Multi-Locus Sequence Typing

What is MLST?

Multilocus Sequence Typing (MLST) is a molecular typing method used to identify and differentiate strains of bacteria based on their DNA sequences. MLST involves analyzing the sequences of several different genes, or loci, across the bacterial genome, which can provide more precise and accurate identification of bacterial strains compared to other typing methods.

The MLST process involves amplifying and sequencing several conserved housekeeping genes, which are genes that are present in most bacteria and are essential for basic cellular functions. By sequencing these genes, researchers can identify differences in the nucleotide sequences of each gene, which can be used to create a unique sequence type for each bacterial strain.

What is MLST used for?

MLST is useful for several reasons. Firstly, it provides a standardized and reproducible method for identifying bacterial strains, which is important for tracking the spread of infections and outbreaks. Secondly, MLST can help researchers understand the evolution and genetic diversity of bacterial populations, as it can reveal patterns of genetic relatedness and help identify the emergence of new strains. Finally, MLST can be used to study the epidemiology of bacterial infections, such as identifying the sources of outbreaks and tracing the transmission of infections between individuals and across different geographic locations.

Overall, MLST is a powerful tool for studying bacterial genetics and epidemiology, and has been widely used in a variety of research and clinical settings to understand the spread and evolution of bacterial pathogens.

Does MLST cover all bacterial species?

No, MLST is specific to bacterial species that have been sequenced and for which appropriate gene targets have been identified. MLST targets conserved housekeeping genes, which are genes that are essential for basic cellular functions and are conserved across many bacterial species. However, not all bacterial species have been sequenced, and even among those that have, not all have appropriate gene targets for MLST. Additionally, MLST schemes may be optimized for specific bacterial species or groups of related species, so the number and selection of gene targets may vary depending on the bacterial group being studied.

That being said, MLST has been developed for many bacterial species and is a widely used typing method in research and clinical settings. As more bacterial genomes are sequenced and analyzed, MLST schemes are continually being developed and updated to cover a wider range of bacterial species and to improve the accuracy and precision of bacterial typing.

What are the different types of MLST?

There are several different types of MLST, which differ in the number and selection of gene targets, the methodology used for sequencing and analysis, and the specific applications for which they are used. Here are some examples:

Classical MLST

This is the original and most widely used form of MLST. It typically targets seven conserved housekeeping genes and is used to differentiate bacterial strains for epidemiological and evolutionary studies.

Core Genome MLST

This approach targets a larger number of genes that are present in the core genome of a bacterial species, which may provide higher resolution and discriminatory power for distinguishing closely related strains.

Whole Genome MLST

This approach involves sequencing the entire genome of a bacterial strain and using bioinformatics tools to identify and analyze gene variations. This can provide the highest level of resolution and accuracy for bacterial typing, but is also the most resource-intensive and expensive method.


This is an electronic database that stores MLST data for a variety of bacterial species, providing a centralized resource for researchers and clinicians to access and compare MLST data across different studies and locations.


This approach uses a core genome MLST scheme, but with a higher number of gene targets to provide even greater resolution and discriminatory power.

MSLT-like methods

There are several related methods, such as Multi-Virulence-Locus Sequence Typing (MVLST), Multi-Drug-Resistance Sequence Typing (MDRST), and others, which apply the principles of MLST to specific applications, such as studying virulence factors or antibiotic resistance in bacterial strains.

Overall, the choice of MLST method depends on the specific bacterial species being studied, the research or clinical application, and the availability of resources and expertise for performing the sequencing and analysis.


Classical MLST

7 conserved housekeeping genes

PCR amplification and sequencing

Epidemiological and evolutionary studies

Core Genome MLST

Large number of genes in the core genome

PCR amplification and sequencing

Higher resolution and discriminatory power

Whole Genome MLST

Entire genome sequence

Next-generation sequencing and bioinformatics

Highest resolution and accuracy


Electronic database of MLST data

Online database

Centralized resource for accessing and comparing MLST data


Large number of gene targets in the core genome

PCR amplification and sequencing

Even greater resolution and discriminatory power


Specific virulence genes

PCR amplification and sequencing

Studying virulence factors


Genes associated with antibiotic resistance

PCR amplification and sequencing

Studying antibiotic resistance

MLST reference schemes used by EzBioCloud Clinical Metagenomics

In the EzBioCloud Clinical Metagenomics, the MLST schemes available at PubMLST repository ( are utilized as the references for MLST reconstruction.

When the list of bacterial species detected in the previous step includes one or more of the MLST-applicable species, the matched MLST schemes are pooled and metagenomic MLST reconstruction is launched.

MLST reconstruction from metagenome reads

First step is the read recruitment for the targeted loci. We have compiled the lengthy set of full-length CDS sequences per each MLST-target locus from the vast Ez-Mx genome database. To collect the subset of the reads that can be utilized to reconstruct the alleles at the MLST-target loci, we map the QC-passed host-removed Illumina reads against the full-length CDS sequence baits (reference index) using Bowtie2.

In the second step, the mapped reads are pooled and assembled into alleles using the transcripts assembly workflow of SPAdes.

In the last step, the assembled alleles are searched against the reference alleles using blastn, looking for the perfectly matched alleles.


Seemann T. MLST: Multi-Locus Sequence Typing. 2017. Available from:

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