Blood circulates throughout the human body and contains molecules drawn from virtually every tissue, including the microbes and viruses which colonize the body. Through massive shotgun sequencing of circulating cell-free DNA from the blood, we identified hundreds of new bacteria and viruses which represent previously unidentified members of the human microbiome. Analyzing cumulative sequence data from 1,351 blood samples collected from 188 patients enabled us to assemble 7,190 contiguous regions (contigs) larger than 1 kbp, of which 3,761 are novel with little or no sequence homology in any existing databases. The vast majority of these novel contigs possess coding sequences, and we have validated their existence both by finding their presence in independent experiments and by performing direct PCR amplification. When their nearest neighbors are located in the tree of life, many of the organisms represent entirely novel taxa, showing that microbial diversity within the human body is substantially broader than previously appreciated.

Reduced-intensity conditioning (RIC) regimens have the potential to decrease toxicities related to hematopoietic stem cell transplantation (HCT) in patients with sickle cell disease (SCD) and thus make HCT a more acceptable therapeutic option for this group of patients. We report the results of 7 patients enrolled on a study to evaluate safety and efficacy of HCT using bone marrow from an HLA matched sibling donor following an RIC regimen for patients with high-risk SCD. The conditioning regimen consisted of busulfan, fludarabine, equine antithymocyte globulin, and total lymphoid irradiation with shielding of the liver, lungs, heart, and gonads on day 1. Graft-versus-host disease (GVHD) prophylaxis consisted of cyclosporine and mycophenolate mofetil. The regimen was well tolerated, and all patients had hematopoietic recovery. Six of 7 patients are stably engrafted off immunosuppression and without sickle cell-related symptoms at 2 to 8.5 years after HCT. Consistent with the complete resolution of SCD related symptoms observed in the 6 engrafted patients, erythropoiesis of complete or predominantly donor origin was detected by red blood cell-specific chimerism assays, despite their having persistent mixed chimerism in the mononuclear and lymphoid compartments. These findings demonstrate the curative potential of allogeneic HCT after an RIC regimen in patients with SCD.

Quantification of cell-free DNA (cfDNA) in circulating blood derived from a transplanted organ is a powerful approach to monitoring post-transplant injury. Genome transplant dynamics (GTD) quantifies donor-derived cfDNA (dd-cfDNA) by taking advantage of single-nucleotide polymorphisms (SNPs) distributed across the genome to discriminate donor and recipient DNA molecules. In its current implementation, GTD requires genotyping of both the transplant recipient and donor. However, in practice, donor genotype information is often unavailable. Here, we address this issue by developing an algorithm that estimates dd-cfDNA levels in the absence of a donor genotype. Our algorithm predicts heart and lung allograft rejection with an accuracy that is similar to conventional GTD. We furthermore refined the algorithm to handle closely related recipients and donors, a scenario that is common in bone marrow and kidney transplantation. We show that it is possible to estimate dd-cfDNA in bone marrow transplant patients that are unrelated or that are siblings of the donors, using a hidden Markov model (HMM) of identity-by-descent (IBD) states along the genome. Last, we demonstrate that comparing dd-cfDNA to the proportion of donor DNA in white blood cells can differentiate between relapse and the onset of graft-versus-host disease (GVHD). These methods alleviate some of the barriers to the implementation of GTD, which will further widen its clinical application.

Dose assessment after radiological disasters is imperative to decrease mortality through rationally directed medical intervention. Our goal was to identify biomarkers capable of qualitative (nonirradiated/irradiated) and/or quantitative (dose) assessment of radiation exposure. Using real-time quantitative PCR, biodosimetry genes were identified in blood samples from cancer patients undergoing total-body irradiation. Time- (5, 12, 23, 48 h) and dose- (0-8 Gy) dependent changes in gene expression were examined in C57BL/6 mice. A training set was used to derive weighted voting classification algorithms (nonirradiated/irradiated) and continuous regression (dose assessment) models that were tested in a separate validation set of mice. Of eight biodosimetry genes identified in cancer patients ( ACTA2 , BBC3 , CCNG1 , CDKN1A , GADD45A , MDK , SERPINE1 , Tnfrsf10b ), expression of BBC3 , CCNG1 , CDKN1A , SERPINE1 and Tnfrsf10b was significantly (P < 0.05) increased in irradiated mice. CCNG1 and CDKN1A expression segregated irradiated mice from controls with an accuracy, specificity and sensitivity of 96.3, 100.0 and 94.4%, respectively, at 48 h. Multiple linear regression analysis predicted doses for the 0-, 1-, 2-, 4-, 6- and 8-Gy treatment groups as 0.0 ± 0.2, 1.6 ± 1.0, 2.9 ± 1.4, 5.1 ± 2.0, 5.3 ± 0.7 and 10.5 ± 5.6 Gy, respectively. These results suggest that gene expression analysis could be incorporated into biodosimetry protocols for qualitative and quantitative assessment of radiation exposure.