Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2016 Oct 19;6:34359.
doi: 10.1038/srep34359.

Label-free, Rapid and Quantitative Phenotyping of Stress Response in E. Coli via Ramanome

Affiliations
Free PMC article

Label-free, Rapid and Quantitative Phenotyping of Stress Response in E. Coli via Ramanome

Lin Teng et al. Sci Rep. .
Free PMC article

Abstract

Rapid profiling of stress-response at single-cell resolution yet in a label-free, non-disruptive and mechanism-specific manner can lead to many new applications. We propose a single-cell-level biochemical fingerprinting approach named "ramanome", which is the collection of Single-cell Raman Spectra (SCRS) from a number of cells randomly selected from an isogenic population at a given time and condition, to rapidly and quantitatively detect and characterize stress responses of cellular population. SCRS of Escherichia coli cells are sensitive to both exposure time (eight time points) and dosage (six doses) of ethanol, with detection time as early as 5 min and discrimination rate of either factor over 80%. Moreover, the ramanomes upon six chemical compounds from three categories, including antibiotics of ampicillin and kanamycin, alcohols of ethanol and n-butanol and heavy metals of Cu2+ and Cr6+, were analyzed and 31 marker Raman bands were revealed which distinguish stress-responses via cytotoxicity mechanism and variation of inter-cellular heterogeneity. Furthermore, specificity, reproducibility and mechanistic basis of ramanome were validated by tracking stress-induced dynamics of metabolites and by contrasting between cells with and without genes that convey stress resistance. Thus ramanome enables rapid prediction and mechanism-based screening of cytotoxicity and stress-response programs at single-cell resolution.

Figures

Figure 1
Figure 1. The definition of a ramanome.
With a Raman band being conceptionally equivalent to a transcript or metabolite, a ramanome of a cell population provides a multiplex and comprehensive metabolic profile at not just the population level but the single-cell level.
Figure 2
Figure 2. Tracking of E. coli ramanome during response to ethanol.
(A) Temporal changes of Raman band intensity under control (empty symbol) or Eth-stress (solid symbol). Error bar represents SD (n = ~60). (B) PLSR model for quantification of lipid and DNA density in individual cells using ramanome. The mean lipid and mean DNA density of individual cells as predicted by ramanome was plotted versus the corresponding mean density determined by conventional methods (Methods). The unit of mg/s (ng/s) represents total mg (ng) biomass for each unit area of an individual cell.
Figure 3
Figure 3. Comparison of ramanome between stressed and control cells.
Similarity of ramanome was represented by R-value of ANOSIM. (A) Temporal tracking of ramanome variation under each stressor. (B) Radar map representing variation of ramanome among stressors at each time point. (C) Correlation coefficients (R2) of temporal patterns of ramanome among the stressors.
Figure 4
Figure 4. Temporal tracking of stress responses via marker Raman bands of each stressor.
Temporal patterns of those Raman bands underlying each stress-response program were grouped into two clusters via K-means clustering based on the largest silhouette coefficient (SE). The change of mean difference value of Raman band intensity (D-value) between stressed and control cells in a given cluster was plotted as blue lines, with error bar representing SD (n = ~60). Values at 0 min were assumed as zero. Distribution of molecular functions as represented by the Raman bands within each cluster under each stressor was shown on the right.
Figure 5
Figure 5. Raman-barcode of cellular-response to stressors (RBCS).
The change in Raman band intensity was calculated as D-value (between stressed and control cells) and shown as blue (decreased intensity) or red (increased intensity) (p < 0.001; Wilcoxon rank sum test).
Figure 6
Figure 6. Comparisons of inter-cellular heterogeneity among stressors at each time point.
Three Raman bands were shown as example, including 1445 cm−1 (lipids), 1002 cm−1 (proteins) and 782 cm−1 (nucleic acids). RSD, relative standard deviation.

Similar articles

See all similar articles

Cited by 12 articles

See all "Cited by" articles

References

    1. Young J. W., Locke J. C. W. & Elowitz M. B. Rate of environmental change determines stress response specificity. P Natl Acad Sci USA. 110, 4140–4145 (2013). - PMC - PubMed
    1. Ibaneza A. J. et al. . Mass spectrometry-based metabolomics of single yeast cells. P Natl Acad Sci USA. 110, 8790–8794 (2013). - PMC - PubMed
    1. Lidstrom M. E. & Konopka M. C. The role of physiological heterogeneity in microbial population behavior. Nat Chem Biol. 6, 705–712 (2010). - PubMed
    1. Fan H. C., Fu G. K. & Fodor S. P. A. Combinatorial labeling of single cells for gene expression cytometry. Science. 347, 1258367 (2015). - PubMed
    1. Shintaku H., Nishikii H., Marshall L. A., Kotera H. & Santiago J. G. On-Chip Separation and Analysis of RNA and DNA from Single Cells. Anal Chem. 86, 1953–1957 (2014). - PubMed

Publication types

MeSH terms

Feedback