Reply:
Authors: Benjamin Lelouvier, Florence Servant, Michael Courtney, Rémy Burcelin, Jacques Amar
Journal: Hepatology (2016)

Potential conflict of interest: Dr. Lelouvier is employed by and holds intellectual property rights with Vaiomer. Dr. Servant is employed by Vaiomer. Dr. Amar is employed by, holds intellectual property rights, and received grants from Vaoimer. Dr. Courtney is employed by and owns stock in Vaiomer. Dr. Burcelin is employed by, owns stock, and received grants from Vaiomer. Author names in bold designate shared co‐first authorship. We thank Dr. Ling and colleagues for their valuable input. We agree that the blood microbiome, although most likely composed principally of bacteria and bacterial DNA of gut origin, contains bacterial material from other sources, including the oral cavity. These different sources of bacteria are not to be neglected as they could constitute an important component of certain physiopathological conditions. In this context we recently reported that the periodontal microbiota is associated with type 2 diabetes.1 However, we unfortunately had no information on the oral health status of the fibrosis cohorts for the work published in hepatology. One of the interesting features of the blood microbiome is that it incorporates different sources of bacteria and integrates multiple risk factors and clinical parameters such as origin of the patient, diet, living habits, and medical treatment, which makes the blood microbiome a powerful tool for the identification of biomarkers. However, this feature also complicates the task of finding modifications associated with clinical parameters, which are sometimes subtle, are immersed in the background of interindividual variations, and require specific expertise and tools. This interindividual diversity is well represented by principal coordinates analyses, which, in consequence, are not suitable for illustration of the differences between biological groups. For this reason, principal coordinates analyses are not presented in the article. In terms of read numbers, thanks to the high throughput of Illumina MiSeq technology, we obtained an average of 59,695 raw pairs (119,390 reads) per sample, which allowed exhaustive coverage of the operational taxonomic units of the samples as shown by the rarefaction curve (Fig. 1). More details about our sequencing pipeline can be found in our previous work.2 We also totally agree with Dr. Ling and colleagues that analysis of the blood microbiota of healthy individuals is critical for a better understanding of the modifications associated with disorders. We reported such an analysis in a previous publication.3 The question of what proportion of blood bacterial DNA corresponds to living or dormant bacteria is recognized as being of great importance to the understanding of the function of blood microbiome in health and disease.4 However, this question is less relevant in the context of biomarkers, so long as the correlation between the bacterial DNA and clinical parameters is significant and reproducible.Figure 1: Rarefaction curves of the sequencing of the blood samples from the Spanish discovery cohort (A) and the Italian validation cohort (B). Abbreviation: OTU, operational taxonomic unit.