The integration of process analytical technologies (PAT) is paramount for bioprocess intensification. An NIR-based absorption photometer was developed to enable real-time monitoring of optical density in yeast fermentation cultures. Studies showed the photometer provided accurate measurements of optical density above 2.0 and could be used to automate nutrient feeds based on cell density measurements. Below an optical density of 2.0, readings were less accurate due to fluctuations from bubbles. Correlations between photometer readings and offline optical density measurements allowed modeling of culture growth in real-time.

1. NIR-based absorption photometer enables real-time monitoring of optical density in yeast fermentation
Massachusetts Institute of Technology, Department of Chemical Engineering, Cambridge MA 02139
Connor Williams, Nathaniel Swanson, Juan Jose Jaramillo, and Jean-François Hamel
Results
Conclusion
Materials and Methods
Application and Future Work
Acknowledgements
Literature Cited
The integration of process analytical technologies (PAT) is paramount for bioprocess
intensification. Biomass density is one of the most critical attributes of a fermentation
culture and is essential to achieve reliable process characterization. Current methods
of measuring biomass density include wet and dry weight, direct cell counting, optical
density, and plating. A principal disadvantage of these methods is their offline nature,
and without the help of real-time online measurements, critical transition points can
be missed easily. Online probes using near infrared (NIR) wavelengths optimally
measure the absorption of biomass and are independent of color changes. This allows
for an accurate real-time measurement of the optical density. NIR-based probes are a
more attractive alternative to light backscattering technologies which deviate with
decreased viabilities. Other current methods of measuring online biomass density
include dielectric spectroscopy, however, these technologies require frequent and
complex calibrations requiring separate multivariate models to represent varying
cellular characteristics [1].
Optical density data was collected using the BioPAT® Fundalux photometer (Sartorius-
Stedim, NY) in bioreactor cultures [2]. To demonstrate robustness of the NIR-based
photometer probe and its ability to measure the optical density (OD) for a
fermentation culture, a study was conducted to create several correlations between
the absorbance reading obtained from the probe and the OD of the culture. Because
this probe measures the optical properties of the observed culture, it can be
influenced by sparge bubbles in the system and can have various effects depending on
the magnitudes of the current cell density and agitation rate. The experiment was
executed to observe the accuracy of the Fundalux in response to various aeration and
agitation rates to simulate the dynamic nature of a fermentation process. The results
from this study were compared to the standard method of obtaining an offline OD
measurement at 600 nm (OD600) using a spectrophotometer. When used in
conjunction with a project modeling Pichia pastoris, the correlations developed for the
photometer were able to produce accurate OD readings and provide a comprehensive
model of the fermentation growth. Using the bioreactor’s control strategy, this probe
can potentially allow for automated nutrient feeds based on cell density.
This probe is to be used in research
focusing on the development and
optimization of the substrate yield of a
novel process that uses [13C6] glucose
to produce isotopically-labeled serum
albumin from the yeast Pichia pastoris,
with robust and consistent quantity
and enrichment for biomedical
research applications. Stable labelled
albumin is needed as a tool for
enabling the direct measurement of
metabolic behavior and molecular
properties for on-going cancer studies
in a collaborating department.
These results enable us to execute
glucose limited fed-batch using real
time PAT. With the help of the
Fundalux and the bioreactor control
strategy, we have the ability to allow
automated nutrient feeds when a
certain cell density is reached, or if the
slope of the growth curve falls below a
certain point.
Figure 2: Correlation between Fundalux reading and OD600 at variable operating
conditions. The operating condition study was conducted to form an accurate model
that could be used to convert the Fundalux output (which is in an arbitrary absorbance
unit on a scale of 0 – 5) to the equivalent OD600 value given by a spectrophotometer.
The BioPAT® Fundalux has been shown to accurate model the optical density,
and inherently the overall cell density when used to observe the growth of a
fermentation culture online and real-time. Other conclusions related to the
usability of the photometer probe include:
• A significant amount of output deviation and fluctuation at different
operating conditions at optical densities below 2.0.
• Accurate readings available during air sparging at all agitation rates above
optical densities of 2.0.
• With the help of online data tools and the bioreactors control capabilities,
we have the ability to automate nutrient feeds at critical growth points.
Figure 1: Fundalux reading fluctuation at different agitation rates
for optical densities ranging from 0 to 64. As shown in the
experimental data, at lower densities, the unit output varies
significantly, fluctuating ± 15-100% at ODs below 2.0. As the optical
density increased (4.0-64), the fluctuation was never more than
2.0% for all agitation rates.
The trend shows that as agitation rate increased, the fluctuation
decreased. Upon observation, the higher agitation rate caused
greater dissolution of the bubbles, as well as greater turbulence
which dispersed bubbles that previously formed on the glass
window of the probe at lower agitation rates.
Sartorius Stedim (NY) for providing the BioPAT® Fundalux photometer for this
study and Chapter 24 (OR) for support.
Table 1. Operating conditions for study
=
∆ ( )
∆
(1) Whitford, W., C. Julien. “Analytical Technology and PAT”. Bioprocessing
International. January 2007.
(2) “Operating Manual BioPAT® Fundalux: Online measurement of turbidity and
total biomass.” Sartorius Stedim Biotech GmbH. August 2014.
Abstract
The experiment was carried out in a two
liter glass vessel containing 1.8 liters of
water. The cell densities were achieved by
re-suspending active dry baker’s yeast to
achieve the desired cell densities quickly
and accurately. A constant air flow rate of 1
vvm was maintained for the sparge air. Two
rushton impellers were used for radial flow
mixing.
Figure 4: Optical density in real time based on Fundalux correlation model
for an experiment using P. Pastoris. An experimental bioreactor run using
P. Pastoris was conducted with the goal of maximizing the yield of the
protein serum albumin. In the interest of promoting increased specific
productivity, a glucose limited fed-batch process is desirable. Two
subsequent high-concentration glucose feeds were added as the stationary
phase was observed and cell growth slowed. The real-time agitation rate is
shown to vary throughout the experiment, yet the probe still modeled the
offline optical density readings accurately as the OD was above 2.0 after ≈
20 hours, where the probe output is precise within 2%.
Abs = Fundalux probe output
f(x)= polynomial fit for optical density correlation
Optical Density
(OD600)
Agitation Rate
(RPM)
0 250
0.25 500
0.50 750
1.00
2.00
4.00
8.00
16.0
32.0
48.0
64.0
Active dry yeast was added corresponding
to the desired optical density. The agitation
rate was increased incrementally from 250
to 750 RPM. The system was allowed to
settle for 5-10 minutes at each agitation rate
to get an average reading over that period.
Objectives
• Demonstrate the robustness of the NIR-based photometer probe and its ability
to measure optical density for a fermentation culture.
• Develop several correlation curves relating the Fundalux output to the optical
density of the culture to use in growth modeling.
• Determine the range for which the Fundalux output is accurate and consistent.
• Use the bioreactor’s control strategy to model culture growth in real time and
allow for automated nutrient feeds based on cell growth events.
250
350
450
550
650
750
0.00
0.20
0.40
0.60
0.80
1.00
1.20
0 20 40 60 80 100 120 140 160 180
AgitationRate(RPM)
FundaluxReading(AbsUnits)
Time (min)
OD = 0 OD = 0.25 OD = 0.50 OD = 1.00 OD = 2.00
Several Bioreactor studies were executed
with the Fundalux to attain growth curves
to ensure the probe can be used to produce
valid results. Optical density is linearly
proportional to biomass density.
250
350
450
550
650
750
1.20
1.40
1.60
1.80
2.00
2.20
2.40
2.60
2.80
3.00
3.20
165 185 205 225 245 265 285 305 325 345
AgitationRate(RPM)
FundaluxReading(AbsUnits)
Time (min)
OD = 4.00 OD = 8.00 OD = 64.00OD = 48.00OD = 32.00OD = 16.00
R² = 0.9999
0
10
20
30
40
50
60
70
80
0 0.5 1 1.5 2 2.5 3 3.5
OpticalDensity(OD600)
Fundalux Reading (Absorbance Units)
250 (RPM)
500 (RPM)
750 (RPM)
P. Pastoris Exp-2
P. Pastoris Exp-1
S. Cerevisiae Exp-1
Poly. (500 (RPM))
0
0.5
1
1.5
2
2.5
0 0.2 0.4 0.6 0.8 1
OpticalDensity(OD600)
Fundalux Reading (Abs Units)
250 RPM
500 RPM
750 RPM
Figure 3: Variation in Fundalux reading at optical densities ≤ 2.0.
At low densities, the average Fundalux value varies significantly,
deviating up to 40% from the mean across all agitation ranges,
but above an OD of 2.0, the deviation drops to ≤ 2.0 %.
Several subsequent bioreactor experiments were conducted
using the Fundalux. In each, the online photometers output
was compared to the standard offline OD600 reading using a
spectrophotometer. These experiments used different strains
of yeast, including Pichia Pastoris and Saccharomyces
Cerevisiae. Both have been shown to accurately follow the
model, as can be seen in the figure above.
The range where the most error occurs is below optical
densities of 2.0 where the probes reading fluctuation and
deviation across agitation rates are above 2%. Most bioreactor
experiments have lower agitation rates at the beginning of
bioreactor experiments where the cell density is lower, and
this is where the probe is observed to be the most inaccurate.
0
100
200
300
400
500
600
700
800
900
0
10
20
30
40
50
60
70
0 10 20 30 40 50 60
AgitationRate(RPM)
OpticalDensity(OD600)
Duration of Bioreactor Run (hours)
Online Optical Density (Fundalux) Offline Optical Density (OD600) Agitation Rate (RPM)
Feed 1
Feed 2
Presented at ISPE Annual Meeting – Student Poster Competition
Atlanta, GA - September 18-21, 2016