Simultaneous measurement of glucose and glutamine in insect cell culture media by near infrared spectroscopy

Riley, Mark R.; Rhiel, Martin; Zhou, Xiangji; Arnold, Mark A.; Murhammer, David W.

doi:10.1002/(sici)1097-0290(19970705)55:1<11::aid-bit2>3.0.co;2-#

Cited by 91 publications

(54 citation statements)

References 13 publications

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“…Near infrared spectra (NIR) and infrared spectra are routinely analysed by PCA or used in PLS models for estimation of analyte concentrations in unknown samples (Karstang & Henriksen, 1992;Riley, Rhiel, Zhou, Arnold, & Murhammer, 1997;Yeung, Hoare, Thornhill, Williams, & Vaghjiani, 1999), while Seasholtz (1999) described the impact of multivariate analysis of NIR and other spectroscopy at Dow Chemical. In those cases the instruments themselves created the spectra, but the spectra may also be calculated numerically.…”

Section: Introductionmentioning

confidence: 99%

Spectral principal component analysis of dynamic process data

Thornhill

Shah

Huang

et al. 2002

Control Engineering Practice

130

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This article describes principal component analysis (PCA) of the power spectra of data from chemical processes. Spectral PCA can be applied to the measurements from a whole unit or plant because spectra are invariant to the phase lags caused by time delays and process dynamics. The same comment applies to PCA using autocovariance functions, which was also studied. Two case studies are presented. One was derived from simulation of a pulp process. The second was from a refinery involving 37 tags. In both cases, PCA clusters were observed which were characterised by distinct spectral features. Spectral PCA was compared with PCA using autocovariance functions. The performance was similar, and both offered an improvement over PCA using the time domain signals even when time shifting was used to align the phases. r

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Section: Introductionmentioning

confidence: 99%

Spectral principal component analysis of dynamic process data

Thornhill

Shah

Huang

et al. 2002

Control Engineering Practice

130

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“…The analytical utility of NIR spectroscopy is established for measuring millimolar levels of various biological species in simulated matrices Burmeister et al, 1998;Burmeister and Arnold, 1999) and natural matrices from clinical chemistry (Hazen et al, 1998), fermentation (Cavinato et al, 1990;Ge et al, 1994;Hall et al, 1996;Yano et al, 1998), and cell culture Lewis et al, 2000;McShane and CoteÂ , 1998;Riley et al, 1997Riley et al, , 1998aRiley et al, , 1998bZhou et al, 1995) systems. The chemical information originates from overtone and combination transitions associated with fundamental C±H, O±H, and N±H vibrations.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, the well-known relationship between glucose consumption and lactate production generates a concentration correlation that is unacceptable for building PLS calibration models. The implications of cell metabolism on method calibration have been examined in detail elsewhere (Lewis et al, 2000;McShane and CoteÂ , 1998;Riley et al, 1997Riley et al, , 1998aRiley et al, , 1998b. Brie¯y, the calibration samples are best collected at various timepoints during cultivation in order to account for the global chemical changes in the samples.…”

Section: Introductionmentioning

confidence: 99%

“…An adaptive calibration procedure has been proposed to destroy concentration correlations within a set of samples (Riley et al, 1997(Riley et al, , 1998a(Riley et al, , 1998b. This procedure involves spiking samples with known and random amounts of standard materials, thereby adapting the collected samples so they may be used to generate NIR spectra suitable for training multivariate calibration models.…”

Section: Introductionmentioning

confidence: 99%

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Nondestructive near‐infrared spectroscopic measurement of multiple analytes in undiluted samples of serum‐based cell culture media

Rhiel

Cohen

Murhammer

et al. 2001

Biotech & Bioengineering

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An adaptive calibration procedure is used to build selective multivariate calibration models for the measurement of glucose, lactate, glutamine, and ammonia in undiluted serum-based cell culture media. This adaptive procedure removes metabolism-induced covariance between these analytes in a series of calibration samples collected during the cultivation of PC-3 human prostate cancer cells. Partial least-squares calibration models are generated from single-beam near-infrared (NIR) spectra collected over the 4800-to 4200-cm )1 combination spectral range. Calibration models were generated with both the full spectral range and optimized spectral ranges. In both cases, the number of model factors was optimized and model validity was determined by comparing analyte concentrations predicted from a series of independent and unaltered samples that were obtained during a subsequent cultivation of the PC-3 cells. Similar analytical performance was achieved with fewer model factors when the optimized spectral range was used. The lowest standard errors of prediction were 0.82, 0.94, 0.55, and 0.76 mM for glucose, lactate, glutamine, and ammonia, respectively. Different spectral ranges were optimal for each analyte and the optimized spectral range coincided with the distinguishing spectral features of the analyte. The results of this study demonstrate that NIR spectroscopy can be used effectively in the off-line measurement of important nutrients (glucose and glutamine) and byproducts (lactate and ammonia) in a serum-based animal cell culture medium.

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“…13 The extent of matrix variation is a major factor in our ability to model the sample matrix with only a few samples. Although the insect cell culture medium contains over 23 individual components at relatively high concentrations, only three of these components exhibit substantial concentration changes during cultivation.…”

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Matrix-Enhanced Calibration Procedure for Multivariate Calibration Models with Near-Infrared Spectra

1998

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A novel method is introduced for developing calibration models for the spectroscopic measurement of chemical concentrations in an aqueous environment. To demonstrate this matrix-enhanced calibration procedure, we developed calibration models to quantitate glucose and glutamine concentrations in an insect cell culture medium that is a complex mixture of more than 20 components, with three components that manifest significant concentration changes. Accurate calibration models were generated for glucose and glutamine by using a calibration data set composed of 60 samples containing the analytes dissolved in an aqueous buffer along with as few as two samples of the analytes dissolved in culture medium. Standard errors of prediction were 1.0 mM for glucose and 0.35 mM for glutamine. The matrix-enhanced method was also applied to culture medium samples collected during the course of a second bioreactor run. Addition of three culture medium samples to a buffer calibration reduced glucose prediction errors from 3.8 mM to 1.0 mM; addition of two culture medium samples reduced glutamine prediction errors from 1.6 mM to 0.76 mM. Results from this study suggest that spectroscopic calibration models can be developed from a relatively simple set of samples provided that some account for variations in the sample matrix.

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Simultaneous measurement of glucose and glutamine in insect cell culture media by near infrared spectroscopy

Cited by 91 publications

References 13 publications

Spectral principal component analysis of dynamic process data

Spectral principal component analysis of dynamic process data

Nondestructive near‐infrared spectroscopic measurement of multiple analytes in undiluted samples of serum‐based cell culture media

Matrix-Enhanced Calibration Procedure for Multivariate Calibration Models with Near-Infrared Spectra

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