Theoretical Considerations for Next-Generation Proteomics

Towards improved biofilm models

Biofilms are complex microbial communities that have a critical function in many natural ecosystems, industrial settings as well as in recurrent and chronic infections. Biofilms are highly heterogeneous and dynamic assemblages that display complex responses to varying environmental factors, and those properties present substantial challenges for their study and control. In recent years, there has been a growing interest in developing improved biofilm models to offer more precise and comprehensive representations of these intricate systems. However, an objective assessment for ascertaining the ability of biofilms in model systems to recapitulate those in natural environments has been lacking. In this Perspective, we focus on medical biofilms to delve into the current state-of-the-art in biofilm modelling, emphasizing the advantages and limitations of different approaches and addressing the key challenges and opportunities for future research. We outline a framework for quantitatively assessing model accuracy. Ultimately, this Perspective aims to provide a comprehensive and critical overview of medically focused biofilm models, with the intent of inspiring future research aimed at enhancing the biological relevance of biofilm models.

Robust and scalable single-molecule protein sequencing with fluorosequencing

The need to accurately survey proteins and their modifications with ever higher sensitivities, particularly in clinical settings with limited samples, is spurring development of new single molecule proteomics technologies. Fluorosequencing is one such highly parallelized single molecule peptide sequencing platform, based on determining the sequence positions of select amino acid types within peptides to enable their identification and quantification from a reference database. Here, we describe substantial improvements to fluorosequencing, including identifying fluorophores compatible with the sequencing chemistry, mitigating dye-dye interactions through the use of extended polyproline linkers, and developing an end-to-end workflow for sample preparation and sequencing. We demonstrate by fluorosequencing peptides in mixtures and identifying a target neoantigen from a database of decoy MHC peptides, highlighting the potential of the technology for high sensitivity clinical applications.

Sampling the proteome by emerging single-molecule and mass spectrometry methods

Mammalian cells have about 30,000-fold more protein molecules than mRNA molecules, which has major implications in the development of proteomics technologies. We review strategies that have been helpful for counting billions of protein molecules by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and suggest that these strategies can benefit single-molecule methods, especially in mitigating the challenges of the wide dynamic range of the proteome.

A binary/digital approach to amino acid identification and its application to peptide sequencing and protein identification

A binary/digital method is proposed in theory for the identification of single amino acids (AAs) in the bulk or with a few molecules from a single binary measurement. Combined with Edman degradation (or other cleaving method), it can be used to sequence a peptide or identify the parent protein from a partial sequence. The approach is centered on the superspecificity property of transfer RNAs (tRNAs). Markedly different from conventional and recent single molecule (SM) sequencing methods based on analog measurements, it changes the analytical question 'Which AA is it?' to the much simpler one 'Is there an AA in the detection space?'. Each of 20 terminal residues cleaved from 20 copies of a peptide enters a different cavity with a unique tRNA; tRNA charging (or binding with AA) occurs only in the cavity with the cognate AA. The bound AA or the AA separated from the tRNA is detected with a single binary measurement; its identity is known from the position of the single high bit in the resulting 20-bit output. Alternatively, a 20-stage pipeline can be used with sparse samples. Detection of the bound AA can be done optically by tagging the AAs with a fluorescent dye, or of the freed AA electrically with a nanopore. Necessary conditions for accurate AA identification are satisfied in principle; related computations and simulation results are presented. A modified version that can be used for de novo sequencing in parallel of large numbers of peptides immobilized on a glass slide with the tRNAs carrying a fluorescent tag is also proposed. Both methods can be used for protein identification from partial sequences containing 2 or 3 AA types by using only the corresponding tRNAs. Experiments may be performed to validate them, followed by translation into practice with existing technology; potential implementation issues are discussed. Binary/digital amino acid identification for peptide sequencing.

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.