Next-Generation Proteomics: Massively Parallel Single-Molecule Protein Identifica
Next-Generation Proteomics: Massively Parallel Single-Molecule Protein Identifica
批准号:
8710285
负责人:
EDWARD M MARCOTTE
金额:
$77.25万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-30 至 2017-07-31
关键词:
Amino Acid SequenceAntibodiesBiochemicalBiological AssayBiological MarkersBiologyBiopsyBloodCommunicable DiseasesComplex MixturesDNADNA SequenceDevelopmentDiagnosisDiagnosticDiseaseFluorescence MicroscopyGene ExpressionGenomeGoalsGrowthIndividualMalignant NeoplasmsMassive Parallel SequencingMedicineMethodsMolecularMonitorMutationNucleic AcidsNucleotidesPatternPeptide Sequence DeterminationPeptidesPost-Translational Protein ProcessingProceduresProteinsProteomicsReadingResearchRunningSalivaSamplingSerumTechnologyUrineabstractingbasecancer diagnosisinterestnext generationprotein aminoacid sequenceprotein expressionprotein profilingsingle moleculesuccess
中文摘要
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英文摘要
DESCRIPTION
Abstract:
The development of next-generation DNA sequencing methods for quickly acquiring genome and gene
expression information has transformed biology. The basis of “next-gen” DNA sequencing is the acquisition of
large numbers of short reads (typically 35–500 nucleotides) in parallel. Currently available single-molecule
next-gen sequencing platforms monitor the sequencing of single DNA molecules using fluorescence
microscopy, allowing for approx. a 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, molecular diagnostic, and biomarker discovery assays. What is urgently
needed is a massively parallel method, akin to next-gen DNA sequencing, for identifying and quantifying
individual peptides or proteins in a sample. I propose a single-molecule peptide sequencing strategy that will
achieve exactly this goal. This will in principle allow billions of distinct peptides to be sequenced in parallel (or
at least sequenced sufficiently to provide informative sequence patterns), thereby identifying proteins
composing the sample and digitally quantifying them by direct counting of peptides. This transformative
approach should enable the quantitative, massively parallel sequencing of proteins. Success of the proposed
research will create a technology sufficiently ready for real-world protein sequencing problems. Such an
approach would have broad applications across biology and medicine, and could be as fundamental for
proteins as, for example, PCR is for nucleic acid research. Potential applications include, for example, profiling
of protein expression in normal body niches or in disease, metaproteomics, profiling the circulating serum
antibodies, the search for and quantification of protein post-translational modifications, and, of particular
interest, identifying biomarkers relevant to cancer and infectious diseases. In short, single-molecule
sequencing could potentially solve many of the problems currently limiting the field of proteomics and
biomarker discovery, promising improvements of more than 5 orders of magnitude in sensitivity and throughput
and offering a path forward that can reasonably be expected to mirror the phenomenal growth and impact of
next-gen DNA sequencing.
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资助金额:$77.25万
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依托单位:
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依托单位:
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依托单位:
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依托单位:
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Cell chips for genome-wide protein and RNA localization in single cells
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依托单位:
海外基金