Comparative Genomic and Transcriptomic Analysis of Naegleria fowleri Clinical and Environmental Isolates

ABSTRACT

Out of over 40 species of Naegleria, which are free-living thermophilic amebae found in freshwater and soil worldwide, only Naegleria fowleri infects humans, causing primary amebic meningoencephalitis (PAM), a typically fatal brain disease. To understand the population structure of Naegleria species and the genetic relationships between N. fowleri isolates and to detect pathogenic factors, we characterized 52 novel clinical and environmental N. fowleri genomes and a single Naegleria lovaniensis strain, along with transcriptomic data for a subset of 37 N. fowleri isolates. Whole-genome analysis of 56 isolates from three Naegleria species (N. fowleri, N. lovaniensis, and Naegleria gruberi) identified several genes unique to N. fowleri that have previously been linked to the pathogenicity of N. fowleri, while other unique genes could be associated with novel pathogenicity factors in this highly fatal pathogen. Population structure analysis estimated the presence of 10 populations within the three Naegleria species, of which 7 populations were within N. fowleri. The whole-nuclear-genome (WNG) phylogenetic analysis showed an overall geographical clustering of N. fowleri isolates, with few exceptions, and provided higher resolution in identifying potential clusters of isolates beyond that of the traditional locus typing. There were only 34 genes that showed significant differences in gene expression between the clinical and environmental isolates. Genomic data generated in this study can be used for developing rapid molecular assays and to conduct future population-based global genomic analysis and will also be a valuable addition to genomic reference databases, where shotgun metagenomics data from routine water samples could be searched for the presence of N. fowleri strains.

IMPORTANCEN. fowleri, the only known Naegleria species to infect humans, causes fatal brain disease. PAM cases from 1965 to 2016 showed <20 cases per year globally. Out of approximately 150 cases in North America since 1962, only four PAM survivors are known, yielding a >97% case fatality rate, which is critically high. Although the pathogenesis of N. fowleri has been studied for the last 50 years, pathogenetic factors that lead to human infection and breaching the blood-brain barrier remain unknown. In addition, little is known regarding the genomic diversity both within N. fowleri isolates and among Naegleria species. In this study, we generated novel genome sequences and performed comparative genomic and transcriptomic analysis of a set of 52 N. fowleri draft genome sequences from clinical and environmental isolates derived from all over the world in the last 53 years, which will help shape future genome-wide studies and develop sensitive assays for routine surveillance.

INTRODUCTION

Naegleria species are free-living thermophilic amebae found mainly in freshwater and soil worldwide (1, 2). Over 40 Naegleria species have been characterized based on genetic variations in the internal transcribed spacer (ITS) sequences on the ribosomal DNA and the mitochondrial small subunit (mtSSU) rRNA gene (3). Only one species, Naegleria fowleri, infects humans and causes the rare disease called primary amebic meningoencephalitis (PAM) (4, 5), a fast-progressing and typically fatal brain disease. N. fowleri has been isolated from rivers, lakes, hot springs, swimming pools, sewage, tap waters, soil, and dust in the air (6–11). Human infection occurs when water containing the ameba enters the nose and finds its way through the nasal mucosa and olfactory nerve, entering the brain (12, 13). The progress of the disease is rapid, with a median of 5 days from onset of symptoms to death (14). PAM patients suffer from severe inflammation of the central nervous system that leads to headache, fever, vomiting, seizures, and altered mental status (15). Mortality is very high, mainly due to delayed diagnosis of the causative organism, overwhelming inflammation of the central nervous system, and lack of effective treatment (10). Although the worldwide incidence of PAM is low, the presence of N. fowleri in human-associated environments is an important public health issue because of the rapid onset and high mortality of PAM. Recent trends suggest a spread of N. fowleri infections from traditionally warmer southern-tier states in the United States to colder northern-tier states such as Minnesota. More alarmingly, N. fowleri colonization of two public drinking water systems in Louisiana was documented for the first time in 2013. The contamination was linked to the death of a 4-year-old whose only known exposure was playing on a backyard water slide (9, 16).

In recent years, with very few published draft genomes of the three important Naegleria species, N. fowleri (17, 18), Naegleria lovaniensis (19), and Naegleria. gruberi (20), we sought to understand the genetic diversity among these three Naegleria species as well as to obtain insights on N. fowleri-specific protein clusters that might be responsible for the pathogenicity of the species. Although there are enormous genetic variations among Naegleria species, little is known about intraspecies genetic diversity, especially within the pathogenic N. fowleri species. To gain a better understanding of the population structure for Naegleria species, the genetic relationships between N. fowleri strains and with other Naegleria species, and to detect possible pathogenetic factors, we genome sequenced and characterized 52 clinical and environmental N. fowleri isolates (representing 49 unique N. fowleri isolates) and a single N. lovaniensis strain, isolated from all over the world, along with transcriptomic data for a subset of 37 N. fowleri strains.

RESULTS

Genome assembly, structure, and annotation of N. fowleri and N. lovaniensis genomes.

As previously described (21), we made an attempt to generate a “close-to-complete” genome assembly from a 1969 N. fowleri TY isolate that caused PAM in a patient from Virginia using HiSeq Illumina and PacBio data. The genome assembly was verified using optical mapping data. This led to the final haploid assembly, which consisted of 37 chromosomes and had a total size of 27.9 Mb (27,994,426 bp) with chromosome size ranging from 1,206,962 bp to 537,351 bp. Similarly, a single isolate of N. lovaniensis (76-15-250) was also sequenced using the PacBio RS II sequencing platform using 4 single-molecule real-time (SMRT) cells, which resulted in 401,530 reads with an average read length of 6,065 bp. FALCON long read assembler reconstructed the best assembly, consisting of 199 contigs with an N₅₀ of 455,122 bp and a total size of 30.8 Mb (30,830,598 bp). Benchmarking Universal Single-Copy Orthologs (BUSCO) v4.0.6 evaluation of gene completeness performed by searching 255 eukaryotic benchmarking universal single-copy orthologs showed that for N. fowleri TY and N. lovaniensis 76-15-250 draft genomes, 222/255 (87%) and 214/255 (84%) genes, respectively, were identified, either completely or in fragments (Table 1). Smaller numbers of complete BUSCOs were found for the previously published N. fowleri (ATCC 30894; 208/255 genes) and N. fowleri (ATCC 30863; 211/255 genes) genomes than for N. fowleri TY, while the number of complete BUSCOs identified in N. lovaniensis (76-15-250; 201/255 genes) was slightly smaller than that for the published N. lovaniensis (ATCC 30569; 205/255 genes) draft genome.

TABLE 1.

BUSCO analysis of Naegleria species genomes^a

BUSCO type	No. of BUSCOs in genomes of:
	N. fowleri (TY)b	N. fowleri (ATCC 30894)c	N. fowleri (ATCC 30863)c	N. lovaniensis (ATCC 30569)c	N. lovaniensis (76-15-250)	N. gruberi (ATCC 30224)c
Complete	215	208	211	205	201	203
Duplicated	2	2	1	10	2	1
Fragmented	7	11	11	13	13	14
Missing	33	36	33	37	41	38

^aGenome completeness was evaluated by analyzing 255 conserved BUSCOs (v4.0.6) of the Eukaryota odb10 data set.

^bOut of 52 N. fowleri genomes sequenced, BUSCO analysis results are shown only for the “close-to-complete” genome of the N. fowleri TY isolate.

^cPublished Naegleria genomes.

The N. fowleri TY and N. lovaniensis 76-15-250 genomes were gene dense, with 71% and 75% of the genomes, respectively, being defined as coding sequences. Besides the nuclear genome, Naegleria spp. include a circular mitochondrial genome and an extrachromosomal plasmid encoding ribosomal RNAs. The mitochondrial genome of the N. fowleri TY isolate was 49,486 bp, while the size of the mitochondrial genome of N. lovaniensis 76-15-250 was 48,529 bp. Furthermore, the ribosomal DNA (rDNA) plasmids of N. fowleri TY and N. lovaniensis 76-15-250 were 15,976 bp and 13,153 bp, respectively.

De novo repeat prediction analysis using RepeatMasker v4.0.8 and RepeatModeler on N. fowleri TY genomes identified approximately 5.28% of the total genome was repetitive sequences (Table 2). Simple repeats represent 1.64% of the genome sequences, while 1.56% are Long interspersed nuclear elements (LINEs) and 1.65% are unclassified repeats. Approximately 10.78% of the total genome of N. lovaniensis 76-15-250 was identified as repetitive regions (Table 2). Repetitive sequences are thought to be important for the appropriate folding of the genome, and they confer unique identity on an organism by introducing genetic variation within a species (22).

TABLE 2.

Summary of repetitive sequences identified in N. fowleri TY and N. lovaniensis (76-15-250)

Isolate or type of repeat element	No. of elements	Length occupied (bp)	% of the genome
N. fowleri TY
Long interspersed nuclear elements (LINEs)	851	435,553	1.56
LTR elements	27	5,803	0.02
DNA elements	54	58,557	0.21
Unclassified	1,683	460,648	1.65
Small RNA	165	17,776	0.06
Simple repeats	10,470	457,811	1.64
Low complexity	827	39,272	0.14
N. lovaniensis 76-15-250
Short interspersed nuclear elements (SINEs)	14	27,504	0.09
Long interspersed nuclear elements (LINEs)	71	105,310	0.34
LTR elements	81	70,415	0.23
DNA elements	157	317,286	1.03
Unclassified	2,501	1,550,165	5.03
Small RNA	226	921,552	2.99
Simple repeats	6,930	295,228	0.96
Low complexity	683	33,426	0.11

Ab initio gene prediction, incorporating transcriptome sequencing (RNAseq) data, of the N. fowleri TY nuclear genome using BRAKER2 identified 9,405 protein coding genes. Out of 9,405 genes predicted in the TY genome, 6,368 genes (68%) were functionally annotated using eggNOG-mapper, where ortholog assignments were made to the precomputed clusters and phylogenies present in the eggNOG 5 database, which also includes gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway information of each ortholog group. The number of ab initio protein coding gene predictions for the remaining N. fowleri draft genomes sequenced in this study, either incorporating RNAseq data or not, ranged from 9,363 to 9,635 genes (see Table S1 in the supplemental material). Ab initio gene prediction of the N. lovaniensis 76-15-250 nuclear genome using Augustus identified 11,305 genes. eggNOG-mapper functionally annotated 7,323 genes (65%) in the N. lovaniensis 76-15-250 genome. The set of predicted proteins identified to be complete BUSCOs both in N. fowleri TY and N. lovaniensis 76-15-250 genomes were highly similar to their respective previously identified Naegleria species draft genome assemblies (Table 3). The number of genes assigned to the various clusters of orthologous groups (COGs) functions for both species are summarized in Fig. 1.

TABLE 3.

BUSCO analysis of Naegleria species annotated protein sequences^a

BUSCO type	No. of BUSCOs in:
	N. fowleri (TY)b	N. fowleri (ATCC 30894)c	N. fowleri (ATCC 30863)c	N. lovaniensis (ATCC 30569)c	N. lovaniensis (76-15-250)	N. gruberi (ATCC 30224)c
Complete	220	219	210	220	220	203
Duplicated	3	2	7	16	4	1
Fragmented	7	7	8	10	9	14
Missing	28	29	37	25	26	38

^aGenome completeness was evaluated by analyzing 255 conserved BUSCOs (v4.0.6) of the Eukaryota odb10 data set. Publicly available protein coding sequences were downloaded from figshare (https://doi.org/10.6084/m9.figshare.8313656) for N. fowleri (ATCC 30894), while for the rest of the published genomes, the reannotated protein sequences using Braker2 were used for the BUSCO analysis.

^bOut of 52 N. fowleri genomes sequenced, BUSCO analysis is shown only for the “close-to-complete” genome of the N. fowleri TY isolate.

^cPublished Naegleria genomes.

FIG 1.

Summary of eggNOG-mapper results on the functional annotation of N. fowleri TY and N. lovaniensis 76-15-250 genomes. The number of genes assigned to the various clusters of orthologous groups (COGs) functions based on eggNOG-mapper for the N. fowleri TY and N. lovaniensis 76-15-250 genomes.

TABLE S1

Isolate information and sequencing statistics. Download Table S1, XLSX file, 0.02 MB ^{(20.4KB, xlsx)} .

This is a work of the U.S. Government and is not subject to copyright protection in the United States. Foreign copyrights may apply.

Identification of orthologous gene clusters among Naegleria species.

To identify N. fowleri genes that are unique compared to those in N. gruberi and N. lovaniensis, proteins from each of the species (N. fowleri TY, N. lovaniensis 76-15-250, and N. gruberi) were initially clustered using Neptune, CD-HIT, and OrthoMCL, and the unique genus-specific genes and clusters were parsed out from each of the three tools. The genus formed 11,530 protein clusters (with at least 2 or more proteins present) and 7,511 orthologous clusters (with at least two species present). There were 5,749 protein clusters shared by all Naegleria species, out of which 4,019 clusters had exactly one protein from each of the three species. In total, 1,246 clusters are shared between N. fowleri and N. lovaniensis, while N. fowleri shares only 255 protein clusters with N. gruberi (Fig. 2). There were 638 and 3,018 proteins that did not cluster with any species (singletons) for N. lovaniensis and N. gruberi, respectively (see Table S2 in the supplemental material). A total of 404 N. fowleri genes were identified that were unique compared to N. gruberi and N. lovaniensis, of which 80 genes have an annotation with known function and GO term assigned. GO term enrichment analysis on the unique N. fowleri genes showed that GO terms in each of the three categories, namely biological process (BP), molecular function (MF), and cellular component (CC), were significantly enriched after accounting for multiple testing. For the biological process category, GO terms describing the cytoskeleton, morphogenesis, and movements were enriched among N. fowleri-specific gene clusters, with P values of <0.05 (see Fig. S1a and Table S3 in the supplemental material). For the cellular component category, phagocytic cup, lysosome activity, and actin-related components were detected (Fig. S1b and Table S3). For the molecular function category, GO terms describing phosphatase and hydrolase activity, along with actin related binding and motor activity, were enriched among N. fowleri-specific gene clusters (Fig. S1c and Table S3).

FIG 2.

Results of cluster analysis showing the number of orthologous clusters shared between the three Naegleria species.

FIG S1

Bar graph showing the results of the gene ontology (GO) enrichment analysis. GO terms associated with the N. fowleri-specific genes at the genus level for the (a) biological process, (b) molecular function, and (c) cellular component categories are shown. Download FIG S1, PDF file, 1.0 MB ^{(1MB, pdf)} .

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TABLE S2

(a) Naegleria fowleri TY-specific proteins (singleton clusters/proteins) that did not cluster with any of the other two Naegleria species. (b) Naegleria lovaniensis (76-15-20) singleton clusters/proteins that did not cluster with any of the other two Naegleria species. (c) Naegleria gruberi (ATCC 30224) singleton clusters/proteins that did not cluster with any of the other two Naegleria species. Download Table S2, XLSX file, 0.1 MB ^{(131.2KB, xlsx)} .

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TABLE S3

Gene ontology (GO) enrichment analysis of the GO terms associated with the Naegleria species-specific genes. Download Table S3, XLSX file, 0.9 MB ^{(962.4KB, xlsx)} .

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To understand the protein diversity at the population level within the genus Naegleria, predicted proteins of all sequenced isolates (i.e., 56 Naegleria isolates representing 3 species) were also clustered into gene clusters/families using CD-HIT and Neptune. A total of 16,380 protein clusters were identified in Naegleria species. There was a total of 3,583 protein clusters shared among all 3 Naegleria species, where each cluster contained at least one protein sequence from the 53 N. fowleri, the two N. lovaniensis, and the single N. gruberi genomes. At the population level, 1,468 protein clusters were shared between N. fowleri and N. lovaniensis, while N. fowleri only shared 77 protein clusters with N. gruberi, and N. lovaniensis shared 283 protein clusters with N. gruberi. Also, there were 274 (containing 301 N. fowleri proteins), 3,619, and 7,648 protein clusters for N. fowleri, N. lovaniensis, and N. gruberi, respectively, that contained only single-species proteins (see Fig. S2 in the supplemental material). Out of 301 N. fowleri-specific proteins obtained from the population level analysis, only 51 genes were identified to be functionally annotated or contained a characterized domain. GO terms associated with cytoskeleton, lytic vesicle, actin-related components, transmembrane binding, and protease-related functions were mostly enriched among the N. fowleri-specific proteins obtained from the population-level comparison (uncorrected P < 0.05); however, after multiple correction only the GO terms associated with cellular response to toxic substances in biological processes was statistically significant (Bonferroni P = 0.03956) (see Fig. S3 and Table S3 in the supplemental material). There were 118 N. fowleri-specific proteins that were common within the three Naegleria species-level genome comparison and the population-level comparison with 56 Naegleria genomes from 3 species, indicating that there is variability in the protein coding genes within N. fowleri isolates.

FIG S2

Results of cluster analysis showing the number of orthologous clusters shared between the three Naegleria species at the population level, including all 53 N. fowleri isolates. Download FIG S2, EPS file, 0.4 MB ^{(455KB, eps)} .

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FIG S3

Bar graph showing results of GO enrichment analysis. GO terms associated with the N. fowleri-specific genes at the population level (including all 53 N. fowleri isolates) for the biological process, molecular function, and cellular component categories are shown. Download FIG S3, PDF file, 2.7 MB ^{(2.7MB, pdf)} .

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To investigate patterns of shared gene content, we ran a principal-component analysis (PCA) on the gene family distribution matrix of Naegleria species using the “panpca” function (micropan R package). Around 52% of the total variation among the Naegleria species genomes were seen along the two principal components (Fig. 3). Isolates from the same species formed nonoverlapping groups even after including all of the observed gene families in Naegleria species.

FIG 3.

Principal-component analysis (PCA) for the three Naegleria species gene cluster/family distribution matrix. Each data point represents a Naegleria species genome in the two first principal components of the gene cluster distribution matrix. Percentages on the axis show how much of the total Naegleria species gene family matrix variation is seen along each principal component.

Population structure of Naegleria species.

The clustered coancestry heatmap (Fig. 4), generated using ChromoPainter and fineSTRUCTURE analysis using genome-wide haplotype data from 56 Naegleria isolates, supported the existence of 3 species. This analysis estimated the presence of 10 populations within Naegleria species, of which 7 populations were within N. fowleri. Similarly to the phylogenetic analysis of N. fowleri isolates (described below), the population structure analysis also identified 4 major populations within N. fowleri, which correlated with the 4 genotypic phylogenetic clades. All N. fowleri isolates showed high shared coancestry with N. gruberi, while the two N. lovaniensis isolates showed the highest shared coancestry with N. gruberi and very limited shared coancestry with N. fowleri. Only one N. fowleri isolate, NF30863, showed some evidence of shared coancestry with N. lovaniensis. This analysis suggested that N. gruberi could be an ancestral species to both N. lovaniensis and N. fowleri, with more shared ancestry with N. lovaniensis than N. fowleri (Fig. 4).

FIG 4.

ChromoPainter coancestry matrix for Naegleria species with population structure assigned based on fineSTRUCTURE analysis. The heatmap shows the number of shared DNA chunks (coancestry) copied from a donor genome (x axis) to a recipient genome (y axis). This analysis estimated the presence of 10 populations within Naegleria species, of which 7 populations were within N. fowleri.

Phylogenetic relationship among N. fowleri strains based on nuclear and mitochondrial genome data.

Maximum-likelihood phylogenetic analysis of the whole nuclear genome (WNG) (Fig. 5) and mitochondrial genome of N. fowleri isolates (see Fig. S4 in the supplemental material) revealed that all isolates clustered primarily into four and three phylogenetic clades, respectively. In fact, the WNG phylogenetic topological relationships among isolates were similar to the phylogenetic relationships previously inferred from both traditional mitochondrial small subunit (mtSSU) rRNA and ITS genotyping loci, where isolates belonging to a particular genotype formed a distinct clade. Essentially, the four main clades inferred in the WNG phylogeny consisted of isolates that corresponded to the four genotypes; clade 1 included 28 isolates with genotype I loci (shown in red), clade 2 consisted of 17 isolates with genotype III loci (shown in green), clade 3 included 2 isolates with genotype II loci (shown in purple), and clade 4 consisted of 2 isolates with genotype IV, based on the ITS locus only (shown in blue) (Fig. 5). The population structure analysis using ChromoPainter and fineSTRUCTURE also identified N. fowleri populations that correlated with the phylogenetic clades. Based on population structure analysis, clade 1 (genotype 1) isolates formed 2 populations. Similarly, clade 2 (genotype III) isolates formed three populations, with the V516 isolate forming a single population, which was also observed in the WNG phylogeny, where the V516 isolate was clustered as an outgroup for all clade 2 isolates. All of the clade 3 (genotype II) and clade 4 (genotype IV) isolates formed their own separate clades and populations in both the WNG phylogeny and population structure analysis and showed high levels of intrapopulation coancestry within their respective populations. The phylogenetic clades reconstructed using WNG partially agreed with previous reporting by Pelandakis et al. (23) that N. fowleri isolates tended to form geographical clusters, in which clade 2 isolates belonged to the American variant group and clade 4 included isolates from the South Pacific Chooz (SPC) variant (V1005 is isolated from Australia), while the rest of the clades consisted of isolates from the widespread Euro-American (WEA) variant. Clade 4 (genotype IV) not only included a South Pacific strain (V1005) from Australia but also an isolate (V604) from Arkansas, United States, an exception to the geographical specificity of identifying genotype IV isolates (Fig. 5). Similarly, the mitochondrial phylogeny formed three clades that correspond to their traditional genotyping loci (Fig. S4). Although clustered together with the WNG sequences, the Australian isolate V1005 and the Arkansas isolate V604 showed an identical ITS genotype (IV) but differed in the mtSSU genotypes (I and III, respectively). To our knowledge, these are rare instances, where ITS and mtSSU genotypes are showing disagreement with each other (24). This may suggest a possible horizontal gene transfer in the mitochondrial genome leading to these discrepancies. Similarly, the clade 2 isolates that clustered with other genotype III isolates in the WNG phylogenetic tree, V516 and V518, clustered with the clade 1 (genotype 1) isolates in the mitochondrial phylogeny, again suggesting possible horizontal gene transfer of the entire mitochondrial genome (Fig. S4).

FIG 5.

Whole-genome phylogeny of all the N. fowleri isolates. Isolate label contains isolate identifier (ID), clinical (C) or environmental (E) isolate, the U.S. state or country of origin, mitochondrial small subunit (mtSSU) rRNA gene, and internal transcribed space (ITS) genotype. “NA” represents missing data and, for genotyping data, cases in which the genotyping loci was not confidently identified from the draft genomes of those isolates. Only one isolate from each of the duplicated N. fowleri isolates was included in the phylogenetic analysis. A recently published N. fowleri isolate (ATCC 30894) by Liechti et al. (18) was included in this phylogenetic analysis. Bootstrap support estimates of major ancestral nodes are also shown.

FIG S4

Whole-genome phylogeny of all the N. fowleri mitochondrial genomes. Download FIG S4, PDF file, 0.02 MB ^{(24KB, pdf)} .

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Even though the topology of the WNG phylogenetic tree among the isolates was similar to previously inferred phylogenetic trees using traditional mtSSU rRNA and ITS typing loci, where isolates belonged to a particular genotype formed a distinct clade, the WNG phylogenetic tree provided sufficient resolution to distinguish strains even within a genotype. For example, within clade 2 isolates (genotype III), there is a subclade in which 6 clinical and environmental (V069, FWHS, V523, V070, SFHS-3, and V068), all from Arizona and isolated in 1987, clustered together, and the average core single-nucleotide polymorphism (SNP) difference within this subclade was 14 SNPs (4 to 29 SNPs), indicating all these 6 isolates might have originated from a common ancestor and suggesting that they could possibly represent a single N. fowleri isolate (Table S4). V523 being the only clinical isolate in this clade suggests that this clinical case could have been the result of acquiring any of the other three environmental isolates, but which isolate/strain was acquired by the infected individual could not be inferred from the genomic data alone without strong epidemiological data to support any possible exposure event. Also, two isolates from Oklahoma (both isolated in 2005) formed a two-isolate subclade within clade 1 (genotype I); one caused a clinical case (V556) and the other was an environmental isolate (V557), and they both showed high genetic similarity (11 SNP differences), suggesting these two isolates could be the same N. fowleri strain and that the most likely source of the clinical case could be the environmental isolate. Similarly, two clinical isolates from Florida (V615 and V616; clade 1 [genotype 1], both isolated in 2009) also showed high genetic similarity (5-SNP difference; Table S4). Similarly, we also noticed other evidence of geographical clustering within the U.S. isolates. For example, two isolates each from Arkansas (V625 [2010] and V641 [2013]; 8-SNP difference) and Minnesota (V626 [2010] and V640 [2012]; 3-SNP difference) could be the same isolate within each of their respective states. At the same time, not all geographically clustered isolates would necessarily be the same isolate. For example, two isolates each from California (DIGERNES [1980s] and Camp [1978]; 55-SNP difference) and Texas (V019 [1984] and V020 [1984]; 124-SNP difference) cannot possibly be the same isolate due to the higher pairwise genetic differences. In contrast, we also noticed evidence of clustering of isolates originating from different states of the United States. For examples, the Arizona clinical isolate V387 (1996) was very similar to the clinical isolate V444 (2004), which was originally isolated from the brain of a cow from California (9-SNP difference), suggesting that the same N. fowleri isolate is capable of producing PAM in both humans and animals. Clinical isolate V204 (1990) from Mexico was very similar to environmental isolate V072 (1987) from New Mexico (20-SNP difference).

TABLE S4

Pairwise single-nucleotide polymorphism (SNP) differences between each of the N. fowleri isolates. Download Table S4, XLSX file, 0.02 MB ^{(25.2KB, xlsx)} .

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Only a limited number of genes showed significant transcriptome differences among clinical and environmental N. fowleri strains.

RNAseq analysis carried out to study transcriptome changes among clinical (N = 29) and environmental (N = 8) N. fowleri strains identified 34 differentially expressed genes (false-discovery rate [FDR], <1%; q < 0.1) (see Table S5 and Fig. S5 in the supplemental material). Among these, 14 genes had higher levels of gene expression in clinical strains compared to those in environmental isolates. These included genes with the following annotations: serine C-palmitoyl transferase, structural constituent of ribosome, DNA replication initiation, mitogen-activated protein (MAP) kinase activity, ion channel binding, and a gene with the Hint (Hog/INTein) auto-proteolytic protein-processing domain. At the same time, some of the genes that showed increased gene expression in the environmental isolates compared to the clinical isolates included genes responsible for ATP binding, regulation of the canonical Wnt signaling pathway, translation initiation factor activity, guanylate cyclase activity, cAMP biosynthetic process, methyltransferase small domain, cytoskeleton organization, and pyridoxal 5′-phosphate salvage. None of the GO terms associated with these differentially expressed genes were statistically significant in our GO term enrichment analysis, precluding us from assessing the functions and pathways of these genes in terms of the pathogenicity of N. fowleri.

FIG S5

Volcano plot highlighting the significantly differentially expressed genes between clinical and environmental N. fowleri isolates. Download FIG S5, EPS file, 0.4 MB ^{(417.1KB, eps)} .

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TABLE S5

Differentially expressed genes among clinical and environmental N. fowleri isolates based on transcriptome sequencing (RNAseq) analysis. Download Table S5, XLSX file, 0.01 MB ^{(14.6KB, xlsx)} .

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DISCUSSION

Out of the 40 described Naegleria species, only N. fowleri is known to infect humans and cause death. Data on PAM cases from 1965 to 2016 show that fewer than 20 cases per year have been reported globally (25). Only four well-documented PAM survivors are known among approximately 150 cases that occurred in North America since 1962, yielding an astounding >97% case fatality rate, which is one of the highest among infectious diseases. Although the pathogenesis of N. fowleri has been studied for the last 50 years, the mechanisms or the pathogenetic factors that lead to human infection and breaching of the blood-brain barrier to invade the central nervous system remain unknown. In addition, little is known regarding the genomic diversity both within N. fowleri isolates and among Naegleria species. In this study, we performed comparative genomic and transcriptomic analysis of a set of 52 N. fowleri draft genomes from clinical and environmental isolates derived from all over the world in the last 53 years, which will help shape the future genome-wide studies of this pathogen. In addition, we genome sequenced one N. lovaniensis isolate and performed comparative genome analysis of 56 isolates from 3 Naegleria species, including the available published genomes.

The genome sequence of N. fowleri TY (21), generated based on scaffolding long-read PacBio de novo-assembled contigs through guided optical mapping data and polishing with high-quality Illumina reads, has generated a “near-to-complete” reference genome with the highest quality to date for the human-pathogenic ameba N. fowleri. We believe that the 37 final contigs generated can be considered equivalent to 37 chromosomes, even though karyotyping studies are needed for final confirmation. The recently published NF30894 genome (18), sequenced using Oxford Nanopore Technology (ONT) and assembled into 90 contigs has an estimated genome size of 29.54 Mb, which is longer than the TY genome, but NF30894 has a lower N₅₀ value (717,491 bp versus 756,811 bp) than that of the TY genome. The TY genome showed the presence of 215 complete BUSCO genes, while the NF30894 genome only indicated the presence of 208 complete BUSCO genes along. The number of fragmented BUSCO genes was higher in the ONT-assembled NF30894 genome than that in the TY genome. Even though both ONT and PacBio generate long contigs, the incorporation of optical mapping (26), which captures the labeling patterns of long DNA molecules using restriction enzymes, for scaffolding merged most of the TY contigs. The use of such optical mapping for scaffolding Illumina-polished ONT contigs is highly recommended (27) in determining the whole-genome sequences of complex eukaryotes like N. fowleri. Even though the N. lovaniensis 76-15-250 genome sequenced in this study has a very similar total genome length to that of a recently published N. lovaniensis (ATCC 30569) (19) genome, the number of contigs was higher (199 contigs) in the former genome isolate than in the latter isolate (111 contigs). The N. lovaniensis 76-15-250 genome also has a smaller N₅₀ value (455,122 bp versus 657,933 bp). The incorporation of optical mapping for scaffolding these contigs would have improved the N. lovaniensis 76-15-250 draft genome.

Although fewer protein coding genes (9,405) were identified in the TY genome compared to those identified in all Naegleria species, especially in NF30894 (13,925) and NF30863 (17,252), we believe the predicted number of genes in the TY genome could possibly be a much more realistic estimate, mainly because of better genome scaffolding through optical mapping, as well as the incorporation of RNAseq data in the ab initio gene prediction. Ab initio gene prediction for NF30894 did not include transcriptomic data, while that for NF30863 included RNAseq data in gene calling but the genome lacked substantial enrichment of genomic DNA (17), which was reflected in the large number of contigs generated (1,729 contigs) and hence the greater number of predicted genes. However, the analysis of BUSCOs on all the protein coding genes showed a larger number of complete BUSCOs in the TY genome (220 genes) than in the NF30894 (219 genes) and NF30863 (210 genes) genomes, suggesting that the TY gene prediction could possibly be more realistic. Ab initio gene prediction of the N. lovanensis 76-15-250 gene predicted a smaller number than that predicted in the published N. lovaniensis (ATCC 30569) genome. The differences in the number of predicted genes might be due to lack of evidence from RNAseq data in our annotation, although both genomes have the same number of complete BUSCOs.

Recently, Herman et al. (28) sequenced two new N. fowleri isolates, V212 and 986, and by incorporating transcriptomic data for gene annotation they identified 12,677 and 11,599 genes, respectively. Even though the numbers of genes identified in these two genomes were a little higher than what we detected in the TY genome but lower than the numbers of genes detected in previously sequenced N. fowleri genomes, we believe that the scaffolding of the TY genome using optical mapping might have led to a realistic estimation of the number of genes present in N. fowleri. By comparing three N. fowleri (V212, 986, and NF30863) genomes against the N. gruberi ATCC 30224 genome, Herman et al. (28) detected 11,399 orthogroups (protein coding gene families), while our comparison of N. fowleri (52 isolates), N. lovaniensis (2 isolates), and N. gruberi (1 isolate) also estimated similar number of orthogroups (11,530). Similarly, Herman et al. (28) identified 7,656 genes shared among all genomes of the two Naegleria species, and 10,451 were shared by three N. fowleri isolates, whereas our analysis using multiple isolates from three Naegleria species estimated the presence of only 3,583 genes shared among the Naegleria species and 5,402 genes that were shared by all the 52 N. fowleri isolates. The disparity in the gene content could be mainly due to the greater genetic diversity of N. fowleri isolates included in this study, as well the fact that as our comparison included an additional Naegleria species, N. lovaniensis. Likewise, the numbers of unique N. fowleri genes identified in this study and by Herman et al. (28) were 274 and 458, respectively.

Considering that the high mortality rate of PAM comes from the combination of the intensive immune responses, tissue degradation during infection through overwhelming inflammation of the central nervous system, and parasite motility and phagocytosis, the results of GO enrichment analysis conducted on the unique N. fowleri genes in this study reflect the potential factors involved in the pathogenesis of PAM. For example, during the trophozoite free-living stage, N. fowleri uses a structure called a food cup to ingest bacteria and yeast, and in the human host, this same structure is used to ingest red and white blood cells and tissue (29). We were able to identify N. fowleri-unique genes that could facilitate the functions of the food cup, including those encoding acid hydrolases (Ty_07029 and Ty_03291), phospholipases (Ty_08620), and phospholipolytic enzymes that might play an active role in nerve tissue destruction. GO term analysis of unique N. fowleri genes also showed the presence of statistically enriched GO terms associated with pathways potentially involved in food cup and phagocytic cellular components, such as early phagosome (GO:0032009), phagocytic cup (GO:001891), and phagolysosome (GO:0032010), which were enriched in seven unique N. fowleri genes (Ty_00511, Ty_01019, Ty_01138, Ty_02771, Ty_5276, Ty_06706, and Ty_07422). It is also known that N. fowleri secretes a pore-forming protein termed naegleriapore A (with the protein domain saposin B type; UniProt accession number Q9BKM2), as well as proteases, to traverse the extracellular matrix during infection and to kill and digest cells (18, 30). Four genes with saposin B-type domains (Ty_05913, Ty_06795, Ty_06806, and Ty_08201), which could potentially be naegleriapore A coding genes, were detected in the TY genomes, but none were unique to N. fowleri. The prominent protease cathepsin protease (Nf314 or cathepsin [Ty_06276]), which is highly associated with the pathogenic N. fowleri strains (31–34), was also identified as a unique N. fowleri gene in our analysis (see Table S3 in the supplemental material). Herman et al. (28) identified that gene expression of both the precursor protein for naegleriapore A and cathepsin A were upregulated in pathogenic N. fowleri strains during a transcriptomic study comparing the gene expression profiles of an N. fowleri strain passed through mice to the expression of the same strain grown in axenic medium. The endosomal vesicle trafficking gene Rab GTPase Rab14 (Ty_05736) (28), which regulates early steps during phagocytosis and endocytosis, was one of the N. fowleri-unique genes identified in this study. Genome-wide transcription profiling by Herman et al. (28) found that the gene expression of Rab32, a paralogue of Rab14, was upregulated in pathogenic N. fowleri strains.

Proteins associated with actin cytoskeletal rearrangements have been linked as a pathogenicity factor in N. fowleri, in particular NF-actin, which is involved in phagocytosis and its location in the food cup structure (17, 35). Furthermore, actin binding proteins and upstream regulators of actin polymerization were reported to correlate with virulence. In our GO term analysis of unique N. fowleri genes, several GO terms associated with actin were significantly enriched (GO:0070360: migration of symbiont within host by polymerization of host actin; GO:0070359: actin polymerization-dependent cell motility involved in migration of symbiont in host; and GO:0070358: actin polymerization-dependent cell motility; Table S3). Among the N. fowleri-unique genes, we detected four cytoskeleton protein coding genes, actin-binding protein profilin (Ty_09040), tubulin beta (Ty_01613), actin (Ty_06706), and tubulin-binding protein kinesin family member C1 (Ty_08296). Profilin is known to regulate the actin cytoskeletal rearrangements by inhibiting actin polymerization, and it controls the Rap1 signaling pathway, which in turn regulates plasma membrane receptors, cytoskeleton rearrangement, intracellular adhesion, and cell mobility. Considering that upstream regulation of actin polymerization was reported to be a virulence factor (36), the actin-binding protein profilin (Ty_09040) could be an important player in the pathogenicity of N. fowleri. As noted above, actin is also dependent on phagocytosis, and Dianokova et al. (37) showed that the actin binding myosins are concentrated around the phagocytic cups, and thus myosins may be involved in phagocytic process in N. fowleri (17). A few studies have detected ∼11 myosin motor proteins, which were considered potential pathogenicity factors and include myosin II heavy chain and myosin Ie. We also detected several myosin motor protein coding genes in N. fowleri, including type I myosin protein coding genes (n = 6), myosin heavy chain (n = 4), myosin light chain kinase (n = 1), myosin XI tail binding (n = 1), and cofilin/tropomyosin-type actin binding protein (n = 1); however, none of the myosin protein coding genes were N. fowleri-specific genes. All of the myosin proteins are implicated in the organization and polarization of the actin cytoskeleton.

As previously identified (18), we also found several protein coding genes containing a DNAJ (HSP40) domain, which are known as regulators of HSP70 (38), a heat shock protein (HSP) linked to the pathogenicity of N. fowleri. A few genes encoding HSP70, HSP90, and HSP20 were also identified in the N. fowleri genome, but none of the HSP coding genes were unique to N. fowleri.

Variations in virulence of different N. fowleri virulence isolates are poorly understood, due to the small number of reference N. fowleri isolates used in virulence studies. Ideally, in animal studies, randomly obtained N. fowleri isolates from freshwater environments would be used to investigate whether N. fowleri isolates have the same capacity to cause PAM. In the absence of these data, we studied population structures within 52 N. fowleri isolates obtained from human PAM patients and environmental samples. Forty-eight of the 52 N. fowleri isolates came from 14 U.S. states, 2 from Mexico, and 1 each from Australia and Colombia. However, one major limitation of this study was that the number of environmental samples available was much lower than for the clinical samples (12 and 40 for genome comparison and 8 and 29 for transcriptome analyses, respectively). We only had environmental isolates from 4 out of 14 states, namely, Arizona (N = 8), Georgia (N = 1), New Mexico (N = 1), and Oklahoma (N = 1). The only Colombian isolate was from an environmental sample, and no clinical isolates were available from Colombia for genome comparison. Eight environmental isolates were collected in connection with three clinical samples from Arizona, and the high-resolution WNG phylogenetic analysis indicated possible links of six environmental isolates to a single clinical case in Arizona. The high-resolution separation of isolates based on the WNG phylogeny within a given mtSSU or ITS genotype suggests that new loci could be identified for the development of more descriptive genotyping tools useful for infection source tracking investigations.

RNAseq data showed only a limited number of genes (N = 34) that were differentially expressed among clinical and environmental N. fowleri isolates. Moreover, the expression fold change between the clinical and environmental isolates was low. Only 1.2- to 1.9-fold and 1.3- to 2.8-fold expression differences were noted among genes in clinical isolates that were more or less expressed than those in the environmental isolates (see Table S5 in the supplemental material). Perhaps this is not surprising, given the fact that (i) the number of environmental isolates was low (N = 8) compared to that from the clinical cases (N = 29), and (ii) all the isolates from both groups were maintained under identical laboratory conditions that are different from conditions inside the host (human brain) or warm freshwater environments. Moreover, it has already been shown (28) that the gene expression profile of a mouse-passaged N. fowleri strain compared to that of the same strain grown in axenic medium was different, suggesting that gene expression differed depending on whether the organism was in an infectious stage within the host, where it encounters host immune cells, or outside in a freshwater environment. Nevertheless, some of the differentially expressed genes between clinical and environmental isolates could be involved in pathogenesis and virulence, assuming that the clinical isolates represent only a minor population of N. fowleri in the environment and that they possess intrinsically different gene expression profile. When we looked at the chromosomal locations of some of the differentially expressed genes, we noticed something quite interesting (see Table S5 in the supplemental material). Nine out of 14 more highly expressed genes (64%) in clinical isolates were restricted to 3 chromosomes (chromosomes 3, 7, and 23). Likewise, 12 of 20 genes expressed at a lower level (60%) in clinical isolates were restricted to only 2 chromosomes (chromosomes 15 and 19). Since the chromosomal locations of a majority of the differentially genes in clinical strains (versus environmental strains) are mutually exclusive from each other, this seems to indicate an epigenetic regulation of gene expression that might regulate virulence in N. fowleri.

In summary, the genomic and transcriptomic data of this study will help shape future research in N. fowleri from basic biology to understanding of virulence and pathogenicity, global population structures, geographic origins, environmental exposure, and transmission dynamics. In addition, data generated in this study can be used for identifying novel genotyping loci for developing rapid molecular assays and will also be a valuable addition to genomic reference databases, where shotgun metagenomics data from routine water samples could be searched for the presence of N. fowleri strains.

MATERIALS AND METHODS

Naegleria species cultures and isolates.

The 52 Naegleria fowleri isolates and a nonpathogenic Naegleria species, Naegleria lovaniensis isolate (76-15-250) used in this study were cultured axenically in T-25 flasks in Nelson medium at 37°C (N. fowleri isolates) and 30°C (N. lovaniensis), respectively (39, 40). Forty-eight of the 52 N. fowleri isolates were originally from the United States (from 14 states) and the isolates included 37 from PAM patients and 11 from environmental water samples (from 4 states and Colombia). The remaining four N. fowleri isolates were from PAM patients outside the United States (2 from Mexico and 1 each from Australia and Colombia). Some of the metadata about the N. fowleri isolates are provided in Table S1 in the supplemental material.

Preparation of genomic DNA and RNA libraries.

Genomic DNA and RNA was extracted after harvesting log-phase trophozoites (∼2 × 10⁶) by placing the culture flasks on ice for 10 min to dislodge the trophozoites from flask walls, followed by centrifugation at 1,500 × g for 10 min. The resulting culture pellet was washed 3 times with 1× PBS and was used in DNA or RNA extraction according to the manufacturer’s instructions (DNeasy blood and tissue kit and RNeasy minikit; Qiagen). Culture pellets were stored at −80°C with 1 ml of TRIzol after a 1× PBS wash. Extracted RNA was converted to cDNA and purified with a Qiagen PCR purification kit before library preparation for sequencing.

For Illumina library preparation, genomic DNA was sheared to a mean size of 600 bp using an LE220 focused ultrasonicator (Covaris, Inc., Woburn, MA). DNA fragments were AMPure (Beckman Coulter, Inc., Indianapolis, IN) cleaned and used to prepare dual-indexed sequencing libraries using NEBNext Ultra library prep reagents (New England Biolabs, Inc., Ipswich, MA) and barcoding indices synthesized in the CDC Biotechnology Core Facility. Libraries were analyzed for size and concentration, then pooled and denatured for loading onto flow cells for cluster generation. Sequencing was performed on an Illumina HiSeq2500 (or MiSeq) instrument using HiSeq Rapid SBS v2 250- × 250-cycle (or MiSeq 250- × 250-cycle) paired-end sequencing kits. On completion, sequence reads were filtered for read quality, base called, and demultiplexed using bcl2fastq (v2.19). A standard 20-kb PacBio library was size selected at 10 kb and then run on an RS II instrument for 360-min movies on 4 SMRTcells.

Processing of genomic data.

We recently generated a “close-to-complete” genome of an N. fowleri TY isolate (ATCC 30107) using HiSeq (Illumina) and RS II (Pacific Biosciences, Menlo Park, CA) instruments and verified the assembled genome with optical mapping data (21). Briefly, genomic DNA was harvested from log-phase trophozoites (∼2 × 10⁶), and libraries were prepared for PacBio sequencing runs using the SMRTbell template prep kit 1.0 and polymerase binding kit P6, the filtered reads (minLength = 1000bps) were de novo assembled using Canu v1.6 (41), and the resulting consensus sequences were determined with Quiver (v1) (https://github.com/PacificBiosciences/GenomicConsensus). The assembly was confirmed by comparison to restriction digest optical maps obtained from log-phase trophozoites (∼1 × 10⁶) using the Argus system (OpGen) with MapSolver (v2.1.1; http://www.opgen.com). Final PacBio assembly of the TY strain was further polished by mapping Illumina reads using unicycler_polish (default parameters; Unicycler package v4.4) (42). This led to the identification of 37 contigs representing 37 chromosomes in N. fowleri (21). For all remaining N. fowleri isolates (see Table S1 in the supplemental material) described in this study, a combination of HiSeq/MiSeq (Illumina, San Diego, CA) libraries was prepared using the NEBNext Ultra library prep kit (New England Biolabs). The Illumina reads were trimmed with cutadapt (43) to remove adaptor sequences and reads below Q20 and 75 bp. Short-read assemblies were carried out using SPAdes (44) with the “-careful” option. The de novo assemblies were improved by scaffolding the best contigs with SSPACE (45) using the short-read Illumina sequences. The resultant scaffolds from each of the isolates were mapped against the “complete” N. fowleri TY PacBio genome using ABACAS (46), which uses the MUMmer alignment tool to identify syntenies of contigs against the reference genome and generates “pseudo chromosomes,” taking overlapping contigs and gaps into account. Remaining sequence gaps were filled using GapFiller (47), which used short-read Illumina sequences to fill the gaps. Contigs from the previously published N. fowleri draft genome were also obtained from GenBank and scaffolded using ABACAS based on the N. fowleri TY genome. The isolate pairs Davis and V414, Wade and V457, and V067 and V523 were cryopreserved in different time frames and sequenced, so technically those isolate pairs are the same isolates with different names. A single N. lovaniensis isolate (76-15-250), sequenced using both PacBio and Illumina, was processed similarly as described above, but no restriction digest optical maps were generated for this isolate. For all N. fowleri isolates, the two traditional genotyping loci (24, 48, 49), mitochondrial small subunit rRNA (mtSSU rRNA), and the internal transcribed spacer (ITS) were identified by comparing their genome data to a local database of reference loci using custom Python scripts.

Genome completeness and annotation.

To assess the completeness of the N. fowleri TY and N. lovaniensis 76-15-250 genomes, BUSCO v4.0.6 (50) was used to search the latest and updated set of 255 conserved eukaryotic Benchmarking Universal Single-Copy Orthologs (BUSCO) of the Eukaryota odb10 data set. To validate the output of BUSCO and for comparison between Naegleria species, the tool with the updated Eukaryota odb10 data set was reapplied to the previously published genomes of N. fowleri (17, 18), N. gruberi (20), and N. lovaniensis (ATCC 30569) (19).

Repetitive elements were predicted using a de novo approach by applying RepeatMasker v4.0.8 (51), which uses the Repeat Protein Database, which contains more than 7,400 entries and includes 16.1 million amino acids covering 133 subclasses of transposable elements, and by using RepeatModeler (52). The protein coding genes on the nuclear genome of all N. fowleri isolates were predicted using an ab initio approach taking into account RNAseq data by applying Braker2 (https://github.com/Gaius-Augustus/BRAKER) (53), which incorporates both GeneMark (54) and Augustus v3.3.2 (55) genome annotation tools. Briefly, Braker2 was initially run on the N. fowleri TY genome in -esmode without RNAseq evidence in order to train N. fowleri-specific Augustus parameters. Once the Augustus parameters were obtained, a second Braker2 run was performed by reusing the pretrained parameters and providing the RNAseq evidence to Augustus only. For those isolates with RNAseq data, evidence was provided by mapping the RNAseq data (in .bam format) using TopHat2 (56) (-library-type fr-unstranded and the rest with default parameters) to the corresponding draft genome of the isolate. For isolates without RNAseq data, genome annotation was performed using Augustus using pretrained parameters without providing expression data evidence. The protein coding genes on the nuclear genomes of other Naegleria species (both newly sequenced and published) were reannotated using Augustus after obtaining respective species-specific training parameters as described above, except for N. fowleri (ATCC 30894), where gene annotations were publicly available. The completeness of the gene annotations of N. fowleri TY and N. lovaniensis 76-15-250 along with those of all previously published Naegleria species were assessed using BUSCO as described above. Functional annotation of all the Naegleria sp. predicted genes were obtained using eggNOG-mapper (57), which is based on eggNOG v4.5 orthology data.

Identifying orthologous genes among Naegleria species.

To gain an overview of the gene repository of the genus Naegleria and to identify N. fowleri genes that are unique compared to N. gruberi and N. lovaniensis, proteins from each of the species were clustered using Neptune (58), CD-HIT (59), and OrthoMCL (60). The default parameter was used for Neptune to calculate the proper size of the k-mer, and both the filter length and filter percentage were set at 0.4. For CD-HIT (v4.6), the CD-HIT-2d comparison algorithm was used with a word size of 2 (-n 2) and 0.4 as the length difference cutoff (-s2). For OrthoMCL, the complete predicted protein coding sequences from all three Naegleria species genomes were searched against themselves using BLASTP with an E-value cutoff of 1E−10 and a minimum percent identity of 50% for significance. The best BLASTP scores were used for identifying orthologous groups using the OrthoMCL algorithm (60). A matrix with the information on the presence or absence of all orthologous genes present in all 56 isolates in the three Naegleria species was created and imported into the R package micropan (61), to perform principal-component analysis (PCA) and to generate visualizations to describe genome clustering. GO term enrichment analysis for the N. fowleri genes identified as unique compared to N. gruberi and N. lovaniensis, both at the genus and population level, was performed using GOATOOLS (62), and the statistically enriched GO terms were identified after Bonferroni multiple testing P value correction (p_bonferroni < 0.05). All of the statistically significant enriched GO terms within biological process (BP), molecular function (MF), and cell component (CC) categories were visualized using the Seaborn package in IPython (63).

Population structure analysis of Naegleria species.

To elucidate the possible population structure within the 56 Naegleria isolates representing three Naegleria species, the ChromoPainter algorithm (64) was applied to the genome-wide haplotype data, generated from a core genes nucleotide alignment generated by concatenating all the genes shared among the 3 Naegleria species, using the linkage model. A recombination map file was created by specifying a uniform recombination rate per site per generation using a Perl script called makeuniformrecfile.pl (http://www.paintmychromosomes.com). Each isolate is reconstructed using the haplotypes of each of the other isolates in the sample as possible donors. The donor in each region is interpreted as the isolate with which the haplotype shares the most recent common ancestor for that stretch of DNA. The output from ChromoPainter is a coancestry matrix that summarizes the similarity between isolates in terms of the number of haplotype “DNA chunks” used to reconstruct the recipient isolate from each donor isolate. The fineSTRUCTURE algorithm (64) used the coancestry matrix generated by ChromoPainter to perform model-based clustering using a Bayesian Markov chain Monte Carlo (MCMC) approach to explore the population structure. FineSTRUCTURE was run for 400,000 iterations; the first 200,000 iterations were discarded as MCMC burn-in. The thinning interval was specified at 100.

Phylogenetic analysis of N. fowleri isolates/strains.

N. fowleri Illumina reads were mapped to the N. fowleri TY “complete” reference genome using BWA-MEM v0.7.12 (65) for short-read mapping. SNPs were called using Freebayes v1.0.2 (https://github.com/ekg/freebayes), requiring a minimum read coverage of 10× with a Phred quality score of at least 20. For each SNP that passes these criteria in any one isolate, consensus base calls for the SNP loci were extracted from all genomes mapped, and if the Phred quality scores were under 20, that allele was treated as unknown and represented with a gap (N) character. Chromosomal SNPs with confident homozygous calls in >90% of the genomes mapped were concatenated to form an SNP alignment. A maximum-likelihood (ML) phylogenetic tree was inferred from the chromosomal SNP alignment using RAxML (v8.2.9) (66) with a generalized time-reversible model and gamma distribution model with site-specific rate variations (GTRGAMMA nucleotide model in RAxML with ascertainment correction [-asc-corr=stamatakis] and 100 bootstrap pseudoreplicates used to assess branch support for the ML phylogeny). Only one isolate from each of the pairs of isolates (Davis and V414, Wade and V457, and V067 and V523) that were cryopreserved at different times were used in the phylogenetic analysis. The aforementioned chromosomal SNP alignment was also used to calculate the SNP differences among closely related N. fowleri isolates or phylogenetic clades. Phylogenetic analysis of all of the N. fowleri mitochondrial genomes were also performed as described above.

Differential gene and transcript expression analysis of clinical and environmental N. fowleri isolates.

Thirty-seven of the 52 N. fowleri isolates were available for differential gene expression analysis, including 29 from clinical PAM patients and 8 from environmental samples (see Table S1 in the supplemental material). RNAseq reads in FASTQ format for each isolate were first aligned to the N. fowleri TY reference genome using TopHat2 (56), and then transcript assembly was performed using Cufflinks (67). All transcript assemblies were merged using Cuffmerge to create a single merged transcriptome annotation. Counts for each gene were quantified and normalized across all samples using Cuffnorm v2.2.1.35. Differentially expressed genes in either clinical or environmental groups were identified by Cuffdiff using the following cutoffs: log₂ fold change > 1 or < −1 and false-discovery rate [FDR] < 1%.

Data availability.

All sequencing and transcriptomic data associated with this study were submitted to the National Center for Biotechnology Information’s Sequence Read Archive (SRA) under BioProject accession identifier PRJNA642022. All of the gene sequences of N. fowleri TY and functional annotations of all genes and of the N. fowleri unique genes are available in the figshare repository (https://figshare.com/projects/Comparative_genomic_and_transcriptomic_analysis_of_Naegleria_fowleri_clinical_and_environmental_isolates/118200).