Retracing the path of evolution: polymorphisms of aspA codon 363 shape the fitness of Yersinia pestis

TL;DR

A specific mutation in the aspA gene of Yersinia pestis affects its fitness and evolution, revealing how the bacteria adapted over time.

Contribution

The study reveals how polymorphisms at aspA codon 363 influence Y. pestis fitness and evolutionary dynamics.

Findings

The TTG allele at aspA codon 363 inactivates AspA and provides a competitive advantage in bacterial niche.

The GTG allele expresses active AspA and offers fitness benefits under stress conditions.

An evolutionary relay of inactivating and restoring mutations at aspA codon 363 shaped Y. pestis microevolution.

Abstract

Yersinia pestis, the etiologic agent of plague, is a genetically monomorphic pathogen. By screening 1085 published Y. pestis genomes, we identified an unusual mutation hotspot within codon 363 of the aspartate ammonia-lyase gene aspA with at least six alleles in the population. Our investigation delves into the significance of the polymorphism at the aspA codon 363 and its impact on the fitness of Y. pestis strains. Notably, we found that the dominating TTG allele (L363), resulting in AspA inactivation, confers a fitness advantage to Y. pestis when competing with other bacteria inhabiting a similar niche, due to elevated expression of pesticin. However, the TTG strain exhibits fitness deficits under various stress conditions compared to the GTG strain (V363), which expresses an active AspA. Drawing from these observations, we propose an evolutionary hypothesis for Y. pestis at the aspA codon 363 locus. It is inferred that GTG represented the ancestral state at this locus. However, the TTG strain swiftly dominated populations in the early evolutionary stage of Y. pestis, likely owing to the V363L substitution that conferred a competitive advantage to Y. pestis over other bacteria. Subsequently, spontaneous mutations emerged, reinstating AspA activity, thereby offering fitness advantages across diverse environments and get fixed within the population. Our findings portraited a scenario of inactivating-restoring mutations relay in Y. pestis microevolution, shedding new lights on the evolutional dynamics of pathogens.

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Introduction

Yersinia pestis, the notorious agent behind plague, ranks among the most lethal and globally impactful pathogenic bacteria. Its presence spans diverse ecological niches encompassing humans, rodents, fleas, and various natural environments such as soil, facilitating its survival, propagation, and persistence throughout its lifecycle [1]. Notably, genomic comparative analyses trace the emergence of Y. pestis from the enteric pathogen Yersinia pseudotuberculosis to around 7000 years ago [2]. Key genetic acquisitions, notably the pla gene, especially the subsequent I259 T substitution in Pla, play pivotal roles in the pathogenicity and epidemic dissemination of Y. pestis [3]. Further enhancements to its flea-borne transmission potential involve the inactivation of ureD, rcsA, and pde2, paired with the acquisition of ymt [4–6].

The evolutionary landscape of Y. pestis reveals over thirty phylogroups within five primary branches [7]. Notably, the first pandemic stems from an extinct lineage labelled 0.ANT4 [8], while the second and third pandemics trace back to strains within branch 1, representing the most widely dispersed lineage within Y. pestis. Branches 1–4 radiated from the Big Bang node that emerged in the early fourteenth century, immediately preceding the Black Death [9]. Branch 0, a root lineage of Y. pestis, houses ancient strains identified so far and several “atypical” groups. Among these, the 0.PE7 group stands as the oldest among all modern Y. pestis natural isolates [7]. Remarkably, the 0.PE4 group, assigned to the biovar Microtus, exhibits high virulence in mice but reduced virulence in larger mammals like guinea pigs and humans [10].

Genomic analyses indicate that Y. pestis as a genetically monomorphic species, showing very limited genetic diversity, with a genome mutation rate estimated between 3.1 × 10^−9^–1.3 × 10^−7^ per site per year [7]. While the fixation of single nucleotide polymorphisms (SNPs) in the Y. pestis genome primarily occurs through neutral processes like genetic drift, our focus lies on codon 363 of YPO0348 (aspA), encoding aspartate ammonia-lyase (AspA, also known as aspartase) displaying significant polymorphism with six distinct alleles [7].

AspA, ubiquitous in procaryotes, plays a pivotal role in aspartate metabolism by catalyzing the deamination of aspartate to fumarate and ammonia, which can be integrated into gluconeogenesis and nitrogen assimilation, respectively [11]. AspA deficiency in bacteria hampers the utilization of exogenous aspartate and intracellular aspartate formed by transamination, disrupting its recycling into the tricarboxylic acid cycle [12]. Among the alleles of Y. pestis AspA, the codon at position 363 is highly polymorphic. Six different alleles have been reported so far: GTG (Val), TCG (Ser), TTT and TTC (Phe), ATG (Met), and TTG (Leu). Notably, the prevalent TTG codon in modern Y. pestis strains inactivates AspA enzymatic activity, contrasting with other alleles encoding active AspA variants [13,14]. This mutation possibly suggests a selective advantage, considering the rarity of aspartate deficiency in bacteria [15]. The presence of other alleles hints at reverted mutation events on Y. pestis AspA, indicating the potential role of natural selection in shaping aspA codon 363 diversity. Previous research has linked functional AspA to the avirulence of Y. pestis in humans, as observed in attenuated biovar Microtus strains where the encoding nucleotides at the locus represent an active AspA [14].

The diverse codons at Y. pestis aspA codon 363, corresponding to distinct AspA enzyme activities, likely establish connections between locus polymorphisms and Y. pestis fitness in varied environments. Therefore, we investigated this possibility in this study.

Materials and methods

Genome data collection

Genome assemblies and raw sequencing data (comprising both modern strains and ancient DNA) of Y. pestis were acquired from the NCBI GenBank and SRA databases as of July 2021. Low-quality reads (<Q20) were filtered using Trimmomatic (v0.38) [16], and the filtered sequencing data for modern strains were assembled with SPAdes (v3.13.0) to validate the reliability of public assemblies [17]. Our final dataset comprised 992 assemblies of modern strains and 93 ancient DNA sequences of Y. pestis. Besides, a total of 311 genome assemblies and 581 raw sequencing datasets of Y. pseudotuberculosis retrieved from the NCBI repository were also used.

SNP identification and phylogenetic analysis

The assemblies were aligned to the CO92 chromosome reference (NC_003143.1) using MUMmer (v3.23) [18]. Core-genome SNPs were identified from the MUMmer alignments, excluding those in repetitive regions. A maximum-likelihood tree was generated from the identified SNPs using IQ-TREE (v1.6.5) [19] with the GTR + G model and ultrafast bootstrapping (bootstrap = 1,000). The resulting tree was visualized with the online tool iTOL (v6.8) [20]. Briefly, to ensure both clarity and representativeness in the phylogenetic reconstruction, we selected 992 modern Y. pestis genomes from a pool of over 3,000 strains included in our recent study [21]. For lineages containing only the TTG allele at codon 363 of aspA, representative genomes were randomly subsampled to minimize redundancy. Conversely, all lineages harbouring non-TTG alleles were retained in full to facilitate a comprehensive evaluation of allelic diversity across the phylogeny.

For modern Y. pestis strains, the allele state at codon 363 of aspA was determined from the SNP matrix and further validated using raw sequencing reads. Reads were aligned to the CO92 reference genome (GCF_000009065.1) using BWA-MEM (v0.7.17) [22] with default parameters, and variants were called using GATK HaplotypeCaller (v4.2.4.0) [23], requiring a minimum of ten supporting reads and an allele frequency > 0.9. For ancient DNA (aDNA), phylogroup assignment was based on previously published studies. We retrieved publicly available Y. pestis aDNA genomes published up to July 2021. Raw reads were processed using Trimmomatic v0.38 to remove reads shorter than 30 bp or with a Phred score below 20. The filtered sequencing data were mapped to the CO92 reference genome using BWA-MEM with default settings. Aligned reads were extracted using SAMtools v1.9 with the -bF 4 flag and subsequently merged. Reads with more than 10 soft- or hard-clipped bases were removed using samclip, and PCR duplicates were eliminated using Picard’s MarkDuplicates tool (v2.21.2). Mutation sites at the aspA 363 codon for each genome were subsequently identified with GATK's HaplotypeCaller module with a minimum threshold of three supporting reads and an allele frequency greater than 0.9. Positions that did not meet these criteria were manually inspected in the corresponding BAM files, with sites near read termini excluded to reduce the potential impact of terminal damage.

We also examined the allele state of codon 363 in the aspA gene across Y. pseudotuberculosis. A total of 892 strains were analysed, comprising 311 genome assemblies from NCBI GenBank and 581 raw sequencing datasets from the NCBI SRA database. Raw reads were trimmed using Trimmomatic and assembled with SPAdes (v3.13.0). All assemblies were aligned to the Y. pestis CO92 reference chromosome using MUMmer, and the codon 363 position in aspA was subsequently inspected to determine the corresponding allele as described above.

Bacterial strains and growth conditions

The bacterial strains and plasmids used in this study are listed in Table S1. Y. pestis biovar Microtus strain 201, a human-avirulent strain while lethal in mice, was isolated from the rodent Microtus brandti in Inner Mongolia, China, and has a gene content almost identical to that of Y. pestis strain 91001 [10,24]. Strain 201 is a GTG strain belonging to phylogroup 0.PE4C and expresses an active AspA [13,14]. To generate the isogenic TTG mutant, allelic exchange was performed using a suicide plasmid pDS132, as illustrated in Figure S1. Briefly, a fragment of the aspA gene carrying the desired point mutation (e.g. TTG at codon 363) was PCR-amplified and cloned into pDS132 digested with SphI and SacI. The recombinant plasmid (pDS132_TTG) was electroporated into E. coli S17-λpir, which was then used as a donor strain for conjugation with Y. pestis strain 201. After overnight culture, the bacterial mixture was plated on Yersinia Selective Agar Base (YSAB) supplemented with 8 µg/ml chloramphenicol. Selected Y. pestis colonies were subcultured in LB broth and counter-selected on LB agar supplemented with 7% sucrose. Lastly, allelic exchange at the aspA locus was confirmed by Sanger sequencing. All strains were grown in LB or TMH liquid medium (Table S2), or on LB agar at 26°C (for Y. pestis) or 37°C (for E. coli or Y. pseudotuberculosis). The glycerol-preserved strains were inoculated into 5 ml of medium and fully activated overnight. The subcultured inocula in fresh medium were used in follow-up experiments. Chloramphenicol (34 μg/ml) was added to the media when needed.

Aspa enzymatic activity detection

AspA activity was assessed using Nessler's reagent colorimetric method. Bacteria were grown to late-exponential phase, harvested, washed in PBS, then suspended to an optical density of OD_620_ = 2.5. Aliquots (1 ml) of bacterial suspensions were incubated with 50 mM L-aspartic acid or ddH_2_O (control) at 37°C. After 30 min of incubation, 0.4 ml Nessler’s reagent (0.09 M K_2_HgI_4_ and 2.5 M KOH) was added to each sample to detect ammonium production. A yellow–brown coloration indicated active AspA, whereas pale yellow reflected minimal or no activity. This assay enabled direct detection of AspA activity without protein purification.

Growth curves

The Y. pestis strains were incubated in LB/TMH medium at 26℃ with shaking overnight for activation recovery. Inocula were subcultivated in fresh medium at 26℃. Samples with an optical density at 600 nm (OD_600_) of 1.0 were incubated in 150 ml Erlenmeyer flasks containing 60 ml medium of interest at a ratio of 1: 200. Triplicates were performed for each strain and OD_600_ of each sample was recorded at regular intervals during the growth cycle.

When the curve reached plateau, the data were collected for growth curve plotting. To avoid long and variable lag time, for all other specific-medium growth experiments, both strains were subcultured twice at 26°C in each specific medium prior to growth experiments to adapt to the conditions. The results of all growth curves were presented as the normalized areas under the growth curves, with the TTG strains as the standards. All experiments were performed three times independently with three replicates.

Real-time cell analysis (RTCA) assay

The HeLa cells were cultivated in Dulbecco’s modified Eagle’s medium (DMEM, Gibco, USA) containing 10% fetal bovine serum at 37°C in a 5% CO_2_ incubator. 50 μl of the medium was pipetted into each well of the E-plate connected to the RTCA iCELLigence system to measure the baseline. 5 × 10^3^ HeLa cells were added into each well of the E-plate. The E-plate containing the cells was incubated for 30 min under room temperature, followed by being transferred to the RTCA iCELLigence system at 37°C in a 5% CO_2_ incubator. When cell proliferation came into the stable logarithmic growth period, Y. pestis cells were resuspended in the same medium and were added to the wells at a multiplicity of infection (MOI) of 10. The cell index was measured at 2 min intervals. The experiment was performed three times independently with three replicates.

Competition assay

The GTG and TTG strains stored at −80℃ in 15% glycerol were incubated in liquid TMH/LB medium at 26℃ with shaking for 24 h for activation recovery. The cultures were subcultivated in fresh medium at 26℃ with shaking and once the OD_620_ reached 1.0, they were mixed in a certain proportion in each assay. The mixtures were incubated at a ratio of 1:20 in liquid media at 26℃ with shaking for 96 h subsequently or were transferred at the exponential phase for another passage every 8/12 h. In total, all the liquid cultures were maintained for up to 30/100 passages. In the meantime, a fraction of each passage (including the initial mixture as the starting population) was harvested by centrifugation and stored at −80℃ for genomic DNA extraction (QIAGEN DNA Extraction kit).

As for the competition assay in vivo, female mice were challenged by mixtures at a certain proportion via Subcutaneous injection (∼1000 CFU per mouse). Tissue samples (0.25 g) from spleens of mice (n = 10 for each group) were collected once the mice died and used for DNA extraction (QIAGEN tissue DNA Extraction kit).

Amplicon sequencing enables high resolution of a single nucleotide while maintaing high-throughtput capability for multiple competitive samples through deep sequencing. Thus, each genomic DNA was used as the template and high-fidelity PCR amplicon sequencing was performed using primers amplicon-F (5’ ACG ATA CTT GCA TTA CTA TG 3’) and amplicon-R (5’ GGT TAA GAT AAG TGA CGA TG 3’) with specific Barcodes. The frequency of the GTG and TTG strains in each passage or tissue sample was obtained by calculating the ratio of G: T at the target site of the amplicon.

To visually evaluate the fitness difference between the two strains, a competition index μ was introduced [25]:

$$[eqn]$$

where T and G denote raw read counts from the amplicon of the TTG and the GTG strains, respectively. Terms (T_t_/G_t_) can be interpreted as the ratio of the absolute number of the TTG to the GTG strain at a time point (t), which is normalized to that at the initial time point (t_0_). Denary logarithm transform is used to determine the ratio μ. According to the meaning of the ratio μ, the points below the X axis imply that the GTG shows a competitive advantage, that is, the portion of the GTG strain can outnumber that of the TTG strain during the series passages.

Viability of the two strains in macrophage

RAW cells were spread in 12-well plates at a density of 10^6^ cells per well and incubated overnight at 37℃ in an incubator containing 5% CO_2_ overnight before infection. The GTG and TTG strains were allowed to grow at 26℃ to the exponential growth phase (OD_620_ = 1.0, equivalent to a bacterial density of 2 × 10^8^ CFU/ml), followed by adding to the cells at a concentration at a multiplicity of infection (MOI) of 5. Plates were centrifuged at 700 × g for 5 min to facilitate bacterial contact with macrophages. Media were discarded and PBS was added to wash the cells after 30 min of infection. gentamicin 30 μg/ml was added to kill the bacterial cells which failed to enter the macrophages for 30 min and use the sample at the time as point 0 h. Cells were lysed in each well with 0.3% Triton X-100 for 15 min at 2, 4, 6, and 8 h, and the CFU count was performed on the two strains. The experiment was performed three times independently with three replicates.

Mice challenge assay

Overnight cultures of the two strains were allowed to grow at 26℃ to the exponential growth phase (OD_620_ = 1.0), which were used to challenge mice (female BABL/c, 8 weeks old). The mice (n = 10) were challenged with the two strains subcutaneously or intravenously (∼ 1000 CFU per mouse) and mortality was recorded continuously for two weeks. Mice at the terminal stage of infection were euthanized by cervical dislocation following institutional guidelines and ethical regulations. Survival curves were analysed using the log-rank (Mantel–Cox) test. All the mice were handled as per the Guidelines for the Welfare and Ethics of Laboratory Animals of China. All experiments were performed twice independently.

Survival assay under stressed conditions

Overnight cultures of the TTG and GTG strains were allowed to grow in TMH at 26℃ to the exponential growth phase (OD_620_ = 1.0), which were used for the survival assays of the two strains under certain stressed conditions. CFU of the culture above was counted as the control. Then, the cultures were transferred into the solutions simulating different stressed conditions such as acid (pH = 5.5, 30 min), cold shock (4℃), heat shock (50℃, 10 min), anaerobic, high salinity (0.5 M NaCl, 1 h), and oxidative stress (0.2 M H_2_O_2_, 10 min) for a period. CFU of each strain was counted at different time points. And the survival rate was the ratio of the CFU at a time point divided by that of control. All experiments were performed at least three times independently with three replicates.

RNA extraction and data analysis

Total RNA was extracted using the PureLink™ RNA Mini Kit (Invitrogen, USA) for creating a cDNA library and transcriptomics sequencing. Differential expressions were expressed as the logarithm to base 2 of fold change (Log_2_FC). The genes with differential values more than twofold were applied to analyse the differential expression according to the Y. pestis 91001 genome annotation. Each sample included three biological replicates.

Bactericidal assay

A bactericidal assay was established using E. coli cells expressing Y. pestis FyuA (DH5α-fyuA) from a pET22b vector to test if there was a difference between the two strains in killing E. coli cells expressing FyuA. Overnight cultures of the TTG and GTG strains and Y. pseudotuberculosis or DH5α-fyuA were allowed to grow to the exponential growth phase. Initial CFU was counted as the control. Mix Y. pseudotuberculosis or DH5α-fyuA with the TTG or GTG strain and the mixture was incubated at 26℃. The mixture was gradient-diluted and the diluted mixture was dripped onto the plate containing ampicillin (100 μg/ml). CFU of the Y. pseudotuberculosis or DH5α-fyuA was counted on the same plate for the comparison between the survival rate after the E. coli cells undergoing the bactericidal effect by the two strains. Meanwhile, the CFU of each strain was also counted on a yersinia selective agar base for the comparison between the survival rate after mixed with the E. coli cells. All experiments were performed at least three times independently with three replicates.

Ethics statement

The animal study was conducted in accordance with institutional guidelines and ethical regulations of the Beijing Institute of Microbiology and Epidemiology (IACUC-IME-2023-001).

Statistical analysis

All data of the experimental groups were obtained from three independent experiments and expressed as mean ± standard deviation. As appropriate, statistical analysis was applied using the Student t-test, Wilcoxon test, the one-way analysis of variance, or chi-square test. The one-way analysis of variance was performed when groups are more than two, the Student–Newman–Keuls-q test was applied for multiple comparisons, and chi-square test was used to analyse the comparison of the composition ratio between the two groups. Statistical significance was set as follows: *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

Supplementary Material

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Revised Table S3.xlsx

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