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Aperiomics Launches Commercial NGS-based Pathogen Detection Services


NEW YORK (GenomeWeb) — Aperiomics has officially launched its commercial sequencing and bioinformatics-based pathogen detection service, debuting at the annual meeting of the Association for Molecular Pathology last week.

The company will offer three distinct services based on metagenomic sequencing and bioinformatic analyses to identify infectious organisms in mixed samples. Its Absolute-ID is intended for the detection of known pathogens, while its Absolute-Discovery will be used in cases where it is necessary to characterize unknown or novel organisms.

A third test, Absolute-Biome is intended to detect and characterize all microorganisms, the entire microbiome, of a single sample.

Crystal Icenhour, the company's CEO, told GenomeWeb that the services are being marketed as research-use only, but that Aperiomics hopes with its commercial launch to be able to move into more clinical applications as well.

Though the company's interpretation services are research tools, she said that there have been cases where Aperiomics has analyzed clinical lab specimens, in instances where all other technologies have failed to find the source of a patient's infection. However, Aperiomics makes clear to ordering clients that its reports are not intended for diagnostic use.

Because the cost of sequencing remains a little too high for routine use, Icenhour said that the company expects its market to be mainly identifying pathogens in environmental or clinical samples where other standard approaches have failed.

"Our market is really any client that has a problem they can't answer in another way," she said. "Eventually we'd like to be in more basic pathogen identification ... The price is too high right now, but we'll get there," she added.

While the cost of the company's services vary based on the extent of analysis and the particular sample, Icenhour said that, for example, Aperiomics' Absolute-Discovery ranges from $1,500 to $2,500.

Previously called NextGen Diagnostics, Aperiomics rebranded and relaunched itself in June of this year and then officially debuted its commercial services last week. The company's informatic and analytic strategies were developed by its three co-founders, Keith Crandall, Evan Johnson, and Eduardo Castro-Nallar.

Crandall is the director of the Computational Biology Institute at George Washington University; Johnson is an assistant professor of medicine, biostatistics, and bioinformatics at Boston University's School of Medicine; and Castro-Nallar recently received his PhD from the biological sciences program at GWU.

While Aperiomics performs sample preparation and sequencing itself — a step Icenhour said is necessary because many of its clients don't have the resources to perform those analyses themselves — it distinguishes itself mainly in its unique informatic approach.

Right now the company uses both Illumina and Life Technologies' Ion Torrent sequencing, but it is platform agnostic overall.

All the DNA in a sample is sequenced, Icenhour explained, and then sequences that are not of interest, for example, those belonging to an infected human or animal, are filtered out, leaving only the data corresponding to microbial or other pathogen DNA present in the sample.

Icenhour said that the company calls its informatics strategy "no-assembly required" because, unlike other sequencing methods, it does not require that pathogen sequences be assembled. Rather, it identifies pathogens present in a sample by matching fragments of their genomes to references without assembling them.

"Traditionally, when people have genomic data, they assemble sequences in order to analyze them," she said. "But that takes a very long time and artifacts can be introduced into that process."

"With our approach, we can identify what's in a sample with very low coverage and in a rapid time frame without assembling the data. Basically, we are looking at the pieces of the puzzle and matching them to completed puzzles we already know about," said Icenhour.

The company's infomatics platform utilizes a Bayesian statistical framework that incorporates information on sequence quality, mapping quality and provides "posterior probabilities" of matches to a known database of target genomes.

In some cases, for example, if there is a novel virus that is discovered, the company does have to do assembly. But initial discovery of what is in the sample can be done without this step.

The company's founders have published on the public-facing version of their approach, called pathoscope, which Icenhour said is similar to, but not identical to, what Aperiomics uses in its internal commercial efforts.

In a study in Genome Research in 2013 the group reported that an early version of pathoscope required less than 1x coverage compared to 50-100x coverage required by assembly-based algorithms. The researchers also demonstrated that their approach was more accurate than existing methods: in a comparison of data from Escherichia coli O104:H4 to 30 other E. coli strains, pathoscope showed "substantial improvement over naïve mapping, context mapping, and assembly-based methods for species identification and strain attribution," the authors reported.

In a more recent study, published in BMC Bioinformatics this year, researchers led by the Aperiomics founders showed that a version of pathoscope specifically designed for clinical samples could identify multiple pathogens in a single clinical sample, accurately identify pathogens at the subspecies level, and determine the nearest phylogenetic neighbor of novel or highly mutated pathogens.

The study also showed the method outperformed previously published pathogen identification methods with regard to computational speed, sensitivity, and specificity.

The application of metagenomics to clinical samples seems to be an emerging need and growing area of interest for the field. For example, researchers from the University of Warwick in the UK recently published a study demonstrating that direct metagenomic sequencing of DNA in sputum samples could accurately detect TB infection.

According to Icenhour, Aperiomics is hoping that sequencing-based strategies like its three new services may in the future be used in routine detection and classification of pathogens in clinical infectious disease diagnosis, as the cost and difficulty of sequencing go down.

In the mean time, it offers an option to close the case on difficult instances of infection that other more standard methods have not been able to resolve.