Bioprocess Monitoring - Off-line Monitoring PDF

IMC Krems Bioprocess Monitoring – off-line monitoring Bioprocess Monitoring off-line monitoring DI Dr. Markus Luchner WS 2024 Markus Luchner...

IMC Krems Bioprocess Monitoring – off-line monitoring Bioprocess Monitoring off-line monitoring DI Dr. Markus Luchner WS 2024 Markus Luchner Page 1  IMC Krems Bioprocess Monitoring – off-line monitoring Goals for off-line monitoring: Important to understand critical process parameters (CPP) example: product quality and mass and so on Requirements  Easy handling  “fast” analysis  Reproducibility  Broad spectrum of analytes Markus Luchner Page 2  IMC Krems Bioprocess Monitoring – off-line monitoring Goals for off-line monitoring: Markus Luchner Page 3  IMC Krems Bioprocess Monitoring – off-line monitoring Off-line measurements which are standard in industrial fermentations: analysis of:  biomass  carbohydrates If eg all glucose consumed  protein quantity and quality  phosphate and lipid concentrations  enzyme activity  broth rheology bei fungy system can they produce micellium  …  Samples are usually taken every 4 – 8 hours  Results are available e.g. 24 hours later Markus Luchner Page 4  IMC Krems Bioprocess Monitoring – off-line monitoring “classical” off-line analytics  Cell dry mass (CDM)  Viable Cell Number (VCN) important for mammalian cell culture  Product yield  Product purity  Substrate composition  Supernatant composition  Nucleotides Markus Luchner Page 5  IMC Krems Bioprocess Monitoring – off-line monitoring Biomass / Cell Dry Mass: BDM or CDM = Gravimetric: - taking sample with a well known volume (e.g. 10 ml) - centrifugation of cells - re-washing of cell pellet - filling in a tarred beaker - 24 h drying at 105 °C or via IR-oven - reweighting of beaker Specific cell dry mass [g/L] = net weight [g] / volume [ml] *1000 Markus Luchner Page 6  IMC Krems Bioprocess Monitoring – off-line monitoring Biomass / Cell Dry Mass: Gravimetric: Advantages: - Easy method - Reproducible - Operator independent - Wide used in industry Disadvantage: - Time consuming (24 h) - Labour-intensive Markus Luchner Page 7  IMC Krems Bioprocess Monitoring – off-line monitoring Biomass / Cell Dry Mass: IR- or halogen lamp:  taking sample with a well known volume  drying chamber with integrated balance  measurement result within few minutes 20 min Source: Mettler Markus Luchner Page 8  IMC Krems Bioprocess Monitoring – off-line monitoring Biomass / optical density (OD): Photometric: - defined volume measured in a cuvette with photometer - 600 nm wavelength (OD600) - linear range from 0.2 to 0.6  dilution of sample - principle of Lambert-Beer Law Markus Luchner Page 9  IMC Krems Bioprocess Monitoring – off-line monitoring Optical density Lambert-Beer Law I E   log   * c * d I0 E Extinction I intensity of transmitted light I0 intensity of irradiated light ελ molar extinction coefficient c concentration d path length of cuvette Markus Luchner Page 10  IMC Krems Bioprocess Monitoring – off-line monitoring Optical density Advantages: - Rapid method (< 5 min) - Low instrumentation (photometer) - Application for bacteria, yeast, mammalian cells,… many microorganism Disadvantages: - Operator dependent (pipetting) - Dilution errors - Accuracy Markus Luchner Page 11  IMC Krems Bioprocess Monitoring – off-line monitoring Microscopic Thoma chamber / hemocytometer: - microscope slide with a defined volume - quadratic grid - counting of cells per quadrate (b-field) Markus Luchner Page 12  IMC Krems Bioprocess Monitoring – off-line monitoring Thoma chamber different volumes for different types of cells Markus Luchner Page 13  IMC Krems Bioprocess Monitoring – off-line monitoring Calculation of cell number in Thoma chamber Markus Luchner Page 14  IMC Krems Bioprocess Monitoring – off-line monitoring Thoma chamber / hemocytometer Advantages: - Low instrumentation (microscope) - Application for bacteria, yeast, mammalian cells,… Disadvantage: - Time consuming (counting of cells in microscope) - Cell aggregates Markus Luchner Page 15  IMC Krems Bioprocess Monitoring – off-line monitoring Most Probable Number (MPN) eg mesure amount of cells in drinking water serial dilution of a probe in a liquid medium until the final tubes in the series show no growth 3 repetitions the last tube showing growth should have developed from 10 or fewer cells incubation for 24h and se in wich phase therese no growth anymore Markus Luchner Page 16  IMC Krems Bioprocess Monitoring – off-line monitoring MPN - method  Statistical table for most probably number  Numerical code  last 3 dilution steps showing growth  Statistical methods ‘most probable number‘ (MPN Tables) Markus Luchner Page 17  IMC Krems Bioprocess Monitoring – off-line monitoring MPN Last 3 positive steps (turbidity): 321 MPN (table): 150  150 cells in the dilution  10-2 that contains 10 µL sample  1 mL sample: 15.000 cells  dilution factor (medium/ sample) = 10  cells per cm3 sample: 150.000 Markus Luchner Page 18  IMC Krems Bioprocess Monitoring – off-line monitoring MPN  time consuming (cultivation time of cells)  Statistical test – accuracy lower  applications in beverage-industry, milk-industry, diagnostics, waste water treatment,… - less in biotechnology production Markus Luchner Page 19  IMC Krems Bioprocess Monitoring – off-line monitoring Agar plate method: “Koch” Preparation of dilution row (10-1, 10-2,…) Agar plating of 1 ml of diluted sample Incubation for 48 hours Addition of antibiotics  determination of plasmid containing cells (resistance marker) Addition of Inducer  determination of non producing cells  Agar plate with 30 to 300 colonies (colony forming units (cfu´s)) are used Calculation: cfu = colonies * dilution factor [cells per ml] Markus Luchner Page 20  IMC Krems Bioprocess Monitoring – off-line monitoring Agar plating method: Advantages: - universal method for yeast and bacteria - identification of contaminants (selection agar, different types of colonies,…) gleiche kolonien haben gleiche farbe oder form und bei kontamination erkennt mans - monitoring of water quality,… selective agar for gramm positiv or negativ - easy handling Disadvantages: - influence of operator - accuracy +/- 20 % - stressed cells have poorly cell division - not applicable in mammalian cells bc they dont grow on agarplates Markus Luchner Page 21  IMC Krems Bioprocess Monitoring – off-line monitoring NucleoCounter Principle: fluorescence microscopic method cells stained with probidium iode (PI) für cells mit gechädigter hülle da PI binds to DNA of disrupted cells es an nuleus bindet  determination of total cell number and viable cells Markus Luchner Page 22  IMC Krems Bioprocess Monitoring – off-line monitoring NucleoCounter: one measurement after incubation only with PI additional incubation with cell lyses reagent and staining with PI  Viable cells = total cells (second incubation) – dead cells Non-viable cells Total cell count Markus Luchner Page 23  IMC Krems Bioprocess Monitoring – off-line monitoring NucleoCounter: https://chemometec.com/ Markus Luchner Page 24  IMC Krems Bioprocess Monitoring – off-line monitoring NucleoCounter: Key benefits: - Easy operation and suitable for multiple users - 30 sec. analysis time - 5*103 – 2*106 cells / ml - Calibration free - Portable/compact - Safe sample handling and disposal - Excellent reproducibility Markus Luchner Page 25  IMC Krems Bioprocess Monitoring – off-line monitoring Flow Cytometry: Flow cytometry is a useful technique for multi-parameter analysis Simultaneous measurement of multiple parameters - FSC (forward scatter light) for cell size - SSC (side scatter light) surface of the cells (disrupted) - up to 3 (or more) fluorescence channels (e.g. for dead cells) - by using of calibration beads measurement of total cell number (TCN)  Preparation of cells by staining with different fluorescence dyes - e.g. propidium iodide (PI): for staining of dead cells - ethidium bromide (EB): living cells, which can’t proliferate Markus Luchner Page 26  IMC Krems Bioprocess Monitoring – off-line monitoring Principle: Markus Luchner Page 27  IMC Krems Bioprocess Monitoring – off-line monitoring Principle: NICHT LERNEN DIESE NR Laser with 488 and 633 nm Detection of 530, 585 and 670 nm Markus Luchner Page 28  IMC Krems Bioprocess Monitoring – off-line monitoring Flow cytometer: Also used for cell sorting FACS: fluorescence activated cell sorting For clone screening Markus Luchner Page 29  IMC Krems Bioprocess Monitoring – off-line monitoring Flow Cytometry Markus Luchner Page 30  IMC Krems Bioprocess Monitoring – off-line monitoring Flow Cytometry: Summary: Simultaneous measurement of different variables Measurement of energy level of cells Measurement of cell cycle Determination of viable cell number (VCN) Cell size determination …Internal PH Markus Luchner Page 31  IMC Krems Bioprocess Monitoring – off-line monitoring Analysis of carbohydrates: Analysis of carbohydrates in supernatant Control of utilisation of C-source in fermentation Calculation of yield coefficient (substrate utilization vs. produced biomass (YX/S)) X  X0 YX / S  S0  S Important for selection of carbon source – the higher Y the better utilization of substrate Markus Luchner Page 32  IMC Krems Bioprocess Monitoring – off-line monitoring Analysis of carbohydrates:  Lactate in supernatant inhibits cell growth (especially in mammalian cells)  useful for control of cultivation  Glucose in supernatant in C-limited fermentations reflects growth inhibition (no utilisation of C-source)  Level of pyruvate, formiate,… as control for metabolic state of culture Markus Luchner Page 33  IMC Krems Bioprocess Monitoring – off-line monitoring Analysis of carbohydrate: HPLC: ion exchange HPLC YSI / Bioprofiler system: - multiparameter analysis system - e.g. glucose, lactate, glutamate, ethanol, ammonia, methanol, pH… - based on enzymatic reactions (immobilized enzymes on a membrane) Markus Luchner Page 34  IMC Krems Bioprocess Monitoring – off-line monitoring Comparison YSI / Bioprofiler vs. HPLC e.g. YSI / Bioprofiler:  Fast measurement (2 minutes)  Less probe preparation  Precision +/- 2% HPLC:  Time consuming (retention time of analyte ~ 30 minutes, UPLC shorter)  Higher accuracy  More analytes in parallel Markus Luchner Page 35  IMC Krems Bioprocess Monitoring – off-line monitoring “Cheap” sugar measurement: Sugar test device for blood sugar: Disadvantage:  Accuracy  Dilution of sample  Matrix effect Advantage:  Fast measurement  Cheap Markus Luchner Page 36  IMC Krems Bioprocess Monitoring – off-line monitoring Analysis of nucleotides: Goal:  nucleotides (ADP, ATP, ppGpp, cAMP,….) reflects the energy state of the cells  for monitoring of stress (ppGpp is a stress marker for unloaded t- RNA)  Analysis with reversed phase HPLC Disadvantage: time consuming analysis Markus Luchner Page 37  IMC Krems Bioprocess Monitoring – off-line monitoring Product quality and quantity:  Product quality and quantity is the key issue of a biotechnology process  Yield is cash cow of a process  Product quality is essential for therapeutic application (glycosylation) Markus Luchner Page 38  IMC Krems Bioprocess Monitoring – off-line monitoring Product quality and quantity: Staining methods: - Biuret-test - Bradford - Lowry-test - BCA-assay - UV-methods Staining with protein-binding dyes – analysing with spectral- photometer Disadvantages: - low sensitive - calibration curve necessary - no information about product quality Markus Luchner Page 39  IMC Krems Bioprocess Monitoring – off-line monitoring Product quality and quantity: Activity tests: enzyme activity assays coupled enzymatic assay  Information about product quality  very selective tests  enzyme activity only with native proteins more information: e.g. www.thermofisher.com www.sigmaaldrich.com Markus Luchner Page 40  IMC Krems Bioprocess Monitoring – off-line monitoring Product quality and quantity: Binding tests: Immunochemical methods ELISA (enzyme linked immunosorbent assay) Selective tests Only reaction with target protein Markus Luchner Page 41  IMC Krems Bioprocess Monitoring – off-line monitoring ELISA: “only” (?) correct folded proteins are detected (depends on sensitivity of antibody) High sensitive, low detection limits (ng-range) Well established method Laborious (robots) Selective test for target protein Markus Luchner Page 42  IMC Krems Bioprocess Monitoring – off-line monitoring Product quality and quantity: Qualification by gel electrophoresis (SDS-PAGE) this is one dimenstional - size of protein - semi-quantitative (imaging software) - detection of dimers,…  Useful, when no specific antibody (ELISA) for a protein available  Precision +/- 10 %  Laborious you gotta have a marker Markus Luchner je dünkler desto konzentrierter. Page 43  IMC Krems Bioprocess Monitoring – off-line monitoring Product quality and quantity: 2-dimensional differential gel electrophoresis (DIGE) novel technology for protein analytic “Proteomics” monitoring of the whole proteome of a cell analysis of glycosylation  Hundreds of proteins on one gel  Difficult to analyze (bioinformatics, databases) mesure isoelectric point ans size Markus Luchner Page 44  IMC Krems Bioprocess Monitoring – off-line monitoring DIGE: Proteomics 150 kD 10 4 pI 7 6 pI 11 42 cm DeCyder Software Analysis spot picking trypsine digestion peptide mass fingerprint (PMF) identification using the MASCOT database © GE-Healthcare MS/MS for confirmation of identification Markus Luchner Page 45  IMC Krems Bioprocess Monitoring – off-line monitoring Application: shifts of protein pattern due to recomb. gene expression (yellow =down regulated) 4 pI 7 4 pI 7 4 pI 7 22´ after induction 68´ after induction 150´ after induktion Significantly changed 24 45 65 proteins Significance level: average ratio >±1.5, Student´s t-test < 0.05 Dürrschmid, K. et.al. (2005): Monitoring the dynamics of transcription and translation in the time course of recombinant cultivations.. Mol Cell Proteomics, 4, 8 (Suppl1), 285. Markus Luchner Page 46 ML0 IMC Krems Bioprocess Monitoring – off-line monitoring Novel trends in Bioprocess Monitoring Availability of sophisticated biochemical procedures providing analysis on molecular level (DNA chips, sequencing, 2-D- electrophoresis, MS, RT-PCR, etc.) Key issues: increase quality of information on metabolic level deeper understanding of metabolic regulatory networks Markus Luchner Page 47 Folie 47 ML0 17.102023 Markus Luchner; 2023-10-17T10:55:47.910  IMC Krems Bioprocess Monitoring – off-line monitoring Characterization of cellular systems on molecular level Markus Luchner Page 48  IMC Krems Bioprocess Monitoring – off-line monitoring Sampling demands sampling procedure should enable collection of samples representing in vivo conditions (high turnover of metabolites) rapid sampling short time interval between harvest and quenching high sampling frequency – low sample volumes high sample volume - reactor empty withn hours Sampling  quenching  extraction  separation Markus Luchner Page 49  IMC Krems Bioprocess Monitoring – off-line monitoring sampling concentration of glucose outside cell Markus Luchner Page 50  IMC Krems Bioprocess Monitoring – off-line monitoring Quenching - Extraction quenching procedure should – instantly arrest (freeze) cellular metabolic activity – cause no significant cell membrane damage should occur - loss of intracellular metabolites – not modify the intracellular metabolites, neither physically nor chemically, so as to render them unidentifiable or undetectable – differences between exometabolome - endometabolome extraction procedure should – extract as wide a range of metabolites as possible – dilution effects should be kept as minimal as possible – not modify the intracellular metabolites, neither physically nor chemically, so as to render them unidentifiable or undetectable – deliver a sample matrix compatible to the analytical method of choice Markus Luchner Page 51  IMC Krems Bioprocess Monitoring – off-line monitoring Analytical Platforms combination of separation technology and detection method HPLC-MS (high performance liquid chromatographie mass spectrometry) LC-MS-MS (liquid chromatographie 2-dimensional mass spectrometry) UPLC-MS (ultra performance liquid chromatographie mass spectrometry) GC-MS (gas chromatographie mass spectrometry) GC-MS-MS (2-dimensional gas chromatographie mass spectrometry) CE-MS (capillary eectrophoresis mass spectrometry) NMR (1H, C13, P31) (nuclear magnetic resonance) LC-NMR (liquid chromatography nuclear magnetic resonance) FT-IR (fourier transformation infrared spectroscopy) Transcriptomics ….. Markus Luchner Page 52  IMC Krems Bioprocess Monitoring – off-line monitoring Transcriptome analysis: Deeper look inside the cell on transcriptome level Large scale and high throughput method (E. coli 4200 genes, mouse 24.000 genes) Applications: Strain improvement (finding of bottlenecks) Check for changes in gene expression during long-term culture (mammalian cell culture, intensive reactor systems – stress of cells during cultivation) Markus Luchner Page 53  IMC Krems Bioprocess Monitoring – off-line monitoring Principle of microarrays: Isolation of mRNA species  Reverse Transcription using fluorescence marked nucleotides  Hybridisation Powerful tool to screen shifts in transcription red... down-regulated, green... up-regulated Markus Luchner Page 54  IMC Krems Bioprocess Monitoring – off-line monitoring controlled inducerfeed (limited induction) Transcription profile pulse induction (fully induced system) Markus Luchner Page 55 diffrent clusters, data from fermentation  IMC Krems Bioprocess Monitoring – off-line monitoring Transcription profile of E. coli cultivation after clustering of genes Markus Luchner Page 56  IMC Krems Bioprocess Monitoring – off-line monitoring Summary microarrays: Advantages - High throughput system - Thousands of genes with one experiment - Finding of bottlenecks in Metabolism Disadvantages: - Specific binding of cDNA (false positive genes) - Time consuming, Laborious - Sample preparation - expensive (1 slide > € 100, fluorescence dyes,…) - Analysis: bioinformatics for high data Markus Luchner Page 57  IMC Krems Bioprocess Monitoring – off-line monitoring Real-time PCR Analysis of specific mRNA by selection of suitable primers Quantitative method for transcriptome analysis Single genes are analysed Disadvantages: - Sample preparation - Isolation of mRNA - Lots of dilution steps - Time consuming - Laborious - Expensive (fluorescence dye, enzymes) Markus Luchner Page 58  IMC Krems Bioprocess Monitoring – off-line monitoring Real-time PCR Markus Luchner Page 59  IMC Krems Bioprocess Monitoring – off-line monitoring Real-time PCR Advantage: easy to establish less expensive than other methods especially useful if different primer sets are applied Drawback: unspecific binding possible General: DNA extraction crucial specificity of primers Markus Luchner Page 60  IMC Krems Bioprocess Monitoring – off-line monitoring Backlogs of off-line analytics:  complexity of analytical procedures and assays  too low sampling frequency Fusion of sophisticated analytical techniques with continuously emerging computing facilities  i.e. exploitation of on-line data through correlation to key variables of metabolism using mathematical modeling and simulation techniques (e.g. neural network simulations) Markus Luchner Page 61