular analysis. Overall, this strategy provides a novel perspective on engineering nano-scaffolds to achieve a more ordered nanotopography of microfluidic chips.

Molecular recognition ligands are of great significance in many fields, but our ability to develop new recognition molecules remains to be expanded. Here, we developed a Sequential Multidimensional Analysis algoRiThm for aptamer discovery (SMART-Aptamer) from high-throughput sequencing (HTS) data of SELEX libraries based on multilevel structure analysis and unsupervised machine learning to discover nucleic acid recognition ligands with high accuracy and efficiency. We validated SMART-Aptamer with three sets of HTS data from screening pools against hESCs, EpCAM, and CSV. High affinity aptamers for all three targets were successfully obtained, and the results revealed that SMART-Aptamer is able to pick out high affinity aptamers with low false positive and negative rates. With the advantages of accuracy, efficiency, and robustness, SMART-Aptamer represents a paradigm-shift strategy for the discovery of binding ligands for a variety of biomedical applications.

ScRNA-seq has the ability to reveal accurate and precise cell types and states. Existing scRNA-seq platforms utilize bead-based technologies uniquely barcoding individual cells, facing practical challenges for precious samples with limited cell number. Here, we present a scRNA-seq platform, named Paired-seq, with high cells/beads utilization efficiency, cell-free RNAs removal capability, high gene detection ability and low cost. We utilize the differential flow resistance principle to achieve single cell/barcoded bead pairing with high cell utilization efficiency (95%). The integration of valves and pumps enables the complete removal of cellfree RNAs, efficient cell lysis and mRNA capture, achieving highest mRNA detection accuracy (R = 0.955) and comparable sensitivity. Lower reaction volume and higher mRNA capture and barcoding efficiency significantly reduce the cost of reagents and sequencing. The singlecell expression profile of mES and drug treated cells reveal cell heterogeneity, demonstrating the enormous potential of Paired-seq for cell biology, developmental biology and precision medicine.

Current techniques for studying gut microbiota are unable to answer some important microbiology questions, like how different bacteria grow and divide in the gut. We propose a method that integrates the use of sequential d-amino acid–based in vivo metabolic labeling with fluorescence in situ hybridization (FISH), for characterizing the growth and division patterns of gut bacteria. After sequentially administering two d-amino acid–based probes containing different fluorophores to mice by gavage, the resulting dual-labeled peptidoglycans provide temporal information on cell wall synthesis of gut bacteria. Following taxonomic identification with FISH probes, the growth and division patterns of the corresponding bacterial taxa, including species that cannot be cultured separately in vitro, are revealed. Our method offers a facile yet powerful tool for investigating the in vivo growth dynamics of the bacterial gut microbiota, which will advance our understanding of bacterial cytology and facilitate elucidation of the basic microbiology of this gut “dark matter.”