Environmental monitoring using a rapid non- destructive ...

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Environmental monitoring using a rapid non-destructive automated compendial method

Andrew Sage, Principle ScientistRapid Micro Biosystems

New England PDA16 May, 2008

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Overview

• overview of the automated compendial rapid microbial enumeration technology- the Growth Direct system

• application to environmental testing in manufacturing facilities:– water– air– surface

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The business problem: high cost of culture-based QC microbiological testing in pharmaceutical manufacturing

↓cost of materials↓regulatory risk: “gold standard”↓skills required↑sensitivity (for culturable bugs)

↑ time to results↑ cost of labor↑ cost of held inventory↑ cost of product scrap↑ cost of plant downtime↑ cost of cleanup

$$$$

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Goals in automating the compendial method

• Improve accuracy & decrease time-to-results– replace human eye with digital imaging

• facilitate system validation– use same procedures and method

principles as traditional culture

• save labor & improve compliance– automate analysis and documentation

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Automating the compendial method by replacing the human eye with sensitive digital imaging- a better set of eyes

~100 cells ~5x106 cells

Growth Direct system visual plate counting

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Using large area non-magnified digital imaging to detect microscopic microcolonies

CCD chip

photosensitive pixellamp

“autofluorescing” microcolony

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How the image analysis software enumerates growing microbes

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Image analysis using Growth Direct software

make a stack of images from the various time points

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Image analysis using Growth Direct™ software

find objects on each image using image analysis software

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align images

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trace all objects backwards through time

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identify growing objects (intensity increases over time)


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ignore debris (objects that do not grow over time)


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report number of growing objects


5 growing microcolonies

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2 hrs3 hrs4 hrs5 hrs6 hrs7 hrs8 hrs9 hrs10 hrs11 hrs12 hrs13 hrs14 hrs15 hrs16 hrs17 hrs18 hrs

0.5 mm

Accuracy: by analyzing image time series system counts growing colonies and ignores inanimate fluorescent debris

P. aeruginosa

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The work flow of the automated compendial test

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Labor savings and improved compliance from an automated compendial test

• labor savings – data acquisition is automated – documentation is electronic, and easily

transferred to data management systems

• increased compliance – fewer data management errors – greater reproducibility

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Automating the compendial test preserves its advantages while addressing its weaknesses

• captures the positive features of the compendial tests– non-destructive– ultra-sensitive (1 CFU )– breadth of testing applications– enumerates replicating cells– high throughput – no added reagents– industry standard media, membranes

• addresses the limitations of the compendial tests– automation: ↓labor, ↑compliance, ↑reproducibility–speed: saves days, generally ~50% faster

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Bacteria detected by cellular autofluorescenceAcidovorax delafieldii Curtobacterium sp. Proteus vulgaris Acidovorax sp. Deinococcus proteolyticus Pseudomonas aeruginosa Acidovorax temperans Dermacoccus nishinomiyaensis Pseudomonas fluorescens Acinetobacter junii Enterococcus faecalis Pseudomonas putida Afipia broomeae Escherichia coli Pseudomonas stutzeri Arthrobacter sp. Geobacillus stearothermophilus Ralstonia pickettii Bacillus cereus Hydrogenophagea sp. Rhodococcus erythropolis Bacillus clausii Hyphomicrobium sp. Roseomonas gilardii Bacillus fusiformis Kocuria kristinae Roseomonas sp. Bacillus gibsonii Kocuria rhizophila Salmonella enterica Bacillus licheniformis Kytococcus sedentarius Serratia marcesens Bacillus megaterium Macrococcus caseolyticus Sphingomonas paucimobilis Bacillus pumilus Methylobacterium extorquens Sphingomonas spp. Bacillus sp. Methylobacterium radiotolerans Sphingomonas terrae Bacillus subtilis Microbacterium luteolum Staphylococcus aureus Bacillus vortex Microbacterium maritypicum Staphylococcus capitis Bacteriodes fragilis Microbacterium sp. Staphylococcus epidermidis Brachybacterium sp. Micrococcus luteus Staphylococcus equorum Bradyrhizobium spp. Moraxella osloensis Staphylococcus haemolyticus Brevibacterium sp. Myxococcus xanthus Staphylococcus hominis Brevundimonas diminuta Neisseria sp. Staphylococcus saccharolyticus Burkholderia cepacia Paenibacillus lautus Staphylococcus sp. Caulobacter leidyii Paenibacillus sp. Staphylococcus warneri Cellulomas sp. Pantoea agglomerans Streptococcus sp. Chromobacterium violaceum Paracoccus sp. Streptomyces chrysolmalus complex Clostridium sporogenes Porphyromonas gingivalis Streptomyces coelicolor Corynebacterium sp. Prevotella melaninogenica Streptomyces sp. Corynebacterium xerosis Propionibacterium acnes Vibrio natriegens Corynebacterium pseudodiptheriticum

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Fungi detected by cellular autofluorescence

Penicillium roquefortii Candida albicans Zygosaccharomyces rouxiiPenicillium notatum Aureobasidium pullulans Trichoderma asperellumPenicillium corylophylumAspergillus versicolor Sporotrichum pruinosum Penicillium chrysogeneumAspergillus sp.Sporidiobolus johnsoniiPenicillium camemberti Aspergillus niger Schizosaccharomyces pombeFusarium solaniAspergillus fumigatus Schizophyllum fasciatumEpicoccum nigrumAspergillus flavusSchizophyllum communeCladosporium herbarumArthrinium sacchariSaccharomyces cerevisiae Chaetomium globosumAlternaria geophilaRhizopus oligosporusCandida parapsilosis Alternaria alternata

21Candida albicans (~12 cells)Escherichia coli (~120 cells)

Time savings: the system detects microscopic microcolonies(scanning EM images)

1 micron

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The automated compendial method saves days for slow growing strains

2.73.60.9Proionibacterium acnes

1.21.80.6Clostridium sporogenes1.62.40.8Aspergillus niger1.931.1Ralstonia picketii2.13.61.5Aspergillus versicolor2.43.71.3Mycoplasma bovis2.441.6Deinococcus proteolyticus

4.86.71.9Mycobacterium chelonae6.170.9Bacteroides vulgatis

14.617.22.6Methylobacterium extorquens

Visual(days)

Growth Direct(days)

Days saved

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Time savings is greatest for slow growing microbes

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Water testing

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Rapid detection of water microbes: autofluorescent detection detects the same colonies that later become visible by eye

2.5 days

Growth Direct microcolonies

5 days

visual plate counting

sample: purified water from a pharmaceutical facility

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Correlation of Growth Direct and visible counts in pharma water samples

Growth Direct (68 hr) vs visible counts

visible colonies at 120 hr0 50 100 150 200 250 300 350G

row

th D

irect

col

onie

s at

68

hr

0

50

100

150

200

250

300

350

y = 1.02x

R2 = 0.90

R2A, 32.5ºC

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visual plate counting (5 days)

Growth Direct (1.5 days)

Accuracy: resolving at the microcolony stage colonies that are uncountable by traditional visible plate

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Air monitoring

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20 hr


72 hr


Rapid detection of airborne microbes at a pharma plant

3072 hrs (TSA, 32.5ºC)

21 hrs39 hrs

12 hrs

18 hrs

12 hrs

Rapid detection of diverse airborne microbes at a pharma facility

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Air monitoring: co-trending of rapid (1.5 day) and traditional (3 day) tests at a pharma facility

y = 1.105x + 0.41R2 = 0.7899

0

20

40

60

0 20 40 60visible colonies (72 hr)

Gro

wth

Dire

ct c

olon

ies

(36

hr)

4-Sep-0719-Sep-072-Oct-0715-Nov-07

32.5 ºC, TSA

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Air monitoring: co-trending of rapid (1 day) and traditional (2 day) tests at a pharma facility

0

2

4

6

8

10

2 3 4 5 6 7 8 9 10 11

date

colo

nies

det

ecte

d

Naked agar (48 hours)

Growth Direct (18 hours)

6 Dec24 Oct 9 Nov 16 Jan 21 Dec 17 Oct 8 Mar 1 May

visual plate count at 48 hr

Growth Direct test at 20 hr

17 Oct 24 Oct 9 Nov 6 Dec 21 Dec 16 Jan 8 Mar 1 May

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Comparing recovery on membranes and agar in air testing using a “half membrane” strategy

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y = 1.04x - 5.1, R2 = 0.96

020406080

100120140160180

0 50 100 150agar (CFU)

mem

bran

e (C

FU)

y = 0.93x - 1.7, R2 = 0.87

0

50

100

150

200

0 50 100 150 200agar (CFU)

mem

bran

e (C

FU)

y = 0.94x - 0.93, R2 = 0.97

0

50

100

150

200

250

0 50 100 150 200 250agar (CFU)

mem

bran

e (C

FU)

y = 1.00x + 2.1, R2 = 0.77

010203040506070

0 20 40 60

agar (CFU)

mem

bran

e (C

FU)

Various air samplers, “half-membrane” experiments show equivalent recovery on membrane and agar

Air Ideal (90 mm) Air Ideal (55 mm)

SAS 180 SMA P201

TSA medium

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Surface monitoring

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Rapid detection of microbes on surfaces at a pharma site

15 hr


72 hr


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0

5

10

15

20

2 3 4 5 6 7 8 9 10 11date

colo

nies

det

ecte

d

Naked agar (48 hours)

Growth Direct (24 hours)

Oct 17 Nov 9Oct 24 Dec 6 Dec 21 Jan 16 Mar 8 May 1

Surface testing: co-trending of rapid (1 day) and traditional (2 day) tests at a pharma facility

visual plate count at 48 hr

Growth Direct test at 24 hr

TSA, 32.5 °C

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Comparing recovery on membranes and agar in surface testing using capture efficiency (Whyte et al, 1989)

Efficiency (E) = fraction recovered of total microbes/ replicate

• Sample multiple times on same location (e.g. 5 replicates)

• Incubate• Count each plate

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Comparing efficiency of recovery for surface contact plates: membrane Vs agar

Whyte et al, 1989. J. Hosp. Inf., 13: 33-41

Efficiency (E) = fraction recovered of total microbes/ replicateE = [1 − log (slope)]

1

10

100

1000

0 2 4 6 8 10replicate contact plate number

colo

nies

reco

vere

d

membrane

agar

Emembrane = 0.34Eagar = 0.28

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0.32 ± 0.100.26 ± 0.09latex gloves9 “thumbs”

0.40 ± 0.08

0.32 ± 0.13

0.38 ± 0.12

0.40 ± 0.13

membrane

average capture efficiency

0.40 ± 0.09

0.31 ± 0.10

0.49 ± 0.07

0.38 ± 0.11

agar

plexiglass10 sites

tyvek8 sites

glass10 sites

stainless steel12 sites

Surface

Surface contact testing: equivalent capture efficiencies on membranes vs. agar

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Validation Question -Growth Direct System, New Technology?

• Growth Direct is not an alternative technology– it is based on standard USP growth based membrane filtration methods– the results are given as CFU’s.

• The “novel” Growth Direct is an automated compendial method:– the system is an “Automated” colony counter and can be linked to

the USP Chapter <16> Automated Methods of Analysis. – validation requires proof that the camera sees as many micro-colonies

as the eye would see colonies on the membrane surface.– Performance Qualification would follow standard requirements in

chapter <1227>, <61> etc.– other validation components are standard incubator and software

validation protocols.

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Summing up• Advantages of the an automated compendial

enumeration method:– addresses same broad spectrum of QC applications

as the compendial method– sensitive digital imaging detects microcolonies– non-destructive, compatible with microbial ID– equivalent counts to current method

• Autofluorescence-based detection offers equivalent results with substantial time savings for environmental applications:– water– air– surfaces

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Environmental monitoring using a rapid non-destructive automated

compendial method

Environmental monitoring using a rapid non- destructive ...

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