The identification and quantification of proteins lags behind DNA sequencing methods in scale, sensitivity and dynamic range. Here we show that sparse amino acid sequence information can be obtained for individual protein molecules for thousands to millions of molecules in parallel. We demonstrate selective fluorescent labeling of cysteine and lysine residues in peptide samples, immobilization of labeled peptides on a glass surface, and imaging by total internal reflection microscopy to monitor reductions in each molecule’s fluorescence following consecutive rounds of Edman degradation. The obtained sparse fluorescent sequence of each molecule was then assigned to its parent protein in a reference database. We demonstrate the method on synthetic and naturally-derived peptide molecules in zeptomole-scale quantities. We also fluorescently label phosphoserines and demonstrate single-molecule, positional readout of the phosphorylated sites. We measured >93% efficiencies for dye labeling, survival, and cleavage; further improvements should empower studies of increasingly complex proteomic mixtures, with the high sensitivity and digital quantification offered by single molecule sequencing.

Motile ciliopathies are characterized by specific defects in cilia beating that result in chronic airway disease, subfertility, ectopic pregnancy, and hydrocephalus. While many patients harbor mutations in the dynein motors that drive cilia beating, the disease also results from mutations in so-called dynein axonemal assembly factors (DNAAFs) that act in the cytoplasm. The mechanisms of DNAAF action remain poorly defined. Here, we show that DNAAFs concentrate together with axonemal dyneins and chaperones into organelles that form specifically in multiciliated cells, which we term DynAPs, for dynein axonemal particles. These organelles display hallmarks of biomolecular condensates, and remarkably, DynAPs are enriched for the stress granule protein G3bp1, but not for other stress granule proteins or P-body proteins. Finally, we show that both the formation and the liquid-like behaviors of DynAPs are disrupted in a model of motile ciliopathy. These findings provide a unifying cell biological framework for a poorly understood class of human disease genes and add motile ciliopathy to the growing roster of human diseases associated with disrupted biological phase separation.

The proteomes of cells, tissues, and organisms reflect active cellular processes and change continuously in response to intracellular and extracellular cues. Deep, quantitative profiling of the proteome, especially if combined with mRNA and metabolite measurements, should provide an unprecedented view of cell state, better revealing functions and interactions of cell components. Molecular diagnostics and biomarker discovery should benefit particularly from the accurate quantification of proteomes, since complex diseases like cancer change protein abundances and modifications. Currently, shotgun mass spectrometry is the primary technology for high-throughput protein identification and quantification; while powerful, it lacks high sensitivity and coverage. We draw parallels with next-generation DNA sequencing and propose a strategy, termed fluorosequencing, for sequencing peptides in a complex protein sample at the level of single molecules. In the proposed approach, millions of individual fluorescently labeled peptides are visualized in parallel, monitoring changing patterns of fluorescence intensity as N-terminal amino acids are sequentially removed, and using the resulting fluorescence signatures (fluorosequences) to uniquely identify individual peptides. We introduce a theoretical foundation for fluorosequencing and, by using Monte Carlo computer simulations, we explore its feasibility, anticipate the most likely experimental errors, quantify their potential impact, and discuss the broad potential utility offered by a high-throughput peptide sequencing technology.

Photography was employed for the quantitation and differentiation of G- and V-series nerve agent mimics with the use of self-propagating cascades. Fluoride anion and thiols, released from a G-nerve agent mimic (i.e., diisopropyl fluorophosphate) and a V-nerve agent mimic (i.e., demeton-S-methyl), respectively, were used to initiate self-propagating cascades that amplify fluorescence signals exponentially in a ratiometric manner. A homemade LEGO dark-box, a cell phone, and 96-well plates were employed to collect photographs of the fluorescence response to the analytes. The photographic images were digitally processed in the 1931 xyY color space using a watershed and morphological erosion algorithm to generate chromaticity vs concentration calibration curves. We show that the two different amplification routines are selective for their analyte class and thus successfully discriminated the G- and V-series nerve agent mimics. Further, accurate concentrations of the analytes are determined using the chromaticity and LEGO approach given herein, thus demonstrating a simple and on-site constructible/portable device for use in the field.

The proteomes of cells, tissues, and organisms reflect active cellular processes and change continuously in response to intracellular and extracellular cues. Deep, quantitative profiling of the proteome, especially if combined with mRNA and metabolite measurements, should provide an unprecedented view of cell state, better revealing functions and interactions of cell components. Molecular diagnostics and biomarker discovery should benefit particularly from the accurate quantification of proteomes, since complex diseases like cancer change protein abundances and modifications. Currently, shotgun mass spectrometry is the primary technology for high-throughput protein identification and quantification; while powerful, it lacks high sensitivity and coverage. We draw parallels with next-generation DNA sequencing and propose a strategy, termed fluorosequencing, for sequencing peptides in a complex protein sample at the level of single molecules. In the proposed approach, millions of individual fluorescently labeled peptides are visualized in parallel, monitoring changing patterns of fluorescence intensity as N-terminal amino acids are sequentially removed, and using the resulting fluorescence signatures (fluorosequences) to uniquely identify individual peptides. We introduce a theoretical foundation for fluorosequencing and, by using Monte Carlo computer simulations, we explore its feasibility, anticipate the most likely experimental errors, quantify their potential impact, and discuss the broad potential utility offered by a highthroughput peptide sequencing technology. Author SummaryThe development of next-generation DNA and RNA sequencing methods has transformed biology, with current platforms generating >1 billion sequencing reads per run. Unfortunately, no method of similar scale and throughput exists to identify and quantify specific proteins in complex mixtures, representing a critical bottleneck in many biochemical and molecular diagnostic assays. What is urgently needed is a massively parallel method, akin to next-gen DNA sequencing, for identifying and quantifying peptides or proteins in a sample. In principle, single-molecule peptide sequencing could achieve this goal, PLOS Computational Biology |