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In Situ Near-Infrared (NIR) Versus High-Throughput Mid- Infrared (MIR) Spectroscopy to Monitor Biopharmaceutical Production

Publication . Sales, Kevin C.; Rosa, Filipa; Sampaio, Pedro N.; Fonseca, LuÍs P.; B. Lopes, Marta; Calado, Cecília

The development of biopharmaceutical manufacturing processes presents critical constraints, with the major constraint being that living cells synthesize these molecules, presenting inherent behavior variability due to their high sensitivity to small fluctuations in the cultivation environment. To speed up the development process and to control this critical manufacturing step, it is relevant to develop high-throughput and in situ monitoring techniques, respectively. Here, high-throughput mid-infrared (MIR) spectral analysis of dehydrated cell pellets and in situ near-infrared (NIR) spectral analysis of the whole culture broth were compared to monitor plasmid production in recombinant Escherichia coil cultures. Good partial least squares (PLS) regression models were built, either based on MIR or NIR spectral data, yielding high coefficients of determination (R-2) and low predictive errors (root mean square error, or RMSE) to estimate host cell growth, plasmid production, carbon source consumption (glucose and glycerol), and by-product acetate production and consumption. The predictive errors for biomass, plasmid, glucose, glycerol, and acetate based on MIR data were 0.7 g/L, 9 mg/L, 0.3 g/L, 0.4 g/L, and 0.4 g/L, respectively, whereas for NIR data the predictive errors obtained were 0.4 g/L, 8 mg/L, 0.3 g/L, 0.2 g/L, and 0.4 g/L, respectively. The models obtained are robust as they are valid for cultivations conducted with different media compositions and with different cultivation strategies (batch and fed-batch). Besides being conducted in situ with a sterilized fiber optic probe, NIR spectroscopy allows building PLS models for estimating plasmid, glucose, and acetate that are as accurate as those obtained from the high-throughput MIR setup, and better models for estimating biomass and glycerol, yielding a decrease in 57 and 50% of the RMSE, respectively, compared to the MIR setup. However, MIR spectroscopy could be a valid alternative in the case of optimization protocols, due to possible space constraints or high costs associated with the use of multi-fiber optic probes for multi-bioreactors. In this case, MIR could be conducted in a high-throughput manner, analyzing hundreds of culture samples in a rapid and automatic mode.

2015-06Journal article

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In situ NIR spectroscopy monitoring of plasmid production processes effect of producing strain, medium composition and the cultivation strategy

Publication . Lopes, Marta B.; Gonçalves, Geisa A. L.; Felício-Silva, Daniel; Prather, Kristala L. J.; Monteiro, Gabriel; Prazeres, Duarte M. F.; Calado, Cecília

BACKGROUNDWhile the pharmaceutical industry keeps an eye on plasmid DNA production for new generation gene therapies, real-time monitoring techniques for plasmid bioproduction are as yet unavailable. This work shows the possibility of in situ monitoring of plasmid production in Escherichia coli cultures using a near infrared (NIR) fiber optic probe. RESULTSPartial least squares (PLS) regression models based on the NIR spectra were developed for predicting bioprocess critical variables such as the concentrations of biomass, plasmid, carbon sources (glucose and glycerol) and acetate. In order to achieve robust models able to predict the performance of plasmid production processes, independently of the composition of the cultivation medium, cultivation strategy (batch versus fed-batch) and E. coli strain used, three strategies were adopted, using: (i) E. coliDH5 cultures conducted under different media compositions and culture strategies (batch and fed-batch); (ii) engineered E. coli strains, MG1655endArecApgi and MG1655endArecA, grown on the same medium and culture strategy; (iii) diverse E. coli strains, over batch and fed-batch cultivations and using different media compositions. PLS models showed high accuracy for predicting all variables in the three groups of cultures. CONCLUSIONNIR spectroscopy combined with PLS modeling provides a fast, inexpensive and contamination-free technique to accurately monitoring plasmid bioprocesses in real time, independently of the medium composition, cultivation strategy and the E. coli strain used.

2015-02Journal article

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High-throughput bioassay for mechanism of action determination of antibacterial drugs

Publication . Ribeiro Da Cunha, Bernardo; Fonseca, Luís P. P.; Calado, Cecília

While the ‘war’ on infectious diseases has been considered won, antibiotic-resistant bacteria are currently responsible for 25,000 death’s yearly in Europe. No new broadspectrum antibiotic has been introduced since the 1960s, and the last new class was discovered in 1986. As the antibiotic pipeline is clearly exhausted, new tools to advance antibiotic research are required. The current work explored Fourier-transform infrared spectroscopy to classify the mechanism of action of 13 antibiotics, acting by 3 distinct Mode-Of-Action (MOA) and belonging to 7 different classes. After optimization of a biological assay and pre-processing techniques, principal component analysis and partial least squares discriminant analysis were applied in a multi-level approach, including the MOA, antibiotic class and ultimately individual antibiotics acting on very specific molecular targets. Overall results indicate that the proposed method presents metabolic resolution to identify antibiotics at three levels of classification (i.e. different MOA, classes and even acting on specific targets). Interestingly, the resolution capacity obtained at these three levels of classification depended on the antibiotic type, which highlights the importance of the multilevel approach taken. Ultimately the present work reinforces the applicability of the method has a metabolic fingerprinting tool for antibiotic discovery.

2017-03-30Conference object

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Metabolic proﬁling of recombinant Escherichia coli cultivations based on high-throughput FT-MIR spectroscopic analysis

Publication . Sales, Kevin C.; Rosa, Filipa; Ribeiro Da Cunha, Bernardo; Sampaio, Pedro; B. Lopes, Marta; Calado, Cecília

Escherichia coli is one of the most used host microorganism for the production of recombinant products, such as heterologous proteins and plasmids. However, genetic, physiological and environmental factors inﬂuence the plasmid replication and cloned gene expression in a highly complex way. To control and optimize the recombinant expression system performance, it is very important to understand this complexity. Therefore, the development of rap-id, highly sensitive and economic analytical methodologies, which enable the simultaneous characterization of the heterologous product synthesis and physiologic cell behavior under a variety of culture conditions, is highly desirable. For that, the metabolic proﬁle of recombinant E. coli cultures producing the pVAX-lacZ plasmid model was analyzed by rapid, economic and high-throughput Fourier Transform Mid-Infrared (FT-MIR) spectroscopy. The main goal of the present work is to show as the simultaneous multivariate data analysis by principal component analysis (PCA) and direct spectral analysis could represent a very interesting tool to monitor E. coli culture processes and acquire relevant information according to current quality regulatory guidelines. While PCA allowed capturing the energetic metabolic state of the cell, e.g. by identifying different C-sources consumption phases, direct FT-MIR spectral analysis allowed obtaining valuable biochemical and metabolic information along the cell culture, e.g. lipids, RNA, protein synthesis and turnover metabolism. The information achieved by spectral multivariate data and direct spectral analyses complement each other and may contribute to understand the complex interrelationships between the recombinant cell metabolism and the bioprocess environment towards more economic and robust processes design according to Quality by Design framework.

2017Journal article

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Towards an automated statistical workflow for biomarker screening in Fourier-transform infrared spectroscopy

Publication . Ribeiro Da Cunha, Bernardo; Aleixo, Sandra; Fonseca, Luís P.; Calado, Cecília

The increasing availability and sensitivity of analytical technologies has resulted in much higher complexity of molecular and cellular data, which biomarkers facilitate the bridge with a given biological state under scrutiny. Importantly, biomarkers are critical in spectroscopic technologies, as is the case of Fourier-transform infrared spectroscopy, for which different approaches to identify biomarkers have been established, for instance univariate statistical hypothesis tests. A workflow for the automatic application of said statistical tests is proposed with the objective of enabling a high throughput screening-approach that ensures statistical robustness, and works in a user-independent manner, thereby reducing analysis bias. The proposed workflow is the first step towards an automated method for biomarker screening, thus it is limited to distinguishing two populations. Firstly, the method used in previous work was improved to ensure the most powerful and accurate statistical tests are applied. Then, the statistical workflow was generalized to a more comprehensive range of data sets of two populations, for instance when sample size is not deemed high (less than thirty observations). Lastly, future work is outlined regarding the extension of the workflow to cases with more than two populations, but also of methods that can increase the pool of putative biomarkers that will then be screened for statistical significance.

2019-04-18Conference object

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