Reversion of neurovirulent mutations, recombination and high intra-host diversity in vaccine-derived poliovirus excreted by patients with primary immune deficiency.

Patients with Primary immunodeficiency (PIDs) may be infected by Polioviruses (PVs), especially when vaccinated with live Oral Polio Vaccine before diagnosis. They may establish long-term shedding of divergent strains and may act as reservoirs of PV transmission. This study delved into the effect of the genetic evolution of complete PV genomes, from MHC class II-deficient patients, on the excretion duration and clinical outcomes. Stool samples from three PID patients underwent analysis for PV detection through inoculation on cell culture and real-time PCR, followed by VP1 partial sequencing and full genome sequencing using the Illumina technology. Our findings revealed a low number of mutations for one patient who cleared the virus, while two exhibited a high intra-host diversity favoring the establishment of severe outcomes. Neurovirulence-reverse mutations were detected in two patients, possibly leading to paralysis development. Furthermore, a recombination event, between type 3 Vaccine-Derived Poliovirus and Sabin-like1 (VDPV3/SL1), occurred in one patient. Our findings have suggested an association between intra-host diversity, recombination, prolonged excretion of the virus, and emergence of highly pathogenic strains. Further studies on intra-host diversity are crucial for a better understanding of the virus evolution as well as for the success of the Global Polio Eradication Initiative.

Assessing global drivers of parasite diversity: host diversity and body mass boost avian haemosporidian diversity.

Biodiversity varies worldwide and is influenced by multiple factors, such as environmental stability and past historical events (e.g. Panama Isthmus). At the same time, organisms with unique life histories (e.g. parasites) are subject to unique selective pressures that structure their diversity patterns. Parasites represent one of the most successful life strategies, impacting, directly and indirectly, ecosystems by cascading effects on host fitness and survival. Here, I focused on a highly diverse, prevalent and cosmopolitan group of parasites (avian haemosporidians) to investigate the main drivers (e.g. host and environmental features) of regional parasite diversity on a global scale. To do so, I compiled data from 4 global datasets on (i) avian haemosporidian (malaria and malaria-like) parasites, (ii) bird species diversity, (iii) avian functional traits and (iv) climate data. Then, using generalized least square models, I evaluated the effect of host and environmental features on haemosporidian diversity. I found that haemosporidian diversity mirrors host regional diversity and that higher host body mass increases haemosporidian diversity. On the other hand, climatic conditions had no effect on haemosporidian diversity in any model. When evaluating Leucocytozoon parasites separately, I found parasite diversity was boosted by a higher proportion of migratory hosts. In conclusion, I demonstrated that haemosporidian parasite diversity is intrinsically associated with their hosts' diversity and body mass.

High-resolution environmental and host-related factors impacting questing Ixodes scapularis at their northern range edge.

The geographic range of tick populations has expanded in Canada due to climate warming and the associated poleward range shifts of their vertebrate hosts. Abiotic factors, such as temperature, precipitation, and snow, are known to directly affect tick abundance. Yet, biotic factors, such as the abundance and diversity of mammal hosts, may also alter tick abundance and consequent tick-borne disease risk. Here, we incorporated host surveillance data with high-resolution environmental data to evaluate the combined impact of abiotic and biotic factors on questing Ixodes scapularis abundance in Ontario and Quebec, Canada. High-resolution abiotic factors were derived from remote sensing satellites and meteorological towers, while biotic factors related to mammal hosts were derived from active surveillance data that we collected in the field. Generalized additive models were used to determine the relative importance of abiotic and biotic factors on questing I. scapularis abundance. Combinations of abiotic and biotic factors were identified as important drivers of abundances of questing I. scapularis. Positive and negative linear relationships were found for questing I. scapularis abundance with monthly mean precipitation and accumulated snow, but no effect was found for the relative abundance of white-footed mice. Positive relationships were also identified between questing I. scapularis abundance with monthly mean precipitation and mammal species richness. Therefore, future studies that assess I. scapularis should incorporate host surveillance data with high-resolution environmental factors to determine the key drivers impacting the abundance and geographic spread of tick populations and tick-borne pathogens.

Opening the Black Box of Host Range, Vectorial Diversity, and Genetic Variants of Genus Anaplasma: The Contributing Factors Toward Its Zoonosis.

Background: Genus Anaplasma of the family Anaplasmataceae possesses bacteria of hematopoietic origin, which are obligate intracellular Gram-negative bacteria transmitted mainly by tick vectors. The members of this group of infectious agents are not new as etiological agents of animal diseases worldwide. However, now, reports of their zoonotic potential have gained currency to study these pathogens. The emergence of new species of Anaplasma and the spread of existing species to new areas and hosts highlight the importance of monitoring and improving diagnostic and treatment options for zoonotic diseases caused by Anaplasma. Conclusion: This review focuses on the general and distinctive characteristics of Anaplasma spp., with particular emphasis on the novel species and their diverse spectrum of hosts as potential risk factors impacting its emerging zoonosis.

The Alternative Host with the Most: Understanding the Ecology of Xanthomonas hortorum pv. carotae on Noncarrot Crops in Central Oregon.

Bacterial blight of carrot, caused by Xanthomonas hortorum pv. carotae (Xhc), is an economically important disease in carrot (Daucus carota subsp. sativus) seed production. The objectives of this study were to determine if Xhc was present on noncarrot crops grown in central Oregon and, if detected, evaluate its ability to colonize alternative hosts. Surveys of three carrot seed fields and adjacent fields of rye (Secale cereale), alfalfa (Medicago sativa), parsley root (Petroselinum crispum var. tuberosum), and Kentucky bluegrass (Poa pratensis) demonstrated that Xhc was present on noncarrot crops. Greenhouse experiments were conducted to determine the ability of Xhc to colonize crops cultivated in the region. Carrot, alfalfa, curly parsley (Petroselinum crispum), Kentucky bluegrass, mint (Mentha × piperita), parsley root, roughstalk bluegrass (Poa trivialis), and wheat (Triticum aestivum) plants were spray-inoculated with Xhc and destructively sampled at 1, 7, 14, and 28 or 25 days post-inoculation. Xhc populations were quantified using viability quantitative PCR and dilution plating. A significant (P ≤ 0.03) effect of crop was observed at 1, 14, and 28 or 25 days in both experiments. While carrot hosted the most Xhc at the final timepoint, other crops supported epiphytic Xhc populations including wheat and both bluegrasses. Mint, parsley root, and alfalfa hosted the least Xhc. Bacterial blight symptoms were observed on carrots but not on noncarrot crops. This suggests that crops grown in central Oregon have the potential to be asymptomatically colonized by Xhc and may serve as reservoirs of the pathogen in carrot seed production systems.

Inference of Infectious Disease Transmission through a Relaxed Bottleneck Using Multiple Genomes Per Host.

In recent times, pathogen genome sequencing has become increasingly used to investigate infectious disease outbreaks. When genomic data is sampled densely enough amongst infected individuals, it can help resolve who infected whom. However, transmission analysis cannot rely solely on a phylogeny of the genomes but must account for the within-host evolution of the pathogen, which blurs the relationship between phylogenetic and transmission trees. When only a single genome is sampled for each host, the uncertainty about who infected whom can be quite high. Consequently, transmission analysis based on multiple genomes of the same pathogen per host has a clear potential for delivering more precise results, even though it is more laborious to achieve. Here, we present a new methodology that can use any number of genomes sampled from a set of individuals to reconstruct their transmission network. Furthermore, we remove the need for the assumption of a complete transmission bottleneck. We use simulated data to show that our method becomes more accurate as more genomes per host are provided, and that it can infer key infectious disease parameters such as the size of the transmission bottleneck, within-host growth rate, basic reproduction number, and sampling fraction. We demonstrate the usefulness of our method in applications to real datasets from an outbreak of Pseudomonas aeruginosa amongst cystic fibrosis patients and a nosocomial outbreak of Klebsiella pneumoniae.

Investigation of the individual genetic evolution of SARS-CoV-2 in a small cluster during the rapid spread of the BF.5 lineage in Tokyo, Japan.

There has been a decreasing trend in new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases and fatalities worldwide. The virus has been evolving, indicating the potential emergence of new variants and uncertainties. These challenges necessitate continued efforts in disease control and mitigation strategies. We investigated a small cluster of SARS-CoV-2 Omicron variant infections containing a common set of genomic mutations, which provided a valuable model for investigating the transmission mechanism of genetic alterations. We conducted a study at a medical center in Japan during the Omicron surge (sub-lineage BA.5), sequencing the entire SARS-CoV-2 genomes from infected individuals and evaluating the phylogenetic tree and haplotype network among the variants. We compared the mutations present in each strain within the BA.5 strain, TKYnat2317, which was first identified in Tokyo, Japan. From June 29th to July 4th 2022, nine healthcare workers (HCWs) tested positive for SARS-CoV-2 by real-time PCR. During the same period, five patients also tested positive by real-time PCR. Whole genome sequencing revealed that the infected patients belonged to either the isolated BA.2 or BA.5 sub-lineage, while the healthcare worker infections were classified as BF.5. The phylogenetic tree and haplotype network clearly showed the specificity and similarity of the HCW cluster. We identified 12 common mutations in the cluster, including I110V in nonstructural protein 4 (nsp4), A1020S in the Spike protein, and H47Y in ORF7a, compared to the BA.5 reference. Additionally, one case had the extra nucleotide-deletion mutation I27* in ORF10, and low frequencies of genetic alterations were also found in certain instances. The results of genome sequencing showed that the nine HCWs shared a set of genetic mutations, indicating transmission within the cluster. Minor mutations observed in five HCW individuals suggested the emergence of new virus variants. Five amino acid substitutions occurred in nsp3, which could potentially affect virus replication or immune escape. Intra-host evolution also generated additional mutations. The cluster exhibited a mild disease course, with individuals in this case, recovering without requiring any medical treatments. Further investigation is needed to understand the relationship between the genetic evolution of the virus and the symptoms.

Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks.

Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low-frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is partially maintained among repeated serial samples from the same host, it can transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.

During an infectious disease outbreak, tracing who infected whom allows public health scientists to see how a pathogen is spreading and to establish effective control measures. Traditionally, this involves identifying the individuals an infected person comes into contact with and monitoring whether they also become unwell. However, this information is not always available and can be inaccurate. One alternative is to track the genetic data of pathogens as they spread. Over time, pathogens accumulate mutations in their genes that can be used to distinguish them from one another. Genetically similar pathogens are more likely to have spread during the same outbreak, while genetically dissimilar pathogens may have come from different outbreaks. However, there are limitations to this approach. For example, some pathogens accumulate genetic mutations very slowly and may not change enough during an outbreak to be distinguishable from one another. Additionally, some pathogens can spread rapidly, leaving less time for mutations to occur between transmission events. To overcome these challenges, Torres Ortiz et al. developed a more sensitive approach to pathogen genetic testing that took advantage of the multiple pathogen populations that often coexist in an infected patient. Rather than tracking only the most dominant genetic version of the pathogen, this method also looked at the less dominant ones. Torres Ortiz et al. performed genome sequencing of SARS-CoV-2 (the virus that causes COVID-19) samples from 451 healthcare workers, patients, and patient contacts at participating London hospitals. Analysis showed that it was possible to detect multiple genetic populations of the virus within individual patients. These subpopulations were often more similar in patients that had been in contact with one another than in those that had not. Tracking the genetic data of all viral populations enabled Torres Ortiz et al. to trace transmission more accurately than if only the dominant population was used. More accurate genetic tracing could help public health scientists better track pathogen transmission and control outbreaks. This may be especially beneficial in hospital settings where outbreaks can be smaller, and it is important to understand if transmission is occurring within the hospital or if the pathogen is imported from the community. Further research will help scientists understand how pathogen population genetics evolve during outbreaks and may improve the detection of subpopulations present at very low frequencies.

SARS-CoV-2 within-host diversity of human hosts and its implications for viral immune evasion.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously evolving, bringing great challenges to the control of the virus. In the present study, we investigated the characteristics of SARS-CoV-2 within-host diversity of human hosts and its implications for immune evasion using about 2,00,000 high-depth next-generation genome sequencing data of SARS-CoV-2. A total of 44% of the samples showed within-host variations (iSNVs), and the average number of iSNVs in the samples with iSNV was 1.90. C-to-U is the dominant substitution pattern for iSNVs. C-to-U/G-to-A and A-to-G/U-to-C preferentially occur in 5'-CG-3' and 5'-AU-3' motifs, respectively. In addition, we found that SARS-CoV-2 within-host variations are under negative selection. About 15.6% iSNVs had an impact on the content of the CpG dinucleotide (CpG) in SARS-CoV-2 genomes. We detected signatures of faster loss of CpG-gaining iSNVs, possibly resulting from zinc-finger antiviral protein-mediated antiviral activities targeting CpG, which could be the major reason for CpG depletion in SARS-CoV-2 consensus genomes. The non-synonymous iSNVs in the S gene can largely alter the S protein's antigenic features, and many of these iSNVs are distributed in the amino-terminal domain (NTD) and receptor-binding domain (RBD). These results suggest that SARS-CoV-2 interacts actively with human hosts and attempts to take different evolutionary strategies to escape human innate and adaptive immunity. These new findings further deepen and widen our understanding of the within-host evolutionary features of SARS-CoV-2. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of the coronavirus disease 2019, has evolved rapidly since it was discovered. Recent studies have pointed out that some mutations in the SARS-CoV-2 S protein could confer SARS-CoV-2 the ability to evade the human adaptive immune system. In addition, it is observed that the content of the CpG dinucleotide in SARS-CoV-2 genome sequences has decreased over time, reflecting the adaptation to the human host. The significance of our research is revealing the characteristics of SARS-CoV-2 within-host diversity of human hosts, identifying the causes of CpG depletion in SARS-CoV-2 consensus genomes, and exploring the potential impacts of non-synonymous within-host variations in the S gene on immune escape, which could further deepen and widen our understanding of the evolutionary features of SARS-CoV-2.

Intra-Host Co-Existing Strains of SARS-CoV-2 Reference Genome Uncovered by Exhaustive Computational Search.

The COVID-19 pandemic caused by SARS-CoV-2 has had a severe impact on people worldwide. The reference genome of the virus has been widely used as a template for designing mRNA vaccines to combat the disease. In this study, we present a computational method aimed at identifying co-existing intra-host strains of the virus from RNA-sequencing data of short reads that were used to assemble the original reference genome. Our method consisted of five key steps: extraction of relevant reads, error correction for the reads, identification of within-host diversity, phylogenetic study, and protein binding affinity analysis. Our study revealed that multiple strains of SARS-CoV-2 can coexist in both the viral sample used to produce the reference sequence and a wastewater sample from California. Additionally, our workflow demonstrated its capability to identify within-host diversity in foot-and-mouth disease virus (FMDV). Through our research, we were able to shed light on the binding affinity and phylogenetic relationships of these strains with the published SARS-CoV-2 reference genome, SARS-CoV, variants of concern (VOC) of SARS-CoV-2, and some closely related coronaviruses. These insights have important implications for future research efforts aimed at identifying within-host diversity, understanding the evolution and spread of these viruses, as well as the development of effective treatments and vaccines against them.

Single nucleotide variants in Pseudomonas aeruginosa populations from sputum correlate with baseline lung function and predict disease progression in individuals with cystic fibrosis.

The severity and progression of lung disease are highly variable across individuals with cystic fibrosis (CF) and are imperfectly predicted by mutations in the human gene CFTR, lung microbiome variation or other clinical factors. The opportunistic pathogen Pseudomonas aeruginosa (Pa) dominates airway infections in most CF adults. Here we hypothesized that within-host genetic variation of Pa populations would be associated with lung disease severity. To quantify Pa genetic variation within CF sputum samples, we used deep amplicon sequencing (AmpliSeq) of 209 Pa genes previously associated with pathogenesis or adaptation to the CF lung. We trained machine learning models using Pa single nucleotide variants (SNVs), microbiome diversity data and clinical factors to classify lung disease severity at the time of sputum sampling, and to predict lung function decline after 5 years in a cohort of 54 adult CF patients with chronic Pa infection. Models using Pa SNVs alone classified lung disease severity with good sensitivity and specificity (area under the receiver operating characteristic curve: AUROC=0.87). Models were less predictive of lung function decline after 5 years (AUROC=0.74) but still significantly better than random. The addition of clinical data, but not sputum microbiome diversity data, yielded only modest improvements in classifying baseline lung function (AUROC=0.92) and predicting lung function decline (AUROC=0.79), suggesting that Pa AmpliSeq data account for most of the predictive value. Our work provides a proof of principle that Pa genetic variation in sputum tracks lung disease severity, moderately predicts lung function decline and could serve as a disease biomarker among CF patients with chronic Pa infections.

Challenges in Harnessing Shared Within-Host Severe Acute Respiratory Syndrome Coronavirus 2 Variation for Transmission Inference.

Background: The limited variation observed among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) consensus sequences makes it difficult to reconstruct transmission linkages in outbreak settings. Previous studies have recovered variation within individual SARS-CoV-2 infections but have not yet measured the informativeness of within-host variation for transmission inference. Methods: We performed tiled amplicon sequencing on 307 SARS-CoV-2 samples, including 130 samples from 32 individuals in 14 households and 47 longitudinally sampled individuals, from 4 prospective studies with household membership data, a proxy for transmission linkage. Results: Consensus sequences from households had limited diversity (mean pairwise distance, 3.06 single-nucleotide polymorphisms [SNPs]; range, 0-40). Most (83.1%, 255 of 307) samples harbored at least 1 intrahost single-nucleotide variant ([iSNV] median, 117; interquartile range [IQR], 17-208), above a minor allele frequency threshold of 0.2%. Pairs in the same household shared significantly more iSNVs (mean, 1.20 iSNVs; 95% confidence interval [CI], 1.02-1.39) than did pairs in different households infected with the same viral clade (mean, 0.31 iSNVs; 95% CI, .28-.34), a signal that decreases with increasingly stringent minor allele frequency thresholds. The number of shared iSNVs was significantly associated with an increased odds of household membership (adjusted odds ratio, 1.35; 95% CI, 1.23-1.49). However, the poor concordance of iSNVs detected across sequencing replicates (24.8% and 35.0% above a 0.2% and 1% threshold) confirms technical concerns that current sequencing and bioinformatic workflows do not consistently recover low-frequency within-host variants. Conclusions: Shared within-host variation may augment the information in consensus sequences for predicting transmission linkages. Improving sensitivity and specificity of within-host variant identification will improve the informativeness of within-host variation.

Novel Multilocus Sequence Typing and Global Sequence Clustering Schemes for Characterizing the Population Diversity of Streptococcus mitis.

Streptococcus mitis is a common oral commensal and an opportunistic pathogen that causes bacteremia and infective endocarditis; however, the species has received little attention compared to other pathogenic streptococcal species. Effective and easy-to-use molecular typing tools are essential for understanding bacterial population diversity and biology, but schemes specific for S. mitis are not currently available. We therefore developed a multilocus sequence typing (MLST) scheme and defined sequence clusters or lineages of S. mitis using a comprehensive global data set of 322 genomes (148 publicly available and 174 newly sequenced). We used internal 450-bp sequence fragments of seven housekeeping genes (accA, gki, hom, oppC, patB, rlmN, and tsf) to define the MLST scheme and derived the global S. mitis sequence clusters using the PopPUNK clustering algorithm. We identified an initial set of 259 sequence types (STs) and 258 global sequence clusters. The schemes showed high concordance (100%), capturing extensive S. mitis diversity with strains assigned to multiple unique STs and global sequence clusters. The tools also identified extensive within- and between-host S. mitis genetic diversity among isolates sampled from a cohort of healthy individuals, together with potential transmission events, supported by both phylogeny and pairwise single nucleotide polymorphism (SNP) distances. Our novel molecular typing and strain clustering schemes for S. mitis allow for the integration of new strain data, are electronically portable at the PubMLST database (https://pubmlst.org/smitis), and offer a standardized approach to understanding the population structure of S. mitis. These robust tools will enable new insights into the epidemiology of S. mitis colonization, disease and transmission.

Genetic Diversity of Grapevine Virus A in Three Australian Vineyards Using Amplicon High Throughput Sequencing (Amplicon-HTS).

Shiraz disease (SD) is one of the most destructive viral diseases of grapevines in Australia and is known to cause significant economic loss to local growers. Grapevine virus A (GVA) was reported to be the key pathogen associated with this disease. This study aimed to better understand the diversity of GVA variants both within and between individual SD and grapevine leafroll disease (LRD) affected grapevines located at vineyards in South Australia. Amplicon high throughput sequencing (Amplicon-HTS) combined with median-joining networks (MJNs) was used to analyze the variability in specific gene regions of GVA variants. Several GVAII variant groups contain samples from both vineyards studied, suggesting that these GVAII variants were from a common origin. Variant groups analyzed by MJNs using the overall data set denote that there may be a possible relationship between variant groups of GVA and the geographical location of the grapevines.

Phylogenetic inference of pneumococcal transmission from cross-sectional data, a pilot study.

Background: Inference on pneumococcal transmission has mostly relied on longitudinal studies which are costly and resource intensive. Therefore, we conducted a pilot study to test the ability to infer who infected whom from cross-sectional pneumococcal sequences using phylogenetic inference. Methods: Five suspected transmission pairs, for which there was epidemiological evidence of who infected whom, were selected from a household study. For each pair, Streptococcus pneumoniae full genomes were sequenced from nasopharyngeal swabs collected on the same day. The within-host genetic diversity of the pneumococcal population was used to infer the transmission direction and then cross-validated with the direction suggested by the epidemiological records. Results: The pneumococcal genomes clustered into the five households from which the samples were taken. The proportion of concordantly inferred transmission direction generally increased with increasing minimum genome fragment size and single nucleotide polymorphisms. We observed a larger proportion of unique polymorphic sites in the source bacterial population compared to that of the recipient in four of the five pairs, as expected in the case of a transmission bottleneck. The only pair that did not exhibit this effect was also the pair that had consistent discordant transmission direction compared to the epidemiological records suggesting potential misdirection as a result of false-negative sampling. Conclusions: This pilot provided support for further studies to test if the direction of pneumococcal transmission can be reliably inferred from cross-sectional samples if sequenced with sufficient depth and fragment length.

Distribution of intra-host variations and mutations in the genomes of SARS-CoV-2 and their implications on detection and therapeutics.

The ongoing circulation of SARS-CoV-2 variants of concern (VOCs) has caused global concerns, because VOCs could escape current vaccines, antiviral drugs, and diagnosis. Analyzing mutations and intra-host diversities in different and widespread VOCs can provide important insights to virus adaptive evolution and validity of vaccines, antiviral drugs, and diagnosis. In this study, by analyzing 1744 high-throughput sequencing data for intra-host single-nucleotide variations (iSNVs) and 3,668,205 genome sequences for mutations in different VOCs, it was found that Omicron variant is still evolving at high speed, especially having high iSNVs frequency in its S and N genes. The efficacies of antibodies or detection primers targeting these two genes are at high risks to be invalid. Instead, highly conserved regions such as NSP8 gene could be better therapeutic and detection targets. Furthermore, mutations in later VOCs could be traced to the minor alleles in the previous variant samples such as Alpha and Delta in different countries. Finally, it was found that mutations C14408T in RdRp and A18163G in NSP14 gene might be associated with the higher genetic diversity in Omicron. Our findings not only contribute to understanding the adaptive evolution of SARS-CoV-2 VOCs, but also provide useful information for both drugs and diagnostic kits development.

Within-Host Genotypic and Phenotypic Diversity of Contemporaneous Carbapenem-Resistant Klebsiella pneumoniae from Blood Cultures of Patients with Bacteremia.

It is unknown whether bacterial bloodstream infections (BSIs) are commonly caused by single organisms or mixed microbial populations. We hypothesized that contemporaneous carbapenem-resistant Klebsiella pneumoniae (CRKP) strains from blood cultures of individual patients are genetically and phenotypically distinct. We determined short-read whole-genome sequences of 10 sequence type 258 (ST258) CRKP strains from blood cultures in each of 6 patients (Illumina HiSeq). Strains clustered by patient by core genome and pan-genome phylogeny. In 5 patients, there was within-host strain diversity by gene mutations, presence/absence of antibiotic resistance or virulence genes, and/or plasmid content. Accessory gene phylogeny revealed strain diversity in all 6 patients. Strains from 3 patients underwent long-read sequencing for genome completion (Oxford Nanopore) and phenotypic testing. Genetically distinct strains within individuals exhibited significant differences in carbapenem and other antibiotic responses, capsular polysaccharide (CPS) production, mucoviscosity, and/or serum killing. In 2 patients, strains differed significantly in virulence during mouse BSIs. Genetic or phenotypic diversity was not observed among strains recovered from blood culture bottles seeded with index strains from the 3 patients and incubated in vitro at 37°C. In conclusion, we identified genotypic and phenotypic variant ST258 CRKP strains from blood cultures of individual patients with BSIs, which were not detected by the clinical laboratory or in seeded blood cultures. The data suggest a new paradigm of CRKP population diversity during BSIs, at least in some patients. If validated for BSIs caused by other bacteria, within-host microbial diversity may have implications for medical, microbiology, and infection prevention practices and for understanding antibiotic resistance and pathogenesis. IMPORTANCE The long-standing paradigm for pathogenesis of bacteremia is that, in most cases, a single organism passes through a bottleneck and establishes itself in the bloodstream (single-organism hypothesis). In keeping with this paradigm, standard practice in processing positive microbiologic cultures is to test single bacterial strains from morphologically distinct colonies. This study is the first genome-wide analysis of within-host diversity of Klebsiella pneumoniae strains recovered from individual patients with bloodstream infections (BSIs). Our finding that positive blood cultures comprised genetically and phenotypically heterogeneous carbapenem-resistant K. pneumoniae strains challenges the single-organism hypothesis and suggests that at least some BSIs are caused by mixed bacterial populations that are unrecognized by the clinical laboratory. The data support a model of pathogenesis in which pressures in vivo select for strain variants with particular antibiotic resistance or virulence attributes and raise questions about laboratory protocols and treatment decisions directed against single strains.

SARS-CoV-2 Within-Host and in vitro Genomic Variability and Sub-Genomic RNA Levels Indicate Differences in Viral Expression Between Clinical Cohorts and in vitro Culture.

Background: Low frequency intrahost single nucleotide variants (iSNVs) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) have been increasingly recognised as predictive indicators of positive selection. Particularly as growing numbers of SARS-CoV-2 variants of interest (VOI) and concern (VOC) emerge. However, the dynamics of subgenomic RNA (sgRNA) expression and its impact on genomic diversity and infection outcome remain poorly understood. This study aims to investigate and quantify iSNVs and sgRNA expression in single and longitudinally sampled cohorts over the course of mild and severe SARS-CoV-2 infection, benchmarked against an in vitro infection model. Methods: Two clinical cohorts of SARS-CoV-2 positive cases in New South Wales, Australia collected between March 2020 and August 2021 were sequenced. Longitudinal samples from cases hospitalised due to SARS-CoV-2 infection (severe) (n = 16) were analysed and compared with cases that presented with SARS-CoV-2 symptoms but were not hospitalised (mild) (n = 23). SARS-CoV-2 genomic diversity profiles were also examined from daily sampling of culture experiments for three SARS-CoV-2 variants (Lineage A, B.1.351, and B.1.617.2) cultured in VeroE6 C1008 cells (n = 33). Results: Intrahost single nucleotide variants were detected in 83% (19/23) of the mild cohort cases and 100% (16/16) of the severe cohort cases. SNP profiles remained relatively fixed over time, with an average of 1.66 SNPs gained or lost, and an average of 4.2 and 5.9 low frequency variants per patient were detected in severe and mild infection, respectively. sgRNA was detected in 100% (25/25) of the mild genomes and 92% (24/26) of the severe genomes. Total sgRNA expressed across all genes in the mild cohort was significantly higher than that of the severe cohort. Significantly higher expression levels were detected in the spike and the nucleocapsid genes. There was significantly less sgRNA detected in the culture dilutions than the clinical cohorts. Discussion and Conclusion: The positions and frequencies of iSNVs in the severe and mild infection cohorts were dynamic overtime, highlighting the importance of continual monitoring, particularly during community outbreaks where multiple SARS-CoV-2 variants may co-circulate. sgRNA levels can vary across patients and the overall level of sgRNA reads compared to genomic RNA can be less than 1%. The relative contribution of sgRNA to the severity of illness warrants further investigation given the level of variation between genomes. Further monitoring of sgRNAs will improve the understanding of SARS-CoV-2 evolution and the effectiveness of therapeutic and public health containment measures during the pandemic.

Viral Population Diversity during Co-Infection of Foot-And-Mouth Disease Virus Serotypes SAT1 and SAT2 in African Buffalo in Kenya.

African buffalo are the natural reservoirs of the SAT serotypes of foot-and-mouth disease virus (FMDV) in sub-Saharan Africa. Most buffalo are exposed to multiple FMDV serotypes early in life, and a proportion of them become persistently infected carriers. Understanding the genetic diversity and evolution of FMDV in carrier animals is critical to elucidate how FMDV persists in buffalo populations. In this study, we obtained oropharyngeal (OPF) fluid from naturally infected African buffalo, and characterized the genetic diversity of FMDV. Out of 54 FMDV-positive OPF, 5 were co-infected with SAT1 and SAT2 serotypes. From the five co-infected buffalo, we obtained eighty-nine plaque-purified isolates. Isolates obtained directly from OPF and plaque purification were sequenced using next-generation sequencing (NGS). Phylogenetic analyses of the sequences obtained from recombination-free protein-coding regions revealed a discrepancy in the topology of capsid proteins and non-structural proteins. Despite the high divergence in the capsid phylogeny between SAT1 and SAT2 serotypes, viruses from different serotypes that were collected from the same host had a high genetic similarity in non-structural protein-coding regions P2 and P3, suggesting interserotypic recombination. In two of the SAT1 and SAT2 co-infected buffalo identified at the first passage of viral isolation, the plaque-derived SAT2 genomes were distinctly grouped in two different genotypes. These genotypes were not initially detected with the NGS from the first passage (non-purified) virus isolation sample. In one animal with two SAT2 haplotypes, one plaque-derived chimeric sequence was found. These findings demonstrate within-host evolution through recombination and point mutation contributing to broad viral diversity in the wildlife reservoir. These mechanisms may be critical to FMDV persistence at the individual animal and population levels, and may contribute to the emergence of new viruses that have the ability to spill-over to livestock and other wildlife species.

Low Pathogenicity H7N3 Avian Influenza Viruses Have Higher Within-Host Genetic Diversity Than a Closely Related High Pathogenicity H7N3 Virus in Infected Turkeys and Chickens.

Within-host viral diversity offers a view into the early stages of viral evolution occurring after a virus infects a host. In recent years, advances in deep sequencing have allowed for routine identification of low-frequency variants, which are important sources of viral genetic diversity and can potentially emerge as a major virus population under certain conditions. We examined within-host viral diversity in turkeys and chickens experimentally infected with closely related H7N3 avian influenza viruses (AIVs), specifically one high pathogenicity AIV (HPAIV) and two low pathogenicity AIV (LPAIVs) with different neuraminidase protein stalk lengths. Consistent with the high mutation rates of AIVs, an abundance of intra-host single nucleotide variants (iSNVs) at low frequencies of 2-10% was observed in all samples collected. Furthermore, a small number of common iSNVs were observed between turkeys and chickens, and between directly inoculated and contact-exposed birds. Notably, the LPAIVs have significantly higher iSNV diversities and frequencies of nonsynonymous changes than the HPAIV in both turkeys and chickens. These findings highlight the dynamics of AIV populations within hosts and the potential impact of genetic changes, including mutations in the hemagglutinin gene that confers the high pathogenicity pathotype, on AIV virus populations and evolution.