e coli y alcohol

8/10/2019 e coli y alcohol

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The present contribution describes the development of simple,

albeit accurate, mathematical models which could quantify the

microbial produced ethanol in correlation with other alcohols in E.

coli cultures under initially aerobic and then anaerobic, controlled

laboratory conditions. The applicability of the constructed models

was tested in real postmortem cases that had positive BACs

(BAC > 0.10 g/L) and co-detection of higher alcohols and 1-butanol

during the original ethanol analysis. The applicability of the

models was also tested to microbial cultures of blood culture

media inoculated with postmortem blood from autopsy cases

under aerobic/anaerobic controlled experimental conditions.

2. Materials and methods

2.1. Microbial cultures

2.1.1. Bacterial strain

The bacterial strain used in this study was E. coli ATCC 35218. The E. coli strain

was stored at 80 8C (Mikrobank beads – Prolab Diagnostics, Canada) and prior to

use it was revived by transferring 3–5 beads into 10 mLof Brain Heart Infusion (BHI)

(CM0225, Oxoid) and was incubated at 37

8C for 18–24 h. The bacterial inoculum

was adjusted to a working concentration of 106 cells/mL using spectrophotometry.

In brief, a standard solution of 108 cells/mL was prepared from an initial culture

after overnight incubation at 37

8C aerobically and the concentration was

determined using the spectrophotometer (Model 6305, Jenway, England) at

600 nm. In order to obtain a final concentration of 106 cells/mL, 100

mL of the

standard

inoculum

were

added

in

9.9

mL

of

BHI

in

sterile

tubes.

The

tubes

wereincubated aerobically for the first 5 days. After this period 1 mLof sterile parafine oil

wasadded in each tube as an overlay and the tubes were placed into GENbag anaer

incubation systems (45534, bioMerieux, France) so as to provide anaerobic

conditions from day 6 to day 30. The incubation, both anaerobic and aerobic, was

performed at 25 8C for 30 days.

2.1.2. Bacterial enumeration

The bacterial concentration was determined by the pour plate count technique

[16]. Decimal dilutions were performed in tubes with 9 mL of Maximal Recovery

Diluent

(MRD,

02-510,

Scharlau

Chemie,

Spain).

From

each

tube

an

inoculum

of

1 mLwas transferred into 2 petri dishes and 15 mL of Plate Count Agar (1.05463,

Merck KGaA, Germany) melted at approximately 45 8C were added. After

solidification

all

plates

were

incubated

aerobically

at

37

8C

for

48

h.

Colonies

were

counted under a colony counter (Stuart SC6, Barloworld Scientific Ltd., UK).

2.2. Postmortem blood derived microbial cultures

2.2.1. Identification of microbes

Seven postmortem blood samples were examined for the presence of E. coli,

Staphylococcus aureus, Enterococcus spp., and Clostridium spp. Ten

mL of aseptically

collected blood was added into 1 mL of Buffered Peptone Water – BPW (CM1049,

Oxoid, UK). E. coli was isolated by plating a loopful of BPW on Violet Red Bile agar

(4021852, Biolife, Italy) and Chromocult Coliform Agar (1.10426.0500, Merck KGaA,

Germany).

The

inoculated

media

were

incubated

aerobically

at

37

8C

for

24

h.

Characteristic colonies were selected, pure cultured and identified to the genus

level using the API20E system (bioMerieux, France). For the isolation of Gram

positive

strains

(S. aureus

and Enterococcus

spp.),

Manitol

Salt

agar

(CM0085,

Oxoid,

UK) and D-Coccosel Bile Esculin Agar (51025, bioMerieux, France) were used,

respectively. The plates were incubated at 37 8C aerobically. Characteristic colonies

were selected, pure cultured and identified to the genus level by biochemical tests.

For Staphylococci the catalase test, the coagulase test (Staphytect Plus, Oxoid, UK)

and the API STAPH system (bioMerieux, France) were used. Biochemical

identification of the Enterococci was performed using the catalase test and the

API 20 STREP system (bioMerieux, France). For the isolation of Clostridium species a

loopful was streaked onto blood agar plates, the inoculated plates were incubated

anaerobically using the GENbag anaer incubation systems (bioMerieux, France) for

48

h

at

37

8C

and

were

examined

for

b-haemolysis.

Identification

was

performed

microscopically after Gram stain and with the use of the API 20A system

(bioMerieux, France).

2.2.2. Normal human blood culture media inoculated with postmortem blood

(postmortem blood derived microbial cultures)

The postmortem blood derived cultures were performed by a procedure based to

that described by Appenzeller and colleagues [15] modified to fit the conditions of

microbial cultures used herein. Specifically, ethanol free whole human blood from

healthy individuals was inoculated with postmortem blood (100

mL/mL of normal

human blood). Postmortem blood samples were collected into sterilized collection

tubes

containing

anticoagulant,

during

autopsy

from

cases

with

putrefaction

and

also were subjected to the procedure of microbial identification (described in

Section 2.2.1). The blood samples were kept at 4 8C until further use. One mL

portions

of

the

inoculated

blood

were

transferred

into

40

sterilized

blood

tubes

(Vacuette EDTAK3, 3 mL). Twenty tubes were spiked with the appropriate volume

of a concentrated glucose solution (sterile dextrose 5% (w/v), pyrogen free solution

for intravenous infusion, DEMO Ltd., Greece) so as to obtain 200 mg/dL final glucose

concentration. The other tubes were incubated without additional glucose. All the

tubes were capped and incubated at 25

8C. On the seventh day a sterile parafin oil

overlay

was

added

into

each

tube

and

the

tubes

were

placed

into

the

GENbag

anaer

incubation system. At days 0, 1, 2, 3, 5, 7, 9, 11, 15 and 20 two tubes were removed

from the incubation system and alcohols concentrations were determined by HS-

GC–FID.

2.3.

Determination

of

volatiles

The alcohols concentration in the culture medium and the blood samples were

determined by the previously described procedure [16].

2.4. Statistical analysis

Regression analysis was employed to model the correlation between the

microbial produced ethanol and the other higher alcohols. The experimental data

were consistent with a Gaussian distribution (normality test) and were analyzed

with multiple linear regression (MLR) methods to model the relationship between

ethanol concentrations as the dependent variable being in linear correlation with

the concentrations of the other alcohols (independent variables). Each descriptor’s

relevance

to

the

current

model

was

assessed

by

partial

least

squares

(PLS)

regression utilizing the PLS1 algorithm. During the analysis, one outlier value was

removed from the dataset.

3.

Results

and

discussion

3.1.

Experimental

determination

of

alcohols

produced

in

pure E. coli

cultures

E. coli is a Gram negative, aerobic and facultative anaerobic, rod-

shaped bacterium that is commonly found in the lower intestine of

warm-blooded organisms. It is considered one of the main

colonizers in corpses and of the main ethanol producers [17].

The growth curve of E. coli during the 30 days incubation at 25

8C is

presented in Fig. 1. During the first 5 days of incubation the

conditions were aerobic. On the fifth day up to the end of the

incubation the conditions of microbial growth changed to

anaerobic. By the fifth day of incubation the bacterial population

reached the stationary phase of growth. The change from aerobic to

anaerobic conditions was selected in order to approximate the

usual conditions where a postmortem blood evolves from death to

autopsy (initially air is available, which gradually decreases and

finally depletes) [1,19] and the duration of changing was selected

in order to obtain the optimal microbial growth. At 4

8C no growth

was observed as expected (not shown) [15,16,18].

The amounts of ethanol, and other alcohols produced under the

applied experimental conditions were variable (Table 1). Ethanol

1,0E+06

1,0E+07

1,0E+08

1,0E+09

1,0E+10

302520151050

Days

B a c t e r i a l c o u n t ( L o g 1 0 C F U

/ m L

Fig. 1. Growth curve of E. coli showing the number of bacteria during the incubation

period

of

30

days

at

25

8C. The

time

of

change

between

aerobic

and

anaerobic

incubation is shown by the dotted line at 5 days.

V.A. Boumba et al. / Forensic Science International 232 (2013) 191–198192



was produced in higher concentrations compared to the other

alcohols. Considering the ethanol concentration at days 0 and 5

(0 g/L and 0.55 g/L, respectively), it is concluded that the mean rate

of ethanol increase is 0.11 g/L/day (or 11 mg/dL/day) during the

first five-days period of incubation. After switching to anaerobic

conditions, from day six to day nine, the rate of ethanol production

decreased to a mean rate of 0.017 g/L/day (or 1.7 mg/dL/day).

Afterwards, from day 10 to the end of the experiment, ethanol kept

a plateau concentration of about 0.62 g/L.

The most abundantly produced alcohol (except ethanol) was 1-

propanol which was continuously increasing during the first 17

days. Interestingly, the mean rate of 1-propanol’s increase was

0.42 mg/dL/day during the first five days, while for the next twelve

days the increase rate declined, and afterwards, from day 18 to the

end, 1-propanol showed no considerable change. The third in

abundance alcohol was 1-butanol which increased the first five

days with a rate approximately 10 times slower (0.042 mg/dL)

than the respective increase rate of 1-propanol, while afterwards it

remained practically stable. Finally, isobutanol and methyl-

butanol increased slowly for twelve days and then remained

stable.

Our results show that 1-propanol and 1-butanol are the main

alcohols that are produced simultaneously with ethanol by

microbes under the applied experimental conditions. The amountsof ethanol and other alcohols produced by E. coli in BHI cultures

under combined aerobical/anaerobical conditions were higher

compared to those produced by

E.

coli in BHI cultures under strict

anaerobic conditions [16]. The observed discrepancies are

attributed to the presence/absence of air. Therefore it is observed

that higher amounts of alcohols are produced by certain microbes

(here

E.

coli) under aerobic conditions.

It is of importance to underline that 1-butanol was produced

during the first five days of incubation, in the presence of air, while

during this period both ethanol and 1-propanol had the higher

production rates; ethanol and 1-propanol continued to accumu-

late, with a decreased production rate, for further 4 and 12 days,

respectively, under anaerobic conditions. To explain these results

the following aspects should be considered: (i) ethanol can be

produced from all the available postmortem substrates but with

higher rates and yields from carbohydrates; (ii) 1-propanol and 1-

butanol (and the other higher alcohols) could be produced from all

the available postmortem substrates through branched biochemi-

cal pathways that depend on glucose metabolism; and (iii) 1-

propanol, isobutanol and methyl-butanols are produced using

amino acids as substrates [20]. Therefore, it should be concluded

that carbohydrates (as the preferable substrate) were consumed by

the microbes during the aerobic phase of growth, generating

mainly ethanol, 1-propanol and 1-butanol. As carbohydrates were

being depleted from the medium, other available substrates were

consumed continuing to generate higher alcohols (1-propanol,

isobutanol and methyl-alcohols) and ethanol in line with previous

suggestion [20].

3.2. Formulation of models for ethanol production by E. coli

3.2.1.

Statistical

evaluation

of

volatiles

All volatiles during the first 5 days follow a linear approxima-

tion (r 2 > 0.9, not shown here) with the exception of ethanol. Forthe next days (6–30), MLR is not able to successfully fit a similar

linear model (smaller

r 2 value) regarding all variables with the

notable exception of 1-propanol. Probably, 1-propanol plays a

significant role in the successful model prediction while all data is

better to be treated simultaneously since for the first 5 days, data is

ambiguous regarding the variance. By performing a principal

component analysis (PCA) for the whole data to determine how

original variables are projected to a smaller set of underlying

variables, it becomes evident that ethanol explains 99% of the total

variance while the remaining 1% is explained by 1-propanol.

Table 1

Alcohols concentration produced during the 30 days incubation period of E. coli in BHI culture medium at 25

8C under aerobic (days 1–5) and anaerobic (days 6–30)

conditions.

Day Ethanol (g/L) 1-Propanol (mg/dL) Isobutanol (mg/dL) 1-Butanol (mg/dL) Methyl-butanol (mg/dL)

0

0

0

0

0

0

1 0.49 1.12 0.01 0.1 0.03

2 0.48 1.33 0.01 0.15 0.03

3 0.50 1.50 0.01 0.18 0.04

4 0.52 1.81 0.01 0.19 0.04

5 0.55 2.08 0.02 0.21 0.05

6 0.53 2.05 0.02 0.21 0.05

7 0.56 2.18 0.02 0.22 0.06

8 0.59 2.30 0.02 0.23 0.04

9 0.61 2.33 0.02 0.23 0.05

10

0.62

2.85

0.02

0.24

0.06

11 0.58 2.67 0.02 0.23 0.06

12 0.60 2.87 0.03 0.24 0.08

13 0.63 3.18 0.03 0.24 0.08

14 0.60 2.63 0.03 0.23 0.08

15 0.58 2.78 0.02 0.23 0.07

16 0.61 3.04 0.03 0.23 0.11

17 0.61 3.22 0.03 0.23 0.07

18 0.62 3.01 0.03 0.23 0.07

19 0.62 3.15 0.03 0.23 0.07

20

0.63

3.47

0.03

0.24

0.08

21 0.62 3.23 0.03 0.24 0.08

22 0.62 3.30 0.03 0.22 0.06

23

0.61

3.18

0.03

0.24

0.07

24 0.61 3.07 0.03 0.24 0.08

25 0.61 3.08 0.03 0.23 0.07

26 0.61 3.16 0.03 0.23 0.08

27 0.61 3.56 0.03 0.23 0.09

28 0.60 3.13 0.03 0.23 0.07

29 0.61 3.20 0.03 0.24 0.08

30 0.62 3.63 0.03 0.24 0.09

V.A. Boumba et al. / Forensic Science International 232 (2013) 191–198 193



Therefore, it is shown again that the most important variations

arise from ethanol and 1-propanol. Finally, by subtracting one by

one variable, it is concluded that isobutanol and methyl-butanol

are the variables that do not significantly contribute to the total

variation.

3.2.2.

Modeling

whole

data

By performing a PLS model the descriptors relevance becomes

also evident as it is shown in Fig. 2A. The significance of each

alcohol in building the mathematical models is in relevance with

its produced amount.

The corresponding model (r 2 = 0.90) is described by Eq. (1A):

Ethanol ¼ 0:05 1-propanol þ 1:13 isobutanol þ 0:95

1-butanol 1:60 methyl-butanol þ 0:31 (1A)

By modeling the data with only the most significant variables

(1-propanol and 1-butanol) the prediction shows a considerably

satisfactory linear correlation (r 2 = 0.75), indicating the power of

these two alcohols as descriptors of the process, as it is shown in

Fig. 2B. Therefore we obtain the following model:

Ethanol ¼ 0:05 1-propanol þ 0:53 1-butanol þ 0:32 (1B)

3.2.3.

Modeling

data

from

day

1

to

5

If we analyze the data separately for the first 5 days of aerobical

incubation, we see that the ethanol concentration is heavily

dependent on 1-propanol, followed by isobutanol, and then by 1-

butanol concentration (Fig. 3). The variance of methyl-butanol is of

least significance. The relevant PLS model is described by the Eq. (2):

Ethanol ¼ 0:07 1-propanol þ 3:77 isobutanol 0:26

1-butanol þ 0:07 methyl-butanol þ 0:39 (2)

3.2.4. Modeling data from day 6 to 30

Using similar methodology and the data for the anaerobic

cultivation period from day 6 to day 30 the PLS model is as

described by Eq. (3):


1-butanol 1:62 methyl-butanol þ 0:14 (3)

The descriptors relevance shows again the significance of 1-

propanol and 1-butanol in describing the process which is very

similar with the whole dataset (Fig. 4).

3.2.5. Validation modeling with PLS

Validation modeling was performed by creating a small dataset

of 13 randomly selected values of measurements made every 3

days (validation dataset). The rest of the data values were used as

the training dataset. The resulted PLS model is described by the

following equation:


1-butanol 1:74 methyl-butanol þ 0:29

This equation was applied to the validation dataset with

r 2 = 0.93 showing that the model for the whole dataset can indeed

successfully describe the ethanol production from E. coli under the

applied experimental conditions confirming our results.

3.2.6. Aspects of microbial ethanol production modeling

The models for estimating ethanol production by E. coli under a

combination of aerobic/anaerobic conditions were presumably

correlated to 1-propanol and 1-butanol, as the relevant descrip-

tor’s significance revealed. This result is in discordance with the

models constructed previously for E. coli under strict anaerobic

conditions, where the main descriptors of ethanol modeling were

1-butanol followed by methyl-butanol. On the other hand, theresult is in concordance with the models constructed previously

for C. perfringens and C. sporogenes [16].

It is worth mentioning that 1-propanol [6,8–10] and 1-butanol

[7] have been recognized, in previous studies by other authors to

be correlated with the postmortem ethanol production basically in

qualitative terms. Our results confirm and enhance the significance

of the presence of 1-propanol and 1-butanol as main indicators of

microbial ethanol production and further, recognize them as the

main descriptors of the quantification process. The relevance of

both these alcohols as descriptors of ethanol modeling is so

powerful that the model constructed by using only these two

variants is quite satisfactory and in agreement with the general

consideration that the simplest the model the easier its applica-

tion.

3.3. Applicability of the models to death-related forensic cases

3.3.1. Real postmortem cases

The applicability of the models presented in this report was

tested in 60 postmortem cases. The cases were selected by

reviewing retrospectively our chromatogram archives and select-

Fig. 2. (A) Four descriptors (4D) model and (B) two descriptors (2D) model for ethanol production by E. coli by analyzing the whole dataset for the 30 days of incubation.




ing those that had positive blood alcohol concentrations

(BAC 0.10 g/L) and co-detection of higher alcohols and 1-butanolduring the original ethanol analysis. The concentrations of 1-

butanol and higher alcohols were calculated for the selected cases.

Cases were classified according to the manner of death – as

resulted from the retrospective review of the forensic pathologist’s

report – as natural (11 cases, 18.3%), violent (14 cases, 23.3%) or

undetermined (35 cases, 58.3%) cases. Also, it was revealed that 58

out of the 60 samples were from corpses with putrefaction, one

from a corpse with extended trauma and one from a totally

carbonized body. In Table 2 are presented the measured BACs, the

estimated ethanol concentrations after applying each model

(Eqs. (1A), (1B), (2) and (3)) and the relative standard error for

each one of the selected cases. The higher acceptable standard

error (in order to consider successful the application of the models)

in the estimation of the produced ethanol when compared to themeasured original BACs, was selected to be 40%, the same as in our

previous relevant study [16].

The model described by Eq. (1A) estimated successfully the

microbial produced ethanol in 24 out of the 60 cases (38%), the

model described by Eq. (2) estimated successfully the microbial

produced ethanol in 16 out of the 60 cases (25%), and the model

described by Eq. (3) estimated successfully the microbial producedethanol in 22 out of the 60 cases (35%). However, the simplest

model, described by Eq. (1B) that was constructed by only two

descriptors 1-propanol and 1-butanol was applied successfully in

the majority of cases (26 out of 60 cases, 42%).

The overall picture was that at least one of the current models

(Eqs. (1A), (1B), (2) and (3)) were applied successfully in: 41 out of

the 60 cases (68%), 39 of them with putrefaction (39/41, 95%); in

28/43 cases (65%) with BAC lower than 0.7 g/L; and, in 13 out of 17

cases (76%) with BAC higher than 0.7 g/L. These results are

consistent with the general expressed consideration that decom-

position is an aggravating factor for postmortem ethanol produc-

tion and, in line with the statement that concentrations of ethanol

lower than 0.7 g/L are most probably due to microbial ethanol neo-

formation [2,21,22].

3.3.2. Postmortem blood-derived microbial cultures

Post-mortem blood samples from seven autopsy cases were

used to inoculate normal human blood, with and without

additional glucose, as described in Section 2.2. The initial glucose

Fig. 3. Four descriptors (4D) model for ethanol production by E. coli by analyzing the data for the first five days of incubation under aerobic conditions.

Fig. 4. Four descriptors (4D) model for ethanol production by E. coli by analyzing the data from day 6 to day 30 of incubation under anaerobic conditions.




concentration of the spiked blood samples was chosen to be

200 mg/dL in order to be the same with the glucose content of the

BHI culture medium. The selection of cases was randomized

amongst routinely autopsied corpses with obvious signs of

putrefaction at autopsy. The characteristics of the selected cases

(microbes detected, original BACs, estimated BACs and relative

standard error ranges after applying the models to the autopsy

samples) and, the results after applying the models described by

Eqs.

(1B)

and

(2)

to

the

inoculated

samples

for

each

case

(mean

estimated BACs and standard deviations, relative standard error

ranges) are presented in Table 3. Five out of the seven blood

samples carried microbial strains (E. coli, Enterococcus faecalis,

Klebsiella species) commonly found in human corpses [1,23].

Clostridium species were not identified in blood samples from cases

1, 5 and 6, while for the cases 2, 3, 4 and 7 the results were

inconclusive. Four out of the seven blood samples were positive for

ethanol and other alcohols during the original ethanol analysis

(these

were

presented

as

cases

15,

37,

50

and

59

in

Table

2).

When

Table 2

Application of each model constructed for E. coli (Eqs. (1A), (1B), (2) and (3)) in postmortem cases to calculate the microbially produced ethanol. The original ethanol

concentration measured for each case along with the manner of death are also provided.

Case no. Manner of death Measured ethanol (g/L) Estimated ethanol (g/L) Relative standard error (E %)

Eq. (1A) Eq. (1B) Eq. (2) Eq. (3) Eq. (1A) Eq. (1B) Eq. (2) Eq. (3)

1 Undetermined 0.10 0.35 0.37 0.45 0.17 244 259 337 68

2 Undetermined 0.10 0.61 0.63 0.77 0.41 489 504 637 294

3 Natural 0.16 0.59 0.45 1.01 0.25 268 184 530 58

4 Natural 0.16 0.35 0.36 0.44 0.17 113 123 171 3

5 Violent 0.19 0.44 0.45 0.58 0.26 135 138 208 366 Natural 0.20 0.33 0.34 0.42 0.15 64 70 111 25

7 Violent 0.20 0.60 0.60 0.77 0.39 198 201 283 97

8 Natural 0.21 0.51 0.50 0.71 0.32 145 138 236 52

9 Undetermined 0.21 0.54 0.41 1.00 0.35 158 94 376 66

10 Natural 0.22 0.47 0.48 0.60 0.28 116 121 178 29

11 Undetermined 0.25 0.38 0.40 0.48 0.20 52 57 92 21

12 Undetermined 0.27 0.31 0.32 0.39 0.13 13 19 44 52

13 Violent 0.28 0.68 0.67 0.79 0.53 148 142 187 92

14 Undetermined 0.29 0.49 0.49 0.63 0.30 70 72 121 3

15 Violent 0.33 1.00 0.81 0.55 1.20 200 141 63 261

16 Undetermined 0.33 1.34 0.97 0.72 1.76 304 193 117 433

17 Violent 0.34 0.66 0.62 0.64 0.57 92 81 86 66

18 Undetermined 0.35 0.62 0.52 1.03 0.42 78 49 194 20

19 Natural 0.38 0.31 0.32 0.42 0.14 17 15 10 63

20 Natural 0.39 0.77 0.56 1.34 0.23 98 43 245 42

21 Undetermined 0.39 0.40 0.42 0.51 0.22 2 6 29 45

22 Undetermined

0.42

0.84

0.85

1.05

0.61

101

104

151

4723 Violent 0.42 0.67 0.66 0.88 0.46 59 57 110 9

24 Natural 0.42 0.50 0.52 0.63 0.31 20 23 51 26

25 Natural 0.42 0.38 0.58 0.70 0.52 9 38 67 23

26 Undetermined 0.47 1.11 0.81 2.03 0.87 137 73 333 85

27 Violent

0.52

0.74

0.74

0.95

0.52 43 43 84 1

28 Undetermined 0.54 0.31 0.32 0.39 0.13 44 41 28 76

29 Undetermined 0.58 1.36 0.76 2.97 1.10 135 32 414 90

30 Undetermined

0.59

0.49

0.49

0.64

0.29

18

17 8

50

31 Undetermined 0.60 0.76 0.71 1.07 0.54 27 20 79 9

32 Undetermined 0.60 0.36 0.38 0.52 0.18 40 37 14 70

33 Undetermined 0.61 0.79 0.81 0.98 0.57 29 32 61 7

34 Violent 0.62 1.09 0.96 1.65 0.84 76 55 166 36

35 Undetermined 0.62 0.66 0.68 0.83 0.46 7 9 34 27

36 Undetermined 0.63 1.19 0.93 2.06 0.94 89 48 226 49

37 Undetermined 0.64 0.63 0.61 0.72 0.48 2 5 13 26

38 Violent 0.65 1.02 0.96 1.03 0.95 57 48 58 45

39 Violent 0.66 0.51 0.40 0.91 0.32 22 39 38 51

40

Undetermined

0.66

0.28

0.57

2.15

1.35

57

14 224 104

41 Undetermined 0.68 0.93 0.78 1.20 0.27 36 14 76 139

42 Undetermined 0.69 0.48 0.46 0.68 0.29 30 33 1 58

43 Violent 0.69 0.79 0.54 1.55 0.57 12 24 119 19

44 Undetermined 0.71 0.66 0.57 1.04 0.45 7 19 46 36

45 Undetermined 0.71 0.48 0.49 0.62 0.29 31 32 12 59

46 Natural 0.72 0.75 0.75 1.11 0.09 4 4 54 88

47 Undetermined 0.73 0.79 0.74 1.10 0.57 7 2 50 22

48 Undetermined 0.75 0.96 0.98 1.19 0.73 28 30 59 3

49 Undetermined 0.81 0.63 0.59 1.02 0.12 23 28 25 85

50

Violent

0.84

0.88

0.87

1.15

0.65 5 4 37

21

51 Undetermined 0.87 1.23 1.11 1.76 0.25 41 28 102 72

52 Undetermined 0.91 0.91 0.92 1.14 0.68 1 2 26 25

53 Undetermined

0.94

2.13

0.82

5.42

1.81 127

13 477 93

54 Undetermined 0.98 0.73 0.56 1.30 0.52 26 43 32 47

55 Violent 1.06 0.42 0.44 0.55 0.25 60 59 48 77

56 Undetermined 1.08 0.49 0.49 0.65 0.30 55 55 40 72

57 Violent 2.15 0.98 0.95 1.05 0.85 55 56 51 6158 Undetermined 2.58 1.10 1.00 1.59 0.85 57 61 38 67

59 Undetermined 2.94 0.83 0.80 0.97 0.70 72 73 67 76

60 Natural 3.56 0.78 0.78 1.01 0.56 78 78 72 84




ethanol and other alcohols were produced during the incubation of the inoculated samples the procedure was considered positive and

the applicability of the models was tested. Therefore the procedure

was positive only for two out of the seven tested postmortem

bloods (cases 1 and 2 from Table 3).

The application of the current models for the original autopsy

blood of the first case, where

E.

coli was identified, gave acceptable

standard errors (selected to be

<40%). In the inoculated blood

samples in the presence of additional glucose higher amounts of

ethanol were produced and, the models gave better scores when

applied to these samples compared to the inoculated blood

samples without additional glucose (Table 3). These results show

that the current models could be used to estimate neo-formed

ethanol by

E.

coli either under unspecified environmental

conditions or in laboratory conditions. The observed discrepanciesshould be apparently attributed to the differences in the glucose

content of the medium and possibly to differences in the

succession of microbes in the inoculated blood samples compared

to the original blood.

In the second case the models estimated that only a portion of

the detected ethanol could be of microbial origin. Since E. faecalis is

not an ethanol producing microorganism [16] we should assume

that another microbe (not identified) was activated in the original

blood, from death to autopsy, and then during incubation of the

inoculated samples. In the inoculated blood samples with

additional glucose, more ethanol was produced compared to the

samples without additional glucose. Interestingly, in this latter

case, the application of the models succeeded better scores than

those

obtained

for

the

inoculated

samples

with

glucose.

Theseresults show that the current models could be used successfully to

estimate the neo-formed ethanol in cases where ‘‘ethanol

producing’’ microbe(s) (different than E. coli) had grown either

under unspecified environmental conditions or under laboratory

conditions.

In the autopsy blood samples from cases 3 and 4,

Klebsiella

species had produced the alcohols to each autopsy blood sample.

Previously, it was reported that Klebsiella pneumoniae was capable

of producing ethanol in urine spiked with glucose, by fermentation

at 35

8C [24]. However, the application of the current models was

within acceptable standard error range only in case 4 (Table 3). The

results suggest that in cases where Klebsiella species were

activated, occasionally, the models could be used effectively.

Alternatively,

we

cannot

exclude

the

possibility

that

more

microbe(s) could have grown to each original blood, and hadproduced the alcohols. Finally, the inoculation procedure was

negative for cases 3 and 4, probably indicating that the ‘‘ethanol

producing’’ microbes that generated the alcohols in the original

blood (Klebsiella species or other) could not been regenerated to

the inoculated samples under the applied experimental conditions.

Postmortem blood samples that were negative for ethanol in the

original volatile analysis (cases 5–7) did not produce alcohols during

incubation of the inoculated samples, irrespectively whether

microbes had been detected (case 5) or not (cases 6 and 7). For

these last three cases it can be concluded that there were not present

‘‘ethanol producing’’ microbes in the autopsy bloods and, conse-

quently, there was not alcohols production during the incubation

period of the postmortem blood derived cultures.

In general, these results indicate that whenever a blood sampleis contaminated with microbe species that are ‘‘ethanol produ-

cers’’, a profile of ethanol and other alcohols would be generated if

the conditions are favorable for microbial growth. In such a case

the current models show a potential for application, irrespectively

of the activated microbe(s). Influencing factors appear to be the

culture composition and more specifically the glucose content, the

conditions of microbial growth and probably, the succession of

microbes.

3.3.3. Aspects, limitations and outcomes of the application of models

The working hypothesis for our study is that although the

postmortem or putrefactive conditions could be extremely

different and variable among different cases, the patterns of other

alcohols

would

follow

more

or

less,

in

qualitative

and

quantitativeterms, the ethanol production, since the biochemical pathways of

their microbial production are interactive [20]. The patterns of

produced ethanol and other alcohols, under controlled experi-

mental conditions, could be described by mathematical equations

(models); the patterns of ethanol and alcohols produced under

different, real conditions, could be approximated by the models,

and this is why ethanol estimation should be made within an

acceptable standard error.

Ideally, a model should exist for every postmortem case

(predisposing that it was constructed under the same conditions)

which is impossible, since the conditions could not be defined

accurately. In our view, each model represents a ‘‘tool’’ which could

be used as an alternate choice to estimate the microbially produced

ethanol

in

real

cases.

In

every

given

case,

the

effectiveness

of

each

Table 3

Characteristics of the autopsy bloods used to inoculate normal human blood (original BACs, estimated BACs and relative standard error ranges (jE %j)) and results for the

inoculated samples with and without additional glucose in each case (produced ethanol concentration, relative standard error ranges after applying the models described by

Eqs. (1B) and (2), respectively).

Case Microbes detected BAC (g/L) Estimated

BAC range (g/L)

Range

of jE %j

Fermentation experiment

Blood without glucose Blood with glucose

Produced

ethanol

(g/L),

mean

SD

Range of jE %j

(Eqs.

(1B)

and

(2))

Produced ethanol

(g/L),

mean

SD

Range of jE %j

(Eqs.

(1B)

and

(2))

1 E. coli, E. faecalis 0.64 0.48–0.72 2–26 0.17

0.06 26a 0.69

0.10 27–40b

2 E. faecalis 2.94 0.71–0.97 67–76 0.76

0.11 0–40, 1–27 1.05

0.12 31–40, 3–35

3 K. pneumoniaea,

E. faecalis

0.33 0.55–1.20 63–261 0 – 0 –

4 Klebsiella spp.,

E. faecalis

0.84 0.65–1.15 4–37 0 – 0 –

5 E. faecalis 0 0 – 0 – 0 –

6 ND 0 0 – 0 – 0 –

7 ND 0 0 – 0 – 0 –

Abbreviation: ND, none (microbe) detected.a This value represents the best score achieved by applying the simplest model described by Eq. (1B).b Values resulted for the simplest model described by Eq. (1B).




model in achieving the goal is different (due to the different

postmortem conditions, resulting in different alcohol patterns);

thus, one ‘‘tool’’ could be more effective and accurate than the

others for each case. Incidentally, all the proposed so far models,

these presented herein, as well as, those presented in our previous

relevant study [16], were applied successfully for 57 out of 60 cases

presented in Table 2. Nevertheless, lack of adequate evidence in

respect to the origin of ethanol for these cases does not allow a

definite conclusion, although putrefaction and extensive trauma of

the body are recognized aggravating factors for ethanol production

[3,4,21,25,26].

4. Concluding remarks

The present approach, approximates the problem of microbial

ethanol production with a novel, simple methodology. The models

are suggested as tools which could make feasible the quantification

of the microbial neo-formed ethanol in postmortem cases. The

alcohols 1-propanol and 1-butanol are proven consistent with

microbial production of ethanol and the two most significant

alcohols in the modeling process. Nevertheless, given the

complexity of the human body decomposition and the co-existing

microbial

activity,

our

results

point

out

that

the

more

models

areavailable the more possible is one of them to estimate adequately

the postmortem ethanol in a given case. Of course, since the extent

of ethanol production in each case cannot be defined, we cannot

conclude, yet, which is the most suitable model for each case. Thus,

ongoing work should be conducted before suggesting the adequate

and reliable application of any model to real cases.

Acknowledgment

We thank Professor Stathis Frilligos for critical reading of the

manuscript.

References

[1] J.E.L. Corry, Possible sources of ethanol ante- and postmortem: its relation to thebiochemistry andmicrobiology of decomposition, J. Appl. Bacteriol. 44 (1978) 1–56.

[2] C.L. O’Neal, A.Poklis,Postmortem production of ethanoland factors thatinfluenceinterpretation: a critical review, Am. J. Forensic Med. Pathol. 17 (1996) 8–20.

[3] K. Ziavrou, V.A. Boumba,T. Vougiouklakis, Insights into the originof postmortemethanol, Int. J. Toxicol. 24 (2005) 69–77.

[4] F.C. Kugelberg, A.W. Jones,Interpretingresults of ethanol analysis in postmortemspecimens: a review of the literature, Forensic Sci. Int. 165 (2007) 10–29.

[5] S.M. Petkovic, M.A. Simic, D.N. Vujic, Postmortem production of ethanol indifferent tissues under controlled experimental conditions, J. Forensic Sci. 50(2005) 204–208.

[6] R. Nanikawa,K. Ameno, Y. Hashimoto, K. Hamada, Medicolegal studies on alcoholdetected in dead bodies – alcohol levels in skeletal muscle, Forensic Sci. Int. 20(1982) 133–140.

[7] W. Gubala, n-Butanol in blood as the indicator of how long a dead body lay inwater, Forensic Sci. Int. 46 (1990) 127–128.

[8] S. Felby,E. Nielsen, Congener production inbloodsamples duringpreparationand

storage,

Blutalkohol 32 (1995) 5–58.[9] F.Moriya, Y.Hashimoto,Postmortemproduction ofethanol andn-propanol inthebrain of drowned persons, Am. J. Forensic Med. Pathol. 25 (2004) 131–133.

[10] J. Furumiya, H. Nishimura, A. Nakanishi, Y. Hashimoto, Postmortem endogenousethanol production and diffusion from the lung due to aspiration of wood chipdust in the work place, Leg. Med. (Tokyo) 13 (2011) 210–212.

[11] B.L. Soderberg, R.O. Salem, C.A. Best, J.E. Cluette-Brown, M. Laposata, Fatty acidethyl

esters. Ethanol metabolites that reflect ethanol intake, Am. J. Clin. Pathol.119 (2003) S94–S99.

[12] S. Aradottir, S. Seidl, F.M. Wurst, B.A. Jonsson, C. Alling, Phosphatidylethanol inhuman organs and blood: a study on autopsymaterial and influences by storageconditions, Alcohol Clin. Exp. Res. 28 (2004) 1718–1723.

[13]

R.D. Johnson, R.J. Lewis, D.V. Canfield, K.M. Dubowski, C.L. Blank, Utilizing theurinary 5-HTOL/5-HIAA ratio to determine ethanol origin in civil aviation acci-dent victims, J. Forensic Sci. 50 (2005) 670–675.

[14] G. Høiseth, R. Karinen, A.S. Christophersen, L. Olsen, P.T. Normann, J. Mørland, Astudy of ethyl glucuronide in post-mortem blood as a marker of ante-mortemingestion of alcohol, Forensic Sci. Int. 165 (2007) 41–45.

[15] B.M. Appenzeller, M. Schuman, R. Wennig, Was a child poisoned by ethanol?

Discriminationbetween ante-mortemconsumptionand post-mortemformation,Int. J. Legal Med. 122 (2008) 429–434.

[16] V.A. Boumba, V. Economou, N. Kourkoumelis, P. Gousia, C. Papadopoulou, T.Vougiouklakis, Microbial ethanolproduction: experimental studyandmultivari-ate

evaluation, Forensic Sci. Int. 215 (2012) 189–198.[17] K.J. Ryan, C.G. Ray (Eds.), Sherris Medical Microbiology, 4th ed., McGraw Hill,

Norwalk, CT, 2004.[18] A.W. Jones, L. Hylen, E. Svensson, A. Helander, Storage of specimens at 4 8C or

addition of sodiumfluoride (1%)prevents formationof ethanolin urineinoculatedwith

Candida albicans, J. Anal. Toxicol. 23 (1999) 333–336.[19] P. Saukko, B. Knight, The pathophysiology of death, in: Knight’s Forensic Pathol-

ogy, Oxford University Press Inc., New York, 2004, pp. 52–97 (Chapter 2).[20] V.A. Boumba, K. Ziavrou, T. Vougiouklakis, Biochemical pathways generating

post-mortem volatile compounds co-detected during forensic ethanol analysis,Forensic

Sci. Int. 174 (2008) 133–151.[21] R. Hanzlick, Ethanol concentration in decomposing bodies: another look, less

concern, Am. J. Forensic Med. Pathol. 30 (2009) 88–89.[22] R.E. Zumwalt, R.O. Bost, I. Sunshine, Evaluation of ethanol concentrations in

decomposed bodies, J. Forensic Sci. 27 (1982) 549–554.

[23] J.A. Morris, L.M. Harrison, S.M. Partridge, Post mortem bacteriology: a re-evalua-tion,

J. Clin. Pathol. 59 (1) (2006) 1–9.[24] H.A. Sulkowski, A.H. Wu,Y.S. McCarter, In-vitro production of ethanolin urine by

fermentation, J. Forensic Sci. 40 (1995) 990–993.[25] D.M. Butzbach, Theinfluence of putrefactionand samplestorage on post-mortem

toxicology results, Forensic Sci. Med. Pathol. 6 (2010) 35–45.[26]

G. Scopp, Postmortem toxicology, Forensic Sci. Med. Pathol. 2 (2010) 314–325.


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