Bacterial Identification 101

Bacterial identification is the process of assigning an unknown bacterial strain to a known species or subspecies (note that only a few species have subspecies). Species is a basic unit of taxonomy, or classification of living organisms, and yet, it is not evident that ‘species’ as a discrete entity exists in the real bacterial world. Nevertheless, we still need the concept of species for practical reasons when classifying and identifying bacteria. Therefore we must also have an accepted working practice when defining bacterial species. Bacterial identification is a routine process for many clinical and environmental microbiology laboratories,  as well as those in the biotechnology and food processing sectors where quality control is extremely important. In recent years, big advances in bacterial identification have followed big advances in analytical chemistry and molecular biology, particularly, high-throughput DNA sequencing. There are now numerous methods that can be used to identify bacteria, and still, accuracy, turn-around-time (TAT), and cost are major concerns for laboratories that need to do this routinely. The accuracy of bacterial identification methods in particular, or rather inaccuracy, can lead to costly mistakes in industrial problem solving, and more importantly, costly mistakes in medical diagnoses and treatment.

Taxonomy consists of three basic interconnected processes: classification, nomenclature, and identification [Learn more]. Most academic, clinical and industrial microbiology laboratories focus on identification. Much fewer still fulfill the other processes of classification and nomenclature; these scientists are called “taxonomists”.


Two Categories of Identification Methods

All methods for bacterial identification fall into two categories:

  1. Pattern-based identification: A bacterial cell is made of DNA, RNA, proteins and other complex molecules that can be extracted and detected as various patterns. Patterns that are specific to a known species, we can be used to identify them. Various types of phenotypic, chemical, molecular and immunological patterns are used to assign bacterial isolates to known species. The quality of the identification is highly dependent on the quality of known patterns used to represent the true and broad diversity of the species. If new patterns have arisen in a target species (e.g. new variant), then identification can likely fail.
  2. Species concept-based identification: In this method, each bacterial isolate is compared to the type strains of  known species using the criterion that is used for defining bacterial species. Since the same method used to classify new species, is used to identify isolates, in theory, every identification should be successful and accuracy should be guaranteed. The only pitfall is that the cost and TAT of this method are generally higher than those of pattern-based methods.


Pattern-based identification systems

Method Pattern to detect Useful links
 Biochemical profiles  Presence of specific enzymes and metabolic pathways
 PCR  Presence of specific DNA sequences
 Gene sequencing  Sequence of a gene (e.g. 16S, gyrB)
Immunological  Presence of specific antigen
 MALDI-TOF  Mass spectra of whole cells. Patterns are mainly from ribosomal proteins that are most abundant in cells.  Seng et al. 2009
 Chemical  Profile of chemical components (e.g. cellular fatty acids, whole proteins). MALDI-TOF is one of these.


Species Concept-based Identification

The bacterial species concept is now based on direct comparison of genome sequences, so a species concept-based identification scheme can similarly be built using genome sequence data. This process involves two steps: (1) selection of phylogenetically close species using a fast search engine and (2) calculation of average nucleotide identify (ANI) to the chosen species. The generally accepted ANI cutoff for species boundary is 95~96 %.  The general standards and procedure for the taxonomic purposes were proposed that should give a good overview about the species concept-based identification scheme. [Chun et al., 2018].


The BIOiPLUG team / Last edited on Mar. 25, 2018