Targeted Metagenomics for Clinical Detection and Discovery of Bacterial Tick-Borne Pathogens

Sample overview.

(i) Clinical specimens. A convenience sample of residual clinical specimens originally submitted to Mayo Clinic Medical Laboratories from health care providers nationwide for PCR testing for tick-borne pathogens was retained following routine requested testing, frozen at −80°C, and included in this analysis. Submission of a clinical specimen for testing for a tick-borne agent was considered to be a proxy for clinical suspicion of a tick-borne disease. Residual specimen types included blood (K₂ EDTA), submitted for Lyme PCR (Borrelia burgdorferi and Borrelia mayonii) or tick-borne panel PCR (Babesia microti, Ehrlichia chaffeensis, Ehrlichia muris subsp. eauclairensis, Ehrlichia ewingii, and Anaplasma phagocytophilum), and synovial fluid, cerebrospinal fluid (CSF), and fresh tissue, submitted for Lyme PCR. Residual blood specimens submitted to the Vanderbilt University Medical Center for Ehrlichia PCR testing from health care providers in Tennessee were also included. The study was approved by the Institutional Review Boards at Mayo Clinic (protocol identification number 14-001148), Vanderbilt University (protocol identification number 140738), and the CDC (protocol identification numbers 6635 and 6870).

(ii) Controls.

To ascertain DNA amplification considered to be background, molecular-grade water and blood from healthy donors were obtained and screened via 16S V1-V2 metagenomics. Blood from healthy donors (K₂ EDTA) (n = 500) was obtained from Innovative Research (Novi, MI) (n = 100), Biological Specialty Corporation (Colmar, PA) (n = 100), BioIVT (Westbury, NY) (n = 120), ZenBio (Research Triangle Park, NC) (n = 60), BioChemed (Winchester, VA) (n = 60), and Discovery Life Sciences (Los Osos, CA) (n = 60). Healthy donor blood specimens originated from the Midwest (Innovative Research), Northeast (Biological Specialty Corporation), and Southeastern (BioIVT, ZenBio, BioChemed, and Discovery Life Sciences) United States. Molecular-grade water (three different lots) was obtained from Fisher (Pittsburgh, PA).

DNA extraction.

DNA was extracted using the MagNA Pure 96 instrument (Roche, Indianapolis, IN) and the DNA and viral NA small-volume kit (Roche, Indianapolis, IN) with the associated DNA blood SV 3.1 extraction protocol. One hundred microliters was used for the input, and purified DNA was eluted in 100 μl. Each 96-well DNA plate included a negative and a positive control. The negative control consisted of pooled blood from healthy donors. The positive control consisted of Escherichia coli strain ATCC 8739 DNA spiked into pooled blood from healthy donors at a final concentration of 127 fg/μl.

16S rRNA gene primer design and amplification.

Conserved regions flanking the V1-V2 region of the 16S rRNA gene were utilized for primer design based on a ClustalO DNA sequence alignment of tick-borne bacterial species, including Borrelia species, encompassing both the Lyme and RF groups; Anaplasma; Ehrlichia; Rickettsia; Francisella; and E. coli (see Fig. S2 in the supplemental material). Illumina Nextera XT index adaptor sequences (underlined) were included in the synthesis of forward primer 5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCTGCTGCCTCCCGTAGGAGT-3′ and reverse primer 5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGAGAGTTTGATCCTGGCTCAG-3′ (IDT, Coralville, IA).

For 16S V1-V2 PCR amplification, the DNA template concentration was optimized for sensitivity (without inhibition) using DNA extracted from blood samples positive for either B. burgdorferi or B. miyamotoi. Template DNA volumes of 1 to 5 μl were tested, with the resulting amplicon being quantified using TapeStation high-sensitivity screen tape (Agilent, Santa Clara, CA). The final optimized 50-μl PCR mixture consisted of 25 μl of premix ExTaq, DNA polymerase hot-start version (TaKaRa Bio, San Francisco, CA), 100 ng of each primer, and 4 μl of purified template DNA. Using the Veriti Dx 96-well thermal cycler, 0.2 ml (Thermo Fisher Scientific, Grand Island, NY), PCR cycling conditions were as follows: an initial denaturation step at 95°C for 4 min and 45 cycles of denaturation at 94°C for 30 s, annealing at 56°C for 30 s, and extension at 75°C for 30 s, followed by a final extension step at 72°C for 10 min. Each 96-well plate for PCR included the two DNA extraction controls described above, one negative PCR control of pooled healthy human donor blood DNA, and two PCR positive controls of E. coli DNA diluted in TE (Tris-EDTA) buffer (pH 8.0), at a final concentration of 127 fg/μl.

Library preparation and multiplexing.

Dual Nextera XT indices (XT index kit v2, sets A to D; Illumina, San Diego, CA) were added via PCR to the V1-V2 amplicons to allow multiplexed sequencing of 384 samples. Each 50-μl reaction mixture consisted of 25 μl of premix ExTaq DNA polymerase hot-start version, 10 μl of water (Fisher, Pittsburgh, PA), 5 μl each of forward and reverse indices, and 5 μl of the 16S V1-V2 amplicon. PCR conditions were 95°C for 3 min and 8 cycles at 95°C for 30 s, 55°C for 30 s, and 72°C for 30 s, followed by a final extension step at 72°C for 5 min. The resulting uniquely indexed libraries were purified using 1.8× AMPure XP (Beckman Coulter, Miami, FL) according to the manufacturer’s protocol and eluted in 50 μl of 10 mM Tris (pH 8.5) (Tris base; Sigma-Aldrich, St. Louis, MO).

Purified libraries for each sample were quantified using the FLx800T microplate fluorescence reader (BioTek, Winooski, VT) and the Quant-iT Qubit high-sensitivity double-stranded DNA (dsDNA) assay kit (Invitrogen, Carlsbad, CA). Each library was normalized to a final concentration of 4 nM by dilution in 10 mM Tris (pH 8.5). A B. burgdorferi positive clinical specimen with a threshold cycle (C_T) value of 34 by pan-Borrelia PCR (14) was used as an internal sequencing control. The positive control was independently indexed, bead cleaned, and normalized to 4 nM like all other samples. The same indexed control was used throughout 16S metagenomics sequencing of all samples. A pool for each of the four 96-well plates was prepared and then combined into a single final library pool consisting of 384 uniquely indexed libraries. To remove DNA fragments smaller than 300 bp, the final pooled library was subjected to a 0.8× bead cleanup by adding 40 μl AMPure XP beads to a 50-μl aliquot of the pooled library. The resulting final pooled library was quantified using the Qubit 3.0 fluorometer (Life Technologies, Carlsbad, CA) with the Quant-iT dsDNA high-sensitivity kit and diluted using 10 mM Tris buffer (pH 8.5) to obtain a final concentration of 4 nM.

16S metagenomic sequencing.

Paired-end sequencing (2 by 250 bp) of the final pooled library (360 patient samples and 24 controls) was performed using an Illumina MiSeq and 500 cycle V2 reagent kit (Illumina). The pooled library was denatured by combining 5 μl of the 4 nM library with 5 μl of 0.2 N NaOH (Sigma-Aldrich, St. Louis, MO), briefly vortexed, and centrifuged at 280 × g for 1 min, followed by a 5-min incubation at room temperature. The denatured library was then diluted with 990 μl chilled Illumina hybridization buffer (HT1) and put on ice, resulting in a 20 pM denatured library in 1 mM NaOH. The library was further diluted to an optimized 12.5 pM concentration by combining 375 μl of the 20 pM library with 225 μl chilled HT1, which was stored on ice until use. The 12.5 pM library was, unless otherwise indicated, combined with 12.5 pM PhiX (Illumina) at 60 μl PhiX (10%) and 540 μl of the denatured and diluted amplicon library. The combined library was heat denatured at 96°C for 2 min, followed by 5 min in an ice water bath immediately before loading 600 μl into the MiSeq reagent cartridge.

Bioinformatic analysis and taxonomic prediction.

Sequence reads were demultiplexed into 384 individual samples, followed by the removal of the adaptor and indices by internal MiSeq software prior to analysis using a custom bioinformatic workflow. Reads from each sample were subjected to adaptor and quality-based trimming (quality score Q30) using FaQCs 1.34 (15). Paired reads were merged using Flash 1.2.11 (16), with a mismatch density set to 0.25. The resulting quality-trimmed, merged reads were assigned taxonomic predictions with Kraken 0.10.5 (17) using the MiniKraken database (18 October 2017). A default kmer length of 31 bp was used. The final output for each sample was a taxon-based read abundance CSV file; all individual-sample CSV files were concatenated into a single file. Sequence read abundance and mean, median, minimum, and maximum read counts were determined using unmodified output files. For read abundance, for each sample with a tick-borne taxonomic prediction, the percentage of reads for the tick-borne agent relative to reads for all other bacteria taxa was calculated.

For analysis of taxonomic predictions in controls and clinical samples, only those with ≥50 sequence reads were included. This level of stringency was applied in order to avoid false positives in clinical samples due to error rates in Illumina sequencing and the high number of uniquely indexed libraries (384) included per sequencing run. For subtraction analysis, taxonomic predictions (≥50 sequence reads) were manually collapsed to order, the highest taxon level with specificity for the most common tick-borne agents (i.e., Rickettsiales and Spirochaetales). Background taxonomic predictions were established from 500 individual blood specimens from healthy donors, molecular-grade water from three lots tested 805 times, and pooled blood from healthy donors tested 335 times. A breakdown of the taxonomic predictions from individual blood specimens from the 5 different companies is available in Table S5. Taxa were included in the background data set if they were present in at least two control specimens; singleton taxonomic predictions were not included. Background taxonomic predictions were manually subtracted from those taxonomic predictions in clinical specimens in order to determine unique taxa in clinical samples. After subtraction, the number of taxonomic predictions for Rickettsiales (54%) and Spirochaetales (10%) relative to all other taxonomic predictions in clinical samples was manually determined. Taxonomic predictions for clinical specimens were also analyzed at the genus level for Anaplasma, Borrelia, Borreliella, Ehrlichia, Francisella, and Rickettsia. The nomenclature for B. burgdorferi sensu lato genospecies has been in flux over the last several years. Both Borrelia and, more recently, Borreliella have been utilized for this species, although it has not been uniformly applied. For the purposes of this article and for clarity, regardless of the nomenclature used in databases, all B. burgdorferi sensu lato genospecies in this article are classified as Borrelia (18).

Validation of taxonomic predictions.

All samples positive for taxonomic predictions of Anaplasma, Borrelia, Borreliella, Ehrlichia, Francisella, and Rickettsia were subjected to secondary in vitro confirmation. If taxonomic predictions corresponding to two different tick-borne bacteria were identified, confirmatory assays for both predicted taxa were performed. For Anaplasma and Ehrlichia, a real-time PCR assay that uses hybridization probes and targets the groEL gene, followed by melting temperature analysis of PCR products, was utilized (19). For Borrelia, one to eight housekeeping genes, uvrA, rplB, recG, pyrG, pepX, clpX, nifS, and clpA, were amplified, sequenced, and analyzed (14). For Francisella, a real-time TaqMan PCR assay was employed for species identification (20, 21). For Rickettsia, a pan-Rickettsia TaqMan PCR assay (12) targeting the ribosomal protein L16P gene was utilized. For species that could not be identified by PCR, sequencing of the V1-V4 region of the 16S rRNA gene (∼785 to 830 bp) was performed. Briefly, 16S amplicons were tagmented and indexed according to the Nextera XT manufacturer’s protocol and sequenced with the 300-cycle V2 reagent kit (Illumina). De novo consensus 16S sequences were generated using CLC Genomics Workbench (Qiagen), using one or more of the following parameters: word size of 20 to 30, default quality trimming of the paired reads, and 25 to 100% sampling of the paired reads. Consensus sequences were corroborated by mapping the paired reads to a reference sequence corresponding to the original taxonomic prediction (length and similarity fractions set to 0.9 and 0.95, respectively). Assemblies required >100× coverage and a Q score of >60 for each nucleotide site. If de novo and reference mapping assemblies yielded identical consensus sequences, primers were trimmed, and FASTA files were exported for further analysis. To maximize 16S sequence length for analyses, the V1-V4 sequence was stitched together with the V1-V2 consensus sequence derived from mapping and querying the NCBI nonredundant DNA database. Maximum likelihood trees were constructed using the general time-reversible model in MEGA (version 7.0) (22) with 1,000 bootstrap replicates. Pairwise genetic distances were calculated in MEGA (version 7.0) using the Kimura-2 model. Primer sequences and PCR and sequencing conditions are provided in Table S3. For specimens with taxonomic predictions that could not be confirmed by PCR or sequencing, DNA was reextracted from the original specimen and tested a second time by 16S metagenomics.

BLASTn analysis.

The quality-trimmed, merged reads from each sample with a MiniKraken taxonomic prediction of Anaplasma, Borrelia, Borreliella, Ehrlichia, Francisella, Rickettsia, or other significant identifications were independently mapped (CLC Genomics) to reference sequences corresponding to their original taxonomic predictions. Default parameters were used for mapping, with the exception of the length and similarity fractions, set to 0.8 and 0.9, respectively. Consensus sequences derived from each mapping were subjected to BLASTn analysis to query the NCBI nonredundant DNA database (November 2018).

Limit of detection of 16S metagenomics.

A limit of detection was determined by adding 10-fold dilutions of B. burgdorferi B31 DNA (diluted in pooled healthy donor blood DNA) to pooled healthy donor blood DNA to yield final concentrations of 6 × 10⁶ genomes/ml of blood to 60 genomes/ml of blood. To simulate coinfected samples, DNA extracted from a human blood specimen strongly positive for A. phagocytophilum (groEL real-time PCR C_T of 26; read count of 42,027) was added to the 10-fold dilutions of B. burgdorferi B31 DNA. The volume of extracted human DNA was held consistent across all samples. For the calculation of genomic equivalents, a conversion value of 1.63 fg/genome was utilized.

Data availability.

Raw sequence read data have been deposited for control specimens (molecular-grade water) in the Sequence Read Archive (SRA) under project accession number PRJNA637310. Source codes for bioinformatic pipelines used in this study are available upon request. All unique 16S sequences have been uploaded to the GenBank database. The 16S V1-V4 sequence for the Anaplasma species identified here was deposited in the NCBI database with accession number MG429812. The novel Rickettsia-like and N. risticii 16S sequences were deposited in the NCBI database with accession numbers MK580529 and MK580530, respectively.

Sample overview.

A total of 13,038 residual clinical specimens (blood, cerebrospinal fluid [CSF], synovial fluid, and tissue) submitted by a health care provider for PCR testing for Anaplasma phagocytophilum, Borrelia burgdorferi, Borrelia mayonii, Ehrlichia chaffeensis, Ehrlichia muris subsp. eauclairensis, Ehrlichia ewingii, or Babesia microti were available for 16S metagenomics testing. Specimens were originally submitted to either the Mayo Clinic (n = 12,494) by providers throughout the United States or the Vanderbilt University Medical Center (n = 544) by providers in Tennessee (see Fig. S1 in the supplemental material). The most common specimen type was blood (87.4%), followed by CSF (8.9%), synovial fluid (3.7%), and tissue (<0.1%).

16S metagenomics.

The V1-V2 region of the 16S rRNA gene was chosen for the detection of tick-borne bacteria based on BLASTn analysis and multisequence alignments, which verified that nucleotide differences among 28 tick-borne bacterial species (encompassing known pathogens as well as tick-borne species not associated with human illness) within the genera Borrelia, Anaplasma, Ehrlichia, and Francisella were sufficient for correct identification (Fig. S2). Within the Rickettsia genus, interspecies sequence variation in this region is limited.

16S V1-V2 metagenomics yielded reproducible MiniKraken taxonomic predictions of B. burgdorferi down to 6 × 10³ genomes/ml of blood (10/10 detected) in spiked blood samples (Table 1). This limit of detection was equivalent to that measured for pan-Borrelia real-time PCR (Table 1). When spiked into an A. phagocytophilum-positive blood sample to simulate coinfection, B. burgdorferi DNA remained consistently detectable by 16S V1-V2 rRNA metagenomics to 6 × 10⁴ genomes/ml of blood (10/10), with intermittent detection at 6 × 10³ genomes/ml of blood (7/10).

Sequencing statistics for runs encompassing all 13,038 clinical specimens, blood from healthy donors, molecular-grade water, and controls (reads >Q30, clusters passing filter, cluster density, and total read count) are provided in Table S1.

MiniKraken taxonomic predictions.

A total of 92.3% (12,033/13,038) of clinical specimens, 63.2% (509/805) of molecular-grade water samples, and 65.8% (329/500) of blood samples from healthy donors yielded at least one 16S V1-V2 taxonomic prediction (with ≥50 sequence reads) for any bacterial taxa. Taxonomic predictions within the tick-borne genera Anaplasma, Borrelia, Ehrlichia, Francisella, and Rickettsia were specific to clinical specimens. A total of 878 clinical specimens yielded a single taxonomic prediction within one of the tick-borne genera Anaplasma, Borrelia, Ehrlichia, Francisella, and Rickettsia. Three specimens yielded simultaneous taxonomic predictions for two different tick-borne genera, Anaplasma and Borrelia, for a total of 881 specimens identified as being positive for tick-borne bacteria. Taxonomic predictions observed for blood from healthy donors (n = 500) and molecular-grade water samples (n = 805) demonstrated considerable overlap (35/41 orders; 85.4%) (Fig. 1a and Fig. S3). One exception was a taxonomic prediction of Enterobacterales, which was common in blood from healthy donors (296/500; 59%) and rare in molecular-grade water (3/805; 0.4%). The removal of taxonomic predictions identified in individual healthy blood donors, molecular-grade water samples, and pooled healthy donor blood demonstrated that Rickettsiales and Spirochaetales were the two most prevalent bacterial taxa identified in the 13,038 clinical samples from patients with suspected tick-borne illness (Fig. 1b and Table S2).

Increase in the number of detected tick-borne bacteria.

Specific 16S V1-V2 taxonomic predictions for 10 different tick-borne bacteria known to cause human illness included A. phagocytophilum, B. burgdorferi, B. mayonii, B. miyamotoi, Borrelia hermsii, E. chaffeensis, E. muris, E. ewingii, Francisella tularensis, and Rickettsia (Table 2). Additionally, taxonomic predictions corresponding to two species (Anaplasma sp. or Borrelia sp.) previously detected only in ticks or recently associated with human illness were discovered (14, 23, 24). Overall, these identifications doubled the number of detected tick-borne bacteria to 12 species compared to the number of bacterial species originally tested for by PCR (n = 6) (Fig. 1c). All clinical specimens positive for 1 of these 12 bacterial species were blood, except for B. burgdorferi-positive specimens, which included blood (n = 64), synovial fluid (n = 22), and CSF (n = 1). A single blood-contaminated synovial fluid specimen was positive for A. phagocytophilum.

The abundance (percentage) of 16S V1-V2 tick-borne bacterial sequence reads relative to all other bacterial taxa detected in each clinical specimen is shown in Fig. 2a; the corresponding read counts are shown in Table 2. The single sample positive for F. tularensis yielded a relative read abundance of 89.6% and a read count of 12,295. As expected, the average 16S read abundance and mean read count were highest for those bacterial species (A. phagocytophilum, E. chaffeensis, and B. mayonii) associated with higher levels of bacteremia (10⁵ to 10⁶ bacteria/ml) (6, 25). Blood specimens positive for B. burgdorferi exhibited the lowest 16S read abundance, consistent with the low spirochetemia (10² to 10³ genome equivalents/ml) documented for B. burgdorferi-infected patients (11, 26).

Three blood specimens from patients suspected of having tick-borne illness contained simultaneous taxonomic predictions of A. phagocytophilum as well as a taxonomic prediction for B. burgdorferi, B. mayonii, or B. miyamotoi (Fig. 2c). The 16S V1-V2 relative read abundances were higher for B. mayonii and B. miyamotoi (67.9% and 74.0%, respectively) than for A. phagocytophilum (14.8% and 16.4%). For the sample with taxonomic predictions of A. phagocytophilum-B. burgdorferi, the relative read abundances were 86.2% for A. phagocytophilum and 1.7% for B. burgdorferi.

Accuracy of taxonomic predictions for tick-borne bacterial species.

Of the 881 clinical specimens yielding a 16S V1-V2 MiniKraken taxonomic prediction of Anaplasma, Borrelia, Ehrlichia, Francisella, or Rickettsia, 877 (99.5%) were independently verified to be positive by secondary PCR and sequencing (Table 2 and Table S3). The four blood specimens (0.5%) that could not be confirmed yielded taxonomic predictions for A. phagocytophilum (n = 2) or E. chaffeensis (n = 2). DNA reextraction and testing by 16S V1-V2 metagenomics produced the same taxonomic predictions.

Comparison of 16S V1-V2 MiniKraken taxonomic predictions with identifications from independent PCR and sequencing methods demonstrated very high accuracies of taxonomic predictions for the 12 identified tick-borne bacterial species, with 100% agreement observed at the genus level (Table 2). For 9 known tick-borne bacteria with a complete genome available at the time when the MiniKraken database was constructed, 88.9% were correctly identified to the species level (Table 2). When consensus sequences from all positive specimens were queried by BLASTn against the NCBI nonredundant DNA database, species-level taxonomic identifications were achieved for 9/10 (90%) known tick-borne pathogens (Table 2). The Anaplasma species identified in two blood specimens demonstrated only 98.2% sequence identity to all Anaplasma V1-V2 16S sequences in the NCBI database, providing evidence that it may be a novel pathogen. Sequencing and analysis of a larger region of the 16S rRNA gene encompassing the V1-V4 region (837 nucleotides) confirmed that the Anaplasma species in the two blood specimens shared 100% identity to each other and only 98.7% identity to an uncultured Anaplasma sp. (GenBank accession number JN862824.1), which was the highest identity to any sequence in the NCBI nonredundant database (Table S4). Notably, 100% nucleotide identity was shared across a smaller fragment (357 bp) of the 16S rRNA gene with two Anaplasma sequences identified in human-biting ticks: Dermacentor andersoni collected in Alberta and Saskatchewan, Canada, and Dermacentor occidentalis collected in northern California (23, 24). A phylogenetic comparison of the Anaplasma species identified in the two patient blood specimens and Dermacentor ticks to other Anaplasma species is shown in Fig. 3a. The 16S V1-V4 sequence for the Anaplasma species identified here was deposited in the NCBI database with accession number MG429812. The blood specimen positive for “Candidatus Borrelia johnsonii” was previously reported and confirmed by sequencing and phylogenetic analysis of the 16S rRNA, flaB, and glpQ genes (14).

Other taxonomic identifications unique to clinical samples.

Taxonomic predictions for other bacteria in the Rickettsia genus unique to samples from patients suspected of having tick-borne illness were also validated by secondary methods (Table 2 and Fig. 1c). Five blood specimens yielded taxonomic predictions within the Rickettsiales that were not known tick-borne agents. These included one blood specimen with a MiniKraken and BLASTn taxonomic prediction of Neorickettsia risticii (99.7% identity), one blood specimen with a MiniKraken and BLASTn taxonomic prediction of Rickettsia typhi (100% identity), and three blood specimens with MiniKraken taxonomic predictions of Rickettsia and only 97.9% identity to all other Rickettsia species in the NCBI database. The 16S V1-V2 sequence amplified from these three blood specimens displayed 100% nucleotide identity to each other. Sequencing of the 16S V1-V4 region confirmed the accuracy of the MiniKraken and BLASTn predictions at the genus level for all five specimens and at the species level for the N. risticii- and R. typhi-positive specimens. The V1-V4 16S sequence for the N. risticii-positive specimen showed 100% identity (797 bp) to N. risticii 812 (GenBank accession number KX001784.1) and grouped most closely with N. risticii in a phylogenetic analysis of Neorickettsia, Orientia, and Rickettsia species (Fig. 3b). The 16S V1-V4 sequence amplified from one of the three blood specimens with taxonomic prediction of Rickettsia indicated only 98.6% identity to any other Rickettsia species in the NCBI database; phylogenetic analysis revealed that the identified agent falls outside the genus Rickettsia and is therefore denoted a Rickettsia-like species here (Fig. 3b). The novel Rickettsia-like and N. risticii 16S sequences were deposited in the NCBI database with accession numbers MK580529 and MK580530, respectively.

Taxonomic predictions for the causative agents of two other zoonotic diseases, Q fever and leptospirosis, were also confirmed by secondary testing (Table 2). The 16S V1-V2 read abundances for these samples are shown in Fig. 2c. Two blood specimens yielded MiniKraken and BLASTn taxonomic predictions of Coxiella burnetii (100% identity to each other) and 100% identity to the C. burnetii genome reported under GenBank accession number CP001020.1 across the 16S V1-V4 region. Notably, a taxonomic prediction of Leptospirales was identified in 15 blood specimens (Table 2). Primary MiniKraken taxonomic predictions of Leptospira interrogans (the only Leptospira species present in the database) or Leptospira were returned for 14 and 1 specimen, respectively. NCBI taxonomic predictions for these specimens included 12 L. kirschneri, 2 L. interrogans, and 1 L. noguchii specimen. Sequencing of the V1-V4 region of 16S confirmed the BLASTn taxonomic predictions for 14 specimens, with 16S sequences displaying 100% identity to L. kirschneri (NCBI accession number NR_043051.1) (n = 12), 100% identity to L. interrogans (NCBI accession number AY996800) (n = 1), and 99% identity to L. noguchii (NCBI accession number NR_115926.1) (n = 1). One specimen with both MiniKraken and BLASTn taxonomic predictions of L. interrogans could not be confirmed by secondary methods.