1. 1
Alkaline Phosphatase Enzyme Activity
Measurement as a robust on-line
Monitoring Assay for Water Quality
Assessment
Zina Al-Saffar, Joep Appels, Aleksandra Nnezev
microLAN Company and Het Water Laboratorium, The Netherlands
Abstract
microLAN company is specialized in early warning systems for water quality monitoring. One of
the different biosensors types that are made by the company is BACTcontrol. BACTcontrol is an
enzymatic biosensor that measures the metabolism activity of Alkaline Phosphatase enzyme that
produced in most well known aquatic microbial cells using the (MUP) fluorescent substrate. In order to
compare the results obtained from the BACTcontrol biosensor, the relationships between the rate of MUP
hydrolysis and five different standard microbial analysis that usually applied to assess water quality were
investigated. Within the similar type of water, BACTcontrol correlated well with the FCM cells counts,
ATP, ELF-microscopic cells count and the Microscopic live cells count using viable stains, (R2
= 0.99,
0.89, 0.83 and 0.92 respectively). There was considerable loss of correlations after data from different
water types compared together (e.g. Tap water and natural fresh water). No correlation was observed
between BACTcontrol enzymatic measurements and the traditional HPC assay (R2
= -0.32). The
epifluorescence microscopic and flowcytometry bacterial counts paralleled but microscopic counts always
gave lower counts than FCM (<21%). In general, BACTcontrol can be used to trigger alarms when
significant changes are seen in the environment. The alarm can be used to take an automatic sample
which can be properly stored and used for later identification and quantification in the laboratory of the
microbiological change of the sample.
1. Introduction
It is necessary to guaranty the safety
of the water for consumption, as it is critical
to improve livelihood security, economic
growth and reduce health risk and weakness
in communities. It has therefore been
described as a key target within the
millennium Goals [1] [2]. Engineered
ecosystems such as drinking water
production and wastewater treatment plants
follow daily routines in operation and may
suffer from short-term defects or may
expose to dynamic changes in raw water
composition [3]. Environmental ecosystems
such as oceans, groundwater and lakes are
subject to daily or seasonal variations or
sudden events (e.g., acute pollution) [4].

2. 2
Thus, monitoring microbial dynamics in
engineered and environmental aquatic
ecosystems is a key step towards a better
understanding of the driving forces and
consequences of changes in bacterial
concentrations and community composition
[5]. Nowadays, microbial water quality is
most often monitored through traditional
techniques. These methods, especially the
culture-dependent are labor-intensive and
time-consuming as the results are usually
available 1 to 3 days after sampling.
Furthermore, cultivation based methods are
usually hugely underestimating the real
number of target organism. Hence, there is a
need for a rapid, cultivation-independent,
objective and easy to use method to
characterize the microbial community of
drinking water quantitatively and
qualitatively. Promising tools are biosensors.
Biosensors in water quality offer advantages
over current analytical methods includes an
on-site real-time analysis which can avoid
sample degradation, high selectivity, high
specificity, relatively low cost of
construction and storage and the ability to
measure samples with minimal sample
preparation [6] [7].
Many heterotrophic microorganisms
maintain their growth by producing
intercellular and extracellular enzymes in
order to provide low molecular weight
organic compounds that could be uptaken
into the cells from high molecular weight
organic compounds which cannot be directly
utilized by bacteria [8]. Microbial enzymes
are, therefore, directly related to the
concentrations and ratios of limiting
nutrients, and may be sensitive indicators of
organic pollution in aquatic environments
[9]. Enzyme based-tests are sensitive, simple
to preform and in most cases do not require
a conformation step. ALP is a cell-surface
bounded enzyme, abundantly present in
nature and found in different human body
tissues as well as animal and in many
aquatic microbes. Phosphatase enzyme
hydrolyzes phosphoric acid monoesters to
produce phosphate and the corresponding
alcohol [10]. The importance of this enzyme
in biological systems and its abundance in
nature has made ALP activity assessments
one of the most commonly performed
enzymatic tests [11]. More recently, ALP
enzyme activity has been exploited as a
rapid assay for the validation of the milk
product pasteurization without any
cultivation step [12]. In addition, ALP
activity measurement was applied for water
quality assessment and as a sensitive
indicator of organic pollutions in aquatic
ecosystem in various studies [13] [14] [4]
[15] [16]. One of the extensively employed
assays to detect ALP activity is the
fluorometric method. This method is based
on measuring the fluorescence associated
with the formation of 4-methylumelliferone
(MUF) from the weekly fluorescent
substrate 4-methylumbelliferyl phosphate
(MUP) upon binding with ALP enzyme [17]
The objective of this study which
was carried at microLAN company in
Waalwijk and supported by HWL (Het
Water laboratorium, Haarlem), was to
compare the measurement of the ALP
activity performed by BACTcontrol
biosensor with different standard microbial
analysis that usually applied for the
evaluation of general microbial water
quality and to measure its efficiency as a

3. 3
tool that can be used to detect changes in
water quality.
2. Material and Methods
Samples Collection.
In order to compare measurements of
ALP activity from BACTcontrol
measurements for alkaline phosphatase
activity with different validated laboratory
methods, four different types of water were
analyzed in this study. Namely, non-
chlorinated household tap water that was
collected from the building where
microLAN Company is located (Waalwijk,
Netherlands), the water is supplied by
Brabant Water. Surface lake water (Zandput
Lake, in the vicinity of Oosterhout,
Netherlands) and two industrial water
samples. The industrial water samples were
collected from plant company that uses tap
water to germinate plant seeds. The
company uses tap water in the early first
stage of germination, later and during the
different production process line, the water
is collected, desalinated with reverse
osmosis and reused again. In general, all
samples were collected in 1L sterilized
plastic bottles containing 25g/L Trisodium
Nitrilotriacetate (NTA) and 20g/L Sodium
Thiosulfate (Na2S2O3) to neutralize the
residual chlorine. Stored on ice in a cooling
box, transported to the laboratory and
analyzed within 5 h after sampling.
Heterotrophic Plate Count.
Industrial and surface water samples
were diluted in decimal steps (10-1
– 10-3
)
with autoclaved tap water. Tap water was
used without dilution. Water plate count
agar (ISO) (Oxoid, Hampshire, UK) was
prepared according to the instruction
provided by the manufactured company and
kept at 4o
C prior to use. For all tested water
samples, 1ml of the test sample or an
appropriate decimal dilution, are pipetted
into sterile Petri dishes and (14 ml) of sterile
molten, cooled (to 45°C) plate count agar
medium is added followed by gently mixing
to distribute the sample throughout the agar.
Plates were left to harden and then incubated
at 22o
C. Plate colonies were quantified after
72h. All measurements were done in
duplicates.
ATP Measurements.
Total and free ATP were determined
using the Celsis AdvanceTM
luminometer
(Celsis International, Suffolk, UK) and
reagents Celsis LuminEXTM
and Celsis
LuminATETM
, Celsis, Germany). For free
ATP analysis, water sample (100µl),
LuminATE reagent (100µl) and (100µl)
sterile water were automatically combined
together and then luminescence were
measured after 20 s reaction time at 20o
C.
Total ATP were measured by replacing the
(100µl) sterilized water with (100µ)
LuminEXTM
extraction reagent (Celsis,
Germany) to breakdown the microbial cells.
The cell-bound ATP was calculated by
subtracting the total ATP from the free ATP
for each individual sample (cell-bound ATP
= total ATP – free ATP). All samples were
measured in duplicates. Luminescence was
measured in relative light units (RLUs),
which were converted to ATP
concentrations (ng/ml) by conversion factors

4. 4
calculated from a calibration curve of ATP
standards measured on the same day as the
experiment ATP. For the blank control, the
water sample was replaced with 100µl of
autoclaved sterile water.
Staining and Flow-Cytometric
Measurements.
Flow cytometric measurement was
carried out as described by Hammes et al.
(2013) [18]. Working dye solution of SYBR
Green I (200µl, final volume) was prepared
by diluting 10000X SYBR Green I (Sigma-
Aldrich, Life Science, USA) 1:100 in a
hydrous dimethylsulfoxide (DMSO),
combined SYBR Green I and Propidium
Iodide (PI) dye solution was prepared by
mixing (5µl) SYBR Green I (10000X),
(245µl) DMSO and (250µl) of 1mg/ml PI
solution (Sigma-Aldrich, US), to obtain final
volume of 500µl. All working solutions
were stored at -20°C until use. For surface
and industrial water, samples were diluted
1:10 in sterile autoclaved water. Water
samples were divided into sub-samples
(100µl), pre-heated to 37°C for (4min)
before adding the dyes. After pre-incubation
water samples were stained either with a
mixture of SYBR Green I and PI or with
single SYBR Green I dye, followed by 15
min incubation at 37°C in the dark. Prior to
analysis, water samples were diluted 1:10
with 0.1µm (Millex VV, Ireland) Evian
filtered bottled water. Filtered (0.1µm,
Millex VV, Ireland) Evian bottled drink
water was used for control. FCM
measurements were performed using a BD
ACURRI C6 flow cytometer (BD Accuri
cytometers, Belgium), Equipped with a 50
mW laser emitting at a fixed wavelength of
488 nm. Green fluorescence (FL1), was
collected at (533/30 nm), red fluorescence
(FL3), was collected at (670 nm Long pass).
The forward scatters (FSC) was collected on
488 nm to sort the cell according to their
size. The trigger was set on the green
fluorescence channel. The measurements
were calibrated to measure the number of
particles in 50µl of the tested water samples.
All samples data were collected as
logarithmic signals and were acquired on
two-parameter histogram plots. All water
samples were measured in duplicates with
both stains.
Total Epifluorescent Microscopic
Microbial Count using Live/Dead BacLight
Bacterial Viability and Counting Satin.
Viable and damaged bacterial cells
in the tested water samples were enumerated
using SYTO 9 and Propidium Iodide (PI)
fluorescent stains (InvitrogenTM
/Molecular
probes, Lot.672950 USA) that can
differentiate between cells with intact and
damaged cytoplasmic membranes [19].
Water sample volumes ranged between (1-
10 ml) were mixed with Cyto 9 and PI
fluorescent satin (1.5µl fluorescent stain for
each 1ml of the sample water), vortexed for
2 sec and incubated for 15-20 min in the
dark at room temperature. Bacteria were
then concentrated by filtering the water
sample over (0.22 µm) isopore poly carb
membrane filter (MilliPore, Ireland). The
filters containing the concentrated bacteria
were mounted on microscopic slides
(Thermo Scientific, San Francisco, Calif).
Microscopy. Microscopic quantitative
counts were carried out on model BX 40,

5. 5
Olympus fluorescent microscope, equipped
with type U filter cubic unit. Stained
bacteria were viewed with a 100X objective
(1000X total magnification), viable green
fluorescent cells were observed with
excitation/emission of 480/500 nm where
dead red bacterial cells were seen with
excitation/emission of 537/640 nm.
ELF-97 Single Cell level Phosphatase
Staining.
The novel alkaline phosphatase
substrate 2-(5´ -chloro-
2´phosphoryloxyphenyl)-6-chloro-4(3H)
quinazolinone (ELF-97TM
, Molecular
Probes, Thermo Fisher, the Netherlands);
[20] [21] [22], was used to label microbial
cells with alkaline phosphatase activity and
counted by BX 40 fluorescent microscope.
The labeling procedure with ELF-97TM
was
carried out as previously described by
(Dignum et al. 2004) [21]. Sample volumes
(1-10 ml) were filtered over (0.22 µm)
isopore poly carb membrane filter
(MilliPore, Ireland) to concentrate the
bacteria. Bacterial cells on the filter were
fixed by covering the filter with 1-2 ml of
0.1% (w/v) glutaraldehyde and 0.01% (w/v)
formaldehyde (final concentrations) for 30
min at room temperature. The filter was then
washed 5 times with autoclaved sterile water
to remove the fixative solutions. Microbial
cells with alkaline phosphatase activity were
labeled with the ELF-97TM
substrate, by
saturating the filter with 1 ml of the
detection buffer provided by the
manufacturer (Molecular Probes, Thermo
Fisher, the Netherlands), containing a 1:20
dilution of ELFP substrate. After 30 min
incubation at room temperature (20o
C) in
the dark, the reaction was stopped by 100X
dilution by washing the filters with sterile
water and let to dry for 1 min at room
temperature. The filters were then mounted
on microscopic slides (Thermo, Scientific,
San Francisco, Calif). Microscopy. Visual
inspection of the green fluorescent signal
from product, ELF-97 alcohol (ELFA) was
carried out on a BX 40 Olympus
fluorescence microscope with UV
epifluorescence furnishing: excitation filter
(bandpass 366 ± 25 nm)
Bulk Alkaline Phosphatase Enzyme
Activity measurement with BACTcontrol
Biosensors.
4-Methylumbelliferyl-Phosphate
(MUP) was used as the substrate for
measuring alkaline phosphatase activity
[23]. The MUP substrate with a
concentration of (5mM) was dissolved in a
buffer solution consisted of (800 mM)
Glycine (pH 10), (0.5 ml/100 ml) Triton-X-
100, (1.57g/100 ml) Sodium Thiosulfate
Pentahydrate and (0.1% w/v) Sodium azide
added as dry chemical. The detection buffer
was supplied from (microLAN,
Netherlands) and stored at -20°C till used.
For sample analysis, (10-1000ml) of the
tested water sample was automatically
added to (0.25 ml) of the detection buffer
containing the (MUP) substrate, followed by
incubation for 10 min at 45°C to stabilize
the reaction mixture. The total measurement
time was set to 40 min and the alkaline
phosphatase activity was determined by
measuring the fluorescence associated with
the formation of 4-methylumelliferone

6. 6
(MUF) per time and volume (pmol MUF
min-1
100 ml-1
). The increase of fluorescence
is permanently monitored, and the slope of
the signal in the steady state phase is used to
calculate the enzymatic activity by least
square linear regression analysis [24]. The
blank values are determined using the same
procedure used for standard measurements
with the addition of an extra step, in which
the water samples were first filtered with
0.45µm filter (TAMI Ind., France) prior to
the addition of the detection buffer, the
filtered volume for the blank is set to 10ml.
The fluorescence signal of the reaction
product wa
360 nm and emission detection at 450 nm.
Statistical Analysis and Software. Statistical
data evaluations were performed using
Excel (MS Office 2007). Correlation
coefficients (R2
) were calculated using MS
Excel data analysis tool. The correlation
coefficients between BACTcontrol and the
tested laboratory methods were calculated
first between water samples from different
types and again between water samples from
similar types.
3. Results and Discussion
In order to compare the results
obtained from BACTcontrol biosensors and
to determine the possible relationship
between phosphatase activity and microbial
content of the tested water samples, the bulk
ALP enzymatic activity preformed with
BACTcontrol was compared with the
measurements of different methods applied
for water analysis, included: flow cytometry
(FCM), total and intact cell numbers, total
and cell bounded ATP, heterotrophic plate
count (HPC), microscopic total cell count
(TCC) and microscopic ELF-labeled total
cell count for microbial cell with ALP
activity.
Correlation between Bulk ALP Enzymatic
Activity measured with BACTcontrol
Biosensor and Cells Count measured with
FCM.
FCM is a sensitive and rapid method
that can be used along with fluorescent dyes
to enumerate the bacteria in a water sample
with a high degree of reproducibility [18].
The total FCM bacterial cells count in all of
the water samples varied in the range of 1.6-
220 X 105
cell/ml. The intact cells counts
ranged between 1.3- 185 X 105
cell/ml. The
highest total and intact bacterial cells count
were measured in the industrial 1 water
sample and the lowest microbial content was
measured in the tap water sample (Fig. 1).
ALP enzyme activity measured with
BACTcontrol biosensor correlated well with
the total and intact cells concentration
measured with flow cytometer for three of
the tested water samples (samples from
hydro culture production and Tap water),
except for surface water were the ALP
activity measured was higher than the total
and life FCM cell count (Fig.2). The total
ALP enzyme activity determined with
BACTcontrol biosensors for water samples
tested were summarized in (Table.1).
The correlation coefficients (R2
)
calculated between bulk ALP enzyme
activity measured with BACTcontrol and
with total or intact FCM cells concentration

7. 7
for industrial 1, industrial 2 and tap water
samples were (0.97 and 0.99 respectively).
The correlation coefficient calculated
between BACTcontrol and total or intact
FCM cells concentration for all water
samples tested including surface water
sample were (0.36 and 0.4 respectively).
The absence of the correlation in
surface water sample, in the present study,
could be the result of various factors
(physical conditions, nutrient availability,
presence of various compounds such as
humic acids, biocides, and toxins etc.) that
influence enzymatic production and/or
activity. Many studies have reported that
ALP enzyme activity in aquatic microbial
cells is found to be strongly affected by the
concentration of P available in the water and
that is not dependent on the biomass amount
of the micro plankton and bacterioplankton
found in the sample [25] [26]. Additionally,
the high ALP enzyme activity measured in
surface water compared with low FCM cells
concentration may be related to the presence
of clay particles that are common in many
surfaces water. These clay particles can
modify the enzyme activity by forming
aggregates with the organic molecules (e.g.
enzyme) and this formed enzyme-clay
complexes could alter the level of activity.
Todd Tietjen and Robert Wetzel (2003)
reported in their study that adsorption of the
substrate onto clay surfaces results in a
concentration effect and increased enzyme
activity that is associated with clay particles
[27].
Figure 1. Flow cytometry total and intact microbial cells
count. All water samples were stained with SYBR Green I
and PI. Microbial cells stained with SYBR Green I were
enumerated as live cells. Errors bars indicate the
standard deviation of duplicate measurements.
Table 1. ALP enzyme activity data measured with
BACT control biosensor.
Water Sample
ALP enzyme activity
(pmol/min/ml)
Industrial 1 2.94
Industrial 2 0.25
Tap water 0.31
Surface water 3.60
0
50
100
150
200
250
Industrial 1 Industrial 2 Tap water Surface
water
cellscountcell/mlX105
Water Sample
total FCM cells count
Intact FCM cells count

8. 8
Figure 2. Flow cytometry total and life cells concentration
compared with ALP enzyme activity measured with
BACTcontrol biosensor. All water samples for FCM
measurements were stained with SYBR Green I and PI. ALP
enzyme activity was measured using MUP substrate (5mM).
Errors bars indicate the standard deviation of duplicate
measurements.
Correlation between Bulk ALP Enzyme
Activity measured with BACTcontrol
Biosensor and with Total and Cell Bounded
Adenosine Tri-Phosphate Concentrations.
ATP is another rapid method that has
been highlighted several times as a potential
parameter for evaluating the microbial quality of
drinking water with a detection limit of < 0.2 pg
[28] [29] [30]. ATP is the energy currency of
all living cells, and therefore a useful indicator
of microbial viability or as a parameter for
assessing microbial re-growth in drinking water
[31].
The highest total ATP concentration was
measured in industrial 1 water sample (1.07 ng
ATP/ml) and the lowest total ATP concentration
was measured in tap water sample (0.004 ng
ATP/ml), (Fig.3). The cell bounded ATP were
calculated by subtracting the measured total
ATP from the free ATP for each water sample.
The highest percentage of the cell bounded ATP
(98%) was measured in industrial 1 water
sample while the lowest percentage of (61%)
was measured in surface water sample (Fig.4).
Concurrent with the ATP and FCM data, all
viability indicators suggested a higher
percentage of potentially viable cells in
industrial 1 water sample than in other water
samples tested (Fig. 1) and (Fig. 4).
Note that for a straight comparison of viability
data, the intercellular bounded ATP
concentration values (from Fig.4) were set as
100% for all water samples.
Figure 3. Total ATP concentration for different water types.
Total ATP was measured with the enzymatic assay in a
luminometer. All data points are average values of duplicates
samples. Errors bars indicate standard deviation.
Figure 4. Percentage of total to bounded ATP measured in all
of the tested water samples.
0
0.5
1
1.5
2
2.5
3
3.5
4
0
50
100
150
200
250
Industrial 1 Industrial 2 Tap water Surface water
ALPenzymeactivitypmol/min/ml
cellsconcentrationcell/mlX105
water sample
total FCM cell concentration
life FCM cell concentration
ALP enzyme activity (BACT control)
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
Industrial 1 Industrial 2 Tap water Surface
water
totalATPconcnetrationngATP/ml
water sample

9. 9
Figure 5. ALP enzyme activity measured with BACTcontrol
biosensor compared with total and cell bounded ATP
measured with the enzymatic assay in a illuminometer. ALP
enzyme activity was measured using the MUP (5mM)
substrate. Error bars indicate the standard deviation of
duplicate measurements.
As observed in total and life FCM results, ALP
enzyme activities measured with BACTcontrol,
correlated well with total and bounded ATP
measurements for three of the water samples of
the same type. The correlation coefficients
measured between total or bounded ATP for
(Industrial 1, Industrial 2 and Tap water) and
between BACTcontrol were (0.85 and 0.89
respectively), (Fig. 5). Again, the correlations
were not as good as in previous FCM results
when surface water was included in the
calculation and only poor correlations were
observed between bulk ALP enzyme activity
and total or bounded ATP (R2
= 0.2 and 0.17
respectively).
Both ATP and ALP enzyme activity
measurement with BACTcontrol assays are very
rapid but not very specific, in which both assays
do not discriminate neither the type nor the
species of the contaminants. From figure 4, we
can note that the percentage of cell bounded
ATP in surface water sample is low when
compared with other tested water samples,
where the ALP measured with BACTcontrol
was too high, (Fig.5). This is expected as the
ALP enzyme activity measured in surface water
may show associations with several
extracellular organic contaminants (e.g.
enzymes) that may have been produced from
non-microbial origins such as plants, animals,
algae, particles from soil matrix and even humic
compounds. Those contaminants differ in their
enzyme activity level from that produced from
bacterial origin (which is the major contaminant
in tap water). It is also important to note here
that, surface water differ from tap water in its
chemical and biological composition as its raw
untreated water that does not contain any
disinfection residuals and that no harsh end
treatment (e.g., UV- C irradiation) was yet
applied on it. In addition, both ATP and ALP
enzymes levels were found to be affected by the
microbial growth phase and the mineral content
of the water [32] [33]. In other studies, it was
reported that alkaline phosphatase production
level in most marine microbial cells (e.g.
bacteria, algae, yeasts, protozoa) is strongly
related to the inorganic phosphate Pi ( HPO4
2-
)
availability in water and that it can change
seasonally [25] [34]. Thus, making a reasonable
assumption that changes in the physical and the
biochemical parameters are more common in
surface water than in treated tap water, this may
give a good explanation for the differences
between different water types.
0
0.5
1
1.5
2
2.5
3
3.5
4
0
0.2
0.4
0.6
0.8
1
1.2
Industrial 1 Industrial 2 Tap water Surface water
ALPenzymeactivitypmol/min/ml
ATPconcentration(ngATP/ml)
water sample
bounded ATP
total ATP
ALP enzyme activity
(BACT control)

10. 10
Correlation between Bulk ALP Enzyme
Activity measured with BACTcontrol
Biosensor and Microscopic ELF-labeled Cells
Count.
The new single-cell ALP method using
the enzyme-labeled fluorescent (ELF) substrate
is now used in several studies to detect ALP
activity within an individual cell level [35] [36]
. The ALP in the cell reacts with the soluble
ELF substrate (2-(5’-chloro-2’-
phosphoryloxyphenyl)-6-chloro-4-(3H)-quina
zolinone to produce an insoluble yellow-green
fluorescent precipitate at the site of the ALP
enzyme activity, (Fig. 6).
Cells with the generated fluorescent color can
then be detected or enumerated by the
epifluorescent microscope or by flow cytometer.
In our study, a good correlation (R2
= 0.83) was
found between ALP bulk enzyme activity
measured by BACTcontrol and with
microscopic ELF- labeled total cells count
within the same water type (tap water), but this
correlation dropped down (R2
= 0.04) when
surface water sample was included in the
calculation (Fig.7).
The ELF single-cell assay is a qualitative
method that enumerates ALP activity within the
single cell, where the quantitative bulk ALP
Figure 6. Schematic diagram showing differences between the novel ELF-97 and the MUP substrates used to detect and measure
alkaline phosphatase enzyme activity. Upon binding with ALP enzyme, ELF-97 substrate forms a non soluble precipitate at the site of
the enzyme (upper reaction), where with MUP substrate, the reaction product (MUF) is a soluble fluorescent solution that diffuse in
the reaction surrounding away from the enzyme site of production (lower reaction).

11. 11
assay by BACTcontrol biosensors, measures
both the intercellular and the extracellular ALP
enzyme level. This may explain the absence of
correlation between the two assays in surface
water sample as the presence of an extracellular
contaminant is applicable. We should also note
here that, spectrofluorometric measurement
account for changes in labeling intensity due to
both the proportion of cells labeled and the
number of sites per cell. In contrast, microscopy
cannot statistically quantify intensity as ELF-
labeled cells with different active enzyme sites
are enumerated as one cell.
Significant correlations were found
between the ELF single-cell assay and other
quantitative assays used in this study (Table 2),
which support the previous explanation that the
high bulk ALP activity level measured in the
surface water, belonging to the presence of an
extracellular contaminant.
Figure 7. Bulk ALP enzyme activity level measured with
BACT control biosensor compared with microscopic ELF-
labeled cells count. Bulk ALP enzyme activity was measured
using the MUP (5mM) subs
Table 2. Comparison between ELF single- cell assay and
different quantitative assays used for four different water
samples, each test was run in duplicate.
Parameter ELF single-cell sassy
Microscopic total cell count 0.98
Total FCM cell count 0.92
Life FCM cell count 0.88
Total ATP 0.98
Bounded ATP 0.98
R2
–values of the correlation between ELF single-cell
assay and the different quantitative assays used.
Correlation between Bulk ALP Enzyme
Activity measured with BACTcontrol
Biosensor and Heterotrophic Plate Count
(HPC).
The observed level of correlation
between aerobic heterotrophic bacteria on water
plate count agar and ALP enzyme activity
measured with BACTcontrol in our water
samples did not prove to be statistically
significant, (R2
= -0.32), (Fig.8).
Figure 8. Bulk ALP enzyme activity level measured with
BACTcontrol biosensor, compared with heterotrophic plate
count (HPC). Bulk ALP enzyme activity was measured using
MUP (5mM) substrate. Errors bars indicate the standard
deviation of duplicate measurements.
0
0.5
1
1.5
2
2.5
3
3.5
4
0
2
4
6
8
10
12
Industrial 1 Industrial 2 Tap water Surface water
ALPenzymeactivity(pmol/min/ml)
TotalcellcountwithELFsubstrate
(cell/mlX105)
water sample
Total cell count with ELF
substrate
ALP enzyme activity
with BACT control
0
20000
40000
60000
80000
100000
120000
140000
0
0.5
1
1.5
2
2.5
3
3.5
4
Industrial 1 Industrial 2 Tap water Surface water
CFU/ml
ALPtotalenzymeactivity(pmol/min/ml)
water sample
HPC
ALP enzyme activity (BACT
control)

12. 12
The absence of correlation between HPC
and ALP microbial enzymatic activity or with
the other biological parameters (e.g. FCM total
cell count and ATP) was also observed in other
previous studies [37] [38]. It could be explained
by the often described phenomenon, that due to
differences in nutrient concentration between
water and cultural medium used, only a minute
fraction (less than 1%) of the total water
microbial cells are cultivable on conventional
agar plates and this fraction varies even between
waters from different origins. In drinking water,
for example, the nutrient concentration on
conventional HPC agar plates is up to 1000
higher than the concentrations typically found in
water [39]. Mezule and coworkers reported that
not all viable bacteria and fungi present in water
are cultivable (so called viable-but-not-
cultivable (VNBC) bacterial state) [40], thus
indicating that the HPC method gives a poor
reflection of the total viable biomass in the
aquatic environment. In addition, some
heterotrophic bacteria do not produce
phosphatase while other including metabolically
active but not cultivable microorganisms can
produce these enzymes [41]. Notably, several
samples displayed considerable deviation from
the average value, also reflected in high
standard deviation (Fig. 8). This is attributed
predominantly to the heterogeneity of the
microbial communities of the different samples.
Correlation between Bulk ALP Enzyme
Activity measured with BACTcontrol
Biosensor and Microscopic Cells Count.
The average percentage of the difference
between FCM intact cells count and
microscopic intact cells count was 21%. The
average percentage between FCM intact cells
count and microscopic ELF-labeled cells count
was 9%, where it increased to 44% between
microscopic intact cells count and microscopic
ELF-labeled cells count. The microscopic intact
cells counts ranged between 0.04 -36 X 105
cells/ml, (table 3). The correlation analysis
between FCM intact cells count and with
microscopic intact cells count was (R2
= 0.94),
for all water samples tested. The correlation
coefficient between bulk enzymatic activity
with BACTcontrol and microscopic total cells
count within the similar type of water correlated
well (R2
= 0.92), and again dropped lower
between different water types (R2
= 0.14). When
epifluorescence microscopy and flow cytometer
are used to measure total cell counts, the
methods are suspected to errors due to the
formation of cell clusters or the attachment of
cells to inorganic compounds [42] and this may
explain the 21% differences in total cells count
between the both methods. The microscopic
cells count with ELF-97 substrate was 44% less
than the microscopic cells count with viable
stains (SYBR Green I and PI). This is expected
as ELF stain only cells with alkaline
phosphatase activity and despite the fact that
ALP enzyme can constitutively synthesize in
many microbial taxa, it can be stimulative in
another and that its production is strongly
influenced by several environmental and
biological effects [43] [44].

13. 13
Table 3. Number of intact microbial cells counted with FCM,
microscopic live cells count using viable stains and microscopic
cells count using ELF-97 substrate.
Research Conclusions
This study demonstrated that bulk ALP
activity measured with BACTcontrol biosensor
can provide an early warning method for
detecting a certain level of microbial and
bacterial parameters in aquatic environments. It
can potentially be used to perform routine
monitoring due to its rapidity (20-30 min)
instead of 72h that is needed for the culture-
based methods). More specifically, the study
demonstrated:
 There were significant correlations
between bulk ALP enzyme activity
level measured with BACTcontrol
biosensor and with different biological
parameters (total and intact FCM cells
counts, total and bounded ATP, total
microscopic cell count and total
microscopic ELF- labeled cell count)
when measured in similar water type.
These correlations varied when
measured between different water types
most likely due to the differences in
chemical and biological compositions.
 A poor correlation was observed
between total ALP and HPC. The
absence of correlation is expected for
several reasons. First, ALP synthesis
ability is not a universal characteristic of
all microorganisms and its synthesis is
strongly affected by different physical,
chemical and environmental factors such
as (water temperature, pH, and
phosphate availability). Second, the
enzyme activity level differs between the
different microbial types, and third, the
Poor reflection of the total viable
biomass by HPC method due to the
presence of the viable but not-cultivable
bacterial cells.
 Ideally and due to the complexity of the
relationships among microbial and
biological parameters, total ALP activity
measurement should not be used alone to
assess water quality and further standard
microbial analysis in the laboratory is
required in combination to identify
changes in water quality in more detail
and specific.
Acknowledgment
We sincerely thank Dr. Aleksandra Knezev
and Roland Tschumie from Het Water
Laboratorium- Haarlem- the Netherlands for
the scientific comments, guidance, and
warming helps.
Water
Sample
FCM total
intact cells
count
cell/ml X10
5
Microscopic
total cells
count with
viable stains
cells/ml X10
5
Microscopic total
cells count with
ELF-97
cells/ml X10
5
Industrial 1 185 36 11
Industrial 2 23.5 13 5.75
Tap water 1.3 0.039 0.03
Surface
water
30 1.5 0.39

14. 14
Bibliography
[1] W. Bank, "World Development Report
2008: Agriculture for Development,"
World Bank, Washington, DC, USA, 2007.
[2] UNESCO, "The United Nations World
Water Development Report 3: Water in a
Changing World," Routledge, London, UK,
2009.
[3] C. Hwang, F. Q. Ling, L. G. Andersen, M.
W. Lechevallier and W. T. Liu, "Microbial
community dynamics of an urban
drinkingwater distribution system subjected
to phases of chloramination and
chlorination treatments," Appl. Environ.
Microbiol., vol. 78, p. 7856–7865, 2012.
[4] E. Pamer, G. Vujovic, P. Knezevic, D.
Kojic, D. Prvulovic, B. Miljanovic and G.
Grubor-Lajsic, "Water Quality Assessment
in Lakes of Vojvodina," Int. J. Environ.
Res., vol. 5, no. 4, pp. 891-900, 2011.
[5] S. Read, M. Marzorati, B. C. M. Guimarães
and N. Boon, "Microbial Resource
Management revisited: successful
parameters and new concepts," Appl.
Microbiol. Biotechnol, vol. 90, p. 861–871,
2011.
[6] D. M. Lucilene and T. K. Lauro, "Review
of the use of biosensors as analytical tools
in the food and drink industries," Food
Chemistry, vol. 77, p. 237–256, 2002.
[7] A. Pooja, S. Annu, D. Neeraj and C.
Ashok, "Biosensors as innovative tools for
the detection of food borne pathogens,"
Biosensors and Bioelectronics , vol. 28 ,
pp. 1-12 , 2011.
[8] U. Münster and R. J. Chróst, Origin,
composition, and microbial utilization of
dissolved organic matter, New York: (In: J.
Overbeck, and J.R. Chróst (Eds.), Aquatic
microbial ecology: Biochemical and
molecular approaches Springer-Verlag,
1990, pp. 8-46.
[9] J. W. Ammerman and B. W. Glover,
"Continuous underway measurement of
microbial ectoenzyme activities in aquatic
ecosystems," MARINE ECOLOGY
PROGRESS SERIES, vol. Vol. 201, pp. 1-
12, 2000.
[10] J. L. Millan, "Alkaline Phosphatases,
Structure, substrate specificity and
functional relatedness to other members of
a large superfamily of enzymes,"
Purinergic Signalling, vol. 2, pp. 335-341,
2006.
[11] P. Nalini, P. Ellaiah, T. Prabhakar and G.
Girijasankar, "Microbial alkaline
phosphatases in bioprocessing,"
Int.J.Curr.Microbiol.App.Sci, vol. 4, no. 3,
pp. 384-396, 2015.
[12] S. A. Rankin, A. Christiansen, W. Lee, D.
S. Banavara and A. Lopez-Hernandez,
"Invited review: The application of alkaline
phosphatase assays for the validation of
milk product pasteurization," J. Dairy Sci.,
vol. 93, p. 5538–5551, 2010.
[13] E. Bentzen and W. Taylor, "The
importance of dissolved organic
phosphorus to phosphorus uptake by
limnetic plankton," Limnol. Oceanogr., vol.
37, no. 2, pp. 217-231, 1992.
[14] J. B. Cotner and R. G. Wetzel, "Uptake of
dissolved inorganic and organic
phosphorus compounds by phytoplankton
and bacterioplankton," Limnol. Oceanogr.,
vol. 37, no. 2, pp. 232-243, 1992.
[15] N. S. O. Tekaya, H. Ben Ouada, F.
Lagarde, H. Ben Ouada and N. Jaffrezic-

15. 15
Renault, "Ultra-sensitive conductometric
detection of heavy metals based on
inhibition of alkaline phosphatase activity
from Arthrospira platensis,"
Bioelectrochemistry, vol. 90, p. 24–29,
2013.
[16] M. Awasthi, "Relevance of alkaline
phosphatase activity of immobilized green
algae and cyanobacteria for heavy metal
toxicity monitoring," J. Mater. Environ.
Sci. , vol. 3, pp. 446-451, 2012.
[17] K. Yoshitomi, "Alkaline phosphatase
activity in cheeses measured by
fluorometry," Int. J. Food Sci. Technol.,
vol. 39, p. 349–353, 2004.
[18] E. I. Prest, F. Hammes, S. Kotzsch, M. C.
M. van Loosdrecht and J. S.
Vrouwenvelder, "Monitoring
microbiological changes in drinking water
systems using a fast and reproducible flow
cytometric method," water research, vol.
47, pp. 7131-7142, 2013.
[19] M. Berney, F. Hammes, F. Bosshard, H. U.
Weilenmann and T. Egli, "Assessment and
interpretation of bacterial viability by using
LIVE/DEAD BacLight kit in combination
with flow cytometry," Applied and
EnviromentalMicrobiology , vol. 73, pp.
3283-3290, 2007.
[20] Z. Hunag, W. You, R. P. Haugland, V. B.
Paragas and A. Olson, "A Novel
Fluorogenic Substrate for Detecting
Alkaline Phosphatase Activity in Situ',"
The Joumal of Histochemistry and
Cytochemistry, vol. 41, no. 2, pp. 313-317,
1993.
[21] D. Marco, Hans, L. H., C. M. Hans, J. L.
Hendrikus and R. P., "Detecting the
phosphate status of phytoplankton by
enzyme-labelled fluorescence and flow
cytometry," FEMS Microbiology Ecology,
vol. 48, pp. 29-38, 2004 .
[22] D. Marco, L. H. Hans, F. Virgilio, J. G.
Herman, C. P. M. Hans and P. Roel, "Flow
cytometric detection of phosphatase
activity combined with 13C-CO2 tracer-
based growth rate assessment in
phytoplankton populations from a shallow
lake," Aquat Microb Ecol , vol. 37, pp.
159-169, 2004.
[23] N. B ı h , I. M k, G. V
Y. Levi, "A colorimetric and fluorometric
microplate assay for the detection of
microcystin-LR in drinking water without
preconcentration," Food and Chemical
Toxicology, vol. 40, pp. 1677-1683, 2002.
[24] A. H. Farnleitner, L. Hocke, C. Beiwl, G.
G. Kavka, T. Zechmeister, A. k. T.
Kirschner and R. L. Mach, "Rapid
enzymatic detection of Escherichia coli
contamination in polluted river water,"
Letters in Applied Microbiology, vol. 33,
pp. 246-250, 2001.
[25] C. Labry, D. Delmas and A. Herbland,
"Phytoplankton and bacterial alkaline
phosphatase activities in relation to
phosphate and DOP availability within the
Gironde plume waters (Bay of Biscay),"
Journal of Experimental Marine Biology
and Ecology, vol. 2, no. 318, pp. 213-225,
2005.
[26] R. J. Chróst and J. Overbeck, "Kinetics of
alkaline phosphatase activity and
phosphorus availability for phytoplankton
and bacterioplankton in lake plusee (North
German Eutrophic Lake)," Microb Ecol,
vol. 3, no. 13, pp. 229-48, 1987.
[27] T. Tietjen and R. G. Wetzel, "Extracellular

16. 16
enzyme-clay mineral complexes: Enzyme
adsorption, alteration of enzyme activity,
and protection from photodegradation,"
Aquatic Ecology, vol. 37, p. 331–339,
2003.
[28] V. Liebers, D. Bachmann, G. Franke, S.
Freundt, H. Stubel, M. Düser, B. Kendzia,
M. Böckler, T. Brüning and M. Raulf,
"Determination of ATP-activity as a useful
tool for monitoring monitoringmicrobial
load in aqueous humidifier samples,"
International Journal of Hygiene and
Environmental Health, vol. 218, pp. 246-
253, 2015.
[29] M. Berneya, M. Vitala, I. H. lshoffa, H. U.
Weilenmann, T. Eglia and F. Hammesa,
"Rapid, cultivation-independent assessment
of microbial viability in drinking water,"
Water Research, vol. 42, pp. 4010-4018,
2008.
[30] J. Y. Lee and R. A. Deininger, "Arapid
method for detecting bacteria in drinking
water," Rapid Methods Automation
Microbiol, vol. 7, p. 135–145, 1999.
[31] E. Siebel, Y. Wang, E. T. T and F.
Hammes, "Correlations between total cell
concentration, total adenosine tri-phosphate
concentration and heterotrophic plate
counts during microbial monitoring of
drinking water," Drink. Water Eng. Sci.,
vol. 1, pp. 1-6, 2008.
[32] S. J. Vogel, M. Tank and N. Goodyear,
"Variation in detection limits between
bacterial growth phases and precision of an
ATP bioluminescence system," Letters in
Applied Microbiology, vol. 58, pp. 370-
375, 2014.
[33] R. Rej and J. P. Bretaudiere, "Effects of
Metal Ions on the Measurement of Alkaline
Phosphatase Activity," CLIN. CHEM, vol.
26, no. 3, pp. 423-428, 1980.
[34] B. Karin and M. David, "Bioavailability of
inorganic and organic phosphorus
compounds to natural assemblages of
microorganisms in Hawaiian coastal
waters," Mar. Ecol. Prog. Ser. , vol. 11, no.
1, pp. 265-273, 1994 .
[35] L. Ou, B. Huang, L. Lin, H. Hong, F.
Zhang and Z. Chen, "Phosphorus stress of
phytoplankton in the Taiwan Strait
determined by bulk and single-cell alkaline
phosphatase activity assays," MARINE
ECOLOGY PROGRESS SERIES, vol. 327,
p. 95–106, 2006.
[36] M. P. Peacock and R. M. Kudela, "A
method for determining alkaline
phosphatase activity in marine
phytoplankton using spectrofluorometry,"
Journal of Microbiological Methods, vol.
89, p. 209–212, 2012.
[37] M. Vital, M. Marco Dignum, A. Magic-
Knezev, P. Ross, L. Rietveld and F.
Hammes, "Flow cytometry and adenosine
tri-phosphate analysis: Alternative
possibilities to evaluate major
bacteriological changes in drinking water
treatment and distribution systems," Water
Research, vol. 46, pp. 4665-4676, 2012.
[38] F. Hammes, F. Goldschmidt, M. Vital, Y.
Wanga and T. Egli, "Measurement and
interpretation of microbial adenosine tri-
phosphate (ATP) in aquatic environments,"
Water Research, vol. 44, pp. 3915-3923,
2010.
[39] F. Hammes, M. Berney, Y. Wang, M.
Vital, O. Koster and T. Egli, "Flow-
cytometric total bacterial cell counts as a
descriptive microbiological parameter for

17. 17
drinking water treatment processes," Water
Research, vol. 42, pp. 269-277, 2008.
[40] L. Mezule, S. Larsson and T. Juhna,
"Application of DVC-FISH method in
tracking E. coli in drinking water
distribution networks," Drink. Water Eng.
Sci., vol. 6, pp. 25-31, 2013.
[41] I. Barcina, P. Lebaron and J. Vives-Rego,
"Survival of allochthonous bacteria in
aquatic systems: a biological approach,"
FEMS Microbiology Ecology, vol. 23, no.
1, pp. 1-9, 1997.
[42] I. Douterelo, J. B. Boxall, P. Deines, R.
Sekar, K. E. Fish and C. A. Biggs,
"Methodological approaches for studying
the microbial ecology of drinking water
distribution systems," Water Research, vol.
65, pp. 134-156, 2014.
[43] C. Labry, D. Delmas and A. Herbland,
"Phytoplankton and bacterial alkaline
phosphatase activities in relation to
phosphate and DOP availability within the
Gironde plume waters (Bay of Biscay),"
Journal of Experimental Marine Biology
and Ecology, vol. 2, no. 318, pp. 213-225,
2005.
[44] A. Cunha, A. Almeida, F. J. R. C. Coelho,
N. C. M. Gomes, V. Oliveira and A. L.
Santos, "Bacterial Extracellular Enzymatic
Activity in Globally Changing Aquatic
Ecosystems," Department of Biology &
CESAM, University of Aveiro, Portugal,
2010.