Direct Detection of Biofilms and CIP-Related Problems in Liquid Process Systems Mark Fornalik Ethox International 1
Product Quality & Process Health Product quality depends in large part on cleanliness of the liquid product transfer line Traditional methods of monitoring system health: Analyzing final product Analyzing residual product in process water flush Swabbing interior surfaces of tanks & lines for biofilms (ATP, PCR analysis) But.. Most bacteria recovered don t grow in culture in the microbiology lab Analyzing effluent water does not provide any indication of what remains behind on the pipe wall ATP and PCR methods require critical cell mass for signal 2
Transfer Line Contamination Contamination Problems: Cross contamination between product types Physical waste spots, streaks, particles, filter plugging, viscosity changes Chemical waste chemical contamination of final product Increased brand change time Loss of product flow Increased production runs to allow for waste 3
Insoluble Wall Fouling Fouling: The unwanted formation of insoluble residues on engineering materials in contact with flowing solutions Fouling is what is left on wall surface after even a proper water flush clean Chemical cleaning must be designed to address water-insoluble wall fouling 4
Insoluble Wall Fouling Types* Organic Inorganic Biological (bacteria, fungi, algae - BIOFILMS) Particulate (corrosion) Crystallization/Scale (boilers, heat exchangers) Combination (any two or more of the above) * T.R. Bott, Fouling of Heat Exchangers,, Elsevier (1995) 5
Fouling Rate fouling mass physical chemical secondary fouling induction period time The goal of cleaning is to return the system to the induction period level of fouling 6
Fouling Cell: Sanitary Cross with Insoluble material deposits on pipe wall and mirror-polished end cap during product flow Polished End Caps Mirror-polished end caps Product Flow Material that adsorbs (sticks) on pipe wall also adsorbs on mirror-polished end caps (fouling cell discs) 7
Measuring Wall Fouling Fourier transform infrared beam Spectrum from reflected infrared beam Fouled end cap (fouling cell disc) 8
Fouling Identification FTIR provides a chemical fingerprint of the fouling, as well as an indication of fouling amount 9
Process Cleaning: A Structured Approach Biofilm Control Chemical Clean Optimization Water Flush Optimization System Design 10
Water Flush Effluent: Product Displacement 1000 100 Old process water flush end point Percent of Dye in the Flush Solution 10 1 0.1 0.01 Water flush plateau Magenta Yellow Cyan 0.001 0.0001 0 5 10 15 20 25 30 35 Time (minutes) Insufficient water flush leaves product behind in pipe; optimized water flush reaches plateau more quickly for faster cleaning times 11
Powerflush (Two-Phase Flow) Cleaning Efficient flow ratio Water-rich flow ratio Cleaning efficiency varies as a function of the ratio of air flow to water flow 12
Measuring Powerflush Cleaning Efficiency with FTIR 0.0080 0.0075 0.0070 0.0065 0.0060 0.0055 Before powerflush Absorbance 0.0050 0.0045 0.0040 0.0035 0.0030 0.0025 0.0020 0.0015 0.0010 0.0005 0.0000 After powerflush -0.0005-0.0010 3500 3000 2500 2000 1500 1000 Wavenumbers (cm-1) Peak height data correlate to effectiveness of cleaning: the smaller the peak, the more effective the cleaning 13
Chemical Cleaning Variables Chemical cleaner formulation Concentration Temperature Order of addition 14
Measuring Chemical Cleaning Efficiency FTIR peak height before & after cleaning provides an estimate of cleaning efficiency 100% cleaning efficiency 80% 60% 40% 20% 0% TSP NaOCl TSP/NaOCl NaOH Citric acid 15
Studying Chemical Cleaning Parameters Impact of temperature cleaning efficiency 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 25 C 45 C 65 C 5% NaOH cleaning efficiency 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Impact of concentration 0.2% 1.0% 5.0% NaOH wt% @ 60 C 16
Biofouling/Biofilms* Unwanted adhesion of bacteria or other organisms onto surfaces of solutionhandling systems Not necessarily uniform in space & time May contain significant amounts of inorganic materials held together by the polymeric matrix *(Charackis & Marshall, Biofilms, 1990) 17
Biofilm-Related Contaminants Cells (possibly pathogenic) Anions (acetate, formate, nitrate, etc.) Proteins, glycoproteins, carbohydrates, fatty acids Enzymes Surfactants Organic and inorganic particles Substrate degradation (metals, plastics) 18
Biofilm Resistance to Cleaning Standard CIP methods may not remove biofilm Biofilms able to grow after 8 months desiccation Biofilms withstood 80C or higher water temperatures Biofilms withstood 20, 50 and 200 ppm chlorine, 25 ppm iodine Food Protection Report, 7(5):8 (1991) 19
Standard Methods to Measure System Health & Cleanliness Product testing: Taste Chemistry Plating/culturing Process testing: Cleaning water effluent testing Plating Residual product Swab testing by plating ATP and/or PCR testing 20
Key Points Biofilms exist in chemical as well as water transfer lines Biofilms can alter the chemistry of the product or water going through the line Biofilms can evade detection by traditional microbiological testing methods because these methods focus on recovering and growing cells from biofilms Fouling cell technology relies on measuring exopolymer, not necessarily cells, in place on the surface of interest, avoiding inefficient scraping and culturing methods 21
Bacteria Populations in a Pipe TRADITIONAL SAMPLING: 1% of total bacteria population inside of pipe is planktonic (free swimming organisms from bulk solution) 1% 99% FOULING CELL SAMPLING: 99% of total bacteria population inside of pipe is sessile (attached biofilm on the wall of the pipe) Sessile organisms (biofilms) can be very resistant to cleaning 22
45 C Ultrapure Water Biofouling 1 day 2 days 4 days 9 days 23
Biofilm Chemistry Over Time 0.020 0.019 0.018 *Subtraction Result:ir1848, 610 NRX disc #26, 3-month exposure, no clean *Subtraction Result:ir1896, 610 NRX, 14 batches (4 days), disc #7 (1/30-2/2/98) *Subtraction Result:ir2288, 610, NRX, #10, 24 hours, 5 batches, 2/26-2/27/98 *Subtraction Result:ir1974, disc 10, 610 NRX, 1 batch, 4 hrs, without santoprene gasket 0.017 0.016 0.015 0.014 0.013 0.012 0.011 0.010 0.009 0.008 Absorbance 0.007 0.006 0.005 0.004 0.003 0.002 6 mo 0.001 0.000-0.001 24 hrs -0.002-0.003-0.004 8 hrs -0.005-0.006-0.007 2 hrs -0.008 4000 3800 3600 3400 3200 3000 2800 2600 2400 2200 2000 1800 1600 1400 1200 1000 800 600 Wavenumbers (cm-1) Biofilm changes to cleaning-resistant exopolymer upon aging 24
Biofilm Resistance to Cleaning: Bleach Treatment 25
Mapping Process CIP Efficacy in a Brewery FTIR spectra of fouling cells placed in 5 locations of a manufacturing process (stage A through E) for 8 weeks FTIR & epifluorescence of fouling cells can provide cleaning efficacy data from end to end of a process 26
Process Mapping in a Brewery: FTIR Peak Heights by Location 0.05 0.045 0.04 0.035 absorbance units 0.03 0.025 0.02 0.015 0.01 0.005 0 A B C D E Process Start Packaging 27
Brewery Wort Line 2 weeks, 100x objective 8 weeks, 100x objective 0.05 0.045 0.04 0.035 absorbance units 0.03 0.025 0.02 0.015 0.01 0.005 0 A B C D E 28
Brewery Aging Line 2 weeks, 100x objective 8 weeks, 100x objective 0.05 0.045 0.04 0.035 absorbance units 0.03 0.025 0.02 0.015 0.01 0.005 0 A B C D E 29
Brewery Filler Inlet Line 2 weeks, 100x objective 8 weeks, 100x objective 0.05 absorbance units 0.045 0.04 0.035 0.03 0.025 0.02 FTIR determines onset of biofouling in process 0.015 0.01 0.005 0 A B C D E 30
Brewery Filler Inlet Line 8 weeks, 100x objective 8 weeks, 100x objective 31
Winery Bottling Line 1 After CIP 1-week exposure, 100x 4-week exposure, 100x 32
Winery Bottling Line 2 After CIP 1-week exposure, 100x 4-week exposure, 100x 33
Winery Bottling Line 2 Before & After CIP Removed by CIP Not Removed by CIP After water flush After CIP 34
Biotech Company Fermentation 2-day exposure before CIP 2-day exposure after CIP CIP: 5% NaOH, 65 C, 30 min daily 4-week exposure after CIP 35
Biotech Company Recovery 2-day exposure before CIP 2-day exposure after CIP CIP: 5% NaOH, 65 C, 30 min daily 4-week exposure after CIP 36
Fermentation vs. Recovery 37
Pharma Company Steam System Diaphragm Valve Areas selected for analysis 38
Pharma Company Steam Valve Stereo Microscopy Organic material 40X 39
Pharma Company Steam Valve Confocal Microscopy 40
Pharma Company Steam Valve Confocal Microscopy Region of heavy fouling 41
Pharma Company Steam Valve Atomic Force Microscopy Height image Phase image Apparent scale formation 42
Pharma Company Steam Valve Atomic Force Microscopy Height image Phase image Apparent organic material (biofilm exopolymer) 43
Process Cleaning Improvement Flow Chart On-site process assessment: system design water flush parameters wall fouling Fouling cell studies to determine: fouling chemistry fouling rate presence of organisms Lab cleaning studies to determine: appropriate cleaning chemicals chemical concentration, temperature chemical contact time, order of addition Process trials with new cleaning procedure: implement new cleaning procedure verify improvement 44
Conclusions In-line fouling cells can provide: An early warning for issues of process cleanliness and health Information on chemistry and rate of fouling within system Objective data on CIP efficacy Ability to determine efficacy of proposed cleaning changes in the lab, not in production Ability to screen new products for fouling propensity These methods are complimentary to existing process health measures 45