Identification Methods for Bacteria and Fungi

Vikki Warren, Identification Services Manager

The revised Annex 1 came into force on 25 August 2023. These guidelines apply to sterile medicinal product manufacture, and aim to ensure that microbial, particulate and endotoxin/pyrogen contamination is prevented in the final product. This is obviously an essential goal when it comes to sterile medicinal products, so the application of the guidelines to create an effective contamination control strategy is of paramount importance.

With respect to the identification of microorganisms as part of the environmental monitoring programme, Annex 1 states that microorganisms detected in grade A and B areas should be identified to species level, and that consideration should also be given to the identification of microorganisms detected in grade C and D areas, where action limits or alert levels are exceeded, or following the isolation of organisms that may indicate a loss of control, deterioration in cleanliness, or that may be difficult to control. The importance of maintaining a current understanding of the typical flora of these areas is also highlighted.

Species level identification is therefore a key part of good manufacturing practice for medicinal products, and a quick turnaround is often required by pharmaceutical microbiologists. There are a number of different approaches to microbial identification – all of them have their pros and cons, so what are the key differences between the methods?

Phenotypic methods are often viewed as “traditional” microbiology and they use the metabolic differences between species to identify microorganisms. Generally, they involve a combination of Gram staining, culture, and biochemical tests. As the different tests are carried out, the results obtained narrow the possible options, until an identification is obtained.

The genotypic approach, on the other hand, identifies microbes on the basis of sequencing, and is sometimes referred to as the “gold standard”, as the DNA sequence has the potential to offer an unambiguous route to identification. Databases of genomes and gene fragments have been created, and this has transformed our ability to understand the relationships between different species, in some cases resulting in their reclassification.

Proteotypic identification, could be seen as sitting between genotypic and phenotypic methods since the genomic information is translated into proteins, and these proteins also reflect the cells’ metabolic functions.

The different categories include a number of different approaches, but in this article, I look at the methods that I have encountered, and been asked about most commonly.

Phenotypic methods

API strips

API (Analytical Profile Index) strips are a well established and commonly used identification method, familiar to many microbiologists. The tests detect enzymatic activity and the assimilation or fermentation of sugars, and when they were developed in the 1970s, they simplified identification by bringing together different biochemical tests in microtubes on one convenient strip, doing away with the need for racks of test tubes. Different strips are produced for different groups of organisms, and the user undertakes presumptive identification in order to select the appropriate strip.

Reagents in each tube are rehydrated with a suspension of the unknown isolate and following incubation, some tubes within the strips display colour changes due to alterations in pH. Assimilation tests within the strips are inoculated with minimal media – the bacteria grow if they are able to utilise the corresponding substrate, and a positive result is recorded if growth is observed. Other tubes within the strips may require the addition of reagents before recording a positive or negative result. A profile number determined from the sequence of positive and negative results is used to identify the species.

Advantages of API strips are that they are economical, have a long shelf life and are easy to use. Some disadvantages are that as a manual method, errors can be easily introduced; the requirement for incubation means that identification takes longer than some other methods; they are not used to identify moulds, and they identify a relatively limited range of bacteria and yeasts – 700 species in total.


VITEK 2 is an automated platform for phenotypic identification of bacteria and yeasts, as well as determination of antimicrobial resistance. The system essentially takes the API strip concept a step further, miniaturising the reaction tubes into cards with 64 microwells each. Different cards are available for the identification of different groups of organisms, and they are inoculated, incubated and interpreted automatically. During incubation the cards are read at 15-minute intervals to assess turbidity and colour changes. Data is collected and a quantitative value for proximity to each of the taxa within the VITEK database is calculated. If a unique identification is not achieved, a list of possible organisms is given, or the strain is determined to be outside the scope of the database.

The primary advantages of VITEK 2, in comparison to API strips, are elimination of some repetitive manual tasks and reduced opportunity for human error. VITEK 2 does, however, share many of the features of API strips: incubation is required, identification is limited to the strains included in the proprietary database, and it cannot be used to identify moulds.


BIOLOG is a biochemical testing method, based on carbon utilisation. The method provides a metabolic fingerprint and unlike API strips or VITEK 2, it can be used to identify filamentous fungi in addition to bacteria and yeasts. Product literature states that the method can identify more than 2,900 species.

The tests are performed within a 96 well microtiter plate, which includes a variety of different carbon sources and a redox dye. A change in the colour of the dye signifies growth in the well. The inoculated plates are incubated, read and compared to the BIOLOG databases. Manual, semi-automated and automated options are available. The manufacturers state that Gram stain and other pre-tests are not required – this may be seen as an advantage over other phenotypic systems. However, similarly to API and VITEK 2, the method requires a period of incubation, increasing the time taken to make an identification.

Proteotypic identification

MALDI-TOF mass spectrometry

Matrix assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry identifies bacteria and fungi by comparing a peptide mass fingerprint (PMF) of the unknown organism with the PMFs contained within a database. Essentially, this method is based on the analysis of proteins within the cell. For species-level identification, the mass range used represents mainly ribosomal proteins with a few housekeeping proteins. The most notable feature of this technique, particularly when compared with phenotypic techniques such as API strips, is its rapid turnaround – it can provide an identification in under an hour. However, some of our customers have highlighted examples to us that suggest the MALDI-TOF databases can, on some occasions, deliver poor isolate identifications.

Genotypic identification

16S sequencing – bacterial identification

16S sequencing identifies bacteria on the basis of the 16S ribosomal RNA gene, with full gene or some other combination of variable regions used. The variations that exist within the sequences can be used to determine the relationships between different organisms and build phylogenetic trees.

In practice, when people refer to the 16S technique, they are usually referring to sequencing the first 500 base pairs of the full gene. This is usually sufficient to identify bacteria at the species level. There are, however, some occasions where full 16S sequencing is required for identification of common environmental isolates, for example, in strains where indel mutations are present, and for distinguishing between some closely related species.

At NCIMB, sequence data is examined against the validated MicroSEQ® database in the first instance. Most identification systems, be it API strips, MALDI-TOF or MicroSEQ, are limited in their coverage of bacterial species. However, with 16S sequence data when MicroSEQ doesn’t provide a high enough species level match we can also use the (non-validated) European Nucleotide Archive (ENA) database from EMBL-EBI to match sequences obtained to published data, as well as the client’s own historic data collection and the NCIMB reference collection. 16S can be used to rapidly identify both viable and non-viable organisms, those with complex growth requirements and Gram variable isolates, as well as slow growing and /or non-fermenters.

Fungal identification – D2 LSU and ITS

Two approaches to genotypic identification of fungi are sequencing of the D2 region of the large subunit ribosomal RNA gene (D2 LSU), and sequencing of either one or both of the internal transcribed spacer regions between the small and large subunit ribosomal RNA genes (ITS). D2 LSU sequencing is probably the most widely used approach for mould and yeast identification at present. As with 16S sequencing for bacteria, sequence data obtained can be analysed using a validated commercial database that has been built using reference strains. Publicly available, but non-validated sources, such as the EMBL-EBI ENA database can also be used. This is a very active area of research and the amount of data available is continually expanding as researchers upload new results. In contrast to D2 LSU sequencing, at present, ITS generally relies more heavily on the use of data obtained from the unvalidated public databases.

When sequencing fungal isolates, NCIMB always uses a validated D2 LSU database in the first instance, as this gives the most reliable result. However, some families and genera are known to be difficult to identify to species level using D2 sequencing, and in my own experience, while it is usually possible to obtain a species level identification of yeasts using D2 LSU sequencing, we don’t get that level of identification for some moulds. In these cases it is often possible to obtain species level identification using ITS sequencing, as there is generally a higher level of differentiation between ITS sequences. Unlike ribosomal DNA, ITS sequences have no functional role, and consequently have accumulated a greater level of mutation, which aids identification.

Visit our microbial identification services pages or contact us to find out more about NCIMB’s bacterial and fungal identification pages.

Annex 1 states that microorganisms detected in grade A and B areas should be identified to species level


API stripsStrips of microtubes containing dehydrated substrates for biochemical tests. The microtubes are inoculated and incubated. Results are recorded as positive or negative, and an identification made using the profile obtained.Economical, user-friendly, long shelf life.Manual method. Risk of human error. Results based on colour changes which can be viewed differently by different operators. Does not identify moulds.
VITEK 2Automated platform for phenotypic identification of bacteria and yeasts.Faster than manual testing; eliminates repetitive manual tasks. Reduced risk of human error compared to API strips.Phenotypic method, dependent on
growth. Limited to the strains in the proprietary database. Does not identify moulds. High consumable costs compared to MALDI-TOF.
BIOLOGIdentification based on carbon utilisation. The method, which is undertaken in a 96 well microtiter plate, provides a metabolic fingerprint.Can be used to identify filamentous fungi in addition to yeasts and bacteria.High reagent costs compared to MALDI-TOF.
MALDI-TOFIdentification based on a peptide mass fingerprint.Fast, low costs, high throughput. Mass spectra of unidentified species can be added to the database after identification by sequencing. Lower cost than sequencing.Tailored to clinical isolates; high equipment costs. Has been reported to misidentify or provide no identification for some isolates. Result can be affected by sample preparation.
16SIdentification based on sequencing bacterial 16S ribosomal RNA gene.Fast and accurate. Gold standard technique. Can identify fastidious and uncultivable microorganisms.
Comprehensive sequence databases.
Can have a higher cost than
manual tests.
D2 LSUIdentification based on sequencing D2 region of the large subunit (LSU) ribosomal RNA gene of yeasts and mouldsFast and accurate. Gold standard technique. Can identify fastidious and uncultivable microorganisms.
Comprehensive sequence databases.
Can have a higher cost than
manual tests.
ITSIdentification based on sequencing internal transcribed spacer region of yeasts and moulds.ITS region has high degree of variation between closely related species. Wide range of ITS sequences in public databasesCan have a higher cost than
manual tests. Public databases used are not validated in same way as MicroSeq16S and D2 LSU databases.