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Related Concept Videos

Proteomics01:33

Proteomics

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Genomics02:02

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Moving Toward Metaproteogenomics: A Computational Perspective on Analyzing Microbial Samples via Proteogenomics.

Franziska Singer1,2, Mathias Kuhring3, Bernhard Y Renard4,5

  • 1NEXUS Personalized Health Technologies, ETH Zürich, Zürich, Switzerland.

Methods in Molecular Biology (Clifton, N.J.)
|October 22, 2024
PubMed
Summary

Proteogenomics combines genomic and proteomic data to analyze microbial samples. This approach creates custom protein databases for complex samples, overcoming limitations of traditional methods.

Keywords:
BacteriaBioinformaticsComputational proteomicsMetagenomicsMetaproteomicsMicrobesMicrobial community samplesProtein identificationProteogenomicsTandem mass spectrometry

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Computational Biology

Background:

  • Microbiome research and biotechnology drive microbial sample analysis.
  • Mass spectrometry enables metaproteome analysis of complex microbial mixtures.
  • Next-generation sequencing aids metagenome and genome characterization.

Purpose of the Study:

  • To provide an overview of computational challenges and opportunities in proteogenomics and metaproteomics.
  • To showcase an integrative proteogenomic method for creating sample-specific protein databases.
  • To present a simulation tool for estimating detection limits of microbial non-model organisms.

Main Methods:

  • Proteogenomic approach combining genomic and proteomic methods.
  • Integrative method using a graph network to combine RNA-Seq and peptide data.
  • Simulation tool to evaluate error-tolerant searches and proteogenomic influences.

Main Results:

  • An integrative method was demonstrated to create sample-specific protein databases, bypassing reference databases.
  • A simulation tool was provided to assess computational limits in detecting non-model organisms.
  • The study evaluated the impact of error-tolerant searches on database detection.

Conclusions:

  • Proteogenomics offers a tailored blueprint for microbial sample analysis.
  • Future strategies should integrate genome- and proteome-based methods for metaproteogenomics.
  • Overcoming current limitations requires combining strengths of both approaches.