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Bacterial killing and the dimensions of bacterial death

Authors: Renfei Wu; Cong Li; Jiuyi Li; Jelmer Sjollema; Gésinda I. Geertsema-Doornbusch; H. Willy de Haan-Visser; Emma S. C. Dijkstra; +6 Authors

Bacterial killing and the dimensions of bacterial death

Abstract

Bacteria can be dead, alive, or exhibit slowed or suspended life forms, making bacterial death difficult to establish. Here, agar-plating, microscopic-counting, SYTO9/propidium-iodide staining, MTT-conversion, and bioluminescence-imaging were used to determine bacterial death upon exposure to different conditions. Rank correlations between pairs of assay outcomes were low, indicating different assays measure different aspects of bacterial death. Principal-component analysis yielded two principal components, named "reproductive-ability" (PC1) and "metabolic-activity" (PC2). Plotting of these principal components in two-dimensional space revealed a dead region, with borders defined by the PC1 and PC2 values. Sensu stricto implies an unpractical reality that all assays determining PC1 and PC2 must be carried out in order to establish bacterial death. Considering this unpracticality, it is suggested that at least one assay determining reproductive activity (PC1) and one assay determining metabolic activity (PC2) should be used to establish bacterial death. Minimally, researchers should specifically describe which dimension of bacterial death is assessed, when addressing bacterial death.

Country
Netherlands
Keywords

Microbial ecology, Principal Component Analysis, Microbial Viability, Bacteria, QR100-130, Luminescent Measurements, Chemie, Luminescent Measurements/methods, Bacteria/classification, Article

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
Green
gold