BSPS Program (ESI-Mass Spectrometry) Biological Sample Data Analysis; Disruption of Bacteria Spores

Abstract

The various biological processing technologies and biological identification approaches are essential for support of the mission to develop and demonstrate an advanced Biological Sample Preparation System. The BSPS will be used in conjunction with ESI-mass spectrometry for biological point detection and identification purposes. This report discusses the design and testing of a model for biological sample identification using mass spectrometry and protein sequence information available for various organisms. This is based on nature of various organisms and their protein sequence entries available, including experimentally verified postltanslational modifications. It is also based on significance based testing. Tested the model for biological sample data analysis including positive and negative ion MALDI TOF mass spectra for protein extract of H. pylori(26695) samples (reported in literature). This model may be used in conjunction with pattern recognition algorithms for Bio-sample ID through sample processing and ESI mass spectrometry. Protein biomarkers (LC-ESI as well as MALDI TOF MS) data available for some environmental bacteria samples show variability in the mass tables obtained at different growth times for the bacteria.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2005
Accession Number
ADA449717

Entities

People

  • Ravi P. Lall

Organizations

  • Edgewood Chemical Biological Center

Tags

Communities of Interest

  • Counter WMD

DTIC Thesaurus Topics

  • Bacteria
  • Bacteriology
  • Biological Factors
  • Chemistry
  • Data Analysis
  • Detection
  • Detectors
  • Identification
  • Mass Spectra
  • Mass Spectrometers
  • Mass Spectrometry
  • Microbiology
  • Microorganisms
  • Proteins
  • Spectra
  • Spectrometry
  • Spores

Fields of Study

  • Chemistry

Readers

  • Analytical Chemistry
  • Microbial Pathology
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference