Metagenomic analysis of bloodstream infections in patients with acute leukemia and therapy-induced neutropenia

Abstract

Leukemic patients are often immunocompromised due to underlying conditions, comorbidities and the effects of chemotherapy, and thus at risk for developing systemic infections. Bloodstream infection (BSI) is a severe complication in neutropenic patients, and is associated with increased mortality. BSI is routinely diagnosed with blood culture, which only detects culturable pathogens. We analyzed 27 blood samples from 9 patients with acute leukemia and suspected BSI at different time points of their antimicrobial treatment using shotgun metagenomics sequencing in order to detect unculturable and non-bacterial pathogens. Our findings confirm the presence of bacterial, fungal and viral pathogens alongside antimicrobial resistance genes. Decreased white blood cell (WBC) counts were associated with the presence of microbial DNA, and was inversely proportional to the number of sequencing reads. This study could indicate the use of high-throughput sequencing for personalized antimicrobial treatments in BSIs.

Figure 1

(A) Distribution of sequencing reads between human and microbial origins. (B) Distribution of the detected microbes. Colored numbers indicate the number of occurrences per sampling category (red numbers: fever onset, blue: persistent fever, green: follow up). Two fever samples did not contain microorganisms, and there were no detections of pathogen DNA in 1 persistent fever sample and 6 follow up samples.

Figure 2

(A) Shannon’s diversity index is shown for bacteria, fungi and viruses at different time points of neutropenic fever. Significant decrease can be seen in bacterial diversity in follow up samples, due to antibiotic treatment. *denotes p ≤ 0.05. (B) Distribution of microbial reads per time points.

Figure 3

(A) Distributions of bacterial reads are shown in different diseases stages, with Propionibacterium dominating during the initial fever episode, while Corynebacterium, Staphylococcus and Dolosigranulum were also detected in persisting fevers. Bacterial taxa which consisted of <1% of all reads in a sample are not shown. (B) Distribution of fungal taxa detected in the samples used in this study indicate the presence of Fusarium in different disease stages, possibly implying subclinical fungal infections. (C) Distribution of reads belonging viral taxa at different sampling time points. Numbers within the pie charts indicate the number of samples positive for the given pathogen.

Figure 4. Relative abundances of bacterial, fungal and viral taxa are shown in individual samples.

The highest bar for each patient represents the highest number of reads; the heights of other bars of the same patient are proportional to the highest. Wider bars represent taxa on the species level, slim bars show domains. Only taxa with ≥1% relative abundance are shown.

Figure 5

(A) Clinical characteristics of the samples used in this study, measured at the time of sampling. (B) Comparison of white blood cell count and absolute neutrophil count between samples with and without the presence of microbial DNA. (C) Comparison of WBC and ANC between samples with the highest microbial reads (>10,000) versus samples with microbial reads lower than 10,000. *denotes p ≤ 0.05. WBC: white blood cell count, ANC: absolute neutrophil count, CRP: C-reactive protein, MASCC: Multinational Association for Supportive Care in Cancer risk score.