This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: In acute, life-threatening infections, rapidly characterizing the microorganisms in a patient sample can help guide diagnosis and treatment. Computational methods known as taxonomic profilers can analyze metagenome sequencing data generated from the microorganisms' genomic information and compare it with reference genomes of individual microorganisms.
However, taxonomic profilers are still under development and are not yet in common use. Current methods can produce false-positive results or inaccurate abundance estimates. Researchers at the Helmholtz Centre for Infection Research (HZI) have developed a new taxonomic profiler called Metax.
By using information about how sequencing reads are distributed across microbial reference genomes, Metax can distinguish true microbial signals from artifacts more reliably and improve both taxonomic identification and abundance estimation. The study was published in the journal Cell. "In clinical samples, for example, microbial profiling can provide important information about microorganisms that may be relevant for an infection," explains Alice McHardy, a professor and head of the research group "Computational Biology for Infection Research" at HZI.
"Such information can complement established diagnostic approaches and help researchers and clinicians investigate potential pathogens. But taxonomic profiling is equally important far beyond clinical applications, from human microbiome research to environmental monitoring." Most taxonomic profilers compare sequencing reads from a sample with reference genomes stored in databases. This seemingly straightforward task is complicated by the fact that different microorganisms can share highly similar DNA sequences.
Reference genomes may also contain contaminating sequences. In addition, traces of microbial DNA can sometimes come from laboratory reagents used during sample preparation—a source of contamination often referred to as the "kitome." As a result, sequencing reads may match reference genomes of microorganisms that are not actually present in the sample. "An important piece of information is where these matching reads occur across the genome," says Dr.
Zhi-Luo Deng, a scientist in McHardy's research group and first author of the study. "If a microorganism is truly present, we generally expect reads to be distributed across multiple regions of its genome. False-positive signals, in contrast, are often restricted to only one or a few local regions, with little or no support elsewhere." Metax was designed to look beyond a simple sequence match.
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