• Find shared interest across broad areas of expertise that can drive analysis and interpretation of the massive amounts of sequencing data that are accumulating.

    • Advances in sequencing technology have generated tremendous amounts of sequencing data, a fact that Karen Nelson, Lita Proctor, and Jennifer Russo Wortman all addressed in different ways. Vincent Young emphasized the importance of finding common ground among broad areas of expertise where experts can work together to drive analysis and interpretation of those data. Too often, he said, sequencing projects end up “half-baked” because researchers are unsure how to proceed.

  • Supplement sequencing studies with mechanistic studies.

    • Peter Turnbaugh noted that sequencing studies should be complemented with mechanistic studies in animal or perhaps even non-animal model systems. Regardless of the specific research question, without knowing anything about fundamental mechanisms, it is difficult to know what to measure in human studies.

  • Collect prospective data that can inform causality.

    • Many comments were made throughout the workshop about the abundance of data showing correlations, but not causality, between the microbiome (both composition and activity) and health or disease. Johanna Lampe expressed concern that not enough attention is being directed toward causality. In many cases, it is not clear if a microbial community known to be associated with a disease is a consequence of that disease or a contributing factor. She has been pushing the cancer community to start collecting fecal samples, but the need exists across multiple disease areas, not just cancer.

  • Continue to explore not just the microbiome, but also the metabolome and its role in human health and disease.

    • Josef Neu urged more studies aimed at understanding the metabolic consequences of the microbiome. For example, researchers have identified microbes associated with necrotizing enterocolitis and other phenomena in preterm babies, but they do not understand the metabolic implications of this association. Johanna


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