Host DNA depletion on frozen human respiratory samples enables successful metagenomic sequencing for microbiome studies

Abstract

Most respiratory microbiome studies use amplicon sequencing due to high host DNA. Metagenomics sequencing offers finer taxonomic resolution, phage assessment, and functional characterization. We evaluated five host DNA depletion methods on frozen nasal swabs from healthy adults, sputum from people with cystic fibrosis (pwCF), and bronchoalveolar lavage (BAL) from critically ill patients. Median sequencing depth was 76.4 million reads per sample. Untreated nasal, sputum, and BAL had 94.1%, 99.2%, and 99.7% host reads, respectively. Host depletion effects varied by sample type, generally increasing microbial reads, species and functional richness; this was mediated by higher effective sequencing depth. Rarefaction curves showed species richness saturation at 0.5-2 million microbial reads. Most methods did not change Morisita-Horn dissimilarity for BAL and nasal samples although the proportion of gram-negative bacteria decreased for sputum from pwCF. Freezing did not affect the viability of Staphylococcus aureus but reduced the viability of Pseudomonas aeruginosa and Enterobacter spp.; this was mitigated by adding a cryoprotectant. QIAamp-based host depletion minimally impacted gram-negative viability even in non-cryoprotected frozen isolates. While some host depletion methods may shift microbial composition, metagenomics sequencing without host depletion severely underestimates microbial diversity of respiratory samples due to shallow effective sequencing depth and is not recommended.

Fig. 1. Overview of study design.

Samples collected from the same participant were aliquoted so that paired comparisons could be made between treated and untreated samples. For nasal samples, it was only feasible to collect 4 swabs from a participant at the same time, thus a total of 10 swabs for the untreated condition was required to allow for paired treated and untreated comparisons.

Fig. 2. Sample relative read abundances of microbial non-viral and viral clades stratified by sample type and subject.

Note viral clades depicted using predicted microbial (largely bacterial) host to facilitate interpretability as most DNA viruses identified by metagenomics sequencing are bacteriophages. Prediction algorithms for phage viral hosts reliable only at the genus level, thus viral profiles depicted at this level. Bronchoalveolar lavage (BAL) from critically ill patients A Microbes (non-viral) and B Viruses. Nasal swab samples from healthy adults C Microbes (non-viral) and D Viruses. Spontaneously expectorated sputum from people living with cystic fibrosis E Microbes (non-viral) and F Viruses. Empty space indicates samples that failed sequencing (no microbial reads identified). Nasal swab samples were collected from 10 different subjects as it is not feasible to collect more than 4 nasal swabs per participant at any given time, thus the experimental design was modified to ensure an equal number of replicates for each host depletion group, resulting in a larger number of control samples for nasal swabs.

Fig. 3. Alpha and beta diversity stratified by sample type and treatment method.

Species richness in mean values ± SD for microbial non-viral (A) and viral (B) communities. Boxplot of potential bias measured by Morisita-Horn dissimilarity (1 – Morisita-Horn similarity index) between each host depletion method and corresponding untreated sample for non-viral microbial (C) and viral (D) communities. Note most BAL samples had no detected viral communities. Statistical significance was tested with linear mixed-effect model adjusting for repeated measures in a participant as a random effect variable. *p-value < 0.05, **p-value < 0.01 and ***p-value < 0.001.

Fig. 4. Volcano plot of differential abundance.

A Non-viral microbes and B viral host genus by sample type and host depletion treatment. Each dot represents association analyzed by differential abundance analysis. Microbial taxa that showed strong significant changes (q-val < 0.01, |effect size| > 2) and viral host genus with significant changes (q-val < 0.1, |effect size| > 0.3) were labeled with their names. The analysis was conducted with linear mixed-effect model (feature ~ sample type + lyPMA + Benzonase + HostZERO + MolYsis + QIAamp, random effect = subject id) after centered-log ratio normalization.

Fig. 5. Mean relative abundance of top 20 significant taxa identified by differential abundance analysis using linear mixed-effect model (feature ~ lyPMA + Benzonase + HostZero + MolYsis + QIAamp + (1|subject id)) after centered log-ratio transformation.

Analyses were stratified by sample type. A Non-viral microbial species and B viral host genus for bronchoalveolar lavage, C microbial species and D viral host genus for nasal swabs, and E microbial species and F viral host genus for sputum. Statistical significances threshold q-value < 0.1.

Fig. 6. Viability of pathogens isolated from sputum samples under different treatment conditions.

For each species and experimental group, viabilities of 7 strains of Staphylococcus aureus, 6 strains of Pseudomonas aeruginosa, and 5 strains of Achromobacter spp. obtained from sputum cultures assessed using colony-forming unit (CFU) tests. A pseudocount of 1 was added prior to log₁₀ transformation due to the presence of zero counts. MolYsis had a strong negative effect on viability for Staphylococcus aureus (−4.3 log₁₀ cells/mL, p-value < 0.001) thus was not further tested in gram-negative isolates. DNA/RNA shield, when added to unfrozen culture, universally rendered all isolates non-viable.