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. 2019 Jun 27;9(1):9343.
doi: 10.1038/s41598-019-45662-6.

Untargeted metabolomics unveil alterations of biomembranes permeability in human HaCaT keratinocytes upon 60 GHz millimeter-wave exposure

Pierre Le Pogam  1 , Yann Le Page  2 , Denis Habauzit  2 , Mickael Doué  1 , Maxim Zhadobov  1 , Ronan Sauleau  1 , Yves Le Dréan  2 , David Rondeau  3   4
Affiliations

Untargeted metabolomics unveil alterations of biomembranes permeability in human HaCaT keratinocytes upon 60 GHz millimeter-wave exposure

Pierre Le Pogam et al. Sci Rep. .

Abstract

A joint metabolomic and lipidomic workflow is used to account for a potential effect of millimeter waves (MMW) around 60 GHz on biological tissues. For this purpose, HaCaT human keratinocytes were exposed at 60.4 GHz with an incident power density of 20 mW/cm², this value corresponding to the upper local exposure limit for general public in the context of a wide scale deployment of MMW technologies and devices. After a 24h-exposure, endo- and extracellular extracts were recovered to be submitted to an integrative UPLC-Q-Exactive metabolomic and lipidomic workflow. R-XCMS data processing and subsequent statistical treatment led to emphasize a limited number of altered features in lipidomic sequences and in intracellular metabolomic analyses, whatever the ionization mode (i.e 0 to 6 dysregulated features). Conversely, important dysregulations could be reported in extracellular metabolomic profiles with 111 and 99 frames being altered upon MMW exposure in positive and negative polarities, respectively. This unexpected extent of modifications can hardly stem from the mild changes that could be reported throughout transcriptomics studies, leading us to hypothesize that MMW might alter the permeability of cell membranes, as reported elsewhere.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
PCA plots generated from endocellular lipidomic sequences from the features displaying both a Fold-Change ≥2 and a p-value < 0.05 upon R-XCMS data processing performed from UHPLC-HRMS sequences recorded in (A) Positive-Ion Mode and (B) Negative-Ion Mode. Note that SHi (with i = 1 to 4) and MMWj (with j = 1 to 4) are related to the non-exposed and exposed samples, respectively; QC represents the overall of the quality control samples.
Figure 2
Figure 2
PCA plots yielded by exocellular lipidomic analyses from the ions having a Fold-Change ≥2 with a p-value < 0.05 upon R-XCMS data processing performed from UHPLC-HRMS sequences recorded in (A) Positive-Ion Mode and (B) Negative-Ion Mode. Note that SHi (with i = 1 to 4) and MMWj (with j = 1 to 4) are related to the non-exposed and exposed samples, respectively; QC represents the overall of the quality control samples.
Figure 3
Figure 3
PCA plots obtained from endocellular metabolomic analyses from the features displaying both a Fold-Change ≥2 and a p-value < 0.05 upon R-XCMS data processing performed from UHPLC-HRMS sequences recorded in (A) Positive-Ion Mode and (B) Negative-Ion Mode. Note that SHi (with i = 1 to 4) and MMWj (with j = 1 to 4) are related to the non-exposed and exposed samples, respectively; QC represents the overall of the quality control samples.
Figure 4
Figure 4
PCA plots of exocellular metabolomics sequences, selecting ions having both a FC > 2 and a p-value < 0.05 upon R-XCMS data processing performed from UHPLC-HRMS sequences recorded in (A,B) Positive-Ion Mode and (C) Negative-Ion Mode. Note that SHi (with i = 1 to 4) and MMWj (with j = 1 to 4) are related to the non-exposed and exposed samples, respectively; QC represents the overall of the quality control samples.
Figure 5
Figure 5
Schematic workflow of the sample preparation procedure.
See this image and copyright information in PMC

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