ModelingmicrobialethanolproductionbyE.coliunderaerobic/ anaerobicconditions:Applicabilitytorealpostmortemcasesandto postmortembloodderivedmicrobial cultures Vassiliki A. Boumba a, *, Nikolaos Kourkoumelis b , Pana giota Gou sia c , Van gel is Economou c , Chri ssan thy Papadopoulou c , The odore Vou giouklakis a a DepartmentofForensicMedicine&Toxicology, Medical School, UniversityofIoannina, 45110Ioaninna, Greece b DepartmentofMedical Physics, Medical School, University ofIoannina, 45110 Ioaninna, Greece c DepartmentofMicrobiology, Medical School,UniversityofIoannina, 45110Ioaninna, Greece 1.Introduction Determination ofbloodalcohol concentration (BAC)inpost- mortemcasesispartofthedeathinvestigation processsince ethanol might beacausalorcontributory factortothemannerofdeath. Theaccuratescientificinterpretation oftheethanol analysis results presentsacritical taskincaseswheremicrobial ethanol neo-formation issuspected, or,alternatively, theoriginofpostmortemethanol (antemortemingestionormicrobial produc- tion)isquestioned. Inordertoachieveafeasibleaccuracyininterpreting theresults ofpostmortemethanol analysis different approaches havebeen suggested. Theanalysis ofmultiplespecimens andfrommultiple samplingsitescouldreveal atypical distribution ofethanol throughout thedifferent compartments ofthedeadbodyand thuscouldbeindicative ofpostmortemethanol neo-formation [1– 5].Thedetermination ofvariouslowmolecular weightvolatiles in postmortemspecimens issuggestedasacriteriontospecifythe originofthemeasuredpostmortemethanol and, ifcertainvolatiles aredetectedthenpostmortemethanol productionshouldbe suspected [3,4,6–10] .Finally, thedetermination ofvarious non- oxidativemetabolites ofethanol isusedtodistinguish theante mortemingestionfromthepostmortemsynthesis ofethanol [4,11–15] . Commonfeatureintheaforementioned approaches is thatthedocumentation, ornot,ofthemicrobially produced ethanol arisesinqualitative terms. Recentlywereportedtheformulation ofmathematical models forcalculating themicrobial neo-formedethanol instrict anaerobic cultures ofthebacterial strainsEscherichiacoli, Clostridiumperfringens, andClostridiumsporogenes[16]. This approachwasthefirstapproximation tothequantification ofthemicrobial ethanol productionincaseswhereotherlow molecular weight alcoholswereproducedsimultaneously with ethanol. ForensicScienceInternational232(2013)191–198 ARTICLEINFO Article history: Received26April2013 Recei ved in re vi sed form 19 July 2013 Accepted26July2013 Avai labl e onl ine 7 Augus t 2013 Keywords: Postmortemethanol Postmortemblood Multiplelinearregression Autopsy E.coli Microbialethanol ABSTRACT The mathematical modeli ng of the mi crobial eth ano l production und er str ict anaerobic exp eri mental conditi onsfor some bact eri al spec ies has beenpropo sedby ourresear ch group as the firstappro xima tion to the quant i fication of the microbial eth anol pr oduction in cas es where other alcohols were produced simulta neou sly wit h ethanol . T he pr es ent st ud y a im s t o: (i ) s tu d y the mi cr ob i al e th ano l pr od uc t io n by Esc her ichia coli under controlle d aerobi c/a nae rob ic condi ti ons; (ii ) model the corre latio n between the mi crobial produced ethanol andthe ot herhigher alc ohol s; and(iii ) test theirappl icabi li ty in: (a)real postmortem cas es that had po si ti ve BACs (>0.10 g/ L) and co-d etec ti on of hi gher al cohols and 1- butanol duri ng the or ig inal ethanol anal ysis and (b) po st mort em bl ood deri ve d mi cr obial cultur es unde r aerobi c/ anaero bi c contro lled experi mental condit ions. The st at is tical ev al uation of the result s reveal ed that the formul at ed mo de ls were pr esumably cor rel ated to 1-propanol and 1-butan ol whic h were recognizedas the mos t signific ant des crip tor s of the modeli ng process. The signific anceof 1-propanol and1-butan ol as descri ptors was so powerf ul thatthey coul d be used as the only indep end ent vari abl es to creat ea simpl e and sat isf act ory model . The current modelsshowed a pot ential forapplic ation to esti mat e microbial ethanol– wit hin an acce ptable stan dard error – in va ri ous test ed ca ses where et hanol and ot her al cohols have been pr oduc ed fr om di ff erent microbes. 2013Els evier Ir ela nd Ltd . Al l ri ghts reserved. * Correspondingauthor.Tel.:+302651007724;fax:+302651007857. E-mailaddresses: [email protected], [email protected](V.A.Boumba). ContentslistsavailableatScienceDirect Forensic Science Int ernational journal homepage: www.elsevier .com/locate/forsciint 0379-0738/$–seefrontmatter2013ElsevierIrelandLtd.Allrightsreserved. http://dx.doi.org/10.1016/j.forsciint.2013.07.021
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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.
V.A. Boumba et al. / Forensic Science International 232 (2013) 191–198194
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.
V.A. Boumba et al. / Forensic Science International 232 (2013) 191–198 195
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 %)
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).
V.A. Boumba et al. / Forensic Science International 232 (2013) 191–198 197
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.
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