A typical treatment path for many patients with acute leukemia (AL) includes multiple rounds of chemotherapy followed by allogeneic hematopoietic cell transplantation (allo-HCT). Extensive antibiotic exposure, prolonged and repeated healthcare facility contact, nutritional changes, and gut barrier damage in these patients result in major disruptions in the gut microbial communities [1, 2]. Gut dysbiosis has been associated with adverse HCT outcomes including infection [3,4,5], graft-versus-host disease [6, 7], and mortality [8,9,10].
Diversity, typically defined by the Shannon diversity index (SDI) , is commonly used as an indicator of microbiome “health”. However, this definition is limited because microbial communities with the same level of diversity may have vastly different compositions with different impacts on the host. After repeated courses of antibiotics, the gut microbiome in healthy individuals usually regains its original diversity but sometimes stabilizes in a different steady state . Although the long-term consequences of such microbiome shifts are unclear, their occurrence highlights the limitations of SDI when used as a sole descriptor of the microbiome. We hypothesized that in the setting of HCT, the pre-conditioning microbiome may be diverse but have a different configuration from its original state before chemotherapy for the underlying hematologic malignancy. In other words, diversity may mask a failure of microbiome recovery to its original state. We suspected that prolonged exposure to multiple antibiotics during intensive chemotherapy exemplifies sustained, compounded ecosystem perturbations, contrasting with the previously reported scenario of pulse disturbance (e.g., brief exposure to a single antibiotic) . Compounded perturbations often yield unanticipated consequences for the microbial ecosystem .
Identifying microbiome shifts along the path from induction chemotherapy through HCT requires longitudinal studies that span the different phases of treatment. Such an approach would establish the relationship between the original pre-chemotherapy microbiome and the pre-HCT microbiome. We therefore investigated whether the microbiome has recovered to its original pre-chemotherapy baseline at the time of referral for allo-HCT. We were able to study serial stool samples of three AL patients, collected three times weekly during the initial anti-leukemia chemotherapy and through the course of allo-HCT, starting before transplant conditioning to post-transplant day 14. The University of Minnesota Institutional Review Board approved this observational study.
We use the following notations for critical timepoints: (i) AL-b (acute leukemia baseline), the sample collected before anti-leukemia chemotherapy; (ii) AL-e (acute leukemia endpoint), the last sample collected during hospitalization for anti-leukemia chemotherapy; (iii) HCT-b, the sample collected upon hospital admission for HCT (before conditioning); and (iv) HCT-e, the sample collected at post-transplant day 14. Stool samples were analyzed by 16S rRNA genome profiling of the V4 hypervariable region on the Illumina MiSeq platform (Illumina, Inc., San Diego, CA) at the University of Minnesota Genomics Center. Raw sequence data are available under NCBI BioProject accession SRP141385 and SRP141394.
SDI dynamics are shown in Fig. 1a–c. In patients 1 and 2, SDI decreased during chemotherapy but recovered at least partially by HCT-b. In patient 3, SDI remained relatively stable through chemotherapy until HCT-b. Next, we investigated compositional differences between longitudinal samples from baseline. Dissimilarity between samples was measured using the Bray-Curtis (B-C) dissimilarity index , where a lower B-C index reflects more similar community compositions. With AL-e defined as baseline (Fig. 1d–f), B-C curves in all three patients were V-shaped. This was not surprising because we expected AL-e to be the point where microbiome injury was most severe, and hence, we expected the microbiome at the preceding and subsequent timepoints to be increasingly dissimilar to AL-e.
AL-b and HCT-b microbiomes in patients 1 and 2 had a relatively similar B-C distance from AL-e. A tempting explanation for this finding was that AL-b and HCT-b microbiomes were relatively similar to each other. This scenario would mean recovery of the microbiome after AL-e to its original state (AL-b), i.e., true microbiome recovery. To evaluate this explanation directly, we then measured B-C dissimilarities to the AL-b timepoint (Fig. 1g–i). Surprisingly, the HCT-b sample was highly dissimilar to AL-b in patients 1 and 2. This finding shows that during the interval between completion of chemotherapy and admission for HCT in these two patients, the microbiome recovered its diversity after a low-diversity state at AL-e, but did not recover its original pre-chemotherapy configuration at AL-b; rather, it developed an almost completely different composition at HCT-b. In patient 3, although the HCT-b sample was ~20% dissimilar to AL-e (suggesting at least partial recovery) (Fig. 1f), both HCT-b and AL-e samples were ~75% dissimilar to AL-b (Fig. 1i), suggesting that the path of recovery was not toward the original baseline, AL-b. Supplementary Fig. S1 shows the relative abundance of four of the most prominent taxa in longitudinal samples.
While the diversity of the pre-HCT microbiome may be comparable to the original microbiome before anti-leukemia chemotherapy, our results indicate that its composition may be completely different. Whether the new microbiome configuration is equally able to withstand further insults (e.g., vulnerability to pathobiont invasion and expansion during HCT) needs further research. Although limited by small sample size, our findings suggest that recovery of diversity alone is not an adequate surrogate for microbiome recovery. Microbiota composition and its potential functionality should be considered along with diversity in drawing conclusions from microbiome studies.
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A University of Minnesota Medical School Innovation grant (to AR), a University of Minnesota Foundation grant (to AR), and funding from Achieving Cures Together and Hubbard Foundation supported this research. We thank Markas Welke, Andrea Hoeschen and Kevin Olson for coordinating sample collections. Sequence data were processed and analyzed using the resources of the Minnesota Supercomputing Institute.
Conflict of interest
The authors declare that they have no conflict of interest.
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Rashidi, A., Kaiser, T., Holtan, S.G. et al. Pre-transplant recovery of microbiome diversity without recovery of the original microbiome. Bone Marrow Transplant 54, 1115–1117 (2019). https://doi.org/10.1038/s41409-018-0414-z
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