1. No category

Differentiating between live and dead bacteria in water samples
using PMA-16S rDNA and 16S rRNA based sequence
Li,
1
R. ,
Tun,
1Department
2
H.M. ,
Khafipour,
2,3
E. ,
3,4
Kumar, A. ,
Fernando,
5
W.G.D. ,
1
Farenhorst, A.
of Soil Science; 2Department of Animal Science; 3Department of Medical Microbiology and Infectious Diseases; 4Department of Microbiology;
5Department
of Plant Science; University of Manitoba, Winnipeg, Manitoba, Canada
Introduction
!!The limitation of DNA based techniques is the inability to
differentiate live (vital) and dead (inactive) cells, which can
lead to false positive results in the absence of live microbes
in water [1,2].
!!Propidium monoazide (PMA) has been used for the
selective removal of dead cells from downstream DNA
applications [3,4].
!!Ribosomal ribonucleic acid (rRNA) can demonstrate active
microbial cells in water as it is produced by metabolically
active cells.
•! Output paired-end reads were merged using PANDASeq
!"
assembler and analyzed using QIIME.
#"
Bioinformatics
Mycobacterium smegmatis, Bacillus amyloquefaciens
Dead Mycobacterium smegmatis, Bacillus amyloquefaciens
and live E.coli, Yersinia enterocolitica
Dead
•! Multivariate data analysis [Prinicpal Co-ordinate Analysis
(PCoA), PERMANOVA] was done for detecting differences
for beta-diversity. P < 0 .05 was considered significant.
$"
Statistics
Results
!!The efficiencies of RNA and PMA-DNA based methodologies
to discriminate live and dead cells of bacterial community are
shown in Figure 1 and Table 1.
E.coli,
Yersinia
enterocolitica,
and
Mycobacterium smegmatis, Bacillus amyloquefaciens
1
!"
#"
Different water sources
!!For both the lake and river water, the bacterial profile was
significantly different between the DNA and RNA based
$"
methods (P = 0.10), but not the DNA and PMA-DNA
methodologies. For treated water (plant, piped, cistern), the
bacterial profile was similar for the RNA, DNA and PMADNA methods (Table 2).
live
1
Comparison Group
DNA vs. RNA
DNA vs. PMA
P (MC)
0.34
0.06
DNA vs. RNA
0.05
DNA vs. PMA
0.29
DNA vs. RNA
DNA vs. PMA
0.09
0.37
DNA vs. RNA
DNA vs. PMA
0.13
0.13
P-values based on Montel Carlo test
Table 2. Permutation Montel Carlo test unweighted unifrac distance of different water
source using DNA based, RNA based and PMA-DNA based methodologies
Water source
Comparison Groups
P (MC)
DNA vs. PMA
0.37
First Nations Cistern
DNA vs. RNA
0.13
DNA vs. PMA
0.26
First Nations Tap
DNA vs. RNA
0.15
First Nations
DNA vs. PMA
0.37
DNA vs. RNA
0.10
Source Water
DNA vs. PMA
0.33
Winnipeg Tap
DNA vs. RNA
0.22
DNA vs. PMA
0.61
Red River
DNA vs. RNA
0.11
Discussion
!!In this study, we found that RNA method were more
reliable than PMA-DNA in differentiating live/dead
bacterial cells in both spiked water and different water
sources. The efficiency of
PMA-DNA method in
detecting live bacterial could be affected by several
factors, such as the concentration of PMA dye, the
PMA incubation time and temperature. RNA is only
produced by metabolically active cells, making RNA
suitable to detect live bacterial cells.
Extraction of DNA, RNA and PMA-DNA from spiked
water and water samples
!!Spiked water (100 mL) and water samples (500 mL) were
filtered through 0.20µm, 47nm polyethersulfone filter.
DNA and RNA were extracted. RNA was transcripted to
cDNA.
!!Filtered-based PMA-DNA was extracted as described by
Hellein et al. (2012) and Nocker et al. (2010)
!!The library of V4 amplicons of 16S rRNA constructed and
subjected to 300 cycle paired-end MiSeq Illumina
sequencing [5].
Dead E.coli, Yersinia enterocolitica,
•! Alpha- & beta-diversity of microbial communities were
determined.
!!To compare the efficiency of PMA-based 16S rDNA versus
16S rRNA sequencing in detecting live bacterial cells in
different water samples.
!! Water was spiked with two Gram positive strains
Mycobacterium smegmatis, Bacillus amyloliquefaciens
strain BS6, and two Gram negative strains E. coli, Yersinia
enterocolitica in the following treatments: A) all live
strains, B) all dead strains, C) live negative strains + dead
positive strains, and D) live positive strains + dead negative
strains.
!!Water samples were collected in a fly-in First Nations
community in Manitoba from a lake, the water treatment
plant, piped tap water and cistern water. Piped tap water
and river water (Red River) were also collected in the City
of Winnipeg, Manitoba.
Mycobacterium smegmatis, Bacillus amyloquefaciens
•! The resulting operational taxonomic units were aligned at
97% similarity threshold to green-genes database.
Spiked water
Water samples
Treatment
Live E.coli, Yersinia enterocolitica,
•! Demulitiplexing merged reads, quality check and chimera
detection and filtering was done in QIIME.
Objective
Materials and Methods
Table 1. Permutation Montel Carlo test unweighted unifrac distance of spiked water
using DNA based, RNA based and PMA-DNA based methodologies
Acknowledgements
!!We gratefully acknowledge the Natural Sciences and
Engineering Council of Canada (NSERC) for provided
research funding to complete this study.
References
Figure 1. PCoA analysis of unweighted unifrac distances showing bacterial
composition variations in the spiked water among DNA based, RNA based, and
PMA-DNA based profiles. A) all live strains, B) all dead strains, C) live
negative strains + dead positive strains, and D) live positive strains + dead
negative strains.
create-h2o.ca
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UNIVERSITY Gut Microbiome and
OF MANITOBA Large Animal Biosecurity Laboratories