Overview of Bacterial Identification Methods and Strategies

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Overview of Bacterial Identification Methods and Strategies

Rationale for Approaching Organism Identification

It is challenging to determine how most effectively to present and teach diagnostic microbiology in a way that is sufficiently comprehensive and yet not excessively cluttered with rare and seldom-needed facts about bacterial species uncommonly encountered. Approximately 530 different bacterial species or taxa are reported by clinical microbiology laboratories across the United States (Figure 13-1). Yet 95% of the bacterial identifications reported are distributed across only 27 of these taxa. This is an indication of how infrequently the other 500 or more taxa are identified and reported. Therefore, although the chapters in Part III, Bacteriology, are intended to be comprehensive in terms of the variety of bacterial species presented, it is helpful to keep in perspective which taxa are most likely to be encountered in the clinical environment. The relative frequencies with which the common bacterial species and organism groups are reported in clinical laboratories are presented in Figure 13-2.

Historically, most chapters in microbiology texts have been organized by genus name; however, they failed to provide information and processes needed to understand what is involved in analyzing information from the clinical specimen to the identification of the correct genus. Many texts (including this one) provide flow charts containing algorithms or identification schemes for organism workup. Although these are helpful, one must be aware of the limitations of flow charts. In some cases they may be too general to be helpful; that is, they may lack sufficient detail to be useful for discriminating among key microbial groups and species. In other cases, they may be too esoteric to be of practical use in routine clinical practice (e.g., identification schemes based on cellular analysis of fatty acid analysis). In addition, many other criteria that must be incorporated into the identification process are too complex to be included in most flow charts. Thus, flow charts are only one of many tools used in the field of diagnostic microbiology.

Also, as discussed later in this chapter, organism taxonomy and profiles continuously change. Detailed flow charts are at risk of quickly becoming outdated. Furthermore, as is evident throughout the chapters in Part III, diagnostic microbiology is full of exceptions to rules, and flow charts are not constructed in a manner that readily captures many of the important exceptions.

To meet the challenges of bacterial identification processes beyond what can be portrayed in flow charts, the chapters in Part III have been arranged to guide the student through the entire workup of a microorganism, beginning with initial culture of the specimen. In most instances, the first information a microbiologist uses in the identification process is the macroscopic description of the colony, or colony morphology. This includes the type of hemolysis (if any), pigment (if present), size, texture (opaque, translucent, or transparent), adherence to agar, pitting of agar, and many other characteristics (see Chapter 7). After careful observation of the colony, the Gram stain is used to separate the organism into a variety of broad categories based on Gram stain reaction and the cellular morphology of gram-positive or gram-negative bacteria (e.g., gram-positive cocci, gram-negative rods; see Chapter 6). For gram-positive organisms, the catalase test should follow the Gram stain, and testing on gram-negative organisms should begin with the oxidase test. These simple tests, plus growth on MacConkey agar, if the isolate is a gram-negative rod or coccobacillus, help the microbiologist assign the organism to one of the primary categories (organized here as subsections). Application of the various identification methods and systems outlined in this chapter generate the data and criteria discussed in each chapter for the definitive identification of clinically relevant bacteria. Most of the procedures described in the following chapters can be found at the end of this chapter. In this chapter, each procedure includes a photograph of positive and negative reactions. Chapter 6 includes photographs of some commonly used bacteriologic stains. In addition, Table 13-1 lists several commonly used commercial identification systems for a variety of the microorganisms discussed in the following pages.

TABLE 13-1

Examples of Commercial Identification Systems for Various Organisms

Organism Group System Type Manufacturer Incubation Time
Enterobacteriaceae Manual:
 API 20E bioMérieux* 24-48 hr
 API Rapid 20E bioMérieux 4 hr
 Crystal Enteric/Nonfermenter Becton Dickinson Diagnostic Systems 18 hr
 RapID ONE Remel 4 hr
Automated:
 GNI bioMérieux 4-13 hr
 GNI+ bioMérieux 2-12 hr
 NEG ID Type 2 Dade MicroScan§ 15-42 hr
 Rapid NEG ID Type 3 Dade MicroScan 2.5 hr
 Sensititre AP80 Trek Diagnostic Systems 5-18 hr
Enterococcus spp. and Streptococcus spp. Manual:
 API 20 Strep bioMérieux 4-24 hr
 RapID STR Remel 4 hr
 Crystal Gram-Positive ID Becton Dickinson Diagnostic Systems 18 hr
Automated:
 GPI bioMérieux 2-15 hr
 Pos ID2 Dade MicroScan 18-48 hr
 Sensititre AP90 Trek Diagnostic Systems 24 hr
Haemophilus spp. Manual:
 API NH bioMérieux 2 hr
 RapID NH Remel 4 hr
 NHI bioMérieux 4 hr
 Crystal Neisseria/Haemophilus Becton Dickinson Diagnostic Systems 4 hr
Automated:
 HNID Dade MicroScan 4 hr
Neisseria spp. and Moraxella catarrhalis Manual:
 API NH bioMérieux 2 hr
 RapID NH Remel 4 hr
 NHI bioMérieux 4 hr
 Crystal Neisseria/Haemophilus Becton Dickinson Diagnostic Systems 4 hr
Automated:
 HNID Dade MicroScan 4 hr
Nonenteric gram-negative rods Manual:
 API 20NE bioMérieux 24-48 hr
 Crystal Enteric/Nonfermenter Becton Dickinson Diagnostic Systems 18-20 hr
 RapID NF Plus Remel 4 hr
Automated:
 GNI bioMérieux 2-18 hr
 NEG ID Type 2 Dade MicroScan 15-42 hr
 Sensititre AP80 Trek Diagnostic Systems 5-18 hr
Staphylococcus spp. Manual:
 API STAPH bioMérieux 24 hr
 Crystal Gram-Positive Becton Dickinson Diagnostic Systems 18-24 hr
Automated:
 GPI bioMérieux 2-15 hr
 Pos ID2 Date MicroScan 24-48 hr
Coryneform rods Manual:
 API Coryne bioMérieux 24 hr
 RapID CB Plus Remel 4 hr
 Crystal Gram-Positive Becton Dickinson Diagnostic Systems 18-24 hr
Automated:
 GPI bioMérieux 2-15 hr

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*Durham, N.C.: www.bioMerieux-Vitek.com

Sparks, Md.: www.bectondickinson.com

Lenexa, Kan.: www.remelinc.com

§West Sacramento, Calif.: www.dadebehring.com

Westlake, Ohio: www.trekds.com

Because diagnostic microbiology is centered around the identification of organisms based on common phenotypic traits shared with known members of the same genus or family, microbiologists “play the odds” every day by finding the best biochemical “fit” and assigning the most probable identification. For example, the gram-negative rod known as CDC group EF-4a may be considered with either MacConkey-positive or MacConkey-negative organisms, because it grows on MacConkey agar 50% of the time. Therefore, although CDC group EF-4a has been arbitrarily assigned to the section on oxidase-positive, MacConkey-positive, gram-negative bacilli and coccobacilli in this text, it is also included in the discussion of oxidase-positive, MacConkey-negative, gram-negative bacilli and coccobacilli. This example clearly demonstrates the limitations of solely depending on flow charts for the identification process.

The identification process often can be arduous and a drain on resources. Laboratorians must make every effort to identify only those organisms most likely to be involved in the infection process. To that end, the chapters in Part III have also been designed to provide guidance for determining whether a clinical isolate is relevant and requires full identification. Furthermore, the clinical diagnosis and the source of the specimen can help determine which group of organisms to consider. For example, if a patient has endocarditis or the specimen source is blood and a small, gram-negative rod is observed on Gram stain, the microbiologist should consider a group of gram-negative bacilli known as the HACEK (Aggrega-tibacter [formerly the aphrophilus group of Haemophilus and Actinobacillus], Cardiobacterium hominis, Eikenella corrodens, and Kingella spp.), which are not commonly encountered in clinical specimens. Similarly, if a patient has suffered an animal bite, the microbiologist should think of Pasteurella multocida if the isolate is gram negative and Staphylococcus hyicus and Staphylococcus intermedius if the organism is gram positive. Finally, in consideration of an isolate’s clinical relevance, each chapter also provides information on whether antimicrobial susceptibility testing is indicated and, if needed, the way it should be performed.

Future Trends of Organism Identification

Several dynamics are involved in clinical microbiology and infectious diseases that continue to challenge bacterial identification practices. For instance, new species associated with human infections will continue to be discovered, and well-known species may change their characteristics, affecting the criteria used to identify them. For these reasons, identification schemes and strategies for both conventional methods and commercial systems must be continually reviewed and updated. Also, although most identification schemes are based on the phenotypic characteristics of bacteria, the use of molecular and advanced chemical methods (e.g., matrix-assisted laser desorption/ionization time-of-flight mass spectrometry) to detect, identify, and characterize bacteria continues to expand and play a greater role in diagnostic microbiology. In addition, phenotypic, molecular, and advanced chemical methods increasingly will become incorporated into simpler automated systems.

Procedure 13-3   Bacitracin Susceptibility

Procedure 13-7   CAMP Test

Procedure 13-8   Catalase Test

Procedure 13-10   Citrate Utilization

Procedure 13-11   Coagulase Test

Procedure 13-12   Decarboxylase Tests (Moeller’s Method)

Method

Quality Control

Positive:

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