Browse
Submit Data
Databases
API
Help

Dataset Information

51 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Protein identification by nanopore peptide profiling.

ABSTRACT: Nanopores are single-molecule sensors used in nucleic acid analysis, whereas their applicability towards full protein identification has yet to be demonstrated. Here, we show that an engineered Fragaceatoxin C nanopore is capable of identifying individual proteins by measuring peptide spectra that are produced from hydrolyzed proteins. Using model proteins, we show that the spectra resulting from nanopore experiments and mass spectrometry share similar profiles, hence allowing protein fingerprinting. The intensity of individual peaks provides information on the concentration of individual peptides, indicating that this approach is quantitative. Our work shows the potential of a low-cost, portable nanopore-based analyzer for protein identification.

SUBMITTER: Lucas FLR

PROVIDER: S-EPMC8490355 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Protein identification by nanopore peptide profiling.

Lucas Florian Leonardus Rudolfus FLR Versloot Roderick Corstiaan Abraham RCA Yakovlieva Liubov L Walvoort Marthe T C MTC Maglia Giovanni G

Nature communications 20211004 1

Nanopores are single-molecule sensors used in nucleic acid analysis, whereas their applicability towards full protein identification has yet to be demonstrated. Here, we show that an engineered Fragaceatoxin C nanopore is capable of identifying individual proteins by measuring peptide spectra that are produced from hydrolyzed proteins. Using model proteins, we show that the spectra resulting from nanopore experiments and mass spectrometry share similar profiles, hence allowing protein fingerprin ...[more]

PMID: 34608150

Similar Datasets

Identification of tagged glycans with a protein nanopore.

Project description:Structural complexity of glycans derived from the diversities in composition, linage, configuration, and branching considerably complicates structural analysis. Nanopore-based single-molecule sensing offers the potential to elucidate glycan structure and even sequence glycan. However, the small molecular size and low charge density of glycans have restricted direct nanopore detection of glycan. Here we show that glycan sensing can be achieved using a wild-type aerolysin nanopore by introducing a facile glycan derivatization strategy. The glycan molecule can induce impressive current blockages when moving through the nanopore after being connected with an aromatic group-containing tag (plus a carrier group for the neutral glycan). The obtained nanopore data permit the identification of glycan regio- and stereoisomers, glycans with variable monosaccharide numbers, and distinct branched glycans, either independently or with the use of machine learning methods. The presented nanopore sensing strategy for glycans paves the way towards nanopore glycan profiling and potentially sequencing.

| S-EPMC10050315 | biostudies-literature

Identification of epigenetic DNA modifications with a protein nanopore.

Project description:Two DNA bases, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (hmC), marks of epigenetic modification, are recognized in immobilized DNA strands and distinguished from G, A, T and C by nanopore current recording. Therefore, if further aspects of nanopore sequencing can be addressed, the approach will provide a means to locate epigenetic modifications in unamplified genomic DNA.

| S-EPMC3147113 | biostudies-literature

Aerolysin nanopore-based identification of proteinogenic amino acids using a bipolar peptide probe.

Project description:Nanopore technology has attracted extensive attention due to its rapid, highly sensitive, and label-free performance. In this study, we aimed to identify proteinogenic amino acids using a wild-type aerolysin nanopore. Specifically, bipolar peptide probes were synthesised by linking four aspartic acid residues to the N-terminal and five arginine residues to the C-terminal of individual amino acids. With the help of the bipolar peptide carrier, 9 proteinogenic amino acids were reliably recognised based on current blockade and dwell time using an aerolysin nanopore. Furthermore, by changing the charge of the peptide probe, two of the five unrecognized amino acids above mentioned were identified. These findings promoted the application of aerolysin nanopores in proteinogenic amino acid recognition.

| S-EPMC9470019 | biostudies-literature

An Engineered OmpG Nanopore with Displayed Peptide Motifs for Single-Molecule Multiplex Protein Detection.

Project description:Molecular detection via nanopore, achieved by monitoring changes in ionic current arising from analyte interaction with the sensor pore, is a promising technology for multiplex sensing development. Outer Membrane Protein G (OmpG), a monomeric porin possessing seven functionalizable loops, has been reported as an effective sensing platform for selective protein detection. Using flow cytometry to screen unfavorable constructs, we identified two OmpG nanopores with unique peptide motifs displayed in either loop 3 or 6, which also exhibited distinct analyte signals in single-channel current recordings. We exploited these motif-displaying loops concurrently to facilitate single-molecule multiplex protein detection in a mixture. We additionally report a strategy to increase sensor sensitivity via avidity motif display. These sensing schemes may be expanded to more sophisticated designs utilizing additional loops to increase multiplicity and sensitivity.

| S-EPMC9898208 | biostudies-literature

Slowing down single-molecule trafficking through a protein nanopore reveals intermediates for peptide translocation.

Project description:The microscopic details of how peptides translocate one at a time through nanopores are crucial determinants for transport through membrane pores and important in developing nano-technologies. To date, the translocation process has been too fast relative to the resolution of the single molecule techniques that sought to detect its milestones. Using pH-tuned single-molecule electrophysiology and molecular dynamics simulations, we demonstrate how peptide passage through the α-hemolysin protein can be sufficiently slowed down to observe intermediate single-peptide sub-states associated to distinct structural milestones along the pore, and how to control residence time, direction and the sequence of spatio-temporal state-to-state dynamics of a single peptide. Molecular dynamics simulations of peptide translocation reveal the time- dependent ordering of intermediate structures of the translocating peptide inside the pore at atomic resolution. Calculations of the expected current ratios of the different pore-blocking microstates and their time sequencing are in accord with the recorded current traces.

| S-EPMC3902492 | biostudies-literature

Simulation of single-protein nanopore sensing shows feasibility for whole-proteome identification.

Project description:Single-molecule techniques for protein sequencing are making headway towards single-cell proteomics and are projected to propel our understanding of cellular biology and disease. Yet, single cell proteomics presents a substantial unmet challenge due to the unavailability of protein amplification techniques, and the vast dynamic-range of protein expression in cells. Here, we describe and computationally investigate the feasibility of a novel approach for single-protein identification using tri-color fluorescence and plasmonic-nanopore devices. Comprehensive computer simulations of denatured protein translocation processes through the nanopores show that the tri-color fluorescence time-traces retain sufficient information to permit pattern-recognition algorithms to correctly identify the vast majority of proteins in the human proteome. Importantly, even when taking into account realistic experimental conditions, which restrict the spatial and temporal resolutions as well as the labeling efficiency, and add substantial noise, a deep-learning protein classifier achieves 97% whole-proteome accuracies. Applying our approach for protein datasets of clinical relevancy, such as the plasma proteome or cytokine panels, we obtain ~98% correct protein identification. This study suggests the feasibility of a method for accurate and high-throughput protein identification, which is highly versatile and applicable.

| S-EPMC6559672 | biostudies-literature

Peptide array X-linking (PAX): a new peptide-protein identification approach.

Project description:Many protein interaction domains bind short peptides based on canonical sequence consensus motifs. Here we report the development of a peptide array-based proteomics tool to identify proteins directly interacting with ligand peptides from cell lysates. Array-formatted bait peptides containing an amino acid-derived cross-linker are photo-induced to crosslink with interacting proteins from lysates of interest. Indirect associations are removed by high stringency washes under denaturing conditions. Covalently trapped proteins are subsequently identified by LC-MS/MS and screened by cluster analysis and domain scanning. We apply this methodology to peptides with different proline-containing consensus sequences and show successful identifications from brain lysates of known and novel proteins containing polyproline motif-binding domains such as EH, EVH1, SH3, WW domains. These results suggest the capacity of arrayed peptide ligands to capture and subsequently identify proteins by mass spectrometry is relatively broad and robust. Additionally, the approach is rapid and applicable to cell or tissue fractions from any source, making the approach a flexible tool for initial protein-protein interaction discovery.

| S-EPMC3351392 | biostudies-literature

Controlled Translocation of Proteins through a Biological Nanopore for Single-Protein Fingerprint Identification.

Project description:After the successful sequencing of nucleic acids, nanopore technology has now been applied to proteins. Recently, it has been demonstrated that an electro-osmotic flow can be used to induce the transport of unraveled polypeptides across nanopores. Polypeptide translocation, however, is too fast for accurate reading its amino acid compositions. Here, we show that the introduction of hydrophobic residues into the lumen of the nanopore reduces the protein translocation speed. Importantly, the introduction of a tyrosine at the entry of the nanopore and an isoleucine at the entry of the β-barrel of the nanopore reduced the speed of translocation to ∼10 amino acids/millisecond while keeping a relatively large ionic current, a crucial component for protein identification. These nanopores showed unique features within their current signatures, which may pave the way toward protein fingerprinting using nanopores.

| S-EPMC11544688 | biostudies-literature

PPINGUIN: Peptide Profiling Guided Identification of Proteins improves quantitation of iTRAQ ratios.

Project description:BACKGROUND: Recent development of novel technologies paved the way for quantitative proteomics. One of the most important among them is iTRAQ, employing isobaric tags for relative or absolute quantitation. Despite large progress in technology development, still many challenges remain for derivation and interpretation of quantitative results. One of these challenges is the consistent assignment of peptides to proteins. RESULTS: We have developed Peptide Profiling Guided Identification of Proteins (PPINGUIN), a statistical analysis workflow for iTRAQ data addressing the problem of ambiguous peptide quantitations. Motivated by the assumption that peptides uniquely derived from the same protein are correlated, our method employs clustering as a very early step in data processing prior to protein inference. Our method increases experimental reproducibility and decreases variability of quantitations of peptides assigned to the same protein. Giving further support to our method, application to a type 2 diabetes dataset identifies a list of protein candidates that is in very good agreement with previously performed transcriptomics meta analysis. Making use of quantitative properties of signal patterns identified, PPINGUIN can reveal new isoform candidates. CONCLUSIONS: Regarding the increasing importance of quantitative proteomics we think that this method will be useful in practical applications like model fitting or functional enrichment analysis. We recommend to use this method if quantitation is a major objective of research.

| S-EPMC3368728 | biostudies-literature

Profiling single-molecule reaction kinetics under nanopore confinement.

Project description:The study of a single-molecule reaction under nanoconfinement is beneficial for understanding the reactive intermediates and reaction pathways. However, the kinetics model of the single-molecule reaction under confinement remains elusive. Herein we engineered an aerolysin nanopore reactor to elaborate the single-molecule reaction kinetics under nanoconfinement. By identifying the bond-forming and non-bond-forming events directly, a four-state kinetics model is proposed for the first time. Our results demonstrated that the single-molecule reaction kinetics inside a nanopore depends on the frequency of individual reactants captured and the fraction of effective collision inside the nanopore confined space. This insight will guide the design of confined nanopore reactors for resolving the single-molecule chemistry, and shed light on the mechanistic understanding of dynamic covalent chemistry inside confined systems such as supramolecular cages, coordination cages, and micelles.

| S-EPMC8985585 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data