Quick Discrimination of Heavy Metal Resistant Bacterial Populations Using Infrared Spectroscopy Coupled with Chemometrics

Gurbanov R., Ozek N. S., Gözen A. G., Severcan F.

ANALYTICAL CHEMISTRY, vol.87, pp.9653-9661, 2015 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 87
  • Publication Date: 2015
  • Doi Number: 10.1021/acs.analchem.5b01659
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.9653-9661
  • Middle East Technical University Affiliated: Yes


Lead and cadmium are frequently encountered heavy metals in industrially polluted areas. Many heavy metal resistant bacterial strains have a high biosorption capacity and thus are good candidates for the removal of toxic metals from the environment. However, as of yet there is no accurate method for discrimination of highly adaptive bacterial strains among the populations present in a given habitat. In this study, we aimed to find distinguishing molecular features of lead and cadmium resistant bacteria using Attenuated Total Reflectance Fourier Transformed Infrared (ATR-FT-IR) spectroscopy and chemometric approaches. Our results demonstrated that both control and metal exposed E. coli and S. aureus strains could be successfully discriminated from each other using hierarchical cluster and principal component analysis methods. Moreover, we found that lead exposed bacterial strains could be successfully discriminated from cadmium exposed ones with a high heterogeneity value. These clear discriminations can be described by the ability of a bacterium to change its metabolism in terms of the content and structure of cellular macromolecules under heavy metal stress. In our case, cadmium and lead-induced genetic response systems in bacteria caused remarkable alterations in overall cellular metabolism. Bacteria deal with a heavy metal stress by altering nucleic acid methylations and lipid and protein synthesis. Heavy metal burden led to the development of relevant metabolic changes in proteins, lipids, and nucleic acids of the resistant bacteria described in this study. Our approach showed that infrared spectra obtained via ATR-FT-IR spectroscopy coupled with chemometric analysis can be utilized for rapid, low-cost, informative, reliable, and operator-independent discrimination of resistant bacterial populations.