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Human Longevity, Inc. and Venter Institute Scientists Publish Paper Demonstrating Inconsistency in Microbiome Studies due to Variable Approaches to DNA Sequencing and Data Analysis

Comparison of four common library prep methods found significant differences in types of microbes uncovered and showed biases in error and duplication rates

(SAN DIEGO, CA)—October 26, 2015—Human Longevity, Inc. (HLI), the genomics-based, technology-driven company, announced today that its researchers along with those from the J. Craig Venter Institute and the University of California, San Diego, have published a paper in the journal, Proceedings of the National Academy of Sciences (PNAS), outlining the confusing and conflicting microbiome results generated by a variety of next generation sequencing technology. They also outline recommendations for new research community standards in the microbiome research field given these differences. The paper is being published this week in the early online edition of PNAS.

The microbiome is the collection of trillions of microbes that live in and on the human body. The field is rapidly growing as more knowledge is discovered about how these microbes contribute to health and disease.

In this study, the research team led by Marcus Jones, Ph.D., HLI/JCVI, compared whole-genome sequencing data from complete microbial communities using four different library preparation protocols. Two of these methods required polymerase chain reaction (PCR), which is used to amplify nucleic acid fragments in the library prior to sequencing. The authors compared the methods using a synthetic mock community, which was composed of a mixture of 20 microbial genomic DNAs, as well as human stool samples taken at four different time points from a 22-year-old healthy female who was treated with an antibiotic for one week.

The two methods that did not require PCR resulted in lower error rates and higher-quality reads for the mock community compared with the PCR-based methods. Moreover, the four different libraries showed significant variation in the relative abundance of microbial members of the mock community and the stool samples.

According to Dr. Jones, “The findings from this study highlight the urgent need for consistency across next generation sequencing protocols to improve the interpretation of microbiome data in studies of human health and disease. Given our vast collective experience in metagenomics sequencing and analysis we recommend community standardization based on sample type and material abundance along with the inclusions of cell spike-in for DNA extraction controls.”

“We have long been observing the inconsistencies and inaccuracies in microbiome studies in the public domain and set out to both quantify these and to make recommendations based on our experiences. The microbiome is increasingly being used as an important component in healthcare by researchers and companies worldwide, including at HLI which offers complete microbiome sequencing as part of the company’s Health Nucleus comprehensive health service, thus we need standards to ensure that individuals are getting the most accurate and reliable information available,” said J. Craig Venter, Ph.D., Co-founder and CEO, HLI.

About Human Longevity, Inc. (HLI)
HLI is the genomics-based, technology-driven company creating the world’s largest and most comprehensive database of whole genome, phenotype and clinical data.  HLI is developing and applying large scale computing and machine learning to make novel discoveries to revolutionize the practice of medicine.  A privately held company headquartered in San Diego, CA, HLI was founded in 2013 by pioneers in the fields of genomics and stem cell therapy. HLI will be licensing access to its database, and developing new diagnostics and therapeutics as part of their product offerings. In October 2015, HLI launched the first Health Nucleus™, a genomic powered clinical research project that has the potential to transform healthcare. The Health Nucleus platform uses whole genome sequence analysis, advanced clinical imaging and innovative machine learning – combined with a comprehensive curation of personal health history – to deliver the most complete picture of individual health.  For more information, please visit

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