Engineering ClpS for selective and enhanced N-terminal amino acid binding

Real-time detection of 20 amino acids and discrimination of pathologically relevant peptides with functionalized nanopore

Precise identification and quantification of amino acids is crucial for many biological applications. Here we report a copper(II)-functionalized Mycobacterium smegmatis porin A (MspA) nanopore with the N91H substitution, which enables direct identification of all 20 proteinogenic amino acids when combined with a machine-learning algorithm. The validation accuracy reaches 99.1%, with 30.9% signal recovery. The feasibility of ultrasensitive quantification of amino acids was also demonstrated at the nanomolar range. Furthermore, the capability of this system for real-time analyses of two representative post-translational modifications (PTMs), one unnatural amino acid and ten synthetic peptides using exopeptidases, including clinically relevant peptides associated with Alzheimer's disease and cancer neoantigens, was demonstrated. Notably, our strategy successfully distinguishes peptides with only one amino acid difference from the hydrolysate and provides the possibility to infer the peptide sequence.

Contributions from ClpS surface residues in modulating N-terminal peptide binding and their implications for NAAB development

Numerous technologies are currently in development for use in next-generation protein sequencing platforms. A notable published approach employs fluorescently-tagged binding proteins to identity the N-terminus of immobilized peptides, in-between rounds of digestion. This approach makes use of N-terminal amino acid binder (NAAB) proteins, which would identify amino acids by chemical and shape complementarity. One source of NAABs is the ClpS protein family, which serve to recruit proteins to bacterial proteosomes based on the identity of the N-terminal amino acid. In this study, a Thermosynechococcus vestitus (also known as Thermosynechococcus elongatus) ClpS2 protein was used as the starting point for direct evolution of an NAAB with affinity and specificity for N-terminal leucine. Enriched variants were analyzed and shown to improve the interaction between the ClpS surface and the peptide chain, without increasing promiscuity. Interestingly, interactions were found that were unanticipated which favor different charged residues located at position 5 from the N-terminus of a target peptide.

Single-molecule fluorescence methods for protein biomarker analysis

Proteins have been considered key building blocks of life. In particular, the protein content of an organism and a cell offers significant information for the in-depth understanding of the disease and biological processes. Single-molecule protein detection/sequencing tools will revolutionize clinical (proteomics) research, offering ultrasensitivity for low-abundance biomarker (protein) detection, which is important for the realization of early-stage disease diagnosis and single-cell proteomics. This improved detection/measurement capability delivers new sets of techniques to explore new frontiers and address important challenges in various interdisciplinary areas including nanostructured materials, molecular medicine, molecular biology, and chemistry. Importantly, fluorescence-based methods have emerged as indispensable tools for single protein detection/sequencing studies, providing a higher signal-to-noise ratio (SNR). Improvements in fluorescent dyes/probes and detector capabilities coupled with advanced (image) analysis strategies have fueled current developments for single protein biomarker detections. For example, in comparison to conventional ELISA (i.e., based on ensembled measurements), single-molecule fluorescence detection is more sensitive, faster, and more accurate with reduced background, high-throughput, and so on. In comparison to MS sequencing, fluorescence-based single-molecule protein sequencing can achieve the sequencing of peptides themselves with higher sensitivity. This review summarizes various typical single-molecule detection technologies including their methodology (modes of operation), detection limits, advantages and drawbacks, and current challenges with recent examples. We describe the fluorescence-based single-molecule protein sequencing/detection based on five kinds of technologies such as fluorosequencing, N-terminal amino acid binder, nanopore light sensing, and DNA nanotechnology. Finally, we present our perspective for developing high-performance fluorescence-based sequencing/detection techniques.

Artificial intelligence-based multi-omics analysis fuels cancer precision medicine

With biotechnological advancements, innovative omics technologies are constantly emerging that have enabled researchers to access multi-layer information from the genome, epigenome, transcriptome, proteome, metabolome, and more. A wealth of omics technologies, including bulk and single-cell omics approaches, have empowered to characterize different molecular layers at unprecedented scale and resolution, providing a holistic view of tumor behavior. Multi-omics analysis allows systematic interrogation of various molecular information at each biological layer while posing tricky challenges regarding how to extract valuable insights from the exponentially increasing amount of multi-omics data. Therefore, efficient algorithms are needed to reduce the dimensionality of the data while simultaneously dissecting the mysteries behind the complex biological processes of cancer. Artificial intelligence has demonstrated the ability to analyze complementary multi-modal data streams within the oncology realm. The coincident development of multi-omics technologies and artificial intelligence algorithms has fuelled the development of cancer precision medicine. Here, we present state-of-the-art omics technologies and outline a roadmap of multi-omics integration analysis using an artificial intelligence strategy. The advances made using artificial intelligence-based multi-omics approaches are described, especially concerning early cancer screening, diagnosis, response assessment, and prognosis prediction. Finally, we discuss the challenges faced in multi-omics analysis, along with tentative future trends in this field. With the increasing application of artificial intelligence in multi-omics analysis, we anticipate a shifting paradigm in precision medicine becoming driven by artificial intelligence-based multi-omics technologies.

Real-time dynamic single-molecule protein sequencing on an integrated semiconductor device

Studies of the proteome would benefit greatly from methods to directly sequence and digitally quantify proteins and detect posttranslational modifications with single-molecule sensitivity. Here, we demonstrate single-molecule protein sequencing using a dynamic approach in which single peptides are probed in real time by a mixture of dye-labeled N-terminal amino acid recognizers and simultaneously cleaved by aminopeptidases. We annotate amino acids and identify the peptide sequence by measuring fluorescence intensity, lifetime, and binding kinetics on an integrated semiconductor chip. Our results demonstrate the kinetic principles that allow recognizers to identify multiple amino acids in an information-rich manner that enables discrimination of single amino acid substitutions and posttranslational modifications. With further development, we anticipate that this approach will offer a sensitive, scalable, and accessible platform for single-molecule proteomic studies and applications.

Protein Sequencing, One Molecule at a Time

Despite tremendous gains over the past decade, methods for characterizing proteins have generally lagged behind those for nucleic acids, which are characterized by extremely high sensitivity, dynamic range, and throughput. However, the ability to directly characterize proteins at nucleic acid levels would address critical biological challenges such as more sensitive medical diagnostics, deeper protein quantification, large-scale measurement, and discovery of alternate protein isoforms and modifications and would open new paths to single-cell proteomics. In response to this need, there has been a push to radically improve protein sequencing technologies by taking inspiration from high-throughput nucleic acid sequencing, with a particular focus on developing practical methods for single-molecule protein sequencing (SMPS). SMPS technologies fall generally into three categories: sequencing by degradation (e.g., mass spectrometry or fluorosequencing), sequencing by transit (e.g., nanopores or quantum tunneling), and sequencing by affinity (as in DNA hybridization-based approaches). We describe these diverse approaches, which range from those that are already experimentally well-supported to the merely speculative, in this nascent field striving to reformulate proteomics.

Label-Free Optical Analysis of Biomolecules in Solid-State Nanopores: Toward Single-Molecule Protein Sequencing

Sequence identification of peptides and proteins is central to proteomics. Protein sequencing is mainly conducted by insensitive mass spectroscopy because proteins cannot be amplified, which hampers applications such as single-cell proteomics and precision medicine. The commercial success of portable nanopore sequencers for single DNA molecules has inspired extensive research and development of single-molecule techniques for protein sequencing. Among them, three challenges remain: (1) discrimination of the 20 amino acids as building blocks of proteins; (2) unfolding proteins; and (3) controlling the motion of proteins with nonuniformly charged sequences. In this context, the emergence of label-free optical analysis techniques for single amino acids and peptides by solid-state nanopores shows promise for addressing the first challenge. In this Perspective, we first discuss the current challenges of single-molecule fluorescence detection and nanopore resistive pulse sensing in a protein sequencing. Then, label-free optical methods are described to show how they address the single-amino-acid identification within single peptides. They include localized surface plasmon resonance detection and surface-enhanced Raman spectroscopy on plasmonic nanopores. Notably, we report new data to show the ability of plasmon-enhanced Raman scattering to record and discriminate the 20 amino acids at a single-molecule level. In addition, we discuss briefly the manipulation of molecule translocation and liquid flow in plasmonic nanopores for controlling molecule movement to allow high-resolution reading of protein sequences. We envision that a combination of Raman spectroscopy with plasmonic nanopores can succeed in single-molecule protein sequencing in a label-free way.

The emerging landscape of single-molecule protein sequencing technologies

Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell profiling of proteomes is not yet established. Here we describe new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell profiling. These technologies will in turn facilitate biological discovery and open new avenues for ultrasensitive disease diagnostics.

Structure, function, and substrates of Clp AAA+ protease systems in cyanobacteria, plastids, and apicoplasts: A comparative analysis

ATPases Associated with diverse cellular Activities (AAA+) are a superfamily of proteins that typically assemble into hexameric rings. These proteins contain AAA+ domains with two canonical motifs (Walker A and B) that bind and hydrolyze ATP, allowing them to perform a wide variety of different functions. For example, AAA+ proteins play a prominent role in cellular proteostasis by controlling biogenesis, folding, trafficking, and degradation of proteins present within the cell. Several central proteolytic systems (e.g., Clp, Deg, FtsH, Lon, 26S proteasome) use AAA+ domains or AAA+ proteins to unfold protein substrates (using energy from ATP hydrolysis) to make them accessible for degradation. This allows AAA+ protease systems to degrade aggregates and large proteins, as well as smaller proteins, and feed them as linearized molecules into a protease chamber. This review provides an up-to-date and a comparative overview of the essential Clp AAA+ protease systems in Cyanobacteria (e.g., Synechocystis spp), plastids of photosynthetic eukaryotes (e.g., Arabidopsis, Chlamydomonas), and apicoplasts in the nonphotosynthetic apicomplexan pathogen Plasmodium falciparum. Recent progress and breakthroughs in identifying Clp protease structures, substrates, substrate adaptors (e.g., NblA/B, ClpS, ClpF), and degrons are highlighted. We comment on the physiological importance of Clp activity, including plastid biogenesis, proteostasis, the chloroplast Protein Unfolding Response, and metabolism, across these diverse lineages. Outstanding questions as well as research opportunities and priorities to better understand the essential role of Clp systems in cellular proteostasis are discussed.

Leveraging nature's biomolecular designs in next-generation protein sequencing reagent development

Next-generation approaches for protein sequencing are now emerging that could have the potential to revolutionize the field in proteomics. One such sequencing method involves fluorescence-based imaging of immobilized peptides in which the N-terminal amino acid of a polypeptide is readout sequentially by a series of fluorescently labeled biomolecules. When selectively bound to a specific N-terminal amino acid, the NAAB (N-terminal amino acid binder) affinity reagent identifies the amino acid through its associated fluorescence tag. A key technical challenge in implementing this fluoro-sequencing approach is the need to develop NAAB affinity reagents with the high affinity and selectivity for specific N-terminal amino acids required for this biotechnology application. One approach to develop such a NAAB affinity reagent is to leverage naturally occurring biomolecules that bind amino acids and/or peptides. Here, we describe several candidate biomolecules that could be considered for this purpose and discuss the potential for developability of each. Key points • Next-generation sequencing methods are emerging that could revolutionize proteomics. • Sequential readout of N-terminal amino acids by fluorescent-tagged affinity reagents. • Native peptide/amino acid binders can be engineered into affinity reagents. • Protein size and structure contribute to feasibility of reagent developability.

A single amino acid substitution alters ClpS2 binding specificity

ClpS2 is a small protein under development as a probe for selectively recognizing N-terminal amino acids of N-degron peptide fragments. To understand the structural basis of ClpS2 specificity for an N-terminal amino acid, all atom molecular dynamics (MD) simulations were conducted using the sequence of a bench-stable mutant of ClpS2, called PROSS. We predicted that a single amino acid leucine to asparagine substitution would switch the specificity of PROSS ClpS2 to an N-terminal tyrosine over the preferred phenylalanine. Experimental validation of the mutant using a fluorescent yeast-display assay showed an increase in tyrosine binding over phenylalanine, in support of the proposed hypothesis.

Strategies for Development of a Next-Generation Protein Sequencing Platform

Proteomic analysis can be a critical bottleneck in cellular characterization. The current paradigm relies primarily on mass spectrometry of peptides and affinity reagents (i.e., antibodies), both of which require a priori knowledge of the sample. An unbiased protein sequencing method, with a dynamic range that covers the full range of protein concentrations in proteomes, would revolutionize the field of proteomics, allowing a more facile characterization of novel gene products and subcellular complexes. To this end, several new platforms based on single-molecule protein-sequencing approaches have been proposed. This review summarizes four of these approaches, highlighting advantages, limitations, and challenges for each method towards advancing as a core technology for next-generation protein sequencing.