Evaluation of the AutoMicrobic system for identification of glucose nonfermenting gram negative rods

0095-1137/82/020302-06$02.00/0

Evaluation

of the AutoMicrobic

System

for Identification

of

Glucose-Nonfermenting

Gram-Negative Rods

SHARONM.SMITH,1 KENNETH R. CUNDY,1*GERALDL. GILARDI,2AND WILLIAMWONG' DepartmentofMicrobiologyandImmunology, Temple University Schoolof Medicine,Philadelphia,

Pennsylvania 19140,1 andJointDiseases-North GeneralHospital, New York,New York100352 Received 10August 1981/Accepted 14 September 1981

With the EnterobacteriaceaePlus BiochemicalCard,the AutoMicrobicsystem (Vitek Systems, Inc.,

Hazelwood,

Mo.)ispurportedto identify members ofthe family Enterobacteriaceae and seven species of

glucose-nonfermenting

gram-negative rods:Pseudomonasaeruginosa, P.

fluorescens,

P.putida,P.

maltophi-lia,

P. cepacia, and Acinetobacter calcoaceticus(saccharolyticand

non-sacchar-olytic). The latter capability wasexamined in thisinvestigation. Of 410

glucose-nonfermenting

rods included in the identification profile, the AutoMicrobic

system correctly identified 366(89.3%). Of 62

glucose-nonfermenting

organisms

not included in the identification profile, 41 (66%) were correctly reported as

"unidentified organism." The usefulness of the AutoMicrobic system-generated identificationprobability in establishingcriteriaforacceptanceof identification is discussed.

Glucose-nonfermenting gram-negative

rods are

becoming

increasingly important

as

opportu-nistic pathogens

in

patients

receiving antibiotics,

chemotherapy,

or

steroids

or with otherwise

impaired

natural

defense mechanisms.

The

non-fermenters are

often resistant

to

antimicrobial

therapy and,

therefore,

poseathreatas

potential

agents

of serious nosocomial

infections.

For

these

reasons it is

important

that nonfermenters are

quickly

and

accurately identified.

These

organisms

are

often slow

growers

and

are

rela-tively inert

biochemically,

and

thus,

identifica-tion

schemes

require prolonged incubation with

special

media. Identifications

are

therefore

time-consuming and cumbersome. Within

the

last

decade several commercial

microsystems

have

become

available for the

identification of

the

nonfermenters.

These systems, compared with the

conventional

methodology, allow for

easy storage,

inoculation,

and

interpretation

of re-sults, a decreased amount of time needed for

quality control,

and a more

standardized

prod-uct with a greater

correlation

of results from

laboratory

to laboratory. Many

laboratories

therefore

rely

entirely

upon manual systems for the

identification

of nonfermenting organisms with little orno use of conventional

methodolo-gies.

The

AutoMicrobic

system (AMS; Vitek Sys-tems,Inc.,

Hazelwood,

Mo.) is arecently avail-able automated system. Inaddition to the same

advantages of

manual systems, the AMS has automated the

inoculation

of the

biochemical

tests, the

reading

of thetests, the

interpretation

of

the

biochemical

patterns, and the

printing

of a

hard

copy

containing

the final

organism

identifi-cation, which results in a significant

savings

in technologist time. The AMS has been evaluated for its efficiency in (i) screening urines for the enumeration and identification of certain micro-organisms (1, 9, 13, 17, 18), (ii) identifying members of the

family

Enterobacteriaceae

(7, 8,

11), and (iii)

performing

susceptibility

testing (10). The AMS now has the

capacity

to

identify

seven

glucose-nonfermenting

rods: Pseudomo-nas

aeruginosa,

P.

cepacia,

P.

fluorescens,

P.

putida,

P.

maltophilia,

and

Acinetobacter

cal-coaceticus

(saccharolytic

and

non-saccharolyt-ic). This

study

was

designed

to evaluate this

capability of the

AMS.

MATERIALS ANDMETHODS

Microorganisms. Ofthe472 glucose-nonfermenting

gram-negative rods tested, 306 were fresh clinical

isolates obtained from the clinicalmicrobiology

labo-ratories of Temple University Hospital, Children's

Hospital of Philadelphia, and St. Christopher's

Hospi-tal for Children, Philadelphia, Pa. A total of 166

isolates were obtained from an internal reference

collection. The various organisms studied and the

source of the isolates are shown in Table 1. Isolates were grown on 5% sheep blood agar plates (BBL

Microbiology Systems, Cockeysville,Md.) at 35°C for

18 to 24 hbefore identification.

Identificationmethods.The EnterobacteriaceaePlus

Biochemical Cards (EBC+)were purchased from

Vi-tekSystems, Inc., foruse with the AMS. The EBC+ is

anexpanded version oftheEnterobacteriaceae

Bio-chemical Card (EBC) (8) containing four additional tests. Three ofthe tests, growth on acetamide and

cetrimideandfermentationof glucose, are included in

thebiochemical card. The fourth test, production of

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AMS IDENTIFICATION OF NONFERMENTING RODS 303

TABLE 1. Summary of the 472isolates of

glucose-nonfermentinggram-negative rods identified in this study, and their source

Source (no. of

Organism

isolates)'

Reference Clinical

Pseudomonas aeruginosa 8 203

P.fluorescens 21 2

P.putida 26 0

P.maltophilia 27 42

P.cepacia 22 9

Acinetobactercalcoaceticus 8 30

(saccharolytic)

A.calcoaceticus 9 3

(non-saccharolytic)

Achromobacterxylosoxidans 3 3

Alcaligenesdenitrificans 4 0

A.faecalis 5 0

A.odorans 2 1

CDCbgroupVA-1 0 1

Flavobacterium breve 1 0

Flavobacterium group II B 3 7

F.meningosepticum 0 1

Moraxella sp. 0 1

Pseudomonas acidovorans 2 1

P.diminuta 6 0

P.alcaligenes 2 1

P.paucimobilis 4 0

P.pseudoalcaligenes 4 1

P.putrefaciens 2 0

P.stutzeri 7 0

a

Of

the total of 472 isolates tested, 306 (64.8%)

wereclinicalisolates, and 166(35.2%) were from the

referencecollection.

bCDC, Centers for Disease Control.

oxidase,mustbedeterminedmanually,and apositive

reactionmustbe coded into the spaceprovidedonthe

EBC+. In this study the production of oxidase was

tested with the Pathotec cytochrome oxidase strip

(General Diagnostics, Warner-Lambert Co., Morris

Plains, N.J.). Spaceis alsoprovidedforenteringa

six-digitlaboratoryaccession numbersothat the

identifi-cation ofa given patient isolate can be recovered.

Bacterialsuspensions equivalentto aMcFarlandno.1

standard were made in the diluent (0.5% saline) and

dispensed into sterile tubes bythe diluentdispenser

module. Small plastic transfer tubes allowed for the

passage of the suspension of organisms into the

EBC+. Afterthe cards were filled by negative

pres-sure in the filling module, the plastic transfer tubes

werecutandsealed by the sealer module. Thecards

werethenincubatedat35.5°Cin the reader-incubator

module. The programmedcomputerdeterminedwhen

abiochemical testbecamepositive (1). Resultswere

printedoutby thedataterminalafter thecompletion of

the incubation cycle (8 h forP. aeruginosaand 13 h for

othernonfermenters). Thereportcontained the

labo-ratoryaccession number, the time anddateof

comple-tion, anda final identification with theprobability of

correct identification. If thebiochemical pattern was

not compatible with those in the data base, a final

report of "unidentified organism" resulted. If the

organism failedtogrowduring theincubation period,

the finalreportwas "notviable."

Organisms from the various hospital laboratories

wereidentified withthe API 20Eteststrip (Analytab

Products,Plainville, N.J.), the MicroScan Gram

Neg-ativeCombotray (MicroScan, Inc., Hillsdale, N.J.),

theN/Fsystemwheel(Flow Laboratories,Inc.,

Ros-lyn, N.Y.), or conventional methodology or all of

thesemethods. Theseorganisms werethenidentified

by the AMS in conjunction with the EBC+. All

isolates misidentified by the AMS were tested by

conventional methodology to reconfirm identifica-tions.

RESULTS AND DISCUSSION

The ability of the AMS to identify glucose-nonfermenting gram-negative rodswas

evaluat-edby testing 472 organisms obtainedfrom fresh clinical specimens and from a reference

collec-tion (Table 1). Of the isolates (410 organisms) included in the AMS data base, the overall

percent correctidentificationobservedwas89.3

(Table 2). Individual percentages were as fol-lows: P. aeruginosa, 95.7%; P. fluorescens, 91.3%; P.putida, 84.6%; P. maltophilia, 76.8%; P.cepacia, 93.5%; Acinetobacter calcoaceticus

(saccharolytic),

71.0%; and A. calcoaceticus

(non-saccharolytic),

100%. Misidentified

organ-isms were subjected to repeat tests (Table 3), and itwasfoundthat thesamemisidentifications

occurredinatleastone-halfof the repeattrials. The majority of the incorrect identifications

were with isolates of P. maltophilia and A.

TABLE 2. Accuracy of the ASM identification for

glucose-nonfermenting

rods included in the AMS

identification profile

Totalno. No.(%)correctly

Organism of isolates identified'

Pseudomonasaeruginosa 211 202 (95.7)

P.fluorescens 23 21 (91.3)

P.putida 26 22 (84.6)

P.cepacia 31 29 (93.5)

P.maltophilia 69 53 (76.8)

Acinetobactercalcoaceticus

(saccharolytic)

38 27 (71.0)

A.calcoaceticus

(non-saccharolytic)

12 12(100.0)

a Ofthe totalof410isolatesincluded intheAMSdata

base,

366

(89.3%)

were

correctly

identified.

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TABLE 3. Misidentifications forglucose-nonfermenting rods included in the AMS identificationprofile

Organismtested Initial AMS identification Frequencya RepeatAMS identification UIob

P.fluorescenslP. putida

P. cepacia

UIo

UIo

P.aeruginosa

P.cepacia

UIo

Vibriocholerae

UIo

P.cepacia

Klebsiella rhinoscleromatis

Providencia stuartii

4/221 UIO (2)C

P.fluorescensiP. putida (2)

4/211 P.fluorescensiP. putida (4)

1/211 P.cepacia(1)

2/23 UIO(2)

1/26 UIO

1/26 P.aeruginosa(1)

2/26 P. cepacia(2)

1/31 UIO(1)

1/31 P. cepacia (1)

7/69 UIO (2)

P.maltophilia (5)

7/69 P. maltophilia (2)

P.cepacia (4)

UIO (1)

1/69 P.maltophilia(1)

1/69 P. maltophilia (1)

Acinetobactercalcoaceticus

(saccharolytic)

A. calcoaceticus

(non-saccharolytic)

Proteus mirabilis

Shigellasp.

Providencia stuartii

Morganellamorganii

1/38 A. calcoaceticus

(non-saccharolytic)(1)

4/38 A.calcoaceticus(saccharolytic) (3)

Proteus mirabilis(1)

3/38 Shigellasp. (1)

Providencia stuartii(1)

A.calcoaceticus(saccharolytic) (1)

2/38 A.calcoaceticus(saccharolytic) (2)

1/38 A. calcoaceticus(saccharolytic) (1)

aNumberof misidentifications/total number oforganismstested.

bUIO, Unidentified organism.

cNumber ofresponses.

calcoaceticus

(saccharolytic). Of

38 isolates of A. calcoaceticus

(saccharolytic),

10 were

mis-identified as members of the family Enterobac-teriaceae; 7 of 69 isolates of P.

maltophilia

were

unidentified, and another7weremisidentifiedas

P. cepacia.

For the 62 isolates ofglucose nonfermenters whosecorrectidentificationwas notincluded in the AMSidentification profile,41of the isolates (66.1%)werecorrectly reportedas"unidentified

organism" (Table 4). Isolates were most often misidentified as P. cepacia and included six of sixisolates ofAchromobacterxylosoxidans,two

of threeAlcaligenes odorans,twoofthree

Pseu-domonas alcaligenes, one offour Alcaligenes denitrificans, andoneoffourPseudomonas

pau-cimobilis. Misidentified isolates (21 of 62) were

subjectedtorepeattests(Table 5). All organisms that were misidentifiedasP. cepaciawere

sus-ceptible to polymyxin B, whereas P. cepacia is

resistant to polymyxin B (6, 12). Therefore a

correlation of the AMS identification of P.

cepa-cia with thepolymyxin susceptibility would aid

inthe detection ofsomeof the AMS

misidentifi-cations.

AMSidentificationswereaccompanied by the

probability of correct identification as based uponbiochemicalprofiles of isolates in the data base. To examine the correlation between the AMS identifications and theidentification prob-abilities, the number of correct and incorrect

responses for 472 isolates was compared with

the identification probabilities (Table 6). The data showed thatatacorrectidentification prob-ability of -95%, 99.3% of thecorrectresponses weredetected. When loweringthe probabilityto

90%,oneadditionalisolatewascorrectly

identi-fied, and threemore weremisidentified. Similar

numberswere seenwhentheprobabilityinterval was 80 to 89%. When a correct identification probability of less than 80%wasused, therewas

1additionalcorrectresponse,and therewere23

incorrectresponses.Of the 23incorrect respons-es 15 were organisms actually included in the

AMSidentification profile andwere reported as

"unidentified organism." These data suggested

Pseudomonas aeruginosa

P.fluorescens

P.putida

P. cepacia

P. maltophilia

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AMS IDENTIFICATION OF NONFERMENTING 305

TABLE 4. Accuracyof the AMS identification of

62glucose-nonfermenting isolates not included in the

ASM identification profile

Organism Totalno. No.correctly

of isolates identified'

Alcaligenes denitrificans 4 3

A.faecalis 5 4

A.odorans 3 1

Achromobacter 6 0

xylosoxidans

CDCbgroupVA-1 1 1

Flavobacterium breve 1 1

Flavobacterium group II B 10 7

F.meningosepticum 1 1

Moraxella sp. 1 1

Pseudomonas acidovorans 3 3

P.alcaligenes 3 1

P.diminuta 6 5

P.paucimobilis 4 2

P.pseudoalcaligenes 5 3

P.putrefaciens 2 2

P.stutzeri 7 6

aCorrectidentification = "unidentified organism."

Ofthe total of 62 isolates not included in the AMS

identificationprofile,41(66.1%)werecorrectly

identi-fied.

b CDC,Centers forDisease Control.

that

there

was no

advantage

to

using

an

accept-able

identification

probability of lower

than

95%,

since

a

lower

percent

probability resulted

in

agreater

incidence of incorrect

responses.

Retrospective analysis of the AMS

identifica-tion data

was

performed with

an acceptable

identification probability of

.95%.

AMS

identi-fications

were

placed

into four

categories:

(i)

the

correct

identification with

a

probability of

.95%,

(ii)

an

incorrect identification with

a

probability

of

.95%, (iii)

an

identification

with

a

probability

of less than

95%,

or

(iv)

an

"uniden-tified

organism"

response

(Table

7). The

accura-cy

of the AMS in the

correct

identification of the

TABLE 6. Identification versus AMS identification

probability for the 472 glucose-nonfermenting rods

AMS No.

(%)b

of

identification No.

(%)M

of organisms organisms probability correctlyidentified incorrectly

probability

~~~~~~~~identified

.95 404 (99.3) 36 (55.4)

90-94 1 (0.2) 3 (4.6)

80-89 1 (0.2) 3 (4.6)

c79 1 (0.2) 23 (35.4)

a Percentage of the total number of correctly identi-fied organisms.

b Percentage of the total number of incorrectly identified organisms.

organisms

was

88.5% (category

i), and

4.1% of

the

isolates

were

misidentified

(category

ii).

The

remaining 7.4% of the isolates did

not meet the

criteria for

a

reportable identification, either by

having

an

identification

probability of

less than

95%

(category

iii)

or

by

being

reported

as

"un-identified

organism" (category iv). These

re-sponses

would

not

be

considered

incorrect

iden-tifications

but

would

require additional testing

for

complete

identification.

Manual

commercial

systems

for the

identifica-tion

of the nonfermenters

(e.g.,

API

20E,

N/F

system,

Minitek

[BBL Microbiology Systems],

and

Oxi/Ferm

[Roche Diagnostics, Div.

Hoff-mann-La Roche

Inc., Nutley, N.J.]) have been

evaluated

by several workers (2-4, 15,

16, 19).

Some

of the

systems

have been

reported

to

have

an accuracy

of less than 80%

for the

identifica-tion of the

nonfermenters,

which

indicates that

no system

is

entirely

reliable. The evaluations

often have

not

included

representative

numbers

of

organisms

frequently

encountered

in the

clini-cal

laboratory.

The AMS with the

EBC+ card

has been

designed

to

identify only

those

nonfer-menters

commonly

encountered in the

routine

microbiology laboratory (5,

14). This

study

has

TABLE 5. Misidentifications forglucose-nonfermenting rodsnotincluded in the AMS identification

profilea

Organismtested Initial AMSidentification Frequencyb RepeatAMSidentification

Alcaligenes

denitrificans

P.cepacia 1/4 P.cepacia

A.faecalis P. cepacia 1/5 UIO

A.odorans P. cepacia 2/3 P.cepacia

Achromobacterxylosoxidans P. cepacia 6/6 P. cepacia

Flavobacterium group II B Vibriocholerae 1/10 Vibriocholerae

P. maltophilia 2/10 P. cepaciaandP.maltophilia

Pseudomonas diminuta

Morganella

morganii 1/6 UIO

P.alcaligenes P.cepacia 2/3 P.

cepacia

P.paucimobilis Morganella morganii 1/4 UIO

P.cepacia 1/4 P.cepacia

P.pseudoalcaligenes P.

fluorescensiP. putida

2/5 P.

fluorescensiP.

putida

P. stutzeri P. cepacia 1/ UIO

aCorrectidentification fororganismsnotin

profile

= "unidentified

organism"

(UIO).

b Number ofmisidentifications/total number of

organisms

tested.

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TABLE 7. Accuracy of the AMS identificationofglucose-nonfermentingrods withanacceptable

identificationprobabilityof295%

Total No.(%) of No.(%) of No.(%)oflow No.

(%)

of

Organism no.of correct incorrect selectivity Uloe

isolates identificationsb identifications" identificationsd

Pseudomonasaeruginosa 211 202 (95.7) 5

(2.4)

0 (0)

4 (1.9)

P.fluorescens 23 21 (91.3) 0 (0) 0 (0) 2 (8.7)

P.putida 26 22 (84.6) 2 (7.7) 1 (3.8) 1 (3.8)

P.maltophilia 69 51 (73.9) 4 (5.8) 7(10.1) 7(10.1)

P. cepacia 31 28 (90.3) 0 (0) 2 (6.4) 1 (3.2)

Acinetobacter calcoaceticus 38 27 (71.0) 6(23.7) 5(13.2) 0 (0)

(saccharolytic)

A.calcoaceticus 12 12(100.0) 0 (0) 0 (0) 0 (0)

(non-saccharolytic)

aForthetotal of 410isolates, therewere363

(88.5%)

correct

identifications,

17

(4.1%)

incorrect

identifica-tions, 15 (3.7%) lowselectivity identifications,and 15(3.7%) UIO.

b

Correct

identificationtothe genus andspecies levelat anidentification

probability

of

.95%.

cIncorrectidentificationtothegenus andspecieslevelat anidentification

probability

of

295%.

dIdentification to the genus andspecies levelatanidentification

probability

of<95%.

e

UIO,

Unidentifiedorganisms.

included representative numbers (410

organ-isms)

of the

commonly isolated nonfermenters

as

well

as some

(62

isolates)

of the

more

unusual

nonfermenters. The AMS

was

88.5%

accurate

in

the

identification of nonfermenters included in

the

data base.

Although the

percentage

of AMS

misidentifications

was

low

(4.1%),

some

addi-tional

misidentifications could have been

detect-ed

by

testing for

polymyxin

susceptibility.

In summary,

the

AMS

provides

a

rapid

and accurate means

of

identifying

the

majority

of

glucose-nonfermenting

gram-negative

rods

iso-lated

from

clinical

specimens.

The

short

turn-around time and the decreased

amount

of

tech-nologist time required for identification of

not

only

the

nonfermenters

but also members of the

family Enterobacteriaceae

make the

AMS

EBC+

a

useful

adjunct

to

the

microbiology

laboratory. The AMS is

easy to

integrate into

the

work flow of the clinical

laboratory,

espe-cially the laboratory which is

operational for

more than one

shift

per

day.

The AMS

also

allows

for

same-day

reporting of

many

results

which

may be

important in

the

critical

care institution. The additional

capabilities

of the

AMS (yeast

identification,

susceptibility testing, and urine

screening)

may

influence

the decision

for

use of the AMS in the

clinical

laboratory.

LITERATURE CITED

1. Aldridge, C., P.W. Jones, S. Gibson, J. Lanham, M. Meyer, R. Vannest, and R. Charles. 1977. Automated microbiological detection/identification system. J. Clin. Microbiol. 6:406-413.

2. Appelbaum,P.C.,J.Stavitz,M.S. Bentz, and L. C. von Kuster. 1980. Fourmethods for identification of gram-negative nonfermenting rods: organisms more commonly encountered in clinical specimens. J. Clin. Microbiol. 12:271-278.

3. Burdash,N.M.,E. R.Bannister, J.P.Manos,and M. E.

West.1980.Acomparisonoffourcommercial systems for the identification ofgram-negative bacilli. Am. J. Clin. Pathol. 73:564-569.

4. Chester, B., and T.J. Cleary. 1980. Evaluation of the Minitek system for identification of nonfermentative and nonenteric fermentative gram-negativebacteria. J. Clin. Microbiol. 12:509-516.

5. Dowda, H. 1977. Evaluation oftworapid methods for identificationofcommonlyencounterednonfermentingor oxidase-positive,gram-negativerods. J. Clin. Microbiol. 6:605-609.

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11. Kelly,M.T., and J. M. Latimer. 1980. Comparison of the AutoMicrobic System with API, Enterotube, Micro-ID, Micro-Media Systems, and conventional methods for identification of Enterobacteriaceae. J. Clin. Microbiol. 12:659-662.

12. Lennette, E. H., A. Balows, W. J. Hausler, Jr., and J. P. Truant. 1980. Manual ofclinical microbiology, 3rd ed. AmericanSocietyforMicrobiology, Washington, D.C. 13. Nicholson,D.P., and J. A. Koepke. 1979. The

AutoMicro-bicSystem for Urines. J. Clin. Microbiol. 10:823-833. 14. Otto, L.A., and U. Blachman. 1979. Nonfermentative

bacilli: evaluation ofthree systems for identification. J. Clin.Microbiol. 10:147-154.

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RODS 307 15. Shayegani, M., A. M. Lee, and D.M. McGlynn. 1978.

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16. Shayegani,M., P. S.Maupin, and D. M. McGlynn. 1978. Evaluation of the API 20E systemfor identification of nonfermentative gram-negative bacteria. J. Clin. Micro-biol. 7:539-545.

17. Smith, P.B., T. L. Gavan,H. D. Isenberg, A. Sonnen-wirth,W. I. Taylor,J.A. Washington II, and A. Balows.

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18. Sonnenwirth,A.C. 1977. Preprototype ofanautomated microbial detectionandidentificationsystem: a

develop-mentalinvestigation.J.Clin, Microbiol. 6:400-405. 19. Warwood, N.M.,D.J. Blazevic,and L. Hofherr. 1979.

ComparisonoftheAPI20EandCorningN/Fsystemsfor identification ofnonfermentative gram-negative rods. J. Clin.Microbiol. 10:175-179.

VOL. 15, 1982

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