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Application note - 002
Step-by-step user guide: Microbial growth kinetics
The oCelloScope™ system
− An automated easy-to-use cytometer
− Rapid detection and 4D imaging of microbial growth
− Detailed information about cell morphology
− Ideal for time-lapse experiments (fits inside an incubator)
oCelloScope™
- adds unique information to your microbial analysis
C-X000047 1.0
Released 2014-12-23
The oCelloScope™ system
consists of the oCelloScope™
instrument and the
UniExplorer software.
Introduction
There is an increasing demand for sensitive and rapid methods for detection and monitoring of microbial
growth. The oCelloScope™ system is a robust automated system which allows rapid detection and 4D imaging
of microbial growth without affecting samples or assay conditions in any chemical or physiological way. The
unique features of the oCelloScope™ system makes it an important tool within the field of microbial analysis
and ideal for high-throughput assessment of microbial growth. The oCelloScope™ enables monitoring of
growth of all types of microbial samples (bacteria, yeast and fungi) in monocultures as well as in complex
samples or multicultures.
Compared to traditionally used methods, the oCelloScope™ system measures bacterial growth with high
sensitivity by monitoring cell growth at a single cell level. Moreover, it is possible to exclude for example
culture medium components or irrelevant objects from the analysis and thereby significantly increase assay
sensitivity. In addition to growth curves, the oCelloScope™ system provides detailed image data and movies
of bacterial growth for each sample.
Together, these features make oCelloScope™ an easy-to-use imaging cytometer delivering continuous realtime analysis of microbial samples without requiring any additional reagents or staining of cells. Thus, besides
improving your microbial analysis by rapid and sensitive monitoring of growth, the oCelloScope™ system will
also provide you with valuable image data and significantly reduce your costs and workload.
The oCelloScope™ system is ideal for:
• Rapid and sensitive detection of microbial growth.
• Growth kinetics analysis of microbial samples in their ‘natural matrix’ such as body fluids, food and
fermentation samples, and 3D microbial cultures.
• Examination of altered cell morphology at a single cell level without addition of any reagents or staining.
• High throughput assays - no requirement of manual handling or inspection during time-lapse
experiments.
• Rapid data processing and low time-of-result.
• Growth curves combined with high-quality image data and movies of growth kinetics.
• Samples requiring a high biosafety level.
For further information please contact
Klaus R. Andersen
Sales manager, Unisensor A/S
Mail: ka@unisensor.dk
Phone: +45 4187 9404
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Step-by-step user guide
The next pages show how to configure the oCelloScope™ software (UniExplorer) for monitoring of microbial
growth. The guide does not give any guidance on how to prepare or add samples to sample container
(microscope slide or microtiter plates) prior to oCelloScope™ analysis.
1. Start a new job by clicking the “New job” button in the top left corner.
2. Give the new job a name (optional).
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3. Choose the following modules from the list in the right side by double clicking
(or dragging) the following icons:
- “Acquire” (= record new image data)
- “Growth Kinetics Analysis”
then push the “Next” button.
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4. Select instrument at the instrument list (left click) and push the “Next” button to
continue with experimental setup.
Tip: If your instrument is not displayed on the list, push the “Refresh instrument list”
button (alternative: check cables and power to the instrument before pushing
“Refresh instrument list”).
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5. Select sample container in the list. The list shows sample containers supported by
UniExplorer. In this example, the “96 wells, Costar Corning 3596” is selected.
This example shows how to adjust settings for “Simplified view”. More settings
are available in the “Advanced view” tab.
6. Select and enable wells which should be included in the analysis. Wells are selected
with the cursor.
Enabled wells are shown as blue (growth kinetics is only monitored for enabled
wells). Orange squares in the centre of wells represent scan areas for each well.
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7. Select “≤ 20 µm (e.g. bacteria/yeast/fungi)” in the “Object size” list.
8. Adjust time for monitoring of microbial growth by selecting number of repetitions
and repetition interval (hh:mm:ss). For example, select “Number of repetitions” =
33 and “Repetition interval” = 00:15:00 to monitor microbial growth every 15
minutes for eight hours (the first measurement is at t=0).
“Acquire time” shows the total time of monitoring (the total time of data analysis
may exceed monitoring time due to data processing).
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9. Push the “Next” button to continue to settings for growth kinetics analysis.
10. Select or deselect growth algorithms by ticking the boxes (see page 16-17 for a
short description of the different growth algorithms).
Push the “Start” button to start growth kinetics analysis for enabled wells.
START
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11. After pushing “Start”, auto focus will automatically be adjusted for all enabled wells
(live view of each scan area is shown during focus adjustment).
When focus have been adjusted for all wells, the oCelloScope™ system automatically
continues with growth kinetics analysis. Real-time growth curves and image data can
be followed during analysis.
12. The “Warning” box below will be shown if it is not possible to determine auto
focus for one or more wells. To continue the growth kinetics analysis, focus have
to be adjusted in the “Advanced view” tab (see the oCelloScope™ User Manual for
more details about settings in “Advanced view”).
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13. During growth kinetics analysis, real-time growth curves and image data can be
inspected for all scan areas (enabled wells):
”Acquire”
Shows enabled wells and ”live view”
”Growth Kinetics Analysis”
Shows real-time growth curves for
all scanned wells.
Live view
Live view of scan area during
scanning.
Between scan repetitions, image
of the last recorded scan area is
shown.
”Current scan”:
Shows live view of scan area during scanning. Between scan
repetitions, image of the last recorded scan area is shown.
”Saved images”: Shows all recorded image data as images or time-lapse movies.
Makes it possible to study microbial growth during analysis for
individual scan areas.
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14. After growth kinetics analysis has finalized, image data are displayed in the
“Raw data” tab. Use the “Select scan area” drop down list to select the well
(scan area) of interest. Image data for each scanned well (scan area) can be
viewed as:
“Raw images”
Displays all raw images for each scan area. The number of raw images is set to
10 images per scan area for “≤ 20 µm (e.g. bacteria/yeast/fungi)” when using
the “Simplified view” settings.
“Z-stack”
Displays Z-stack images for each scan area. Objects can be viewed in and out of
focus by dragging the slider through the Z-stack levels (see next page).
“Best focus”
Displays the Z-stack image determined by UniExplorer to be the best focus
image (see next page).
Select scan area of interest
Zoom in and out by scrolling the mouse wheel.
(the cursor should be pointing at the image while scrolling)
Push ”Play” to see image data as a time-lapse movie or scroll manually through
the image data by dragging the slider along the “Repetition bar”.
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“Z-stack”
Displays Z-stack images for each scan area. Objects can be viewed in and out of
focus by dragging the slider through the Z-stack layers.
“Best focus”
Displays the Z-stack image determined by UniExplorer to be the best focus image.
Shows the Z-stack layer selected by UnisExplorer as the best focus layer.
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15. Image data are easily exported as .bmp (images) or .avi (movies) formats by pushing
the “Export” button.
See the oCelloScope™ User Manual for a more detailed description of the Export
options.
16. Growth curves are displayed in the “Growth Kinetics Analysis” tab.
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17. Compare growth curves for different wells (scan areas) by selecting “All items” in the
“Select scan area” drop down list.
Push the “Select all” button to compare growth curves for all scan areas. To compare
growth curves between two or more scan areas select the scan areas of interest in
the list right to the chart.
Selected growth algorithms are displayed
on chart (two or more growth algorithms
can be displayed at the same time).
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18. Display growth curves combined with a time-lapse movie of microbial growth by
selecting individual scan areas in the “Select scan area” drop down list and tick the
box “Show video”.
Push ”Play” to see growth curves and
image data as a time-lapse movie (or drag
the slider along the “Repetition bar”).
Selected growth algorithms are displayed
on chart (two or more growth algorithms
can be displayed at the same time).
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19. Growth curves and image data are easily exported as .bmp (charts) or .avi (timelapse movies) formats by pushing the “Export” button and selecting “Export chart”,
“Export video” or “Export scan areas”.
Growth kinetic values can be exported as Excel and CSV formats by pushing the
“Export” button and selecting “Export to Excel” or “Export to CSV”.
See the oCelloScope™ User Manual for a more detailed description of the Export
options.
.
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Short description of oCelloScope™ growth algorithms
The Growth Kinetics Analysis (GKA) algorithms produce accurate real-time visualisation of
growth rates for all types of microbial samples such as bacteria, fungi and yeast.
Each algorithm is designed to possess specific advantages to ensure reliable
measurement of microbial growth even at low or very high cell concentrations.
The GKA algorithms (TA, BCA and SESA algorithms) process the entire image at once, i.e.
objects are not processed individually.
Example of bacterial growth kinetics measured by the oCelloScope™ algorithms.
TA algorithm – Total Absorption
The Total Absorption (TA) algorithm is a simple absorption measurement, which is
comparable to conventional used turbidity methods.
TA growth curves are based on pixel values of the whole image where a bright image is
equivalent to a low TA value and a dark image is equivalent to a high TA value. During
microbial growth, the increasing number of microbial objects will reduce light
transmission and the image will become darker and darker.
Limitation: TA is not very sensitive in case of low cell concentrations or at slow growth
rates (for example during lag and stationary growth phases) as microbial growth will only
affect a few pixels at a time compared to the total pixel number of the image. Hence, TA
should preferably be used for measurement of microbial growth in the exponential phase
as growth and cell concentration need to be quite considerable before affecting the
overall light intensity.
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TA Norm algorithm – Total Absorption Normalized
TA Norm is computed in the same way as TA except that the value of the first image is
subtracted from the following images on the growth curve. TA Norm growth curves are
calculated for each individual scan area and will always start at point 0 independently of
the initial cell concentration.
BCA algorithm – Background Corrected Absorption
The Background Corrected Absorption (BCA) algorithm is designed to detect microbial
growth with high sensitivity even at very low or high cell concentrations.
Based on the first image, the BCA algorithm corrects background intensities to obtain
images with an even light distribution before calculating a threshold pixel value which
divide pixels into ‘background pixels’ and ‘object pixels’. The BCA algorithm generates
growth curves based on changes in ‘object pixels’. In this way, BCA is able to determine
microbial growth with high sensitivity as the effect of background intensities are reduced
significantly compared to the TA algorithm.
Limitation: BCA may lead to inaccurate determination of growth curves when for
example condensation obscures light transmission resulting in darker images and
consequently in false ‘object pixels’.
BCA Norm algorithm – Background Corrected Absorption Normalized
BCA Norm is computed in the same way as BCA except that the value of the first image is
subtracted from the following images on the growth curve. BCA Norm growth curves are
calculated for each individual scan area and will always start at point 0 independently of
the initial cell concentration.
SESA algorithm – Segmentation and Extraction of Surface Area
The Segmentation and Extraction of Surface Area (SESA) algorithm measures microbial
growth with high sensitivity and is robust to changes in light intensities caused by for
example condensation.
The SESA algorithm determines microbial growth based on segmentation and contrastbased identification of all objects in a scan area. Growth curves are generated by
summarizing the surface area covered by all identified objects in a scan area. Because
growth curves are based on segmentation, the SESA algorithm is able to measure
microbial growth with high accuracy even at very low cell concentrations and should not
be affected by changes in illumination.
Limitation: SESA is limited at high cell concentrations and may lead to inaccurate
measurement of growth curves when cells are overlapping. In general, the accuracy of
SESA will begin to decline when objects cover more than 20% of the total image area.
SESA Norm algorithm – Segmentation and Extraction of Surface Area Normalized
SESA Norm is computed in the same way as SESA except that the value of the first image
is subtracted from the following images on the growth curve. SESA Norm growth curves
are calculated for each individual scan area and will always start at point 0 independently
of the initial cell concentration.
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