Literature DB >> 24267574

Time-dependent post mortem changes in the composition of intestinal bacteria using real-time quantitative PCR.

Sari Tuomisto1, Pekka J Karhunen, Tanja Pessi.   

Abstract

Post mortem or even normal changes during life occurring in major gut bacterial populations are not known. We investigated Bacteroides sp., Bifidobacterium sp., Clostridium leptum, Clostridium coccoides, Streptococcus sp., Lactobacillus sp. and Enterobacteriacaea ratios in 7 fecal samples from healthy volunteers and in 61 autopsies rectum and cecum samples and studied the effect of post mortem time using quantitative real-time PCR. Bacterial ratios in stool samples from volunteers and rectum samples from autopsy cases were similar and did not change significantly up to 5 days post mortem. In cecum, significant post mortem time-dependent differences were observed in ratios of Bacteroides sp. (p = 0.014) and Lactobacillus sp. (p = 0.024). Our results showed that ratios of Bacteroides sp., Bifidobacterium sp., Clostridium leptum, Clostridium coccoides, Streptococcus sp., Lactobacillus sp. and Enterobacteriacaea can be investigated in autopsy rectum samples up to 5 days after death.

Entities:  

Year:  2013        PMID: 24267574      PMCID: PMC4176747          DOI: 10.1186/1757-4749-5-35

Source DB:  PubMed          Journal:  Gut Pathog        ISSN: 1757-4749            Impact factor:   4.181


Background

Basic knowledge on the composition of intestinal bacterial populations and changes occurring after death is lacking. Even the normal composition of intestinal microbiota in life is not fully known [1]. Only one study exists in which intestinal bacterial populations have been studied in three elderly women after death using PCR and sequencing [2]. Resident micro-organisms living in the intestinal tract influence host’s normal well-being and physiology including gut metabolism and the regulation of epithelial cell growth [3]. Intestinal microbiota functions as a physical barrier against invading pathogens. It has been suggested that gut microbiota may have a role on the development of diseases, e.g. alcoholic liver cirrhosis [4] and atherosclerosis [5]. Detailed bacterial population studies on the intestinal tract have mostly concentrated on fecal samples because they are easy to collect. Intestinal microbiota consists of a large and diverse community containing hundreds of commensal bacterial species [6]. From sequencing libraries of 16S rRNA genes Durban et al. found that two dominant phyla, Firmicutes and Bacteroidetes accounted for nearly 85% of all sequences in stool samples [7]. Compared to these two major phyla, Bifidobacterium genus is present in eight to ten-fold lower numbers [8]. Although Bacteroides sp., Bifidobacterium sp. and bacteria belonging to the Clostridium coccoides–group (cluster XIVa) and Clostridium leptum–group (cluster IV) dominate in colon [9,10] there is substantial inter- and intra-individual variation in species composition and distribution [7,11]. This study aimed to investigate ratios of major intestinal bacterial populations in healthy volunteers and in rectum and cecum autopsy samples. Post mortem time-dependent changes were studied in order to see whether autopsy samples can be used for basic research concerning lifetime. Six species: Bacteroides sp. (phylum Bacteroidetes), Clostridium sp. (Firmicutes), Streptococcus sp. (Firmicutes), Lactobacillus sp. (Firmicutes), Bifidobacterium sp. (Actinobacteria) and Enterobactericaea (Proteobacteria) were chosen since they represent the major intestinal bacterial phyla [12].

Findings

Study design and results

This study comprises of 61 male cases collected in the Department of Forensic Medicine of the University of Tampere and 7 male volunteers. The selection criteria for the autopsies have been described elsewhere [13]. None of the controls or cases was reported to has been used antibiotics. Deceased had been stored in +4°C within 24 hours after death. Written consent was obtained from the volunteers. Samples of the autopsy cases were taken from rectum and cecum. All samples were frozen immediately at −80°C until further processing. On the basis of time post mortem the cases were divided into groups: 1–3 days, 4–5 days and >5 days. Demographic characteristics of these groups are shown in the Table 1.
Table 1

Demographic characteristics of the study subjects divided by post mortem time

 
 
 
 
 
Basic cause of death
 
N
PM mean
Age mean (range)
BMI mean (range)
Heart diseases %
Other diseases %
Violent deaths (suicide, accident, poisoning) %
Autopsy cases:       
1–3 days
19
2.3
55 (18–79)
29.3 (20.4–42.1)
7 (37%)
4 (21%)
8 (42%)
4–5 days
21
4.5
58 (20–86)
28.4 (18.4–43.6)
10 (48%)
9 (43%)
2 (10%)
>5 days
21
6.5
61 (28–76)
30.7 (21.1–50.3)
15 (71%)
2 (10%)
4 (19%)
p-value
 
 
0.373
0.543
0.079
0.086
0.096
Control volunteers7 45 (26–57)27.1 (20.8–37.2) 

PM mean = Post mortem mean time.

Demographic characteristics of the study subjects divided by post mortem time PM mean = Post mortem mean time. Fecal samples were weighed to be 150 mg (wet weight). Bacterial DNA was extracted from the samples using Zymo Fecal DNA Kit (Zymo Research Corporation, Irvine, California, USA). The bacterial ratios were determined by RT-qPCR using specific primers and probes (Table 2). The primers and probes for Enterobacteriacaea and Lactobacillus sp. were designed and confirmed by using BLAST (http://www.ncbi.nlm.nih.gov/) and Ribosomal Database Project (http://rdp.cme.msu.edu/probematch/search.jsp). Specificity and cross reactivity of the designed primers and probes were tested using bacterial cultures from clinical samples [13]. PCR assays were performed with AbiPrism 7000 HT Sequence Detection System (Taqman, AppliedBiosystems, California, USA) with Taqman Environmental MasterMix. Endogen and DNA-free water was used as a negative control.
Table 2

Used primers and probes

Primer and probeSequence (5′-3′)Reference
Bacteroides sp.
 
[14]
Forward
TGGTAGTCCACACAGTAAACGATGA
 
Reverse
CGTACTCCCCAGGTGGAATACTT
 
Probe
GTTTGCCATATACAGTAAGCGGCCAAGCG
 
Bifidobacterium sp .
[15]
Forward
CGGGTGAGTAATGCGTGACC
 
Reverse
TGATAGGACGCGACCCCA
 
Probe
CTCCTGGAAACGGGTG
 
Clostridium leptum
 
[15]
Forward
CCTTCCGTGCCGSAGTTA
 
Reverse
GAATTAAACCACATACTCCACTGCTT
 
Probe
CACAATAAGTAATCCACC
 
Clostridium coccoides
[15]
Forward
GACGCCGCGTGAAGGA
 
Reverse
AGCCCCAGCCTTTCACATC
 
Probe
CGGTACCTGACTAAGAAG
 
Enterobactericaea
 
This study
Forward
GCGGTAGCACAGAGAGCTT
 
Reverse
GGCAGTTTCCCAGACATTACTCA
 
Probe
CCGCCGCTCGTCACC
 
Lactobacillus sp.
This study
Forward
GCTAGGTGTTGGAGGGTTTCC
 
Reverse
CCAGGCGGAATGCTTAATGC
 
Probe
TCAGTGCCGCAGCTAA
 
Streptococcus sp. mainly Str. mitis- group*
[13]
Forward
CCAGCAGCCGCGGTAATA
 
Reverse
CCTGCGCTCGCTTTACG
 
Probe
ACGCTCGGGACCTACG
 
Universal
 
[16]
Forward
TGGAGCATGTGGTTTAATTCGA
 
Reverse
TGCGGGACTTAACCCAACA
 
ProbeCACGAGCTGACGACA[A/G]CCATGCA 

*This was abbreviated as Streptococcus sp. in the text.

Used primers and probes *This was abbreviated as Streptococcus sp. in the text. The comparative Ct method (ΔΔCt, ΔCt sample – ΔCt reference sample)[17], was used where mean values from healthy male volunteers were calculated and used as a reference to determine bacterial relative amount in rectum samples. The differences of the Ct values between the bacteria and the universal bacteria measurement (ΔCt) for each sample were calculated; the comparative Ct (ΔΔCt) for sample and reference samples was calculated. To determine relative amounts of bacteria in cecum samples the rectal sample was used as an inner reference. Two standard curves were used to determine the total amount of bacteria. Tenfold dilution series of between 33 ng/ml and 0.00033 ng/ml from E. coli genomic DNA (ATCC 35401–5) as well as between 109 and 105 colony forming units (CFU) per milliliter from E .coli (ATCC 25922) were applied. The amount of CFU or bacterial DNA in the sample was calculated using values from universal measurement and the equation y = slope log (X) + intercept [18]. Statistical analyses were performed with Kruskal-Wallis median test with PASW Statistical Software, version 18 (SPSS Ltd, Quarry Bay, Hong Kong). If P-value was less than 0.05 (considered significant) pairwise Post Hoc comparisons using Mann–Whitney U-test were done. Median values of different bacteria in the stool of healthy controls and in post mortem rectum samples showed no statistically significant changes over post mortem time (Figure 1). In cecum, significant post mortem time-dependent differences were observed over the groups in the relative amounts of Bacteroides sp. (p = 0.014) and Lactobacillus sp. (p = 0.024, Table 3). There were significantly more Bacteroides sp. (p = 0.012) and less Lactobacillus sp. (p = 0.015) already in 4–5 days. Statistically significant differences in the total amount of bacterial DNA were seen in healthy volunteers and autopsy rectum samples (p = 0.044, Table 4). In autopsy rectum, the amount of bacterial DNA remained quite stable with time elapsing post mortem except for a high increase observed after day 5 post mortem (p = 0.023). A slightly higher total amount of bacterial DNA (measured as a wet weight) in stool samples donated by the volunteers compared to autopsy rectum samples might be due to lower water concentration in stool compared to rectum without changes in bacterial ratios [19]. Inter-individual variation was great at all time points and in all bacterial measurements.
Figure 1

Relative amounts (n-fold difference) of measured bacteria (sp., , sp., , sp. and sp.) in fecal samples of controls and rectum of autopsy cases. Individual values are presented as boxes, median values with horizontal lines. Comparisons over the groups were calculated using non-parametric Kruskal-Wallis test.

Table 3

The relative amounts (n-fold difference) of measured bacteria in cecum samples compared to rectum samples over post mortem time

 
 
Bacterial Group
 
 
 
Bacteroides sp.
C. leptum
C. coccoides
Bifidobacterium sp.
Enterobactericaea
Streptococcus sp.
Lactobacillus sp.
All
Median
0.32
0.72
1.29
1.18
0.86
2.19
0.82
 25th–75th0.13–1.060.41–1.610.27–3.940.52–2.660.09–3.380.52–7.500.25–3.61
1–3 days
 
 
 
 
 
 
 
 
 
Median
0.15
0.59
0.64
2.03
1.37
3.56
1.25
 
25th–75th
0.01–0.43
0.31–2.94
0.20–4.55
0.84–35.63
0.26–14.77
0.85–35.32
0.46–7.11
4–5 days
 
 
 
 
 
 
 
 
 
Median
0.53
1.09
1.27
0.61
0.68
2.28
0.30
 
25th–75th
0.17–1.60
0.60–1.81
0.15–2.30
0.26–2.34
0.03–1.85
0.34–8.07
0.16–1.95
>5 days
 
 
 
 
 
 
 
 
 
Median
0.53
0.60
2.81
1.03
0.86
1.85
1.09
 
25th–75th
0.21–1.45
0.41–1.39
0.59–4.27
0.45–1.61
0.16–7.94
0.27–5.68
0.65–7.84
 p-value0.0140.4720.4210.0540.3580.1920.024

Results are presented as median and 25th-75th interquartile range. Non-parametric median, Kruskal-Wallis-test comparisons between groups.

Table 4

The total amount of bacterial DNA in fecal samples

   Nng/g median*25 th -75 th p-value 1) p-value 2)
Healthy volunteers
Stool
Control
7
26
9.2-36.7
 
 
Autopsy cases
Rectum
1-3 days
18
8
2.0-53.6
 
 
 
 
4-5 days
21
8
1.7-41.4
 
 
 
 
>5 days
20
42
12.0-124.2
0.044
0.023
Autopsy cases
Cecum
1-3 days
19
51
13-3-94.1
 
 
 
 
4-5 days
21
68
5.1-194.7
 
 
  >5 days21486.5-113.6 0.982

*1 ng/g corresponds to 4.8x1010 colony forming units using E. coli as a standard. P-values (over the groups) for 1)healthy volunteers and autopsy cases, 2)autopsy cases only.

25th -75th interquartile range. Non-parametric median, Kruskal-Wallis-test comparisons over the groups.

Relative amounts (n-fold difference) of measured bacteria (sp., , sp., , sp. and sp.) in fecal samples of controls and rectum of autopsy cases. Individual values are presented as boxes, median values with horizontal lines. Comparisons over the groups were calculated using non-parametric Kruskal-Wallis test. The relative amounts (n-fold difference) of measured bacteria in cecum samples compared to rectum samples over post mortem time Results are presented as median and 25th-75th interquartile range. Non-parametric median, Kruskal-Wallis-test comparisons between groups. The total amount of bacterial DNA in fecal samples *1 ng/g corresponds to 4.8x1010 colony forming units using E. coli as a standard. P-values (over the groups) for 1)healthy volunteers and autopsy cases, 2)autopsy cases only. 25th -75th interquartile range. Non-parametric median, Kruskal-Wallis-test comparisons over the groups.

Conclusion

This study showed that relative amounts of major intestinal bacteria in rectum of autopsy cases were similar to stool donated by volunteers and remained quite stable over post mortem time up to 5 days, after which the total amount of bacteria started to increase. In contrast, in cecum significant post mortem time-dependent differences were observed as increase in ratio of strictly anaerobic Bacteroides sp. and decrease of facultative Lactobacillus sp. due to hypoxia after death. In cecum there is accumulation of undigested nutrients and metabolites produced by bacteria after death, which may be conducive to anaerobic bacterial growth. This study showed that autopsy rectum samples can be used to evaluate major intestinal bacterial populations concerning lifetime up to 5 days after death.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

ST performed experiments and analyses, helped in collection of the autopsy samples and wrote the manuscript. PK was the iniator of the project and group leader and participated in writing the script. TP was the guarantor of the microbiological part of the study, designed the sample collection and experiments, and participated in writing the manuscript. All authors read and approved the final manuscript.
  19 in total

1.  Development of a 5' nuclease-based real-time PCR assay for quantitative detection of cariogenic dental pathogens Streptococcus mutans and Streptococcus sobrinus.

Authors:  Akihiro Yoshida; Nao Suzuki; Yoshio Nakano; Miki Kawada; Takahiko Oho; Toshihiko Koga
Journal:  J Clin Microbiol       Date:  2003-09       Impact factor: 5.948

2.  Quantitative multiprobe PCR assay for simultaneous detection and identification to species level of bacterial pathogens.

Authors:  Samuel Yang; Shin Lin; Gabor D Kelen; Thomas C Quinn; James D Dick; Charlotte A Gaydos; Richard E Rothman
Journal:  J Clin Microbiol       Date:  2002-09       Impact factor: 5.948

Review 3.  Secretion and absorption by colonic crypts.

Authors:  John P Geibel
Journal:  Annu Rev Physiol       Date:  2005       Impact factor: 19.318

4.  Transient bacteraemia: a possible cause of sudden life threatening events.

Authors:  James A Morris; Linda M Harrison; Jhulan Biswas; David R Telford
Journal:  Med Hypotheses       Date:  2007-04-27       Impact factor: 1.538

5.  Characterization of fecal microbial communities in patients with liver cirrhosis.

Authors:  Yanfei Chen; Fengling Yang; Haifeng Lu; Baohong Wang; Yunbo Chen; Dajiang Lei; Yuezhu Wang; Baoli Zhu; Lanjuan Li
Journal:  Hepatology       Date:  2011-06-26       Impact factor: 17.425

6.  Molecular analysis of jejunal, ileal, caecal and recto-sigmoidal human colonic microbiota using 16S rRNA gene libraries and terminal restriction fragment length polymorphism.

Authors:  Hidenori Hayashi; Rei Takahashi; Takahiro Nishi; Mitsuo Sakamoto; Yoshimi Benno
Journal:  J Med Microbiol       Date:  2005-11       Impact factor: 2.472

Review 7.  Quantitative analysis of multi-species oral biofilms by TaqMan Real-Time PCR.

Authors:  Nao Suzuki; Akihiro Yoshida; Yoshio Nakano
Journal:  Clin Med Res       Date:  2005-08

8.  Enterotypes of the human gut microbiome.

Authors:  Manimozhiyan Arumugam; Jeroen Raes; Eric Pelletier; Denis Le Paslier; Takuji Yamada; Daniel R Mende; Gabriel R Fernandes; Julien Tap; Thomas Bruls; Jean-Michel Batto; Marcelo Bertalan; Natalia Borruel; Francesc Casellas; Leyden Fernandez; Laurent Gautier; Torben Hansen; Masahira Hattori; Tetsuya Hayashi; Michiel Kleerebezem; Ken Kurokawa; Marion Leclerc; Florence Levenez; Chaysavanh Manichanh; H Bjørn Nielsen; Trine Nielsen; Nicolas Pons; Julie Poulain; Junjie Qin; Thomas Sicheritz-Ponten; Sebastian Tims; David Torrents; Edgardo Ugarte; Erwin G Zoetendal; Jun Wang; Francisco Guarner; Oluf Pedersen; Willem M de Vos; Søren Brunak; Joel Doré; María Antolín; François Artiguenave; Hervé M Blottiere; Mathieu Almeida; Christian Brechot; Carlos Cara; Christian Chervaux; Antonella Cultrone; Christine Delorme; Gérard Denariaz; Rozenn Dervyn; Konrad U Foerstner; Carsten Friss; Maarten van de Guchte; Eric Guedon; Florence Haimet; Wolfgang Huber; Johan van Hylckama-Vlieg; Alexandre Jamet; Catherine Juste; Ghalia Kaci; Jan Knol; Omar Lakhdari; Severine Layec; Karine Le Roux; Emmanuelle Maguin; Alexandre Mérieux; Raquel Melo Minardi; Christine M'rini; Jean Muller; Raish Oozeer; Julian Parkhill; Pierre Renault; Maria Rescigno; Nicolas Sanchez; Shinichi Sunagawa; Antonio Torrejon; Keith Turner; Gaetana Vandemeulebrouck; Encarna Varela; Yohanan Winogradsky; Georg Zeller; Jean Weissenbach; S Dusko Ehrlich; Peer Bork
Journal:  Nature       Date:  2011-04-20       Impact factor: 49.962

9.  Comparative assessment of human and farm animal faecal microbiota using real-time quantitative PCR.

Authors:  Jean-Pierre Furet; Olivier Firmesse; Michèle Gourmelon; Chantal Bridonneau; Julien Tap; Stanislas Mondot; Joël Doré; Gérard Corthier
Journal:  FEMS Microbiol Ecol       Date:  2009-03-19       Impact factor: 4.194

10.  The Firmicutes/Bacteroidetes ratio of the human microbiota changes with age.

Authors:  D Mariat; O Firmesse; F Levenez; Vd Guimarăes; H Sokol; J Doré; G Corthier; J-P Furet
Journal:  BMC Microbiol       Date:  2009-06-09       Impact factor: 3.605

View more
  10 in total

1.  Changes in gut bacterial populations and their translocation into liver and ascites in alcoholic liver cirrhotics.

Authors:  Sari Tuomisto; Tanja Pessi; Pekka Collin; Risto Vuento; Janne Aittoniemi; Pekka J Karhunen
Journal:  BMC Gastroenterol       Date:  2014-02-24       Impact factor: 3.067

2.  Potential use of bacterial community succession for estimating post-mortem interval as revealed by high-throughput sequencing.

Authors:  Juanjuan Guo; Xiaoliang Fu; Huidan Liao; Zhenyu Hu; Lingling Long; Weitao Yan; Yanjun Ding; Lagabaiyila Zha; Yadong Guo; Jie Yan; Yunfeng Chang; Jifeng Cai
Journal:  Sci Rep       Date:  2016-04-07       Impact factor: 4.379

3.  Development and Use of a Real-Time Quantitative PCR Method for Detecting and Quantifying Equol-Producing Bacteria in Human Faecal Samples and Slurry Cultures.

Authors:  Lucía Vázquez; Lucía Guadamuro; Froilán Giganto; Baltasar Mayo; Ana B Flórez
Journal:  Front Microbiol       Date:  2017-06-30       Impact factor: 5.640

4.  Dietary quality of predominantly traditional diets is associated with blood glucose profiles, but not with total fecal Bifidobacterium in Indonesian women.

Authors:  Shiela Stefani; Sanny Ngatidjan; Monica Paotiana; Kurnia A Sitompul; Murdani Abdullah; Dyah P Sulistianingsih; Anuraj H Shankar; Rina Agustina
Journal:  PLoS One       Date:  2018-12-21       Impact factor: 3.240

5.  Age-dependent association of gut bacteria with coronary atherosclerosis: Tampere Sudden Death Study.

Authors:  Sari Tuomisto; Heini Huhtala; Mika Martiskainen; Sirkka Goebeler; Terho Lehtimäki; Pekka J Karhunen
Journal:  PLoS One       Date:  2019-08-22       Impact factor: 3.240

6.  Oral Administration of Flavonifractor plautii Strongly Suppresses Th2 Immune Responses in Mice.

Authors:  Tasuku Ogita; Yoshinari Yamamoto; Ayane Mikami; Suguru Shigemori; Takashi Sato; Takeshi Shimosato
Journal:  Front Immunol       Date:  2020-02-28       Impact factor: 7.561

7.  Potential use of molecular and structural characterization of the gut bacterial community for postmortem interval estimation in Sprague Dawley rats.

Authors:  Huan Li; Siruo Zhang; Ruina Liu; Lu Yuan; Di Wu; E Yang; Han Yang; Shakir Ullah; Hafiz Muhammad Ishaq; Hailong Liu; Zhenyuan Wang; Jiru Xu
Journal:  Sci Rep       Date:  2021-01-08       Impact factor: 4.379

8.  Experimental validation of small mammal gut microbiota sampling from faeces and from the caecum after death.

Authors:  Dagmar Čížková; Ľudovít Ďureje; Jaroslav Piálek; Jakub Kreisinger
Journal:  Heredity (Edinb)       Date:  2021-05-27       Impact factor: 3.832

9.  Dietary Supplementation with Oleum Cinnamomi Improves Intestinal Functions in Piglets.

Authors:  Dan Yi; Qiuhong Fang; Yongqing Hou; Lei Wang; Haiwang Xu; Tao Wu; Joshua Gong; Guoyao Wu
Journal:  Int J Mol Sci       Date:  2018-04-25       Impact factor: 5.923

10.  A Comprehensive Evaluation of Enterobacteriaceae Primer Sets for Analysis of Host-Associated Microbiota.

Authors:  Carolina N Resendiz-Nava; Hilda V Silva-Rojas; Angel Rebollar-Alviter; Dulce M Rivera-Pastrana; Edmundo M Mercado-Silva; Gerardo M Nava
Journal:  Pathogens       Date:  2021-12-23
  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.