Multiplex single-molecule interaction profiling of DNA-barcoded proteins

Rapid discovery of high-affinity antibodies via massively parallel sequencing, ribosome display and affinity screening

Developing therapeutic antibodies is laborious and costly. Here we report a method for antibody discovery that leverages the Illumina HiSeq platform to, within 3 days, screen in the order of 108 antibody-antigen interactions. The method, which we named 'deep screening', involves the clustering and sequencing of antibody libraries, the conversion of the DNA clusters into complementary RNA clusters covalently linked to the instrument's flow-cell surface on the same location, the in situ translation of the clusters into antibodies tethered via ribosome display, and their screening via fluorescently labelled antigens. By using deep screening, we discovered low-nanomolar nanobodies to a model antigen using 4 × 106 unique variants from yeast-display-enriched libraries, and high-picomolar single-chain antibody fragment leads for human interleukin-7 directly from unselected synthetic repertoires. We also leveraged deep screening of a library of 2.4 × 105 sequences of the third complementarity-determining region of the heavy chain of an anti-human epidermal growth factor receptor 2 (HER2) antibody as input for a large language model that generated new single-chain antibody fragment sequences with higher affinity for HER2 than those in the original library.

Recent advances in generative biology for biotherapeutic discovery

Generative biology combines artificial intelligence (AI), advanced life sciences technologies, and automation to revolutionize the process of designing novel biomolecules with prescribed properties, giving drug discoverers the ability to escape the limitations of biology during the design of next-generation protein therapeutics. Significant hurdles remain, namely: (i) the inherently complex nature of drug discovery, (ii) the bewildering number of promising computational and experimental techniques that have emerged in the past several years, and (iii) the limited availability of relevant protein sequence-function data for drug-like molecules. There is a need to focus on computational methods that will be most practically effective for protein drug discovery and on building experimental platforms to generate the data most appropriate for these methods. Here, we discuss recent advances in computational and experimental life sciences that are most crucial for impacting the pace and success of protein drug discovery.

Simultaneous Imaging of Multiple miRNAs in Mitochondria Controlled by Fluorescently Encoded Upconversion Optical Switches for Drug Resistance Studies

Mitochondrial miRNAs (mitomiRs) are essential regulators of biological processes by influencing mitochondrial gene expression and function. To comprehensively understand related pathological processes and treatments, simultaneous imaging of multiple mitomiRs is crucial. In this study, we present a technique that enables simultaneous monitoring of multiple mitomiRs in living cells using a near-infrared (NIR) photoactivated controlled detection probe (PD-mFleU) with a fluorescence-encoded error correction module and a nonsupervised machine learning data-processing algorithm. This method allows controlled sensing imaging of mitomiRs with a DNA reporter probe that can be activated by NIR light after targeted mitochondrial localization. Multilayer upconversion nanoparticles (UCNPs) are used for encoding probes and error correction. Additionally, the density-based spatial clustering of applications with the noise (DBSCAN) algorithm is used to process and analyze the image. Using this technique, we achieved rapid in situ imaging of the abnormal expression of three mitomiRs (miR-149, miR-590, and miR-671) related to mt-ND1 in drug-resistant cells. Furthermore, upregulating the three mitomiRs simultaneously efficiently reverted drug-resistant cells to sensitive cells. Our study provides an analytical strategy for multiplex imaging of mitomiRs in living cells with potential clinical applications.

Polony gels enable amplifiable DNA stamping and spatial transcriptomics of chronic pain

Methods for acquiring spatially resolved omics data from complex tissues use barcoded DNA arrays of low- to sub-micrometer features to achieve single-cell resolution. However, fabricating such arrays (randomly assembled beads, DNA nanoballs, or clusters) requires sequencing barcodes in each array, limiting cost-effectiveness and throughput. Here, we describe a vastly scalable stamping method to fabricate polony gels, arrays of ∼1-micrometer clonal DNA clusters bearing unique barcodes. By enabling repeatable enzymatic replication of barcode-patterned gels, this method, compared with the sequencing-dependent array fabrication, reduced cost by at least 35-fold and time to approximately 7 h. The gel stamping was implemented with a simple robotic arm and off-the-shelf reagents. We leveraged the resolution and RNA capture efficiency of polony gels to develop Pixel-seq, a single-cell spatial transcriptomic assay, and applied it to map the mouse parabrachial nucleus and analyze changes in neuropathic pain-regulated transcriptomes and cell-cell communication after nerve ligation.

Biomacromolecule-Assisted Screening for Reaction Discovery and Catalyst Optimization

Reaction discovery and catalyst screening lie at the heart of synthetic organic chemistry. While there are efforts at de novo catalyst design using computation/artificial intelligence, at its core, synthetic chemistry is an experimental science. This review overviews biomacromolecule-assisted screening methods and the follow-on elaboration of chemistry so discovered. All three types of biomacromolecules discussed─enzymes, antibodies, and nucleic acids─have been used as "sensors" to provide a readout on product chirality exploiting their native chirality. Enzymatic sensing methods yield both UV-spectrophotometric and visible, colorimetric readouts. Antibody sensors provide direct fluorescent readout upon analyte binding in some cases or provide for cat-ELISA (Enzyme-Linked ImmunoSorbent Assay)-type readouts. DNA biomacromolecule-assisted screening allows for templation to facilitate reaction discovery, driving bimolecular reactions into a pseudo-unimolecular format. In addition, the ability to use DNA-encoded libraries permits the barcoding of reactants. All three types of biomacromolecule-based screens afford high sensitivity and selectivity. Among the chemical transformations discovered by enzymatic screening methods are the first Ni(0)-mediated asymmetric allylic amination and a new thiocyanopalladation/carbocyclization transformation in which both C-SCN and C-C bonds are fashioned sequentially. Cat-ELISA screening has identified new classes of sydnone-alkyne cycloadditions, and DNA-encoded screening has been exploited to uncover interesting oxidative Pd-mediated amido-alkyne/alkene coupling reactions.

Unbiased discovery of autoantibodies associated with severe COVID-19 via genome-scale self-assembled DNA-barcoded protein libraries

Pathogenic autoreactive antibodies that may be associated with life-threatening coronavirus disease 2019 (COVID-19) remain to be identified. Here, we show that self-assembled genome-scale libraries of full-length proteins covalently coupled to unique DNA barcodes for analysis by sequencing can be used for the unbiased identification of autoreactive antibodies in plasma samples. By screening 11,076 DNA-barcoded proteins expressed from a sequence-verified human ORFeome library, the method, which we named MIPSA (for Molecular Indexing of Proteins by Self-Assembly), allowed us to detect circulating neutralizing type-I and type-III interferon (IFN) autoantibodies in five plasma samples from 55 patients with life-threatening COVID-19. In addition to identifying neutralizing type-I IFN-α and IFN-ω autoantibodies and other previously known autoreactive antibodies in patient plasma, MIPSA enabled the detection of as yet unidentified neutralizing type-III anti-IFN-λ3 autoantibodies that were not seen in healthy plasma samples or in convalescent plasma from ten non-hospitalized individuals with COVID-19. The low cost and simple workflow of MIPSA will facilitate unbiased high-throughput analyses of protein-antibody, protein-protein and protein-small-molecule interactions.

Mechanism-Based Strategy for Optimizing HaloTag Protein Labeling

HaloTag labeling technology has introduced unrivaled potential in protein chemistry and molecular and cellular biology. A wide variety of ligands have been developed to meet the specific needs of diverse applications, but only a single protein tag, DhaAHT, is routinely used for their incorporation. Following a systematic kinetic and computational analysis of different reporters, a tetramethylrhodamine- and three 4-stilbazolium-based fluorescent ligands, we showed that the mechanism of incorporating different ligands depends both on the binding step and the efficiency of the chemical reaction. By studying the different haloalkane dehalogenases DhaA, LinB, and DmmA, we found that the architecture of the access tunnels is critical for the kinetics of both steps and the ligand specificity. We showed that highly efficient labeling with specific ligands is achievable with natural dehalogenases. We propose a simple protocol for selecting the optimal protein tag for a specific ligand from the wide pool of available enzymes with diverse access tunnel architectures. The application of this protocol eliminates the need for expensive and laborious protein engineering.

Spatially Resolved, Error-Robust Multiplexed MicroRNA Profiling in Single Living Cells

Simultaneous imaging of multiple microRNAs (miRNAs) in individual living cells is challenging due to the lack of spectrally distinct encoded fluorophores and non-cytotoxic methods. We describe a multiplexed error-robust combinatorial fluorescent label-encoding method, termed fluorophores encoded error-corrected labels (FluoELs), enabling multiplexed miRNA imaging in living cells with error-correcting capability. The FluoELs comprise proportional dual fluorophores for encoding and a constant quantitative single fluorophore for error-corrected quantification. Both are embedded in 260 nm core-shell silica nanoparticles modified with molecular beacon detection probes. The FluoELs are low cytotoxic and could accurately quantify and spatially resolve nine breast-cancer-related miRNAs and evaluate their coordination. The FluoELs enabled a single-cell analysis platform to evaluate miRNA expression profiles and the molecular mechanisms underlying miRNA-associated diseases.

Antigen identification and high-throughput interaction mapping by reprogramming viral entry

Deciphering immune recognition is critical for understanding a broad range of diseases and for the development of effective vaccines and immunotherapies. Efforts to do so are limited by a lack of technologies capable of simultaneously capturing the complexity of adaptive immunoreceptor repertoires and the landscape of potential antigens. To address this, we present receptor-antigen pairing by targeted retroviruses, which combines viral pseudotyping and molecular engineering approaches to enable one-pot library-on-library interaction screens by displaying antigens on the surface of lentiviruses and encoding their identity in the viral genome. Antigen-specific viral infection of cell lines expressing human T or B cell receptors allows readout of both antigen and receptor identities via single-cell sequencing. The resulting system is modular, scalable and compatible with any cell type. These techniques provide a suite of tools for targeted viral entry, molecular engineering and interaction screens with broad potential applications.

An open source toolkit for repurposing Illumina sequencing systems as versatile fluidics and imaging platforms

Fluorescence microscopy is a key method in the life sciences. State of the art -omics methods combine fluorescence microscopy with complex protocols to visualize tens to thousands of features in each of millions of pixels across samples. These -omics methods require precise control of temperature, reagent application, and image acquisition parameters during iterative chemistry and imaging cycles conducted over the course of days or weeks. Automated execution of such methods enables robust and reproducible data generation. However, few commercial solutions exist for temperature controlled, fluidics coupled fluorescence imaging, and implementation of bespoke instrumentation requires specialized engineering expertise. Here we present PySeq2500, an open source Python code base and flow cell design that converts the Illumina HiSeq 2500 instrument, comprising an epifluorescence microscope with integrated fluidics, into an open platform for programmable applications without need for specialized engineering or software development expertise. Customizable PySeq2500 protocols enable experimental designs involving simultaneous 4-channel image acquisition, temperature control, reagent exchange, stable positioning, and sample integrity over extended experiments. To demonstrate accessible automation of complex, multi-day workflows, we use the PySeq2500 system for unattended execution of iterative indirect immunofluorescence imaging (4i). Our automated 4i method uses off-the-shelf antibodies over multiple cycles of staining, imaging, and antibody elution to build highly multiplexed maps of cell types and pathological features in mouse and postmortem human spinal cord sections. Given the widespread availability of HiSeq 2500 platforms and the simplicity of the modifications required to repurpose these systems, PySeq2500 enables non-specialists to develop and implement state of the art fluidics coupled imaging methods in a widely available benchtop system.

Combinatorial Approaches for Efficient Design of Photoswitchable Protein-Protein Interactions as In Vivo Actuators

Light switchable two-component protein dimerization systems offer versatile manipulation and dissection of cellular events in living systems. Over the past 20 years, the field has been driven by the discovery of photoreceptor-based interaction systems, the engineering of light-actuatable binder proteins, and the development of photoactivatable compounds as dimerization inducers. This perspective is to categorize mechanisms and design approaches of these dimerization systems, compare their advantages and limitations, and bridge them to emerging applications. Our goal is to identify new opportunities in combinatorial protein design that can address current engineering challenges and expand in vivo applications.

Revealing protein-protein interactions at the transcriptome scale by sequencing

We describe PROPER-seq (protein-protein interaction sequencing) to map protein-protein interactions (PPIs) en masse. PROPER-seq first converts transcriptomes of input cells into RNA-barcoded protein libraries, in which all interacting protein pairs are captured through nucleotide barcode ligation, recorded as chimeric DNA sequences, and decoded at once by sequencing and mapping. We applied PROPER-seq to human embryonic kidney cells, T lymphocytes, and endothelial cells and identified 210,518 human PPIs (collected in the PROPER v.1.0 database). Among these, 1,365 and 2,480 PPIs are supported by published co-immunoprecipitation (coIP) and affinity purification-mass spectrometry (AP-MS) data, 17,638 PPIs are predicted by the prePPI algorithm without previous experimental validation, and 100 PPIs overlap human synthetic lethal gene pairs. In addition, four previously uncharacterized interaction partners with poly(ADP-ribose) polymerase 1 (PARP1) (a critical protein in DNA repair) known as XPO1, MATR3, IPO5, and LEO1 are validated in vivo. PROPER-seq presents a time-effective technology to map PPIs at the transcriptome scale, and PROPER v.1.0 provides a rich resource for studying PPIs.

Systems Approaches to Unravel T Cell Function and Therapeutic Potential in Autoimmune Disease

Producing Ag-specific immune responses constrained to target tissues or cells that can be engaged or disengaged at will is predicated on understanding the network of genes governing immune cell function, defining the rules underlying Ag specificity, and synthesizing the tools to engineer them. The successes and limitations of chimeric Ag receptor (CAR) T cells emphasize this goal, and advances in high-throughput sequencing, large-scale genomic screens, single-cell profiling, and genetic modification are providing the necessary data to bring it to fruition-including a broader application into the treatment of autoimmune diseases. In this review, we delve into the implementation of these developments, survey the relevant works, and propose a framework for generating the next generation of synthetic T cells informed by the principles learned from these systems approaches.

Directed evolution of orthogonal RNA-RBP pairs through library-vs-library in vitro selection

RNA-binding proteins (RBPs) and their RNA ligands play many critical roles in gene regulation and RNA processing in cells. They are also useful for various applications in cell biology and synthetic biology. However, re-engineering novel and orthogonal RNA-RBP pairs from natural components remains challenging while such synthetic RNA-RBP pairs could significantly expand the RNA-RBP toolbox for various applications. Here, we report a novel library-vs-library in vitro selection strategy based on Phage Display coupled with Systematic Evolution of Ligands by EXponential enrichment (PD-SELEX). Starting with pools of 1.1 × 1012 unique RNA sequences and 4.0 × 108 unique phage-displayed L7Ae-scaffold (LS) proteins, we selected RNA-RBP complexes through a two-step affinity purification process. After six rounds of library-vs-library selection, the selected RNAs and LS proteins were analyzed by next-generation sequencing (NGS). Further deconvolution of the enriched RNA and LS protein sequences revealed two synthetic and orthogonal RNA-RBP pairs that exhibit picomolar affinity and >4000-fold selectivity.

Logic gates in nanoscale based on interaction of thiolated DNA with AuNPs and strand displacement

Both DNA molecules and AuNPs are promising materials in Nanotechnology due to their special properties and also their interaction between each other. In this article, we present a series of methods via combining the DNA strand displacement reaction with the interaction of thiolated DNA and AuNPs to construct several logic gates, such as NOT, YES, NAND, XOR gates. The results demonstrate the computing power in nanoscale molecules and reactions.

Parallel optically detected magnetic resonance spectrometer for dozens of single nitrogen-vacancy centers using laser-spot lattice

We develop a parallel optically detected magnetic resonance (PODMR) spectrometer to address, manipulate, and read out an array of single nitrogen-vacancy (NV) centers in diamond in parallel. In this spectrometer, we use an array of micro-lenses to generate a 20 × 20 laser-spot lattice (LSL) on the objective focal plane and then align the LSL with an array of single NV centers. The quantum states of NV centers are manipulated by a uniform microwave field from a Ω-shape coplanar coil. As an experimental demonstration, we observe 80 NV centers in the field of view. Among them, magnetic resonance (MR) spectra and Rabi oscillations of 18 NV centers along the external magnetic field are measured in parallel. These results can be directly used to realize parallel quantum sensing and multiple times speedup compared with the confocal technique. Regarding the nanoscale MR technique, PODMR will be crucial for a high throughput single molecular MR spectrum and imaging.

Neutralizing IFNL3 Autoantibodies in Severe COVID-19 Identified Using Molecular Indexing of Proteins by Self-Assembly

Unbiased antibody profiling can identify the targets of an immune reaction. A number of likely pathogenic autoreactive antibodies have been associated with life-threatening SARS-CoV-2 infection; yet, many additional autoantibodies likely remain unknown. Here we present Molecular Indexing of Proteins by Self Assembly (MIPSA), a technique that produces ORFeome-scale libraries of proteins covalently coupled to uniquely identifying DNA barcodes for analysis by sequencing. We used MIPSA to profile circulating autoantibodies from 55 patients with severe COVID-19 against 11,076 DNA-barcoded proteins of the human ORFeome library. MIPSA identified previously known autoreactivities, and also detected undescribed neutralizing interferon lambda 3 (IFN-λ3) autoantibodies. At-risk individuals with anti- IFN-λ3 antibodies may benefit from interferon supplementation therapies, such as those currently undergoing clinical evaluation.

In vivo mRNA display enables large-scale proteomics by next generation sequencing

Large-scale proteomic methods are essential for the functional characterization of proteins in their native cellular context. However, proteomics has lagged far behind genomic approaches in scalability, standardization, and cost. Here, we introduce in vivo mRNA display, a technology that converts a variety of proteomics applications into a DNA sequencing problem. In vivo-expressed proteins are coupled with their encoding messenger RNAs (mRNAs) via a high-affinity stem-loop RNA binding domain interaction, enabling high-throughput identification of proteins with high sensitivity and specificity by next generation DNA sequencing. We have generated a high-coverage in vivo mRNA display library of the Saccharomyces cerevisiae proteome and demonstrated its potential for characterizing subcellular localization and interactions of proteins expressed in their native cellular context. In vivo mRNA display libraries promise to circumvent the limitations of mass spectrometry-based proteomics and leverage the exponentially improving cost and throughput of DNA sequencing to systematically characterize native functional proteomes.

HaloTag-based conjugation of proteins to barcoding-oligonucleotides

Highly sensitive protein quantification enables the detection of a small number of protein molecules that serve as markers/triggers for various biological phenomena, such as cancer. Here, we describe the development of a highly sensitive protein quantification system called HaloTag protein barcoding. The method involves covalent linking of a target protein to a unique molecule counting oligonucleotide at a 1:1 conjugation ratio based on an azido-cycloalkyne click reaction. The sensitivity of the HaloTag-based barcoding was remarkably higher than that of a conventional luciferase assay. The HaloTag system was successfully validated by analyzing a set of protein-protein interactions, with the identification rate of 44% protein interactions between positive reference pairs reported in the literature. Desmoglein 3, the target antigen of pemphigus vulgaris, an IgG-mediated autoimmune blistering disease, was used in a HaloTag protein barcode assay to detect the anti-DSG3 antibody. The dynamic range of the assay was over 104-times wider than that of a conventional enzyme-linked immunosorbent assay (ELISA). The technology was used to detect anti-DSG3 antibody in patient samples with much higher sensitivity compared to conventional ELISA. Our detection system, with its superior sensitivity, enables earlier detection of diseases possibly allowing the initiation of care/treatment at an early disease stage.

Generation and Selection of a Panel of Pan-Filovirus Single-Chain Antibodies using Cell-Free Ribosome Display

Filoviruses, which include ebolaviruses and marburgvirus, can cause outbreaks of highly lethal hemorrhagic fever. This disease causes significant morbidity and mortality in humans and non-human primates, with human fatality rates reaching 90% during some outbreaks. Currently, there is lack of licensed vaccines or antivirals for these viruses. Since early symptoms of filovirus infection mimic more common diseases, there is a strong unmet public health and biodefense need for broad-spectrum filovirus rapid diagnostics. We have generated a panel of mouse single-chain Fv-antibodies (scFvs) to filovirus glycoproteins (GPs) using cell-free ribosome display and determined their cross-reactivity profiles to all known filovirus species. Two scFvs (4-2 and 22-1) were able to detect all known Ebolavirus and Marburgvirus species. This is the first report on ribosome display scFvs that can detect a broad set of filovirus GPs, which demonstrates the potential for use in diagnostics.

Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library

Protein dimerization events that occur only in the presence of a small-molecule ligand enable the development of small-molecule biosensors for the dissection and manipulation of biological pathways. Currently, only a limited number of chemically induced dimerization (CID) systems exist and engineering new ones with desired sensitivity and selectivity for specific small-molecule ligands remains a challenge in the field of protein engineering. We here describe a high throughput screening method, combinatorial binders-enabled selection of CID (COMBINES-CID), for the de novo engineering of CID systems applicable to a large variety of ligands. This method uses the two-step selection of a phage-displayed combinatorial nanobody library to obtain 1) "anchor binders" that first bind to a ligand of interest and then 2) "dimerization binders" that only bind to anchor binder-ligand complexes. To select anchor binders, a combinatorial library of over 10⁹ complementarity-determining region (CDR)-randomized nanobodies is screened with a biotinylated ligand and hits are validated with the unlabeled ligand by bio-layer interferometry (BLI). To obtain dimerization binders, the nanobody library is screened with anchor binder-ligand complexes as targets for positive screening and the unbound anchor binders for negative screening. COMBINES-CID is broadly applicable to select CID binders with other immunoglobulin, non-immunoglobulin, or computationally designed scaffolds to create biosensors for in vitro and in vivo detection of drugs, metabolites, signaling molecules, etc.

Protein-Nucleic Acid Conjugation with Sterol Linkers Using Hedgehog Autoprocessing

Hedgehog (Hh) precursor proteins contain an autoprocessing domain called HhC whose native function is protein cleavage and C-terminal glycine sterylation. The transformation catalyzed by HhC occurs in cis from a precursor protein and exhibits wide tolerance toward both sterol and protein substrates. Here, we repurpose HhC as a 1:1 protein-nucleic acid ligase, with the sterol serving as a molecular linker. A procedure is described for preparing HhC-active sterylated DNA, called steramers, using aqueous compatible chemistry and commercial reagents. Steramers have KM values of 7-11 μM and reaction t1/2 values of ∼10 min. Modularity of the HhC/steramer method is demonstrated using four different proteins along with structured and unstructured sterylated nucleic acids. The resulting protein-DNA conjugates retain the native solution properties and biochemical function. Unlike self-tagging domains, HhC does not remain fused to the conjugate; rather, enzymatic activity is mechanistically coupled to conjugate release. That unique feature of HhC, coupled with efficient kinetics and substrate tolerance, may ease access and open new applications for these suprabiological chimeras.

Unified rational protein engineering with sequence-based deep representation learning

Rational protein engineering requires a holistic understanding of protein function. Here, we apply deep learning to unlabeled amino-acid sequences to distill the fundamental features of a protein into a statistical representation that is semantically rich and structurally, evolutionarily and biophysically grounded. We show that the simplest models built on top of this unified representation (UniRep) are broadly applicable and generalize to unseen regions of sequence space. Our data-driven approach predicts the stability of natural and de novo designed proteins, and the quantitative function of molecularly diverse mutants, competitively with the state-of-the-art methods. UniRep further enables two orders of magnitude efficiency improvement in a protein engineering task. UniRep is a versatile summary of fundamental protein features that can be applied across protein engineering informatics.

Domain swapping of complementarity-determining region in nanobodies produced by Pichia pastoris

Easy preparation of chimeric nanobodies with various scaffolds is important for customizing abilities of nanobodies toward practical utilization. To accomplish high-throughput production of various nanobodies, utilization of microbes is an attractive option. In the present study, various chimeric nanobodies were prepared using the methylotrophic yeast Pichia pastoris. We designed chimeric nanobodies with complementarity-determining regions (CDRs) against green fluorescent protein (GFP) or cluster of differentiation 4 (CD4) based on the scaffold of GFP-nanobody. FLAG-tagged chimeric nanobodies were prepared by one-step cloning and produced using P. pastoris. Secreted chimeric nanobodies were purified from the culture media of P. pastoris transformants. Relative binding abilities of purified chimeric nanobodies to GFP and CD4 was tested using a BIACORE T-200. P. pastoris successfully produced a high yield of FLAG-tagged chimeric nanobodies. FLAG-tagged GFP- and CD4-nanobodies were shown to specifically bind to GFP and CD4, respectively. Chimeric nanobodies, in which the CDR2 or 3 of GFP-nanobody was replaced with CDRs of CD4-nanobody, acquired the ability to bind to CD4 without binding to GFP. These results demonstrate successful production of functional chimeric nanobodies using P. pastoris. These results also suggest that swapping of CDRs, especially CDRs 2 or 3, potentially enables a novel method of creating nanobodies.

Barcoded DNA nanostructures for the multiplexed profiling of subcellular protein distribution

Massively parallel DNA sequencing is established, yet high-throughput protein profiling remains challenging. Here, we report a barcoding approach that leverages the combinatorial sequence content and the configurational programmability of DNA nanostructures for high-throughput multiplexed profiling of the subcellular expression and distribution of proteins in whole cells. The barcodes are formed by in situ hybridization of tetrahedral DNA nanostructures and short DNA sequences conjugated with protein-targeting antibodies, and by nanostructure-assisted ligation (either enzymatic or chemical) of the nanostructures and exogenous DNA sequences bound to nanoparticles of different sizes (which cause these localization sequences to differentially distribute across subcellular compartments). Compared with linear DNA barcoding, the nanostructured barcodes enhance the signal by more than 100-fold. By implementing the barcoding approach on a microfluidic device for the analysis of rare patient samples, we show that molecular subtypes of breast cancer can be accurately classified and that subcellular spatial markers of disease aggressiveness can be identified.

Large-Scale, Quantitative Protein Assays on a High-Throughput DNA Sequencing Chip

High-throughput DNA sequencing techniques have enabled diverse approaches for linking DNA sequence to biochemical function. In contrast, assays of protein function have substantial limitations in terms of throughput, automation, and widespread availability. We have adapted an Illumina high-throughput sequencing chip to display an immense diversity of ribosomally translated proteins and peptides and then carried out fluorescence-based functional assays directly on this flow cell, demonstrating that a single, widely available high-throughput platform can perform both sequencing-by-synthesis and protein assays. We quantified the binding of the M2 anti-FLAG antibody to a library of 1.3 × 10⁴ variant FLAG peptides, exploring non-additive effects of combinations of mutations and discovering a "superFLAG" epitope variant. We also measured the enzymatic activity of 1.56 × 10⁵ molecular variants of full-length human O⁶-alkylguanine-DNA alkyltransferase (SNAP-tag). This comprehensive corpus of catalytic rates revealed amino acid interaction networks and cooperativity, linked positive cooperativity to structural proximity, and revealed ubiquitous positively cooperative interactions with histidine residues.

Porous Hydrogel-Encapsulated Photonic Barcodes for Multiplex Detection of Cardiovascular Biomarkers

Early detection of cardiac troponin I (cTnI), B-type natriuretic peptide (BNP), and myoglobin (Myo) is essential for the diagnosis of acute myocardial infarction (AMI) and heart failure (HF). We designed a porous hydrogel-encapsulated photonic crystal (PhC) barcode-based suspension array for multiple cardiovascular marker detection. The hybrid hydrogel was composed of polyethylene glycol diacrylate (PEGDA) and gelatin, resulting in a porous and hydrophilic scaffold which ensured stability of the PhC in aqueous solutions. The encapsulated PhC barcodes had stable diffraction peaks for the corresponding markers. Using a sandwich format, the proposed suspension array was used for simultaneous multiplex detection of cardiovascular biomarkers in a single tube. The immunoassay results we tested on cTnI, BNP, and Myo could be assayed in the ranges of 0.01 to 1000 ng/mL, 0.1 to 10 000 pg/mL, and 1 to 10 000 ng/mL with limits of detection of 0.009 ng/mL, 0.084 pg/mL, and 0.68 ng/mL at 3σ, respectively. This method also showed acceptable accuracy and repeated detection, and the results were consistent with the results of conventional clinical methods for detecting actual clinical samples. Therefore, suspension arrays based on hydrogel-encapsulated PhC barcodes are highly promising for AMI diagnosis.

Engineered peptide barcodes for in-depth analyses of binding protein libraries

Binding protein generation typically relies on laborious screening cascades that process candidate molecules individually. We have developed NestLink, a binder selection and identification technology able to biophysically characterize thousands of library members at once without the need to handle individual clones at any stage of the process. NestLink uses genetically encoded barcoding peptides termed flycodes, which were designed for maximal detectability by mass spectrometry and support accurate deep sequencing. We demonstrate NestLink's capacity to overcome the current limitations of binder-generation methods in three applications. First, we show that hundreds of binder candidates can be simultaneously ranked according to kinetic parameters. Next, we demonstrate deep mining of a nanobody immune repertoire for membrane protein binders, carried out entirely in solution without target immobilization. Finally, we identify rare binders against an integral membrane protein directly in the cellular environment of a human pathogen. NestLink opens avenues for the selection of tailored binder characteristics directly in tissues or in living organisms.

Why the c-Fos/c-Jun complex is extremely conserved: An in vitro evolution exploration by combining cDNA display and proximity ligation

Transcriptional regulation involves a series of sophisticated protein-protein and protein-DNA interactions (PPI and PDI). Some transcriptional complexes, such as c-Fos/c-Jun and their binding DNA fragments, have been conserved over the past one billion years. Considering the thermodynamic principle for transcriptional complex formation, we hypothesized that the c-Fos/c-Jun complex may represent a thermodynamic summit in the evolutionary space. To test this, we invented a new method, termed One-Pot-seq, which combines cDNA display and proximity ligation to analyse PPI/PDI complexes simultaneously. We found that the wild-type c-Fos/c-Jun complex is indeed the most thermodynamically stable relative to various mutants of c-Fos/c-Jun and binding DNA fragments. Our method also provides a universal approach to detect transcriptional complexes and explore transcriptional regulation mechanisms.

Nucleic Acid-Barcoding Technologies: Converting DNA Sequencing into a Broad-Spectrum Molecular Counter

The emergence of high-throughput DNA sequencing technologies sparked a revolution in the field of genomics that has rippled into many branches of the life and physical sciences. The remarkable sensitivity, specificity, throughput, and multiplexing capacity that are inherent to parallel DNA sequencing have since motivated its use as a broad-spectrum molecular counter. A key aspect of extrapolating DNA sequencing to non-traditional applications is the need to append nucleic-acid barcodes to entities of interest. In this review, we describe the chemical and biochemical approaches that have enabled nucleic-acid barcoding of proteinaceous and non-proteinaceous materials and provide examples of downstream technologies that have been made possible by DNA-encoded molecules. As commercially available high-throughput sequencers were first released less than 15 years ago, we believe related applications will continue to mature and close by proposing new frontiers to support this assertion.

Ribosome display and selection of single-chain variable fragments effectively inhibit growth and progression of microspheres in vitro and in vivo

Distinguishing the surface markers of cancer stem cells (CSCs) is a useful method for early diagnosis and treatment of tumors, as CSCs may participate in tumorigenesis and metastasis by migrating into the circulatory system. However, the potential targets of CSCs are expressed at low levels in the natural state and are always changing. Thus, dynamic screening has been reported to be an effective measure for exploring CSC markers. In recent years, diverse single-chain variable fragments (scFvs) have been widely used in immunotherapy. In this study, we determined that the scFvs, screened using RD, had a high affinity to microspheres and could inhibit their progression. We also observed that the selected scFvs underwent evolution in vitro, and antitumor-associated proteins were successfully expressed. Combined with chemotherapy, the scFvs had a synergistic effect on the inhibition of the microspheres' progression in vitro and in vivo, which could be ascribed to their high affinity for stem-like cells and the inhibition of the microspheres' collective behaviors. In addition, proteins inhibiting CD44⁺ /CD24⁺ and MAPK were involved. Our data indicated that dynamic screening of the scFvs in a natural state was of great significance in the inhibition of the microspheres in vitro and in vivo.

Protein Interactomics by Two-Hybrid Methods

Comprehensive identification of direct, physical interactions between biological macromolecules, such as protein-protein, protein-DNA, and protein-RNA interactions, is critical for our understanding of the function of gene products as well as the global organization and interworkings of various molecular machines within the cell. The accurate and comprehensive detection of direct interactions, however, remains a huge challenge due to the inherent structural complexity arising from various post-transcriptional and translational modifications coupled with huge heterogeneity in concentration, affinity, and subcellular location differences existing for any interacting molecules. This has created a need for developing multiple orthogonal and complementary assays for detecting various types of biological interactions. In this introduction, we discuss the methods developed for measuring different types of molecular interactions with an emphasis on direct protein-protein interactions, critical issues for generating high-quality interactome datasets, and the insights into biological networks and human diseases that current interaction mapping efforts provide. Further, we will discuss what future might lie ahead for the continued evolution of two-hybrid methods and the role of interactomics for expanding the advancement of biomedical science.

High-throughput characterization of protein-protein interactions by reprogramming yeast mating

High-throughput methods for screening protein-protein interactions enable the rapid characterization of engineered binding proteins and interaction networks. While existing approaches are powerful, none allow quantitative library-on-library characterization of protein interactions in a modifiable extracellular environment. Here, we show that sexual agglutination of Saccharomyces cerevisiae can be reprogrammed to link interaction strength with mating efficiency using synthetic agglutination (SynAg). Validation of SynAg with 89 previously characterized interactions shows a log-linear relationship between mating efficiency and protein binding strength for interactions with K_ds ranging from below 500 pM to above 300 μM. Using induced chromosomal translocation to pair barcodes representing binding proteins, thousands of distinct interactions can be screened in a single pot. We demonstrate the ability to characterize protein interaction networks in a modifiable environment by introducing a soluble peptide that selectively disrupts a subset of interactions in a representative network by up to 800-fold. SynAg enables the high-throughput, quantitative characterization of protein-protein interaction networks in a fully defined extracellular environment at a library-on-library scale.

Deep learning for single-molecule science

Exploring and making predictions based on single-molecule data can be challenging, not only due to the sheer size of the datasets, but also because a priori knowledge about the signal characteristics is typically limited and poor signal-to-noise ratio. For example, hypothesis-driven data exploration, informed by an expectation of the signal characteristics, can lead to interpretation bias or loss of information. Equally, even when the different data categories are known, e.g., the four bases in DNA sequencing, it is often difficult to know how to make best use of the available information content. The latest developments in machine learning (ML), so-called deep learning (DL) offer interesting, new avenues to address such challenges. In some applications, such as speech and image recognition, DL has been able to outperform conventional ML strategies and even human performance. However, to date DL has not been applied much in single-molecule science, presumably in part because relatively little is known about the 'internal workings' of such DL tools within single-molecule science as a field. In this Tutorial, we make an attempt to illustrate in a step-by-step guide how one of those, a convolutional neural network (CNN), may be used for base calling in DNA sequencing applications. We compare it with a SVM as a more conventional ML method, and discuss some of the strengths and weaknesses of the approach. In particular, a 'deep' neural network has many features of a 'black box', which has important implications on how we look at and interpret data.

An in vitro tag-and-modify protein sample generation method for single-molecule fluorescence resonance energy transfer

Biomolecular systems exhibit many dynamic and biologically relevant properties, such as conformational fluctuations, multistep catalysis, transient interactions, folding, and allosteric structural transitions. These properties are challenging to detect and engineer using standard ensemble-based techniques. To address this drawback, single-molecule methods offer a way to access conformational distributions, transient states, and asynchronous dynamics inaccessible to these standard techniques. Fluorescence-based single-molecule approaches are parallelizable and compatible with multiplexed detection; to date, however, they have remained limited to serial screens of small protein libraries. This stems from the current absence of methods for generating either individual dual-labeled protein samples at high throughputs or protein libraries compatible with multiplexed screening platforms. Here, we demonstrate that by combining purified and reconstituted in vitro translation, quantitative unnatural amino acid incorporation via AUG codon reassignment, and copper-catalyzed azide-alkyne cycloaddition, we can overcome these challenges for target proteins that are, or can be, methionine-depleted. We present an in vitro parallelizable approach that does not require laborious target-specific purification to generate dual-labeled proteins and ribosome-nascent chain libraries suitable for single-molecule FRET-based conformational phenotyping. We demonstrate the power of this approach by tracking the effects of mutations, C-terminal extensions, and ribosomal tethering on the structure and stability of three protein model systems: barnase, spectrin, and T4 lysozyme. Importantly, dual-labeled ribosome-nascent chain libraries enable single-molecule co-localization of genotypes with phenotypes, are well suited for multiplexed single-molecule screening of protein libraries, and should enable the in vitro directed evolution of proteins with designer single-molecule conformational phenotypes of interest.

Multiplexed Nucleic Acid Hybridization Assays Using Single-FRET-Pair Distance-Tuning

Multiplexed photoluminescence (PL) detection plays an important role in chemical and biological sensing. Here, it is shown that time-gated (TG) detection of a single terbium-donor-based Förster resonance energy transfer (FRET) pair can be used to selectively quantify low nanomolar concentrations of multiple DNAs or microRNAs in a single sample. This study demonstrates the applicability of single-TG-FRET-pair multiplexing for molecular (Tb-to-dye) and nanoparticle (Tb-to-quantum-dot) biosensing. Both systems use acceptor-sensitization and donor-quenching for quantifying biomolecular recognition and modification of the donor-acceptor distance for tuning the PL decays. TG intensity detection provides extremely low background noise and a quick and simple one-step assay format. Single-TG-FRET-pair multiplexing can be combined with spectral and spatial resolution, paving the way for biosensing with unprecedented high-order multiplexing capabilities.

Time, space, and disorder in the expanding proteome universe

Proteins are highly dynamic entities. Their myriad functions require specific structures, but proteins' dynamic nature ranges all the way from the local mobility of their amino acid constituents to mobility within and well beyond single cells. A truly comprehensive view of the dynamic structural proteome includes: (i) alternative sequences, (ii) alternative conformations, (iii) alternative interactions with a range of biomolecules, (iv) cellular localizations, (v) alternative behaviors in different cell types. While these aspects have traditionally been explored one protein at a time, we highlight recently emerging global approaches that accelerate comprehensive insights into these facets of the dynamic nature of protein structure. Computational tools that integrate and expand on multiple orthogonal data types promise to enable the transition from a disjointed list of static snapshots to a structurally explicit understanding of the dynamics of cellular mechanisms.

Single-molecule fluorescence resonance energy transfer in molecular biology

Single-molecule fluorescence resonance energy transfer (smFRET) is a powerful technique for studying the conformation dynamics and interactions of individual biomolecules. In this review, we describe the concept and principle of smFRET, illustrate general instrumentation and microscopy settings for experiments, and discuss the methods and algorithms for data analysis. Subsequently, we review applications of smFRET in protein conformational changes, ion channel open-close properties, receptor-ligand interactions, nucleic acid structure regulation, vesicle fusion, and force induced conformational dynamics. Finally, we discuss the main limitations of smFRET in molecular biology.

Bulked sample analysis in genetics, genomics and crop improvement

Biological assay has been based on analysis of all individuals collected from sample populations. Bulked sample analysis (BSA), which works with selected and pooled individuals, has been extensively used in gene mapping through bulked segregant analysis with biparental populations, mapping by sequencing with major gene mutants and pooled genomewide association study using extreme variants. Compared to conventional entire population analysis, BSA significantly reduces the scale and cost by simplifying the procedure. The bulks can be built by selection of extremes or representative samples from any populations and all types of segregants and variants that represent wide ranges of phenotypic variation for the target trait. Methods and procedures for sampling, bulking and multiplexing are described. The samples can be analysed using individual markers, microarrays and high-throughput sequencing at all levels of DNA, RNA and protein. The power of BSA is affected by population size, selection of extreme individuals, sequencing strategies, genetic architecture of the trait and marker density. BSA will facilitate plant breeding through development of diagnostic and constitutive markers, agronomic genomics, marker-assisted selection and selective phenotyping. Applications of BSA in genetics, genomics and crop improvement are discussed with their future perspectives.

Crosslinking of DNA-linked ligands to target proteins for enrichment from DNA-encoded libraries

Achieving sufficient enrichment of ligands from DNA-encoded libraries for detection can be difficult, particularly for low affinity ligands within highly complex libraries. To address this challenge, we present an approach for crosslinking DNA-linked ligands to target proteins using electrophilic or photoreactive groups. The approach involves the teathering of a ssDNA oligonucleotide to a DNA-encoded molecule to enable attachment of a reactive group post-synthetically via DNA hybridization. Crosslinking traps ligand-protein complexes while in solution and allows for stringent washing conditions to be applied in the subsequent purification. Five reactive groups (tosyl, NHS ester, sulfonyl fluoride, phenyl azide, and diazirine) were tested for crosslinking efficiency and specificity with three DNA-linked ligands to their target proteins. In a model selection, crosslinking resulted in improved enrichment of both high and a low affinity ligands in comparison to a selection with a solid-phase immobilized protein.

Homogeneous Entropy-Driven Amplified Detection of Biomolecular Interactions

While a range of artificial biochemical circuits is likely to play a significant role in biological engineering, one of the challenges in the field is the design of circuits that can transduce between biomolecule classes (e.g., moving beyond nucleic acid only circuits). Herein, we design a transduction mechanism whereby a protein signal is transduced into an amplified nucleic acid output using DNA nanotechnology. In this system, a protein is recognized by nucleic acid bound recognition elements to form a catalytic complex that drives a hybridization/displacement reaction on a multicomponent nucleic acid substrate, releasing multiple target single-stranded oligonucleotides in an amplified fashion. Amplification power and simple one-pot reaction conditions lead us to apply the scheme in an assay format, achieving homogeneous and rapid (∼10 min) analyte detection that is also robust (operable in whole blood and plasma). In addition, we demonstrate the assay in a microfluidic digital assay format leading to improved quantification and sensitivity approaching single-molecule levels. The present scheme we believe will have a significant impact on a range of applications from fundamental molecular interaction studies to design of artificial circuits in vivo to high-throughput, multiplexed assays for screening or point-of-care diagnostics.

Cell-free ribosome display and selection of antibodies on arrayed antigens

In vitro display technology is a powerful tool for discovery and optimisation of novel antibodies. With increasing demands on various binding molecules in proteomics studies, techniques for a large-scale generation of antibodies or antibody fragments are needed. Here, we describe a novel method for parallel generation of different antibody fragments (scFv) by integrating cell-free ribosome display with array technology. We have demonstrated the procedure by successfully isolating scFv antibodies specific to 16 different cancer biomarkers via a single process. Our results provide proof of principle for multiple production of various scFv antibodies simultaneously.

Femtosecond UV-laser pulses to unveil protein-protein interactions in living cells

A hallmark to decipher bioprocesses is to characterize protein-protein interactions in living cells. To do this, the development of innovative methodologies, which do not alter proteins and their natural environment, is particularly needed. Here, we report a method (LUCK, Laser UV Cross-linKing) to in vivo cross-link proteins by UV-laser irradiation of living cells. Upon irradiation of HeLa cells under controlled conditions, cross-linked products of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were detected, whose yield was found to be a linear function of the total irradiation energy. We demonstrated that stable dimers of GAPDH were formed through intersubunit cross-linking, as also observed when the pure protein was irradiated by UV-laser in vitro. We proposed a defined patch of aromatic residues located at the enzyme subunit interface as the cross-linking sites involved in dimer formation. Hence, by this technique, UV-laser is able to photofix protein surfaces that come in direct contact. Due to the ultra-short time scale of UV-laser-induced cross-linking, this technique could be extended to weld even transient protein interactions in their native context.